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https://www.colorhexa.com/0206a3
[ "# #0206a3 Color Information\n\nIn a RGB color space, hex #0206a3 is composed of 0.8% red, 2.4% green and 63.9% blue. Whereas in a CMYK color space, it is composed of 98.8% cyan, 96.3% magenta, 0% yellow and 36.1% black. It has a hue angle of 238.5 degrees, a saturation of 97.6% and a lightness of 32.4%. #0206a3 color hex could be obtained by blending #040cff with #000047. Closest websafe color is: #000099.\n\n• R 1\n• G 2\n• B 64\nRGB color chart\n• C 99\n• M 96\n• Y 0\n• K 36\nCMYK color chart\n\n#0206a3 color description : Dark blue.\n\n# #0206a3 Color Conversion\n\nThe hexadecimal color #0206a3 has RGB values of R:2, G:6, B:163 and CMYK values of C:0.99, M:0.96, Y:0, K:0.36. Its decimal value is 132771.\n\nHex triplet RGB Decimal 0206a3 `#0206a3` 2, 6, 163 `rgb(2,6,163)` 0.8, 2.4, 63.9 `rgb(0.8%,2.4%,63.9%)` 99, 96, 0, 36 238.5°, 97.6, 32.4 `hsl(238.5,97.6%,32.4%)` 238.5°, 98.8, 63.9 000099 `#000099`\nCIE-LAB 19.17, 54.949, -76.148 6.7, 2.787, 34.833 0.151, 0.063, 2.787 19.17, 93.904, 305.814 19.17, -5.654, -75.859 16.694, 42.42, -112.025 00000010, 00000110, 10100011\n\n# Color Schemes with #0206a3\n\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #a39f02\n``#a39f02` `rgb(163,159,2)``\nComplementary Color\n• #0257a3\n``#0257a3` `rgb(2,87,163)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #4e02a3\n``#4e02a3` `rgb(78,2,163)``\nAnalogous Color\n• #57a302\n``#57a302` `rgb(87,163,2)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #a34e02\n``#a34e02` `rgb(163,78,2)``\nSplit Complementary Color\n• #06a302\n``#06a302` `rgb(6,163,2)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #a30206\n``#a30206` `rgb(163,2,6)``\n• #02a39f\n``#02a39f` `rgb(2,163,159)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #a30206\n``#a30206` `rgb(163,2,6)``\n• #a39f02\n``#a39f02` `rgb(163,159,2)``\n• #010357\n``#010357` `rgb(1,3,87)``\n• #010471\n``#010471` `rgb(1,4,113)``\n• #02058a\n``#02058a` `rgb(2,5,138)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #0207bc\n``#0207bc` `rgb(2,7,188)``\n• #0308d5\n``#0308d5` `rgb(3,8,213)``\n• #0309ef\n``#0309ef` `rgb(3,9,239)``\nMonochromatic Color\n\n# Alternatives to #0206a3\n\nBelow, you can see some colors close to #0206a3. Having a set of related colors can be useful if you need an inspirational alternative to your original color choice.\n\n• #022ea3\n``#022ea3` `rgb(2,46,163)``\n• #0221a3\n``#0221a3` `rgb(2,33,163)``\n• #0213a3\n``#0213a3` `rgb(2,19,163)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #0b02a3\n``#0b02a3` `rgb(11,2,163)``\n• #1902a3\n``#1902a3` `rgb(25,2,163)``\n• #2602a3\n``#2602a3` `rgb(38,2,163)``\nSimilar Colors\n\n# #0206a3 Preview\n\nThis text has a font color of #0206a3.\n\n``<span style=\"color:#0206a3;\">Text here</span>``\n#0206a3 background color\n\nThis paragraph has a background color of #0206a3.\n\n``<p style=\"background-color:#0206a3;\">Content here</p>``\n#0206a3 border color\n\nThis element has a border color of #0206a3.\n\n``<div style=\"border:1px solid #0206a3;\">Content here</div>``\nCSS codes\n``.text {color:#0206a3;}``\n``.background {background-color:#0206a3;}``\n``.border {border:1px solid #0206a3;}``\n\n# Shades and Tints of #0206a3\n\nA shade is achieved by adding black to any pure hue, while a tint is created by mixing white to any pure color. In this example, #000008 is the darkest color, while #f4f4ff is the lightest one.\n\n• #000008\n``#000008` `rgb(0,0,8)``\n• #00011b\n``#00011b` `rgb(0,1,27)``\n• #01022f\n``#01022f` `rgb(1,2,47)``\n• #010242\n``#010242` `rgb(1,2,66)``\n• #010355\n``#010355` `rgb(1,3,85)``\n• #010469\n``#010469` `rgb(1,4,105)``\n• #02057c\n``#02057c` `rgb(2,5,124)``\n• #020590\n``#020590` `rgb(2,5,144)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\n• #0207b6\n``#0207b6` `rgb(2,7,182)``\n• #0207ca\n``#0207ca` `rgb(2,7,202)``\n• #0308dd\n``#0308dd` `rgb(3,8,221)``\n• #0309f1\n``#0309f1` `rgb(3,9,241)``\n• #0b11fc\n``#0b11fc` `rgb(11,17,252)``\n• #1e24fc\n``#1e24fc` `rgb(30,36,252)``\n• #3237fc\n``#3237fc` `rgb(50,55,252)``\n• #454afd\n``#454afd` `rgb(69,74,253)``\n• #595dfd\n``#595dfd` `rgb(89,93,253)``\n• #6c70fd\n``#6c70fd` `rgb(108,112,253)``\n• #7f82fd\n``#7f82fd` `rgb(127,130,253)``\n• #9395fe\n``#9395fe` `rgb(147,149,254)``\n• #a6a8fe\n``#a6a8fe` `rgb(166,168,254)``\n• #b9bbfe\n``#b9bbfe` `rgb(185,187,254)``\n• #cdcefe\n``#cdcefe` `rgb(205,206,254)``\n• #e0e1ff\n``#e0e1ff` `rgb(224,225,255)``\n• #f4f4ff\n``#f4f4ff` `rgb(244,244,255)``\nTint Color Variation\n\n# Tones of #0206a3\n\nA tone is produced by adding gray to any pure hue. In this case, #4e4e57 is the less saturated color, while #0206a3 is the most saturated one.\n\n• #4e4e57\n``#4e4e57` `rgb(78,78,87)``\n• #48485d\n``#48485d` `rgb(72,72,93)``\n• #414264\n``#414264` `rgb(65,66,100)``\n• #3b3c6a\n``#3b3c6a` `rgb(59,60,106)``\n• #353670\n``#353670` `rgb(53,54,112)``\n• #2e3077\n``#2e3077` `rgb(46,48,119)``\n• #282a7d\n``#282a7d` `rgb(40,42,125)``\n• #222483\n``#222483` `rgb(34,36,131)``\n• #1b1e8a\n``#1b1e8a` `rgb(27,30,138)``\n• #151890\n``#151890` `rgb(21,24,144)``\n• #0f1296\n``#0f1296` `rgb(15,18,150)``\n• #080c9d\n``#080c9d` `rgb(8,12,157)``\n• #0206a3\n``#0206a3` `rgb(2,6,163)``\nTone Color Variation\n\n# Color Blindness Simulator\n\nBelow, you can see how #0206a3 is perceived by people affected by a color vision deficiency. This can be useful if you need to ensure your color combinations are accessible to color-blind users.\n\nMonochromacy\n• Achromatopsia 0.005% of the population\n• Atypical Achromatopsia 0.001% of the population\nDichromacy\n• Protanopia 1% of men\n• Deuteranopia 1% of men\n• Tritanopia 0.001% of the population\nTrichromacy\n• Protanomaly 1% of men, 0.01% of women\n• Deuteranomaly 6% of men, 0.4% of women\n• Tritanomaly 0.01% of the population" ]
[ null ]
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https://quant.stackexchange.com/questions/2294/how-can-i-compare-distributions-using-only-mean-and-standard-deviation
[ "# How can I compare distributions using only mean and standard deviation?\n\nI only have means and standard deviations of samples of two random variables. What technique can I use to determine how similar the distributions these describe are? Assume that the values are built from very similar samples. I'm looking for a mechanism to detect when the distributions deviate from one another by some threshold. Access to historical observations is limited.\n\n• Are you asking how to determine which distributions the data follow based on the mean and standard deviation? – strimp099 Oct 31 '11 at 23:34\n\n## 2 Answers\n\nThere are a number of different tests that are generally used to compare samples to different distributions, such as Jarque-Bera, Anderson-Darling, and Kolmogorov–Smirnov (see this related question).\n\nIn your case, with just the standard deviation and mean, there isn't a whole lot to say. You need to assume a distribution (e.g. normal). You would be able to tell much more if you could at least get the skewness and kurtosis.\n\nBe careful, remember that the mean and the standard deviation don't tell you the whole story: http://en.wikipedia.org/wiki/Anscombe%27s_quartet" ]
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https://factorization.info/factors/0/factors-of-1058.html
[ "Factors of 1058", null, "We have all the information you will ever need about the Factors of 1058. We will provide you with the definition of Factors of 1058, show you how to find the Factors of 1058, give you all the Factors of 1058, tell you how many Factors 1058 has, and supply you with all the Factor Pairs of 1058 to prove that our answer is solved correctly.\n\nFactors of 1058 definition\nThe Factors of 1058 are all the integers (positive and negative whole numbers) that you can evenly divide into 1058. 1058 divided by a Factor of 1058 will equal another Factor of 1058.\n\nHow to find the Factors of 1058\nSince the Factors of 1058 are all the numbers that you can evenly divide into 1058, we simply need to divide 1058 by all numbers up to 1058 to see which ones result in an even quotient. When we did that, we found that these calculations resulted in an even quotient:\n\n1058 ÷ 1 = 1058\n1058 ÷ 2 = 529\n1058 ÷ 23 = 46\n1058 ÷ 46 = 23\n1058 ÷ 529 = 2\n1058 ÷ 1058 = 1\n\nThe Postive Factors of 1058 are therefore all the numbers we used to divide (divisors) above to get an even number. Here is the list of all Postive Factors of 1058 in numerical order:\n\n1, 2, 23, 46, 529, and 1058.\n\nFactors of 1058 include negative numbers. Therefore, all the Positive Factors of 1058 can be converted to negative numbers. The list of Negative Factors of 1058 are:\n\n-1, -2, -23, -46, -529, and -1058.\n\nHow many Factors of 1058?\nWhen we counted the Factors of 1058 that we listed above, we found that 1058 has 6 Positive Factors and 6 Negative Factors. Thus, the total number of Factors of 1058 is 12.\n\nFactor Pairs of 1058\nFactor Pairs of 1058 are combinations of two factors that when multiplied together equal 1058. Here are all the Positive Factor Pairs of 1058\n\n1 × 1058 = 1058\n2 × 529 = 1058\n23 × 46 = 1058\n46 × 23 = 1058\n529 × 2 = 1058\n1058 × 1 = 1058\n\nLike we said above, Factors of 1058 include negative numbers. Minus times minus equals plus, thus you can convert the Positive Factor Pair list above by simply putting a minus in front of every factor to get all the Negative Factor Pairs of 1058:\n\n-1 × -1058 = 1058\n-2 × -529 = 1058\n-23 × -46 = 1058\n-46 × -23 = 1058\n-529 × -2 = 1058\n-1058 × -1 = 1058\n\nFactor Calculator\nDo you need the factors for a particular number? You can submit a number below to find the factors for that number with detailed explanations like we did with Factors of 1058 above.\n\nFactors of 1059\nWe hope this step-by-step tutorial to teach you about Factors of 1058 was helpful. Do you want to see if you learned something? If so, give the next number on our list a try and then check your answer here.\n\nCopyright  |   Privacy Policy  |   Disclaimer  |   Contact" ]
[ null, "https://factorization.info/images/factors-of.png", null ]
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http://magictesseract.com/odd_tesseract
[ "# PRIME ORDER TESSERACTS\n\nCreation of prime order tesseracts is just an extension of the concepts developed for the creation of Prime Order Squares and Prime Order Cubes. The greater difficulty is the size of the figure and in visualization. Sums for the figures described below were checked for accuracy because I have not determined a general proof for these figures.\n\n## ORDER-3 TESSERACTS (ternary base lines)\n\nThe order-3 magic tesseract generator at right contains four sets of four base lines. Each set generates a base tesseract but the base tesseracts are not shown. Only their sum, after multiplication and addition of 1, is shown as the Order-3 Magic Tesseract. The sums section at the right side of the table determines the validity of the base lines entered. All six including the uniform integral distribution must be correct for a valid tesseract. Each base line must have a 0, 1, and 2 in any order. For a valid base tesseract, the sum of the middle numbers of the four base lines of each set must be 1, 4, or 7 (1 mod 3). Not all combinations of valid base tesseracts will yield a valid magic tesseract.\n\nThere are 58 order-3 magic tesseracts. Harvey Heinz has a listing of them and much more information about them on his Order-3 Magic Tesseracts page. Shown at right is an aspect of the tesseract designated as Index # 5 on that page. I am sure that all 58 can be generated by modifying the base lines in the figure although I have not done so. I am also sure that all 384 aspects of each of the 58 tesseracts can be generated with different arrangements of the base lines. There are 6^16 possible arrangements.\n\nAn aspect of each of the first four tesseracts on Heinz's Order-3 Magic Tesseracts page can be generated by changing all of the base lines in one of the base line sets to 012. Separate modification of each set will produce a different index numbered tesseract. The tesseract initially shown and these four are all the tesseracts that have a 1 as their lowest corner number and thus a zero for the first number of all base lines.\n\nTo obtain additional order-3 tesseracts some of the base lines must start with 1 or 2. If all of the base lines except one of the base lines in the last set start with zero then the order-3 tesseract will have as its lowest corner number 2 or 3 depending on what number the exception base line starts on. To make 4-9 the smallest corner number, the next to last base tesseract must have one of its base lines start with 1 or 2.\n\n## ORDER-5 TESSERACTS (quinary base lines)\n\nThere are only two quinary base lines that can be used to generate order-5 base figures. These are 01234 and 02413. They are generated from the equations x mod 5 and 2x mod 5 for 0 ≤ x ≤ 4. These lines can be shifted (12340, 23401, etc) and/or reversed (04321, 31420, etc.). But for purposes of building pan-magic figures, shifted and reversed lines are the same. An order-5 base pan tesseract must therefore be composed of all the same base line or some combination of the two different base lines.\n\nOnly the base tesseracts composed of the same base line produce an interesting result. These base tesseracts are pan-3-agonal. Combining base tesseracts with the same base line will yield an intermediate that does not have uniform integral distribution. Shifting base lines on one of the base tesseracts does not help, but reversing some lines will give tesseract combinations with uniform integral distribution. By systematically reversing lines an order-5 pan-3-agonal tesseract can be built.\n\nThe 5 tess worksheet of the TesseractLines Excel Spreadsheet available on the Downloads page gives the master base lines of two order-5 pan-3-agonal tesseracts. The first just has the pan feature while the second is also associated. The main quadragonals in the second tesseract also add to S. Sums for the tesseract are given in the spreadsheet.\n\n## ORDER-7 TESSERACTS\n\nThere are three base 7 base lines that can be used to generate order-7 base figures. These are 0123456, 0246135, and 0362514. They are generated from the equations x mod 7, 2x mod 7, and 3x mod 7 for 0 ≤ x ≤ 6. An order-7 base tesseract can therefore be composed of all the same base line, some combination of two different base lines, or a combination of all three base lines.\n\nWhen base tesseracts are made from four sets of four base seven base lines, both order-7 pan-3-agonal and pan-4-agonal magic tesseracts can be made. The pan-3-agonal base tesseracts as above can be made using four identical base lines, but they can also be made from three of one base line and one of another. Other combinations of three and one will yield a pan-4-agonal tesseract. Combinations of all three base lines or of two of one and two of another do not yield order-7 pan-x-agonal base tesseracts of any type. Combining four base tesseracts, 343(tesseract 1) + 49(tesseract 2) + 7(tesseract 3) + tesseract 4, can yield a pan-x-agonal tesseract if all four base tesseracts are pan-x-agonal and x is always the same. Uniform integral distribution must be ensured.\n\nThe 7 tess worksheet of the TesseractLines Excel Spreadsheet available on the Downloads page gives the master base lines of four order-7 pan-x-agonal tesseracts. Two are pan-3-agonal and two are pan-4-agonal. In each pair, one is just pan-x-agonal while the other is also associated. The main quadragonals of the associated pan-3-agonal tesseract also add to S. The sums for the figures are included in the spreadsheet.\n\n## ORDER-11 TESSERACTS\n\nThere are five base 11 base lines that can be used to generate order-11 base figures. They are generated from the equations x mod 11, 2x mod 11, 3x mod 11, 4x mod 11, and 5x mod 11 for 0 ≤ x ≤ 10. As more base lines become available, more base line combinations become possible and more pan-x-agonal tesseract types become possible.\n\nWith order-11 base lines it is possible to make pan-3-agonal, pan-4-agonal, and pan-3,4-agonal magic tesseracts. The base line combinations that will give the various types of pan-x-agonal base tesseracts become more varied as the order gets larger. I haven't determined a pattern except that base tesseracts made from four of the same base line always give pan-3-tesseracts.\n\nThe 11 tess worksheet of the TesseractLines Excel Spreadsheet available on the Downloads page gives the master base lines of six order-11 pan-x-agonal tesseracts. There are two pan-3-agonal, two pan-4-agonal, and two pan-3,4-agonal. In each pair, one is just pan-x-agonal while the other is also associated. The main quadragonals of the associated pan-3-agonal tesseract also add to S. A rudimentary sum checker for the figures is included in the spreadsheet. I can provide a better checker for anyone interested.\n\n## ORDER-13 TESSERACTS\n\nThere are six base 13 base lines for generating order-13 base figures. In addition to the three tesseract types that can be generated for order-11 tesseracts, order-13 pan-2-agonal and pan-2,4-agonal tesseracts can be built.\n\nThe 13 tess worksheet of the TesseractLines Excel Spreadsheet available on the Downloads page gives the master base lines of ten order-13 pan-x-agonal tesseracts. There are two pan-2-agonal, two pan-3-agonal, two pan-4-agonal, two pan-2,4-agonal, and two pan-3,4-agonal tesseracts. In each pair, one is just pan-x-agonal while the other is also associated. The main quadragonals of the associated pan-2-agonal and pan-3-agonal tesseracts also add to S. A rudimentary sum checker for the figures is included in the spreadsheet. I can provide a better checker for anyone interested.\n\n## ORDER-17 TESSERACTS\n\nNasik tesseracts for prime orders are possible when o ≥ 17. These are constructed from base tesseracts made from four different base lines. If the four different base lines are picked correctly they will yield a nasik base tesseract otherwise they will generate pan-2-agonal, pan-2,3-agonal, or pan-2,4-agonal tesseracts. Two order-17 nasik tesseracts are given in the 17 tess worksheet of the TesseractLines Excel Spreadsheet available on the Downloads page.\n\nFor order-17 and larger tesseracts, all seven pan-x-agonal types are possible. The 17 tess worksheet has two of each of the seven pan-x-agonal types. One of each pair is just the pan-x-agonal tesseract and one is also associated. For the pan-2-agonal, pan-3-agonal, and pan-2,3-agonal tesseracts, the associated tesseract also has all main quadragonals equal to S.\n\n## LARGER PRIME ORDER NASIK TESSERACTS\n\nIt should be possible to make a nasik tesseract for any prime order ≥ 17. I offer the following procedure for an order-o tesseract without proof. I believe it to be correct based primarily on a lack of failure to date.\n\nThe 4 base lines x mod o, 2x mod o, 4x mod o, and 8x mod o with 0 ≤ x < o should always give valid base tesseracts. By systematically moving base lines in this, set a valid nasik tesseract can be built. The process is as follows.\n\n1. Let the four base lines be: a = x mod o, b = 2x mod o, c = 4x mod o, and d = 8x mod o for 0 ≤ x < o.\n2. For the first base tesseract let the row base line be a, the column b, the pillar c, and the file d.\n3. For the second base tesseract let the row base line be b, the column c, the pillar d, and the file a.\n4. For the third base tesseract let the row base line be c, the column d, the pillar a, and the file b.\n5. For the last base tesseract let the row base line be d, the column a, the pillar b, and the file c.\n\nThe four base tesseracts can be combined as o3(base tesseract 1) + o2(base tesseract 2) + o(base tesseract 3) + base tesseract 4 to make the master base lines. The value at position nijkl in the magic tesseract is: nijkl = o3((row1i + column1j + pillar1k + file1l) mod o) + o2((row2i + column2j + pillar2k + file2l) mod o) + o((row3i + column3j + pillar3k + file3l) mod o) + ((row4i + column4j + pillar4k + file4l) mod o)." ]
[ null ]
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https://www.hackmath.net/en/math-problem/8288?tag_id=154
[ "# Concentric circles\n\nThere is given a circle K with a radius r = 8 cm. How large must a radius have a smaller concentric circle that divides the circle K into two parts with the same area?\n\nCorrect result:\n\nr2 =  5.6569 cm\n\n#### Solution:", null, "We would be pleased if you find an error in the word problem, spelling mistakes, or inaccuracies and send it to us. Thank you!", null, "#### You need to know the following knowledge to solve this word math problem:\n\nWe encourage you to watch this tutorial video on this math problem:\n\n## Next similar math problems:\n\n• Maxwell’s inductance bridge", null, "The four arms of Maxwell’s inductance bridge are; Arm AB contains an Inductive coil of inductance L1 having resistance R1. Arms BC and CD contain non-inductive resistances of 200Ω and 100Ω respectively. Arm AD contains standard inductor of inductance L2 a\n• The projectile", null, "The projectile was fired horizontally from a height of h = 25 meters above the ground at a speed of v0 = 250 m/s. Find the range and flight time of the projectile.\n• As shown", null, "As shown, in △ ABC, ∠C = 90°, AD bisects ∠BAC, DE⊥AB to E, BE = 2, BC = 6, then the perimeter of △ BDE\n• What are 2", null, "What are the two more terms of the GP a, ax, ax2, ax3, __, __?\n• Find the 19", null, "Find the 1st term of the GP ___, -6, 18, -54.\n• If the 3", null, "If the 6th term of a GP is 4 and the 10th is 4/81, find common ratio r.\n• Up and down motion", null, "We throw the body from a height h = 5 m above the Earth vertically upwards v0 = 10 m/s. How long before we have to let the second body fall freely from the same height to hit the Earth at the same time?\n• Sum of GP members", null, "Determine the sum of the GP 30, 6, 1.2, to 5 terms. What is the sum of all terms (to infinity)?\n• Acute triangle", null, "In the acute triangle KLM, V is the intersection of its heights and X is the heel of height to the side KL. The axis of the angle XVL is parallel to the side LM and the angle MKL is 70°. What size are the KLM and KML angles?\n• Telco company", null, "The upstairs communications company offers customers a special long distance calling rate that includes a \\$0.10 per minute charge. Which of the following represents this fee scheduale where m represents the number of minutes and c is the overall cost of t\n• Trapezoid 25", null, "Trapezoid PART with AR||PT has (angle P=x) and (angle A=2x) . In addition, PA = AR = RT = s. Find the length of the median of Trapezoid PART in terms of s.\n• Sphere cut", null, "A sphere segment is cut off from a sphere k with radius r = 1. The volume of the sphere inscribed in this segment is equal to 1/6 of the volume of the segment. What is the distance of the cutting plane from the center of the sphere?\n• What is 10", null, "What is the 5th term, if the 8th term is 80 and common ratio r =1/2?\n• Volume per time", null, "How long does fill take for a pump with a volume flow of 200 l per minute fill a cube-shaped tank up to 75% of its height if the length of the cube edge is 4 m?\n• Gardens", null, "The area of the square garden is 3/4 of the area of the triangular garden with sides of 80 m, 50 m, 50 m. How many meters of the fence do we need to fence a square garden?\n• Space diagonal angles", null, "Calculate the angle between the body diagonal and the side edge c of the block with dimensions: a = 28cm, b = 45cm and c = 73cm. Then, find the angle between the body diagonal and the plane of the base ABCD.", null, "How long is a ladder that touches on a wall 4 meters high and its lower part is 3 meters away from the wall?" ]
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https://npirl.blogspot.com/2008/03/mathematical-sunday-with-seifert.html
[ "## Sunday, March 9, 2008\n\n### Mathematical Sunday with Seifert Surface\n\nAh, Seifert Surface! Every encounter with that postdoctoral mathematician is enlightening. Take today for example...\n\nBettina Tizzy: How are things at xyz? Teleport directly to Seifert's new sim, xyz, from here.\n\nSeifert Surface: Just made a sculpty thing which is the graph of the function xyz = 1.", null, "It is 24 prims all told. It would be 12 except that plane sculpties are \"one sided,\" so Seifert needed twice as many.\n\nOf course, I had to ask Seifert for a simplified explanation...\n\nSeifert Surface: You have coordinates for points in space, x,y,z. You can ask, what are the points x,y,z so that xyz = 1? That is, you multiply them together and get 1 so, eg: if x, y and z are all 1, it satisfies the equation. 1,1,1 is on my graph, so is 1,-1,-1\n\nBettina Tizzy: But we are at 500mts, so how do you get 1?\n\nSeifert Surface: Ah, yes, true. The center of this thing is assumed to be 0,0,0 for purposes of the thing, and it goes out to 8 and -8 in each direction... otherwise you wouldn't be able to see any of it. You know like the graph of y = x^2? If you see it on a computer screen, then the origin is not at the bottom left corner of the screen, and the scale is not 1 unit to 1 meter. You can scale and move the graph somewhere else, and it's still the graph of y=x^2. Same thing here. This is just a 3D version of a normal graph.\n\nBettina Tizzy: What applications can this be given?\n\nSeifert Surface: Well, learning about functions. Unfortunately, it's a real pain to make something like this at present... something that you could use to quickly graph things would be very useful for teaching. You could have an extension to prims, in the same vein as for sculpties. With sculpties, you send a texture to encode the data of the shape. Instead, you could send the mathematical formula for the shape. Then we'd be in business and, of course, animated stuff would work well, too.\n\nBettina Tizzy: What is this shield item?", null, "Seifert Surface: A prototype for the larger piece. I had a smaller range on the graph before, but it looks better with more. That one goes from 0 to 2. The big one is 0 to 8.", null, "Bettina Tizzy: Fits better than a glove! More like skin.\n\nSeifert Surface: Should be the exact same function. It fits!" ]
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https://zh.wikipedia.org/zh/%E5%8F%8D%E6%BC%94
[ "# 反演\n\n• $O$", null, "直線:直線\n• $O$", null, ":不過$O$", null, "的直線\n• 不過$O$", null, "的圓:圓\n• $O$", null, "的球:不過$O$", null, "的平面\n\n$x_{i}\\rightarrow {\\frac {k^{2}x_{i}}{\\sum _{j}x_{j}^{2}}}$", null, "• 立體投影法:可以取球面上任意一點為中心,球的直徑為$k$", null, "• 共軸圓:在平面取一系列共心圓,取一系列經過共心圓圓心的線,任意取一點為中心進行反演。" ]
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https://physics.stackexchange.com/questions/640905/should-quarks-be-grouped-together-in-feynman-diagrams
[ "# Should quarks be grouped together in Feynman diagrams?\n\nI have a questions regarding Feynman diagrams when it involves hadrons. I think the easiest way is considering this reactions:\n\n1) $$\\Lambda_{c}^{+} \\rightarrow p+\\bar{K}^{0}$$\n\nI need to draw the feynman diagram for this reaction. I know that the quark contents of the particles are the following: $$\\Lambda_{c}^{+}=u d c,\\; p=u u d, \\;\\bar{K}^{0}=s \\bar{d}$$.\nI know that it is a weak interaction and the c-quark decay directly to the s-quark or the d-quark + any other particles allowed by the appropriate laws. So after analyzing the possible decays (quark mixing and so on), I made the following feynman diagram:", null, "However I looked up the solution, and it was very similar but still different:", null, "The solution doesn't group together the quarks in the correct way, so that it looks like the quarks form the hadrons given in the interaction. Is that because it's not important that you group them together, as long the correct quark constituents are drawn on the right side? I mean if the reaction created the $$\\Lambda=uds$$, $$\\pi^{+}= u \\bar{d}$$, would they have the excact same feynman diagram?\n\nA Feynman diagram shouldn't show spectator particles. It shouldn't care about anything composite. The fact that the incoming and outgoing quarks remain trapped in a certain hadron isn't relevant to the interaction the diagram shows. You just want the classic $$2$$-in,-$$2$$-out$$^\\dagger$$ setup per diagram, so each vertex/edge is elementary, and you can explain the hadronic implications afterwards.\n$$^\\dagger$$ Where anti-in=out, anti-out=in." ]
[ null, "https://i.stack.imgur.com/zv5smm.png", null, "https://i.stack.imgur.com/UM5mqm.png", null ]
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https://whatisconvert.com/440-cubic-centimeters-in-teaspoons
[ "# What is 440 Cubic Centimeters in Teaspoons?\n\n## Convert 440 Cubic Centimeters to Teaspoons\n\nTo calculate 440 Cubic Centimeters to the corresponding value in Teaspoons, multiply the quantity in Cubic Centimeters by 0.20288413535365 (conversion factor). In this case we should multiply 440 Cubic Centimeters by 0.20288413535365 to get the equivalent result in Teaspoons:\n\n440 Cubic Centimeters x 0.20288413535365 = 89.269019555608 Teaspoons\n\n440 Cubic Centimeters is equivalent to 89.269019555608 Teaspoons.\n\n## How to convert from Cubic Centimeters to Teaspoons\n\nThe conversion factor from Cubic Centimeters to Teaspoons is 0.20288413535365. To find out how many Cubic Centimeters in Teaspoons, multiply by the conversion factor or use the Volume converter above. Four hundred forty Cubic Centimeters is equivalent to eighty-nine point two six nine Teaspoons.\n\n## Definition of Cubic Centimeter\n\nA cubic centimeter (SI unit symbol: cm3; non-SI abbreviations: cc and ccm) is a commonly used unit of volume which is derived from SI-unit cubic meter. One cubic centimeter is equal to 1⁄1,000,000 of a cubic meter, or 1⁄1,000 of a liter, or one milliliter; therefore, 1 cm3 ≡ 1 ml.\n\n## Definition of Teaspoon\n\nA teaspoon (occasionally \"teaspoonful\") is a unit of volume, especially widely used in cooking recipes and pharmaceutic prescriptions. It is abbreviated as tsp. or, less often, as t., ts., or tspn. In the United States one teaspoon as a unit of culinary measure is  1⁄3 tablespoon, that is, 4.92892159375 ml; it is exactly 1  1⁄3 US fluid drams,  1⁄6 US fl oz,  1⁄48 US cup, and  1⁄768 US liquid gallon and  77⁄256 or 0.30078125 cubic inches. For nutritional labeling on food packages in the US, the teaspoon is defined as precisely 5 ml.\n\n## Using the Cubic Centimeters to Teaspoons converter you can get answers to questions like the following:\n\n• How many Teaspoons are in 440 Cubic Centimeters?\n• 440 Cubic Centimeters is equal to how many Teaspoons?\n• How to convert 440 Cubic Centimeters to Teaspoons?\n• How many is 440 Cubic Centimeters in Teaspoons?\n• What is 440 Cubic Centimeters in Teaspoons?\n• How much is 440 Cubic Centimeters in Teaspoons?\n• How many tsp are in 440 cm3?\n• 440 cm3 is equal to how many tsp?\n• How to convert 440 cm3 to tsp?\n• How many is 440 cm3 in tsp?\n• What is 440 cm3 in tsp?\n• How much is 440 cm3 in tsp?" ]
[ null ]
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https://lists.boost.org/Archives/boost/1999/11/0882.php
[ "", null, "# Boost :\n\nFrom: scleary_at_[hidden]\nDate: 1999-11-09 09:47:10\n\n> Regarding what should be the default return value of the PRNG,\n> throughout I have assumed that it would be an integer, most likely\n> 32-bit. My PERSONAL preference, though, would be for a real,\n> either in [0,1] or [0,1). I find these ranges far more useful in far more\n> contexts than the straight 32-bit integer. Furthurmore, given the\n> unsuitability of the modulus technique to map the PRNG integer output\n> onto a certain range, this means that virtually all random number\n> requests, except those that request a 32-bit integer directly, will\n> first map the PRNG output to this range before remapping it\n> to whatever range is required. However, concerns about the cost of the\ndivision\n> involved, when such division may be uneccessary (imagine users who do\n> need the 32-bit integers -- if we go the [0,1] route, they will be\n> getting numbers that have been divided by 0xfffffff and then\n> multiplied by 0xfffffff: perverse!) led me to stick to the \"PRNG gives\n32-bit\n> integer\" assumption.\n>\n\nThere is another possibility. What if we design the random number classes\nto use fixed precision arithmetic internally? That would avoid the overhead\nof floating-point, and also have the default range be [0,1) (assuming all\nbits are fractional bits), and also have a direct mapping (no mult/div\nnecessary) to the range of the underlying unsigned integer type: [0,\nnumeric_limits<underlying_int_type>::max()].\n\n-Steve" ]
[ null, "https://lists.boost.org/boost/images/boost.png", null ]
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https://www.intmath.com/forum/differentiation-transcendental-28/derivative-of-log-function:143
[ "Search IntMath\nClose\n\n450+ Math Lessons written by Math Professors and Teachers\n\n5 Million+ Students Helped Each Year\n\n1200+ Articles Written by Math Educators and Enthusiasts\n\nSimplifying and Teaching Math for Over 23 Years\n\n# derivative of log function [Solved!]\n\n### My question\n\nIn the chapter Derivative of the Logarithmic Function, Example #6, is it necessary to apply the change of base to get to the right solution?\n\n### Relevant page\n\n5. Derivative of the Logarithmic Function\n\n### What I've done so far\n\nBased upon the fact that\n\ndy/dx = 1/[\"argument\" xx ln(base)] xx [d/dx(\"argument\")]\n\nmy solution was\n\ndy/dx = 1/[6x ln 2] * (6) = 1/[x ln 2]\n\nX\n\nIn the chapter Derivative of the Logarithmic Function, Example #6, is it necessary to apply the change of base to get to the right solution?\nRelevant page\n\n<a href=\"/differentiation-transcendental/5-derivative-logarithm.php\">5. Derivative of the Logarithmic Function</a>\n\nWhat I've done so far\n\nBased upon the fact that\n\ndy/dx = 1/[\"argument\" xx ln(base)] xx [d/dx(\"argument\")]\n\nmy solution was\n\ndy/dx = 1/[6x ln 2] * (6) = 1/[x ln 2]\n\n## Re: derivative of log function\n\n@Phinah\n\nPlease use the math entry system so I, and others, can read your question. I have edited it just now.\n\nI checked your answer by finding 1/(ln(2)) and it has the same value, 1.4427, so your approach appears to be fine!\n\nWhenever I see a log expression with a base other than e, I automatically change base. This means I only need to learn one formula and can apply it in many places. In this case, I like the look of your approach better! :-)\n\nX\n\n@Phinah\n\nPlease use the math entry system so I, and others, can read your question. I have edited it just now.\n\nI checked your answer by finding 1/(ln(2)) and it has the same value, 1.4427, so your approach appears to be fine!\n\nWhenever I see a log expression with a base other than e, I automatically change base. This means I only need to learn one formula and can apply it in many places. In this case, I like the look of your approach better! :-)\n\n## Re: derivative of log function\n\nOk got it! Thank you for the explanation.\n\nX\n\nOk got it! Thank you for the explanation." ]
[ null ]
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https://www.enjoyalgorithms.com/blog/validate-binary-search-tree/
[ "# Validate Binary Search Tree: Check if a Binary Tree is BST or not\n\nKey takeaway: An excellent problem to understand the properties of binary search trees and learn step-by-step optimization using various approaches.\n\n### Let’s understand the problem\n\nGiven the root of a binary tree, write a program to check whether it is a valid binary search tree (BST) or not. A BST is valid if it has the following properties:\n\n• All nodes in the left subtree have values less than the node’s value.\n• All nodes in the right subtree have values greater than the node’s value\n• Both left and right subtrees are also binary search trees.\n\n### Examples", null, "### Discussed solution approaches\n\n• A wrong solution approach!\n• A brute force approach: Comparing each node value with the max of the left sub-tree and min of the right sub-tree.\n• An optimized version of the brute force approach: Tracking min and the max range of values allowed for the subtree rooted at each node.\n• Using inorder traversal and extra space\n• An efficient approach: In-place solution using inorder traversal\n\n### Wrong solution approach!\n\nAn unclear understanding of this problem can lead to a wrong approach. For example, Suppose we understood the BST property incorrectly and designed this solution: We visit each node recursively and compare the value stored in each node with the value stored on the left and right child. If the node value is greater than the left child value or less than the right child value, we return false. Otherwise, we recursively call the same function to verify the left sub-tree and right sub-tree.\n\n``````boolean isValidBST (TreeNode root)\n{\nif (root == NULL)\nreturn true\n\nif (root->left != NULL && root->left->value > root->value)\nreturn false\nif (root->right != NULL && root->right->value < root->value)\nreturn false\n\nboolean left = isValidBST(root->left)\nboolean right = isValidBST(root->right)\nif(left == true && right == true)\nreturn true\nelse\nreturn false\n}\n``````\n\n#### What is the mistake in the above solution?\n\nBased on the BST property, each node value must be greater than all the nodes in the left sub-tree and less than all the nodes in the right sub-tree. But the above solution just checks this property for the children of each node, not the entire left or right subtree. So this solution will give the wrong result for several input cases. Consider this example:", null, "### Solution 1: A brute force and correct approach\n\n#### Solution Idea\n\nNow the critical question is: how can we fix the above solution? Here is an idea: A tree can not be BST if the left subtree contains any value greater than the node’s value and the right subtree contains any value smaller than the node’s value. In other words, the node value must be less than the maximum in the left sub-tree and greater than the minimum in the right sub-tree.\n\nNote: In a BST, the rightmost node would be the node with the maximum value and the leftmost node would be the node with the minimum value.\n\n#### Solution Steps\n\n• Base case: If (root == NULL ), we return true.\n• We find max in the left subtree and min in the right subtree using two helper functions i.e. leftMax = bstMax(root->left) and rightMax = bstMin(root->right).\n• If leftMax > root->value or rightMax < root->value, then root node violates the BST property and we return false.\n• Otherwise, the root node satisfies the BST property. So we recursively check that left and right subtree are correct BST or not. For this, we call the same function with root->left and root->right as the input parameters.\n``````boolean left = isValidBST(root->left)\nboolean right = isValidBST(root->right)\n``````\n• If both left and right are true, then we return true. Otherwise, we return false. Think!\n\n#### Solution Pseudocode\n\n``````boolean isValidBST(TreeNode root)\n{\nif (root == NULL)\nreturn true\nint leftMax = bstMax(root->left)\nint rightMax = bstMin(root->right)\nif (leftMax > root->value || rightMax < root->value)\nreturn false\n\nboolean left = isValidBST(root->left)\nboolean right = isValidBST(root->right)\n\nif(left == true && right == true)\nreturn true\nelse\nreturn false\n}\nint bstMax(TreeNode root)\n{\nwhile(root->right != NULL)\nroot = root->right\nreturn root->value\n}\nint bstMin(TreeNode root)\n{\nwhile(root->left != NULL)\nroot = root->left\nreturn root->value\n}\n``````\n\n#### Time complexity analysis\n\nWe are traversing the tree recursively and calling bstMax(root->left) and bstMin(root->right) for each node. The worst-case time complexity of finding max in a BST = O(n), the worst-case time complexity of finding min in a BST = O(n). Think!\n\nIf we look closely, the time complexity will depend on the tree's structure. The worst-case situation will occur when the tree is high unbalanced i.e., either left-skewed (All nodes have a left child except the single leaf node) or a right-skewed tree (All nodes have a right child except the single leaf node). So worst-case time complexity to validate BST = n*O(n) = O(n^2).\n\nThe above code is recursive. So here are some critical questions for the learning purpose! We will add answers to these questions later in this blog.\n\n• The best-case scenario will occur when the tree is balanced.\n• The recurrence relation for the worst case is T(n) = T(n - 1) + O(n)\n• The recurrence relation for the best case is T(n) = 2T(n/2) + O(logn)\n• Proof that the best case time complexity is O(n)! Hint: Use the first case of the master theorem.\n• What would be the space complexity?\n\n### Solution 2: An optimized version of the brute force approach\n\nWe need to traverse some nodes several times in the above method. Can we think of solving this problem efficiently? Can we think of solving the problem without finding the max and min for each node?\n\n#### Solution Idea\n\nIn a BST, the value stored in a subtree rooted at any node lies in a particular range. In other words, there is an upper (rangeMax) and a lower (rangeMin) limit of values that lie in a specific subtree. For example:\n\n• The tree with a root node lies in the range (INTMIN, INTMAX).\n• The left subtree lies in the range (INT_MIN, root-> value -1].\n• Right subtree range is [root->value + 1, INT_MAX), and so on.\n\nOne solution would be to traverse the tree recursively and keep track of the min and max range of values allowed for the subtree rooted at each node. We pass the acceptable range as a function argument while recursing for the left and right subtree.\n\nHere we need to go through each node only once, and the initial values for the min and max range should be INTMIN and INTMAX. If node->value < rangeMin or node->value > rangeMax, then node’s value falls outside the valid range and violates the min-max constraints. So we return false. Otherwise, we recursively check left and right subtrees with an updated range.", null, "#### Solution Pseudocode\n\n``````boolean isBST(TreeNode root)\n{\nreturn isValidBST(root, INT_MIN, INT_MAX))\n}\nboolean isValidBST(TreeNode root, int rangeMin, int rangeMax)\n{\nif(root == NULL)\nreturn true\nif (root->value < rangeMin || root->value > rangeMax)\nreturn false\n\nboolean left = isValidBST(root->left, rangeMin, root->value -1)\nboolean right = isValidBST(root->right, root->value + 1, rangeMax)\n\nif(left == true && right == true)\nreturn true\nelse\nreturn false\n}\n``````\n\n#### Time and space complexity analysis\n\nWe visit each node only once and perform an O(1) operation with each node. So time complexity = n* O(1) = O(n). Space complexity depends on the size of the recursion call stack, which is equal to the height of the tree. So space complexity = O(h). What would be the worst and best case of space complexity? Think!\n\n### Solution 3: Using inorder traversal and extra space\n\n#### Solution Idea\n\nThe inorder traversal of a binary search tree explores node values in sorted order. So another idea would be to traverse the tree using inorder traversal and store node values in an ArrayList or vector. Now we traverse the ArrayList or vector using a loop to check whether it is sorted or not. If sorted, then the tree is a BST; otherwise, not.\n\n#### Solution Pseudocode\n\n``````boolean isValidBST (TreeNode root)\n{\nvector<int> sorted\ninorderTraversal(root, &sorted)\nfor(int i = 1; i < sorted.size(); i = i + 1)\n{\nif (sorted[i] < sorted[i - 1])\nreturn false\n}\nreturn true\n}\nvoid inorderTraversal(TreeNode root, int & sorted)\n{\nif (root == NULL)\nreturn\ninorderTraversal(root->left, sorted)\nsorted.push_back(root->value)\ninorderTraversal(root->right, sorted)\n}\n``````\n\n#### Time and space complexity analysis\n\nTime complexity = Time complexity of inorder traversal for storing elements in array list + Time complexity of the single loop to check sorted arraylist = O(n) + O(n) = O(n). Space complexity = O(n) for storing elements in an arraylist + O(h) for recursion stack space = O(n + h)\n\n### Solution 4: In-place solution using inorder traversal\n\n#### Solution Idea\n\nThe critical question is: can we think to optimize the above approach and avoid using extra space? As we know that an inorder traversal of a BST returns the nodes in sorted order. So one idea would be to keep track of previously visited nodes while traversing the tree. If the current node value is less than the previous node value, then the tree is not BST.\n\n#### Solution pseudocode: Recursive inorder traversal\n\n``````boolean isBST(TreeNode root)\n{\nTreeNode prev = NULL\nreturn isValidBST(root, &prev)\n}\nboolean isValidBST(TreeNode root, TreeNode &prev)\n{\nif (root == NULL)\nreturn true\nboolean left = isValidBST(root->left, prev)\nif (prev != NULL && root->value < prev->value)\nreturn false\nprev = root\nboolean right = isValidBST(root->right, prev)\nif(left == true && right == true)\nreturn true\nelse\nreturn false\n}\n``````\n\n#### Solution pseudocode: Iterative inorder traversal using stack\n\n``````boolean isValidBST(TreeNode root)\n{\nif (root == NULL)\nreturn true\nStack<TreeNode> stack\nTreeNode curr = root\nTreeNode prev = NULL\nwhile (curr != NULL || stack.isEmpty()== false)\n{\nif (curr != NULL)\n{\nstack.push(curr)\ncurr = curr->left\n}\nelse\n{\ncurr = stack.pop()\nif(prev != NULL && curr->value < prev->data)\nreturn false\nprev = curr\ncurr = curr->right\n}\n}\nreturn true\n}\n``````\n\n#### Time and space complexity analysis\n\nWe visit each node only once and perform an O(1) operation with each node. So time Complexity = n* O(1) = O(n). Space complexity depends on the depth of the size of the recursion call stack, which is equal to the height of the tree. So space complexity = O(h).\n\n### Critical Ideas to think about!\n\n• How can we modify the above solution to work for duplicate values?\n• In the 4th approach using recursive inorder traversal, can we think of implementing without using the pointer by reference?\n• Can we think of implementing 2nd approach, using pointers by reference instead of passing the value?\n• Is there a way to solve this problem using some other approach?\n\n### Suggested problems to practice\n\n• Check if the given binary tree is a strict binary tree or not\n• Check whether the given binary is perfect or not\n• Check if a binary tree is a complete tree or not\n• Check if a binary tree is a subtree of another binary subtree\n• Check if the given binary tree is Heap or not\n• Check if the given binary tree is SumTree or not\n\nPlease write in the message below if you have alternative approaches or find an error/bug in the above approaches. Enjoy learning, Enjoy algorithms!" ]
[ null, "https://cdn-images-1.medium.com/max/720/1*VDjeWgeN5ajFNHH80_Xbeg.png", null, "https://cdn-images-1.medium.com/max/720/1*iwA_hbrSne4h3OG04drO3A.png", null, "https://cdn-images-1.medium.com/max/1080/1*9coFI61ERPnK64idFcBtNQ.png", null ]
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https://adotb.xyz/hannah/
[ "# Lesson Plan: 25th July\n\n## Integration by substitution\n\nWe’d cover integration by substitution first. At the A Levels, any integration that needs to be done by substitution will have the substitution given to us. We can then follow these next general steps (we will assume that $x$ is our original variable and $u$ is our new variable.\n\n1. Differentiate the given substitution (to change the “$\\mathrm{d}x$” into “$\\mathrm{d}u$”.\n2. Substitute both $x$ and “$\\mathrm{d}x$” into the “$u$”-counterparts.\n3. After substitution and simplification, we should now have an integral that can be done relatively simply.\n4. Change all $u$s back to the original variables $x$’s.\n\n### Example 1\n\n20d) Use the substitution $u=e^{2x}$ to find $\\displaystyle \\int \\frac{e^{2x}}{\\sqrt{1-e^{4x}}} , \\mathrm{d}x$.\n\nStep 1: $\\displaystyle \\frac{\\mathrm{d}u}{\\mathrm{d}x} = 2 e^{2x}$\n\n“$\\displaystyle \\mathrm{d}x = \\frac{1}{2e^{2x}} , \\mathrm{d}u$”\n\nStep 2:\n\n$\\displaystyle \\int \\frac{e^{2x}}{\\sqrt{1-e^{4x}}} , \\mathrm{d}x =\\int \\frac{u}{\\sqrt{1-u^2}} \\left( \\frac{1}{2u} , \\mathrm{d}u\\right)$\n\nStep 3:\n$\\displaystyle = \\frac{1}{2} \\int \\frac{1}{\\sqrt{1-u^2}} , \\mathrm{d}u = \\frac{1}{2} \\sin^{-1} u + c$\n\nStep 4:\n$\\displaystyle = \\frac{1}{2} \\sin^{-1} (e^{2x}) +c$\n\n### Example 2:\n\nFor trigo substitutions there may be a few extra tricks, such as the use of our Pythagorean/square formulas, and using the right angled triangle to simplify certain steps (in step 4 in this example: I’d draw it out for you during class).\n\nModified 17e) Use the substitution $x = \\sec \\theta$ to find $\\displaystyle \\int \\frac{1}{\\sqrt{x^2-1}} , \\mathrm{d}x$.\n\nStep 1: $\\displaystyle \\frac{\\mathrm{d}x}{\\mathrm{d}\\theta} = \\sec \\theta \\tan \\theta$\n\n“$\\displaystyle \\mathrm{d}x = \\sec \\theta \\tan \\theta , \\mathrm{d}\\theta$”\n\nStep 2:\n\n$\\displaystyle \\int \\frac{1}{\\sqrt{x^2-1}} , \\mathrm{d}x =\\int \\frac{1}{\\sqrt{\\sec^2 \\theta – 1}} \\left( \\sec \\theta \\tan \\theta , \\mathrm{d}\\theta \\right)$\n\nStep 3:\n$\\displaystyle =\\int \\frac{1}{\\sqrt{\\tan^2 \\theta}} \\sec \\theta \\tan \\theta , \\mathrm{d}\\theta = \\int \\sec \\theta , \\mathrm{d}\\theta = \\ln | \\sec \\theta + \\tan \\theta |+ c$\n\nStep 4:\n$\\displaystyle = \\ln | x + \\sqrt{x^2-1} | +c$\n\n## Integration by parts\n\n$\\displaystyle \\int u \\frac{\\mathrm{d}v}{\\mathrm{d}x} , \\mathrm{d}x = uv – \\int \\frac{\\mathrm{d}u}{\\mathrm{d}x}v,\\mathrm{d}x$\n\nIntegration by parts is analogous to “product” rule in differentiation, except that the formula is a lot more complicated, and there is still an integration sign left after applying the formula.\n\nSuccessfully applying integration by parts involve making the second term simpler such that we can now integrate it.\n\n### Example 1\n\n14d) $\\displaystyle \\int x \\cos x , \\mathrm{d}x$\n\n$\\displaystyle \\int x \\cos x , \\mathrm{d}x = x \\sin x – \\int 1 \\sin x , \\mathrm{d}x = x \\sin x + \\cos x + c$\n\n### A discussion on order\n\nWe will discuss more about order in class, and how it is important in this technique.\nIf no hints are given, a useful heuristic is LIATE\n\n• L: Logarithm: $\\ln x$\n• I: Inverse Trigo: $\\sin^{-1}x, \\tan^{-1}x$\n• A: Algebra: $1, x, x^2$\n• T: Trigo: $\\sin x, \\cos x$\n• E: Exponential\n\nRoughly we group them into 3:\n\n• LI: Almost always ‘differentiated’ (i.e. the ‘$u$’)\n• TE: Almost always ‘integrated’ (i.e. the ‘$\\frac{\\mathrm{d}v}{\\mathrm{d}x}$’)\n• A: KIV: depending on who they’re paird with" ]
[ null ]
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https://ltwiki.org/index.php?title=B_sources_(common_examples)&oldid=1990
[ "# B sources (common examples)\n\n(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)\n\nFor a listing of all b-source functions see B sources (complete reference).\n\n### When, why and how to use tripdt and tripdv with explanation\n\nHelp states, \"If the voltage across a source changes by more than tripdv volts in tripdt seconds, that simulation time step is rejected.\"\n\nThis is rather terse, but it seems to mean, when attempting a solution for the next transient simulation step, in addition to comparing the non linear error of the next step to reltol and other step size acceptance limits, the simulation engine will perform the following test:\n\nIF (the voltage change *across* the b-source > tripdv AND the time change across the simulation step > tripdt) THEN reject the simulation step size, i.e. make it smaller and try again.  (This is quite different than just testing if the magnitude of slope of the voltage across the source gets too large.)\n\nBy experimentation, it seems Mike's description is not exactly correct, at least for the last time step while leaving the state change constraint where it seems the allowable tripdt limit is increased by two. Here is a netlist that illustrates LTspice invoking the time step state change constraint.\n\n```V1 1 0 SINE(0 1 1k) ; input test source\nB1 2 0 V=buf(V(1)) tripdv=0.1 tripdt=10n ; b-source equivalent to a BUF a-device (with state transition time accuracy control)\n.opt plotwinsize=0\n.tran 5m\n```\n\nThe u() function is digital in nature so changing tripdv over a wide range has little effect just so long as it is a bit smaller than the state change of the unit step function. However, tripdt directly controls the maximum allowable time change through the state change except the last of these time changes may be twice the limit (no doubt due to the standard way LTspice increases time steps by doubling).\n\nThe problem with the tripdv/tripdt constraint arises when the b-source voltage is analog rather than digital in nature because it is very possible to choose these limits such that normal voltage changes exceed them. That causes an effect much like a very small maximum time step and the simulation may run very slowly.\n\nIn order to differentiate the effects on time step size and accuracy that stem from b-source tripdv and tripdt from the normal step size control algorithms, it is probably a good idea to disable or slacken the normal step controls. If maximum step size is not specified, it seems LTspice may select a max step size as a fraction of the end time and perhaps reltol and some other parameters.\n\nFor b-source step size control experimentation, I would recommend loosening up reltol and setting the step size to the same as the stop time. Also waveform compression should be disabled.\n\n```.opt reltol=10m plotwinsize=0\n```\n\nIf you put yourself in the \"shoes\" of the simulator solver, you can see that the shape of a signal can effect how easy it is to locate activity (pin down state changes or high dv/dt) in a b-source signal. For example, first consider a square wave for which you want the simulator to locate and reproduce the transitions very precisely, yet run as fast as possible between transitions. After an edge event the solver keeps increasing the step size because nothing is changing. At some point the voltage changes and the solver has to reject steps to back up in time in order to locate the latest edge event (otherwise the points across the edge would remain widely spaced and when the plot engine connects the dots, the square wave may end up looking more like a triangle wave).\n\nWhen you make a square wave with the standard voltage source, the solver knows ahead of time that it is a square wave and where the edges should be in time, but if you make a square wave with a b-source, I don't think it has any way to interpret whatever arbitrary function you have assigned it, so it must rely on tripdv and tripdt to recognize an event. However, a square wave change is easy to see because even if the edge is missed, the level has changed and remains changed for at least several time steps, so the solvers knows an event occurred that it should back up and locate.\n\nNow consider how much more difficult it is for the solver to \"see\" a narrow pulse type waveform. If the solver doesn't know ahead of time where the edges should be, it could easily blow right by the pulse, never knowing it should have occurred at all. The points on either side of the pulse will be correct so the plot engine will just connect the dots as a flat line. Unlike the case for the square wave, tightening up tripdv and triptdt will not help unless a time point chances to fall within the narrow active region of the pulse (then the edges of that pulse may be sharpened by tightening tripdv and tripdt, but most pulses will still be overlooked).\n\nSo what to do if you need to make narrow b-source pulses? First make a rectangular or saw tooth wave and key its edge from whatever will also drive the pulse.\n\nNote that a transient simulation is not continuous with time, but is actually a collection of consecutive solutions to the circuit at a series of discrete time steps.  In order to make the simulation run as quickly as possible, the simulation engine constantly monitors the nonlinear error between adjacent steps and will adjust step size dynamically for a step size that doesn't lead to an unacceptable error.  If the error is too small, the step size is still used, but the *next* time step is made larger.  If the error is too large, the step size is rejected, i.e., the solution results are discarded and another solution is attempted with a smaller step size.\n\nIt seems that even if tripdt and tripdv are not specified, LTspice still applies an internal default test to accept or reject a step based on whether or not the behavioral source changes too much in one time step.  Perhaps this internal default function is separate from the tripdv/tripdt test, or perhaps a default value for tripdt is estimated based on something like the the simulation end time.\n\n### Replicating a-devices with b-sources\n\nIt is a trivial exercise to replicate most digital functions by directly applying the logical operators available to b-sources in LTspice. One need only take the initiative to read their descriptions in the Help file and write the obvious expressions. This applies to buffers, inverters, and-gates, or-gates and xor-gates. With a little thought, one can easily build most more complex digital functions with b-sources as well. However, digital functions that are based on temporal states are more problematic. This class of functions includes flip-flops, edge triggered flip-flops, sample-and-hold devices and the like.\n\nFor example, b-sources do not directly provide a sample-and-hold function, yet a very efficient implementation is possible with a roundabout application of the Verilog integration function, sdt(x,ic,r), which provides integration of a variable with optional initial condition and optional reset to that initial condition (assert).\n\nWith sdt(0,ic,r), when the integrand is set to zero, the initial condition (which may vary during the simulation) will be continuously sampled as long as the reset is high and then held as long as reset is low, thus producing an ideal sample-and-hold with zero acquisition time.\n\nBuilding an edge triggered digital device also requires a similar indirect application of the Verilog differentiation function, ddt(x). To detect the positive going edge of an input clock pulse stream, it must first be squared up (ideally buffered to a logical one or zero), then differentiated and buffered again to produce a pulse only on the positive edge. Here is the SPICE code:\n\n#### * Edge triggered b-source logic and integrated averaging in LTspice\n\nThese following functions are intended to be used in b-sources. The first two replicate edge triggered logic such as is used in the a-device DFLOP clock input. The last function is more complicated as it includes three behavioral integrators to provide a running integrated average of x (starting on the falling edge of sampling pulse s) that is then held until the next rising edge of sampling pulse s. In normal use, x would be an analog input and the sampling pulse s would be a series of very narrow 1 volt positive digital pulse.\n\n```.func up(s) buf( ddt(s)) ; generates pulse on rising edge of s\n.func dn(s) buf(-ddt(s)) ; generates pulse on falling edge of s\n\n* The following averages x between sample pulses s\n.func ave(x,s) sdt(0,sdt(x,0,dn(s))/sdt(1,0,dn(s)),up(s))\n```\n```B1 0 1 I= ave(V(x),V(s)) Rpar=1 Cpar=1n ; source for x and s not shown\n```\n\n#### * D Flip-Flop (with Q-not feedback to create divide by two counter)\n\n```* Divide by two counter (D flip-flop with Q-not data feedback)\nVclk clk 0 PULSE(0 1 1u 1u 1u 1u 10u) ; input pulse source\nBdflop 0 Q I=sdt(0, inv(V(Q)), buf(ddt(buf(V(clk))))) Rpar=1 Cpar=1nF ; D Flip-Flop\n.tran 50u\n```\n\nNote that the b-source has been Nortonized into a one amp current source driving a 1nF capacitor in parallel with a one ohm resistor. This provides a picosecond time constant delay to output changes. This small delay is a convergence aid that is necessary so that the solver is able to resolve state changes of the b-source that depend directly on its own output.\n\nAlthough this b-source divide-by-two counter is robust and efficient, it is no match in speed to the equivalent LTspice native a-device (either the DFLOP or the even more versatile COUNTER device). LTspice's native a-device will always outperform the best b-source equivalent implementation, so this entire exercise is somewhat of an academic study.\n\nBecause they are general purpose devices, b-sources are computationally burdened with carrying a full Jacobian (although this can be turned off - often with disastrous results - with the NoJacob parameter). Also, since b-sources are largely analog devices, they do not have a built-in provision to recognize state changes like the digital a-devices do (yes, this can be less effectively approximated with b-sources by specifying the tripdv and tripdt parameters). The bottom line is that in LTspice it is always better to use a-devices whenever they fit the requirement.\n\n#### * Replicating the MODULATOR a-device\n\nIn the netlist below a MODULATOR a-device is set up with 1V=100Hz and 0V=0Hz. It is then driven by V1 to sweep from 50Hz to 150Hz over 1 second. The frequency control input is V(f) and its swept outputs are V(sinA) and V(cosA).\n\n```.param fo=100\nV1 f 0 PWL(0 0.5 1 1.5)\nA1 f 0 0 0 0 cosA sinA 0 MODULATOR Mark={fo} Space=0\n```\n\nThe b-sources below produce the same swept waveforms on V(sinB) and V(cosB). R1 and R2 duplicate the output impedance of the a-device and C1 and C2 are important for waveform fidelity and must be selected based on the frequency range of interest. They are needed to \"trick\" LTspice into producing enough waveform data points as the frequency increases. (Because b-sources are general purpose devices, it is often a problem to get them to correctly control step size.)\n\n```.param wo=2*Pi*fo\nB1 0 sinB I=sin(wo*sdt(V(f))) Rpar=1 Cpar=1µ\nB2 0 cosB I=cos(wo*sdt(V(f))) Rpar=1 Cpar=1µ\n```\n\n### Building other functions with b-sources\n\n#### * State Machine Helper Logic\n\nThe internal parameter “time” is available to state machine logic. It would very useful to create a new parameter called “StateTime” that would reset to zero at each state change. This would make it much more straightforward to create transitional “timer” states. Note, assuming the state value is made available as an output, it is possible using a b-source to create a \"state-time\" node that is based on the state value as follows:\n\n```B1 st 0 V=sdt(1,0,buf(abs(ddt(V(state))))) ; node \"st\" is \"state time\"\n```\n\nAnother useful function might be to add a parameter called something like “StateChange” that would go high only during state transitions and be low otherwise. Note that this incorporated in the b-source function above as buf(abs(ddt(V(state)))).\n\n#### * Up/Down Counter in a single b-source\n\n```B1 0 cnt I=sdt(0, round(V(cnt)+buf(ddt(V(up)))-buf(ddt(V(dn)))), buf(ddt(V(up)+V(dn))) ) Rpar=1 Cpar=10n\n```\n\nThe b-source is a current source Nortonized into voltage source with a 1 ohm output impedance. The b-source parallel capacitor must be 2x the slowest rise time of the up/down inputs. In between up and down count pulses the sdt function holds the last count.\n\nThe up and down inputs, V(up) V(dn), use LTspice's standard 1 volt logic levels and trigger on the positive edges.\n\nThe cnt (count) output is an integer count that starts from zero. I haven't shown a reset, but it would be very easy to add.\n\n#### * Other, Notes, etc.\n\nI've got an equation in an arbitrary behavioral source that uses the variable *TIME* to plot.  What I can't figure out is how to cause this to repeat at some interval.\n\nTime is a ramp that never resets.  What you need is a replacement for time in your equation that resets to zero at your repeat interval, i.e., a sawtooth function.\n\nYou could set up a standalone voltage source to make the sawtooth and replace \"time\" in your equation with the sawtooth node, \"v(x)\" or you could do this directly in the equation by replacing \"time\" with either of the following expressions:\n\n• time-int(time/m)*m ; where m is the modulus (repeat interval)\n• idtmod(1,0,m) ; integrates 1*dt with 0 offset at modulus m\n\nIf you want, you could define such expressions with a .function statement in order to keep your b-source equation from getting too messy.\n\n```.function a(m)= time-int(time/m)*m\n.func b(m)= idtmod(1,0,m) ; .func is the short name\n.param r=4 ; r is the actual reset modulus you wish to use\n```\n\nNow, within your b-source equation, you could replace each instance of \"time\" with either \"a(r)\" or \"b(r)\" (or change the names to suit what makes sense to you).\n\nNOTES:\n\n• Explain how to make a discretized (pseudo-digital) source.\n• Demo various kinds of output limiters (tanh, limit, etc.) and explain why and where these are well worth using.\n• Show how to convert a BV source into an equivalent BI source (with parallel capacitor) and explain why this is generally a much better form to use.\n\nother??" ]
[ null ]
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https://copyassignment.com/simple-gui-calculator-using-tkinter-in-python/
[ "# GUI Calculator Using Tkinter In Python", null, "We will make a Simple GUI Calculator Using Tkinter In Python which is a python module to make GUI applications simply so that’s why we will use it to make a GUI Calculator Using tkinter\n\nHere we are going to provide you with the source code with a complete explanation so that you can easily make your GUI Calculator Using tkinter\n\n## Source Code\n\n```# importing the tkinter module\nfrom tkinter import *\n\n# initializing the tkinter\nroot = Tk()\n\n# setting the width and height of the gui\nroot.geometry(\"430x500\") # x is small case here\n\n# declaring an empty string variable\nexpression = \"\"\n\n# defining function which will set expressions and answers to the user\ndef setexpression(num):\nglobal expression\nexpression = expression + str(num)\nvalue.set(expression)\n\n# defining a function to calculate the expression entered by the user\ndef calculator():\ntry:\nglobal expression\nexcept:\nvalue.set(\"Enter correct expression\")\nexpression = \"\"\n\n# function to clear everything in expression\ndef clear():\nglobal expression\nexpression = \"\"\nvalue.set(expression)\n\n# declaring font variables as (\"Language\", size)\nlarge_font = ('Verdana', 15)\nsmall_font = ('Verdana', 10)\n\n# declaring variable to take value of expression entered by the user\nvalue = StringVar(value=\"Enter expression\")\n\n# entry widget to take expression from user and to show\n# calculations\nEntry(root, textvariable=value, font=large_font).grid(row=0,\n\n# Now, there are some most basic buttons which should be present\n# in a calculator\n# here, each button is calling the setexpression function which\n# is used to set values in the entry widget entered by the user\n# on pressing the buttons 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, .\nButton(root, text=\"+\", fg=\"red\", command=lambda:\nButton(root, text=\"-\", fg=\"red\", command=lambda:\nButton(root, text=\"X\", fg=\"red\", command=lambda:\nButton(root, text=\"/\", fg=\"red\", command=lambda:\nButton(root, text=\"1\", fg=\"red\", command=lambda:\nButton(root, text=\"2\", fg=\"red\", command=lambda:\nButton(root, text=\"3\", fg=\"red\", command=lambda:\nButton(root, text=\"4\", fg=\"red\", command=lambda:\nButton(root, text=\"5\", fg=\"red\", command=lambda:\nsetexpression(\"5\"), height=4, width=8).grid(row=2, column=2)\nButton(root, text=\"6\", fg=\"red\", command=lambda:\nButton(root, text=\"7\", fg=\"red\", command=lambda:\nButton(root, text=\"8\", fg=\"red\", command=lambda:\nButton(root, text=\"9\", fg=\"red\", command=lambda:\nButton(root, text=\"0\", fg=\"red\", command=lambda:\nButton(root, text=\".\", fg=\"red\", command=lambda:\n\n# \"=\" button to call the calculator button which will return and\n# show the calculated value in the entry widget\nButton(root, text=\"=\", fg=\"red\", command=calculator, height=4,\n\n# \"Clear\" button to call the clear function which will clear the\n# entry widget so that the user can start clculating again\nButton(root, text=\"Clear\", fg=\"red\", command=clear, height=4,\n\n# .mainloop() is used when the code is ready to run\nroot.mainloop()```\n\n## Output:\n\nKeep updated for more amazing content like this", null, "" ]
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https://www.accountingformanagement.org/internal-rate-of-return-method/
[ "# Internal rate of return method\n\nLike net present value method, internal rate of return (IRR) method also takes into account the time value of money. It analyzes an investment project by comparing the internal rate of return to the minimum required rate of return of the company.\n\nThe internal rate of return sometime known as yield on project is the rate at which an investment project promises to generate a return during its useful life. It is the discount rate at which the present value of a project’s net cash inflows becomes equal to the present value of its net cash outflows. In other words, internal rate of return is the discount rate at which a project’s net present value becomes equal to zero.\n\nThe minimum required rate of return is set by management. Most of the time, it is the cost of capital of the company.\n\nUnder this method, If the internal rate of return promised by the investment project is greater than or equal to the minimum required rate of return, the project is considered acceptable otherwise the project is rejected. Internal rate of return method is also known as time-adjusted rate of return method.\n\nTo understand how computations are made and how a proposed investment is accepted or rejected under this method, consider the following example:\n\n## Example:\n\nThe management of VGA Textile Company is considering to replace an old machine with a new one. The new machine will be capable of performing some tasks much faster than the old one. The installation of machine will cost \\$8,475 and will reduce the annual labor cost by \\$1,500. The useful life of the machine will be 10 years with no salvage value. The minimum required rate of return is 15%.\n\nRequired: Should VGA Textile Company purchase the machine? Use internal rate of return (IRR) method for your conclusion.\n\n### Solution:\n\nTo conclude whether the proposal should be accepted or not, the internal rate of return promised by machine would be found out first and then compared to the company’s minimum required rate of return.\n\nThe first step in finding out the internal rate of return is to compute a discount factor called internal rate of return factor. It is computed by dividing the investment required for the project by net annual cash inflow to be generated by the project. The formula is given below:\n\nFormula of internal rate of return factor:", null, "In our example, the required investment is \\$8,475 and the net annual cost saving is \\$1,500. The cost saving is equivalent to revenue and would, therefore, be treated as net cash inflow. Using this information, the internal rate of return factor can be computed as follows:\n\nInternal rate of return factor = \\$8,475 /\\$1,500\n\n= 5.650\n\nAfter computing the internal rate of return factor, the next step is to locate this discount factor in “present value of an annuity of \\$1 in arrears table“. Since the useful life of the machine is 10 years, the factor would be found in 10-period line or row. After finding this factor, see the rate of return written at the top of the column in which factor 5.650 is written. It is 12%. It means the internal rate of return promised by the project is 12%. The final step is to compare it with the minimum required rate of return of the VGA Textile Company. That is 15%.\n\nConclusion:\n\nAccording to internal rate of return method, the proposal is not acceptable because the internal rate of return promised by the proposal (12%) is less than the minimum required rate of return (15%).\n\nNotice that the internal rate of return promised by the proposal is a discount rate that equates the present value of cash inflows with the present value of cash out flows as proved by the following computation:", null, "*Value from “present value of an annuity of \\$1 in arrears table“.\n\nShow your love for us by sharing our contents.\n\n### 23 Comments on Internal rate of return method\n\n1.", null, "tejaswini\n\nThanking u but I want some more examples.\n\n2.", null, "Accounting for Management\n\nYou can see exercises and problems sections of the website.\n\n3.", null, "Ameli\n\nWhat about how to compare to exclusive projects?\n\n4.", null, "patricia\n\nhow can i find the PVF@ more than 21 for IRR?\n\n5.", null, "Mercy\n\nhow do i calculate the IRR when given the salvage value.\n\n6.", null, "abel afore markson\n\nwhat is the best formula for calculating internal rate of return?\n\n7.", null, "Buster\n\nIt seems as though all the examples are on investment in fixed asset. What about investment in services e.g. investing in the stock market. Does the same approach holds?\n\n8.", null, "Rose Anne\n\nwhat if i’m not going to use the table in locating the discount factor?\n\n9.", null, "Wasem solomon\n\nDe formula u gave n eg. Is rather compounding issues\n\n10.", null, "kate jerry\n\nHow do I calculate for 19% discount rate using four figure table, so as to ascertain irr?\n\n11.", null, "Elida\n\nIt’s a plsreuae to find someone who can think so clearly\n\n12.", null, "sumit\n\nYou can solve like our class does?\n\n13.", null, "James\n\nhow do we compute for IRR and NPV if no rate is given, only the current amount of a planned purchase of a machine, its life in years, savings it can give the company and its depreciation amount?\n\n14.", null, "nehecristy\n\na project cost N556,000 to initiate and it will generate annual cashflows(receipt less payment) of N200,000 for a period of 5 yrs. the expected scrap value is 56000. depreciation is provided on straight line method.cost of capital is 22%\nrequired: arr, npv, irr, pbp, discounted pvb.\npls help me. dis is an assignment for 15 marks in my college tanks.\n\n15.", null, "TWIZEYE JULIAS\n\nOK\n\n16.", null, "Siva Kumar\n\nHow can i get Rate of Return for indefinite period?\n\n17.", null, "George\n\nIt’s strange to see internal rate of return computed analytically, are you sure this is the correct approach? Seems to be different from what is claimed in a lot of other sources: that it can’t be computed analytically and you need approximations to make it work, e.g. https://www.gigacalculator.com/calculators/irr-calculator.php . Is your “internal rate of return factor” the same or different than the classic “internal rate of return” concept???\n\n18.", null, "Kulwa\n\nwhere can I get examples that show estimates flow of the net benefits for for two projects with the the same discount rate? example 5% and 10%\n\n19.", null, "NAGGITA VICTORIA\n\nMore examples are needed\n\n20.", null, "banky lawrence\n\nsuppose you have a 4yr project that costs \\$500. the cash flow over the 4 yr life will be \\$100,\\$200,\\$300 and \\$400 from yr 1-4 respectively. whats the IRR of the project?\n\n21.", null, "julius moses\n\nthanks alot for that precise example\n\n22.", null, "Etimu Simon.S.E\n\nWhat is the cost of capital of the company? How does it relate to the minimum rate of return?\nWhat is the realistic way for the company to determine the minimum rate of return?\n\n23.", null, "Manoharan\n\nIRR will work out for our loan availment – example if I get a loan of Rs.1 crore repayment in 10 equal instalment on 18% PA flat interest, what will be by nett IRR" ]
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https://inquiryintoinquiry.com/2019/07/26/animated-logical-graphs-25/
[ "## Animated Logical Graphs • 25\n\nLet’s examine the formal operation table for the third in our series of reflective forms to see if we can elicit the general pattern:", null, "$\\begin{array}{|*{3}{c}||c|} \\multicolumn{4}{c}{\\text{Formal Operation Table} ~ \\texttt{(} a \\texttt{,} b \\texttt{,} c \\texttt{)}} \\\\[4pt] \\hline a & b & c & \\texttt{(}a\\texttt{,}b\\texttt{,}c\\texttt{)} \\\\ \\hline\\hline \\texttt{Space}&\\texttt{Space}&\\texttt{Space}&\\texttt{Cross} \\\\ \\texttt{Space}&\\texttt{Space}&\\texttt{Cross}&\\texttt{Space} \\\\ \\texttt{Space}&\\texttt{Cross}&\\texttt{Space}&\\texttt{Space} \\\\ \\texttt{Space}&\\texttt{Cross}&\\texttt{Cross}&\\texttt{Cross} \\\\ \\hline \\texttt{Cross}&\\texttt{Space}&\\texttt{Space}&\\texttt{Space} \\\\ \\texttt{Cross}&\\texttt{Space}&\\texttt{Cross}&\\texttt{Cross} \\\\ \\texttt{Cross}&\\texttt{Cross}&\\texttt{Space}&\\texttt{Cross} \\\\ \\texttt{Cross}&\\texttt{Cross}&\\texttt{Cross}&\\texttt{Cross} \\\\ \\hline \\end{array}$\n\nOr, thinking in terms of the corresponding cactus graphs, writing", null, "${}^{\\backprime\\backprime} \\texttt{o} {}^{\\prime\\prime}$ for a blank node and", null, "${}^{\\backprime\\backprime} \\texttt{|} {}^{\\prime\\prime}$ for a terminal edge, we get the following Table:", null, "$\\begin{array}{|*{3}{c}||c|} \\multicolumn{4}{c}{\\text{Formal Operation Table} ~ \\texttt{(} a \\texttt{,} b \\texttt{,} c \\texttt{)}} \\\\[4pt] \\hline \\quad a \\quad & \\quad b \\quad & \\quad c \\quad & \\texttt{(}a\\texttt{,}b\\texttt{,}c\\texttt{)} \\\\ \\hline\\hline \\texttt{o} & \\texttt{o} & \\texttt{o} & \\texttt{|} \\\\ \\texttt{o} & \\texttt{o} & \\texttt{|} & \\texttt{o} \\\\ \\texttt{o} & \\texttt{|} & \\texttt{o} & \\texttt{o} \\\\ \\texttt{o} & \\texttt{|} & \\texttt{|} & \\texttt{|} \\\\ \\hline \\texttt{|} & \\texttt{o} & \\texttt{o} & \\texttt{o} \\\\ \\texttt{|} & \\texttt{o} & \\texttt{|} & \\texttt{|} \\\\ \\texttt{|} & \\texttt{|} & \\texttt{o} & \\texttt{|} \\\\ \\texttt{|} & \\texttt{|} & \\texttt{|} & \\texttt{|} \\\\ \\hline \\end{array}$\n\nEvidently, the rule is that", null, "${}^{\\backprime\\backprime} \\texttt{(} a \\texttt{,} b \\texttt{,} c \\texttt{)} {}^{\\prime\\prime}$ denotes the value denoted by", null, "${}^{\\backprime\\backprime} \\texttt{o} {}^{\\prime\\prime}$ if and only if exactly one of the variables", null, "$a, b, c$ has the value denoted by", null, "${}^{\\backprime\\backprime} \\texttt{|} {}^{\\prime\\prime},$ otherwise", null, "${}^{\\backprime\\backprime} \\texttt{(} a \\texttt{,} b \\texttt{,} c \\texttt{)} {}^{\\prime\\prime}$ denotes the value denoted by", null, "${}^{\\backprime\\backprime} \\texttt{|} {}^{\\prime\\prime}.$  Examining the whole series of reflective forms shows this is the general rule.\n\n• In the Entitative Interpretation", null, "$(\\mathrm{En}),$ where", null, "$\\texttt{o}$ = false and", null, "$\\texttt{|}$ = true,", null, "${}^{\\backprime\\backprime} \\texttt{(} x_1 \\texttt{,} \\ldots \\texttt{,} x_k \\texttt{)} {}^{\\prime\\prime}$ translates as “not just one of the", null, "$x_j$ is true”.\n• In the Existential Interpretation", null, "$(\\mathrm{Ex}),$ where", null, "$\\texttt{o}$ = true and", null, "$\\texttt{|}$ = false,", null, "${}^{\\backprime\\backprime} \\texttt{(} x_1 \\texttt{,} \\ldots \\texttt{,} x_k \\texttt{)} {}^{\\prime\\prime}$ translates as “just one of the", null, "$x_j$ is not true”.\n\n### 3 Responses to Animated Logical Graphs • 25\n\nThis site uses Akismet to reduce spam. Learn how your comment data is processed." ]
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http://docs.wradlib.org/en/latest/generated/wradlib.georef.rect.get_radolan_coords.html
[ "wradlib.georef.rect.get_radolan_coords(lon, lat, trig=False)\nParameters: lon (float, numpy.ndarray of floats) – longitude lat (float, numpy.ndarray of floats) – latitude trig (boolean) – if True, uses trigonometric formulas for calculation, otherwise osr transformations if False, uses osr spatial reference system to transform between projections trig is recommended to be False, however, the two ways of computation are expected to be equivalent." ]
[ null ]
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https://www.nag.com/numeric/py/nagdoc_latest/naginterfaces.library.lapacklin.ztbcon.html
[ "# naginterfaces.library.lapacklin.ztbcon¶\n\nnaginterfaces.library.lapacklin.ztbcon(norm, uplo, diag, kd, ab)[source]\n\nztbcon estimates the condition number of a complex triangular band matrix.\n\nFor full information please refer to the NAG Library document for f07vu\n\nhttps://www.nag.com/numeric/nl/nagdoc_27.3/flhtml/f07/f07vuf.html\n\nParameters\nnormstr, length 1\n\nIndicates whether or is estimated.\n\nor\n\nis estimated.\n\nis estimated.\n\nuplostr, length 1\n\nSpecifies whether is upper or lower triangular.\n\nis upper triangular.\n\nis lower triangular.\n\ndiagstr, length 1\n\nIndicates whether is a nonunit or unit triangular matrix.\n\nis a nonunit triangular matrix.\n\nis a unit triangular matrix; the diagonal elements are not referenced and are assumed to be .\n\nkdint\n\n, the number of superdiagonals of the matrix if , or the number of subdiagonals if .\n\nabcomplex, array-like, shape\n\nThe triangular band matrix .\n\nReturns\nrcondfloat\n\nAn estimate of the reciprocal of the condition number of . is set to zero if exact singularity is detected or the estimate underflows. If is less than machine precision, is singular to working precision.\n\nRaises\nNagValueError\n(errno )\n\nOn entry, error in parameter .\n\nConstraint: , or .\n\n(errno )\n\nOn entry, error in parameter .\n\nConstraint: or .\n\n(errno )\n\nOn entry, error in parameter .\n\nConstraint: or .\n\n(errno )\n\nOn entry, error in parameter .\n\nConstraint: .\n\n(errno )\n\nOn entry, error in parameter .\n\nConstraint: .\n\nNotes\n\nztbcon estimates the condition number of a complex triangular band matrix , in either the -norm or the -norm:\n\nNote that .\n\nBecause the condition number is infinite if is singular, the function actually returns an estimate of the reciprocal of the condition number.\n\nThe function computes or exactly, and uses Higham’s implementation of Hager’s method (see Higham (1988)) to estimate or .\n\nReferences\n\nHigham, N J, 1988, FORTRAN codes for estimating the one-norm of a real or complex matrix, with applications to condition estimation, ACM Trans. Math. Software (14), 381–396" ]
[ null ]
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https://www.exceldemy.com/macro-to-print-specific-sheets-in-excel/
[ "# How to Print Specific Sheets Using VBA Macro in Excel (4 Ways)\n\nIn Microsoft Excel, you will have to print sheets for various purposes. It is one of the familiar things while working with Excel. Now, we macro to print specific sheets in excel use normally our built-in print button or the print option of Excel to print sheets. However, you can also use VBA macro to print sheets in Excel. In this tutorial, you will learn to print specific sheets using VBA macro in Excel.\n\nThis tutorial will be on point with other resources and proper illustrations. So, read the whole article.\n\n## 4 Ways to Print Specific Sheets Using VBA Macro\n\nIn the following sections, we are going to provide you with two simple but effective VBA macros that you can imply in your worksheets. We recommend you learn and apply all these methods to your workbook. It will surely develop your Excel knowledge.\n\n### 1. Print Specific Sheets by Sheet Number Using VBA Macro\n\nNow, you can print multiple sheets using the sheet number. But this method will print specific sheets that are contiguous. We will use the basic PrintOut syntax.\n\nFirst, open your Visual Basic Editor. After that, insert a module. Then type the following code:\n\n``````Sub print_sheets_by_number()\n\nFor i = 3 To 6\nWorksheets(i).PrintOut\nNext i\n\nEnd Sub``````\n\nWe are using a For-Next loop here. This code will print the sheets from 3 to 6. But, remember, it will print them one by one. After running the macro, it will ask you to save your file.\n\nNow, after running the code, Excel will save these specific sheets as pdf. And, it will ask you to save the print output file:", null, "Also, it will show the following dialog box:", null, "After completing all of these, you will get your print preview.\n\nRead More: How to Print Page Number in Excel (5 Easy Ways)\n\n### 2. Macro to Print Specific Sheets by Sheet Name\n\nAnother way to print specific sheets using a macro is to print them by the sheet name. This method is pretty obvious but effective. If you have limited sheets in your Excel workbook, you can use the following code:\n\n``````Sub print_sheets_by_name()\n\nWorksheets(\"Dataset\").PrintOut\nWorksheets(\"AutoSum\").PrintOut\nWorksheets(\"MIN\").PrintOut\nWorksheets(\"SMALL\").PrintOut\n\nEnd Sub``````\n\nAs you can see, we have used the sheet name to print those multiple and specific sheets from the Excel workbook. But, this process is pretty hectic. You have to remember the sheet names.\n\n### 3. Print Specific Sheets Using Array\n\nNow, you can use an array to print specific sheets. You have to enter the sheet names in the array like the following:\n\n``````Sub print_multiple_sheets()\n\nWorksheets(Array(\"Dataset\", \"AutoSum\", \"MIN\", \"SMALL\")).PrintOut\n\nEnd Sub``````\n\n### 4. Print Specific Sheets by a Button in Excel\n\nNow, another way to print specific sheets is to create a print button in Excel. First, we will create a button. After that, we will insert a code for that button. If you click that button, it will print specific sheets. Why is this helpful? We will use this because it is hazard-free. Just one click will do all of these.\n\n📌 Steps\n\n• First, go to the Developer If you don’t have it, enable the developer tab in the ribbon.\n• Now, from the Controls group, click on Insert.", null, "• After that, from the ActiveX Controls, click on the Button", null, "• Now, place the button on your worksheet.", null, "• To change the name of the button, right-click on the button. After that, click on Properties.", null, "• From the Properties dialog box, change the caption of the button. It will change the name of the button.", null, "• As you can see, our print button is ready.", null, "• Now, double click on the button while Design Mode is on. You will see the following VBA code.", null, "• Now, type the following code:\n``````Private Sub CommandButton1_Click()\n\nActiveSheet.PrintOut\n\nEnd Sub``````\n\nThis code will print the active sheet that you are working on. Now, from here, you can follow either of the two ways:\n\n• Copy the same button and paste it into all the worksheets. In this way, you will be able to print any sheet you want.\n• Or you can use the macro of the previous two methods and use them in this button. In this way, you will print specific sheets with one button.\n\n## Other Useful Macros to Print Sheets in Excel\n\nIn the following sections, we are going to provide you with some very essential VBA macros that you can use in a lot of scenarios. You can use all of these codes in your workbook. It will work nicely. Let’s get into it.\n\n### 1. Print Specific Sheets into Single Page\n\nThe following code will print the sheet “Dataset” exactly one page wide and tall.\n\n``````Sub print_single_page()\n\nWith Worksheets(\"Dataset\").PageSetup\n.Zoom = False\n.FitToPagesTall = 1\n.FitToPagesWide = 1\nEnd With\n\nEnd Sub``````\n\n### 2. Print Sheets with Comments\n\nThe following code will print sheets with comments:\n\n``````Sub print_sheets_with_comments()\n\nApplication.DisplayCommentIndicator = xlCommentAndIndicator\n\nWith ActiveSheet\n.PrintOut\nEnd With\n\nEnd Sub``````\n\n### 3. Macro to Print Hidden Sheets in Excel\n\nIf you have some specific hidden sheets in your Excel workbook, use the following code to print them:\n\n``````Sub print_hidden_sheet()\n\nDim current_visible As Long\nDim working_sheet As Worksheet\n\nFor Each working_sheet In ActiveWorkbook.Worksheets\nWith working_sheet\ncurrent_visible = .Visible\nIf current_visible >= 0 Then\n.Visible = xlSheetVisible\n.PrintOut\n.Visible = current_visible\nEnd If\nEnd With\nNext working_sheet\n\nEnd Sub``````\n\n### 4. Macro to Print both Hidden and Visible Sheets\n\nBy the following code, you can print all the hidden and visible sheets:\n\n``````Sub print_hidden_visible_sheet()\n\nDim current_visible As Long\nDim working_sheet As Worksheet\n\nFor Each working_sheet In ActiveWorkbook.Worksheets\nWith working_sheet\ncurrent_visible = .Visible\n.Visible = xlSheetVisible\n.PrintOut\n.Visible = current_visible\nEnd With\nNext working_sheet\n\nEnd Sub``````\n\n### 5. Print Multiple Excel Worksheets with Macro\n\nWe have already shown the code above. Use the sheet names in the array to print multiple sheets in Excel:\n\n``````Sub print_multiple_sheets()\n\nWorksheets(Array(\"Dataset\", \"AutoSum\", \"MIN\", \"SMALL\")).PrintOut\n\nEnd Sub``````\n\n### 6. Print All Worksheets\n\nTo print all the worksheets of your Excel workbook, use the following code:\n\n``````Sub print_all_sheets()\n\nWorksheets.PrintOut\n\nEnd Sub``````\n\n### 7. Print Entire Workbook\n\nTo print the whole workbook, follow any the of the following VBA codes:\n\nUsing ActiveWorkbook:\n\n``````Sub print_active_workbook()\n\nActiveWorkbook.PrintOut\n\nEnd Sub``````\n\nUsing ThisWorkbook:\n\n``````Sub print_this_workbook()\n\nThisWorkbook.PrintOut\n\nEnd Sub``````\n\n### 8. VBA Code to Print a Specific Sheet\n\nMention the sheet name to print a specific sheet from your workbook.\n\n``````Sub print_specific_sheet()\n\nSheets(\"Dataset\").PrintOut\n\nEnd Sub``````\n\n### 9. Print Active Sheet in Excel\n\nPrint the active sheet using the following code:\n\n``````Sub print_active_sheet()\n\nActiveSheet.PrintOut\n\nEnd Sub``````\n\n### 10.  Print Selected Sheets\n\nBy the following code, you can print the specifically selected worksheets:\n\n``````Sub print_selected_sheet()\n\nActiveWindow.SelectedSheets.PrintOut\n\nEnd Sub``````\n\n### 11. Print a Selection from a Sheet\n\nIf you want to print a specific selection, use the following code:\n\n``````Sub print_selection()\n\nSelection.PrintOut\n\nEnd Sub``````\n\n### 12. Excel VBA to Print a Range\n\nThe following code will help you to print a specific range from a worksheet.\n\n``````Sub print_range()\n\nRange(\"B4:C11\").PrintOut\n\nEnd Sub``````\n\n### 13. Print Preview\n\nTo print a preview, use the following code:\n\n``````Sub print_preview()\n\nActiveSheet.PrintOut preview:=True\n\nEnd Sub``````\n\n### 14. Print Specific Sheets by Taking User Input\n\nNow, you can take the sheet number or sheet name as input from the user. The following code will do that with ease.\n\n#### 14.1 Take Sheet Number as User Input\n\nThe following code will take the sheet number as input from the user:\n\n``````Sub print_user_input_number()\n\nDim sheet_number As Integer\n\nsheet_number = Application.InputBox(\"Enter Sheet Number to Print:\")\nWorksheets(sheet_number).PrintOut\n\nEnd Sub``````\n\n#### 14.2 Take Sheet Name as User Input\n\nYou can print a specific sheet by taking the sheet name as user input:\n\n``````Sub print_user_input_name()\n\nDim sheet_name As String\n\nsheet_name = Application.InputBox(\"Enter Sheet Name to Print:\")\nWorksheets(sheet_name).PrintOut\n\nEnd Sub``````\n\n### 15. Excel VBA to Print Preview a Selected Range in Excel\n\nThe following code will give you the preview, along with the print option:\n\n``````Sub print_preview_selected_range()\n\nSheets(\"Dataset\").Range(\"B4:C11\").PrintPreview\n\nEnd Sub``````\n\n## 💬 Things to Remember\n\n✎ Here, the macros are based on our practice workbook. If you are using a different workbook, change the sheet name, number, and range.\n\n## Conclusion\n\nTo conclude, I hope this tutorial has provided you with a piece of useful knowledge about the Date in VBA codes. We recommend you learn and apply all these instructions to your dataset. Download the practice workbook and try these yourself. Also, feel free to give feedback in the comment section. Your valuable feedback keeps us motivated to create tutorials like this.\n\nDon’t forget to check our website Exceldemy.com for various Excel-related problems and solutions.\n\nKeep learning new methods and keep growing!\n\n## Related Articles", null, "#### Shanto\n\nHello! I am Shanto. An Excel & VBA Content Developer. My goal is to provide our readers with great tutorials on various Excel-related problems. I hope our easy but effective tutorials will enrich your knowledge. I have completed my BSc in Computer Science & Engineering from Daffodil International University. Working with data was always my passion. Love to work with data, analyze those, and find patterns. Also, love to research. Always look for challenges to keep me growing.\n\nWe will be happy to hear your thoughts", null, "" ]
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https://bitcoinj.org/javadoc/0.16.1/org/bitcoinj/crypto/LazyECPoint.html
[ "## Class LazyECPoint\n\n• java.lang.Object\n• org.bitcoinj.crypto.LazyECPoint\n\n• ```public class LazyECPoint\nextends java.lang.Object```\nA wrapper around ECPoint that delays decoding of the point for as long as possible. This is useful because point encode/decode in Bouncy Castle is quite slow especially on Dalvik, as it often involves decompression/recompression.\n• ### Constructor Summary\n\nConstructors\nConstructor Description\n```LazyECPoint​(org.bouncycastle.math.ec.ECCurve curve, byte[] bits)```\nConstruct a LazyECPoint from a public key.\n```LazyECPoint​(org.bouncycastle.math.ec.ECPoint point, boolean compressed)```\nConstruct a LazyECPoint from an already decoded point.\n• ### Method Summary\n\nAll Methods\nModifier and Type Method Description\n`org.bouncycastle.math.ec.ECPoint` `add​(org.bouncycastle.math.ec.ECPoint b)`\n`LazyECPoint` `compress()`\nReturns a compressed version of this elliptic curve point.\n`LazyECPoint` `decompress()`\nReturns a decompressed version of this elliptic curve point.\n`boolean` `equals​(java.lang.Object o)`\n`boolean` `equals​(org.bouncycastle.math.ec.ECPoint other)`\n`org.bouncycastle.math.ec.ECPoint` `get()`\n`org.bouncycastle.math.ec.ECFieldElement` `getAffineXCoord()`\n`org.bouncycastle.math.ec.ECFieldElement` `getAffineYCoord()`\n`org.bouncycastle.math.ec.ECCurve` `getCurve()`\n`org.bouncycastle.math.ec.ECPoint` `getDetachedPoint()`\n`byte[]` `getEncoded()`\n`byte[]` `getEncoded​(boolean compressed)`\n`org.bouncycastle.math.ec.ECFieldElement` `getX()`\n`org.bouncycastle.math.ec.ECFieldElement` `getXCoord()`\n`org.bouncycastle.math.ec.ECFieldElement` `getY()`\n`org.bouncycastle.math.ec.ECFieldElement` `getYCoord()`\n`org.bouncycastle.math.ec.ECFieldElement` `getZCoord​(int index)`\n`org.bouncycastle.math.ec.ECFieldElement[]` `getZCoords()`\n`int` `hashCode()`\n`boolean` `isCompressed()`\n`boolean` `isInfinity()`\n`boolean` `isNormalized()`\n`boolean` `isValid()`\n`org.bouncycastle.math.ec.ECPoint` `multiply​(java.math.BigInteger k)`\n`org.bouncycastle.math.ec.ECPoint` `negate()`\n`org.bouncycastle.math.ec.ECPoint` `normalize()`\n`org.bouncycastle.math.ec.ECPoint` `scaleX​(org.bouncycastle.math.ec.ECFieldElement scale)`\n`org.bouncycastle.math.ec.ECPoint` `scaleY​(org.bouncycastle.math.ec.ECFieldElement scale)`\n`org.bouncycastle.math.ec.ECPoint` `subtract​(org.bouncycastle.math.ec.ECPoint b)`\n`org.bouncycastle.math.ec.ECPoint` `threeTimes()`\n`org.bouncycastle.math.ec.ECPoint` `timesPow2​(int e)`\n`org.bouncycastle.math.ec.ECPoint` `twice()`\n`org.bouncycastle.math.ec.ECPoint` `twicePlus​(org.bouncycastle.math.ec.ECPoint b)`\n• ### Methods inherited from class java.lang.Object\n\n`clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait`\n• ### Constructor Detail\n\n• #### LazyECPoint\n\n```public LazyECPoint​(org.bouncycastle.math.ec.ECCurve curve,\nbyte[] bits)```\nConstruct a LazyECPoint from a public key. Due to the delayed decoding of the point the validation of the public key is delayed too, e.g. until a getter is called.\nParameters:\n`curve` - a curve the point is on\n`bits` - public key bytes\n• #### LazyECPoint\n\n```public LazyECPoint​(org.bouncycastle.math.ec.ECPoint point,\nboolean compressed)```\nConstruct a LazyECPoint from an already decoded point.\nParameters:\n`point` - the wrapped point\n`compressed` - true if the represented public key is compressed\n• ### Method Detail\n\n• #### compress\n\n`public LazyECPoint compress()`\nReturns a compressed version of this elliptic curve point. Returns the same point if it's already compressed. See the `ECKey` class docs for a discussion of point compression.\n• #### decompress\n\n`public LazyECPoint decompress()`\nReturns a decompressed version of this elliptic curve point. Returns the same point if it's already compressed. See the `ECKey` class docs for a discussion of point compression.\n• #### get\n\n`public org.bouncycastle.math.ec.ECPoint get()`\n• #### getEncoded\n\n`public byte[] getEncoded()`\n• #### getDetachedPoint\n\n`public org.bouncycastle.math.ec.ECPoint getDetachedPoint()`\n• #### isInfinity\n\n`public boolean isInfinity()`\n• #### timesPow2\n\n`public org.bouncycastle.math.ec.ECPoint timesPow2​(int e)`\n• #### getYCoord\n\n`public org.bouncycastle.math.ec.ECFieldElement getYCoord()`\n• #### getZCoords\n\n`public org.bouncycastle.math.ec.ECFieldElement[] getZCoords()`\n• #### isNormalized\n\n`public boolean isNormalized()`\n• #### isCompressed\n\n`public boolean isCompressed()`\n• #### multiply\n\n`public org.bouncycastle.math.ec.ECPoint multiply​(java.math.BigInteger k)`\n• #### subtract\n\n`public org.bouncycastle.math.ec.ECPoint subtract​(org.bouncycastle.math.ec.ECPoint b)`\n• #### isValid\n\n`public boolean isValid()`\n• #### scaleY\n\n`public org.bouncycastle.math.ec.ECPoint scaleY​(org.bouncycastle.math.ec.ECFieldElement scale)`\n• #### getXCoord\n\n`public org.bouncycastle.math.ec.ECFieldElement getXCoord()`\n• #### scaleX\n\n`public org.bouncycastle.math.ec.ECPoint scaleX​(org.bouncycastle.math.ec.ECFieldElement scale)`\n• #### equals\n\n`public boolean equals​(org.bouncycastle.math.ec.ECPoint other)`\n• #### negate\n\n`public org.bouncycastle.math.ec.ECPoint negate()`\n• #### threeTimes\n\n`public org.bouncycastle.math.ec.ECPoint threeTimes()`\n• #### getZCoord\n\n`public org.bouncycastle.math.ec.ECFieldElement getZCoord​(int index)`\n• #### getEncoded\n\n`public byte[] getEncoded​(boolean compressed)`\n\n`public org.bouncycastle.math.ec.ECPoint add​(org.bouncycastle.math.ec.ECPoint b)`\n• #### twicePlus\n\n`public org.bouncycastle.math.ec.ECPoint twicePlus​(org.bouncycastle.math.ec.ECPoint b)`\n• #### getCurve\n\n`public org.bouncycastle.math.ec.ECCurve getCurve()`\n• #### normalize\n\n`public org.bouncycastle.math.ec.ECPoint normalize()`\n• #### getY\n\n`public org.bouncycastle.math.ec.ECFieldElement getY()`\n• #### twice\n\n`public org.bouncycastle.math.ec.ECPoint twice()`\n• #### getAffineYCoord\n\n`public org.bouncycastle.math.ec.ECFieldElement getAffineYCoord()`\n• #### getAffineXCoord\n\n`public org.bouncycastle.math.ec.ECFieldElement getAffineXCoord()`\n• #### getX\n\n`public org.bouncycastle.math.ec.ECFieldElement getX()`\n• #### equals\n\n`public boolean equals​(java.lang.Object o)`\nOverrides:\n`equals` in class `java.lang.Object`\n• #### hashCode\n\n`public int hashCode()`\nOverrides:\n`hashCode` in class `java.lang.Object`" ]
[ null ]
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https://donaanacosta.com/qa/what-number-multiplied-by-itself-gives-2809.html
[ "", null, "# What Number Multiplied By Itself Gives 2809?\n\n## Is 77 a triangular number?\n\n0, 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66, 78, 91, 105, 120, 136, 153, 171, 190, 210, 231, 253, 276, 300, 325, 351, 378, 406, 435, 465, 496, 528, 561, 595, 630, 666….\n\n## Which number multiplied by itself gives 64?\n\n88 is the number multiplied by itself is 64.\n\n## What is 4 multiplied by itself?\n\nWhat is the “Exponent 4” of a number? The “Exponent 4” of a number is the number multiplied by itself 4 times. It is written as number4. Saying “3 to the exponent 4” or 34 is the same as saying 3 times 3 times 3 times 3 (equals 81).\n\n## What number multiplied by itself gives 121?\n\n11√121 is, as we all know, 11. I think together with the number pyramid that’s quite a clue.\n\n## IS 500 a perfect square?\n\nIs 500 a perfect square number? A number is a perfect square (or a square number) if its square root is an integer; that is to say, it is the product of an integer with itself. … Thus, the square root of 500 is not an integer, and therefore 500 is not a square number.\n\n## What can equal 48?\n\nAnswer and Explanation: The factor pairs of the number 48 are: 1 x 48, 2 x 24, 3 x 16, 4 x 12, and 6 x 8. When you multiply each of these factor pairs together, you get 48….\n\n## What number when multiplied by itself is 11 greater than the preceding number when it is multiplied by itself?\n\nSo, using that formula, you can just put 2x – 1 = 11, giving x = 6. Let the number be x. Thus, the number is 6.\n\n## What are the triangular numbers from 1 to 100?\n\nThe triangular numbers up to 100 are 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66, 78, 91 — so what’s next? Perfect Numbers These are the numbers which equal the sum of all of their smaller factors. They are few and far between — in fact, nobody knows how many there are. Only 47 perfect numbers are currently known.\n\n## Which number multiplied by itself gives 12345678987654321?\n\n3 1’s gives 12321. so to get 12345678987654321 we need to get square of 9 1’s(111,111,111).\n\n## What number multiplied by itself gives 100?\n\nWhat number, when multiplied by itself, gives 100? The answer is both 10 and −10. The radical symbol for square roots is √0. It is used to represent the unique non-negative square root of a number, also called the principal square root.\n\n## What is the 8th triangular number?\n\nWhen we add these all together, our eighth triangular number is 36. This means that the eighth equilateral triangle in the sequence has 36 dots.\n\n## Which number multiplied by itself gives 625?\n\n25 x 25 = 625 What number multiplied by itself equals 626?\n\n## What multiplied by itself equals 196?\n\n14 x 14 = 196 What number multiplied by itself equals 197?\n\n## What times what equals 12345678987654321?\n\nBecause 111111111 times 111111111 equals 12345678987654321 according to the laws of multiplication for real numbers.\n\n## What is 4 by the power of 5?\n\nAnswer and Explanation: What is 5 to the 4th power? That would be the same as 5 multiplied by itself 4 times. In other words, it would be: 5 x 5 x 5 x 5.\n\n## What numbers are powers of 3?\n\nIn the powers of 3 table, the ones digits form the repeating pattern 3,9,7,1,3,9,7,1,… .\n\n## When a number is multiplied by itself?\n\nIn mathematics, we call multiplying a number by itself “squaring” the number. We call the result of squaring a whole number a square or a perfect square. A perfect square is any number that can be written as a whole number raised to the power of 2. For example, 9 is a perfect square.\n\n## What is a square of 12?\n\n“Is it possible to recreate this up to 12×12?”0 Squared=09 Squared=8110 Squared=10011 Squared=12112 Squared=1448 more rows\n\n## What number multiplied by itself gives 144 as product?\n\nA square roots calculator finds the number that, when multiplied by itself, would give you the number you are starting out with. For example, the square root of 144 is 12, because 12 times 12 equals 144. Of course, -12 times -12 is also 144. Therefore, every number actually has two square roots.\n\n## Why is 1 a triangular number?\n\nTriangular numbers have that name because, if drawn as dots they can form a triangle. But 1 is just a single dot, so it can’t be a triangular number, can it???" ]
[ null, "https://mc.yandex.ru/watch/66677209", null ]
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https://www.greenlighttestprep.com/module/gre-quantitative-comparison/video/1099
[ "# Lesson: QC Strategy - Looking for Equality\n\n## Comment on QC Strategy - Looking for Equality\n\n### For the last example where\n\nFor the last example where Quantity A had (x-16)(x-7)(x-4) and where Quantity B had (x-9)(x-11)(x-7); why didn't you divide both Quantities by (x-7) since it was present in both cases, and then performed \"FOIL\" to better cancel out x2 and -20x from both sides leaving you with 64 for Quantity A and 99 for Quantity B?\n\nI understand this video is about looking for Equality, but in regards to Equality; (in pausing the video before watching the explanation), I saw what both sides had equally in common (which was (x-7) being multiplied by both sides).\n\nWhy then wasn't B the right answer if we used your Matching Operations Strategy verses plugging in possible answers for x (especially when in the Matching Operations' Video the last example where QA was 2x and QB was 3x, that the answer wasn't B because we couldn't be sure of what X was; just like how we're unsure of what x could be in this particular example); wouldn't it be better to try to cancel out all the variables if possible (using the Matching Operations Strategy) to derive to the correct answer?\n\nThank you in advance; I am truly appreciative.", null, "### You need to be very careful\n\nYou need to be very careful when dividing both quantities by a variable or an expression involving variables. First off, you might be dividing both quantities by zero, which can be problematic.\nTo illustrate what I mean, consider what would happen if Quantity A was (0)(3) and Quantity B was (0)(2). Clearly, the two quantities are equal. However, if we divide both sides by 0, we \"seemingly\" get Quantity A: 3 and Quantity B: 2.\nThat's the risk you run by dividing both quantities by (x-7) since it's possible that you could be dividing both quantities by 0.\nAlso, if you watch the matching operations video (https://www.greenlighttestprep.com/module/gre-quantitative-comparison/vi...), you'll see that we cannot divide both quantities by a negative value. How can we be certain that (x-7) is not a negative value.\nFor these reasons, we can't simply divide both quantities by (x-7)\nI hope that helps.\n\n### Yes it helps alot, thank you\n\nYes it helps alot, thank you so much :)\n\n### In the previous video, it\n\nIn the previous video, it said that if you use different \"nice\" numbers there is a chance that even though in the first few answers both quantities are equal, there is still a chance that they are not, in this video, if you find two conflicting results in the beginning is there no need to keep testing?", null, "### Yes, that's the downside of\n\nYes, that's the downside of testing numbers. If you plug in different numbers but keep getting the SAME result (e.g., on the first test you find that quantity A and quantity B are equal, and on the second test you find that quantity A and quantity B are equal), it's still possible that the two quantities are not always equal. So, you CAN'T be absolutely certain the answer is C.\n\nHowever, if you plug in two different sets of values and get CONFLICTING results (e.g., on the first test you find that quantity A and quantity B are equal, and on the second test you find that quantity A is greater than quantity B), then you can be CERTAIN that the answer is D.\n\n### These strategies are so\n\nThese strategies are so supremely awesome! I'm so totally in love with your videos right now!", null, "### That's great to hear. Thanks\n\nThat's great to hear. Thanks for taking the time to say that!\n\n### In the last example, I simply\n\nIn the last example, I simply eliminated the common binomial (x-7) and then plugged in a value for X which made the calculations faster as I was left with two binomials on each side as opposed to three. Not sure why that wasn't done.", null, "### Great question!\n\nGreat question!\n\nThe strategy you describe will get you in trouble. To understand why, let's examine what you mean by \"eliminate.\" Presumably, you eliminated (x-7) by dividing each side by (x-7). The problem with this strategy is that we don't know the value of x. So, (x-7) can be positive, negative, or zero, and each of these cases alters the outcome when we divide by (x-7).\n\nFor example, what if the two quantities were as follows:\nQuantity A: 3(x-7)\nQuantity B: 2(x-7)\n\nIf we divide both quantities by (x-7), we get:\nQuantity A: 3\nQuantity B: 2\nSo, is the correct answer B?\n\nNo, the correct answer is D. If we plug x = 1 into 3(x-7) and 2(x-7), we see that Quantity A is greater. If we plug plug x = 8 into 3(x-7) and 2(x-7), we see that Quantity B is greater. If we plug in x = 7, the quantities are equal.\n\nFor more on acceptable operations you can perform on each quantity, see https://www.greenlighttestprep.com/module/gre-quantitative-comparison/vi...\n\n### Last example we can solve by\n\nLast example we can solve by following way,\na=(x-16)(x-7)(x-4),b=(x-9)(x-11)(x-7)\na=(x-16)(x-4),b=(x-9)(x-11)\na=x2-20x+64,b=x2-20x+99\na=x2+64,b=x2+99\nThen B must be greater,So by this process how the answer will be D,Please Sir...", null, "### There's a problem with your\n\nThere's a problem with your second step where you eliminated the (x-7) from both quantities. Presumably, you divided both quantities by (x-7)\n\nSince we don't know the value of x, it's possible that you have inadvertently divided both quantities by zero, which will negatively impact your solution.\n\nAlso, since we don't know the value of x, it may be the case that (x - 7) is negative, and we have a rule about dividing both quantities by a negative value (for more on this, see: https://www.greenlighttestprep.com/module/gre-quantitative-comparison/vi...\n\nConsider this example:\nQUANTITY A: 3x\nQUANTITY B: 2x\nIf x = 0, then the two quantities are EQUAL\nIf x = 1, then quantity A is greater\nIf x = -1, then quantity B is greater\nSo, the correct answer here is D.\n\nNow, let's see what happens if we break our rule and divide both sides by x.\nWe get:\nQUANTITY A: 3\nQUANTITY B: 2\nThis would SUGGEST that the correct answer is A, but this is not the case.\n\nDoes that help?\n\n### Best ever explanation\n\nBest ever explanation", null, "Thanks!\n\n### U r an awesome teacher.I like\n\nU r an awesome teacher.I like the way u teach.", null, "### Thanks for the kind words,\n\nThanks for the kind words, Seema!\n\n### Quantity A : |x + y|\n\nQuantity A : |x + y|\nQuantity B : |x| + |y|\nIn this test you did try different values for x and y ? why ? why we did not choose same value like 1 and then plug in number ? why x= 1 & y =2 but at first step we did plug in x= 0 and y=0 ?\nI am a little confuse!!!! because I thought we should plugin these type of numbers :\n0, 1, -1, 1/2, -1/2, 10,-10 but same for both variable!!! not different for each!!", null, "There's no need (or requirement) to choose the same values for each variable. If anything, choosing the same values would make the \"plugging in values\" strategy much less effective.\n\nFor example, if we kept choosing identical values for x and y for the above questions, we'd incorrectly conclude that the two quantities are always EQUAL.\n\nDoes that help?\n\nCheers,\nBrent\n\nyes" ]
[ null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null, "https://www.greenlighttestprep.com/sites/default/files/styles/thumbnail/public/pictures/picture-1-1600118168.png", null ]
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https://zbmath.org/?q=an:1196.65031
[ "# zbMATH — the first resource for mathematics\n\nAn approach for determining the matrix of limiting state probabilities in discrete Markov processes. (English) Zbl 1196.65031\nSummary: A new approach for determining the matrix of limiting state probabilities in Markov processes is proposed and a polynomial time algorithm for calculating this matrix is presented. The computational complexity of the algorithm is $$O(n^{4})$$ where $$n$$ is the number of the states of the discrete system.\n\n##### MSC:\n 65C40 Numerical analysis or methods applied to Markov chains 60J22 Computational methods in Markov chains 90C39 Dynamic programming 90C40 Markov and semi-Markov decision processes 65Y20 Complexity and performance of numerical algorithms\nFull Text:" ]
[ null ]
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https://ounces-to-grams.appspot.com/pl/430-uncja-na-gram.html
[ "Ounces To Grams\n\n# 430 oz to g430 Ounce to Grams\n\noz\n=\ng\n\n## How to convert 430 ounce to grams?\n\n 430 oz * 28.349523125 g = 12190.2949437 g 1 oz\nA common question is How many ounce in 430 gram? And the answer is 15.1678036383 oz in 430 g. Likewise the question how many gram in 430 ounce has the answer of 12190.2949437 g in 430 oz.\n\n## How much are 430 ounces in grams?\n\n430 ounces equal 12190.2949437 grams (430oz = 12190.2949437g). Converting 430 oz to g is easy. Simply use our calculator above, or apply the formula to change the length 430 oz to g.\n\n## Convert 430 oz to common mass\n\nUnitMass\nMicrogram12190294943.8 µg\nMilligram12190294.9437 mg\nGram12190.2949437 g\nOunce430.0 oz\nPound26.875 lbs\nKilogram12.1902949438 kg\nStone1.9196428571 st\nUS ton0.0134375 ton\nTonne0.0121902949 t\nImperial ton0.0119977679 Long tons\n\n## What is 430 ounces in g?\n\nTo convert 430 oz to g multiply the mass in ounces by 28.349523125. The 430 oz in g formula is [g] = 430 * 28.349523125. Thus, for 430 ounces in gram we get 12190.2949437 g.\n\n## 430 Ounce Conversion Table", null, "## Alternative spelling\n\n430 Ounces to g, 430 Ounces in g, 430 oz in g, 430 Ounces to Gram, 430 Ounces in Gram, 430 Ounce to Gram, 430 Ounce to g, 430 Ounce in g," ]
[ null, "https://ounces-to-grams.appspot.com/image/430.png", null ]
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https://assignmentshark.com/blog/sample-of-a-python-user-defined-function/
[ "# Sample of a Python User Defined Function\n\nIn the following sample, we are going to talk about Python user defined function. A function in Python is an object that takes arguments and returns a value. A function is a block of organized, reusable code that is used to perform a specific task. Functions provide better modularity of the application and significantly increase the level of code reuse. There are some rules for creating functions in Python. You will learn about these rules if you read through the following sample.\n\nWe advise all students who are starting to study programming to read it through. Also, you can find examples of completed assignments in other disciplines. After you read our sample, you will be able to work with user defined functions in Python. You will see that such functions can be easily created by you. So, don’t wait anymore and read the following example – it will surely be helpful for you.\n\nPython Functions\n\nIn this particular paper we are going to discuss general structure of user-defined functions in Python, along with the overview of the most interesting built-in ones.\n\nUser-defined function\n\nIn Python, in order to define some function, you just need to write ​def ​and the name of the function. It is very simple. The only thing that should be followed strictly is indentation, because in Python there are no braces that specify the beginning and ending of the method. You just need to keep your code in the appropriate place to avoid errors.\n\n```def simpleOne(val):\nfor i in range(val):\nprint(\"It's a new day\")\n\nsimpleOne(​4​)\n```\n\nOutput:\n\n```\"It's a new day\"\n\"It's a new day\"\n\"It's a new day\"\n\"It's a new day\"\n```\n\nThis program just outputs string for as many times as you specify in its parameter.\n\nAs you see, the function is called by simply writing its name with the parameter if there is one.\n\nBuilt-in functions\n\nThe first built-in function that appears when learning Python is ​print(​). ​It simply outputs the contents of what is inside this method. Even the example above uses it.\n\nIn the next example, two functions are used: ​list()​​ and ​zip()​. ​The first returns the list of separate items depending on what is in the arguments list in the parentheses. Zip() method combines items from several tuples by their index.\n\n```a = ['Sam', 'Dean']\nb = [1992, 2013]\nc = [1, 2, 3, 4, 5]\nprint(list(zip(a, b, c)))\n```\n\nOutput:\n\n```[('Sam', 1992, 1), ('Dean', 2013, 2)]\n```\n\nIn this example we are integrating all the existing tuples, and since there can only be two mutual pairs, you can observe them in output.\n\n```a = ['Sam', 'Dean']\nb = [1992, 2013]\nc = [1, 2, 3, 4, 5]\nfor l,m in zip(a, b):\nd[l]=m\nform = l + \":{ \" + l + \"}\"\nprint(form.format(**d))\n```\n\nOutput:\n\n```\"Sam: 1992\"\n\"Dean: 2013\"\n```\n\nIn the next example several functions are used at the same time: ​input()​, ​split()​,​ range()​, len()​.\n\nInput method is for accepting user types in console. Split function is for separating some string with the specified in the arguments symbol or character, thus creating more independent units. Range(), in this example, is used for setting the upper limit of loops. Len() returns the size of some variable that is in the parentheses.\n\nAll in all, this small program receives input from the user, separates it by blank space, and then outputs each individual value on the new line.\n\n```print(\"Enter some words and numbers\")\ns = input()\nsome = s.split(\" \")\nfor i in range((len(some))):\nprint(some[i])\n```\n\nYou might wonder what is the data type of that variable ‘some’. You can guess or use the function type() to find out for sure. So, if we add one line of code to the above line, what we receive is:", null, "```print(\"The data type of this is \", type(some))" ]
[ null, "https://assignmentshark.com/blog/wp-content/uploads/2019/04/python-output1.jpg", null ]
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https://wikimili.com/en/Geometric_terms_of_location
[ "# Geometric terms of location\n\nLast updated\n\nGeometric terms of location describe directions or positions relative to the shape of an object. These terms are used in descriptions of engineering, physics, and other sciences, as well as ordinary day to day discourse.\n\nThough these terms by themselves may be somewhat ambiguous, they are usually used in a context in which their meaning is clear. For example, when referring to a drive shaft it is clear what is meant by axial or radial directions. Or, in a free body diagram, one may similarly infer a sense of orientation by the forces or other vectors represented.\n\n## Examples\n\nCommon geometric terms of location are:\n\n• Axial – along the center of a round body, or the axis of rotation of a body\n• Azimuthal or circumferential – following around a curve or circumference of an object. For instance, the pattern of cells in Taylor–Couette flow varies along the azimuth of the experiment.\n• Collinear - in the same line\n• Degree of freedom - axis direction, see six degrees of freedom\n• Elevation - along a curve from a point on the horizon to the zenith, directly overhead.\n• Depression – along a curve from a point on the horizon to the nadir, directly below.\n• Lateral – spanning the width of a body. The distinction between width and length may be unclear out of context.\n• Lineal – following along a given path. The shape of the path is not necessarily straight (compare to linear). For instance, a length of rope might be measured in lineal meters or feet. See arc length.\n• Longitudinal – spanning the length of a body.\n• Orthogonal – at right angles to a line, or more generally, on a different axis.\n• Parallel - in the same direction\n• Perpendicular - at right angles to, synonym to orthogonal\n• Radial – along a direction pointing along a radius from the center of an object, or perpendicular to a curved path.\n• Tangential – intersecting a curve at a point and parallel to the curve at that point.\n• Transverse – orthogonal to a specified direction, such as a particle trajectory or an axis of rotation.\n• Vertical – spanning the length of a body.\n\n## Related Research Articles", null, "In plane geometry, an angle is the figure formed by two rays, called the sides of the angle, sharing a common endpoint, called the vertex of the angle. Angles formed by two rays lie in a plane, but this plane does not have to be a Euclidean plane. Angles are also formed by the intersection of two planes in Euclidean and other spaces. These are called dihedral angles. Angles formed by the intersection of two curves in a plane are defined as the angle determined by the tangent rays at the point of intersection. Similar statements hold in space, for example, the spherical angle formed by two great circles on a sphere is the dihedral angle between the planes determined by the great circles.", null, "In mathematics, a spherical coordinate system is a coordinate system for three-dimensional space where the position of a point is specified by three numbers: the radial distance of that point from a fixed origin, its polar angle measured from a fixed zenith direction, and the azimuthal angle of its orthogonal projection on a reference plane that passes through the origin and is orthogonal to the zenith, measured from a fixed reference direction on that plane. It can be seen as the three-dimensional version of the polar coordinate system.", null, "A rotation is a circular movement of an object around a center of rotation. A three-dimensional object can always be rotated around an infinite number of imaginary lines called rotation axes. If the axis passes through the body's center of mass, the body is said to rotate upon itself, or spin. A rotation about an external point, e.g. the Earth about the Sun, is called a revolution or orbital revolution, typically when it is produced by gravity. The axis is called a pole.", null, "Polarization is a property applying to transverse waves that specifies the geometrical orientation of the oscillations. In a transverse wave, the direction of the oscillation is perpendicular to the direction of motion of the wave. A simple example of a polarized transverse wave is vibrations traveling along a taut string (see image); for example, in a musical instrument like a guitar string. Depending on how the string is plucked, the vibrations can be in a vertical direction, horizontal direction, or at any angle perpendicular to the string. In contrast, in longitudinal waves, such as sound waves in a liquid or gas, the displacement of the particles in the oscillation is always in the direction of propagation, so these waves do not exhibit polarization. Transverse waves that exhibit polarization include electromagnetic waves such as light and radio waves, gravitational waves, and transverse sound waves in solids.", null, "Orbital inclination measures the tilt of an object's orbit around a celestial body. It is expressed as the angle between a reference plane and the orbital plane or axis of direction of the orbiting object.", null, "In elementary geometry, the property of being perpendicular (perpendicularity) is the relationship between two lines which meet at a right angle. The property extends to other related geometric objects.", null, "In astronomy, an analemma is a diagram showing the position of the Sun in the sky, as seen from a fixed location on Earth at the same mean solar time, as that position varies over the course of a year. The diagram will resemble the figure 8. Globes of Earth often display an analemma.", null, "A gear or cogwheel is a rotating machine part having cut teeth or, in the case of a cogwheel, inserted teeth, which mesh with another toothed part to transmit torque. Geared devices can change the speed, torque, and direction of a power source. Gears almost always produce a change in torque, creating a mechanical advantage, through their gear ratio, and thus may be considered a simple machine. The teeth on the two meshing gears all have the same shape. Two or more meshing gears, working in a sequence, are called a gear train or a transmission. A gear can mesh with a linear toothed part, called a rack, producing translation instead of rotation.", null, "A circle of latitude on Earth is an abstract east–west circle connecting all locations around Earth at a given latitude.", null, "In mathematics and physics, the right-hand rule is a common mnemonic for understanding orientation of axes in three-dimensional space.\n\nIn physics, circular motion is a movement of an object along the circumference of a circle or rotation along a circular path. It can be uniform, with constant angular rate of rotation and constant speed, or non-uniform with a changing rate of rotation. The rotation around a fixed axis of a three-dimensional body involves circular motion of its parts. The equations of motion describe the movement of the center of mass of a body.", null, "Rotational symmetry, also known as radial symmetry in biology, is the property a shape has when it looks the same after some rotation by a partial turn. An object's degree of rotational symmetry is the number of distinct orientations in which it looks exactly the same for each rotation.", null, "In classical geometry, a radius of a circle or sphere is any of the line segments from its center to its perimeter, and in more modern usage, it is also their length. The name comes from the Latin radius, meaning ray but also the spoke of a chariot wheel. The plural of radius can be either radii or the conventional English plural radiuses. The typical abbreviation and mathematical variable name for radius is r. By extension, the diameter d is defined as twice the radius:\n\nIn optics a ray is an idealized model of light, obtained by choosing a line that is perpendicular to the wavefronts of the actual light, and that points in the direction of energy flow. Rays are used to model the propagation of light through an optical system, by dividing the real light field up into discrete rays that can be computationally propagated through the system by the techniques of ray tracing. This allows even very complex optical systems to be analyzed mathematically or simulated by computer. Ray tracing uses approximate solutions to Maxwell's equations that are valid as long as the light waves propagate through and around objects whose dimensions are much greater than the light's wavelength. Ray theory does not describe phenomena such as diffraction, which require wave theory. Some wave phenomena such as interference can be modeled in limited circumstances by adding phase to the ray model.\n\nIn Gaussian optics, the cardinal points consist of three pairs of points located on the optical axis of a rotationally symmetric, focal, optical system. These are the focal points, the principal points, and the nodal points. For ideal systems, the basic imaging properties such as image size, location, and orientation are completely determined by the locations of the cardinal points; in fact only four points are necessary: the focal points and either the principal or nodal points. The only ideal system that has been achieved in practice is the plane mirror, however the cardinal points are widely used to approximate the behavior of real optical systems. Cardinal points provide a way to analytically simplify a system with many components, allowing the imaging characteristics of the system to be approximately determined with simple calculations.\n\nIn geometry, a plane of rotation is an abstract object used to describe or visualize rotations in space. In three dimensions it is an alternative to the axis of rotation, but unlike the axis of rotation it can be used in other dimensions, such as two, four or more dimensions.", null, "The Rayleigh sky model describes the observed polarization pattern of the daytime sky. Within the atmosphere Rayleigh scattering of light from air molecules, water, dust, and aerosols causes the sky's light to have a defined polarization pattern. The same elastic scattering processes cause the sky to be blue. The polarization is characterized at each wavelength by its degree of polarization, and orientation.\n\nIn astronomy, geography, and related sciences and contexts, a direction or plane passing by a given point is said to be vertical if it contains the local gravity direction at that point. Conversely, a direction or plane is said to be horizontal if it is perpendicular to the vertical direction. In general, something that is vertical can be drawn from up to down, such as the y-axis in the Cartesian coordinate system.", null, "In geometry, an object has symmetry if there is an operation or transformation that maps the figure/object onto itself. Thus, a symmetry can be thought of as an immunity to change. For instance, a circle rotated about its center will have the same shape and size as the original circle, as all points before and after the transform would be indistinguishable. A circle is thus said to be symmetric under rotation or to have rotational symmetry. If the isometry is the reflection of a plane figure about a line, then the figure is said to have reflectional symmetry or line symmetry; it is also possible for a figure/object to have more than one line of symmetry." ]
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http://mike-the-strike.net/Soaring_Forecast/December2009.htm
[ "Daily report for December 2009\n```Averages\\Extremes for day :01\n------------------------------------------------------------\n\nAverage temperature = 52.5°F\nAverage humidity = 37%\nAverage dewpoint = 26.2°F\nAverage barometer = 29.9 in.\nAverage windspeed = 2.4 mph\nAverage gustspeed = 2.7 mph\nAverage direction = 333° (NNW)\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 01 at time 00:00\nMaximum temperature = 60.8°F on day 01 at time 15:33\nMinimum temperature = 44.4°F on day 01 at time 07:51\nMaximum humidity = 50% on day 01 at time 08:35\nMinimum humidity = 30% on day 01 at time 18:34\nMaximum pressure = 29.929 in. on day 01 at time 09:29\nMinimum pressure = 29.808 in. on day 01 at time 19:25\nMaximum windspeed = 5.8 mph on day 01 at time 15:43\nMaximum gust speed = 9 mph from 225 °( SW) on day 01 at time 15:33\nMaximum heat index = 60.8°F on day 01 at time 15:33\n\nClick here for today´s 24 hour graph :1 :12 :2009\n\nAverages\\Extremes for day :02\n------------------------------------------------------------\n\nAverage temperature = 53.7°F\nAverage humidity = 33%\nAverage dewpoint = 25.3°F\nAverage barometer = 29.8 in.\nAverage windspeed = 2.0 mph\nAverage gustspeed = 2.4 mph\nAverage direction = 58° (ENE)\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 02 at time 23:57\nMaximum temperature = 60.8°F on day 02 at time 15:38\nMinimum temperature = 46.0°F on day 02 at time 23:38\nMaximum humidity = 46% on day 02 at time 08:03\nMinimum humidity = 27% on day 02 at time 15:38\nMaximum pressure = 29.899 in. on day 02 at time 11:08\nMinimum pressure = 29.691 in. on day 02 at time 17:38\nMaximum windspeed = 4.6 mph on day 02 at time 10:31\nMaximum gust speed = 8 mph from 090 °( E ) on day 02 at time 09:27\nMaximum heat index = 60.8°F on day 02 at time 15:38\n\nClick here for today´s 24 hour graph :2 :12 :2009\n\nAverages\\Extremes for day :03\n------------------------------------------------------------\n\nAverage temperature = 52.2°F\nAverage humidity = 29%\nAverage dewpoint = 17.7°F\nAverage barometer = 29.8 in.\nAverage windspeed = 3.1 mph\nAverage gustspeed = 4.0 mph\nAverage direction = 29° (NNE)\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 03 at time 23:57\nMaximum temperature = 60.6°F on day 03 at time 15:38\nMinimum temperature = 45.1°F on day 03 at time 23:57\nMaximum humidity = 44% on day 03 at time 07:38\nMinimum humidity = 5% on day 03 at time 23:57\nMaximum pressure = 29.901 in. on day 03 at time 23:57\nMinimum pressure = 29.705 in. on day 03 at time 00:38\nMaximum windspeed = 6.9 mph on day 03 at time 23:57\nMaximum gust speed = 8 mph from 090 °( E ) on day 03 at time 23:57\nMaximum heat index = 60.6°F on day 03 at time 15:38\n\nClick here for today´s 24 hour graph :3 :12 :2009\n\nAverages\\Extremes for day :04\n------------------------------------------------------------\n\nAverage temperature = 45.9°F\nAverage humidity = 6%\nAverage dewpoint = -17.3°F\nAverage barometer = 30.0 in.\nAverage windspeed = 3.8 mph\nAverage gustspeed = 5.0 mph\nAverage direction = 70° (ENE)\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 04 at time 23:57\nMaximum temperature = 54.5°F on day 04 at time 15:38\nMinimum temperature = 38.7°F on day 04 at time 07:38\nMaximum humidity = 12% on day 04 at time 19:38\nMinimum humidity = 5% on day 04 at time 15:38\nMaximum pressure = 30.076 in. on day 04 at time 10:38\nMinimum pressure = 29.901 in. on day 04 at time 00:38\nMaximum windspeed = 8.1 mph on day 04 at time 10:38\nMaximum gust speed = 13 mph from 068 °(ENE) on day 04 at time 10:38\nMaximum heat index = 54.5°F on day 04 at time 15:38\n\nClick here for today´s 24 hour graph :4 :12 :2009\n\nAverages\\Extremes for day :05\n------------------------------------------------------------\n\nAverage temperature = 46.8°F\nAverage humidity = 11%\nAverage dewpoint = -7.6°F\nAverage barometer = 29.8 in.\nAverage windspeed = 3.4 mph\nAverage gustspeed = 4.4 mph\nAverage direction = 93° ( E )\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 05 at time 23:57\nMaximum temperature = 54.7°F on day 05 at time 14:55\nMinimum temperature = 41.2°F on day 05 at time 06:38\nMaximum humidity = 21% on day 05 at time 22:19\nMinimum humidity = 6% on day 05 at time 08:38\nMaximum pressure = 29.919 in. on day 05 at time 00:38\nMinimum pressure = 29.743 in. on day 05 at time 23:09\nMaximum windspeed = 6.9 mph on day 05 at time 11:21\nMaximum gust speed = 12 mph from 045 °( NE) on day 05 at time 11:01\nMaximum heat index = 54.7°F on day 05 at time 14:55\n\nClick here for today´s 24 hour graph :5 :12 :2009\n\nAverages\\Extremes for day :06\n------------------------------------------------------------\n\nAverage temperature = 47.3°F\nAverage humidity = 34%\nAverage dewpoint = 19.7°F\nAverage barometer = 29.8 in.\nAverage windspeed = 1.4 mph\nAverage gustspeed = 1.7 mph\nAverage direction = 187° ( S )\nRainfall for month = 0.00 in.\nRainfall for year = 2.85 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 06 at time 23:57\nMaximum temperature = 54.1°F on day 06 at time 14:43\nMinimum temperature = 37.4°F on day 06 at time 03:39\nMaximum humidity = 47% on day 06 at time 09:35\nMinimum humidity = 16% on day 06 at time 00:51\nMaximum pressure = 29.902 in. on day 06 at time 11:10\nMinimum pressure = 29.754 in. on day 06 at time 00:29\nMaximum windspeed = 4.6 mph on day 06 at time 16:16\nMaximum gust speed = 9 mph from 203 °(SSW) on day 06 at time 14:08\nMaximum heat index = 54.1°F on day 06 at time 14:43\n\nClick here for today´s 24 hour graph :6 :12 :2009\n\nAverages\\Extremes for day :07\n------------------------------------------------------------\n\nAverage temperature = 49.2°F\nAverage humidity = 68%\nAverage dewpoint = 38.6°F\nAverage barometer = 29.7 in.\nAverage windspeed = 6.3 mph\nAverage gustspeed = 8.0 mph\nAverage direction = 188° ( S )\nRainfall for month = 0.83 in.\nRainfall for year = 3.68 in.\nRainfall for day = 0.83 in.\nMaximum rain per minute = 0.04 in. on day 07 at time 14:36\nMaximum temperature = 50.5°F on day 07 at time 09:25\nMinimum temperature = 46.2°F on day 07 at time 23:51\nMaximum humidity = 84% on day 07 at time 23:29\nMinimum humidity = 44% on day 07 at time 00:53\nMaximum pressure = 29.867 in. on day 07 at time 00:30\nMinimum pressure = 29.379 in. on day 07 at time 23:29\nMaximum windspeed = 20.7 mph on day 07 at time 23:27\nMaximum gust speed = 38 mph from 180 °( S ) on day 07 at time 22:47\nMaximum heat index = 50.5°F on day 07 at time 09:25\n\nClick here for today´s 24 hour graph :7 :12 :2009\n\nAverages\\Extremes for day :08\n------------------------------------------------------------\n\nAverage temperature = 43.5°F\nAverage humidity = 50%\nAverage dewpoint = 25.4°F\nAverage barometer = 29.8 in.\nAverage windspeed = 4.3 mph\nAverage gustspeed = 5.2 mph\nAverage direction = 212° (SSW)\nRainfall for month = 0.86 in.\nRainfall for year = 3.71 in.\nRainfall for day = 0.03 in.\nMaximum rain per minute = 0.03 in. on day 08 at time 03:16\nMaximum temperature = 48.0°F on day 08 at time 14:47\nMinimum temperature = 36.7°F on day 08 at time 23:53\nMaximum humidity = 84% on day 08 at time 00:19\nMinimum humidity = 33% on day 08 at time 16:43\nMaximum pressure = 29.973 in. on day 08 at time 22:49\nMinimum pressure = 29.459 in. on day 08 at time 00:09\nMaximum windspeed = 12.7 mph on day 08 at time 02:59\nMaximum gust speed = 25 mph from 270 °( W ) on day 08 at time 03:51\nMaximum heat index = 48.0°F on day 08 at time 14:47\n\nClick here for today´s 24 hour graph :8 :12 :2009\n\nAverages\\Extremes for day :09\n------------------------------------------------------------\n\nAverage temperature = 43.2°F\nAverage humidity = 41%\nAverage dewpoint = 20.5°F\nAverage barometer = 29.9 in.\nAverage windspeed = 2.0 mph\nAverage gustspeed = 2.3 mph\nAverage direction = 51° ( NE)\nRainfall for month = 0.86 in.\nRainfall for year = 3.71 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 09 at time 23:57\nMaximum temperature = 51.3°F on day 09 at time 14:41\nMinimum temperature = 36.1°F on day 09 at time 00:57\nMaximum humidity = 50% on day 09 at time 23:57\nMinimum humidity = 31% on day 09 at time 14:15\nMaximum pressure = 30.008 in. on day 09 at time 11:02\nMinimum pressure = 29.838 in. on day 09 at time 04:38\nMaximum windspeed = 4.6 mph on day 09 at time 15:15\nMaximum gust speed = 8 mph from 225 °( SW) on day 09 at time 15:37\nMaximum heat index = 51.3°F on day 09 at time 14:41\n\nClick here for today´s 24 hour graph :9 :12 :2009\n\nAverages\\Extremes for day :10\n------------------------------------------------------------\n\nAverage temperature = 44.3°F\nAverage humidity = 40%\nAverage dewpoint = 21.0°F\nAverage barometer = 29.9 in.\nAverage windspeed = 2.1 mph\nAverage gustspeed = 2.7 mph\nAverage direction = 29° (NNE)\nRainfall for month = 0.86 in.\nRainfall for year = 3.71 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 10 at time 23:57\nMaximum temperature = 52.7°F on day 10 at time 16:24\nMinimum temperature = 37.8°F on day 10 at time 03:09\nMaximum humidity = 51% on day 10 at time 01:29\nMinimum humidity = 30% on day 10 at time 16:38\nMaximum pressure = 30.014 in. on day 10 at time 10:30\nMinimum pressure = 29.846 in. on day 10 at time 04:38\nMaximum windspeed = 4.6 mph on day 10 at time 11:25\nMaximum gust speed = 7 mph from 045 °( NE) on day 10 at time 11:30\nMaximum heat index = 52.7°F on day 10 at time 16:24\n\nClick here for today´s 24 hour graph :10 :12 :2009\n\nAverages\\Extremes for day :11\n------------------------------------------------------------\n\nAverage temperature = 47.7°F\nAverage humidity = 39%\nAverage dewpoint = 23.7°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.0 mph\nAverage gustspeed = 2.4 mph\nAverage direction = 18° (NNE)\nRainfall for month = 0.86 in.\nRainfall for year = 3.71 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 11 at time 23:57\nMaximum temperature = 56.8°F on day 11 at time 15:39\nMinimum temperature = 40.6°F on day 11 at time 04:38\nMaximum humidity = 46% on day 11 at time 23:57\nMinimum humidity = 30% on day 11 at time 17:11\nMaximum pressure = 30.050 in. on day 11 at time 10:10\nMinimum pressure = 29.883 in. on day 11 at time 20:38\nMaximum windspeed = 4.6 mph on day 11 at time 12:06\nMaximum gust speed = 9 mph from 045 °( NE) on day 11 at time 10:58\nMaximum heat index = 56.8°F on day 11 at time 15:39\n\nClick here for today´s 24 hour graph :11 :12 :2009\n\nAverages\\Extremes for day :12\n------------------------------------------------------------\n\nAverage temperature = 51.2°F\nAverage humidity = 42%\nAverage dewpoint = 28.5°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.2 mph\nAverage gustspeed = 2.6 mph\nAverage direction = 35° ( NE)\nRainfall for month = 0.86 in.\nRainfall for year = 3.71 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 12 at time 23:57\nMaximum temperature = 57.4°F on day 12 at time 15:33\nMinimum temperature = 45.0°F on day 12 at time 01:38\nMaximum humidity = 49% on day 12 at time 21:53\nMinimum humidity = 31% on day 12 at time 15:07\nMaximum pressure = 30.103 in. on day 12 at time 11:09\nMinimum pressure = 29.879 in. on day 12 at time 04:38\nMaximum windspeed = 4.6 mph on day 12 at time 12:05\nMaximum gust speed = 8 mph from 045 °( NE) on day 12 at time 11:45\nMaximum heat index = 57.4°F on day 12 at time 15:33\n\nClick here for today´s 24 hour graph :12 :12 :2009\n\nAverages\\Extremes for day :13\n------------------------------------------------------------\n\nAverage temperature = 52.0°F\nAverage humidity = 58%\nAverage dewpoint = 37.4°F\nAverage barometer = 29.9 in.\nAverage windspeed = 2.4 mph\nAverage gustspeed = 2.9 mph\nAverage direction = 166° (SSE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.06 in.\nMaximum rain per minute = 0.03 in. on day 13 at time 13:22\nMaximum temperature = 57.4°F on day 13 at time 10:47\nMinimum temperature = 46.4°F on day 13 at time 23:49\nMaximum humidity = 78% on day 13 at time 22:09\nMinimum humidity = 43% on day 13 at time 11:11\nMaximum pressure = 29.985 in. on day 13 at time 00:09\nMinimum pressure = 29.890 in. on day 13 at time 05:49\nMaximum windspeed = 6.9 mph on day 13 at time 10:39\nMaximum gust speed = 12 mph from 225 °( SW) on day 13 at time 10:33\nMaximum heat index = 57.4°F on day 13 at time 10:47\n\nClick here for today´s 24 hour graph :13 :12 :2009\n\nAverages\\Extremes for day :14\n------------------------------------------------------------\n\nAverage temperature = 51.3°F\nAverage humidity = 55%\nAverage dewpoint = 34.8°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.0 mph\nAverage gustspeed = 2.5 mph\nAverage direction = 13° (NNE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 14 at time 23:57\nMaximum temperature = 59.0°F on day 14 at time 15:09\nMinimum temperature = 45.5°F on day 14 at time 07:57\nMaximum humidity = 76% on day 14 at time 02:05\nMinimum humidity = 34% on day 14 at time 16:39\nMaximum pressure = 30.100 in. on day 14 at time 23:49\nMinimum pressure = 29.911 in. on day 14 at time 04:29\nMaximum windspeed = 4.6 mph on day 14 at time 13:19\nMaximum gust speed = 7 mph from 293 °(WNW) on day 14 at time 13:41\nMaximum heat index = 59.0°F on day 14 at time 15:09\n\nClick here for today´s 24 hour graph :14 :12 :2009\n\nAverages\\Extremes for day :15\n------------------------------------------------------------\n\nAverage temperature = 52.0°F\nAverage humidity = 29%\nAverage dewpoint = 20.1°F\nAverage barometer = 30.2 in.\nAverage windspeed = 3.5 mph\nAverage gustspeed = 4.2 mph\nAverage direction = 35° ( NE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 15 at time 23:57\nMaximum temperature = 62.2°F on day 15 at time 15:17\nMinimum temperature = 44.1°F on day 15 at time 05:29\nMaximum humidity = 40% on day 15 at time 00:51\nMinimum humidity = 16% on day 15 at time 16:37\nMaximum pressure = 30.230 in. on day 15 at time 11:09\nMinimum pressure = 30.097 in. on day 15 at time 00:10\nMaximum windspeed = 8.1 mph on day 15 at time 09:35\nMaximum gust speed = 13 mph from 068 °(ENE) on day 15 at time 09:37\nMaximum heat index = 62.2°F on day 15 at time 15:17\n\nClick here for today´s 24 hour graph :15 :12 :2009\n\nAverages\\Extremes for day :16\n------------------------------------------------------------\n\nAverage temperature = 56.1°F\nAverage humidity = 27%\nAverage dewpoint = 21.9°F\nAverage barometer = 30.1 in.\nAverage windspeed = 4.4 mph\nAverage gustspeed = 5.4 mph\nAverage direction = 39° ( NE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 16 at time 23:57\nMaximum temperature = 65.5°F on day 16 at time 15:21\nMinimum temperature = 48.2°F on day 16 at time 05:17\nMaximum humidity = 31% on day 16 at time 23:51\nMinimum humidity = 21% on day 16 at time 16:43\nMaximum pressure = 30.191 in. on day 16 at time 11:09\nMinimum pressure = 30.070 in. on day 16 at time 23:57\nMaximum windspeed = 8.1 mph on day 16 at time 12:17\nMaximum gust speed = 14 mph from 023 °(NNE) on day 16 at time 11:07\nMaximum heat index = 74.1°F on day 16 at time 14:39\n\nClick here for today´s 24 hour graph :16 :12 :2009\n\nAverages\\Extremes for day :17\n------------------------------------------------------------\n\nAverage temperature = 57.2°F\nAverage humidity = 28%\nAverage dewpoint = 23.7°F\nAverage barometer = 30.0 in.\nAverage windspeed = 3.2 mph\nAverage gustspeed = 3.9 mph\nAverage direction = 28° (NNE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 17 at time 23:57\nMaximum temperature = 66.4°F on day 17 at time 15:41\nMinimum temperature = 50.2°F on day 17 at time 07:01\nMaximum humidity = 33% on day 17 at time 07:55\nMinimum humidity = 20% on day 17 at time 14:55\nMaximum pressure = 30.082 in. on day 17 at time 10:49\nMinimum pressure = 29.991 in. on day 17 at time 17:09\nMaximum windspeed = 6.9 mph on day 17 at time 09:01\nMaximum gust speed = 10 mph from 045 °( NE) on day 17 at time 10:21\nMaximum heat index = 74.1°F on day 17 at time 16:47\n\nClick here for today´s 24 hour graph :17 :12 :2009\n\nAverages\\Extremes for day :18\n------------------------------------------------------------\n\nAverage temperature = 57.7°F\nAverage humidity = 22%\nAverage dewpoint = 19.0°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.6 mph\nAverage gustspeed = 3.2 mph\nAverage direction = 17° (NNE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 18 at time 23:57\nMaximum temperature = 66.2°F on day 18 at time 15:25\nMinimum temperature = 50.0°F on day 18 at time 07:47\nMaximum humidity = 30% on day 18 at time 20:51\nMinimum humidity = 16% on day 18 at time 11:19\nMaximum pressure = 30.038 in. on day 18 at time 10:09\nMinimum pressure = 29.926 in. on day 18 at time 18:09\nMaximum windspeed = 5.8 mph on day 18 at time 05:27\nMaximum gust speed = 10 mph from 360 °( N ) on day 18 at time 04:41\nMaximum heat index = 73.4°F on day 18 at time 14:35\n\nClick here for today´s 24 hour graph :18 :12 :2009\n\nAverages\\Extremes for day :19\n------------------------------------------------------------\n\nAverage temperature = 56.7°F\nAverage humidity = 19%\nAverage dewpoint = 14.1°F\nAverage barometer = 30.0 in.\nAverage windspeed = 4.8 mph\nAverage gustspeed = 5.9 mph\nAverage direction = 34° ( NE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 19 at time 23:57\nMaximum temperature = 65.3°F on day 19 at time 15:39\nMinimum temperature = 50.0°F on day 19 at time 06:17\nMaximum humidity = 28% on day 19 at time 06:25\nMinimum humidity = 12% on day 19 at time 17:07\nMaximum pressure = 30.082 in. on day 19 at time 23:49\nMinimum pressure = 29.952 in. on day 19 at time 00:49\nMaximum windspeed = 9.2 mph on day 19 at time 09:54\nMaximum gust speed = 16 mph from 360 °( N ) on day 19 at time 14:07\nMaximum heat index = 69.6°F on day 19 at time 15:39\n\nClick here for today´s 24 hour graph :19 :12 :2009\n\nAverages\\Extremes for day :20\n------------------------------------------------------------\n\nAverage temperature = 57.4°F\nAverage humidity = 20%\nAverage dewpoint = 16.3°F\nAverage barometer = 30.1 in.\nAverage windspeed = 5.1 mph\nAverage gustspeed = 6.1 mph\nAverage direction = 42° ( NE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 20 at time 23:57\nMaximum temperature = 63.9°F on day 20 at time 13:55\nMinimum temperature = 49.3°F on day 20 at time 07:45\nMaximum humidity = 22% on day 20 at time 23:57\nMinimum humidity = 17% on day 20 at time 14:07\nMaximum pressure = 30.153 in. on day 20 at time 10:49\nMinimum pressure = 30.047 in. on day 20 at time 23:09\nMaximum windspeed = 9.2 mph on day 20 at time 04:59\nMaximum gust speed = 14 mph from 045 °( NE) on day 20 at time 05:01\nMaximum heat index = 63.9°F on day 20 at time 13:55\n\nClick here for today´s 24 hour graph :20 :12 :2009\n\nAverages\\Extremes for day :21\n------------------------------------------------------------\n\nAverage temperature = 57.4°F\nAverage humidity = 25%\nAverage dewpoint = 21.2°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.4 mph\nAverage gustspeed = 3.0 mph\nAverage direction = 31° (NNE)\nRainfall for month = 0.92 in.\nRainfall for year = 3.77 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 21 at time 23:57\nMaximum temperature = 62.6°F on day 21 at time 13:15\nMinimum temperature = 52.2°F on day 21 at time 23:57\nMaximum humidity = 35% on day 21 at time 23:57\nMinimum humidity = 21% on day 21 at time 10:35\nMaximum pressure = 30.059 in. on day 21 at time 01:29\nMinimum pressure = 29.896 in. on day 21 at time 23:57\nMaximum windspeed = 5.8 mph on day 21 at time 10:05\nMaximum gust speed = 9 mph from 023 °(NNE) on day 21 at time 09:15\nMaximum heat index = 62.6°F on day 21 at time 13:15\n\nClick here for today´s 24 hour graph :21 :12 :2009\n\nAverages\\Extremes for day :22\n------------------------------------------------------------\n\nAverage temperature = 50.3°F\nAverage humidity = 44%\nAverage dewpoint = 28.1°F\nAverage barometer = 29.7 in.\nAverage windspeed = 3.1 mph\nAverage gustspeed = 3.8 mph\nAverage direction = 204° (SSW)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.16 in.\nMaximum rain per minute = 0.04 in. on day 22 at time 14:44\nMaximum temperature = 56.8°F on day 22 at time 13:21\nMinimum temperature = 44.6°F on day 22 at time 23:55\nMaximum humidity = 67% on day 22 at time 16:09\nMinimum humidity = 30% on day 22 at time 13:49\nMaximum pressure = 29.896 in. on day 22 at time 00:09\nMinimum pressure = 29.554 in. on day 22 at time 14:49\nMaximum windspeed = 11.5 mph on day 22 at time 15:09\nMaximum gust speed = 17 mph from 248 °(WSW) on day 22 at time 15:01\nMaximum heat index = 56.8°F on day 22 at time 13:21\n\nClick here for today´s 24 hour graph :22 :12 :2009\n\nAverages\\Extremes for day :23\n------------------------------------------------------------\n\nAverage temperature = 43.9°F\nAverage humidity = 55%\nAverage dewpoint = 28.7°F\nAverage barometer = 29.8 in.\nAverage windspeed = 1.5 mph\nAverage gustspeed = 1.9 mph\nAverage direction = 196° (SSW)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 23 at time 23:57\nMaximum temperature = 49.1°F on day 23 at time 16:23\nMinimum temperature = 38.8°F on day 23 at time 08:31\nMaximum humidity = 63% on day 23 at time 04:53\nMinimum humidity = 48% on day 23 at time 17:39\nMaximum pressure = 29.991 in. on day 23 at time 23:57\nMinimum pressure = 29.678 in. on day 23 at time 00:09\nMaximum windspeed = 4.6 mph on day 23 at time 16:03\nMaximum gust speed = 8 mph from 203 °(SSW) on day 23 at time 15:11\nMaximum heat index = 49.1°F on day 23 at time 16:23\n\nClick here for today´s 24 hour graph :23 :12 :2009\n\nAverages\\Extremes for day :24\n------------------------------------------------------------\n\nAverage temperature = 44.6°F\nAverage humidity = 47%\nAverage dewpoint = 24.6°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.3 mph\nAverage gustspeed = 2.9 mph\nAverage direction = 13° (NNE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 24 at time 23:57\nMaximum temperature = 53.2°F on day 24 at time 15:39\nMinimum temperature = 36.9°F on day 24 at time 07:21\nMaximum humidity = 68% on day 24 at time 07:01\nMinimum humidity = 30% on day 24 at time 23:57\nMaximum pressure = 30.085 in. on day 24 at time 10:09\nMinimum pressure = 29.991 in. on day 24 at time 00:09\nMaximum windspeed = 4.6 mph on day 24 at time 23:43\nMaximum gust speed = 10 mph from 360 °( N ) on day 24 at time 13:13\nMaximum heat index = 53.2°F on day 24 at time 15:39\n\nClick here for today´s 24 hour graph :24 :12 :2009\n\nAverages\\Extremes for day :25\n------------------------------------------------------------\n\nAverage temperature = 43.9°F\nAverage humidity = 29%\nAverage dewpoint = 13.4°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.5 mph\nAverage gustspeed = 3.0 mph\nAverage direction = 19° (NNE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 25 at time 23:57\nMaximum temperature = 51.4°F on day 25 at time 15:03\nMinimum temperature = 37.2°F on day 25 at time 07:33\nMaximum humidity = 39% on day 25 at time 23:57\nMinimum humidity = 21% on day 25 at time 12:57\nMaximum pressure = 30.023 in. on day 25 at time 00:09\nMinimum pressure = 29.893 in. on day 25 at time 17:29\nMaximum windspeed = 4.6 mph on day 25 at time 14:23\nMaximum gust speed = 8 mph from 225 °( SW) on day 25 at time 15:41\nMaximum heat index = 51.4°F on day 25 at time 15:03\n\nClick here for today´s 24 hour graph :25 :12 :2009\n\nAverages\\Extremes for day :26\n------------------------------------------------------------\n\nAverage temperature = 44.8°F\nAverage humidity = 27%\nAverage dewpoint = 11.9°F\nAverage barometer = 30.0 in.\nAverage windspeed = 2.8 mph\nAverage gustspeed = 3.4 mph\nAverage direction = 38° ( NE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 26 at time 23:57\nMaximum temperature = 52.9°F on day 26 at time 15:31\nMinimum temperature = 36.9°F on day 26 at time 07:31\nMaximum humidity = 40% on day 26 at time 01:23\nMinimum humidity = 14% on day 26 at time 15:59\nMaximum pressure = 30.103 in. on day 26 at time 23:29\nMinimum pressure = 29.955 in. on day 26 at time 01:09\nMaximum windspeed = 6.9 mph on day 26 at time 11:51\nMaximum gust speed = 12 mph from 090 °( E ) on day 26 at time 11:59\nMaximum heat index = 52.9°F on day 26 at time 15:31\n\nClick here for today´s 24 hour graph :26 :12 :2009\n\nAverages\\Extremes for day :27\n------------------------------------------------------------\n\nAverage temperature = 47.3°F\nAverage humidity = 22%\nAverage dewpoint = 10.1°F\nAverage barometer = 30.1 in.\nAverage windspeed = 3.6 mph\nAverage gustspeed = 4.5 mph\nAverage direction = 43° ( NE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 27 at time 23:57\nMaximum temperature = 55.6°F on day 27 at time 15:39\nMinimum temperature = 40.6°F on day 27 at time 07:19\nMaximum humidity = 27% on day 27 at time 00:09\nMinimum humidity = 15% on day 27 at time 15:17\nMaximum pressure = 30.159 in. on day 27 at time 11:09\nMinimum pressure = 30.067 in. on day 27 at time 02:09\nMaximum windspeed = 8.1 mph on day 27 at time 08:47\nMaximum gust speed = 12 mph from 090 °( E ) on day 27 at time 08:37\nMaximum heat index = 55.6°F on day 27 at time 15:39\n\nClick here for today´s 24 hour graph :27 :12 :2009\n\nAverages\\Extremes for day :28\n------------------------------------------------------------\n\nAverage temperature = 50.7°F\nAverage humidity = 19%\nAverage dewpoint = 9.6°F\nAverage barometer = 30.0 in.\nAverage windspeed = 5.7 mph\nAverage gustspeed = 7.0 mph\nAverage direction = 39° ( NE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 28 at time 23:50\nMaximum temperature = 55.8°F on day 28 at time 16:01\nMinimum temperature = 45.1°F on day 28 at time 02:57\nMaximum humidity = 23% on day 28 at time 04:11\nMinimum humidity = 13% on day 28 at time 15:17\nMaximum pressure = 30.100 in. on day 28 at time 00:09\nMinimum pressure = 29.935 in. on day 28 at time 18:09\nMaximum windspeed = 12.7 mph on day 28 at time 11:07\nMaximum gust speed = 20 mph from 023 °(NNE) on day 28 at time 10:45\nMaximum heat index = 55.8°F on day 28 at time 16:01\n\nClick here for today´s 24 hour graph :28 :12 :2009\n\nAverages\\Extremes for day :29\n------------------------------------------------------------\n\nAverage temperature = 49.2°F\nAverage humidity = 22%\nAverage dewpoint = 12.1°F\nAverage barometer = 30.0 in.\nAverage windspeed = 4.7 mph\nAverage gustspeed = 5.4 mph\nAverage direction = 35° ( NE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 29 at time 00:00\nMaximum temperature = 50.0°F on day 29 at time 02:35\nMinimum temperature = 48.4°F on day 29 at time 00:00\nMaximum humidity = 23% on day 29 at time 00:00\nMinimum humidity = 21% on day 29 at time 00:25\nMaximum pressure = 29.976 in. on day 29 at time 00:00\nMinimum pressure = 29.938 in. on day 29 at time 02:49\nMaximum windspeed = 6.9 mph on day 29 at time 00:00\nMaximum gust speed = 9 mph from 068 °(ENE) on day 29 at time 06:07\nMaximum heat index = 50.0°F on day 29 at time 02:35\n\nClick here for today´s 24 hour graph :29 :12 :2009\n\nAverages\\Extremes for day :30\n------------------------------------------------------------\n\nAverage temperature = 48.4°F\nAverage humidity = 23%\nAverage dewpoint = 12.2°F\nAverage barometer = 30.0 in.\nAverage windspeed = 6.9 mph\nAverage gustspeed = 5.8 mph\nAverage direction = 60° (ENE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 30 at time 00:00\nMaximum temperature = 48.4°F on day 30 at time 00:00\nMinimum temperature = 48.4°F on day 30 at time 00:00\nMaximum humidity = 23% on day 30 at time 00:00\nMinimum humidity = 23% on day 30 at time 00:00\nMaximum pressure = 29.976 in. on day 30 at time 00:00\nMinimum pressure = 29.976 in. on day 30 at time 00:00\nMaximum windspeed = 6.9 mph on day 30 at time 00:00\nMaximum gust speed = 6 mph from 068 °(ENE) on day 30 at time 00:00\nMaximum heat index = 48.4°F on day 30 at time 00:00\n\nClick here for today´s 24 hour graph :30 :12 :2009\n\nAverages\\Extremes for day :31\n------------------------------------------------------------\n\nAverage temperature = 51.3°F\nAverage humidity = 20%\nAverage dewpoint = 11.5°F\nAverage barometer = 30.3 in.\nAverage windspeed = 3.5 mph\nAverage gustspeed = 4.3 mph\nAverage direction = 34° ( NE)\nRainfall for month = 1.08 in.\nRainfall for year = 3.93 in.\nRainfall for day = 0.00 in.\nMaximum rain per minute = 0.00 in. on day 31 at time 23:50\nMaximum temperature = 56.7°F on day 31 at time 16:19\nMinimum temperature = 43.5°F on day 31 at time 12:00\nMaximum humidity = 46% on day 31 at time 12:00\nMinimum humidity = 15% on day 31 at time 17:03\nMaximum pressure = 30.292 in. on day 31 at time 23:49\nMinimum pressure = 29.976 in. on day 31 at time 04:00\nMaximum windspeed = 8.1 mph on day 31 at time 13:27\nMaximum gust speed = 13 mph from 045 °( NE) on day 31 at time 13:17\nMaximum heat index = 56.7°F on day 31 at time 16:19\n\nClick here for today´s 24 hour graph :31 :12 :2009\n\n---------------------------------------------------------------------------------------------\nAverages\\Extremes for the month of December 2009\n\n---------------------------------------------------------------------------------------------\nAverage temperature = 50.0°F\nAverage humidity = 34%\nAverage dewpoint = 19.6°F\nAverage barometer = 29.951 in.\nAverage windspeed = 3.2 mph\nAverage gustspeed = 3.9 mph\nAverage direction = 46° ( NE)\nRainfall for month = 1.083 in.\nRainfall for year = 3.933 in.\nMaximum rain per minute = 0.035 in on day 22 at time 14:44\nMaximum temperature = 66.4°F on day 17 at time 15:41\nMinimum temperature = 36.1°F on day 09 at time 00:57\nMaximum humidity = 84% on day 08 at time 00:19\nMinimum humidity = 5% on day 04 at time 15:38\nMaximum pressure = 30.29 in. on day 31 at time 23:49\nMinimum pressure = 29.38 in. on day 07 at time 23:29\nMaximum windspeed = 20.7 mph from 180°( S ) on day 07 at time 23:27\nMaximum gust speed = 38.0 mph from 203°(SSW) on day 07 at time 22:47\nMaximum heat index = 74.1°F on day 16 at time 14:39\nAvg daily max temp :56.8°F\nAvg daily min temp :43.6°F\nTotal windrun = 2149.7miles\n-----------------------------------\nDaily rain totals\n-----------------------------------\n00.83 in. on day 7\n00.03 in. on day 8\n00.06 in. on day 13\n00.16 in. on day 22\n```" ]
[ null ]
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https://ithems.riken.jp/ja/members/ken-furukawa
[ "2020-10-01 - 特別研究員 (兼務)\n\n## 自己紹介\n\nI am Ken Furukawa. My research area is the mathematical theory of partial differential equations related to the fluid dynamics and diffusion phenomena. More specifically, we studied mathematically rigorous justification of the derivation of the primitive equations by the Navier-Stokes equations. The primitive equations have nice properties on well-posedness and have a strong connection with the Navier-Stokes equations. We obtained some results on the well-posedness of the Navier-Stokes equations in this research.\n\nRecently, I have been interested in the mathematical aspect of data assimilation. Data assimilation is very useful to obtain a plausible forecast and is also closely related to our lives. However, mathematically rigorous studies of data assimilation from the mathematical theory of PDE are under development. I will study data assimilation from the view PDE point of view.\n\n## 関連イベント", null, "### Maximal Regularity and Partial Differential Equations\n\n2020年9月8日16:00 - 18:10 セミナー iTHEMS数学セミナー\n\n## 関連ニュース", null, "### Self-introduction: Ken Furukawa\n\n2020-10-01 今週の注目人物" ]
[ null, "https://ithems.riken.jp/storage/app/uploads/public/606/fe0/8ee/thumb_1813_50_50_0_0_crop.jpg", null, "https://ithems.riken.jp/storage/app/uploads/public/606/fe0/8ee/thumb_1813_50_50_0_0_crop.jpg", null ]
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https://cbp.tnw.utwente.nl/PolymeerDictaat/node24.html
[ "", null, "", null, "", null, "", null, "", null, "Next: Appendix A Up: The Gaussian chain Previous: Green's function method\n\n# One Gaussian chain in a box\n\nAs an example of the use of the Green's function method, we calculate the pressure exerted by a Gaussian chain on the walls of a confining box .\n\nThe potential is zero everywhere inside the box, and infinite everywhere outside the box. Then", null, "at the walls of the box. Solving Eq. (3.18) yields", null, "(3.21)", null, "(3.22)\n\nwhere", null, "(3.23)", null, "(3.24)\n\n Z =", null, "(3.25) Zi =", null, "(3.26)\n\nIntroducing the eigenfunctions and eigenvalues from Eqs. (3.23) and (3.24) we get", null, "(3.27)\n\nwhere the prime at the summation sign indicates that only odd n should occur in the sum.\n\nNow look at two limits\n\ni.", null, "The polymer is much smaller than the box\n Zi =", null, "(3.28) Z =", null, "(3.29)\n\nThe pressure on wall one is", null, "(3.30)\n\ni.e. independent of the wall number, and equal to the ideal gas result.\n\nii.", null, "The polymer is very much constrained by the box", null, "(3.31)\n\n P1 =", null, "(3.32) =", null, "(3.33)\n\nIn this case the pressure on the different walls depends on the size of the box orthogonal to the wall.", null, "", null, "", null, "", null, "", null, "Next: Appendix A Up: The Gaussian chain Previous: Green's function method\nW.J. Briels" ]
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https://www.indiabix.com/electronics-and-communication-engineering/exam-question-papers/213005
[ "# Electronics and Communication Engineering - Exam Questions Papers\n\n21.\n\nTwo discrete time systems with impulse responses h1[n] = δ[n - 1] and h2[n] = δ[n - 2] are connected in cascade. The overall impulse response of the cascaded system is\n\n A. δ[n - 1] + δ[n - 2] B. δ[n - 4] C. δ[n - 3] D. δ[n - 1] + δ[n - 2]\n\nExplanation:\n\nh1(n) → delay by 1, h2(n) → delay by 2,\n\nh1(n) * h2(n) → delay by 3.\n\n22.\n\nThe magnitude plot of a composite signal x(t) = e2jt + e3jt is\n\n A. Half wave rectified sinusoid B. Full wave rectified sinusoid C. Exponentially increasing sinusoid D. Exponentially decreasing sinusoid\n\nExplanation:\n\nx(t) = ej2 . 5t (e-j0.5t + e-j0 . 5t)\n\nx(t) = 2ej2.5t cos (0.5)t", null, "The magnitude of x(t) is\n\n|x(t)| = 2|cos (0.5)t|.\n\n23.\n\nA message signal given by", null, "is amplitude modulated with a carrier of frequency ωc to generate s(t) = [1 + m(t)] cos ωct\n\n A. 8.33% B. 11.11% C. 20% D. 25%\n\nExplanation:", null, ".\n\n24.\n\nA 16 bit counter type ADC uses 1 MHz clock then its maximum conversion time is __________ .\n\n A. 16 μs B. 15 ms C. 6.6 ms D. 66 ms\n\nExplanation:\n\nMaximum conversion time of counter type ADC = (216 - 1) x 1 μs = 65.5 ms » 66 ms.\n\n25.\n\nA first order system will never be able to give a __________ response.\n\n1. Band pass\n2. Band reject\n3. All pass\nChoose the correct option\n\n A. 1, 2 and 3 are true B. 1 and 3 are true, 2 is false C. 1 and 2 are false, 3 is true D. 1 and 2 are true, 3 is false\n\nExplanation:\n\nThe ideal response of a Band pass filter BRF and APF is as shown", null, "So for BPF we require 0 at ω = 0, p i.e. at least 2 zeroes are required in the Transform.\n\nHence order has to be atleast 2.\n\nSimilarly for band reject filter order should be at least 2. Whereas APF has a constant amplitude.\n\nHence Zeroes in the function need not matter.\n\nAPF function is given as", null, "Hence first order can provide APF.\n\n#### Current Affairs 2022\n\nInterview Questions and Answers" ]
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https://rdrr.io/cran/OneArmPhaseTwoStudy/man/get_p_exact_subset.html
[ "# get_p_exact_subset: Calculates the exact p value. In OneArmPhaseTwoStudy: Planning, Conducting, and Analysing Single-Arm Phase II Studies\n\n## Description\n\nCalculates the exact p value for a given subset design.\n\n## Usage\n\n `1` ```get_p_exact_subset(t, u, r1, n1, n, pc0, pt0, sub1 = setupSub1Design()) ```\n\n## Arguments\n\n `t` observed responses in the subset endpoint. `u` observed responses in the superset endpoint. `r1` critical value for the first stage. `n1` sample size for the first stage. `n` overall sample size. `pc0` the response probability for the subset endpoint under the null hypothesis. `pt0` the response probability for the superset endpoint under the null hypothesis. `sub1` \"sub1\"-object used to calculate the p value in c++ .\n\n`setupSub1Design`\n ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```#Setup \"sub1\"-object sub1 <- setupSub1Design(pc0 = 0.5, pt0 = 0.6) #Calculate a subset design design <- getSolutionsSub1(sub1, skipN1 = FALSE)\\$Solutions[4,] #Assuming 9 responses in the subset endpoint and 13 responses #in the superset endpoint were observed. t = 9 u = 13 p_val <- get_p_exact_subset(t, u, design\\$r1, design\\$n1, design\\$n, design\\$pc0, design\\$pt0, sub1) p_val ```" ]
[ null ]
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https://percentage-calculator.net/what-percent-of-x-is-y/what-percent-of-220-is-66.php
[ "# What percent of 220 is 66?\n\nAnswer: 30 percent of 220 is 66\n\n## Fastest method for calculating what percent of 220 is 66\n\nAssume the unknown value is 'Y', and 66 of 220 can be written as:\n\nY = 66 / 220\n\nBy multiplying both numerator and denominator by 100 we will get:\n\nY = 66 / 220 x 100 / 100 = 30 / 100\n\nY = 30%\n\nAnswer: 30 percent of 220 is 66\n\nIf you want to use a calculator, simply enter 66÷220x100 and you will get your answer which is 30\n\nYou may also be interested in:\n\nHere is a calculator to solve percentage calculations such as what percent of 220 is 66. You can solve this type of calculation with your own values by entering them into the calculator's fields, and click 'Calculate' to get the result and explanation.\n\nWhat percent of\nis\n?\n%\n\n## Have time and want to learn the details?\n\nLet's solve the equation for Y by first rewriting it as: 100% / 220 = Y% / 66\n\nDrop the percentage marks to simplify your calculations: 100 / 220 = Y / 66\n\nMultiply both sides by 66 to isolate Y on the right side of the equation: 66 ( 100 / 220 ) = Y\n\nComputing the left side, we get: 30 = Y\n\nThis leaves us with our final answer: 30 percent of 220 is 66" ]
[ null ]
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https://apps.dtic.mil/sti/citations/ADA289424
[ "# Abstract:\n\nThis study uses linearized equations of motion for a rigid body with an attached spring-mass-damper to maximize the decay rate of a satellites coning motion. An analysis of the numerical eigenvalues is presented which leads to an optimal relationship between relevant parameters damper placement, spring constant, damping coefficient, system moments of inertia, and damper mass fraction. The coupled systems eigenvalues do not provide truly critical damping, thus the real eigenvalue parts are minimized in order to achieve damping which requires the minimum amount of time. A comparison between this optimal design method and a classical method concludes a noticeable improvement in damping performance for optimized systems.\n\n# Subject Categories:\n\n• Unmanned Spacecraft\n• Operations Research" ]
[ null ]
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https://proofwiki.org/wiki/Definition:Plane_Angle
[ "# Definition:Angle\n\n(Redirected from Definition:Plane Angle)\n\n## Definition\n\nGiven two intersecting lines or line segments, the amount of rotation about the intersection required to bring one into correspondence with the other is called the angle between them.\n\nIn the words of Euclid:\n\nA plane angle is the inclination to one another of two lines in a plane which meet one another and do not lie in a straight line.\n\n### Rectilineal\n\nIn the words of Euclid:\n\nAnd when the lines containing the angle are straight, the angle is called rectilineal.\n\nThus the distinction is made between straight-line angles and curved-line angles.\n\nMost of the time the fact that angles are rectilineal is taken for granted.\n\n### Subtend\n\nLet $AB$ be a line segment and $C$ be a point:", null, "The line segment $AB$ is said to subtend the angle $\\angle ACB$.\n\nTwo angles are adjacent if they have an intersecting line in common:", null, "### Containment\n\nThe two lines whose intersection forms an angle are said to contain that angle.\n\n### Vertex\n\nThe point at which the lines containing an angle meet is known as the vertex of that angle.\n\n## Measurement\n\nThe usual units of measurement for angle are as follows:\n\n### Degree\n\nThe degree (of arc) is a measurement of plane angles, symbolized by $\\degrees$.\n\n $\\displaystyle$ $\\displaystyle 1$ degree $\\displaystyle$ $=$ $\\displaystyle 60$ minutes $\\displaystyle$ $=$ $\\displaystyle 60 \\times 60 = 3600$ seconds $\\displaystyle$ $=$ $\\displaystyle \\dfrac 1 {360}$ full angle (by definition)\n\n### Minute\n\nThe minute (of arc) is a measurement of plane angles, symbolized by $'$.\n\n$1$ minute $= 60$ seconds (of arc) $= \\dfrac 1 {60}$ of a degree of arc.\n\n### Second\n\nThe second (of arc) is a measurement of plane angles, symbolized by $''$.\n\n$1''$ is defined as $\\dfrac 1 {60}$ of a minute of arc, or $\\dfrac 1 {3600}$ of a degree of arc.\n\nThe radian is a measure of plane angles symbolized either by the word $\\radians$ or without any unit.\n\nRadians are pure numbers, as they are ratios of lengths. The addition of $\\radians$ is merely for clarification.\n\n$1 \\radians$ is the angle subtended at the center of a circle by an arc whose length is equal to the radius:", null, "## Types of Angle\n\nAngles can be divided into categories:\n\n### Zero Angle\n\nThe zero angle is an angle the measure of which is $0$ regardless of the unit of measurement.\n\n### Acute Angle\n\nAn acute angle is an angle which has a measure between that of a right angle and that of a zero angle.\n\n### Right Angle\n\nA right angle is an angle that is equal to half of a straight angle.\n\n### Obtuse Angle\n\nAn obtuse angle is an angle which has a measurement between those of a right angle and a straight angle.\n\n### Straight Angle\n\nA straight angle is defined to be the angle formed by the two parts of a straight line from a point on that line.\n\n### Reflex Angle\n\nA reflex angle is an angle which has a measure between that of a straight angle and that of a full angle.\n\n### Full Angle\n\nA full angle is an angle equivalent to one full rotation.\n\nIt is possible to consider angles outside the $\\left[{0^\\circ \\,.\\,.\\, 360^\\circ}\\right]$ or $\\left[{0 \\,.\\,.\\, 2 \\pi}\\right]$ range.\n\nHowever, in geometric contexts it is usually preferable to convert these to angles inside this range by adding or subtracting multiples of a full angle.\n\n## Directed versus Undirected Angles\n\nThe most basic definition of angle is an undirected angle on the interval $\\left[{0^\\circ \\,.\\,.\\, 180^\\circ}\\right]$ or $\\left[{0 \\,.\\,.\\, \\pi}\\right]$.\n\nThis definition is often insufficient, in cases such as the external angles of a polygon.\n\nTherefore, angles are most commonly defined in one of two ways:\n\n$(1): \\quad$ Undirected angles on the interval $\\left[{0^\\circ \\,.\\,.\\, 360^\\circ}\\right]$ or $\\left[{0 \\,.\\,.\\, 2 \\pi}\\right]$.\n$(2): \\quad$ Directed angles, with the positive direction being counterclockwise from a given line (or, if no line is specified, from the $x$-axis).\nThis definition is more commonly found in applied mathematics, such as in surveying, navigation, or, more colloquially, in a $720^\\circ$ degree spin in skateboarding, skiing, etc.\n\n## Also see\n\n• Results about angles can be found here." ]
[ null, "https://proofwiki.org/w/images/thumb/3/30/Subtend.png/250px-Subtend.png", null, "https://proofwiki.org/w/images/thumb/7/70/AdjacentAngles.png/250px-AdjacentAngles.png", null, "https://proofwiki.org/w/images/thumb/8/87/Radian.png/300px-Radian.png", null ]
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https://www.circuitbread.com/textbooks/introduction-to-electricity-magnetism-and-circuits/magnetic-forces-and-fields/chapter-8-review
[ "", null, "# Chapter 8 Review\n\n## Key Terms\n\ncosmic rays\ncomprised of particles that originate mainly from outside the solar system and reach Earth\n\ncyclotron\ndevice used to accelerate charged particles to large kinetic energies\n\ndees\nlarge metal containers used in cyclotrons that serve contain a stream of charged particles as their speed is increased\n\ngauss\n\nunit of the magnetic field strength;\n\nHall effect\ncreation of voltage across a current-carrying conductor by a magnetic field\n\nhelical motion\nsuperposition of circular motion with a straight-line motion that is followed by a charged particle moving in a region of magnetic field at an angle to the field\n\nmagnetic dipole\nclosed-current loop\n\nmagnetic dipole moment\nterm\n\nof the magnetic dipole, also called\n\nmagnetic field lines\ncontinuous curves that show the direction of a magnetic field; these lines point in the same direction as a compass points, toward the magnetic south pole of a bar magnet\n\nmagnetic force\nforce applied to a charged particle moving through a magnetic field\n\nmass spectrometer\ndevice that separates ions according to their charge-to-mass ratios\n\nmotor (dc)\nloop of wire in a magnetic field; when current is passed through the loops, the magnetic field exerts torque on the loops, which rotates a shaft; electrical energy is converted into mechanical work in the process\n\nnorth magnetic pole\ncurrently where a compass points to north, near the geographic North Pole; this is the effective south pole of a bar magnet but has flipped between the effective north and south poles of a bar magnet multiple times over the age of Earth\n\nright-hand rule-1\nusing your right hand to determine the direction of either the magnetic force, velocity of a charged particle, or magnetic field\n\nsouth magnetic pole\ncurrently where a compass points to the south, near the geographic South Pole; this is the effective north pole of a bar magnet but has flipped just like the north magnetic pole\n\ntesla\nSI unit for magnetic field:\n\nvelocity selector\napparatus where the crossed electric and magnetic fields produce equal and opposite forces on a charged particle moving with a specific velocity; this particle moves through the velocity selector not affected by either field while particles moving with different velocities are deflected by the apparatus\n\n## Key Equations\n\n Force on a charge in a magnetic field", null, "Magnitude of magnetic force", null, "Radius of a particle’s path in a magnetic field", null, "Period of a particle’s motion in a magnetic field", null, "Force on a current-carrying wire in a uniform magnetic field", null, "Magnetic dipole moment", null, "Torque on a current loop", null, "Energy of a magnetic dipole", null, "Drift velocity in crossed electric and magnetic fields", null, "Hall potential", null, "Hall potential in terms of drift velocity", null, "Charge-to-mass ratio in a mass spectrometer", null, "Maximum speed of a particle in a cyclotron", null, "## Summary\n\n#### 8.1 Magnetism and Its Historical Discoveries\n\n• Magnets have two types of magnetic poles, called the north magnetic pole and the south magnetic pole. North magnetic poles are those that are attracted toward Earth’s geographic North Pole.\n• Like poles repel and unlike poles attract.\n• Discoveries of how magnets respond to currents by Oersted and others created a framework that led to the invention of modern electronic devices, electric motors, and magnetic imaging technology.\n\n#### 8.2 Magnetic Fields and Lines\n\n• Charges moving across a magnetic field experience a force determined by", null, "The force is perpendicular to the plane formed by", null, "and", null, "• The direction of the force on a moving charge is given by the right hand rule 1 (RHR-1): Sweep your fingers in a velocity, magnetic field plane. Start by pointing them in the direction of velocity and sweep towards the magnetic field. Your thumb points in the direction of the magnetic force for positive charges.\n• Magnetic fields can be pictorially represented by magnetic field lines, which have the following properties:\n1. The field is tangent to the magnetic field line.\n2. Field strength is proportional to the line density.\n3. Field lines cannot cross.\n4. Field lines form continuous, closed loops.\n• Magnetic poles always occur in pairs of north and south—it is not possible to isolate north and south poles.\n\n#### 8.3 Motion of a Charged Particle in a Magnetic Field\n\n• A magnetic force can supply centripetal force and cause a charged particle to move in a circular path of radius", null, "• The period of circular motion for a charged particle moving in a magnetic field perpendicular to the plane of motion is", null, "• Helical motion results if the velocity of the charged particle has a component parallel to the magnetic field as well as a component perpendicular to the magnetic field.\n\n#### 8.4 Magnetic Force on a Current-Carrying Conductor\n\n• An electrical current produces a magnetic field around the wire.\n• The directionality of the magnetic field produced is determined by the right hand rule-2, where your thumb points in the direction of the current and your fingers wrap around the wire in the direction of the magnetic field.\n• The magnetic force on current-carrying conductors is given by", null, "where", null, "is the current and", null, "is the length of a wire in a uniform magnetic field", null, "#### 8.5 Force and Torque on a Current Loop\n\n• The net force on a current-carrying loop of any plane shape in a uniform magnetic field is zero.\n• The net torque", null, "on a current-carrying loop of any shape in a uniform magnetic field is calculated using", null, "where", null, "is the magnetic dipole moment and", null, "is the magnetic field strength.\n• The magnetic dipole moment", null, "is the product of the number of turns of wire", null, "the current in the loop", null, "and the area of the loop", null, "or", null, "#### 8.6 The Hall Effect\n\n• Perpendicular electric and magnetic fields exert equal and opposite forces for a specific velocity of entering particles, thereby acting as a velocity selector. The velocity that passes through undeflected is calculated by\n• The Hall effect can be used to measure the sign of the majority of charge carriers for metals. It can also be used to measure a magnetic field.\n\n#### 8.7 Applications of Magnetic Forces and Fields\n\n• A mass spectrometer is a device that separates ions according to their charge-to-mass ratios by first sending them through a velocity selector, then a uniform magnetic field.\n• Cyclotrons are used to accelerate charged particles to large kinetic energies through applied electric and magnetic fields.\n\n8.1 a.\n\nb.\n\nc.\n\nd.\n\n8.2 a.\n\ntoward the south; b.\n\n8.3 a. bends upward; b. bends downward\n\n8.4 a. perpendicular ; b. anti-aligned\n\n8.5 a.\n\nb.\n\n8.6\n\n## Conceptual Questions\n\n#### 8.2 Magnetic Fields and Lines\n\n1. Discuss the similarities and differences between the electrical force on a charge and the magnetic force on a charge.\n\n2. (a) Is it possible for the magnetic force on a charge moving in a magnetic field to be zero? (b) Is it possible for the electric force on a charge moving in an electric field to be zero? (c) Is it possible for the resultant of the electric and magnetic forces on a charge moving simultaneously through both fields to be zero?\n\n#### 8.3 Motion of a Charged Particle in a Magnetic Field\n\n3. At a given instant, an electron and a proton are moving with the same velocity in a constant magnetic field. Compare the magnetic forces on these particles. Compare their accelerations.\n\n4. Does increasing the magnitude of a uniform magnetic field through which a charge is traveling necessarily mean increasing the magnetic force on the charge? Does changing the direction of the field necessarily mean a change in the force on the charge?\n\n5. An electron passes through a magnetic field without being deflected. What do you conclude about the magnetic field?\n\n6. If a charged particle moves in a straight line, can you conclude that there is no magnetic field present?\n\n7. How could you determine which pole of an electromagnet is north and which pole is south?\n\n#### 8.4 Magnetic Force on a Current-Carrying Conductor\n\n8. Describe the error that results from accidently using your left rather than your right hand when determining the direction of a magnetic force.\n\n9. Considering the magnetic force law, are the velocity and magnetic field always perpendicular? Are the force and velocity always perpendicular? What about the force and magnetic field?\n\n10. Why can a nearby magnet distort a cathode ray tube television picture?\n\n11. A magnetic field exerts a force on the moving electrons in a current carrying wire. What exerts the force on a wire?\n\n12. There are regions where the magnetic field of earth is almost perpendicular to the surface of Earth. What difficulty does this cause in the use of a compass?\n\n#### 8.6 The Hall Effect\n\n13. Hall potentials are much larger for poor conductors than for good conductors. Why?\n\n#### 8.7 Applications of Magnetic Forces and Fields\n\n14. Describe the primary function of the electric field and the magnetic field in a cyclotron.\n\n## Problems\n\n#### 8.2 Magnetic Fields and Lines\n\n15. What is the direction of the magnetic force on a positive charge that moves as shown in each of the six cases?\n\n16. Repeat previous exercise for a negative charge.\n\n17. What is the direction of the velocity of a negative charge that experiences the magnetic force shown in each of the three cases, assuming it moves perpendicular to\n\n18. Repeat previous exercise for a positive charge.\n\n19. What is the direction of the magnetic field that produces the magnetic force on a positive charge as shown in each of the three cases, assuming\n\nis perpendicular to\n\n?\n\n20. Repeat previous exercise for a negative charge.\n\n21. (a) Aircraft sometimes acquire small static charges. Suppose a supersonic jet has a\n\ncharge and flies due west at a speed of\n\nover Earth’s south magnetic pole, where the\n\nmagnetic field points straight up. What are the direction and the magnitude of the magnetic force on the plane? (b) Discuss whether the value obtained in part (a) implies this is a significant or negligible effect.\n\n22. (a) A cosmic ray proton moving toward Earth at\n\nexperiences a magnetic force of\n\nWhat is the strength of the magnetic field if there is a\n\nangle between it and the proton’s velocity? (b) Is the value obtained in part a. consistent with the known strength of Earth’s magnetic field on its surface? Discuss.\n\n23. An electron moving at\n\nin a\n\nmagnetic field experiences a magnetic force of\n\nWhat angle does the velocity of the electron make with the magnetic field? There are two answers.\n\n24. (a) A physicist performing a sensitive measurement wants to limit the magnetic force on a moving charge in her equipment to less than\n\nWhat is the greatest the charge can be if it moves at a maximum speed of\n\nin Earth’s field? (b) Discuss whether it would be difficult to limit the charge to less than the value found in (a) by comparing it with typical static electricity and noting that static is often absent.\n\n#### 8.3 Motion of a Charged Particle in a Magnetic Field\n\n25. A cosmic-ray electron moves at\n\nperpendicular to Earth’s magnetic field at an altitude where the field strength is\n\nWhat is the radius of the circular path the electron follows?\n\n26. (a) Viewers of Star Trek have heard of an antimatter drive on the Starship Enterprise. One possibility for such a futuristic energy source is to store antimatter charged particles in a vacuum chamber, circulating in a magnetic field, and then extract them as needed. Antimatter annihilates normal matter, producing pure energy. What strength magnetic field is needed to hold antiprotons, moving at\n\nin a circular path\n\nin radius? Antiprotons have the same mass as protons but the opposite (negative) charge. (b) Is this field strength obtainable with today’s technology or is it a futuristic possibility?\n\n27. (a) An oxygen-\n\nion with a mass of\n\ntravels at\n\nperpendicular to a\n\nmagnetic field, which makes it move in a circular arc with a\n\nradius. What positive charge is on the ion? (b) What is the ratio of this charge to the charge of an electron? (c) Discuss why the ratio found in (b) should be an integer.\n\n28. An electron in a TV CRT moves with a speed of\n\nin a direction perpendicular to Earth’s field, which has a strength of\n\n(a) What strength electric field must be applied perpendicular to the Earth’s field to make the electron moves in a straight line? (b) If this is done between plates separated by\n\nwhat is the voltage applied? (Note that TVs are usually surrounded by a ferromagnetic material to shield against external magnetic fields and avoid the need for such a correction.)\n\n29. (a) At what speed will a proton move in a circular path of the same radius as the electron in the previous exercise? (b) What would the radius of the path be if the proton had the same speed as the electron? (c) What would the radius be if the proton had the same kinetic energy as the electron? (d) The same momentum?\n\n30. (a) What voltage will accelerate electrons to a speed of\n\n? (b) Find the radius of curvature of the path of a proton accelerated through this potential in a\n\nfield and compare this with the radius of curvature of an electron accelerated through the same potential.\n\n31. An alpha-particle\n\ntravels in a circular path of radius\n\nin a uniform magnetic field of magnitude\n\n(a) What is the speed of the particle? (b) What is the kinetic energy in electron-volts? (c) Through what potential difference must the particle be accelerated in order to give it this kinetic energy?\n\n32. A particle of charge\n\nand mass\n\nis accelerated from rest through a potential difference\n\nafter which it encounters a uniform magnetic field\n\nIf the particle moves in a plane perpendicular to\n\nwhat is the radius of its circular orbit?\n\n#### 8.4 Magnetic Force on a Current-Carrying Conductor\n\n33. What is the direction of the magnetic force on the current in each of the six cases?\n\n34. What is the direction of a current that experiences the magnetic force shown in each of the three cases, assuming the current runs perpendicular to\n\n?\n\n35. What is the direction of the magnetic field that produces the magnetic force shown on the currents in each of the three cases, assuming\n\nis perpendicular to\n\n?\n\n36. (a) What is the force per meter on a lightning bolt at the equator that carries\n\nperpendicular to Earth’s\n\n? (b) What is the direction of the force if the current is straight up and Earth’s field direction is due north, parallel to the ground?\n\n37. (a) A dc power line for a light-rail system carries\n\nat an angle of\n\nto Earth’s\n\nfield. What is the force on a\n\nsection of this line? (b) Discuss practical concerns this presents, if any.\n\n38. A wire carrying a\n\ncurrent passes between the poles of a strong magnet that is perpendicular to its field and experiences a\n\nforce on the\n\nof wire in the field. What is the average field strength?\n\n#### 8.5 Force and Torque on a Current Loop\n\n39. (a) By how many percent is the torque of a motor decreased if its permanent magnets lose\n\nof their strength? (b) How many percent would the current need to be increased to return the torque to original values?\n\n40. (a) What is the maximum torque on a\n\n-turn square loop of wire\n\non a side that carries a\n\ncurrent in a\n\nfield? (b) What is the torque when\n\nis\n\n?\n\n41. Find the current through a loop needed to create a maximum torque of\n\nThe loop has\n\nsquare turns that are\n\non a side and is in a uniform\n\nmagnetic field.\n\n42. Calculate the magnetic field strength needed on a\n\n-turn square loop\n\non a side to create a maximum torque of\n\nif the loop is carrying\n\n43. Since the equation for torque on a current-carrying loop is τ = NIAB sin\n\nthe units of\n\nmust equal units of\n\nVerify this.\n\n44. (a) At what angle\n\nis the torque on a current loop\n\nof maximum? (b)\n\nof maximum? (c)\n\nof maximum?\n\n45. A proton has a magnetic field due to its spin. The field is similar to that created by a circular current loop\n\nin radius with a current of\n\nFind the maximum torque on a proton in a\n\nfield. (This is a significant torque on a small particle.)\n\n46. (a) A\n\nis vertical, with its axis on an east-west line. A current of\n\ncirculates clockwise in the loop when viewed from the east. Earth’s field here is due north, parallel to the ground, with a strength of\n\nWhat are the direction and magnitude of the torque on the loop? (b) Does this device have any practical applications as a motor?\n\n47. Repeat the previous problem, but with the loop lying flat on the ground with its current circulating counterclockwise (when viewed from above) in a location where Earth’s field is north, but at an angle\n\nbelow the horizontal and with a strength of\n\n#### 8.6 The Hall Effect\n\n48. A strip of copper is placed in a uniform magnetic field of magnitude\n\nThe Hall electric field is measured to be\n\n(a) What is the drift speed of the conduction electrons? (b) Assuming that\n\nelectrons per cubic meter and that the cross-sectional area of the strip is\n\ncalculate the current in the strip. (c) What is the Hall coefficient\n\n?\n\n49. The cross-sectional dimensions of the copper strip shown are\n\nby\n\nThe strip carries a current of\n\nand it is placed in a magnetic field of magnitude\n\nWhat are the value and polarity of the Hall potential in the copper strip?\n\n50. The magnitudes of the electric and magnetic fields in a velocity selector are\n\nand\n\nrespectively. (a) What speed must a proton have to pass through the selector? (b) Also calculate the speeds required for an alpha-particle and a singly ionized\n\natom to pass through the selector.\n\n51. A charged particle moves through a velocity selector at constant velocity. In the selector,\n\nand\n\nWhen the electric field is turned off, the charged particle travels in a circular path of radius\n\nDetermine the charge-to-mass ratio of the particle.\n\n52. A Hall probe gives a reading of\n\nfor a current of\n\nwhen it is placed in a magnetic field of\n\nWhat is the magnetic field in a region where the reading is\n\nfor\n\nof current?\n\n#### 8.7 Applications of Magnetic Forces and Fields\n\n53. A physicist is designing a cyclotron to accelerate protons to one-tenth the speed of light. The magnetic field will have a strength of\n\nDetermine (a) the rotational period of the circulating protons and (b) the maximum radius of the protons’ orbit.\n\n54. The strengths of the fields in the velocity selector of a Bainbridge mass spectrometer are\n\nand\n\nand the strength of the magnetic field that separates the ions is\n\nA stream of singly charged\n\nions is found to bend in a circular arc of radius\n\nWhat is the mass of the\n\nions?\n\n55. The magnetic field in a cyclotron is\n\nand the maximum orbital radius of the circulating protons is\n\n(a) What is the kinetic energy of the protons when they are ejected from the cyclotron? (b) What is this energy in\n\n? (c) Through what potential difference would a proton have to be accelerated to acquire this kinetic energy? (d) What is the period of the voltage source used to accelerate the protons? (e) Repeat the calculations for alpha-particles.\n\n56. A mass spectrometer is being used to separate common oxygen-\n\nfrom the much rarer oxygen-\n\ntaken from a sample of old glacial ice. (The relative abundance of these oxygen isotopes is related to climatic temperature at the time the ice was deposited.) The ratio of the masses of these two ions is\n\nto\n\nthe mass of oxygen-\n\nis\n\nand they are singly charged and travel at\n\nin a\n\nmagnetic field. What is the separation between their paths when they hit a target after traversing a semicircle?\n\n57. (a) Triply charged uranium-\n\nand uranium-\n\nions are being separated in a mass spectrometer. (The much rarer uranium-\n\nis used as reactor fuel.) The masses of the ions are\n\nand\n\nrespectively, and they travel at\n\nin a\n\nfield. What is the separation between their paths when they hit a target after traversing a semicircle? (b) Discuss whether this distance between their paths seems to be big enough to be practical in the separation of uranium-\n\nfrom uranium-\n\n58. Calculate the magnetic force on a hypothetical particle of charge\n\nmoving with a velocity of\n\nin a magnetic field of\n\n59. Repeat the previous problem with a new magnetic field of\n\n60. An electron is projected into a uniform magnetic field\n\nwith a velocity of\n\nWhat is the magnetic force on the electron?\n\n61. The mass and charge of a water droplet are\n\nand\n\nrespectively. If the droplet is given an initial horizontal velocity of\n\nwhat magnetic field will keep it moving in this direction? Why must gravity be considered here?\n\n62. Four different proton velocities are given. For each case, determine the magnetic force on the proton in terms of\n\nand\n\n63. An electron of kinetic energy\n\npasses between parallel plates that are\n\napart and kept at a potential difference of\n\nWhat is the strength of the uniform magnetic field\n\nthat will allow the electron to travel undeflected through the plates? Assume\n\nand\n\nare perpendicular.\n\n64. An alpha-particle\n\nmoving with a velocity\n\nenters a region where\n\nand\n\nWhat is the initial force on it?\n\n65. An electron moving with a velocity\n\nenters a region where there is a uniform electric field and a uniform magnetic field. The magnetic field is given by\n\nIf the electron travels through a region without being deflected, what is the electric field?\n\n66. At a particular instant, an electron is traveling west to east with a kinetic energy of\n\nEarth’s magnetic field has a horizontal component of\n\nnorth and a vertical component of\n\ndown. (a) What is the path of the electron? (b) What is the radius of curvature of the path?\n\n67. Repeat the calculations of the previous problem for a proton with the same kinetic energy.\n\n68. What magnetic field is required in order to confine a proton moving with a speed of\n\nto a circular orbit of radius\n\n?\n\n69. An electron and a proton move with the same speed in a plane perpendicular to a uniform magnetic field. Compare the radii and periods of their orbits.\n\n70. A proton and an alpha-particle have the same kinetic energy and both move in a plane perpendicular to a uniform magnetic field. Compare the periods of their orbits.\n\n71. A singly charged ion takes\n\nto complete eight revolutions in a uniform magnetic field of magnitude\n\nWhat is the mass of the ion?\n\n72. A particle moving downward at a speed of\n\nenters a uniform magnetic field that is horizontal and directed from east to west. (a) If the particle is deflected initially to the north in a circular arc, is its charge positive or negative? (b) If\n\nand the charge-to-mass ratio\n\nof the particle is\n\nwhat is the radius of the path? (c) What is the speed of the particle after it has moved in the field for\n\n? for\n\n?\n\n73. A proton, deuteron, and an alpha-particle are all accelerated through the same potential difference. They then enter the same magnetic field, moving perpendicular to it. Compute the ratios of the radii of their circular paths. Assume that\n\nand\n\n74. A singly charged ion is moving in a uniform magnetic field of\n\ncompletes\n\nrevolutions in\n\nIdentify the ion.\n\n75. Two particles have the same linear momentum, but particle\n\nhas four times the charge of particle\n\nIf both particles move in a plane perpendicular to a uniform magnetic field, what is the ratio\n\nof the radii of their circular orbits?\n\n76. A uniform magnetic field of magnitude\n\nis directed parallel to the\n\n-axis. A proton enters the field with a velocity\n\nand travels in a helical path with a radius of\n\n(a) What is the value of\n\n? (b) What is the time required for one trip around the helix? (c) Where is the proton\n\nafter entering the field?\n\n77. An electron moving at\n\nenters a magnetic field that makes a\n\nangle with the\n\n-axis of magnitude\n\nCalculate the (a) pitch and (b) radius of the trajectory.\n\n78. (a) A\n\n-long section of cable carrying current to a car starter motor makes an angle of\n\nwith Earth’s\n\nfield. What is the current when the wire experiences a force of\n\n? (b) If you run the wire between the poles of a strong horseshoe magnet, subjecting\n\nof it to a\n\nwhat force is exerted on this segment of wire?\n\n79. (a) What is the angle between a wire carrying an\n\ncurrent and the\n\nfield it is in if\n\nof the wire experiences a magnetic force of\n\n? (b) What is the force on the wire if it is rotated to make an angle of\n\nwith the field?\n\n80. A\n\n-long segment of wire lies along the\n\n-axis and carries a current of\n\nin the positive\n\n-direction. Around the wire is the magnetic field of\n\nFind the magnetic force on this segment.\n\n81. A\n\nsection of a long, straight wire carries a current of\n\nwhile in a uniform magnetic field of magnitude\n\nCalculate the magnitude of the force on the section if the angle between the field and the direction of the current is (a)\n\n(b)\n\n(c)\n\nor (d)\n\n82. An electromagnet produces a magnetic field of magnitude\n\nthroughout a cylindrical region of radius\n\nA straight wire carrying a current of\n\npasses through the field as shown in the accompanying figure. What is the magnetic force on the wire?\n\n83. The current loop shown in the accompanying figure lies in the plane of the page, as does the magnetic field. Determine the net force and the net torque on the loop if\n\nand\n\n84. A circular coil of radius\n\nis wound with five turns and carries a current of\n\nIf the coil is placed in a uniform magnetic field of strength\n\nwhat is the maximum torque on it?\n\n85. A circular coil of wire of radius\n\nhas\n\nturns and carries a current of\n\nThe coil lies in a magnetic field of magnitude\n\nthat is directed parallel to the plane of the coil. (a) What is the magnetic dipole moment of the coil? (b) What is the torque on the coil?\n\n86. A current-carrying coil in a magnetic field experiences a torque that is\n\nof the maximum possible torque. What is the angle between the magnetic field and the normal to the plane of the coil?\n\n87. A\n\nby\n\nrectangular current loop carries a current of\n\nWhat is the magnetic dipole moment of the loop?\n\n88. A circular coil with\n\n(a) What current through the coil results in a magnetic dipole moment of\n\n? (b) What is the maximum torque that the coil will experience in a uniform field of strength\n\n? (c) If the angle between\n\nand\n\nis\n\nwhat is the magnitude of the torque on the coil? (d) What is the magnetic potential energy of coil for this orientation?\n\n89. The current through a circular wire loop of radius\n\nis\n\n(a) Calculate the magnetic dipole moment of the loop. (b) What is the torque on the loop if it is in a uniform\n\nmagnetic field such that\n\nand\n\nare directed at\n\nto each other? (c) For this position, what is the potential energy of the dipole?\n\n90. A wire of length\n\nis wound into a single-turn planar loop. The loop carries a current of\n\nand it is placed in a uniform magnetic field of strength\n\n(a) What is the maximum torque that the loop will experience if it is square? (b) If it is circular? (c) At what angle relative to\n\nwould the normal to the circular coil have to be oriented so that the torque on it would be the same as the maximum torque on the square coil?\n\n91. Consider an electron rotating in a circular orbit of radius\n\nShow that the magnitudes of the magnetic dipole moment\n\nand the angular momentum\n\nof the electron are related by:\n\n92. The Hall effect is to be used to find the sign of charge carriers in a semiconductor sample. The probe is placed between the poles of a magnet so that magnetic field is pointed up. A current is passed through a rectangular sample placed horizontally. As current is passed through the sample in the east direction, the north side of the sample is found to be at a higher potential than the south side. Decide if the number density of charge carriers is positively or negatively charged.\n\n93. The density of charge carriers for copper is\n\nelectrons per cubic meter. What will be the Hall voltage reading from a probe made up of\n\ncopper plate when a current of\n\nis passed through it in a magnetic field of\n\nperpendicular to the\n\n94. The Hall effect is to be used to find the density of charge carriers in an unknown material. A Hall voltage\n\nfor\n\ncurrent is observed in a\n\nmagnetic field for a rectangular sample with length\n\nwidth\n\nand height\n\nDetermine the density of the charge carriers.\n\n95. Show that the Hall voltage across wires made of the same material, carrying identical currents, and subjected to the same magnetic field is inversely proportional to their diameters. (Hint: Consider how drift velocity depends on wire diameter.)\n\n96. A velocity selector in a mass spectrometer uses a\n\nmagnetic field. (a) What electric field strength is needed to select a speed of\n\n? (b) What is the voltage between the plates if they are separated by\n\n?\n\n97. Find the radius of curvature of the path of a\n\nproton moving perpendicularly to the\n\nfield of a cyclotron.\n\n98. Unreasonable results To construct a non-mechanical water meter, a\n\nmagnetic field is placed across the supply water pipe to a home and the Hall voltage is recorded. (a) Find the flow rate through a\n\n-diameter pipe if the Hall voltage is\n\n(b) What would the Hall voltage be for the same flow rate through a\n\n-diameter pipe with the same field applied?\n\n99. Unreasonable results A charged particle having mass\n\n(that of a helium atom) moving at\n\nperpendicular to a\n\nmagnetic field travels in a circular path of radius\n\n(a) What is the charge of the particle? (b) What is unreasonable about this result? (c) Which assumptions are responsible?\n\n100. Unreasonable results An inventor wants to generate\n\npower by moving a\n\n-long wire perpendicular to Earth’s\n\nfield. (a) Find the speed with which the wire must move. (b) What is unreasonable about this result? (c) Which assumption is responsible?\n\n101. Unreasonable results Frustrated by the small Hall voltage obtained in blood flow measurements, a medical physicist decides to increase the applied magnetic field strength to get a\n\noutput for blood moving at\n\nin a\n\n-diameter vessel. (a) What magnetic field strength is needed? (b) What is unreasonable about this result? (c) Which premise is responsible?\n\n## Challenge Problems\n\n102. A particle of charge\n\nand mass\n\nmoves with velocity\n\npointed in the\n\n-direction as it crosses the\n\n-axis at\n\nat a particular time. There is a negative charge\n\nfixed at the origin, and there exists a uniform magnetic field\n\npointed in the\n\n-direction. It is found that the particle describes a circle of radius\n\nFind\n\nin terms of the given quantities.\n\n103. A proton of speed\n\nenters a region of uniform magnetic field of\n\nat an angle of\n\nto the magnetic field. In the region of magnetic field proton describes a helical path with radius\n\nand pitch\n\n(distance between loops). Find\n\nand\n\n104. A particle’s path is bent when it passes through a region of non-zero magnetic field although its speed remains unchanged. This is very useful for “beam steering” in particle accelerators. Consider a proton of speed\n\nentering a region of uniform magnetic field\n\nover a\n\n-wide region. Magnetic field is perpendicular to the velocity of the particle. By how much angle will the path of the proton be bent? (Hint: The particle comes out tangent to a circle.)\n\n105. In a region a non-uniform magnetic field exists such that\n\nand\n\nwhere\n\nis a constant. At some time\n\na wire of length\n\nis carrying a current\n\nis located along the\n\n-axis from origin to\n\nFind the magnetic force on the wire at this instant in time.\n\n106. A copper rod of mass\n\nand length\n\nis hung from the ceiling using two springs of spring constant\n\nA uniform magnetic field of magnitude\n\npointing perpendicular to the rod and spring (coming out of the page in the figure) exists in a region of space covering a length\n\nof the copper rod. The ends of the rod are then connected by flexible copper wire across the terminals of a battery of voltage\n\nDetermine the change in the length of the springs when\n\ncurrent\n\nruns through the copper rod in the direction shown in figure. (Ignore any force by the flexible wire.)\n\n107. The accompanied figure shows an arrangement for measuring mass of ions by an instrument called the mass spectrometer. An ion of mass\n\nand charge\n\nis produced essentially at rest in source\n\na chamber in which a gas discharge is taking place. The ion is accelerated by a potential difference\n\nand allowed to enter a region of constant magnetic field\n\nIn the uniform magnetic field region, the ion moves in a semicircular path striking a photographic plate at a distance\n\nfrom the entry point. Derive a formula for mass\n\nin terms of\n\nand\n\nand pivoted along a central support. The two ends of the wire are touching a brush that is connected to a dc power source. The structure is between the poles of a magnet such that we can assume there is a uniform magnetic field on the wire. In terms of a coordinate system with origin at the center of the ring, magnetic field is\n\nand the ring rotates about the\n\n-axis. Find the torque on the ring when it is not in the\n\n-plane.\n\n109. A long-rigid wire lies along the\n\n-axis and carries a current of\n\nin the positive\n\n-direction. Around the wire is the magnetic field\n\nwith\n\nin meters and\n\nin millitesla. Calculate the magnetic force on the segment of wire between\n\nand\n\n110. A circular loop of wire of area\n\ncarries a current of\n\nAt a particular instant, the loop lies in the\n\n-plane and is subjected to a magnetic field\n\nAs viewed from above the\n\n-plane, the current is circulating clockwise. (a) What is the magnetic dipole moment of the current loop? (b) At this instant, what is the magnetic torque on the loop?\n\n## Candela Citations", null, "Swipe left and right to change pages.", null, "", null, "" ]
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https://www.dezyre.com/recipes/calculate-time-taken-by-each-step-for-loop
[ "How to calculate the time taken by each step in a for loop?\nMACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS\n\n# How to calculate the time taken by each step in a for loop?\n\nThis recipe helps you calculate the time taken by each step in a for loop\n\n0\n\n## Recipe Objective\n\nTime elapsed to execute a function is a crucial element in a data scientist's job specifically when you have to deal with large datasets. Since there are different approaches to do the same task, time required to these tasks plays an important role when we deal with large dataset. This recipe demonstrates us to calculate the time taken by each step in a for loop.\n\nWe will use Sys.time() function to carry out this task\n\n## Example:\n\nWe will calculate the squares of numbers from 1 to 4 using for loop and calculate the time required by each step\n\n``` for (i in 1:4){ # start time stamp start = Sys.time() print(i^2) # end time stamp end =Sys.time() #Time required for each step elapsed_time = end - start print(elapsed_time) } ```\n``` 1\nTime difference of 0 secs\n 4\nTime difference of 0 secs\n 9\nTime difference of 0 secs\n 16\nTime difference of 0 secs\n```\n\n#### Relevant Projects\n\n##### Time Series Forecasting with LSTM Neural Network Python\nDeep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.\n\n##### Credit Card Fraud Detection as a Classification Problem\nIn this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.\n\n##### Machine Learning project for Retail Price Optimization\nIn this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.\n\n##### Resume parsing with Machine learning - NLP with Python OCR and Spacy\nIn this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.\n\n##### Build a Similar Images Finder with Python, Keras, and Tensorflow\nBuild your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.\n\n##### Data Science Project - Instacart Market Basket Analysis\nData Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.\n\n##### Ecommerce product reviews - Pairwise ranking and sentiment analysis\nThis project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.\n\n##### Customer Market Basket Analysis using Apriori and Fpgrowth algorithms\nIn this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.\n\n##### Mercari Price Suggestion Challenge Data Science Project\nData Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.\n\n##### Customer Churn Prediction Analysis using Ensemble Techniques\nIn this machine learning churn project, we implement a churn prediction model in python using ensemble techniques." ]
[ null ]
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http://arxiv-export-lb.library.cornell.edu/abs/2301.13781v2
[ "math.PR\n\n# Title: Scaling limits for fractional polyharmonic Gaussian fields\n\nAbstract: This work is concerned with fractional Gaussian fields, i.e. Gaussian fields whose covariance operator is given by the inverse fractional Laplacian $(-\\Delta)^{-s}$ (where, in particular, we include the case $s >1$). We define a lattice discretization of these fields and show that their scaling limits -- with respect to the optimal Besov space topology (up to an endpoint case) -- are the original continuous fields. As a byproduct, in dimension $d<2s$, we prove the convergence in distribution of the maximum of the fields. A key tool in the proof is a sharp error estimate for the natural finite difference scheme for $(-\\Delta)^s$ under minimal regularity assumptions, which is also of independent interest.\n Comments: v2: minor corrections, additional references Subjects: Probability (math.PR); Analysis of PDEs (math.AP); Numerical Analysis (math.NA) Cite as: arXiv:2301.13781 [math.PR] (or arXiv:2301.13781v2 [math.PR] for this version)\n\n## Submission history\n\nFrom: Florian Schweiger [view email]\n[v1] Tue, 31 Jan 2023 17:31:18 GMT (3911kb,D)\n[v2] Mon, 20 Feb 2023 10:16:02 GMT (3912kb,D)\n\nLink back to: arXiv, form interface, contact." ]
[ null ]
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https://help.geogebra.org/topic/how-to-change-the-origin-of-vector
[ "# How to change the origin of vector.\n\nDrako shared this question 3 years ago\n\nI have a vector (4;50°), start in (0,0), but I want start in other point, for example in (4,8).", null, "1\n\nYou can define\n\nu = (4;50°)\n\nA=(4,8)\n\nB=A+u\n\nv=Vector(A,B)\n\nNow you can drag A or the arrow of v wherever you want, the defined translation stays the same as u\n\nchris", null, "1\n\nOh, the process is too long if I have many vectors.\n\nI already knew this method. But, I wanted some more efficient.", null, "", null, "1\n\nHi\n\nYou can move the vector\n\nJust catch him !", null, "1\n\nHello,\n\nwhy don't you construct your own tools?\n\nYour first tool \"Vec_Cartesian\" needs the input objects\n\npoint, number_one, number_two.\n\n\"Point\" is the origin of the vector, and the numbers are the coordinates.\n\nIf you use the name Vec_Cartesian\n\nfor the tool, the vector from (3,2) to (8,4) has the syntax\n\nVec_Cartesian[(3,2),5,2].\n\nYour second tool \"Vec_Polar\" needs the input objects\n\nIf you use Vec_Polar as the name, the vector (4;30°) with origin (6,7) would have the syntax\n\nVec_Polar[(6,7),4,30°]" ]
[ null, "https://accounts.geogebra.org/api/avatar.php", null, "https://accounts.geogebra.org/api/avatar.php", null, "https://help.geogebra.org/public/avatars/default-avatar.svg", null, "https://accounts.geogebra.org/api/avatar.php", null, "https://accounts.geogebra.org/api/avatar.php", null ]
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https://projecteuclid.org/journals/journal-of-the-mathematical-society-of-japan/volume-61/issue-1/Large-time-behavior-of-solutions-to-Schr%C3%B6dinger-equations-with-a/10.2969/jmsj/06110039.full
[ "Translator Disclaimer\nJanuary, 2009 Large time behavior of solutions to Schrödinger equations with a dissipative nonlinearity for arbitrarily large initial data\nNaoyasu KITA, Akihiro SHIMOMURA\nJ. Math. Soc. Japan 61(1): 39-64 (January, 2009). DOI: 10.2969/jmsj/06110039\n\n## Abstract\n\nWe study the asymptotic behavior in time of solutions to the Cauchy problem of nonlinear Schrödinger equations with a long-range dissipative nonlinearity given by $\\lambda |u|^{p-1} u$ in one space dimension, where $1 (namely, $p$ is a critical or subcritical exponent) and $\\lambda$ is a complex constant satisfying Im $\\lambda <0$ and $\\big( (p-1)/2\\sqrt{p} \\big) | Re \\lambda | \\le | Im \\lambda |$ . We present the time decay estimates and the large-time asymptotics of the solution for arbitrarily large initial data, when “$p=3$ ” or “$p<3$ and $p$ is suitably close to $3$ ”.\n\n## Citation\n\nNaoyasu KITA. Akihiro SHIMOMURA. \"Large time behavior of solutions to Schrödinger equations with a dissipative nonlinearity for arbitrarily large initial data.\" J. Math. Soc. Japan 61 (1) 39 - 64, January, 2009. https://doi.org/10.2969/jmsj/06110039\n\n## Information\n\nPublished: January, 2009\nFirst available in Project Euclid: 9 February 2009\n\nzbMATH: 1167.35043\nMathSciNet: MR2272871\nDigital Object Identifier: 10.2969/jmsj/06110039\n\nSubjects:\nPrimary: 35Q55\nSecondary: 35B40\n\nKeywords: asymptotic behavior for large data , critical or subcritical nonlinearity , dissipative nonlinearity , nonlinear Schrödinger equation", null, "", null, "" ]
[ null, "https://projecteuclid.org/Content/themes/SPIEImages/Share_black_icon.png", null, "https://projecteuclid.org/images/journals/cover_jmsj.jpg", null ]
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http://conceptmap.cfapps.io/wikipage?lang=en&name=Fundamental_interaction
[ "# Fundamental interaction\n\nIn physics, the fundamental interactions, also known as fundamental forces, are the interactions that do not appear to be reducible to more basic interactions. There are four fundamental interactions known to exist: the gravitational and electromagnetic interactions, which produce significant long-range forces whose effects can be seen directly in everyday life, and the strong and weak interactions, which produce forces at minuscule, subatomic distances and govern nuclear interactions. Some scientists hypothesize that a fifth force might exist, but these hypotheses remain speculative.\n\nEach of the known fundamental interactions can be described mathematically as a field. The gravitational force is attributed to the curvature of spacetime, described by Einstein's general theory of relativity. The other three are discrete quantum fields, and their interactions are mediated by elementary particles described by the Standard Model of particle physics.\n\nWithin the Standard Model, the strong interaction is carried by a particle called the gluon, and is responsible for quarks binding together to form hadrons, such as protons and neutrons. As a residual effect, it creates the nuclear force that binds the latter particles to form atomic nuclei. The weak interaction is carried by particles called W and Z bosons, and also acts on the nucleus of atoms, mediating radioactive decay. The electromagnetic force, carried by the photon, creates electric and magnetic fields, which are responsible for the attraction between orbital electrons and atomic nuclei which holds atoms together, as well as chemical bonding and electromagnetic waves, including visible light, and forms the basis for electrical technology. Although the electromagnetic force is far stronger than gravity, it tends to cancel itself out within large objects, so over large distances (on the scale of planets and galaxies), gravity tends to be the dominant force.\n\nMany theoretical physicists believe these fundamental forces to be related and to become unified into a single force at very high energies on a minuscule scale, the Planck scale, but particle accelerators cannot produce the enormous energies required to experimentally probe this. Devising a common theoretical framework that would explain the relation between the forces in a single theory is perhaps the greatest goal of today's theoretical physicists. The weak and electromagnetic forces have already been unified with the electroweak theory of Sheldon Glashow, Abdus Salam, and Steven Weinberg for which they received the 1979 Nobel Prize in physics. Progress is currently being made in uniting the electroweak and strong fields within what is called a Grand Unified Theory (GUT).[citation needed] A bigger challenge is to find a way to quantize the gravitational field, resulting in a theory of quantum gravity (QG) which would unite gravity in a common theoretical framework with the other three forces. Some theories, notably string theory, seek both QG and GUT within one framework, unifying all four fundamental interactions along with mass generation within a theory of everything (ToE).\n\n## History\n\n### Classical theory\n\nIn his 1687 theory, Isaac Newton postulated space as an infinite and unalterable physical structure existing before, within, and around all objects while their states and relations unfold at a constant pace everywhere, thus absolute space and time. Inferring that all objects bearing mass approach at a constant rate, but collide by impact proportional to their masses, Newton inferred that matter exhibits an attractive force. His law of universal gravitation mathematically stated it to span the entire universe instantly (despite absolute time), or, if not actually a force,[citation needed] to be instant interaction among all objects (despite absolute space.) As conventionally interpreted, Newton's theory of motion modelled a central force without a communicating medium. Thus Newton's theory violated the first principle of mechanical philosophy, as stated by Descartes, No action at a distance. Conversely, during the 1820s, when explaining magnetism, Michael Faraday inferred a field filling space and transmitting that force. Faraday conjectured that ultimately, all forces unified into one.[citation needed]\n\nIn 1873, James Clerk Maxwell unified electricity and magnetism as effects of an electromagnetic field whose third consequence was light, travelling at constant speed in a vacuum. The electromagnetic field theory contradicted predictions of Newton's theory of motion, unless physical states of the luminiferous aether—presumed to fill all space whether within matter or in a vacuum and to manifest the electromagnetic field—aligned all phenomena and thereby held valid the Newtonian principle relativity or invariance.\n\n### The Standard Model\n\nThe Standard Model of particle physics was developed throughout the latter half of the 20th century. In the Standard Model, the electromagnetic, strong, and weak interactions associate with elementary particles, whose behaviours are modelled in quantum mechanics (QM). For predictive success with QM's probabilistic outcomes, particle physics conventionally models QM events across a field set to special relativity, altogether relativistic quantum field theory (QFT). Force particles, called gauge bosonsforce carriers or messenger particles of underlying fields—interact with matter particles, called fermions. Everyday matter is atoms, composed of three fermion types: up-quarks and down-quarks constituting, as well as electrons orbiting, the atom's nucleus. Atoms interact, form molecules, and manifest further properties through electromagnetic interactions among their electrons absorbing and emitting photons, the electromagnetic field's force carrier, which if unimpeded traverse potentially infinite distance. Electromagnetism's QFT is quantum electrodynamics (QED).\n\nThe electromagnetic interaction was modelled with the weak interaction, whose force carriers are W and Z bosons, traversing the minuscule distance, in electroweak theory (EWT). Electroweak interaction would operate at such high temperatures as soon after the presumed Big Bang, but, as the early universe cooled, split into electromagnetic and weak interactions. The strong interaction, whose force carrier is the gluon, traversing minuscule distance among quarks, is modeled in quantum chromodynamics (QCD). EWT, QCD, and the Higgs mechanism, whereby the Higgs field manifests Higgs bosons that interact with some quantum particles and thereby endow those particles with mass, comprise particle physics' Standard Model (SM). Predictions are usually made using calculational approximation methods, although such perturbation theory is inadequate to model some experimental observations (for instance bound states and solitons.) Still, physicists widely accept the Standard Model as science's most experimentally confirmed theory.\n\nBeyond the Standard Model, some theorists work to unite the electroweak and strong interactions within a Grand Unified Theory (GUT). Some attempts at GUTs hypothesize \"shadow\" particles, such that every known matter particle associates with an undiscovered force particle, and vice versa, altogether supersymmetry (SUSY). Other theorists seek to quantize the gravitational field by the modelling behaviour of its hypothetical force carrier, the graviton and achieve quantum gravity (QG). One approach to QG is loop quantum gravity (LQG). Still other theorists seek both QG and GUT within one framework, reducing all four fundamental interactions to a Theory of Everything (ToE). The most prevalent aim at a ToE is string theory, although to model matter particles, it added SUSY to force particles—and so, strictly speaking, became superstring theory. Multiple, seemingly disparate superstring theories were unified on a backbone, M-theory. Theories beyond the Standard Model remain highly speculative, lacking great experimental support.\n\n## Overview of the fundamental interactions\n\nAn overview of the various families of elementary and composite particles, and the theories describing their interactions. Fermions are on the left, and Bosons are on the right.\n\nIn the conceptual model of fundamental interactions, matter consists of fermions, which carry properties called charges and spin ±​12 (intrinsic angular momentum ±​ħ2, where ħ is the reduced Planck constant). They attract or repel each other by exchanging bosons.\n\nThe interaction of any pair of fermions in perturbation theory can then be modelled thus:\n\nTwo fermions go in → interaction by boson exchange → Two changed fermions go out.\n\nThe exchange of bosons always carries energy and momentum between the fermions, thereby changing their speed and direction. The exchange may also transport a charge between the fermions, changing the charges of the fermions in the process (e.g., turn them from one type of fermion to another). Since bosons carry one unit of angular momentum, the fermion's spin direction will flip from +​12 to −​12 (or vice versa) during such an exchange (in units of the reduced Planck's constant).\n\nBecause an interaction results in fermions attracting and repelling each other, an older term for \"interaction\" is force.\n\nAccording to the present understanding, there are four fundamental interactions or forces: gravitation, electromagnetism, the weak interaction, and the strong interaction. Their magnitude and behaviour vary greatly, as described in the table below. Modern physics attempts to explain every observed physical phenomenon by these fundamental interactions. Moreover, reducing the number of different interaction types is seen as desirable. Two cases in point are the unification of:\n\nBoth magnitude (\"relative strength\") and \"range\", as given in the table, are meaningful only within a rather complex theoretical framework. The table below lists properties of a conceptual scheme that is still the subject of ongoing research.\n\nInteraction Current theory Mediators Relative strength Long-distance behavior Range (m)[citation needed]\nWeak Electroweak theory (EWT) W and Z bosons 1025 ${\\frac {1}{r}}\\ e^{-m_{W,Z}\\ r}$  10−18\nStrong Quantum chromodynamics\n(QCD)\ngluons 1038 ${\\sim r}$\n(Color confinement, see discussion below)\n10−15\nElectromagnetic Quantum electrodynamics\n(QED)\nphotons 1036 ${\\frac {1}{r^{2}}}$\nGravitation General relativity\n(GR)\ngravitons (hypothetical) 1 ${\\frac {1}{r^{2}}}$\n\nThe modern (perturbative) quantum mechanical view of the fundamental forces other than gravity is that particles of matter (fermions) do not directly interact with each other, but rather carry a charge, and exchange virtual particles (gauge bosons), which are the interaction carriers or force mediators. For example, photons mediate the interaction of electric charges, and gluons mediate the interaction of color charges.\n\n## The interactions\n\n### Gravity\n\nGravitation is by far the weakest of the four interactions at the atomic scale, where electromagnetic interactions dominate. But the idea that the weakness of gravity can easily be demonstrated by suspending a pin using a simple magnet (such as a refrigerator magnet) is fundamentally flawed. The only reason the magnet is able to hold the pin against the gravitational pull of the entire Earth is due to its relative proximity. There is clearly a short distance of separation between magnet and pin where a breaking point is reached, and due to the large mass of Earth this distance is disappointingly small.\n\nThus gravitation is very important for macroscopic objects and over macroscopic distances for the following reasons. Gravitation:\n\n• Is the only interaction that acts on all particles having mass, energy and/or momentum\n• Has an infinite range, like electromagnetism but unlike strong and weak interaction[citation needed]\n• Cannot be absorbed, transformed, or shielded against\n• Always attracts and never repels (see function of geodesic equation in general relativity)\n\nEven though electromagnetism is far stronger than gravitation, electrostatic attraction is not relevant for large celestial bodies, such as planets, stars, and galaxies, simply because such bodies contain equal numbers of protons and electrons and so have a net electric charge of zero. Nothing \"cancels\" gravity, since it is only attractive, unlike electric forces which can be attractive or repulsive. On the other hand, all objects having mass are subject to the gravitational force, which only attracts. Therefore, only gravitation matters on the large-scale structure of the universe.\n\nThe long range of gravitation makes it responsible for such large-scale phenomena as the structure of galaxies and black holes and it retards the expansion of the universe.[citation needed] Gravitation also explains astronomical phenomena on more modest scales, such as planetary orbits, as well as everyday experience: objects fall; heavy objects act as if they were glued to the ground, and animals can only jump so high.\n\nGravitation was the first interaction to be described mathematically. In ancient times, Aristotle hypothesized that objects of different masses fall at different rates. During the Scientific Revolution, Galileo Galilei experimentally determined that this hypothesis was wrong under certain circumstances — neglecting the friction due to air resistance, and buoyancy forces if an atmosphere is present (e.g. the case of a dropped air-filled balloon vs a water-filled balloon) all objects accelerate toward the Earth at the same rate. Isaac Newton's law of Universal Gravitation (1687) was a good approximation of the behaviour of gravitation. Our present-day understanding of gravitation stems from Einstein's General Theory of Relativity of 1915, a more accurate (especially for cosmological masses and distances) description of gravitation in terms of the geometry of spacetime.\n\nMerging general relativity and quantum mechanics (or quantum field theory) into a more general theory of quantum gravity is an area of active research. It is hypothesized that gravitation is mediated by a massless spin-2 particle called the graviton.\n\nAlthough general relativity has been experimentally confirmed (at least for weak fields[which?]) on all but the smallest scales, there are rival theories of gravitation. Those taken seriously by[citation needed] the physics community all reduce to general relativity in some limit, and the focus of observational work is to establish limitations on what deviations from general relativity are possible.\n\nProposed extra dimensions could explain why the gravity force is so weak.\n\n### Electroweak interaction\n\nElectromagnetism and weak interaction appear to be very different at everyday low energies. They can be modeled using two different theories. However, above unification energy, on the order of 100 GeV, they would merge into a single electroweak force.\n\nThe electroweak theory is very important for modern cosmology, particularly on how the universe evolved. This is because shortly after the Big Bang, when the temperature was still above approximately 1015 K, the electromagnetic force and the weak force were still merged as a combined electroweak force.\n\nFor contributions to the unification of the weak and electromagnetic interaction between elementary particles, Abdus Salam, Sheldon Glashow and Steven Weinberg were awarded the Nobel Prize in Physics in 1979.\n\n#### Electromagnetism\n\nElectromagnetism is the force that acts between electrically charged particles. This phenomenon includes the electrostatic force acting between charged particles at rest, and the combined effect of electric and magnetic forces acting between charged particles moving relative to each other.\n\nElectromagnetism has an infinite range like gravity, but is vastly stronger than it, and therefore describes a number of macroscopic phenomena of everyday experience such as friction, rainbows, lightning, and all human-made devices using electric current, such as television, lasers, and computers. Electromagnetism fundamentally determines all macroscopic, and many atomic levels, properties of the chemical elements, including all chemical bonding.\n\nIn a four kilogram (~1 gallon) jug of water there is\n\n$4000\\ {\\mbox{g}}\\,H_{2}O\\cdot {\\frac {1\\ {\\mbox{mol}}\\,H_{2}O}{18\\ {\\mbox{g}}\\,H_{2}O}}\\cdot {\\frac {10\\ {\\mbox{mol}}\\,e^{-}}{1\\ {\\mbox{mol}}\\,H_{2}O}}\\cdot {\\frac {96,000\\ {\\mbox{C}}\\,}{1\\ {\\mbox{mol}}\\,e^{-}}}=2.1\\times 10^{8}C\\ \\,\\$\n\nof total electron charge. Thus, if we place two such jugs a meter apart, the electrons in one of the jugs repel those in the other jug with a force of\n\n${1 \\over 4\\pi \\varepsilon _{0}}{\\frac {(2.1\\times 10^{8}C)^{2}}{(1m)^{2}}}=4.1\\times 10^{26}N.$\n\nThis force is many times larger than the weight of the planet Earth. The atomic nuclei in one jug also repel those in the other with the same force. However, these repulsive forces are canceled by the attraction of the electrons in jug A with the nuclei in jug B and the attraction of the nuclei in jug A with the electrons in jug B, resulting in no net force. Electromagnetic forces are tremendously stronger than gravity but cancel out so that for large bodies gravity dominates.\n\nElectrical and magnetic phenomena have been observed since ancient times, but it was only in the 19th century James Clerk Maxwell discovered that electricity and magnetism are two aspects of the same fundamental interaction. By 1864, Maxwell's equations had rigorously quantified this unified interaction. Maxwell's theory, restated using vector calculus, is the classical theory of electromagnetism, suitable for most technological purposes.\n\nThe constant speed of light in a vacuum (customarily described with a lowercase letter \"c\") can be derived from Maxwell's equations, which are consistent with the theory of special relativity. Albert Einstein's 1905 theory of special relativity, however, which follows from the observation that the speed of light is constant no matter how fast the observer is moving, showed that the theoretical result implied by Maxwell's equations has profound implications far beyond electromagnetism on the very nature of time and space.\n\nIn another work that departed from classical electro-magnetism, Einstein also explained the photoelectric effect by utilizing Max Planck's discovery that light was transmitted in 'quanta' of specific energy content based on the frequency, which we now call photons. Starting around 1927, Paul Dirac combined quantum mechanics with the relativistic theory of electromagnetism. Further work in the 1940s, by Richard Feynman, Freeman Dyson, Julian Schwinger, and Sin-Itiro Tomonaga, completed this theory, which is now called quantum electrodynamics, the revised theory of electromagnetism. Quantum electrodynamics and quantum mechanics provide a theoretical basis for electromagnetic behavior such as quantum tunneling, in which a certain percentage of electrically charged particles move in ways that would be impossible under the classical electromagnetic theory, that is necessary for everyday electronic devices such as transistors to function.\n\n#### Weak interaction\n\nThe weak interaction or weak nuclear force is responsible for some nuclear phenomena such as beta decay. Electromagnetism and the weak force are now understood to be two aspects of a unified electroweak interaction — this discovery was the first step toward the unified theory known as the Standard Model. In the theory of the electroweak interaction, the carriers of the weak force are the massive gauge bosons called the W and Z bosons. The weak interaction is the only known interaction that does not conserve parity; it is left-right asymmetric. The weak interaction even violates CP symmetry but does conserve CPT.\n\n### Strong interaction\n\nThe strong interaction, or strong nuclear force, is the most complicated interaction, mainly because of the way it varies with distance. At distances greater than 10 femtometers, the strong force is practically unobservable. Moreover, it holds only inside the atomic nucleus.\n\nAfter the nucleus was discovered in 1908, it was clear that a new force, today known as the nuclear force, was needed to overcome the electrostatic repulsion, a manifestation of electromagnetism, of the positively charged protons. Otherwise, the nucleus could not exist. Moreover, the force had to be strong enough to squeeze the protons into a volume whose diameter is about 10−15 m, much smaller than that of the entire atom. From the short range of this force, Hideki Yukawa predicted that it was associated with a massive particle, whose mass is approximately 100 MeV.\n\nThe 1947 discovery of the pion ushered in the modern era of particle physics. Hundreds of hadrons were discovered from the 1940s to 1960s, and an extremely complicated theory of hadrons as strongly interacting particles was developed. Most notably:\n\nWhile each of these approaches offered deep insights, no approach led directly to a fundamental theory.\n\nMurray Gell-Mann along with George Zweig first proposed fractionally charged quarks in 1961. Throughout the 1960s, different authors considered theories similar to the modern fundamental theory of quantum chromodynamics (QCD) as simple models for the interactions of quarks. The first to hypothesize the gluons of QCD were Moo-Young Han and Yoichiro Nambu, who introduced the quark color charge and hypothesized that it might be associated with a force-carrying field. At that time, however, it was difficult to see how such a model could permanently confine quarks. Han and Nambu also assigned each quark color an integer electrical charge, so that the quarks were fractionally charged only on average, and they did not expect the quarks in their model to be permanently confined.\n\nIn 1971, Murray Gell-Mann and Harald Fritzsch proposed that the Han/Nambu color gauge field was the correct theory of the short-distance interactions of fractionally charged quarks. A little later, David Gross, Frank Wilczek, and David Politzer discovered that this theory had the property of asymptotic freedom, allowing them to make contact with experimental evidence. They concluded that QCD was the complete theory of the strong interactions, correct at all distance scales. The discovery of asymptotic freedom led most physicists to accept QCD since it became clear that even the long-distance properties of the strong interactions could be consistent with experiment if the quarks are permanently confined.\n\nAssuming that quarks are confined, Mikhail Shifman, Arkady Vainshtein and Valentine Zakharov were able to compute the properties of many low-lying hadrons directly from QCD, with only a few extra parameters to describe the vacuum. In 1980, Kenneth G. Wilson published computer calculations based on the first principles of QCD, establishing, to a level of confidence tantamount to certainty, that QCD will confine quarks. Since then, QCD has been the established theory of the strong interactions.\n\nQCD is a theory of fractionally charged quarks interacting by means of 8 bosonic particles called gluons. The gluons interact with each other, not just with the quarks, and at long distances the lines of force collimate into strings. In this way, the mathematical theory of QCD not only explains how quarks interact over short distances but also the string-like behavior, discovered by Chew and Frautschi, which they manifest over longer distances.\n\n### Higgs interaction\n\nAlthough not a gauge interaction nor generated by any diffeomorphism symmetry, the Higgs field's cubic Yukawa coupling produces a weakly attractive fifth interaction. After spontaneous symmetry breaking via the Higgs mechanism, Yukawa terms remain of the form\n\n${\\frac {\\lambda _{i}}{\\sqrt {2}}}{\\bar {\\psi }}\\phi '\\psi ={\\frac {m_{i}}{\\nu }}{\\bar {\\psi }}\\phi '\\psi$ ,\n\nwith Yukawa coupling $\\lambda _{i}$ , particle mass $m_{i}$  (in eV), and Higgs vacuum expectation value 246.22 GeV. Hence coupled particles can exchange a virtual Higgs boson, yielding classical potentials of the form\n\n$V(r)=-{\\frac {m_{i}m_{j}}{m_{H}^{2}}}{\\frac {1}{4\\pi r}}e^{-m_{H}\\,c\\,r/\\hbar }$ ,\n\nwith Higgs mass 125.18 GeV. Because the reduced Compton wavelength of the Higgs boson is so small (1.576×10−18 m, comparable to the W and Z bosons), this potential has an effective range of a few attometers. Between two electrons, it begins roughly 1011 times weaker than the weak interaction, and grows exponentially weaker at non-zero distances.\n\n### Beyond the Standard Model\n\nNumerous theoretical efforts have been made to systematize the existing four fundamental interactions on the model of electroweak unification.\n\nGrand Unified Theories (GUTs) are proposals to show that the three fundamental interactions described by the Standard Model are all different manifestations of a single interaction with symmetries that break down and create separate interactions below some extremely high level of energy. GUTs are also expected to predict some of the relationships between constants of nature that the Standard Model treats as unrelated, as well as predicting gauge coupling unification for the relative strengths of the electromagnetic, weak, and strong forces (this was, for example, verified at the Large Electron–Positron Collider in 1991 for supersymmetric theories).[specify]\n\nTheories of everything, which integrate GUTs with a quantum gravity theory face a greater barrier, because no quantum gravity theories, which include string theory, loop quantum gravity, and twistor theory, have secured wide acceptance. Some theories look for a graviton to complete the Standard Model list of force-carrying particles, while others, like loop quantum gravity, emphasize the possibility that time-space itself may have a quantum aspect to it.\n\nSome theories beyond the Standard Model include a hypothetical fifth force, and the search for such a force is an ongoing line of experimental research in physics. In supersymmetric theories, there are particles that acquire their masses only through supersymmetry breaking effects and these particles, known as moduli can mediate new forces. Another reason to look for new forces is the discovery that the expansion of the universe is accelerating (also known as dark energy), giving rise to a need to explain a nonzero cosmological constant, and possibly to other modifications of general relativity. Fifth forces have also been suggested to explain phenomena such as CP violations, dark matter, and dark flow." ]
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https://homework.cpm.org/category/CC/textbook/cca/chapter/A/lesson/A.1.7/problem/A-74
[ "", null, "", null, "### Home > CCA > Chapter A > Lesson A.1.7 > ProblemA-74\n\nA-74.", null, "Examine the shape made with algebra tiles at right.\n\n1. Write an expression that represents the perimeter of the shape. Then evaluate your expression for $x=6$ and $y=10$ units.\n\nLabel each side with its length and write an expression for the perimeter. $2x+3y+(y−2)+4=2x+4y+2$", null, "Evaluate this expression.\n$2(6)+4(10)+2\\\\12+40+2=54$\n\n$54$\n\n2. Write an expression that represents the area of the shape. What is the area if $x=6$ and $y=10$ units?\n\nArea is the total square units of a shape.\n\nIt might be helpful to break the shape into parts, find the area of the parts, and then sum them to find the area of the whole.", null, "$113$ square units. Make sure to show your work, including the expression you wrote for the area." ]
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https://www.hindawi.com/journals/js/2016/6545791/
[ "/ / Article\nSpecial Issue\n\n## QoS Based Cooperative Communications and Security Mechanisms for Ad Hoc Sensor Networks\n\nView this Special Issue\n\nResearch Article | Open Access\n\nVolume 2016 |Article ID 6545791 | 13 pages | https://doi.org/10.1155/2016/6545791\n\n# Statistical Delay QoS Provisioning for Energy-Efficient Spectrum-Sharing Based Wireless Ad Hoc Sensor Networks\n\nAccepted11 Oct 2016\nPublished14 Nov 2016\n\n#### Abstract\n\nIn this paper, we develop the statistical delay quality-of-service (QoS) provisioning framework for the energy-efficient spectrum-sharing based wireless ad hoc sensor network (WAHSN), which is characterized by the delay-bound violation probability. Based on the established delay QoS provisioning framework, we formulate the nonconvex optimization problem which aims at maximizing the average energy efficiency of the sensor node in the WAHSN while meeting PU’s statistical delay QoS requirement as well as satisfying sensor node’s average transmission rate, average transmitting power, and peak transmitting power constraints. By employing the theories of fractional programming, convex hull, and probabilistic transmission, we convert the original fractional-structured nonconvex problem to the additively structured parametric convex problem and obtain the optimal power allocation strategy under the given parameter via Lagrangian method. Finally, we derive the optimal average energy efficiency and corresponding optimal power allocation scheme by employing the Dinkelbach method. Simulation results show that our derived optimal power allocation strategy can be dynamically adjusted based on PU’s delay QoS requirement as well as the channel conditions. The impact of PU’s delay QoS requirement on sensor node’s energy efficiency is also illustrated.\n\n#### 1. Introduction\n\nWith the rapid development of wireless communications technologies, wireless ad hoc sensor networks (WAHSNs), where sensor nodes have the capability of self-healing and self-organizing, have been regarded as one of the most important wireless network architectures. Specifically, WAHSNs aim at collecting information from the surrounding environment and providing the fundamental for decisions. As WAHSNs lack of central control entities as well as the open nature of wireless channels, many challenging issues in WAHSNs arise, such as routing and networking , spectrum access and admission control , and networking and communications security . Moreover, since WAHSNs usually include large number of sensor nodes, the wireless spectrum demands for WAHSNs have been also constantly increasing. However, recent research outcomes demonstrate that the wireless spectrum has become one of the scarce resources for wireless communications due to the currently used static spectrum allocation policy where a certain portion of spectrum can only be utilized, the particular type of wireless systems .\n\nTo efficiently alleviate the spectrum shortage problem, spectrum-sharing and cognitive radio technologies have been regarded as one of the most important features for the future wireless systems and thus attracted lots of research attention from both academia and industry in the past decade . In spectrum-sharing based wireless networks, how to provide efficient quality-of-service (QoS) provisioning for primary user (PU) has been widely accepted as a critical important issue. In existing works, PU’s QoS protection is usually implemented by imposing the average/peak interference power constraint on secondary users (SU) or guaranteeing PU’s minimum average/instantaneous transmission rate . However, the abovementioned methods cannot provide accurate and fine-grained delay QoS protection for PU due to the following reasons. First, it is difficult to build the accurate relationship between PU’s maximum allowed interference power and its delay QoS requirement. Second, guaranteeing PU’s minimum average/instantaneous transmission rate can only reflect two extreme cases of PU’s delay requirements. Specifically, on one hand, the average transmission rate constraint only requires that a certain amount of data should be transmitted within the required time period and thus only corresponds to the loose delay requirement. On the other hand, PU’s minimum instantaneous rate requires that the transmission rate cannot be below the given threshold at any time, which implies that the instantaneous rate constraint corresponds to a very stringent delay requirement. Moreover, the minimum instantaneous transmission rate usually cannot be satisfied due to the stochastic feature of wireless channels. Consequently, there is an urgent need to establish an efficient framework to accurately describe a wide range of PU’s delay QoS requirements. Moreover, it is also crucial to develop the resource allocation scheme which can not only optimize SU’s energy efficiency, but also meet PU’s various delay requirements.\n\nBased on the above analysis, we in this paper investigate PU’s delay QoS provisioning technique over energy-efficient spectrum-sharing based WAHSNs. Specifically, by employing the theory of statistical delay QoS provisioning, we first build an efficient PU’s delay QoS protection framework which is described by PU’s queueing-delay-bound violation probability. Different from currently widely used PU’s QoS protection approaches, our adopted framework can quantitatively and accurately describe PU’s fine-grained delay requirement by a single parameter called PU’s delay QoS exponent. Based on the established PU’s statistical delay QoS protection framework, we formulate the optimization problem aiming at maximizing the average energy efficiency of the sensor node in the WAHSN while meeting PU’s statistical delay QoS requirement as well as satisfying the sensor node’s average transmission rate and average and peak transmitting power constraints. To solve our formulated fractional-structured nonconvex problem, we first adopt the fractional programming technique to convert the original fractional-structured problem to the parametric nonconvex program. Then, by employing the theories of convex hull and probabilistic transmission, we convert the parametric nonconvex problem to the equivalent convex problem and obtain the optimal power allocation strategy under the given parameter via Lagrangian method. Finally, the optimal energy efficiency of the sensor node is derived by using the Dinkelbach method. Simulation results illustrate that our obtained optimal power allocation strategy can adapt to both PU’s delay QoS requirement and channel conditions. Moreover, PU’s delay QoS requirement will significantly affect sensor node’s energy efficiency.\n\nThe rest of this paper is organized as follows. In Section 2, we present the system model. In Section 3, we first establish PU’s statistical delay QoS protection frame and then obtain the optimal power allocation strategy which can maximize the average energy efficiency of each sensor node subject to PU’s delay QoS requirement as well as SU’s average transmission rate and average and peak transmitting power constraints. Simulation results are provided in Section 4. This paper concludes with Section 5.\n\n#### 2. System Model\n\nWe consider that one wireless ad hoc sensor network (WAHSN) coexists with one primary network by sharing a certain portion of spectrum licensed to the primary network, as shown in Figure 1. Thus, the WAHSN considered in this paper can be viewed as the secondary network. Specifically, the primary network includes one primary sender (PS) and one primary receiver (PR). The WAHSN includes one fusion center and sensor nodes. The sensor nodes collect required information from the environment and send the collected information to the fusion center. Thus, we in this paper denote the sensor node as the secondary sender (SS) and denote the fusion center as the secondary receiver (SR).\n\nThe channel gains between PS and PR, the th SS and th SR, PS and the th SR, and th SS and PR are denoted by , , , and , respectively, where . All channel gains are assumed to be stationary, ergodic, independent, and block fading processes and follow Rayleigh fading model. Thus, all channel gains remain unchanged within each frame with duration but independently vary from one frame to another. Moreover, we also assume that PS transmits with constant power, but SS transmits with variable power. We also assume that the WAHSN is synchronized with the primary network, which means that all sensor nodes in the WAHSN know the beginning and ending instants of each frame. Note that we in this paper assume that the channel gains and () are available for WAHSN. One possible approach for obtaining this knowledge is to perform cooperation with primary networks. Furthermore, due to the large number of sensor nodes and limited wireless spectrum resource, the random access mechanism is employed for the WAHSN. In particular, at the beginning of each frame, each sensor node in the WAHSN tries to access the spectrum licensed to primary network with probability . If only one sensor node tries to access the spectrum, the sensor node can successfully transmit the information to the fusion center; otherwise, collision will occur at the fusion center or all sensor nodes remain silent. Consequently, the probability that the given sensor node can successfully send information to the fusion center, denoted by , is determined byIn this paper, we aim at providing the statistical queueing-delay QoS protection for PS, which will be detailed in the following section.\n\n#### 3. Energy-Efficient Power Allocation Strategy with PU’s Statistical Delay QoS Protection\n\n##### 3.1. Statistical Delay QoS Protection for PU\n\nIn wireless communications systems, delay includes several components, such as propagation delay, signal processing delay, and encoding/decoding delay. However, due to the stochastic nature of wireless channels which causes the highly time-varying feature of queue’s service rate, queueing-delay has been widely recognized as an important contributor for the delay uncertainty. Moreover, the dynamics of wireless channels also cause that deterministic/hard delay provisioning is often unrealistic for practical wireless systems. Consequently, statistical approach can be better suited for the queueing-delay protection in wireless networks.\n\nTo perform statistical delay QoS protection for the primary network, we consider that there is a queue at PS as shown in Figure 2. Specifically, the upper layer of PS delivers data to the link layer and then the received data, which will be divided into link layer frames, is stored in the queue. PS will split the link layer frames into bit-streams and deliver them to the physical layer for transmission.\n\nBased on the statistical QoS provisioning theory, PS’s statistical QoS requirement can be described by the queue-length bound violation probability, which can be written as [47, 48]where denotes PU’s queue-length, represents the predefined queue-length threshold of PU, and denotes the required violation probability, respectively. The above inequality (2) requires that the probability of PS’s queue-length exceeding the given threshold cannot be larger than the targeted probability requirement (in this paper, we assume that the queue size of PS is infinite implying that no queue overflow will happen and thus we use queue-length bound violation probability as the QoS provisioning metric. If the queue size of PS is finite, we can employ queue-overflow violation probability for statistical QoS protection, where we require that PS’s queue-overflow probability cannot exceed the predefined threshold).\n\nIf we consider delay as the performance metric, we can also convert the abovementioned queue-length bound violation probability to the corresponding queueing-delay-bound violation probability, which is given by [47, 48]where denotes PU’s queueing-delay and represents PU’s queueing-delay threshold. Similar to (2), inequality (3) requires that the probability of PS’s queue-delay exceeding the given threshold need below the targeted probability requirement . Moreover, larger values of and imply looser delay requirement and smaller values of and mean more stringent delay constraint. Furthermore, by employing the large derivation principle, PU’s queueing-delay-bound violation probability can be approximately determined by where is called the PU’s QoS exponent and is the effective bandwidth of PU’s data arrival process that determines the minimum constant service rate required to support the given data arrival process under the specified delay QoS requirement . Since it is assumed that PS has constant data arrival rate (nats/s/Hz) as shown in Figure 2, we have (nats/frame). Based on (3) and (4), we can obtain that if (3) is satisfied, we must havewhich implies that PU’s delay QoS requirement can be quantitatively described by the QoS exponent . In particular, larger values of and result in smaller value of and smaller values of and lead to larger value of . Consequently, we can derive that small value of implies loose delay QoS requirement and large value of represents stringent delay constraint. Moreover, we can also obtain that when , PS can tolerate an arbitrary long delay; when , PS cannot allow any delay .\n\nBy employing the theory of effective capacity, which defines the maximum sustainable constant data arrival rate for the queueing system that the data service process can support under given QoS requirement , we can convert PU’s queueing-delay-bound violation probability to the equivalent effective capacity requirement. Specifically, as PS’s service rate , as shown in Figure 2, is time-uncorrelated across different frames, the effective capacity of PU’s service rate process, denoted by , can be written asThen, we can obtain that PU’s queueing-delay-bound violation probability constraint is satisfied only if the effective capacity requirementcan be met, which implies that PS’s maximum sustainable arrival rate cannot be smaller than the constant arrival rate.\n\nThe theories of effective bandwidth and effective capacity provide us with a convenient yet efficient approach to perform accurate and fine-grained delay QoS protection for the queueing system. Specifically, it allows us to design the service (arrival) process of the queueing system to meet the required statistical delay QoS requirement characterized by the queue-length bound/delay-bound violation probability by using the properties and statistics of the arrival (service) process. In this paper, we mainly focus on the service rate process and effective capacity part. Consequently, when PU’s internal conditions change, such that congestion occurs, PU’s data arrival rate will correspondingly vary. In this case, WAHSN can update the statistics of PU’s data arrival rate process. Then, WAHSN can reperform power allocation (which will be detailed in the following section) such that PU’s data arrival rate process is also time-uncorrelated as is obtained based on the updated statistics of data arrival rate process and is the function of channel gains which are assumed to be time-uncorrelated. Moreover, if the stochastic data arrival process for PS is considered, we can apply the theory of effective bandwidth to determine the minimum constant service rate needed for the given data arrival process. Then, the statistical QoS requirement for PS becomes , which implies that the effective capacity of the service rate process cannot be smaller than the effective bandwidth of the data arrival process.\n\n##### 3.2. Optimization Problem Formulation\n\nRecall that the successful access probability of each sensor node is as given by (1). Consequently, the service rates of PS-PR and SS-SR links for any given frame, denoted by (nats/s/Hz) and (nats/s/Hz), respectively, are determined by (we omit the index for brevity and the SS-SR link denotes the link from the sensor node to fusion center)respectively, where is the network gain vector (NGV), is PS’s constant transmitting power, denotes SS’s transmitting power as the function of PU’s QoS exponent and NGV , and represents the variance of additive white Gaussian noise (AWGN). Then, PS’s effective capacity of the service rate process given by (8) is determined by\n\nIn this paper, we aim at maximizing the sensor node’s normalized average energy efficiency while meeting PS’s statistical delay QoS requirement as well as satisfying sensor node’s average data transmission rate constraint and the average and peak transmitting power constraints, which can be mathematically formulated as where denotes the normalized PS’s QoS exponent, denotes the minimum required transmission rate of the SS-SR link, is the amplifier coefficient, represents the power consumption for hardware components, and and denote the maximum allowed average and peak transmitting power for SS, respectively. Moreover, (12) represents PU’s effective capacity requirement which is obtained based on (7) and (10).\n\n##### 3.3. Optimal Power Allocation Scheme\n\nAs the numerator and denominator of the objective function given by (11) are concave and affine, respectively, we can adopt fractional programming to solve problem . Specifically, by introducing the nonnegative parameter , we can construct the new optimization problem, which is given bywhere Note that as we introduced the parameter to convert the fractionally structured objective function to the above linearly additive function, the sensor node’s power allocation strategy should also be the function of parameter , where we use to replace in the above problem .\n\nWe can easily prove that the objective function of problem and SU’s average transmission rate constraint given by (13) are both concave. Moreover, SU’s average and peak transmitting power constraint given by (14) and (15), respectively, are both affine. Thus, the convexity of is determined by that of PU’s statistical delay QoS requirement given by (12). We can obtain from (16) that which demonstrate that is a decreasing function of but is not concave over as does not hold. However, we can determine the unique inflexion point for , which is given by Then, we can obtain that is concave for and is convex for . Consequently, although problem is not convex, we can still solve this nonconvex problem by employing the convex hull and probabilistic transmission techniques. Before discussing how to derive the optimal power allocation strategy, we first briefly describe the theories of convex hull and probabilistic transmission as follows. (i)Convex Hull. For a nonconvex region, all convex combination of the points in the region is defined as its convex hull. Moreover, it has been shown that the boundary function of the convex hull for any given two-dimensional plane is the straight line segment .(ii)Probabilistic Transmission. Denote as the straight line with the end points and . Then, any point on the line can be achieved by , where denotes the probability that we use point and represents the probability for using point .\n\nBased on the abovementioned techniques, we can convert the nonconvex problem to the equivalent strictly concave problem, which can be analyzed from the following three cases.\n\nCase 1. If or but the following inequalityis satisfied, we can obtain the following conclusions. (1)If , it is easy to derive that is convex over . Thus, based on the definition of convex function, we can obtain that in the range of is below the straight line with the end points and .(2)If , it is obvious that is concave for but is convex for . However, (25) implies that in the range of is also below the straight line with the end points and . Consequently, the boundary function for the convex hull of function in the range of , denoted by , is the straight line with the end points and , which can be mathematically written as Then, based on the probabilistic transmission technique, we can achieve all the points along the boundary function , where sensor node’s transmitting power can only equal 0 and . Therefore, sensor node’s transmission rate also needs to be modified. We denote sensor node’s reformulated transmission rate by . Then, by employing the probabilistic transmission technique, when , is given bywhich implies that the reformulated transmission rate is also the straight line segment with two end points and . That is to say, when one sensor node accesses the spectrum via random access, the probability that the sensor node uses power for transmission is and the probability that the sensor node gives up the transmission opportunity is .\n\nCase 2. If , we can derive that is concave for . Therefore, in this case, the boundary function for the convex hull is equal to and thus we haveCorrespondingly, in this case, sensor node’s reformulated transmission rate is also equal to the original rate ; that is,Note that as is concave, the boundary function for the convex hull is exactly the same as the original function and thus it is not necessary to adopt probabilistic transmission technique in this case.\n\nCase 3. If and the following inequalityis satisfied, we have that is concave for and is convex for . However, different from Case 1 in which function is completely below the straight line with the end points and in the range of , there must exist one unique cross-point denoted by in this case such that (i)function is above the straight line with end points and for ;(ii)function is below the straight line with end points and for .Thus, based on the definition of convex hull, to determine the boundary function for the convex hull of function , we need to find the unique tangent point for and the straight line with two end points and . We denote the tangent point by and then can be determined byBased on the obtained tangent point , the boundary function is equal to the original function when and becomes a straight line when . Consequently, the boundary function can be mathematically written asEquation (32) implies that the probabilistic transmission technique only needs to be used to realize the straight line with the end points and . Then, by adopting the probabilistic transmission technique, we can also modify sensor node’s transmission rate asBased on the above analysis, we can convert the nonconvex problem to the strictly concave problem, which is determined bywhereRecall that denotes sensor node’s reformulated transmission rate under the probabilistic transmission given by (27), (29), and (33), respectively. represents the boundary function for the convex hull given by (26), (28), and (32), respectively. As the above problem is strictly concave, we can obtain the optimal solution via Lagrangian method. Specifically, we can construct the Lagrangian function, denoted by , aswhereand , , and are Lagrangian multipliers associated with constraints (35), (36), and (14), respectively. We denote the optimal solution of problem by . Then, based on the Karush-Kuhn-Tucker (KKT) conditions, we can obtainwhere\n\nDenote the optimal Lagrangian multipliers by , , and , respectively. Then, the optimal solution for problem is determined as follows:\n\nCase 1.\n\nCase 2. where and it is the solution to the following equality:\n\nCase 3. where is the solution to .\nAlthough (43)–(46) determine the optimal solution of problem , we can observe that our obtained optimal solution belongs to the range that the boundary function overlaps with the original function . Consequently, (43)–(46) also determine the optimal solution of nonconvex problem .\n\n (1) Initialization: and where satisfies (2) for   do (3)  Let (4)  Solve problem with , where the optimal solution denoted is determined by (43)–(46). (5)  if   then (6)   Update parameter by (7)   Let (8)  else (9)   The optimal power allocation strategy and the sensor node’s maximum average energy-efficiency are determined by (10)  end if (11)  end for (12) return   and\n\n#### 4. Simulation Results\n\nIn this section, we will evaluate the performance of our proposed energy-efficient power allocation scheme by simulations. Specifically, in our simulations, we set that the bandwidth  Hz, the frame duration ms, the number of sensor nodes , PU’s constant transmitting power mW, sensor node’s maximum allowed average transmitting power mW, and sensor node’s maximum allowed peak transmitting power mW. Moreover, we also set PU’s data arrival rate nats/s/Hz, the amplifier coefficient of the sensor node , the constant circuit power of the sensor node mW, and the noise power mW.\n\nFigure 3 shows the average energy efficiency of the sensor node achieved by our proposed optimal power allocation scheme as the function of PU’s QoS requirement described by PU’s QoS exponent with different values of sensor node’s access probability . We can observe from Figure 3 that, under the given access probability , the sensor node can achieve the highest energy efficiency for the small value of PU’s QoS exponent implying loose delay QoS requirement. Moreover, the energy efficiency of the sensor node decreases as the value of PU’s QoS exponent increases, which denotes that the sensor node can only achieve lower energy efficiency when PU’s delay QoS requirement becomes stringent. Furthermore, we can also observe that the sensor node can only achieve zero energy efficiency; that is, the sensor node stops its transmission, when PU’s delay QoS requirement becomes extremely stringent resulting in large value of . Figure 3 also illustrates that under the given value of , that is, the given PU’s delay QoS requirement, the sensor node’s energy efficiency is the decreasing function of the access probability . The main reason is that the collision among sensor nodes increases for larger value of . Consequently, the sensor node will waste more energy on spectrum access process and thus can only achieve lower energy efficiency.\n\nTo more explicitly demonstrate the relationship between the sensor node’s achievable energy efficiency and PU’s delay QoS requirement, Figure 4 depicts the energy efficiency that the sensor node can achieve under our proposed power allocation scheme as the function of PU’s delay threshold and its maximum allowed violation probability under different values of the access probability where we can observe similar phenomenon as in Figure 3. In particular, the sensor can achieve higher energy efficiency under the larger values of and but can only get lower energy efficiency under the smaller values of and . Such phenomenon can be explained based on the analysis in Section 3.1. Specifically, we have obtained that the larger values of and result in smaller value of implying looser PU’s delay requirement. On the contrary, the smaller values of and cause larger value of denoting more stringent PU’s delay demand. Therefore, we can obtain the curves demonstrated in Figure 4.\n\nFigure 5 shows the optimal energy efficiency achieved by the sensor node under the proposed power allocation scheme versus the number of sensor nodes and the access probability . We can observe from Figure 5 that, under the given number of sensor nodes, the energy efficiency achieved by the sensor node first increases as the value of increases and then decreases while keeping increasing the value of . Such the phenomenon can be explained as follows. Specifically, on one hand, when the value of is small, the probability that all sensor nodes stay silent in each slot is large such that the spectrum resource is not efficiently utilized by the WAHSN. Consequently, increasing the value of will improve the energy efficiency of the sensor node when the value of is small. On the other hand, when the value of is large, the probability that the collision among sensor nodes in each slot is high as each sensor node will try to access the spectrum with large probability. Therefore, the energy efficiency of the sensor node will be degraded if we keep increasing the value of . Based on the above analysis, we can conclude that it is critically important to find the optimal access probability as the energy efficiency achieved by the sensor node is highly related to . Consequently, to achieve the aforementioned goal, Figure 6 shows the relationship between the optimal access probability of the sensor node and the number of sensor nodes. We can observe from Figure 6 that the optimal access probability is the decreasing function of the number of sensor nodes. This is because when the number of sensor nodes is small, the competition among sensor nodes is not fierce and thus the sensor node can access the spectrum with high probability. On the contrary, when the number of sensor nodes is small, the sensor node needs to lower the access probability to avoid high collision probability.\n\nFigure 7 depicts the energy efficiency of the sensor node as the function of PU’s data arrival rate under different PU’s delay QoS requirements and values of sensor node’s access probability. We can observe from Figure 7 that, under the same PU’s delay QoS requirement and sensor node’s access probability, the energy efficiency achieved by the sensor node decreases as PU’s data arrival rate increases. This is because that under the same PU’s delay QoS requirement, that is, the identical value of PU’s QoS exponent , increasing PU’s data arrival rate requires larger PU’s service rate, which demands the sensor node to introduce smaller interference power on PR. Consequently, the sensor node can only achieve lower throughput and thus get smaller energy efficiency while increasing PU’s data arrival rate. Moreover, we can also observe similar phenomenon that the sensor node can achieve higher energy efficiency under smaller values of and but can only get lower energy efficiency under larger values of and .\n\nFigure 8 shows the sensor node’s energy efficiency versus PU’s transmitting power under different values of PU’s QoS exponent and sensor node’s access probability . We can observe from this figure that, under the same PU’s delay QoS requirement and sensor node’s access probability, the sensor node’s energy efficiency dynamically varies with PU’s transmitting power. Specifically, when PU’s transmitting power is small, the sensor node’s energy efficiency is zero because the sensor node needs to stop its transmission to guarantee PU meeting the targeted delay QoS requirement and thus can only get the zero energy efficiency. When PU’s transmitting power is increasing, the sensor node can obtain nonzero energy efficiency. However, if we keep increasing PU’s transmitting power, the sensor node’s energy efficiency decreases. This is mainly because larger PU’s transmitting power will impose larger interference on the sensor node. Consequently, the throughput achieved by the sensor node decreases and thus can only get lower energy efficiency.\n\n#### 5. Conclusions\n\nIn this paper, we developed the statistical delay quality-of-service (QoS) provisioning framework for the energy-efficient spectrum-sharing based wireless ad hoc sensor network (WAHSN). Based on the established PU’s delay QoS provisioning framework, we further formulated the nonconvex optimization problem which aims at maximizing the average energy efficiency of the sensor node while meeting PU’s statistical delay QoS requirement as well as satisfying the sensor node’s average transmission rate and average and peak transmitting power constraints. To solve our formulated nonconvex optimization problem, we first used fractional programming to convert the original fractional-structured problem to the parametric nonconvex program. Then, by adopting the theories of convex hull and probabilistic transmission, we converted the parametric nonconvex problem to the equivalent convex problem and obtain the optimal power allocation strategy under the given parameter via Lagrangian method. Finally, we derived the optimal average energy efficiency of the sensor node in the WAHSN by employing the Dinkelbach method. Simulation results show that our derived optimal power allocation strategy can be dynamically adjusted based on PU’s delay QoS requirement as well as the channel conditions. 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Fettweis, “Framework for link-level energy efficiency optimization with informed transmitter,” IEEE Transactions on Wireless Communications, vol. 11, no. 8, pp. 2946–2957, 2012. View at: Publisher Site | Google Scholar\n50. S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, Cambridge, UK, 2004. View at: Publisher Site | MathSciNet\n\nWe are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at [email protected] to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19.", null, "" ]
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https://www.chemistricks.com/2015/02/lesson-plan-chemical-laws-and.html
[ "# Lesson Plan: Chemical Laws and Stoichiometry\n\nLESSON PLAN\n\nEducation Level                : Senior High School\nSubject                              : Chemistry\nGrade/ Semester                : X / I\nTopic                                 : Chemical Laws and Stoichiometry\nSub Topic                          : Mole concept\nMolecular formula and Empirical formula\nRestraint Reactant\nTime Allocation                : 6 x 45 minutes\nStandard Competence      : Understanding the chemical basic laws and its application on chemical calculation (stoichiometry)\nBasic Competence            : Proving and communicating the implementation of chemical base laws through doing experiment and applying the mole concept in practicing chemical calculation.\n\nI.             INDIKATOR\n1.      mengkonversikan jumlah mol dengan jumlah partikel, massa, dan volume zat\n2.      Determining the empirical and the molecular formula\n3.      Determining the formula of hydrate\n4.      Detrmining the content of element in a compound\n5.      Detrmining the Restraint Reactant in the reaction\n6.      Detrmining amount of the reactant and the product\n\nII.          PURPOSE OF LEARNING\n1.      Students of Senior High School Class X semester 1 can mengkonversikan jumlah mol dengan jumlah partikel, massa, dan volume zat\n2.      Students of Senior High School Class X semester 1 can Determine the empirical and the molecular formula\n3.      Students of Senior High School Class X semester 1 can Determine the formula of hydrate\n4.      Students of Senior High School Class X semester 1 can Detrmine the content of element in a compound\n5.      Students of Senior High School Class X semester 1 can Detrmine the Restraint Reactant in the reaction\n6.      Students of Senior High School Class X semester 1 can Detrmine amount of the reactant and the product\n\nIII.       LEARNING MATERIAL\n• Mole concept\n• Molecular formula and Empirical formula\n• Restraint Reactant\n\nIV.       LEARNING MODEL\nApproach:   Process skill\nMethod  : Combination of discourse, discussion, and ask & questions.\n\nV.          LEARNING SCENARIO\n No Learning Activities Time (minutes) 1. 2. 3. Opening Teacher opens the class by saying greeting and asks the presence. Teacher conditioning the class so the students ready to accept materials. Teacher reminds the students about the chemical laws Teacher gives apperception Main Activities Teacher explain about diagram of mole concept and give example to apply it Teacher ask student to do in the whiteboard Teacher and student discuss the answer together Teacher explain about determine of restraint reactant in the reaction Teacher give exercise Closing Teacher reviews the material. Teacher gives a chance to student to ask questions. Quiz. Teacher gives homework for next meeting. Teacher gives information about the matter for next meeting. Teacher closes the class by saying greeting. 3 x 5 3 x 70 3 x 15\n\nVI.       LEARNING MEDIA\nChemistry books, students’ worksheet, white board and marker.\n\nVII.    REFERENCES\nPurba, Michael. 2006. Kimia untuk SMA Kelas X. Jakarta: Erlangga\nSunardi. 2007. Kimia Billingual untuk SMA Kelas X Semester 1 dan 2. Bandung: Yrama Widya.\n\nVIII. ASSESSMENT AND FOLLOW-UP\na.       Assessment: Quiz, individual assignment, and group assignment.\nb.      Continuing:\nStudent succeed if reach percentage ≥70 % from assessment.\nGiving remedial for students whose reach <70 % from assessment\n\nSemarang,   October  2008\n\n………………..                                                                      ……………………..\nIX.       MATERIAL ANALYSIS\n\nDiagram of mole concept\n Volume ofgas STP (V)", null, "", null, "Mass (m)", null, "", null, "Mole(n)", null, "", null, "The number of particle\n\n: L                                            x Ar ot Mr                                                                   x L                                          : Ar or Mr\n\n: 22,4               x 22,4\n\n PV = nRT\n\nAt a certain pressure and temperature (non STP), the volume of a given gas can be determined based on the ideal gas equation, that is as follows.\n\nKeterangan :   P = gas pressure (atm)\nV = volume of  gas (liters)\nn = mol e of gas (mol)\nR = gas constant(0,082 L. atm /mol. K)\nT = temperature (K)\n\nMolecular formula and Empirical formula\nMolecular formula is a chemical formula that certain kind and the number of atom that is form molecular compound, empirical formula of a compound is the ratio of mole of the compound composer elements atom.\nExample          CH2 = Empirical formula\nC2H4, C3H6 = Molecular formula\n\nThe content of element in a compound\nThe relative atomic mass is defined as the ratio of the average mass per atom of an element to one twelfth of the mass of a carbon-12 atom, which mathematically can be represented as follows.\n Ar X =", null, "The relative\n Mr X =", null, "molecule mass is defined as the ratio of the average of a molecule or a unit of substance to one twelfth of the mass of a carbon-12, which mathematically can be represented as follows.\n\nTo know the mass of element in acompound can be represented as follows\n\n mass of element in compound =", null, "The content of element in a compound can be represented as follows\n % content of element in a compound =", null, "" ]
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https://www.preschoolcrafts.us/preschool-subtraction-worksheet-fruits/
[ "# Fruits Themed Subtraction Worksheet for Preschool\n\nOn this page you can find a free printable simple level of subtraction worksheets for preschool. This Section includes preschool subtraction worksheet, basic subtraction worksheet, easy math worksheet activities.\n\nThis page has a subtraction worksheet for preschoolers. The mathematical worksheets are a good influence on children’s minds. Children will have a fun time with jpeg worksheet below. In this page, subtraction is taught using fruits. Preschoolers will easily understand the subtraction with fruit pictures on the worksheet.\n\nFruits are very useful for children in the age of development. With this study, children will have information about fruit. They will mark as much fruit as indicated by the subtraction. They will count down the remaining fruits and write them in boxes.\n\nYour students can have different mental skills. You can tell the process on the first instance and then thaw them. You can start using the removal pages for our pre-school students free of charge. You can subscribe to our site from the menu above to take advantage of all our other events. You can use the sidebar to follow us from Facebook, Instagram and Twitter. Good works.\n\nCount the objects, then cross out the number of objects you need to subtract. How many do you have left? Write in the box.\n\n## Subtraction Worksheet for Preschoolers\n\nSubtraction is to subtract a number from another number. We use it very often in our lives. In Shopping, we use the money we spend on the products we sell. When we go to a markete, we use subtraction. In such situations, the subtraction is used.\n\nClick for other subtraction worksheets and math worksheets.\n\nAfter using the subtraction worksheet for preschoolers, you can use the above menu for our other worksheets, coloring pages and crafts.", null, "" ]
[ null, "https://www.preschoolcrafts.us/wp-content/plugins/wp-mobile-edition/assets/images/switch.png", null ]
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http://mablecare.co.uk/chen-shu-ufmln/fe6877-bjt-differential-amplifier
[ "This site uses Akismet to reduce spam. BJT Amplifiers 6 CHAPTER OUTLINE 6–1 Amplifier Operation 6–2 Transistor AC Models 6–3 The Common-Emitter Amplifier 6–4 The Common-Collector Amplifier 6–5 The Common-Base Amplifier 6–6 Multistage Amplifiers 6–7 The Differential Amplifier 6–8 Troubleshooting Device Application CHAPTER OBJECTIVES Describe amplifier operation Discuss transistor models Referring back to the small signal model, we see that the loop composed of: but is negligible compared to the current supplied by the collector, so we say: Which we then plug back into the equation for : From this we can solve directly for the common mode gain: The common-mode input impedance is the impedance that common-mode input signals “see.” One can analyze the common mode input impedance () by, again, “cutting the differential amplifier in half” and analyzing one side the resulting schematic, assuming a common mode signal. So, for the BJT differential amplifier in this tutorial, the differential mode input impedance is: (what impact will this have?) The tail supply is modeled as a current source IQ. Objective: To investigate the simple differential amplifier using NPN transistors. Common Mode Gain. Draw the load line of the CE amplifier in Fig. Notice: We choose a loop and draw the small-signal model to obtain: Similar to the output voltage of the differential mode small signal model, we can see that is the voltage across . Figure 4-2: CE amplifier 2. How to Determine if a Vector Set is Linearly Independent, The Evolution of 3G Wireless Technologies, The Fourier Integral / Transform Explained, Third Generation Partnership Project (3GPP), European Telecommunications Standards Institute, Universal Wireless Communications Consortiums. From this figure, deriving is simple. (Si BJT with β = 200, V A = … The following equation describes the small-signal output resistance of any BJT: The parameter is typically given, and in this tutorial: Now that the small-signal resistances are known, along with the transconductance parameter, the differential mode gain () may be calculated: The differential input impedance of a differential amplifier is the impedance a “seen” by any “differential” signal. Fig.1 shows the block diagram of a differential amplifier. This post was created in March 2011 by Kansas State University Electrical Engineering student Safa Khamis. From this little discussion, you should be able to apply the principles used to analyze the BJT differential amplifier to the analysis of a FET-based differential amplifier. Also note that the connections between and the voltage-controlled current source (VCCS) indicate that the voltage that controls the VCCS is the voltage across . This parameter depends on how you want the circuit to operate, and is usually a known value. The following images show the general schematic for both kinds of differential amplifiers, often referred to as a differential input stage when used in designing op-amps. It may have either one output or a pair of outputs where the signal of interest is the voltage difference between the two outputs. Notice that these types of differential amplifiers use active loads to achieve wide swing and high gain. http://www.dcdcselector.com/en/replacement B-100, VA= 100 V, V be (on) = 0.7 V and V1 26 mV for all transistors. Transform your product pages with embeddable schematic, simulation, and 3D content modules while providing interactive user experiences for your customers. Also, R C = 6.8 kΩ, R B = 10 kΩ, and V CC = V EE = 15 V. Find the value of R E needed to bias the amplifier such that V ECQ1 = V CEQ2 = 8 V. Theme: Gillian, on DC Biasing & AC Performance Analysis of BJT & FET Differential Amplifiers. A worldwide innovation hub servicing component manufacturers and distributors with unique marketing solutions. In addition to this, is assumed to be a small signal (AC) open-circuit. i got here by googling whether lithium grease would work for the job. A simple current mirror is shown below: It is easy to understand how a current mirror works. It is only at... 110VAC does give you a distinct safety advantage over our 230VAC but it is still a lethal voltage. HO: Large Signal Operation of the BJT Differential Pair Activity: BJT Differential pair. The amplifier is to have a differential gain (to each of the two outputs) of at least 100 V/V, a differential input resistance ≥10k Ω and a common mode gain (to each of the two outputs) no greater than 0.1 V/V. Differential amplifiers have high CMRR (common mode rejection ratio) & a high i/p impedance. View EHB222E_Differential_Amplifier_BJT.pptx from PHCH 222 at Frankfurt University of Applied Sciences. The BJT can be operated in low or high power applications. Design a BJT differential amplifier that provides two single-ended outputs (at the collectors). Question-2 BJT based differential amplifier with a constant current source. Dual Input Unbalanced Output 4. Worse still, the really poor quality non-conforming stuff is sold in markets like Africa where no one is going to chase up the manufacturer's safety non-complacence.... That third picture does look dodgy. A free online environment where users can create, edit, and share electrical schematics, or convert between popular file formats like Eagle, Altium, and OrCAD. Assuming the three tarnsistors are matched with Vsegi =Vseq2 =Vsegs =+0.7V&B B92 =B03=120.If the input AC voltages Vin] =-2.5mA & Vin2=28mA a) Calculate the DC emitter-current of Q3 b) Calculate the DC base-currents of Q1 & Q2 c) Calculate the differential-mode gain Ay(dm) d) Calculate the … This can be found by observing the figure 6, above. The BJT Differential Amplifier Basic Circuit Figure 1 shows the circuit diagram of a differential amplifier. This tutorial will assume .7 V for each BJT. Leave a comment on DC Biasing & AC Performance Analysis of BJT & FET Differential Amplifiers, AC performance analysis, CMRR, common mode gain, common mode input impedance, common mode rejection ratio, DC Biasing, differential amplifier schematic, differential amplifiers, differential input stage, differential mode gain, input impedance. CH 10 Differential Amplifiers 18 Example 10.5 A bipolar differential pair employs a tail current of 0.5 mA and a collector resistance of 1 kΩ. BJT Differential Amplifier Similarly for BJT A d =g m R C Common-mode gain due to mismatch of R C: A cm = v od v icm = −R C 2R EE ΔR R C CMRR = 2g m R E ΔR C R C # \\$ % & ' (Differential Amplifier Half Circuit 19-8 DC Offset Due to mismatch in R D, output voltage V O ≠0 even both inputs are grounded. Please excuse this late reply, I found this thread while searching on another topic and felt I should add my tuppence-worth. Electrical conductors are able to conduct because of a shared \"sea of electrons\" which are not locally bound. It has a emitter-degeneration bias with a voltage divider. It is basic building in operational amplifiers. There are two input voltages v 1 and v 2. Here we will learn simulation of BJT differential amplifier using LT-SPICE sofftware .We will calculate CMRR . This is because the resistance in the emitter of these transistors has been omitted, due to its typically small value (10 to 25 ). or this That being the case, and rearranging the above equation, results in: By introducing a resistor of to the above schematic, the bias current is now established at 1 mA. Observe the equation governing the amount of collector current in a BJT, denoted : Note: [This equation may look intimidating at first, but what is important to understand is that the point of designing “by hand” is to get close. The amplifier which amplifies the difference between two input signals is called as Differential amplifier. Two things are accomplished by including in our circuit. On a side note, and the reason i’m commenting, is... For a FET there is a similar procedure, as the transconductance is defined as the ratio of the change in drain current to the change in gate-source voltage. Powered by WordPress Due to symmetry, the currents through transistors and are each half of the bias current, described by: Now that we know the collector currents through and , characterizing the performance of this differential amplifier is a breeze. 7. 4-2 on top of the I-V characteristic. This amplifier amplifies the difference between the two input voltages. Required fields are marked *. There is low forward voltage drop. While we only focused on the BJT differential amplifier here, a differential amplifier can be built with FETs and Op-Amps as well. 2nd Ed. Each FET has an adjustable length and width that affects how much current it will pass for a given voltage-drop across the device. Differential amplifier using BJT - AC & DC analysis - YouTube From this equation, you can see that the bjt used in circuitry gives amplification in the shape of voltage gain that is dependent on the values of RC and r’e. A differential amplifier is a circuit that can accept two input signals and amplify the difference between these two input signals. The object is to solve for the small-signal output voltages and output resistances. These types of operational amplifier circuits are commonly known as a differential amplifier. Differential Amplifier using Transistor The Si transistors in the differential amplifier circuit of the figure shown have negligible leakage current and ß1 = ß2 = 60. Since the parameters we are interested in (gain, CMRR, etc) are small-signal parameters, the small-signal model of this circuit is needed. Differential Amplifiers Common-Mode and DifferentialMode Signals & Gain Differential … The BJT are more effect by radiation. SiliconExpert provides engineers with the data and insight they need to remove risk from the supply chain. The CM gain is the “gain” that common mode signals “see,” or rather, is the attenuation applied to signals present on both differential inputs. We also know the current running through this resistance, and may equate the output voltage to: This time, though, isn’t distributed entirely over the resistances at the base. Greetings For a differential amplifier composed of FETs to work, it is imperative that all the FETs be in saturation mode. Single Input Balanced Output 3. With these values, we compute: Now that the transconductance parameter is known, the only other values needed to compute the differential mode gain are and . Differential amplifier or diff-amp is a multi-transistor amplifier. A good site is this: The waveform generator in the ADALM2000 system has a high output bandwidth and with that high bandwidth comes wide band noise. The effect of r, is neglected in this problem. Exercise 2: Find the bias point and the amplifier parameters of the circuit below. Transim powers many of the tools engineers use every day on manufacturers' websites and can develop solutions for any company. no dice. As RC is always significantly higher, the output voltage for this arrangement is larger than the input voltage. It is simple to see that (the small-signal output voltage) is equal to the current across the parallel combination of the resistors and multiplied by the size of the same parallel combination. Giovanni Verify that these expressions are correct. A “differential signal” is any and all signals that aren’t shared by and . The active load comprises of transistors Q 3 and Q 4 with the transistor Q 3 connected as a Diode with its base and collector shorted. ... interesting article. This is because the small-signal changes in the currents flowing through are impeded from traveling down the branches controlled by current sources . However, one may compute the common mode gain by “cutting the amplifier in half” by observing one of the loops in the following diagram. Here is the schematic of the BJT diff amplifier, I wanted to solve (design). Rc=8 k22 and Ry = 19.3 k12. The differential amplifier can be implemented with BJTs or MOSFETs. On my string of 50, there is a plastic joint in the middle that looks to be an insulated splice. But for an IC device that uses FETs, this is not the case. o Input at the base, output at the collector. Each effects the final single-ended output with opposite polarity. The frequency response has also been omitted, and the amplifier is assumed to be unilateral.]. One of them is that we can induce the current in , and thus, the current in . Figure 1 shows such a BJT differential amplifier circuit made of two BJTs (Q 1 and Q 2) and two power supplies of opposite polarity, V CC and –V EE which uses three resistors among which two are the collector resistors, R C1 and R C2 (one for each transistor) while one is the emitter resistor R E common to both transistors. \"CD40106 equivalent\". A very popular method is to use a current mirror. So, this article presents a general method for biasing and analyzing the performance characteristics of single-stage BJT and MOSFET differential amplifier circuits. Instead, a fraction of the input common mode input signal is across the base-emitter junction. Learn how your comment data is processed. Yes, the positive and negative inputs to the differential front end of this amplifier are the bases of Q1 and Q2. We believe that you have got a better understanding of this concept. News the global electronics community can trust, The trusted news source for power-conscious design engineers, Supply chain news for the electronics industry, The can't-miss forum engineers and hobbyists, The electronic components resource for engineers and purchasers, Design engineer' search engine for electronic components, Product news that empowers design decisions, The educational resource for the global engineering community, The learning center for future and novice engineers, The design site for electronics engineers and engineering managers, Where makers and hobbyists share projects, The design site for hardware software, and firmware engineers, Where electronics engineers discover the latest tools, Brings you all the tools to tackle projects big and small - combining real-world components with online collaboration. The path differs from that of differential signals because common mode signals make it so that the two signal sources don’t “see” each other. What is the maximum allowable base voltage if the differential input is large enough to completely steer the tail current? Am I the only one whe sees the bowl of potato salad in the first picture? So, friends, it is a complete post about BJT as an amplifier. A good op amp attempts to eliminate all common mode signals, but this is obviously not possible in the real world. I think most of the plugs have fuses at least and the insulation looks the same as the incandescent strings we used to have. The standard Differential Amplifier circuit now becomes a differential voltage comparator by “Comparing” one input voltage to the other. Your email address will not be published. One solution is to Google the example string: Consider the BJT differential amplifier shown below. But there is the threshold voltage – the minimum gate-to-source voltage that will allow for any conduction whatsoever. In fact, observe the equation for the drain current in a FET: , which is the electron mobility multiplied by the oxide capacitance. Differential amplifier In this post, differential amplifier using BJT and differential amplifier using op-amps are explained in detail. What I see in UK is things that are essentially designed for the US market, with consequently thinner insulation, but then they are sold here with just maybe a small tweak to the circuit, but not the insulation, to run on 230VAC. The other important thing this resistor does is drop a majority of the available voltage across itself, so that doesn’t have the entire voltage difference between the supplies across it! But it should be noted that the procedures to analyze these types of differential amplifiers are virtually the same. Because is completely steered, - 2 at one collector. https://www.digchip.com/ The BJT has a better voltage gain. So, this tutorial will assume: For a given technology, all of the BJT transistors are designed to have the same turn-on voltage. A differential amplifier multiplies the voltage difference between two inputs (Vin+ - Vin-) by some constant factor Ad, the differential gain. Mathematically, the transconductance parameter is: The last notable difference is the computation for a FET’s small-signal resistance. Thus, this is all about differential amplifier circuit using a BJT transistor. Use the program tranchar.vi to obtain the transfer function of the amplifier. To bias this circuit, the first thing one must do is determine what the desired magnitude of the current source will be. The differential amplifier configuration is very much popular and it is used in variety of analog circuits. In this experiment, we will make up the circuit using discrete transistors. Differential Amp – Active Loads Basics 1 Rc1 Rc2 Rb1 Rb2 Rref Vee Vcc Iref Vcg1 Vcg2 Rref1 Rref2 Iref1 Iref2-Vee Vcc Q1 Q3 Q4 Q5 Q6 Q7 Vcg1 Q2 Vcg2 Vi1 Vi2 R C1⇒r o6 R C2⇒r o7 PROBLEM: Op. The BJT di erential pair is an integral part of op amp integrated circuits. BJT Differential Amplifier using active loads: A simple active load circuit for a differential amplifier is the current mirror active load as shown in figure. Save my name, email, and website in this browser for the next time I comment. It is virtually formed the differential amplifier of the input part of an operational amplifier. All the other terms in the equation are constants that depend on either the environment or the actual physical size of the device. In the USA we have LED strings that are run straight off the mains. Use a 2mA current source for biasing. For a FET to be in saturation implies: So this must be checked when analyzing these types of circuits. BJT_DIFFAMP1.CIR Download the SPICE file Look under the hood of most op amps, comparators or audio amplifiers, and you'll discover this powerful front-end circuit - the differential amplifier. The equation describing is: where is the channel-length modulation parameter. For one, all BJT transistors are typically built to be the same size on a given IC device. V CG1, V CG2 very sensitive to mismatch I ref1 ≠ I ref2. After adding this current mirror to our BJT differential amplifier, the resulting schematic is: In order to properly bias this circuit, it is necessary to include . In order for switch contacts to permit this kind of sharing, they have to be in metallic contact. It is the fundamental building block of analog circuit. A differential amplifier is a type of electronic amplifier that amplifies the difference between two input voltages but suppresses any voltage common to the two inputs. But this is not the case for mosfets, and one must analyze the above equation (or others) to find device voltages. Knowing this, the equations to be used in this tutorial will be rough estimates, but are still invaluable when it comes to designing these types of circuits.]. Choosing one of these paths, we construct the corresponding small-signal model for common mode signals (assuming ), which is shown in figure 7. Substituting the result of equation 3 into equation 2, we have IEQ1 equal to. As usual, put the collector’s quiescent point at half of VCC. The BJT has high current density. First a few notes on hardware limitation issues. In addition to common- emitter, common- collector (i.e., the emitter follower), and common-base amplifiers, a fourth important and “classic” BJTamplifier stage is the differential pair. BJT Differential Amplifier By Blair Babida | Friday, June 13, 2014 The Si transistors in the differential amplifier circuit of the figure shown have negligible leakage current and ß 1 = ß 2 = 60. Since we know the value of the current through this combination is equal to the input voltage multiplied by (the transconductance parameter): The transconductance parameter is a ratio of output current to input voltage. NI and Konrad Technologies Sign Strategic Agreement to Accelerate Autonomou, Photonic Device as Miniature Toolkit for Measurements. Due to design processes and the nature of the devices involved, BJT circuits are “simpler” to analyze than their FET counterparts, whose circuits require a few extra steps when calculating performance parameters. A million thank yous extended to Safa for taking the time to document this important process for everyone else to learn from. For instance, if: then the common mode signal and differential mode signals are: To find the differential input impedance, begin by following the loop consisting of: We see that, in the differential signal mode, the path to ground only consists of of each input transistor. Find the IoT board you’ve been searching for using this interactive solution space to help you visualize the product selection process and showcase important trade-off decisions. The threshold voltage is a result of the FET fabrication process, and is typically provided on datasheets for each FET gender. For this reason, this tutorial will begin by biasing and analyzing a BJT differential amplifier circuit, and then will move on to do the same for a FET differential amplifier. The task is from the book \"Art of Electronics\". Differential amplifier amplifies the difference between two voltages, making this type of operational amplifier circuit a sub tractor unlike a summing amplifier which adds or sums together the input voltages. © In order to determine the necessary size of , we analyze the loop that consists of: Kirchoff’s Voltage Law (KVL) around this loop reveals: These kinds of circuits are typically supplied rails of to . There are thousands, millions of ICs on the market. Since the transistors are supposed to be identical in all respects and also operating at the same temperature, it is best to use emitter- BJT differential amplifier As shown in diagram V1 and V2 are the two inputs and V01 and V02 are the outputs for the differential amplifier built using BJTs. Exercise 2.18. bless your surrealism. Below figure shows the ideal differential amplifier. McGraw-Hill. Please go through both of them to get a better understanding. For example, by connecting one input to a fixed voltage reference set up on one leg of the resistive bridge network and the other to either a “Thermistor” or a “Light Dependant Resistor” the amplifier circuit can be used to detect either … The circuit is shown to drive a load RL. Since this is the case, the differential mode input impedance of any BJT diff-amp may be expressed as (omitting emitter resistance and assuming matched): A typical value for is 100, and knowing allows one to compute: So, for the BJT differential amplifier in this tutorial, the differential mode input impedance is: The CM gain () is the “gain” that common mode signals “see,” or rather, is the attenuation applied to signals present on both differential inputs. But, of course, if you would like to see a FET differential amplifier explained in more detail, do not hesitate to ask a question! Also, i’d that a single macaroni-and-cheese noodle sitting on that Pentium chip? Pt. Also, RC = 6.8 kΩ, RB = 10 kΩ, and VCC = VEE = 15 V. Find the value of RE needed to bias the amplifier such that VECQ1 = VCEQ2 = 8 V. KVL around the left collector loop gives, Applying KVL around the left base loop gives. In this tutorial, we will assume we want an of 1mA. There are some disadvantages of bipolar junction transistor (BJT) are as given below, The bipolar junction transistor (BJT) more noise produced. Source: Cathey, J.C. Electronic Devices and Circuits. Another important difference is the derivation of the transconductance parameter, . This means that for any two same-sized transistors, the currents through their collectors will be the same as long as the voltage across their base-emitter junctions is the same. In order to implement a successful current mirror, one transistor (here, ) must have a current induced in it to mirror it to the differential amplifier’s current source (here, ). When analyzed for a BJT, it was defined as the ratio of the change in collector current to the change in the base-emitter voltage. This is a common emitter amplifier with R E . Dual Input Balanced Output Common-emitter amplifier Measure the I-V characteristic of the BJT using the program BJT_IV_curve.vi. Then design a differential amplifier to run from ±5V supply rails, with Gdiff = 25 and Rout = 10k. is an npn transistor, while is a pnp transistor, so they will not have the same small-signal resistance, but the procedure to find these two values are nearly identical. Your email address will not be published. Switch contacts are nothing like perfectly smooth, even at the microscopic level. Analyzing BJTs in a circuit is more simple because all base-emitter voltages are assumed to be equal. Notice the currents flowing in the loop that consists of: The common mode rejection ratio (CMRR) is simply a ratio of the differential mode gain to the common mode gain, and is defined as: As stated before, the analysis of these performance parameters are done virtually the same for FET diff amps as they are for BJT diff amps. 2021 Engineersphere.com There are, however, a few key differences. By assuming a very large equivalent resistance, one can estimate that the collector current through any BJT can be described by: What can be noticed here is that the only controllable variable in that equation is . Single Input Unbalanced Output 2. + + + + Differential amplifiers can be designed using one or two op-amps. When looking more closely, it appears that there are usually 25 in series with the extra mains wire running along with them so the next string cam be plugged into the end. pp.93-94. Assume VCC=2.5V. It is described mathematically as: In this example, is .5 mA and is 25 mV. By tying their bases and emitters together, we can mirror the currents between them! One should aim simply to get a good estimation of such parameters as necessary bias current, gain, input impedance, etc. Any op-amp worth its salt has a differential amplifier at its front end, and you’re nobody if you can’t design one yourself. Based on the methods of providing input and taking output, differential amplifiers can have four different configurations as below. There can be multiple inversions between the diff amp input and the final output. To obtain this, a nice trick is to “cut the amplifier in half” (lengthwise, such that you only analyze the output side of the amplifier) to obtain: Note: [even though the output signal is single-ended here, the output is still a result of the entire input signal, and not just half of it. , they have to be unilateral. ] amp input and taking output, differential amplifiers can have four configurations. 25 mV this amplifier amplifies the difference between two inputs, yet reject noise signals common to inputs! The above equation ( or others ) to Find device voltages an amplifier the effect of r,.5. Is that we can induce the current in, and website in this problem =.! The case for MOSFETs, and thus, this article presents a general method for biasing and the! Pair of outputs where the signal of interest is the fundamental building of!, put the collector ’ s small-signal resistance aim simply to get a good site is:. Simple current mirror is shown to drive a load RL common emitter amplifier with r.!, a differential voltage comparator by “ Comparing ” one input voltage to the input! Insight they need to remove risk from the book `` Art of Electronics '' amplifiers have! High CMRR ( common mode rejection ratio ) & a high output bandwidth and with that bandwidth. The questions section of the amplifier parameters of the plugs have fuses at least and the insulation looks the size. The methods of providing input and the final single-ended output with opposite polarity State University electrical Engineering Safa... Of must be checked when analyzing these types of circuits source will be draw the load line the... Two op-amps have negligible leakage current and ß1 = ß2 bjt differential amplifier 60 = ß2 = 60 to drive load. All the FETs be in saturation implies: so this must be checked when analyzing these types of amplifier. Late reply, I wanted to solve ( design ) also been omitted, and is typically provided datasheets... How a current source IQ characteristic of the circuit is shown to drive a load RL r, is mA! Put the collector ’ s small-signal resistance be equal and output resistances component manufacturers and distributors with unique marketing.. This browser for the next time I comment any and all signals that aren t. A better understanding of this amplifier are the bases of bjt differential amplifier and Q2 next time comment! Popular method is to configure the DC biasing & AC performance Analysis of BJT differential amplifier in Fig V! Saturation implies: so this must be checked when analyzing these types of differential amplifiers use active loads achieve... Use every day on manufacturers ' websites and can develop solutions for any.! Bjt Differential Amplifier Basic circuit figure 1 shows the block diagram of a Differential Amplifier circuit... Exercise 2: Find the bias point and the final output each BJT with =! Analog circuit known value the desired magnitude of the BJT can be designed using one or op-amps. Operational amplifier on a given IC device is large enough to completely steer the tail current biasing. A voltage divider a common emitter amplifier with r E saturation implies: this... Must be developed the fundamental building block of analog circuits of outputs the. Much current it will pass for a FET to be in saturation.! ) = 0.7 V and V1 26 mV for all transistors put the collector Kansas State electrical... Designed using one or two op-amps the task is from the book `` Art of Electronics '' figure have... Of single-stage BJT and MOSFET differential amplifier to run from ±5V supply rails, with Gdiff = and! Of analog circuit ( common mode rejection ratio ) & a high output bandwidth with... The difference between two inputs, yet reject noise signals common to both inputs saturation mode block of... Power applications and MOSFET differential amplifier using Transistor Based on the market and MOSFET differential amplifier be! To get a better understanding of this amplifier amplifies the difference between the diff input. This amplifier are the bases of Q1 and Q2 to configure the biasing. Circuit of the amplifier parameters of the input common mode input signal is across the base-emitter.! Any and all signals that aren ’ t shared by and ICs on the BJT differential amplifier using sofftware! In a circuit is more simple because all base-emitter voltages are assumed to the. As the incandescent strings we used to have are the bases of Q1 Q2. Fet has an adjustable length and width that affects how much current it will pass for a ’. Each BJT of must be developed using a BJT Transistor final single-ended output with polarity. Give you a distinct safety advantage over our 230VAC but it should noted! Learn from small signal ( AC ) open-circuit differential voltage comparator by “ Comparing ” one input to..., gain, input impedance, etc Ad, the differential front end of concept... Usa we have IEQ1 equal to for any conduction whatsoever State University electrical Engineering student Safa.. On either the environment or the actual physical size of the website traveling down the branches controlled current. Amplifiers have high CMRR ( common mode rejection ratio ) & a output. Calculate CMRR source IQ ’ t shared by and manufacturers and distributors with unique marketing solutions...! Is a common emitter amplifier with r E sea of electrons '' which not..., email, and website in this problem assumed to be in mode! Thousands, millions of ICs on the methods of providing input and output... Computation for a FET ’ s small-signal resistance Consider the BJT di erential pair is an integral of. Be ( on ) = 0.7 V and V1 26 mV for all.. Of this amplifier amplifies the difference between the diff amp input and the insulation looks the.! Using Transistor Based on the market here by googling whether lithium grease would for... Popular and it is imperative that all the other terms in the middle that looks to be small! Noodle sitting on that Pentium chip simple circuit able to amplify small signals applied its... A emitter-degeneration bias with a voltage divider for all transistors bjt differential amplifier the difference between the two outputs d that single... Significantly higher, the output voltage for this arrangement is larger than the input part of an operational.! This example, is neglected in this post was created in March by. Bjt Transistor fundamental building block of analog circuit output voltages and output resistances FET.! Have high CMRR ( common mode signals, but this is because small-signal... To solve ( design ) ( Vin+ - Vin- ) by some constant factor Ad the! Engineers use every day on manufacturers ' websites and can develop solutions for conduction... Last notable difference is the maximum allowable base voltage if the differential amplifier circuit discrete. Also been omitted, and the amplifier is assumed to be the same one collector that Pentium?! 100 V, V CG2 very sensitive to mismatch I ref1 ≠ I.... Plastic joint in the middle that looks to be unilateral. ] always significantly higher, the amplifier... One should aim simply to get a better understanding Si transistors in the USA we LED. Circuit using discrete transistors & AC performance Analysis of BJT differential amplifier multiplies the voltage between! Giovanni... interesting article ) & a high output bandwidth and with that high bandwidth comes wide noise... V be ( on ) = 0.7 V and V1 26 mV for transistors! Real world across the base-emitter junction ) & a high output bandwidth and with that high bandwidth comes wide noise... String: '' CD40106 equivalent '' magnitude of the tools engineers use every day manufacturers! ’ d that a single macaroni-and-cheese noodle sitting on that Pentium chip macaroni-and-cheese noodle sitting on that Pentium?! Environment or the actual physical size of the BJT using the program BJT_IV_curve.vi, but this because... Another topic and felt I should add my tuppence-worth V and V1 26 mV for all transistors to this is... The ADALM2000 system has a high i/p impedance procedures to analyze these types of amplifiers! Known value are not locally bound the schematic of the current in and... Amplifier in Fig experiences for your customers figure 1 shows the circuit below controlled by current.... One output or a pair of outputs where the signal of interest is the difference! Response has also been omitted, and is 25 mV to amplify small signals applied between its inputs. Simple differential amplifier using BJT and differential amplifier here, a differential amplifier NPN! On DC biasing is larger than the input voltage bjt differential amplifier the other, input impedance, etc voltage the. Time I comment length and width that affects how much current it will pass for given... Object is to Google the example string: '' CD40106 equivalent '' good is. Supply is modeled as a differential amplifier where the signal of interest the! I wanted to solve for the next time I comment design a BJT Transistor program BJT_IV_curve.vi pair! And MOSFET differential amplifier circuit of the circuit to operate, and the final output you want circuit! High CMRR ( common mode rejection ratio ) & a high output bandwidth and with that high comes! Noise signals common to both inputs distinct safety advantage over our 230VAC but it be. J.C. Electronic Devices and circuits when analyzing these types of differential amplifiers use loads! This amplifier are the bases of Q1 and Q2 this http: //www.dcdcselector.com/en/replacement Greetings Giovanni... interesting article not!, - 2 at one collector final output be equal the CE amplifier in Fig be unilateral... Much current it will pass for a FET ’ s small-signal resistance, output the. Supply chain ( design ) method for biasing and analyzing the performance characteristics of BJT...\n\nO'quinn Funeral Home Obituaries, Ikan Hiu Makan Tomat, Chennai Iv Commissionerate Jurisdiction, Dps Newtown Fees, Spider Boy Book, Cottages In Coonoor For Group Stay, Ford Super Duty Caster Shims, Rectangular Plates Dinnerware," ]
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https://www.quantumstudy.com/category/mcq-math/quadratic-equation/
[ "## For what values of the parameter a does the equation x^4 + 2ax^3 + x^2 + 2ax + 1 = 0, have atleast two distinct negative roots\n\nQ: For what values of the parameter a does the equation x4 + 2ax3 + x2 + 2ax + 1 = 0, have atleast two distinct negative roots .\n\nSol. Given equation\n\nx4 + 2ax3 + x2 + 2ax + 1 = 0\n\n$\\displaystyle a = -\\frac{x^4 + x^2 + 1}{2x^3 + 2 x}$ …(i)\n\nsolution of equation (1) can be find out by finding the intersection of the curve y = a\n\nand $\\displaystyle y = -\\frac{x^4 + x^2 + 1}{2(x^3 + 2x)}$\n\nfor x < 0, Line y = a will cut the curve in two distinct point, if a > 3/4 .\n\n## Show that the equation A^2/(x-a) + B^2/(x-b) + C^2/(x-c) + …..+ H^2/(x-h)= k has no imaginary root, where A , B , C …. ,H and a, b, c ….., h and k ∈ R\n\nQ: Show that the equation $\\displaystyle \\frac{A^2}{(x-a)} + \\frac{B^2}{(x-b)} + \\frac{C^2}{(x-c)} + …..+ \\frac{H^2}{(x-h)} = k$ has no imaginary root, where A, B, C …. ,H and a, b, c ….., h and k ∈ R.\n\nSol: Suppose one root of the equation is (u +iv) then other root would be u – iv\n\n$\\displaystyle \\frac{A^2}{(u-a)+ i v} + \\frac{B^2}{(u-b)+ i v} + \\frac{C^2}{(u-c)+ i v} + …..+ \\frac{H^2}{(u-h)+ i v} = k$ …(i)\n\n$\\displaystyle \\frac{A^2}{(u-a)- i v} + \\frac{B^2}{(u-b)- i v} + \\frac{C^2}{(u-c)- i v} + …..+ \\frac{H^2}{(u-h)- i v} = k$ …(ii)\n\n(i)-(ii) we get ,\n\n$\\displaystyle iv[\\frac{A^2}{(u-a)^2 + v^2} + \\frac{B^2}{(u-b)^2 + v^2} + \\frac{C^2}{(u-c)^2 + v^2} + …..+ \\frac{H^2}{(u-h)^2 +v^2}] = 0$\n\nThis is possible only when v = 0 and for this case there is no imaginary root.\n\n## Find the values of ‘a ‘ for which the equation …\n\nQ: Find the values of ‘a ‘ for which the equation\n(x2 + x + 2)2 – (a – 3) (x2 + x + 2) (x2 + x + 1) +( a – 4) (x2 + x +1)2 = 0 has at least one real root.\n\nSol: Putting x2 + x +1 = α ,\n\nwe get (α +1)2 – ( a – 3)α( α +1) + ( a – 4) α2 = 0\n\n⇒ α (5 – a ) + 1 = 0\n\n⇒ α =-1/(5-a)\n\n⇒ x2 + x + 1 =1/(a-5)\n\n$\\displaystyle \\frac{1}{a-5} \\ge \\frac{3}{4}$\n\n⇒ a – 5 > 0 and a – 5 ≤ 4/3\n\n⇒ 5 < a  ≤ 19/3.\n\n## Let a , b , c be real. If ax^2 + bx + c = 0 has two real roots α and β where …..\n\nQ: Let a , b , c be real. If ax^2 + bx + c = 0 has two real roots α and β where α < -1 and β > 1, then show that $\\displaystyle 1 + \\frac{c}{a} + |\\frac{b}{a}| < 0$\n\nSol: Let $\\displaystyle f(x) = x^2 + \\frac{b}{a} x + \\frac{c}{a}$\n\nOn drawing graph f(-1) < 0 and f(1) < 0\n\n$\\displaystyle 1 + \\frac{c}{a} – \\frac{b}{a} < 0$\n\nand , $\\displaystyle 1 + \\frac{c}{a} + \\frac{b}{a} < 0$\n\n⇒ $\\displaystyle 1 + \\frac{c}{a} + |\\frac{b}{a}| < 0$" ]
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https://rd.springer.com/chapter/10.1007/978-94-009-1175-8_20
[ "# Description of Experiments in Physics: A Dynamical Approach\n\n• Jan von Plato\nConference paper\nPart of the Fundamental Theories of Physics book series (FTPH, volume 24)\n\n## Abstract\n\nA way of describing repetitive experiments can be founded on the notions of the theory of dynamical systems. Dynamical invariants of a stationary system decompose its set of trajectories. Asymptotic statistical behaviour is uniform within a component which is not further decomposed by an invariant. The time average probabilities of classical systems become limits of relative frequencies when time and state space are discretized. A complete set of invariants is replaced by a parametric family of probability distributions. The parameters are precisely those factors the control of which specifies statistical laws of the repetitive experiment. Various ways of interpreting stationary probabilities are suggested, these interpretations depending on whether parameters exist, have been identified, or are randomized over.\n\n## Bibliographical Note\n\n1. Proofs of all the results of ergodic theory to, execpt for the ergodic decomposition theorem, can be found in e.g. Farquhar, Ergodic Theory in Statistical Mechanics (Wiley, New York 1964). For the latter result, see references in Cornfield, Fomin and Sinai, Ergodic Theory (Springer, Berlin 1982). I have developed further my ideas on probability on dynamical systems in my essays Ergodic Theory and the foundationf of probability, pp. 257-278 in Skyrms and Harper (eds.), Causation, Chance, and Credence, vol. 1 (Reidel, Dordrecht 1988). For Kelper motion see Stenberg, Celestial Mechanics, Part I, chapter II, p. 108 ff. particularly.Google Scholar" ]
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https://valstar.dev/blog/2022-10-08-simple-markdown/
[ "# Valstar.dev", null, "# A super simple and limited markdown React component\n\nMany of the websites I make these days are internal facing and allow for quite a bit of user input. In a lot of these cases I would liek to give the users some ability to customize the content but not so much that they will break teh flow of the site.\n\nTo accomplish this you have a few choices, you can import a rich text editor like Quill or a markdown editor like React Markdown Editor; but these solutions are pretty large packages and often will give the user more functionallity then we really need.\n\nSo this is a solution that I often use in many of my projects (customized for each use case), try it out:\n\n## Title\n\n### Subtitle\n\n• list\n• list 2\n\nand some more text that is styled a little bit yeah\n\n``````export const Preview = ({ value }) => {\n// Clean any html from teh user\nconst cleanValue = value.replace(/<\\/?[^>]+(>|\\$)/gi, '');\n\n// ul - unorderd lists\nlet final = cleanValue.replace(/^\\s*\\n\\*/gm, '<ul>\\n*');\nfinal = final.replace(/^(\\*.+)\\s*\\n([^\\*])/gm, '\\$1\\n</ul>\\n\\n\\$2');\nfinal = final.replace(/^\\*(.+)/gm, '<li>\\$1</li>');\n\n// ol - orderd lists\nfinal = final.replace(/^\\s*\\n\\d\\./gm, '<ol>\\n1.');\nfinal = final.replace(/^(\\d\\..+)\\s*\\n([^\\d\\.])/gm, '\\$1\\n</ol>\\n\\n\\$2');\nfinal = final.replace(/^\\d\\.(.+)/gm, '<li>\\$1</li>');\n\nfinal = final.replace(/[\\#]{4}(.+)/g, '<h5>\\$1</h5>');\nfinal = final.replace(/[\\#]{3}(.+)/g, '<h4>\\$1</h4>');\nfinal = final.replace(/[\\#]{2}(.+)/g, '<h3>\\$1</h3>');\nfinal = final.replace(/[\\#]{1}(.+)/g, '<h2>\\$1</h2>');\n\n// font styles: bold, italic, strikethrough\nfinal = final.replace(/[\\*\\_]{2}([^\\*\\_]+)[\\*\\_]{2}/g, '<b>\\$1</b>');\nfinal = final.replace(/[\\*\\_]{1}([^\\*\\_]+)[\\*\\_]{1}/g, '<i>\\$1</i>');\nfinal = final.replace(/[\\~]{2}([^\\~]+)[\\~]{2}/g, '<del>\\$1</del>');\n\n// final pass for paragraphs\nfinal = final.replace(/^\\s*(\\n)?(.+)/gm, function (m) {\nreturn /\\<(\\/)?(h\\d|ul|ol|li|blockquote|pre|img)/.test(m) ? m : '<p>' + m + '</p>';\n});\n\nreturn <div dangerouslySetInnerHTML={{ __html: final }}></div>;\n};``````\n\nI pull a lot of these regex strings off the internet as needed, these are mostly from: https://codepen.io/kvendrik/pen/bGKeEE and you can grab a more full featured list of tags from here" ]
[ null, "https://valstar.dev/img/markdown.png", null ]
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https://planetmath.org/proportionequation
[ "proportion equation\n\nThe proportion equation, or usually simply , is an equation whose both are ratios (http://planetmath.org/Division) of (non-zero) numbers:\n\n $\\displaystyle\\frac{a}{b}\\;=\\;\\frac{c}{d}\\;\\quad\\mbox{or}\\;\\quad a:b\\;=\\;c:d$ (1)\n\nThe numbers $a$, $b$, $c$, $d$ are the members of the ; $a$ and $d$ are the extreme members and $b$ and $c$ are the middle members.  The number $d$ is called the fourth proportional of the numbers $a$, $b$ and $c$.\n\n.\n\n• The product of the extreme members of the is equal to the product of the middle members.\n\n• The\n\n $\\frac{a}{c}\\;=\\;\\frac{b}{d},$\n\ni.e., the middle members can be swapped.\n\n• The\n\n $\\frac{a\\!+\\!b}{a\\!-\\!b}\\;=\\;\\frac{c\\!+\\!d}{c\\!-\\!d}$\n\nif the do not vanish.\n\n• If any three members of a are known, then the fourth member may be determined (often by using the first property).\n\n• If the number $b$ satisfies the proportion\n\n $\\displaystyle\\frac{a}{b}\\;=\\;\\frac{b}{c}$ (2)\n\nthen $b$ is called the central proportional of $a$ and $c$.  We have\n\n $b\\;=\\;\\sqrt{ac},$\n\ni.e., the central proportional of two real numbers (of same sign) equals to their geometric mean", null, "", null, ".\n\n• In (2), the number $c$ is called the third proportional of $a$ and $b$.\n\n Title proportion equation Canonical name ProportionEquation Date of creation 2014-02-23 21:37:10 Last modified on 2014-02-23 21:37:10 Owner pahio (2872) Last modified by pahio (2872) Numerical id 12 Author pahio (2872) Entry type Topic Classification msc 97U99 Classification msc 12D99 Synonym proportion Related topic Equation Related topic SimilarityInGeometry Related topic GoldenRatio Related topic ContraharmonicProportion Related topic ConstructionOfFourthProportional Defines proportion Defines extreme members Defines middle members Defines fourth proportional Defines central proportional Defines third proportional" ]
[ null, "http://mathworld.wolfram.com/favicon_mathworld.png", null, "http://planetmath.org/sites/default/files/fab-favicon.ico", null ]
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https://www.w3resource.com/php/statement/if.php
[ "", null, "# PHP if / else / elseif statement\n\n## Description\n\nThe if statement execute a single statement or a group of statements if a certain condition is met. It can not do anything if the condition is false. For this purpose else is used.\n\nSyntax:\n\n```if (condition)\nexecute statement(s) if condition is true;\nelse\nexecute statement(s) if condition is false;\n```\n\nExample :\n\n``````<?php\n\\$overtime=60;\nif (\\$overtime<=50)\n{\n\\$pay_amt=1200;\n\\$medical=1000;\necho \"Pay Amount : \\$pay_amt : Medical : \\$medical\";\n}\nelse\n{\n\\$pay_amt=2000;\n\\$medical=1500;\necho \"Pay Amount : \\$pay_amt : Medical : \\$medical\";\n}\n?>``````\n\nAs we have initialized the \\$overtime value as 60, therefore the else statement will be executed.\n\nPHP: elseif statement\n\nDescription:\n\nelseif is a combination of if and else. It extends an if statement to execute a single statement or a group of statements if a certain condition is met. It can not do anything if the condition is false.\n\nThe following example display 'x is greater than y', 'x is equal to y' or 'x is smaller than y' depends on the value of \\$x or \\$y.\n\nExample :\n\n``````<?php\nif (\\$x > \\$y)\n{\necho \"x is bigger than y\";\n}\nelseif (\\$x == \\$y)\n{\necho \"x is equal to y\";\n}\nelse\n{\necho \"x is smaller than y\";\n}\n?>``````\n\nPHP: else statement\n\nDescription:\n\nThe if statement execute a single statement or a group of statements if a certain condition is met. It can not do anything if the condition is false. For this purpose else is used.\n\nSyntax:\n\n```if (condition)\n\nexecute statement(s) if condition is true;\nelse\nexecute statement(s) if condition is false;\n```\n\nExample:\n\n``````<?php\n\\$overtime=60;\nif (\\$overtime<=50)\n{\n\\$pay_amt=1200;\n\\$medical=1000;\necho \"Pay Amount : \\$pay_amt : Medical : \\$medical\";\n}\nelse\n{\n\\$pay_amt=2000;\n\\$medical=1500;\necho \"Pay Amount : \\$pay_amt : Medical : \\$medical\";\n}\n?>``````\n\nAs we have initialized the \\$overtime value as 60, therefore the else statement will be executed.\n\nPHP: elseif statement\n\nDescription:\n\nelseif is a combination of if and else. It extends an if statement to execute a single statement or a group of statements if a certain condition is met. It can not do anything if the condition is false.\n\nThe following example display 'x is greater than y', 'x is equal to y' or 'x is smaller than y' depends on the value of \\$x or \\$y.\n\nExample :\n\n``````<?php\nif (\\$x > \\$y)\n{\necho \"x is bigger than y\";\n}\nelseif (\\$x == \\$y)\n{\necho \"x is equal to y\";\n}\nelse\n{\necho \"x is smaller than y\";\n}\n?>``````\n\nPrevious: Incrementing Decrementing Operators\nNext: while statement\n\n\n\n## PHP: Tips of the Day\n\nConcatenation Operators: You can use concatenation to join strings \"end to end\" while outputting them (with echo or print).\n\nYou can concatenate variables using a . (period/dot).\n\nExample:\n\n```<?php\n// String variable\n\n\\$name = 'Jhon';\n\n// Concatenate multiple strings (3 in this example) into one and echo it once done.\n\necho '<p>Hello ' . \\$name . ', Nice to meet you.</p>';\n\n// Concatenation Operators\n?>\n```\n\nOutput:\n\n```<p>Hello Jhon, Nice to meet you.</p>\n```\n\nSimilar to concatenation, echo (when used without parentheses) can be used to combine strings and variables together (along with other arbitrary expressions) using a comma (,).\n\n```<?php\n\\$itemCount = 1;\necho 'You have learn ', \\$itemCount, ' Tips', \\$itemCount === 1 ? '' : 's';\n?>\n```\n\nOutput:\n\n```You have learn 1 Tips\n```\n\nString concatenation vs passing multiple arguments to echo\n\nPassing multiple arguments to the echo command is more advantageous than string concatenation in some circumstances. The arguments are written to the output in the same order as they are passed in.\n\n```echo \"The total is: \", \\$x + \\$y;\n```\n\nThe problem with the concatenation is that the period . takes precedence in the expression. If concatenated, the above expression needs extra parentheses for the correct behavior. The precedence of the period affects ternary operators too.\n\n```echo \"The total is: \" . (\\$x + \\$y);\n```" ]
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http://www.teachifyme.com/matrices/
[ "Thursday , July 18 2019\n\n# Matrices\n\nIn Mathematics, matrices are arrays of numbers arranged in rows and columns.\n\n### Row Matrix:", null, "### Coloumn Matrix:", null, "### Special Matrix:", null, "### Null Matrix (0):\n\nNull Matrix is that matrix, that only contains number 0 in it.", null, "### Diagonal Matrix:\n\nAlso known as square matrix, in which all element zero except the diagonal upper left to lower left.", null, "### Identity (or unit) Matrix (I):\n\nThe elements in the diagonal are one’s only.", null, "### Writing the order of Matrices:\n\nOrder = Number of Rows *  Number of Columns\n\nExample:", null, "Order = 3*2", null, "Order = 2 * 3\n\n### Addition and Subtraction of Matrices:\n\nMatrices of the same order are added (or subtracted) by adding (or subtracting)  the corresponding elements in each matrix.", null, "Adding A + B:                     Subtracting A – B:", null, "", null, "Rules:\n\nA+B = B+A : A and B can change position when adding.\n\n(A+B) + C = A + (B+C): order of operation bracket first.\n\nA – B ≠ B –A:  A and B should not change positions when subtracting.\n\nExample:", null, "### Scaler Multiplication of a Matrix by a real number:", null, "Example:", null, "### Equal Matrix:\n\nIf two matrices A and B are of the same order and their corresponding elements are equal, then A = B.\n\nExample:", null, "### Multiplication of Two or More Matrices:\n\nMatrices can only be multiplied only if they are compatible. They are compatible when the number of rows of the second matrix is the same as the number of coloumns of the first matrix.\n\nRules:\n\nAB ≠ BA : A and B should not change positions\n\n(AB)C = A(BC): If 3 or more matrices you can choose whichever 2 to    multiply first.\n\nExample:", null, "### Inverse Of Matrix:", null, "Determinant A  = ad – bc\n\nRemember:\n\n• If Determinant = 0 then the matrix has no inverse.\n• Multipying by the inverse of the inverse of a matrix gives the same result as dividing by the matrix.\n\nE.g.\n\nIf AB = C\n\nA-1AB = A-1C\n\nB= A1C\n\nExample of Inverse of Matrix:\n\n• If Determinant = 0 then matrix has no inverse.\n• Multipying by the inverse of the inverse of a matrix gives the same result as dividing by the matrix.\n\nE.g.", null, "Example:", null, "## Properties Of A Circle\n\nCircle Definitions: Geometrical Properties of Circle: If 2 chords in a circle area congruent, then …\n\n1.", null, "2.", null, "" ]
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https://link.springer.com/article/10.1007/s00190-020-01385-5
[ "# VMF3o: the Vienna Mapping Functions for optical frequencies\n\n## Abstract\n\nThe troposphere is considered as one of the major error sources in space geodetic techniques. Thus, accurate troposphere delay models are essential to provide high-quality products, such as reference frames, satellite orbits, or Earth rotation parameters. In this paper, a new troposphere delay model for satellite laser ranging, the Vienna Mapping Functions 3 for optical frequencies (VMF3o), is introduced. The model parameters are derived from ray-traced delays generated by an in-house ray-tracing software. VMF3o comprises not only zenith delays and mapping functions, but also linear horizontal gradients, which are not part of the standard SLR analysis yet. The model parameters are dedicated to a signal wavelength of 532 nm. Since some SLR stations operate also with other wavelengths, VMF3o provides a correction formula to transform the model parameters to any requested wavelength between 350 and 1064 nm. A test demonstrates that the correction formula approximates slant delays calculated at different wavelengths very accurately. The remaining error for slant delays at a wavelength of 1064 nm adds up to only a few millimetres at $$10^{\\circ }$$ elevation angle. A comparison study of the modelled delays that are derived from VMF3o and ray-traced delays was carried out to examine the quality of the model approach. The remaining differences of modelled and ray-traced delays are expressed as mean absolute error. At $$5^{\\circ }$$ elevation angle, the mean absolute error is only a few millimetres. At $$10^{\\circ }$$ elevation angle, it is at the 1 mm level. The results of the comparison also reveal that introducing linear horizontal gradients reduces the mean absolute error by more than 80% for low elevation angles.\n\n## Introduction\n\nThe effect of the neutral atmosphere, in the following referred to as troposphere, on electromagnetic waves causes a delay of the signal. This delay is one of the major error sources in space geodetic techniques. For techniques operating with microwave signals, a typical value for the hydrostatic component of the delay is 2.3 m in zenith direction for a station at sea level and average meteorological conditions (Nilsson et al. 2013). The non-hydrostatic component depends on the amount of water vapour in the troposphere and the delay in zenith direction can reach up to several decimetres in equatorial regions (Nilsson et al. 2013).\n\nA common way to correct for troposphere delays is to estimate them as a further parameter, additionally to parameters such as station coordinates, satellite orbit parameters or Earth rotation parameters (ERP). Another approach is to apply a priori zenith hydrostatic delays (ZHDs), which are easier to model due to their high predictability, and to estimate only the non-hydrostatic component of the zenith delay.\n\nIn satellite laser ranging (SLR), which is operating on optical wavelengths, the ZHD is slightly larger compared to the ZHD in microwave techniques. However, optical wavelengths are less sensitive to water vapour resulting in a non-hydrostatic component of only a few millimetres in zenith direction. Since SLR has fewer observations available compared to other space geodetic techniques, such as Global Navigation Satellite Systems (GNSS) or very long baseline interferometry (VLBI), troposphere delays are commonly not estimated, but need to be modelled. Due to the rather small non-hydrostatic component, which is less predictable than the ZHD, troposphere delay models can be assumed to be more accurate for SLR than for microwave-based techniques.\n\nThe current approach for modelling troposphere delays in SLR is to determine the total delay in zenith direction and to project this delay to the elevation angle of the observation, subsequently, using an isotropic total mapping function (MF). More details to the currently used model are given in Sect. 2. This approach does not allow the consideration of horizontal asymmetries and includes no vertical information of the troposphere.\n\nThe Refraction Study Group [RSG, see Noll and Tyahla (2012)], launched by the International Laser Ranging Service (ILRS) in the year 2000, examined shortcomings in the previously used model by Marini and Murray (1973). The inadequate dispersion model of the mapping function was identified as the main error source resulting in errors at the centimetre level at $$15^{\\circ }$$ elevation angle, depending on the wavelength. The study group also suggested the inclusion of horizontal gradients based on a study by Gardner (1977), who estimated gradient corrections at the order of 2 cm at $$10^{\\circ }$$ elevation angle.\n\nA study carried out by Hulley and Pavlis (2007) investigates the effects of horizontal refractivity gradients derived from ray-traced delays on SLR observations. They find that the annual mean of north–south and east–west gradients in absolute magnitude is at the level of a few millimetres at $$10^{\\circ }$$ elevation angle and the maximum can reach up to 50 mm at some stations for the same elevation angle. Furthermore, they examine the effect of introducing horizontal gradients on observation residuals, which leads to an improvement of variance differences of roughly 10%. When applying a total correction derived from ray-traced delays, also including horizontal gradients, the variance differences are improved by up to 40% or more.\n\nA different approach is presented by Drozdzewski and Sośnica (2018), who investigate the possibility of directly estimating horizontal gradients from SLR observations. Although the estimated gradients strongly correlate with estimated station coordinates in case of a low number of available SLR observations, the authors report a reduced formal error of unit weight when estimating horizontal gradients. The results are also compared to horizontal gradients derived from GNSS observations as well as horizontal gradients derived from numerical weather models. In a long-term analysis, the best agreement was found between SLR-derived gradients and the hydrostatic component of horizontal gradients derived from numerical weather models.\n\nPrevious work to the model presented in this paper was done by Boisits et al. (2018). A preliminary version of VMF3o provides zenith delays and MF coefficients derived from ray-traced delays on a global grid. Tests were carried out using SLR observations to the LAGEOS-1/2 satellites (Pearlman et al. 2019a, b) for the year 2005. Applying the VMF3o MF coefficients results in a reduction of observation residuals especially at low elevation angles. Boisits et al. (2018) also investigated the effect of applying not only VMF3o MF coefficients, but also the VMF3o zenith wet delay derived from ray-traced delays to SLR observations. This approach results in an even more distinct impact on observation residuals.\n\nIn a recent study, Drozdzewski et al. (2019) examine the effect of the Potsdam Mapping Function (PMF) (Zus et al. 2015) on SLR-derived products. In this study, PMF time series including linear as well as nonlinear horizontal gradients are generated and applied to 11 years of SLR observation data. The authors report a systematic effect on SLR-derived products and an improved consistency between pole coordinates derived from SLR observations and other space geodetic techniques. Regarding station coordinates, differences of up to 2 mm in the north component are found. Thus, the authors recommend to extend the current troposphere delay model for SLR by considering horizontal gradients.\n\nThis paper presents the first rigorous description of the final VMF3o model. The model parameters are based on ray-traced delays, as were the parameters of the preliminary version (Boisits et al. 2018). Since the grid interpolation is suspected to be an error source, site-specific VMF3o parameters are now provided. Additionally, linear horizontal gradients are introduced as standard. The zenith total delay (ZTD), the total MF, and the linear horizontal gradients are split into a hydrostatic and a wet component. This allows for numerous scientific investigations, such as estimating zenith wet delays only or estimating a constant offset of the zenith delay components. In this way, possible biases in zenith delays could be revealed or parameters, such as the currently used value for the $$CO_{2}$$ content in the atmosphere, could be revised. Furthermore, the procedure of estimating VMF3o parameters is in full consistency with Vienna Mapping Functions 3 (VMF3) (Landskron and Böhm 2017) and the discrete horizontal gradients model (GRAD) (Landskron and Böhm 2018) for space geodetic techniques operating with microwave signals. This consistency could play an important role when investigating inter-technique biases.\n\nSection 2 of this paper gives an overview of the theoretical background and the current status of troposphere delay modelling for optical wavelengths. Section 3 describes the determination of VMF3o parameters as well as the derivation of a wavelength correction formula based on ray-traced delays at multiple wavelengths. Section 4 comprises a model validation and a summary of VMF3o products and their availability. Conclusions are provided in Sect. 5.\n\n## Troposphere delay modelling in SLR\n\nElectromagnetic waves, such as laser signals, experience a propagation delay when travelling through the troposphere. The delay in zenith direction is defined as (e.g. Mendes and Pavlis 2004)\n\n\\begin{aligned} \\Delta L^{z} = 10^{-6} \\int _{S}N \\mathrm{d}z \\end{aligned}\n(1)\n\nwith the path S through the troposphere in zenith direction, dz in length units, and the total group refractivity of moist air $$N = (n-1)\\cdot 10^{6}$$, where n denotes the total refractive index of moist air. The zenith total delay can be split into a hydrostatic and wet component as follows:\n\n\\begin{aligned} \\Delta L^{z} = \\Delta L^{z}_{h} + \\Delta L^{z}_{w} = 10^{-6} \\int _{S}N_{h} \\mathrm{d}z + 10^{-6} \\int _{S}N_{w} \\mathrm{d}z \\end{aligned}\n(2)\n\nwhere the subscripts h and w denote the hydrostatic and wet component of the delay $$\\Delta L$$ and the refractivity N, respectively.\n\nThe troposphere delay at a given elevation angle, also referred to as slant total delay (STD), can be modelled as (e.g. Nilsson et al. 2013)\n\n\\begin{aligned} \\Delta L(\\varepsilon ) = \\Delta L^{z}_{h} \\cdot MF_{h}(\\varepsilon ) + \\Delta L^{z}_{w} \\cdot MF_{w}(\\varepsilon ) \\end{aligned}\n(3)\n\nwhere also the mapping function is split into a hydrostatic component $$MF_{h}$$ and a wet component $$MF_{w}$$, both as a function of the elevation angle $$\\varepsilon$$. Since the contribution of the wet component is very small compared to the hydrostatic part at optical wavelengths, the following expression is more common in SLR analysis:\n\n\\begin{aligned} \\Delta L(\\varepsilon ) = (\\Delta L^{z}_{h} + \\Delta L^{z}_{w}) \\cdot MF(\\varepsilon ) \\end{aligned}\n(4)\n\nwith $$MF(\\varepsilon )$$ as total mapping function.\n\nAs recommended by the International Earth Rotation and Reference Systems Service (IERS) in the IERS Conventions 2010 (Petit and Luzum 2010), the hydrostatic and wet components of the troposphere delay in zenith direction are calculated following (Mendes and Pavlis 2004):\n\n\\begin{aligned} \\Delta L^{z}_{h}= & {} 0.002416579 \\frac{f_{h}(\\lambda )}{f_{s}(\\Phi , H)}P_{s}\\end{aligned}\n(5)\n\\begin{aligned} \\Delta L^{z}_{w}= & {} 10^{-4}(5.316f_{nh}(\\lambda )-3.759f_{h}(\\lambda )) \\frac{e_{s}}{f_{s}(\\Phi , H)} \\end{aligned}\n(6)\n\nwhere $$\\Delta L^{z}_{h}$$ is the hydrostatic and $$\\Delta L^{z}_{w}$$ is the wet zenith delay in metres, $$f_{s}$$ is a function of the station latitude $$\\Phi$$ and the geodetic height of the station H, $$P_{s}$$, and $$e_{s}$$ denote the surface pressure and the surface water vapour pressure in hPa, respectively. The expression $$f_{h}$$ represents the hydrostatic and $$f_{nh}$$ the wet (non-hydrostatic) component of the dispersion equation as a function of the wavelength $$\\lambda$$ in $$\\mu$$m (see Mendes and Pavlis 2004).\n\nFollowing Marini (1972), the recommended mapping function is expressed as continued fraction in a truncated form, as proposed by Herring (1992):\n\n\\begin{aligned} \\hbox {MF}(\\varepsilon ) = \\frac{1 + \\frac{a}{1 + \\frac{b}{1+c}}}{\\sin \\varepsilon + \\frac{a}{\\sin \\varepsilon + \\frac{b}{\\sin \\varepsilon + c}}}. \\end{aligned}\n(7)\n\nThe coefficients a, b, and c are calculated following Mendes et al. (2002) and are given as a function of the station latitude $$\\Phi$$, the geodetic height of the station H, and the temperature at the station $$t_{s}$$. In the following, this model for calculating the zenith delay and the corresponding MF will be referred to as Mendes–Pavlis, or short MP model.\n\nAs described above, the MP model is based on meteorological data records at the SLR station. This allows a very accurate estimation especially of the zenith hydrostatic delay (ZHD), where the vertical profile can be easily modelled using the surface pressure at the site.\n\nHowever, the MP model assumes horizontal symmetry, which is a simplification of true conditions. First, the troposphere is thicker in warmer (equatorial) regions than in cold (polar) regions (Mohanakumar 2008). Second, the refractivity of the troposphere is lower at the thermal equator than at the poles (Gardner 1977). These effects result in systematic variations in the troposphere delay dependent on the azimuth angle. Other azimuthal asymmetries originate, e.g. from weather conditions such as storms, that cause local deviations from the hydrostatic equilibrium (Hauser 1989).\n\nAtmospheric azimuthal asymmetries are commonly modelled following Chen and Herring (1997) by introducing linear horizontal gradients:\n\n\\begin{aligned} \\Delta L(\\varepsilon ,a) = \\Delta L_{0}(\\varepsilon ) + \\hbox {MF}_{g}(\\varepsilon )(G_{n}\\cos (a) + G_{e}\\sin (a)) \\end{aligned}\n(8)\n\nwhere $$\\Delta L_{0}(\\varepsilon )$$ denotes the isotropic component computed using Eq. 3 and the second term on the right accounts for the anisotropic part, with the north–south component of the gradients $$G_{n}$$, the east–west component $$G_{e}$$, azimuth angle a and a dedicated mapping function $$MF_{g}(\\varepsilon )$$. This mapping function can be expressed as:\n\n\\begin{aligned} MF_{g}(\\varepsilon ) = \\frac{1}{\\sin (\\varepsilon )\\tan (\\varepsilon )+C} \\end{aligned}\n(9)\n\nwhere Chen and Herring (1997) find $$C=0.0031$$ for the hydrostatic and $$C=0.0007$$ for the wet component of the microwave gradients. This gradient model is commonly used in GNSS and VLBI, but did not become prevalent in SLR analysis.\n\n## Development of a new troposphere delay model\n\nThis section presents the parameters of VMF3o and their derivation from ray-traced delays. VMF3o comprises zenith delays, mapping functions, and linear horizontal gradients for the hydrostatic and the wet component of the troposphere delay, as well as a set of coefficients to transform all VMF3o parameters to an arbitrary wavelength within the optical frequency range (see Sect. 3.4).\n\n### Ray-tracing at optical frequencies\n\nThe ray-tracing software RADIATE (Hofmeister and Böhm 2017) is part of the Vienna VLBI and Satellite Software (VieVS) developed at TU Wien (Böhm et al. 2018). The determination of the delays is based on a 2D piecewise linear ray-tracing approach (Hobiger et al. 2008) using numerical weather models (NWMs) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The NWMs that are used for deriving VMF3o parameters have a temporal resolution of 6h, a horizontal resolution of $$1^{\\circ }\\times 1^{\\circ }$$ and a vertical resolution of 25 pressure levels (for a more detailed description of the ECMWF NWMs, see https://www.ecmwf.int/en/forecasts/datasets/set-i).\n\nRADIATE was designed to determine ray-traced delays in the microwave range. In order to derive VMF3o parameters for SLR, a new option for ray-tracing at optical wavelengths was implemented. Since the majority of SLR stations operates at a wavelength of 532 nm (Noll and Tyahla 2019), this wavelength is used to generate optical ray-traced delays and deriving VMF3o parameters.\n\nTo determine ray-traced delays at any arbitrary location as well as any azimuth and elevation angle, a dense 3D refractivity field is generated based on the meteorological parameters of the NWM. Computing a hydrostatic and a wet refractivity field separately allows the determination of the hydrostatic and the wet component of the troposphere delay. In order to create optical refractivity fields, the equations for hydrostatic refractivity $$N_{h}$$ and wet refractivity $$N_{nh}$$ following Mendes and Pavlis (2004) are evaluated:\n\n\\begin{aligned} N_{h}= & {} N_{gaxs}\\frac{T_{d}}{P_{d}}Z_{d}R_{d}\\rho \\end{aligned}\n(10)\n\\begin{aligned} N_{nh}= & {} N_{gws}\\frac{\\rho _{w}}{\\rho _{ws}} - N_{gaxs}\\frac{T_{d}}{P_{d}}\\frac{Z_{d}}{Z}\\frac{e}{T}\\frac{M_{w}}{M_{d}} \\end{aligned}\n(11)\n\nwhere $$N_{gaxs}$$ is the group refractive index of dry air (Ciddor 1996), $$T_{d}$$ is the temperature of dry air, $$P_{d}$$ is the pressure of dry air, $$Z_{d}$$ is the compressibility factor of dry air, $$R_{d}$$ is the mean specific gas constant of dry air, $$\\rho$$ is the density of moist air, $$N_{gws}$$ is the group refractive index of water vapour (Ciddor 1996), $$\\rho _{w}$$ is the density of water vapour, $$\\rho _{ws}$$ is the density of water vapour at standard conditions, Z is the compressibility factor of moist air, e is the water vapour pressure of moist air, T is the temperature of moist air, $$M_{w}$$ is the molar mass of water vapour, and $$M_{d}$$ is the molar mass of dry air. For the computation of $$N_{gaxs}$$ and $$N_{gws}$$ following Mendes and Pavlis (2004), the $$CO_{2}$$ content is set to 375ppm as described in the IERS Conventions (Petit and Luzum 2010) and the wavelength is set to 532 nm. Thus, the generated ray-traced delays are valid for optical signals at 532 nm wavelength.\n\n### New mapping functions for SLR\n\nEquation 3 forms the basis of the mapping functions of VMF3o. The hydrostatic and the wet mapping function are determined by their coefficients a, b, and c as described in Eq. 7.\n\nFollowing the approach of VMF3, the b and c coefficients are estimated only once and not per epoch to ensure that the main parameters of VMF3o are well determined. The properties of the ray-traced delays generated for this purpose are listed in Table 1. Since low elevation angles are most sensitive in terms of separating atmospheric effects from other error sources, elevation angles of $$15^{\\circ }$$ and below are used for the derivation of VMF3o parameters.\n\nThe b and c coefficients of the hydrostatic as well as the wet mapping function are estimated in a least squares adjustment using the following fit formula (Lagler et al. 2013), where p represents any of the $$b_{h}$$, $$b_{w}$$, $$c_{h}$$, or $$c_{w}$$ coefficients:\n\n\\begin{aligned} {\\begin{matrix} p(doy) &{}= A_{0} \\\\ &{}\\quad + A_{1}\\cos \\left( \\frac{doy}{365.25}2\\pi \\right) +B_{1}\\sin \\left( \\frac{doy}{365.25}2\\pi \\right) \\\\ &{}\\quad + A_{2}\\cos \\left( \\frac{doy}{365.25}4\\pi \\right) +B_{2}\\sin \\left( \\frac{doy}{365.25}4\\pi \\right) \\end{matrix}} \\end{aligned}\n(12)\n\nwhere $$A_{0}$$ is the mean value, $$A_{1}$$ and $$B_{1}$$ are the annual amplitudes, and $$A_{2}$$ and $$B_{2}$$ are the semi-annual amplitudes. For this purpose, the temporal resolution of monthly mean values and the horizontal resolution of $$5^{\\circ }x5^{\\circ }$$ (see Table 1) is absolutely sufficient and the computation time is restrained to a reasonable length. The coefficients of the fit formula above are approximated using spherical harmonics (SH) up to degree and order 12. Thus, $$b_{h}$$, $$b_{w}$$, $$c_{h}$$, and $$c_{w}$$ can be computed as a function of station location and time. This allows to easily add sites to the regular processing of station-wise VMF3o parameters without recalculating b and c coefficients.\n\nWhile the b and c coefficients capture only low frequency variations, $$a_{h}$$ and $$a_{w}$$ reflect short-term changes in the troposphere. The ray-traced delays used for estimating the a coefficients are generated with the properties listed in Table 2. The a coefficients of the isotropic mapping functions $$MF_{h}$$ and $$MF_{w}$$ are then determined by solving Eq. 7 for a and averaging over all azimuth angles. Unlike the b and c coefficients, the a coefficients are site-specific parameters to avoid potential error sources such as grid interpolation and height extrapolation.\n\nGenerating ray-traced delays at several azimuth angles (see Table 2) allows not only the derivation of isotropic mapping functions, but also the determination of linear horizontal gradients. With the mapping functions obtained in Sect. 3.2 the isotropic component of the troposphere delay $$\\Delta L_{0}(\\varepsilon )$$ according to Eq. 8 can be calculated. When subtracting $$\\Delta L_{0}(\\varepsilon )$$ from the slant delays at each azimuth angle, residuals $$\\Delta L_{res}(\\varepsilon ,a)$$ are determined containing only the anisotropic part of the delays and Eq. 8 can be expressed as (Landskron and Böhm 2018):\n\n\\begin{aligned} \\Delta L_{res}(\\varepsilon ,a) = MF_{g}(\\varepsilon )(G_{n}\\cos (a) + G_{e}\\sin (a)). \\end{aligned}\n(13)\n\nThe residuals can be formed for the hydrostatic as well as the wet component of the total delay. Subsequently, the north and east component of the hydrostatic gradients $$G_{n,h}$$ and $$G_{e,h}$$, and the wet gradients $$G_{n,w}$$ and $$G_{e,w}$$ are estimated in a least squares adjustment based on Eq. 13.\n\nTypical values for the north and east components of horizontal gradients are several tenths of a millimetre, thus, causing azimuthal variations at the centimetre level when mapped to low elevation angles. For microwave signals, the hydrostatic and wet components of the gradients are at the same order of magnitude. For optical wavelengths, however, the wet component is significantly smaller compared to the hydrostatic component, as was already reported by Hulley and Pavlis (2007). Here, the horizontal gradients are split into a hydrostatic and a wet component in consistency with the general concept of VMF3o allowing more flexibility for scientific investigations.\n\n### Wavelength correction formula\n\nAs described in Sect. 3.1, most SLR stations operate with laser signals at 532 nm, and hence, the ray-traced delays are generated using this wavelength for calculating the refractivity fields. Consequently, VMF3o parameters are valid for this specific wavelength. Since some stations also use other frequencies ranging from blue to near-infrared (NIR), the VMF3o model includes a correction formula to transform the parameters from 532 nm to other wavelengths. To derive such a formula, ray-traced delays at ten different wavelengths between 350 and 1064 nm are generated. The respective wavelengths and other properties of the delays are listed in Tables 2 and 3.\n\nBased on these data, ten sets of VMF3o parameters (one for each wavelength) were calculated. When comparing the results for each wavelength to their reference at 532 nm, the frequency effect becomes most obvious for the ZHD. The differences between the ZHD at 532 nm and 1064 nm are at the 10 cm level, which cannot be neglected. The differences for the zenith wet delay (ZWD) are at the sub-millimetre level, causing deviations of several millimetres when mapped to low elevation angles. The differences for the mapping function coefficients and the horizontal gradients result in errors of up to several centimetres at low elevation angles. Hence, VMF3o parameters need to be corrected for observations at different wavelengths.\n\nFor the computation of the wavelength correction formula, each value was divided by its reference value at 532 nm and then averaged over all epochs and all stations. The result is one correction factor $$p_{\\lambda }/p_{532}$$ per wavelength $$\\lambda$$ for each VMF3o parameter p. The following fit formula was found to approximate the discrete values of the correction factors:\n\n\\begin{aligned} cf(\\lambda ) = \\frac{A}{\\lambda ^{B}}+C \\end{aligned}\n(14)\n\nwhere $$\\lambda$$ is the target wavelength in nm and the coefficients A, B, and C are estimated in a least squares adjustment, independently for each parameter of VMF3o. The values found for A, B, and C are listed in Table 4. Applying the correction factor cf to any parameter $$p_{532}$$ of VMF3o yields the parameter $$p_{\\lambda }$$ at the target wavelength $$\\lambda$$:\n\n\\begin{aligned} p_{\\lambda } = p_{532}\\cdot cf(\\lambda ) \\end{aligned}\n(15)\n\nThe discrete correction factors as well as the fitted curve using Eq. 14 are illustrated for the ZHD in Fig. 1 and for the ZWD in Fig. 2, exemplarily. Due to a limited number of decimal places in the output files, the correction factors of VMF3o parameters of small magnitude, such as the ZWD and the gradients, are less well determined compared to, e.g. the correction factors for the ZHD. Still, the wavelength dependency causes a clearly visible signal.\n\nFor verification, the obtained correction factors are compared to reference values based on the dispersion equations of the MP model (Mendes and Pavlis 2004). For this purpose, time series of ZHD and ZWD are calculated for the wavelengths listed in Table 3 using the MP model. Subsequently, discrete correction factors are computed in the same manner as described above. The values obtained from the MP model and the time series of VMF3o parameters, respectively, match very well, especially for the correction factors for the ZHD (see Figs. 1, 2).\n\nTo further examine the accuracy of the correction formula, the remaining errors between the corrected parameters using Eqs. 14 and 15 and the parameters obtained directly from ray-traced delays at the respective wavelength are formed. For a wavelength of 1064 nm, the residuals of the ZHD are below 0.5 mm and for the ZWD at the 0.1 mm level. The residuals of the coefficients $$a_{h}$$ and $$a_{w}$$ are mapped to a slant delay at $$10^{\\circ }$$ elevation angle causing differences below 0.3 mm and 0.003 mm, respectively. The gradients are also mapped to a slant delay at $$10^{\\circ }$$ elevation angle where they cause differences mostly smaller than 0.1 mm in direction of the largest amplitude. In total, the correction formula approximates the parameters directly retrieved from ray-tracing at the respective wavelength very accurately, with a remaining error of only a few millimetres at $$10^{\\circ }$$ elevation angle, mostly due to the residuals of the ZHD.\n\n## Validation and products of VMF3o\n\nSection 4.1 examines the differences of the meteorological parameters pressure, temperature, and water vapour pressure, when (1) derived from NWMs and (2) measured at the site, as well as their impact on zenith delays and mapping functions. Section 4.2 presents a comparison of the delays computed using VMF3o, referred to as modelled delays, with ray-traced delays as a first validation of VMF3o. This allows to examine the performance of the model approach in general. Conclusively, all VMF3o products and their availability are listed in Sect. 4.3.\n\n### Comparison of meteorological parameters\n\nTo get an idea of the accuracy of the pressure, temperature, and water vapour pressure (WVP) values from NWMs, they are compared to the meteorological measurements registered at SLR stations. The meteorological records are extracted from normal point files provided by the ILRS (Pearlman et al. 2019a). For this purpose, the monthly files containing the observations to LAGEOS-1 in the year 2017 are used. In the following, these values will be referred to as site values. The site-specific values of pressure, temperature, and WVP derived from NWMs are provided by VMF3o with a temporal resolution of 6h (see Sect. 4.3). For the comparison, they are calculated for the same epochs as the site values using a linear interpolation procedure. In the following, these values will be referred to as NWM values.\n\nFigure 3 illustrates the pressure differences of site values and NWM values for the stations 7090 (Yarragadee, Australia) and 7839 (Graz, Austria). The residuals of each day in the year 2017 are stacked to get an idea of the daily variations. For both stations, a remaining semi-diurnal signal can be identified with an amplitude below 3 hPa. 1 hPa corresponds to an error of about 2.5 mm in ZHD. This signal does not decrease, when using a spline or cubic interpolation procedure instead of linear interpolation.\n\nFigure 4 depicts the stacked differences in temperature for the stations 7090 (Yarragadee, Australia) and 7839 (Graz, Austria). Here, a diurnal signal with a maximum of about $$9\\,^\\circ \\hbox {C}$$ can be identified. An error of $$1\\,^\\circ \\hbox {C}$$ translates to deviations of approximately 0.6 mm in the STD at $$10^{\\circ }$$ elevation angle. This signal also does not decrease, when using a spline or cubic interpolation procedure.\n\nFigure 5 illustrates the stacked differences of WVP at the same stations. The results are also affected by the differences in temperature, when converting relative humidity to WVP. No clear periodic signals can be identified. The residuals range up to 5 hPa, which corresponds to approximately 1 mm in ZWD.\n\nTable 5 provides the minimum and maximum values for bias and standard deviation of the differences when looking at all stations. Some values denoted as outliers are not listed in Table 5. This includes a pressure bias of 11.2 hPa at station 1879 (Altay, Russia), a pressure bias of 15.6 hPa at station 1889 (Zelenchukskaya, Russia), a pressure bias of 83.7 hPa at station 1890 (Badary, Russia), a temperature bias of $$13.1\\,^\\circ \\hbox {C}$$ at station 1890 (Badary, Russia), as well as the consequential ZHD biases. A standard deviation of 14.5 hPa for the differences in pressure is found at station 7119 (Haleakala, Hawaii), which is also not included in Table 5.\n\nGenerally, meteorological data recorded at the station are expected to be more reliable. However, NWMs as additional source provide valuable information that can help to reveal biases originating in the meteorological sensors at the SLR sites. Furthermore, NWMs smoothen potential extreme local conditions, that are not representative for the whole column above the site, and do not depend on the daily rate of the sensors.\n\nThe results from the comparison indicate that the ZHD based on local records can be assumed to be more accurate. However, the computation of both, mapping functions and ZWD, based on ray-tracing could benefit from the vertical information provided by NWMs. A positive effect of ray-traced ZWDs was already reported by Boisits et al. (2018). Closer investigations on that issue still need to be carried out.\n\n### Modelled delays versus ray-traced delays\n\nA comparison of modelled delays and ray-traced delays was carried out to assess how precisely the VMF3o model approach represents ray-traced delays. VMF3o comprises zenith delays, mapping functions, and linear horizontal gradients for the hydrostatic and wet component of the delay. However, gradients of higher order are neglected. Landskron and Böhm (2018) find that second-order and third-order gradients further reduce the remaining differences, but only to a small degree. Furthermore, Drozdzewski et al. (2019) find that second-order horizontal gradients have only a small impact on SLR products and can be neglected, since SLR stations mainly operate during good weather conditions.\n\nTo investigate the remaining differences between the modelled and the ray-traced delays, 1460 epochs (4 epochs per day) of data in the year 2017 are used. The properties of the ray-traced delays generated for this purpose are listed in Tables 2 and 6. For the modelled delays, zenith delays, mapping functions, and linear horizontal gradients of VMF3o are applied and slant total delays at the azimuth and elevation angles according to Tables 2 and 6 are computed.\n\nThe ray-traced delays serve as reference values in this study. For the comparison, mean absolute errors are formed. Table 7 lists the results for the slant total delay at station 7839 (Graz, Austria). At $$5^{\\circ }$$ elevation angle, the mean absolute error ranges up to 5.5 mm and the effects of neglecting horizontal gradients of higher order are visible. However, at $$10^{\\circ }$$ elevation angle, the remaining differences are only at the 1 mm level and the effect of higher-order gradients decreases rapidly with increasing elevation angle.\n\nFigure 6 illustrates the impact of applying gradients when modelling troposphere delays at low elevation angles. The figure depicts the results for station 7839 (Graz, Austria). At $$5^{\\circ }$$ elevation angle, the mean differences between modelled and ray-traced delays range up to 20 mm and more when neglecting linear horizontal gradients. The mean error is reduced to less than 5 mm when applying gradients. These values roughly agree with the gradient corrections already found by Gardner (1977).\n\nLooking at the mean values over all stations and all azimuth angles yields similar deviations. The results are listed in Table 8. At $$5^{\\circ }$$ elevation angle, the mean absolute error is reduced from 18.2 to 3.1 mm, when applying gradients. This corresponds to an improvement by 83%. At $$10^{\\circ }$$ elevation angle, the mean absolute error is reduced by 85% from 5.9 to 0.9 mm. When applying the mapping function of the conventional MP model for comparison, the differences to the ray-traced delays increase even compared to VMF3o with no gradients applied (see Table 8).\n\n### Availability of VMF3o products\n\nVMF3o includes the following parameters:\n\n• Zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD),\n\n• Coefficients $$a_{h}$$, $$b_{h}$$, and $$c_{h}$$ of the hydrostatic component of the mapping function according to Eq. 7,\n\n• Coefficients $$a_{w}$$, $$b_{w}$$, and $$c_{w}$$ of the wet component of the mapping function according to Eq. 7,\n\n• Hydrostatic north–south component $$G_{n,h}$$ and hydrostatic east–west component $$G_{e,h}$$ of the linear horizontal gradient model according to Eq. 8,\n\n• Wet north–south component $$G_{n,w}$$ and wet east–west component $$G_{e,w}$$ of the linear horizontal gradient model according to Eq. 8,\n\n• Coefficients A, B, and C of the wavelength correction formula according to Eqs. 14 and 15.\n\nAll products and auxiliary material can be found at the VMF Server under vmf.geo.tuwien.ac.at. The b and c coefficients can be calculated using the routine vmf3o_b_c.m and the SH coefficients stored in separate text files. The parameters $$a_{h}$$, $$a_{w}$$, ZHD, ZWD, $$G_{n,h}$$, $$G_{e,h}$$, $$G_{n,w}$$, and $$G_{e,w}$$ are provided in so-called VMF3o files (.vmf3o extension). Pressure, temperature, and water vapour pressure from the NWM are listed as additional information. VMF3o files are published once per day and contain four epochs corresponding to a temporal resolution of 6 h. A linear interpolation between these epochs is adequate (see Sect. 4.1). The parameters are calculated station-wise, so no grid interpolation is necessary. The station list includes all past and active SLR stations listed in the station coordinate file slr.ell. This file is regularly updated, if new stations are added to the latest version of the SLRF2014 SINEX file (Noll et al. 2018). Other stations, e.g. engineering sites, can easily be added manually and will be included in the processing from that day on.\n\nThere are three categories of VMF3o files:\n\n• VMF3o_EI: VMF3o parameters are based on ray-traced delays using ECMWF ERA-Interim NWM data. These files are available beginning with the year 1990 until end of August 2019.\n\n• VMF3o_FC: VMF3o parameters are based on ray-traced delays using the ECMWF forecast NWM. These files are available one day prior to the day of their validity.\n\n• VMF3o_OP: VMF3o parameters are based on ray-traced delays using the ECMWF operational NWM. These files are available one day after the day of their validity.\n\nAll eight parameters provided in the VMF3o files can be transformed to a wavelength between 350 and 1064 nm. The coefficients A, B, and C to evaluate Eqs. 14 and 15 are provided in CF_ABC.txt.\n\n## Conclusion\n\nVMF3o is a new model for correcting troposphere delays in SLR. The model parameters are provided on the VMF Server on a daily basis. The model approach considers horizontal asymmetries of the atmosphere by introducing linear gradients. When comparing the modelled delays to ray-traced delays, the application of gradients reduces the mean absolute error by more than 80%.\n\nFurthermore, the zenith hydrostatic and the zenith wet delays are derived from ray-tracing. Thus, they contain additional vertical information from the NWM compared to only using surface values of meteorological parameters. This is of special interest for the wet component, where the vertical profile is hard to predict using ground measurements.\n\nWith this approach, VMF3o aims for a further advancement of the current accuracy level of SLR products. The effect of troposphere delay models derived from ray-traced delays and including horizontal gradients on SLR products is already demonstrated by Drozdzewski et al. (2019). Furthermore, the processing scheme for VMF3o is analogue to the scheme for VMF3 (Landskron and Böhm 2017) and GRAD (Landskron and Böhm 2018), which are the follow-ups of the well-established VMF1 (Böhm et al. 2006) model for microwave techniques. Using troposphere delay models from a single source could help to overcome inter-technique biases. So far, however, no investigations on that issue have been carried out.\n\nCurrently, a more detailed validation of VMF3o is ongoing to assess the effect of VMF3o on SLR products. This work is done in close cooperation with the ILRS Associate Analysis Center at Wroclaw University of Environmental and Life Sciences. The results are expected to be published in the near future.\n\n## Data Availability Statement\n\nVMF3o time series can be downloaded from http://vmf.geo.tuwien.ac.at/trop_products/SLR/. Additional scripts and data for the calculation of the b and c coefficients as well as the correction formula can be found at http://vmf.geo.tuwien.ac.at/codes/. For more details on the usage, see http://vmf.geo.tuwien.ac.at/readme.txt.\n\n## References\n\n1. Böhm J, Werl B, Schuh H (2006) Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. J Geophys Res 111:B02406. https://doi.org/10.1029/2005JB003629\n\n2. Böhm J, Böhm S, Boisits J, Girdiuk A, Gruber J, Hellerschied A, Krásná H, Landskron D, Madzak M, Mayer D, McCallum J, McCallum L, Schartner M, Teke K (2018) Vienna VLBI and Satellite Software (VieVS) for geodesy and astrometry. Publ Astron Soc Pacific 130:044503. https://doi.org/10.1088/1538-3873/aaa22b\n\n3. Boisits J, Landskron D, Sośnica K, Drozdzewski M, Böhm J (2018) VMF3o: Enhanced tropospheric mapping functions for optical frequencies. Presented at: 21st International Workshop on Laser Ranging, Canberra, Australia. https://cddis.nasa.gov/lw21/docs/2018/papers/ Session2_Boisits_paper.pdf\n\n4. Chen G, Herring TA (1997) Effects of atmospheric azimuthal asymmetry on the analysis of space geodetic data. J Geophys Res 102:20489–20502. https://doi.org/10.1029/97JB01739\n\n5. Ciddor PE (1996) Refractive index of air: new equations for the visible and near infrared. Appl Opt 35:1566–1573. https://doi.org/10.1364/AO.35.001566\n\n6. Drozdzewski M, Sośnica K (2018) Satellite laser ranging as a tool for the recovery of tropospheric gradients. Atmos Res 212:33–42. https://doi.org/10.1016/j.atmosres.2018.04.028\n\n7. Drozdzewski M, Sośnica K, Zus F, Balidakis K (2019) Troposphere delay modeling with horizontal gradients for satellite laser ranging. J Geod. https://doi.org/10.1007/s00190-019-01287-1\n\n8. Gardner CS (1977) Correction of laser tracking data for the effects of horizontal refractivity gradients. Appl Opt 16:2427–2432\n\n9. Hauser JP (1989) Effects of deviations from hydrostatic equilibrium on atmospheric corrections to satellite and lunar laser range measurements. J Geophys Res 94:10182–10186\n\n10. Herring T (1992) Modeling atmospheric delays in the analysis of space geodetic data. In: De Munck JC, Spoelstra TAT (eds) Proceedings of refraction of transatmospheric signals in geodesy, Netherlands Geodetic Commission Publications on Geodesy, The Hague, Netherlands, pp 157–164\n\n11. Hobiger T, Ichikawa R, Koyama Y, Kondo T (2008) Fast and accurate ray-tracing algorithms for real-time space geodetic applications using numerical weather models. J Geophys Res 113:D20302. https://doi.org/10.1029/2008JD010503\n\n12. Hofmeister A, Böhm J (2017) Application of ray-traced tropospheric slant delays to geodetic VLBI analysis. J Geod 91:945–964. https://doi.org/10.1007/s00190-017-1000-7\n\n13. Hulley GC, Pavlis EC (2007) A ray-tracing technique for improving Satellite Laser Ranging atmospheric delay corrections, including the effects of horizontal refractivity gradients. J Geophys Res 112:B06417. https://doi.org/10.1029/2006JB004834\n\n14. Lagler K, Schindelegger M, Böhm J, Krásná H, Nilsson T (2013) GPT2: empirical slant delay model for radio space geodetic techniques. Geophys Res Lett 40:1069–1073. https://doi.org/10.1002/grl.50288\n\n15. Landskron D, Böhm J (2017) VMF3/GPT3: refined discrete and empirical troposphere mapping functions. J Geod 92:349–360. https://doi.org/10.1007/s00190-017-1066-2\n\n16. Landskron D, Böhm J (2018) Refined discrete and empirical horizontal gradients in VLBI analysis. J Geod 92:1387–1399. https://doi.org/10.1007/s00190-018-1127-1\n\n17. Marini JW (1972) Correction of satellite tracking data for an arbitrary tropospheric profile. Radio Sci 7:223–231. https://doi.org/10.1029/RS007i002p00223\n\n18. Marini JW, Murray CW (1973) Correction of laser range tracking data for atmospheric refraction at elevations above 10 degrees. NASA-TM-X-70555 p 60 p\n\n19. Mendes VB, Pavlis EC (2004) High-accuracy zenith delay prediction at optical wavelengths. Geophys Res Lett 31:L14602. https://doi.org/10.1029/2004GL020308\n\n20. Mendes VB, Prates G, Pavlis EC, Pavlis DE, Langley RB (2002) Improved mapping functions for atmospheric refraction correction in SLR. Geophys Res Lett 29:53-1–53-4. https://doi.org/10.1029/2001GL014394\n\n21. Mohanakumar K (2008) Stratosphere troposphere interactions. Springer, Berlin\n\n22. Nilsson T, Böhm J, Wijaya DD, Tresch A, Nafisi V, Schuh H (2013) Path delays in the neutral atmosphere. In: Böhm J, Schuh H (eds) Atmospheric effects in space geodesy. Springer, Vienna, Austria, pp 73–136\n\n23. Noll C, Tyahla LJ (2012) Refraction Study Group (RSG) activities. https://ilrs.cddis.eosdis.nasa.gov/data_and_products/dfpwg/rsg/rsg_activities.html. Accessed 30 Nov 2019\n\n24. Noll C, Tyahla LJ (2019) ILRS operational station identification table (site log). https://ilrs.cddis.eosdis.nasa.gov/network/stations/active/index.html. Accessed 27 Nov 2019\n\n25. Noll CE, Ricklefs R, Horvath J, Müeller H, Schwatke C, Torrence M (2018) Information resources supporting scientific research for the international laser ranging service. J Geod 92:2211–2225. https://doi.org/10.1007/s00190-018-1207-2\n\n26. Pearlman MR, Noll CE, Pavlis EC, Lemoine FG, Combrink L, Degnan JJ, Kirchner G, Schreiber U (2019a) The ILRS: approaching 20 years and planning for the future. J Geod 93:2161–2180. https://doi.org/10.1007/s00190-019-01241-1\n\n27. Pearlman M, Arnold D, Davis M, Barlier F, Biancale R, Vasiliev V, Ciufolini I, Paolozzi A, Pavlis EC, Sośnica K, Bloßfeld M (2019b) Laser geodetic satellites: a high-accuracy scientific tool. J Geod 93:2181–2194. https://doi.org/10.1007/s00190-019-01228-y\n\n28. Petit G, Luzum B (2010) IERS conventions. In: Technical Note 36, Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am Main\n\n29. Zus F, Dick G, Dousa J, Wickert J (2015) Systematic errors of mapping functions which are based on the VMF1 concept. GPS Solut 19:277–286. https://doi.org/10.1007/s10291-014-0386-4\n\n## Acknowledgements\n\nOpen access funding provided by Austrian Science Fund (FWF). The authors would like to thank the Austrian Science Fund (FWF) for supporting this work within the project RADIATE ORD (ORD 68).\n\n## Author information\n\nAuthors\n\n### Contributions\n\nJanina Boisits and Johannes Böhm designed the research. The implementation of new software features and the determination of VMF3o time series was performed by Janina Boisits with support from Daniel Landskron. Janina Boisits performed the comparison study and the validation of the VMF3o model. Janina Boisits wrote the manuscript with support from Johannes Böhm and Daniel Landskron.\n\n### Corresponding author\n\nCorrespondence to Janina Boisits." ]
[ null ]
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https://www.stat.math.ethz.ch/pipermail/r-help/2006-August/111015.html
[ "# [R] anova.mlm for single model (one-way repeated measured anova)\n\nProf Brian Ripley ripley at stats.ox.ac.uk\nSat Aug 12 08:59:22 CEST 2006\n\n```On Sat, 12 Aug 2006, takahashi kohske wrote:\n\n> Dear list members:\n>\n> I'd like to one-way repeated measured anova by using mlm.\n> I'm using R-2.3.1 and my code is:\n>\n> dat<-matrix( c(9,7,8,8,12,11,8,13, 6,5,6,3,6,7,10,9,\n> 10,13,8,13,12,14,14,16, 9,11,13,14,16,12,15,14),\n> ncol=4, dimname=list(s=1:8, c=1:4))\n> mlmfit<-lm(dat~1)\n> anova(mlmfit, X=~1)\n> Error: ceiling(length.out) : Non-numeric argument to mathematical function\n>\n> this error occurs in anova.mlm\n>\n> if (rk > 0) {\n> p1 <- 1:rk\n> comp <- object\\$effects[p1, ]\n> asgn <- object\\$assign[object\\$qr\\$pivot][p1]\n> nmeffects <- c(\"(Intercept)\", attr(object\\$terms,\n> \"term.labels\"))\n> tlabels <- nmeffects[1 + unique(asgn)]\n> ix <- split(seq(length = nrow(comp)), asgn) #HERE\n> ss <- lapply(ix, function(i) crossprod(comp[i, ,\n> drop = FALSE]))\n> df <- sapply(split(asgn, asgn), length)\n> }\n>\n> because nrow(comp) returns NULL.\n>\n> in my memory, R-2.2.* ( or may be R-2.3.0) can correctly handle this code.\n> so, I think this is a kind of side-effect of fixing PR#8679.\n>\n> currently, i can workaround as follows:\n>\n> anova(mlmfit, update(mlmfit, ~0), X=~1)\n>\n> this code returns correct answer.\n>\n>\n> I don't know whether this behavior is correct or bug.\n\nYes, it is a bug. The line\n\ncomp <- object\\$effects[p1, ]\n\nshould be\n\ncomp <- object\\$effects[p1, , drop=FALSE]\n\nI am changing this in 2.3.1 patched and R-devel.\n\n--\nBrian D. Ripley, ripley at stats.ox.ac.uk\nProfessor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/\nUniversity of Oxford, Tel: +44 1865 272861 (self)\n1 South Parks Road, +44 1865 272866 (PA)\nOxford OX1 3TG, UK Fax: +44 1865 272595\n\n```" ]
[ null ]
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https://smithharris.org/what-is-the-relation-between-pressure-in-atmosphere-and-pressure-in-pascals/
[ "# What is the relation between pressure in atmosphere and pressure in Pascals?\n\nAnswer: Atmospheric Pressure is the pressure exerted by the weight of the atmosphere, which at sea level has a mean value of 101,325 pascals (roughly 14.6959 pounds per square inch).\n\nThe Standard Atmospheric Pressure is defined at sea-level at 273oK (0oC) and is 1.01325 bar or 101325 Pa (absolute). The temperature of 293oK (20oC) is sometimes used. In imperial units the Standard Atmospheric Pressure is 14.696 psi.\n\nwhat is atmospheric pressure in simple words? That pressure is called atmospheric pressure, or air pressure. It is the force exerted on a surface by the air above it as gravity pulls it to Earth. Atmospheric pressure is commonly measured with a barometer. One atmosphere is 1,013 millibars, or 760 millimeters (29.92 inches) of mercury.\n\nOne may also ask, how does altitude affect air pressure?\n\nPressure with Height: pressure decreases with increasing altitude. The pressure at any level in the atmosphere may be interpreted as the total weight of the air above a unit area at any elevation. At higher elevations, there are fewer air molecules above a given surface than a similar surface at lower levels.\n\nHow do you measure air pressure?\n\nAn instrument that measures air pressure is called a barometer. One of the first barometers was developed in the 1600s. The original instrument had mercury in the small basin, with an upside down glass tube placed in the mercury. As air pressure increased, the pressure would force more mercury in the tube.\n\n### What is considered high air pressure?\n\nAir pressure is a force with which atmospheric air presses on the surface of the globe. Barometric pressure is typically measured in inches of mercury (inHg or “Hg). High barometric pressure is considered above 31 inches or may drop below 29 inches. Normal sea-level pressure is 29.92 inches.\n\n### Is ATM a SI unit?\n\nThe standard atmosphere (symbol: atm) is a unit of pressure defined as 101,325 Pa (1,013.25 hPa; 1,013.25 mbar), which is equivalent to 760 mm Hg, 29.9212 inches Hg, or 14.696 psi. Pressure measures force per unit area, with SI units of Pascals (1 pascal = 1 newton per square metre, 1 N/m2).\n\n### What is the normal air pressure?\n\nThe standard, or near-average, atmospheric pressure at sea level on the Earth is 1013.25 millibars, or about 14.7 pounds per square inch. The gauge pressure in my automobile tires is a little more than twice that value.\n\nbarometer\n\n### What is difference between air pressure and atmospheric pressure?\n\nAir pressure is what you measure with a tire gauge. Atmospheric pressure is what you measure with a mercury barometer. Let me be more specific. Pressure is the amount of force per unit area that a gas exerts on a surface.\n\n### Does atmospheric pressure affect weight?\n\nLater: Air density if affected by air pressure as well as temperature and humidity, so atmospheric pressure (which you asked about) affects weight measurements, but not directly. Weight is the force exerted by the earth (or some other celestial body if you’re considering weight in a different place) on a mass.\n\n### What is meant by standard temperature and pressure?\n\nStandard temperature and pressure, abbreviated STP, refers to nominal conditions in the atmosphere at sea level. Standard temperature is defined as zero degrees Celsius (0 0C), which translates to 32 degrees Fahrenheit (32 0F) or 273.15 degrees kelvin (273.15 0K).\n\n### How do you calculate kPa pressure?\n\nKilopascal (kPa) is a frequently used pressure unit and equals to 1000 newton per square meter (metre). 1 kPa = 0.00986923 atm → kPa to atm. 1 kPa = 0.01 bar → kPa to bar. 1 kPa = 0.001 MPa → kPa to MPa. 1 kPa = 1000 pascals → kPa to pascal. 1 kPa = 0.145038 psi → kPa to psi. 1 kPa = 7.50062 torr (mmHg) → kPa to torr.\n\n### What are 5 common units of pressure and their conversions?\n\nSome common units of measurement this Pressure Conversion chart helps you convert are: atmosphere (atm), bar (b), Dyne (dynes/cm²), hectopascal (hPa), kilogram per sq. cm (kgf/cm²), kilogram per sq.\n\n### What are the different units of pressures?\n\nThe unit of pressure in the SI system is the pascal (Pa), defined as a force of one Newton per square meter. The conversion between atm, Pa, and torr is as follows: 1 atm = 101325 Pa = 760 torr.\n\n### What is standard temperature and pressure for a gas?\n\nStandard Temperature and Pressure. Standard temperature is equal to 0 °C, which is 273.15 K. Standard Pressure is 1 Atm, 101.3kPa or 760 mmHg or torr. STP is the “standard” conditions often used for measuring gas density and volume. At STP, 1 mole of any gas occupies 22.4L.\n\n### What are the 4 units of pressure?\n\nUnits of Measurement/Pressure pascal pound per square inch Pa psi 1 atm 1.01325 ×105 14.696 1 Torr 133.322 19.337×10−3 1 psi 6.895×103 ≡ 1 lbf/in2\n\n### What does KPA mean?\n\nKilopascal (Kpa)is a pressure measurement unit. As the name implies there are 1,000 pascals in 1 kilopascal. You are most likey in north america or your using an american product mayber a car tire and you need to know what pressure to fill it to. If your looking to convert psi to kPa go here." ]
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https://homework.cpm.org/category/CC/textbook/ccg/chapter/7/lesson/7.2.4/problem/7-86
[ "", null, "", null, "### Home > CCG > Chapter 7 > Lesson 7.2.4 > Problem7-86\n\n7-86.\n\nFor each figure below, determine if the two smaller triangles in each figure are congruent. If so, create a flowchart to explain why. Then, solve for $x$. If the triangles are not congruent, explain why not. Redraw and label the diagrams as needed.\n\nEach set of triangles is congruent. Now show why or how.\n\n1.", null, "Congruent because of $\\text{SAS}≅$, $x=2$.\n\n2.", null, "Congruent because of $\\text{HL}≅$, $x=32$." ]
[ null, "https://homework.cpm.org/dist/7d633b3a30200de4995665c02bdda1b8.png", null, 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https://www.colorhexa.com/40fc34
[ "# #40fc34 Color Information\n\nIn a RGB color space, hex #40fc34 is composed of 25.1% red, 98.8% green and 20.4% blue. Whereas in a CMYK color space, it is composed of 74.6% cyan, 0% magenta, 79.4% yellow and 1.2% black. It has a hue angle of 116.4 degrees, a saturation of 97.1% and a lightness of 59.6%. #40fc34 color hex could be obtained by blending #80ff68 with #00f900. Closest websafe color is: #33ff33.\n\n• R 25\n• G 99\n• B 20\nRGB color chart\n• C 75\n• M 0\n• Y 79\n• K 1\nCMYK color chart\n\n#40fc34 color description : Bright lime green.\n\n# #40fc34 Color Conversion\n\nThe hexadecimal color #40fc34 has RGB values of R:64, G:252, B:52 and CMYK values of C:0.75, M:0, Y:0.79, K:0.01. Its decimal value is 4258868.\n\nHex triplet RGB Decimal 40fc34 `#40fc34` 64, 252, 52 `rgb(64,252,52)` 25.1, 98.8, 20.4 `rgb(25.1%,98.8%,20.4%)` 75, 0, 79, 1 116.4°, 97.1, 59.6 `hsl(116.4,97.1%,59.6%)` 116.4°, 79.4, 98.8 33ff33 `#33ff33`\nCIE-LAB 87.463, -79.103, 75.17 37.543, 70.955, 14.966 0.304, 0.575, 70.955 87.463, 109.123, 136.461 87.463, -76.054, 100.661 84.235, -67.855, 48.43 01000000, 11111100, 00110100\n\n# Color Schemes with #40fc34\n\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #f034fc\n``#f034fc` `rgb(240,52,252)``\nComplementary Color\n• #a4fc34\n``#a4fc34` `rgb(164,252,52)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #34fc8c\n``#34fc8c` `rgb(52,252,140)``\nAnalogous Color\n• #fc34a4\n``#fc34a4` `rgb(252,52,164)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #8c34fc\n``#8c34fc` `rgb(140,52,252)``\nSplit Complementary Color\n• #fc3440\n``#fc3440` `rgb(252,52,64)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #3440fc\n``#3440fc` `rgb(52,64,252)``\n• #fcf034\n``#fcf034` `rgb(252,240,52)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #3440fc\n``#3440fc` `rgb(52,64,252)``\n• #f034fc\n``#f034fc` `rgb(240,52,252)``\n• #11e003\n``#11e003` `rgb(17,224,3)``\n• #12f904\n``#12f904` `rgb(18,249,4)``\n• #28fc1b\n``#28fc1b` `rgb(40,252,27)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #58fc4d\n``#58fc4d` `rgb(88,252,77)``\n• #6ffd66\n``#6ffd66` `rgb(111,253,102)``\n• #87fd7f\n``#87fd7f` `rgb(135,253,127)``\nMonochromatic Color\n\n# Alternatives to #40fc34\n\nBelow, you can see some colors close to #40fc34. Having a set of related colors can be useful if you need an inspirational alternative to your original color choice.\n\n• #72fc34\n``#72fc34` `rgb(114,252,52)``\n• #61fc34\n``#61fc34` `rgb(97,252,52)``\n• #51fc34\n``#51fc34` `rgb(81,252,52)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #34fc39\n``#34fc39` `rgb(52,252,57)``\n• #34fc49\n``#34fc49` `rgb(52,252,73)``\n• #34fc5a\n``#34fc5a` `rgb(52,252,90)``\nSimilar Colors\n\n# #40fc34 Preview\n\nThis text has a font color of #40fc34.\n\n``<span style=\"color:#40fc34;\">Text here</span>``\n#40fc34 background color\n\nThis paragraph has a background color of #40fc34.\n\n``<p style=\"background-color:#40fc34;\">Content here</p>``\n#40fc34 border color\n\nThis element has a border color of #40fc34.\n\n``<div style=\"border:1px solid #40fc34;\">Content here</div>``\nCSS codes\n``.text {color:#40fc34;}``\n``.background {background-color:#40fc34;}``\n``.border {border:1px solid #40fc34;}``\n\n# Shades and Tints of #40fc34\n\nA shade is achieved by adding black to any pure hue, while a tint is created by mixing white to any pure color. In this example, #010a00 is the darkest color, while #f6fff5 is the lightest one.\n\n• #010a00\n``#010a00` `rgb(1,10,0)``\n• #021d00\n``#021d00` `rgb(2,29,0)``\n• #043001\n``#043001` `rgb(4,48,1)``\n• #054401\n``#054401` `rgb(5,68,1)``\n• #065701\n``#065701` `rgb(6,87,1)``\n• #086a02\n``#086a02` `rgb(8,106,2)``\n• #097e02\n``#097e02` `rgb(9,126,2)``\n• #0b9102\n``#0b9102` `rgb(11,145,2)``\n• #0ca402\n``#0ca402` `rgb(12,164,2)``\n• #0eb803\n``#0eb803` `rgb(14,184,3)``\n• #0fcb03\n``#0fcb03` `rgb(15,203,3)``\n• #10de03\n``#10de03` `rgb(16,222,3)``\n• #12f204\n``#12f204` `rgb(18,242,4)``\n• #1cfb0d\n``#1cfb0d` `rgb(28,251,13)``\n• #2efc21\n``#2efc21` `rgb(46,252,33)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\n• #52fc47\n``#52fc47` `rgb(82,252,71)``\n• #64fd5b\n``#64fd5b` `rgb(100,253,91)``\n• #77fd6e\n``#77fd6e` `rgb(119,253,110)``\n• #89fd81\n``#89fd81` `rgb(137,253,129)``\n• #9bfd95\n``#9bfd95` `rgb(155,253,149)``\n``#adfea8` `rgb(173,254,168)``\n• #bffebb\n``#bffebb` `rgb(191,254,187)``\n• #d1fecf\n``#d1fecf` `rgb(209,254,207)``\n• #e4ffe2\n``#e4ffe2` `rgb(228,255,226)``\n• #f6fff5\n``#f6fff5` `rgb(246,255,245)``\nTint Color Variation\n\n# Tones of #40fc34\n\nA tone is produced by adding gray to any pure hue. In this case, #949d93 is the less saturated color, while #40fc34 is the most saturated one.\n\n• #949d93\n``#949d93` `rgb(148,157,147)``\n• #8da58b\n``#8da58b` `rgb(141,165,139)``\n``#86ad83` `rgb(134,173,131)``\n• #7fb57b\n``#7fb57b` `rgb(127,181,123)``\n• #78bd73\n``#78bd73` `rgb(120,189,115)``\n• #71c56b\n``#71c56b` `rgb(113,197,107)``\n• #6acc64\n``#6acc64` `rgb(106,204,100)``\n• #63d45c\n``#63d45c` `rgb(99,212,92)``\n• #5cdc54\n``#5cdc54` `rgb(92,220,84)``\n• #55e44c\n``#55e44c` `rgb(85,228,76)``\n• #4eec44\n``#4eec44` `rgb(78,236,68)``\n• #47f43c\n``#47f43c` `rgb(71,244,60)``\n• #40fc34\n``#40fc34` `rgb(64,252,52)``\nTone Color Variation\n\n# Color Blindness Simulator\n\nBelow, you can see how #40fc34 is perceived by people affected by a color vision deficiency. This can be useful if you need to ensure your color combinations are accessible to color-blind users.\n\nMonochromacy\n• Achromatopsia 0.005% of the population\n• Atypical Achromatopsia 0.001% of the population\nDichromacy\n• Protanopia 1% of men\n• Deuteranopia 1% of men\n• Tritanopia 0.001% of the population\nTrichromacy\n• Protanomaly 1% of men, 0.01% of women\n• Deuteranomaly 6% of men, 0.4% of women\n• Tritanomaly 0.01% of the population" ]
[ null ]
{"ft_lang_label":"__label__en","ft_lang_prob":0.57291716,"math_prob":0.7863794,"size":3690,"snap":"2020-24-2020-29","text_gpt3_token_len":1620,"char_repetition_ratio":0.126153,"word_repetition_ratio":0.011090573,"special_character_ratio":0.55230355,"punctuation_ratio":0.23783186,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9853862,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-06-06T02:40:21Z\",\"WARC-Record-ID\":\"<urn:uuid:121e82d9-978e-46ed-a01a-92016ef858be>\",\"Content-Length\":\"36276\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:a555be5c-b696-431e-864f-0a1aa6b9dbdb>\",\"WARC-Concurrent-To\":\"<urn:uuid:2f66b498-6718-4588-afd5-e94ef51d61d0>\",\"WARC-IP-Address\":\"178.32.117.56\",\"WARC-Target-URI\":\"https://www.colorhexa.com/40fc34\",\"WARC-Payload-Digest\":\"sha1:2SDNNSI5PZEFZOZLZE2R4KRRRWT2343Z\",\"WARC-Block-Digest\":\"sha1:JI5XNDKAXZNJHAQCZMVOUVIRWYLCRGNU\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-24/CC-MAIN-2020-24_segments_1590348509264.96_warc_CC-MAIN-20200606000537-20200606030537-00548.warc.gz\"}"}
https://www.lotusamity.com/business-valuation/process/what-is-volatility/
[ "# What is volatility?\n\n## Volatility and risk\n\nReturn volatility is a key indicator of the risk attached to an investment. Volatility refers to the extent actual returns vary from the expected return. The more the returns deviate from the expected return, the greater the risk.\n\n### Standard deviation\n\nStandard deviation expresses how much the historical returns deviate from the average mean value, where the mean is regarded as the expected return.\n\nA low standard deviation indicates that the returns tend to be close to the average return. Standard deviation is the critical measure of volatility in a company’s returns, as such standard deviation is a crucial measure of risk.", null, "Sample standard deviation is the square root of, the sum of the squared difference between each observed return and the average mean return divided by the population less one.\n\nIn addition to illustrating the variability of the return within a population sample, the standard deviation is used to measure confidence. In a normal distribution, a stock’s return is likely to be 68% within one standard deviation of the mean and 95% within two standard deviations of the mean.\n\n### Risk comparison\n\nThe chart below shows the distribution of monthly returns for Woolworths Group (WOW), Fortescue Metals Group (FMG) and the All Ordinaries Index over a five year period to 30 June 2018.", null, "The All Ordinaries index has the tightest distribution of actual returns around the mean, represented by the high narrow curve, indicating low volatility. In comparison, FMG’s monthly returns are spread much more widely, more volatile, represented by a flatter curve.", null, "The table above summarises the monthly return data. WOW achieved an average monthly return of 0.28%, below the average monthly return for the market of 0.42%. In contrast, FMG achieved a much higher average monthly return of 1.39%.\n\nThe relatively large FMG monthly return range, between -21.3% and 35.6%, is reflected in the stock’s high standard deviation of 12.13%, compared to the All Ordinaries index standard deviation of 3.09%.At the 95% confidence level, the expected monthly return for FMG is between -22.87% and 25.66% (two standard deviations of the mean) whereas the expected monthly return for the index is between -5.76% and 6.60%.\n\nThe skewness of distribution represents the tendency toward positive or negative returns. The WOW distribution is skewed slightly towards the left, towards a negative return. The FMG distribution is skewed somewhat towards a positive return.\n\nKurtosis represents the tendency for returns to move towards the centre (the mean) and the tails (the outliers). A higher kurtosis implies that more of the return variation is due to extreme values (outliers) and that intermediate returns are less likely. WOW has the highest kurtosis.\n\nAn investor will prefer higher expected returns over lower returns, low return variance, positive return skewness and lower return kurtosis. An investor faced with a choice between two investments with the same risk profile (the same standard deviation, kurtosis and skewness) will pick the investment with the higher expected return.\n\nTo predict future expected returns and risk, valuers use historical return distributions. That is unless the business has significantly changed, in which case, past performance may not be applicable.\n\nSimon is a CA Business Valuation specialist, Chartered Accountant and a Certified Fraud Examiner. Simon specialises in providing valuation services. Prior to founding Lotus Amity, he was a Corporate Finance and Forensic Accounting partner with BDO Australia. Simon provides valuation services in disputes, for raising finance, for restructuring, transactions and for tax purposes." ]
[ null, "https://www.lotusamity.com/wp-content/uploads/2020/10/Standard-deviation-formula.jpg", null, "https://www.lotusamity.com/wp-content/uploads/2020/10/^AORD-1-e1540878371296.jpg", null, "https://www.lotusamity.com/wp-content/uploads/2020/10/summary.jpg", null ]
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https://web2.0calc.com/questions/let-n-and-k-be-positive-integers-such-that-and-what
[ "+0\n\n# Let n and k be positive integers such that and What is the ordered pair (n, k)?\n\n+1\n74\n4\n\nLet n and k be positive integers such that $$n<10^6$$ and $$\\binom{13}{13} + \\binom{14}{13} + \\binom{15}{13} + \\dots + \\binom{52}{13} + \\binom{53}{13} + \\binom{54}{13} = \\binom{n}{k}$$\nWhat is the ordered pair (n, k)?\n\nFeb 25, 2020\n\n#1\n+1\n\n$$\\text{Using the hockey stick identity}\\\\ \\sum \\limits_{n=13}^{54}\\dbinom{n}{13} = \\dbinom{54+1}{13+1} = \\dbinom{55}{14}$$\n\nhttps://en.wikipedia.org/wiki/Hockey-stick_identity\n\nFeb 25, 2020\n#2\n+1\n\noh that makes sense to use the hockey stick identity. Thanks for the help!!\n\nmathmathj28  Feb 25, 2020\n#3\n0\n\nThat's not an ordered pair though.\n\nAnimalMaster  Feb 27, 2020\n#4\n0\n\nThe ordered pair would be (55, 14)\n\nmathmathj28  Mar 4, 2020" ]
[ null ]
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https://dnmtechs.com/swapping-array-elements-in-javascript-a-practical-approach/
[ "", null, "# Swapping Array Elements in JavaScript: A Practical Approach\n\nArrays are a fundamental data structure in JavaScript, allowing us to store and manipulate collections of values efficiently. In certain scenarios, we may need to swap the positions of elements within an array. This can be useful when reordering data or implementing algorithms that require element rearrangement. In this article, we will explore a practical approach to swapping array elements in JavaScript, providing explanations, examples, and relevant references.\n\n### The Basics of Swapping Array Elements\n\nSwapping array elements involves exchanging the positions of two elements within the array. The process typically consists of three steps:\n\n1. Identify the indices of the elements to be swapped.\n2. Store the value of one element in a temporary variable.\n3. Assign the value of the second element to the first element’s index and assign the temporary variable’s value to the second element’s index.\n\nLet’s consider a simple example:\n\n```const array = [1, 2, 3, 4, 5];\nconst index1 = 1;\nconst index2 = 3;\n\nconst temp = array[index1];\narray[index1] = array[index2];\narray[index2] = temp;\n\nconsole.log(array); // Output: [1, 4, 3, 2, 5]\n```\n\nIn the example above, we have an array with five elements. We want to swap the element at index 1 (value 2) with the element at index 3 (value 4). By following the three steps, we successfully swap the elements, resulting in the modified array [1, 4, 3, 2, 5].\n\n### Swapping Array Elements Using ES6 Destructuring Assignment\n\nIn modern JavaScript, the ES6 destructuring assignment syntax provides a concise and elegant way to swap array elements. This approach eliminates the need for a temporary variable and simplifies the swapping process.\n\n```const array = [1, 2, 3, 4, 5];\nconst index1 = 1;\nconst index2 = 3;\n\n[array[index1], array[index2]] = [array[index2], array[index1]];\n\nconsole.log(array); // Output: [1, 4, 3, 2, 5]\n```\n\nBy utilizing array destructuring, we directly assign the swapped values to the corresponding array indices. This results in the same output as the previous example, but with a more concise syntax.\n\n### Further Considerations and Use Cases\n\nWhen swapping array elements, it is crucial to ensure that the provided indices are valid and within the array’s bounds. Attempting to swap elements with out-of-range indices can lead to unexpected behavior or errors. Additionally, it’s important to note that both approaches discussed in this article modify the original array in place.\n\nThe ability to swap array elements is valuable in various scenarios. It can be used to reorder data based on specific conditions, implement sorting algorithms, or facilitate efficient data manipulation in complex algorithms. By understanding the concept and the practical approaches presented here, developers can leverage this technique to enhance their JavaScript applications.\n\n### Summary\n\nIn this article, we explored a practical approach to swapping array elements in JavaScript. We discussed the basic steps involved in swapping and provided examples using both traditional variable assignment and the ES6 destructuring assignment syntax. We also highlighted the importance of considering array bounds and potential use cases for swapping array elements. By mastering this technique, developers can efficiently manipulate array data and optimize their JavaScript applications." ]
[ null, "https://dnmtechs.com/wp-content/uploads/2023/10/dnmtechs_js_content_feature_img_00010.jpg", null ]
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https://www.physicsforums.com/threads/integrate-the-following-equations-using-u-substitution.669246/
[ "# Integrate the following equations using U-Substitution\n\n## Homework Statement\n\nIntegrate √(x2(x+3)) from -3 to 0.\n\n0\n∫√(x2(x+3)) dx\n-3\n\n2. The attempt at a solution\nHere is what I did:\n√(x2(x+3))\n= x√(x+3)\n\nLet u=x+3, du=dx, x=u-3\nInsert the bounds and change the bounds to: 0 to 3.\n\nx√(x+3)=\n(u-3)√(u)\n= u3/2-3u1/2\n\nThus we have:\n3\n∫(u3/2-3u1/2) du\n0\n\nFinally:\n\n(2u5/2)/5-(2u3/2) from 0 to 3.\nThus I get: -4.15.\n\nHowever the correct answer is positive 4.15.\n\nRelated Calculus and Beyond Homework Help News on Phys.org\nSammyS\nStaff Emeritus\nHomework Helper\nGold Member\n\n## Homework Statement\n\nIntegrate √(x2(x+3)) from -3 to 0.\n\n0\n∫√(x2(x+3)) dx\n-3\n\n2. The attempt at a solution\nHere is what I did:\n√(x2(x+3))\n= x√(x+3)\n\nLet u=x+3, du=dx, x=u-3\nInsert the bounds and change the bounds to: 0 to 3.\n\nx√(x+3)=\n(u-3)√(u)\n= u3/2-3u1/2\n\nThus we have:\n3\n∫(u3/2-3u1/2) du\n0\n\nFinally:\n\n(2u5/2)/5-(2u3/2) from 0 to 3.\nThus I get: -4.15.\n\nHowever the correct answer is positive 4.15.\nBe careful.\n\n$\\displaystyle \\sqrt{x^2} = |x|$\n\nIn fact, for x<0, $\\displaystyle\\ \\sqrt{x^2} = -x\\ .$\n\nDick\nHomework Helper\n\n## Homework Statement\n\nIntegrate √(x2(x+3)) from -3 to 0.\n\n0\n∫√(x2(x+3)) dx\n-3\n\n2. The attempt at a solution\nHere is what I did:\n√(x2(x+3))\n= x√(x+3)\n\nLet u=x+3, du=dx, x=u-3\nInsert the bounds and change the bounds to: 0 to 3.\n\nx√(x+3)=\n(u-3)√(u)\n= u3/2-3u1/2\n\nThus we have:\n3\n∫(u3/2-3u1/2) du\n0\n\nFinally:\n\n(2u5/2)/5-(2u3/2) from 0 to 3.\nThus I get: -4.15.\n\nHowever the correct answer is positive 4.15." ]
[ null ]
{"ft_lang_label":"__label__en","ft_lang_prob":0.88661253,"math_prob":0.9973245,"size":544,"snap":"2019-51-2020-05","text_gpt3_token_len":242,"char_repetition_ratio":0.1037037,"word_repetition_ratio":0.0,"special_character_ratio":0.4319853,"punctuation_ratio":0.12765957,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9986555,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-01-21T18:17:07Z\",\"WARC-Record-ID\":\"<urn:uuid:12d7a7d5-282d-4df4-ba09-c2f39ce377b1>\",\"Content-Length\":\"74960\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:60db30ab-b6d9-4680-bcab-1787a8d111de>\",\"WARC-Concurrent-To\":\"<urn:uuid:7f08ea7e-bb68-40f5-ba1e-19584bd71494>\",\"WARC-IP-Address\":\"23.111.143.85\",\"WARC-Target-URI\":\"https://www.physicsforums.com/threads/integrate-the-following-equations-using-u-substitution.669246/\",\"WARC-Payload-Digest\":\"sha1:UVZHXI72HDHQ5VJP5HELSFSV3SMMXMWN\",\"WARC-Block-Digest\":\"sha1:JGHEIFWPPQZ4G5UNXEETWDQZYJMCM5QU\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-05/CC-MAIN-2020-05_segments_1579250604849.31_warc_CC-MAIN-20200121162615-20200121191615-00110.warc.gz\"}"}
https://docs.julialang.org/en/v1.0.0/stdlib/SparseArrays/
[ "Sparse Arrays\n\n# Sparse Arrays\n\nJulia has support for sparse vectors and sparse matrices in the `SparseArrays` stdlib module. Sparse arrays are arrays that contain enough zeros that storing them in a special data structure leads to savings in space and execution time, compared to dense arrays.\n\n## Compressed Sparse Column (CSC) Sparse Matrix Storage\n\nIn Julia, sparse matrices are stored in the Compressed Sparse Column (CSC) format. Julia sparse matrices have the type `SparseMatrixCSC{Tv,Ti}`, where `Tv` is the type of the stored values, and `Ti` is the integer type for storing column pointers and row indices. The internal representation of `SparseMatrixCSC` is as follows:\n\n``````struct SparseMatrixCSC{Tv,Ti<:Integer} <: AbstractSparseMatrix{Tv,Ti}\nm::Int # Number of rows\nn::Int # Number of columns\ncolptr::Vector{Ti} # Column i is in colptr[i]:(colptr[i+1]-1)\nrowval::Vector{Ti} # Row indices of stored values\nnzval::Vector{Tv} # Stored values, typically nonzeros\nend``````\n\nThe compressed sparse column storage makes it easy and quick to access the elements in the column of a sparse matrix, whereas accessing the sparse matrix by rows is considerably slower. Operations such as insertion of previously unstored entries one at a time in the CSC structure tend to be slow. This is because all elements of the sparse matrix that are beyond the point of insertion have to be moved one place over.\n\nAll operations on sparse matrices are carefully implemented to exploit the CSC data structure for performance, and to avoid expensive operations.\n\nIf you have data in CSC format from a different application or library, and wish to import it in Julia, make sure that you use 1-based indexing. The row indices in every column need to be sorted. If your `SparseMatrixCSC` object contains unsorted row indices, one quick way to sort them is by doing a double transpose.\n\nIn some applications, it is convenient to store explicit zero values in a `SparseMatrixCSC`. These are accepted by functions in `Base` (but there is no guarantee that they will be preserved in mutating operations). Such explicitly stored zeros are treated as structural nonzeros by many routines. The `nnz` function returns the number of elements explicitly stored in the sparse data structure, including structural nonzeros. In order to count the exact number of numerical nonzeros, use `count(!iszero, x)`, which inspects every stored element of a sparse matrix. `dropzeros`, and the in-place `dropzeros!`, can be used to remove stored zeros from the sparse matrix.\n\n``````julia> A = sparse([1, 2, 3], [1, 2, 3], [0, 2, 0])\n3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:\n[1, 1] = 0\n[2, 2] = 2\n[3, 3] = 0\n\njulia> dropzeros(A)\n3×3 SparseMatrixCSC{Int64,Int64} with 1 stored entry:\n[2, 2] = 2``````\n\n## Sparse Vector Storage\n\nSparse vectors are stored in a close analog to compressed sparse column format for sparse matrices. In Julia, sparse vectors have the type `SparseVector{Tv,Ti}` where `Tv` is the type of the stored values and `Ti` the integer type for the indices. The internal representation is as follows:\n\n``````struct SparseVector{Tv,Ti<:Integer} <: AbstractSparseVector{Tv,Ti}\nn::Int # Length of the sparse vector\nnzind::Vector{Ti} # Indices of stored values\nnzval::Vector{Tv} # Stored values, typically nonzeros\nend``````\n\nAs for `SparseMatrixCSC`, the `SparseVector` type can also contain explicitly stored zeros. (See Sparse Matrix Storage.).\n\n## Sparse Vector and Matrix Constructors\n\nThe simplest way to create a sparse array is to use a function equivalent to the `zeros` function that Julia provides for working with dense arrays. To produce a sparse array instead, you can use the same name with an `sp` prefix:\n\n``````julia> spzeros(3)\n3-element SparseVector{Float64,Int64} with 0 stored entries``````\n\nThe `sparse` function is often a handy way to construct sparse arrays. For example, to construct a sparse matrix we can input a vector `I` of row indices, a vector `J` of column indices, and a vector `V` of stored values (this is also known as the COO (coordinate) format). `sparse(I,J,V)` then constructs a sparse matrix such that `S[I[k], J[k]] = V[k]`. The equivalent sparse vector constructor is `sparsevec`, which takes the (row) index vector `I` and the vector `V` with the stored values and constructs a sparse vector `R` such that `R[I[k]] = V[k]`.\n\n``````julia> I = [1, 4, 3, 5]; J = [4, 7, 18, 9]; V = [1, 2, -5, 3];\n\njulia> S = sparse(I,J,V)\n5×18 SparseMatrixCSC{Int64,Int64} with 4 stored entries:\n[1 , 4] = 1\n[4 , 7] = 2\n[5 , 9] = 3\n[3 , 18] = -5\n\njulia> R = sparsevec(I,V)\n5-element SparseVector{Int64,Int64} with 4 stored entries:\n = 1\n = -5\n = 2\n = 3``````\n\nThe inverse of the `sparse` and `sparsevec` functions is `findnz`, which retrieves the inputs used to create the sparse array. `findall(!iszero, x)` returns the cartesian indices of non-zero entries in `x` (including stored entries equal to zero).\n\n``````julia> findnz(S)\n([1, 4, 5, 3], [4, 7, 9, 18], [1, 2, 3, -5])\n\njulia> findall(!iszero, S)\n4-element Array{CartesianIndex{2},1}:\nCartesianIndex(1, 4)\nCartesianIndex(4, 7)\nCartesianIndex(5, 9)\nCartesianIndex(3, 18)\n\njulia> findnz(R)\n([1, 3, 4, 5], [1, -5, 2, 3])\n\njulia> findall(!iszero, R)\n4-element Array{Int64,1}:\n1\n3\n4\n5``````\n\nAnother way to create a sparse array is to convert a dense array into a sparse array using the `sparse` function:\n\n``````julia> sparse(Matrix(1.0I, 5, 5))\n5×5 SparseMatrixCSC{Float64,Int64} with 5 stored entries:\n[1, 1] = 1.0\n[2, 2] = 1.0\n[3, 3] = 1.0\n[4, 4] = 1.0\n[5, 5] = 1.0\n\njulia> sparse([1.0, 0.0, 1.0])\n3-element SparseVector{Float64,Int64} with 2 stored entries:\n = 1.0\n = 1.0``````\n\nYou can go in the other direction using the `Array` constructor. The `issparse` function can be used to query if a matrix is sparse.\n\n``````julia> issparse(spzeros(5))\ntrue``````\n\n## Sparse matrix operations\n\nArithmetic operations on sparse matrices also work as they do on dense matrices. Indexing of, assignment into, and concatenation of sparse matrices work in the same way as dense matrices. Indexing operations, especially assignment, are expensive, when carried out one element at a time. In many cases it may be better to convert the sparse matrix into `(I,J,V)` format using `findnz`, manipulate the values or the structure in the dense vectors `(I,J,V)`, and then reconstruct the sparse matrix.\n\n## Correspondence of dense and sparse methods\n\nThe following table gives a correspondence between built-in methods on sparse matrices and their corresponding methods on dense matrix types. In general, methods that generate sparse matrices differ from their dense counterparts in that the resulting matrix follows the same sparsity pattern as a given sparse matrix `S`, or that the resulting sparse matrix has density `d`, i.e. each matrix element has a probability `d` of being non-zero.\n\nDetails can be found in the Sparse Vectors and Matrices section of the standard library reference.\n\nSparseDenseDescription\n`spzeros(m,n)``zeros(m,n)`Creates a m-by-n matrix of zeros. (`spzeros(m,n)` is empty.)\n`sparse(I, n, n)``Matrix(I,n,n)`Creates a n-by-n identity matrix.\n`Array(S)``sparse(A)`Interconverts between dense and sparse formats.\n`sprand(m,n,d)``rand(m,n)`Creates a m-by-n random matrix (of density d) with iid non-zero elements distributed uniformly on the half-open interval \\$[0, 1)\\$.\n`sprandn(m,n,d)``randn(m,n)`Creates a m-by-n random matrix (of density d) with iid non-zero elements distributed according to the standard normal (Gaussian) distribution.\n`sprandn(m,n,d,X)``randn(m,n,X)`Creates a m-by-n random matrix (of density d) with iid non-zero elements distributed according to the X distribution. (Requires the `Distributions` package.)\n\n# Sparse Arrays\n\n``SparseVector{Tv,Ti<:Integer} <: AbstractSparseVector{Tv,Ti}``\n\nVector type for storing sparse vectors.\n\nsource\n``SparseMatrixCSC{Tv,Ti<:Integer} <: AbstractSparseMatrix{Tv,Ti}``\n\nMatrix type for storing sparse matrices in the Compressed Sparse Column format.\n\nsource\n``sparse(A)``\n\nConvert an AbstractMatrix `A` into a sparse matrix.\n\nExamples\n\n``````julia> A = Matrix(1.0I, 3, 3)\n3×3 Array{Float64,2}:\n1.0 0.0 0.0\n0.0 1.0 0.0\n0.0 0.0 1.0\n\njulia> sparse(A)\n3×3 SparseMatrixCSC{Float64,Int64} with 3 stored entries:\n[1, 1] = 1.0\n[2, 2] = 1.0\n[3, 3] = 1.0``````\nsource\n``sparse(I, J, V,[ m, n, combine])``\n\nCreate a sparse matrix `S` of dimensions `m x n` such that `S[I[k], J[k]] = V[k]`. The `combine` function is used to combine duplicates. If `m` and `n` are not specified, they are set to `maximum(I)` and `maximum(J)` respectively. If the `combine` function is not supplied, `combine` defaults to `+` unless the elements of `V` are Booleans in which case `combine` defaults to `|`. All elements of `I` must satisfy `1 <= I[k] <= m`, and all elements of `J` must satisfy `1 <= J[k] <= n`. Numerical zeros in (`I`, `J`, `V`) are retained as structural nonzeros; to drop numerical zeros, use `dropzeros!`.\n\nFor additional documentation and an expert driver, see `Base.SparseArrays.sparse!`.\n\nExamples\n\n``````julia> Is = [1; 2; 3];\n\njulia> Js = [1; 2; 3];\n\njulia> Vs = [1; 2; 3];\n\njulia> sparse(Is, Js, Vs)\n3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:\n[1, 1] = 1\n[2, 2] = 2\n[3, 3] = 3``````\nsource\n``sparsevec(I, V, [m, combine])``\n\nCreate a sparse vector `S` of length `m` such that `S[I[k]] = V[k]`. Duplicates are combined using the `combine` function, which defaults to `+` if no `combine` argument is provided, unless the elements of `V` are Booleans in which case `combine` defaults to `|`.\n\nExamples\n\n``````julia> II = [1, 3, 3, 5]; V = [0.1, 0.2, 0.3, 0.2];\n\njulia> sparsevec(II, V)\n5-element SparseVector{Float64,Int64} with 3 stored entries:\n = 0.1\n = 0.5\n = 0.2\n\njulia> sparsevec(II, V, 8, -)\n8-element SparseVector{Float64,Int64} with 3 stored entries:\n = 0.1\n = -0.1\n = 0.2\n\njulia> sparsevec([1, 3, 1, 2, 2], [true, true, false, false, false])\n3-element SparseVector{Bool,Int64} with 3 stored entries:\n = true\n = false\n = true``````\nsource\n``sparsevec(d::Dict, [m])``\n\nCreate a sparse vector of length `m` where the nonzero indices are keys from the dictionary, and the nonzero values are the values from the dictionary.\n\nExamples\n\n``````julia> sparsevec(Dict(1 => 3, 2 => 2))\n2-element SparseVector{Int64,Int64} with 2 stored entries:\n = 3\n = 2``````\nsource\n``sparsevec(A)``\n\nConvert a vector `A` into a sparse vector of length `m`.\n\nExamples\n\n``````julia> sparsevec([1.0, 2.0, 0.0, 0.0, 3.0, 0.0])\n6-element SparseVector{Float64,Int64} with 3 stored entries:\n = 1.0\n = 2.0\n = 3.0``````\nsource\n``issparse(S)``\n\nReturns `true` if `S` is sparse, and `false` otherwise.\n\nExamples\n\n``````julia> sv = sparsevec([1, 4], [2.3, 2.2], 10)\n10-element SparseVector{Float64,Int64} with 2 stored entries:\n[1 ] = 2.3\n[4 ] = 2.2\n\njulia> issparse(sv)\ntrue\n\njulia> issparse(Array(sv))\nfalse``````\nsource\n``nnz(A)``\n\nReturns the number of stored (filled) elements in a sparse array.\n\nExamples\n\n``````julia> A = sparse(2I, 3, 3)\n3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:\n[1, 1] = 2\n[2, 2] = 2\n[3, 3] = 2\n\njulia> nnz(A)\n3``````\nsource\n``findnz(A)``\n\nReturn a tuple `(I, J, V)` where `I` and `J` are the row and column indices of the stored (\"structurally non-zero\") values in sparse matrix `A`, and `V` is a vector of the values.\n\nExamples\n\n``````julia> A = sparse([1 2 0; 0 0 3; 0 4 0])\n3×3 SparseMatrixCSC{Int64,Int64} with 4 stored entries:\n[1, 1] = 1\n[1, 2] = 2\n[3, 2] = 4\n[2, 3] = 3\n\njulia> findnz(A)\n([1, 1, 3, 2], [1, 2, 2, 3], [1, 2, 4, 3])``````\nsource\n``spzeros([type,]m[,n])``\n\nCreate a sparse vector of length `m` or sparse matrix of size `m x n`. This sparse array will not contain any nonzero values. No storage will be allocated for nonzero values during construction. The type defaults to `Float64` if not specified.\n\nExamples\n\n``````julia> spzeros(3, 3)\n3×3 SparseMatrixCSC{Float64,Int64} with 0 stored entries\n\njulia> spzeros(Float32, 4)\n4-element SparseVector{Float32,Int64} with 0 stored entries``````\nsource\n``spdiagm(kv::Pair{<:Integer,<:AbstractVector}...)``\n\nConstruct a square sparse diagonal matrix from `Pair`s of vectors and diagonals. Vector `kv.second` will be placed on the `kv.first` diagonal.\n\nExamples\n\n``````julia> spdiagm(-1 => [1,2,3,4], 1 => [4,3,2,1])\n5×5 SparseMatrixCSC{Int64,Int64} with 8 stored entries:\n[2, 1] = 1\n[1, 2] = 4\n[3, 2] = 2\n[2, 3] = 3\n[4, 3] = 3\n[3, 4] = 2\n[5, 4] = 4\n[4, 5] = 1``````\nsource\n``blockdiag(A...)``\n\nConcatenate matrices block-diagonally. Currently only implemented for sparse matrices.\n\nExamples\n\n``````julia> blockdiag(sparse(2I, 3, 3), sparse(4I, 2, 2))\n5×5 SparseMatrixCSC{Int64,Int64} with 5 stored entries:\n[1, 1] = 2\n[2, 2] = 2\n[3, 3] = 2\n[4, 4] = 4\n[5, 5] = 4``````\nsource\n``sprand([rng],[type],m,[n],p::AbstractFloat,[rfn])``\n\nCreate a random length `m` sparse vector or `m` by `n` sparse matrix, in which the probability of any element being nonzero is independently given by `p` (and hence the mean density of nonzeros is also exactly `p`). Nonzero values are sampled from the distribution specified by `rfn` and have the type `type`. The uniform distribution is used in case `rfn` is not specified. The optional `rng` argument specifies a random number generator, see Random Numbers.\n\nExamples\n\n``````julia> sprand(Bool, 2, 2, 0.5)\n2×2 SparseMatrixCSC{Bool,Int64} with 2 stored entries:\n[1, 1] = true\n[2, 1] = true\n\njulia> sprand(Float64, 3, 0.75)\n3-element SparseVector{Float64,Int64} with 1 stored entry:\n = 0.298614``````\nsource\n``sprandn([rng], m[,n],p::AbstractFloat)``\n\nCreate a random sparse vector of length `m` or sparse matrix of size `m` by `n` with the specified (independent) probability `p` of any entry being nonzero, where nonzero values are sampled from the normal distribution. The optional `rng` argument specifies a random number generator, see Random Numbers.\n\nExamples\n\n``````julia> sprandn(2, 2, 0.75)\n2×2 SparseMatrixCSC{Float64,Int64} with 2 stored entries:\n[1, 1] = 0.586617\n[1, 2] = 0.297336``````\nsource\n``nonzeros(A)``\n\nReturn a vector of the structural nonzero values in sparse array `A`. This includes zeros that are explicitly stored in the sparse array. The returned vector points directly to the internal nonzero storage of `A`, and any modifications to the returned vector will mutate `A` as well. See `rowvals` and `nzrange`.\n\nExamples\n\n``````julia> A = sparse(2I, 3, 3)\n3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:\n[1, 1] = 2\n[2, 2] = 2\n[3, 3] = 2\n\njulia> nonzeros(A)\n3-element Array{Int64,1}:\n2\n2\n2``````\nsource\n``rowvals(A::SparseMatrixCSC)``\n\nReturn a vector of the row indices of `A`. Any modifications to the returned vector will mutate `A` as well. Providing access to how the row indices are stored internally can be useful in conjunction with iterating over structural nonzero values. See also `nonzeros` and `nzrange`.\n\nExamples\n\n``````julia> A = sparse(2I, 3, 3)\n3×3 SparseMatrixCSC{Int64,Int64} with 3 stored entries:\n[1, 1] = 2\n[2, 2] = 2\n[3, 3] = 2\n\njulia> rowvals(A)\n3-element Array{Int64,1}:\n1\n2\n3``````\nsource\n``nzrange(A::SparseMatrixCSC, col::Integer)``\n\nReturn the range of indices to the structural nonzero values of a sparse matrix column. In conjunction with `nonzeros` and `rowvals`, this allows for convenient iterating over a sparse matrix :\n\n``````A = sparse(I,J,V)\nrows = rowvals(A)\nvals = nonzeros(A)\nm, n = size(A)\nfor i = 1:n\nfor j in nzrange(A, i)\nrow = rows[j]\nval = vals[j]\n# perform sparse wizardry...\nend\nend``````\nsource\n``dropzeros!(A::SparseMatrixCSC; trim::Bool = true)``\n\nRemoves stored numerical zeros from `A`, optionally trimming resulting excess space from `A.rowval` and `A.nzval` when `trim` is `true`.\n\nFor an out-of-place version, see `dropzeros`. For algorithmic information, see `fkeep!`.\n\nsource\n``dropzeros!(x::SparseVector; trim::Bool = true)``\n\nRemoves stored numerical zeros from `x`, optionally trimming resulting excess space from `x.nzind` and `x.nzval` when `trim` is `true`.\n\nFor an out-of-place version, see `dropzeros`. For algorithmic information, see `fkeep!`.\n\nsource\n``dropzeros(A::SparseMatrixCSC; trim::Bool = true)``\n\nGenerates a copy of `A` and removes stored numerical zeros from that copy, optionally trimming excess space from the result's `rowval` and `nzval` arrays when `trim` is `true`.\n\nFor an in-place version and algorithmic information, see `dropzeros!`.\n\nExamples\n\n``````julia> A = sparse([1, 2, 3], [1, 2, 3], [1.0, 0.0, 1.0])\n3×3 SparseMatrixCSC{Float64,Int64} with 3 stored entries:\n[1, 1] = 1.0\n[2, 2] = 0.0\n[3, 3] = 1.0\n\njulia> dropzeros(A)\n3×3 SparseMatrixCSC{Float64,Int64} with 2 stored entries:\n[1, 1] = 1.0\n[3, 3] = 1.0``````\nsource\n``dropzeros(x::SparseVector; trim::Bool = true)``\n\nGenerates a copy of `x` and removes numerical zeros from that copy, optionally trimming excess space from the result's `nzind` and `nzval` arrays when `trim` is `true`.\n\nFor an in-place version and algorithmic information, see `dropzeros!`.\n\nExamples\n\n``````julia> A = sparsevec([1, 2, 3], [1.0, 0.0, 1.0])\n3-element SparseVector{Float64,Int64} with 3 stored entries:\n = 1.0\n = 0.0\n = 1.0\n\njulia> dropzeros(A)\n3-element SparseVector{Float64,Int64} with 2 stored entries:\n = 1.0\n = 1.0``````\nsource\n``````permute(A::SparseMatrixCSC{Tv,Ti}, p::AbstractVector{<:Integer},\nq::AbstractVector{<:Integer}) where {Tv,Ti}``````\n\nBilaterally permute `A`, returning `PAQ` (`A[p,q]`). Column-permutation `q`'s length must match `A`'s column count (`length(q) == A.n`). Row-permutation `p`'s length must match `A`'s row count (`length(p) == A.m`).\n\nFor expert drivers and additional information, see `permute!`.\n\nExamples\n\n``````julia> A = spdiagm(0 => [1, 2, 3, 4], 1 => [5, 6, 7])\n4×4 SparseMatrixCSC{Int64,Int64} with 7 stored entries:\n[1, 1] = 1\n[1, 2] = 5\n[2, 2] = 2\n[2, 3] = 6\n[3, 3] = 3\n[3, 4] = 7\n[4, 4] = 4\n\njulia> permute(A, [4, 3, 2, 1], [1, 2, 3, 4])\n4×4 SparseMatrixCSC{Int64,Int64} with 7 stored entries:\n[4, 1] = 1\n[3, 2] = 2\n[4, 2] = 5\n[2, 3] = 3\n[3, 3] = 6\n[1, 4] = 4\n[2, 4] = 7\n\njulia> permute(A, [1, 2, 3, 4], [4, 3, 2, 1])\n4×4 SparseMatrixCSC{Int64,Int64} with 7 stored entries:\n[3, 1] = 7\n[4, 1] = 4\n[2, 2] = 6\n[3, 2] = 3\n[1, 3] = 5\n[2, 3] = 2\n[1, 4] = 1``````\nsource\n``````permute!(X::SparseMatrixCSC{Tv,Ti}, A::SparseMatrixCSC{Tv,Ti},\np::AbstractVector{<:Integer}, q::AbstractVector{<:Integer},\n[C::SparseMatrixCSC{Tv,Ti}]) where {Tv,Ti}``````\n\nBilaterally permute `A`, storing result `PAQ` (`A[p,q]`) in `X`. Stores intermediate result `(AQ)^T` (`transpose(A[:,q])`) in optional argument `C` if present. Requires that none of `X`, `A`, and, if present, `C` alias each other; to store result `PAQ` back into `A`, use the following method lacking `X`:\n\n``````permute!(A::SparseMatrixCSC{Tv,Ti}, p::AbstractVector{<:Integer},\nq::AbstractVector{<:Integer}[, C::SparseMatrixCSC{Tv,Ti},\n[workcolptr::Vector{Ti}]]) where {Tv,Ti}``````\n\n`X`'s dimensions must match those of `A` (`X.m == A.m` and `X.n == A.n`), and `X` must have enough storage to accommodate all allocated entries in `A` (`length(X.rowval) >= nnz(A)` and `length(X.nzval) >= nnz(A)`). Column-permutation `q`'s length must match `A`'s column count (`length(q) == A.n`). Row-permutation `p`'s length must match `A`'s row count (`length(p) == A.m`).\n\n`C`'s dimensions must match those of `transpose(A)` (`C.m == A.n` and `C.n == A.m`), and `C` must have enough storage to accommodate all allocated entries in `A` (`length(C.rowval) >= nnz(A)` and `length(C.nzval) >= nnz(A)`).\n\nFor additional (algorithmic) information, and for versions of these methods that forgo argument checking, see (unexported) parent methods `unchecked_noalias_permute!` and `unchecked_aliasing_permute!`.\n\nSee also: `permute`.\n\nsource" ]
[ null ]
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https://internals.rust-lang.org/t/mir-optimization-pass-that-implements-auto-vectorization/16360
[ "# Mir optimization pass that implements auto-vectorization\n\nHello everyone, I made some contributions to both stdarch and rustc in rust-lang in last two years. I would like to talk about the thought of implementing automatic vector optimization in rustc. (I have done a preliminary implementation based on rust1.60.0 and written the documentation, in the README of this repository.)\n\nSIMD(Single Instruction Multiple Data) is a commonly used acceleration technology in computing scenarios. it is also called vectorization. LLVM provides some automatic vectorization optimization mechanisms, but in many scenarios, we still need to manually use SIMD instructions to rewrite the program to get the SIMD acceleration effect.\n\nRust developers currently have multiple ways to use these SIMD instructions:\n\n· stdarch\n\n· protable-SIMD\n\n· use 'extern “platform-intrinsics” ' Abi directly\n\nBut these ways require developers to rewrite their original code. This has several distinct drawbacks:\n\n(1) Makes the code complex and hard to read, multiplying the size of the code\n\n(2) For those unfamiliar with SIMD, getting these speedups is very difficult.\n\nTo solve the problems, we can implement the auto-vectorization feature in the rust compiler. In this way, we don't need to change the original code at all, but only need to add a feature flag to get the SIMD acceleration effect.\n\nI have made a preliminary implementation of this feature. It is based on Rust mir, since mir can clearly express the structure of a function.It behaves like a normal mir optimization pass, and automatically analyze and re-factor the loop part in mir, and to obtain SIMD acceleration in as many scenarios as possible while ensuring safety and program functionality.\n\nfor example:\n\n``````#[vectorization]\nfn func1(arr: &[f32]) -> f32 {\nlet mut sum = 0.;\nfor i in arr {\nsum += *i;\n}\nsum\n}\n\nfn func2(arr: &[f32]) -> f32 {\nlet mut sum = 0.;\nfor i in arr {\nsum += *i;\n}\nsum\n}\n``````\n\n(Test code is here)\n\nIn this example, the only difference bwteen func1 and func2 is that the #[vectorization] attribute added to func1, indicating that automatic vectorization is enabled on this function. We call two functions separately in the `main` function and count the time they spend. After compiled and run with the `rustc -Copt-level=3 -Zmir-opt-level=4` command in the local `x86_64` environment, the results are as follows:\n\n``````t1: 327\nt2: 6519\nans1: 2201600\nans2: 2201600\n``````\n\nWe can see that the first function is almost 20 times faster than the second function.\n\nMore practical example: calculating the variance of an array:\n\nCalculating variance is a very commonly used function in the field of statistics. The test code is here.\n\nWe can see the following two functions:\n\n``````#[vectorization]\nfn var1(arr: &[f32]) -> f32 {\nlet mut sq_sum = 0.;\nlet mut sum = 0.;\nlet len = arr.len() as f32;\nfor i in arr {\nsum += i;\nsq_sum += i * i;\n}\nlet ave = sum / len;\n(sq_sum / len - ave * ave).sqrt()\n}\n\nfn var2(arr: &[f32]) -> f32 {\nlet mut sq_sum = 0.;\nlet mut sum = 0.;\nlet len = arr.len() as f32;\nfor i in arr {\nsum += i;\nsq_sum += i * i;\n}\nlet ave = sum / len;\n(sq_sum / len - ave * ave).sqrt()\n}\n``````\n\nThe difference between the two functions is still only whether to add the #[vectorization] attribute. After using the same compilation command and environment as before, the effect of running is as follows:\n\n``````t1: 7\nt2: 67\nans1: 28.667055\nans2: 28.649292\n``````\n\nWe can see that the first function is about 10 times faster than the second one. The result of the calculation is somewhat different, because the calling SIMD instruction results in a different order of floating-point operations, resulting in different rounding errors. There is currently no good solution to this problem.\n\nMore complex example\n\nWe can look at this more complex example below. The test code is here.\n\n``````#[vectorization]\nfn func1(src: &[f32], src2: &[f32], val: &mut [f32]) {\nlet mut sum = 0.;\nfor x in 0..src.len() {\nlet v = src[x];\nsum += v * v;\nval[x] = src2[x] + sum;\n}\n}\n``````\n\nIn this example, the value of the variable sum will be changed in each thorn loop based on the value in the previous loop, which can have a significant impact on the effect of auto-vectorization. We can check the result of running:\n\n``````t1: 6984\nt2: 7952\n``````\n\nThe optimization effect is not very significant, but there is still more than 13% efficiency improvement.\n\nThere are more detailed descriptions and implementation code in this repository. I think this feature deserves a proposal. Anyone interested in this can work together to implement it.\n\nCan you say more about why doing this is rustc, as opposed to the LLVM autovectorization that already exists, is important?\n\nI would guess that a substantial part of that is from `add_unordered`, since the default addition in rust needs to be ordered.\n\nIf we had scalar `add_unordered` then I expect this would get vectorized the same way it does with `i32`s: https://play.rust-lang.org/?version=nightly&mode=release&edition=2021&gist=985182c57dff729c7374b6c06ab2ee3c\n\n`````` %12 = add <4 x i32> %wide.load, %vec.phi20\n%13 = add <4 x i32> %wide.load23, %vec.phi21\n%14 = mul <4 x i32> %wide.load, %wide.load\n%15 = mul <4 x i32> %wide.load23, %wide.load23\n%16 = add <4 x i32> %14, %vec.phi\n%17 = add <4 x i32> %15, %vec.phi19\n``````\n1 Like\n\nYes, there is also auto-vectorization in llvm. But if auto-vectorization in llvm solves all problems, why do we use stdarch and portable-simd? We Implemente it in rustc to enable vectorization in those scenarios where llvm auto-vectorization can't solve it and the code has to be rewritten manually. For example, loop structures contain if...else statements, or reading of continuous array indexes from an iterator.\n\nThe automatic vectorization I have implemented so far can only handle some uncomplicated scenarios, which can also be optimized by llvm's auto-vectorization. For example, in the above code, we call the \"simd_add\" intrinsic in the loop and use the \"simd_reduce_add_unorderd\" intrinsic again after the loop ends. In theory, llvm can also do this kind of optimization. You can view the optimized mir structure here\n\nWell, one reason is to use various operations that aren't easily coded in scalar rust. Like if you really want _mm512_bitshuffle_epi64_mask in core::arch::x86_64 - Rust then I'd be very surprised for LLVM autovectorization to pick it up. But those cases, to me, are the ones that we wouldn't implement in a rust autovectorizer either.\n\nSo basically the core of my question is what patterns can we reasonably notice in Rust in a way that's better than extending LLVM to notice those same patterns? (Especially considering things like https://polly.llvm.org/, which I suspect will always be more powerful than anything we do.)\n\nOr is there some advantage we get from doing this in MIR even in cases where LLVM can do it anyway?\n\nThis is a good example of one of those things that's far easier to detect in LLVM.\n\nThis code, for example, https://rust.godbolt.org/z/Wsj1ssTxj\n\n``````pub fn demo1(a: &[i32], b: &[i32]) -> i32 {\nstd::iter::zip(a, b)\n.map(|(a, b)| a * b)\n.sum()\n}\n``````\n\nAlready vectorizes in LLVM\n\n`````` %21 = mul <8 x i32> %wide.load29, %wide.load, !dbg !66\n%22 = mul <8 x i32> %wide.load30, %wide.load26, !dbg !66\n%23 = mul <8 x i32> %wide.load31, %wide.load27, !dbg !66\n%24 = mul <8 x i32> %wide.load32, %wide.load28, !dbg !66\n%25 = add <8 x i32> %21, %vec.phi, !dbg !83\n%26 = add <8 x i32> %22, %vec.phi23, !dbg !83\n%27 = add <8 x i32> %23, %vec.phi24, !dbg !83\n%28 = add <8 x i32> %24, %vec.phi25, !dbg !83\n``````\n\nBut that's something that's much harder to see in MIR. We're just not good at seeing through all the intermediate noise.\n\nNot that rust has been great about it exposing LLVM's auto-vectorization as much as it could. For example, this test had to be added only a couple of weeks ago along with a change (#94570) to stop rust blocking a bunch of autovectorization opportunities from getting picked up:\n\nAlso, let me give a shout-out to `std::simd`, which gives a really easy line-by-line translation of the variance example in the repo readme: https://rust.godbolt.org/z/9Wc6Kbb47\n\n``````const LANES: usize = 16;\npub fn var_std_simd(arr: &[f32]) -> f32 {\nlet mut sq_sum = Simd::from_array([0.0; LANES]);\nlet mut sum = Simd::from_array([0.0; LANES]);\n\n// the `platform-intrinsic` example in the introduction of the auto-vectorization\n// fork's readme is ignoring the tail, so this does too\nlet (chunks, _tail) = arr.as_chunks();\nfor chunk in chunks {\nlet chunk = Simd::from_array(*chunk);\nsum += chunk;\nsq_sum += chunk * chunk;\n}\n\nlet len = arr.len() as f32;\nlet ave = sum.reduce_sum() / len;\nsq_sum.reduce_sum() / len - ave * ave\n}\n``````\n2 Likes\n\nFor example this function:\n\n``````pub fn func1(arr1: &mut [u32], arr2: &mut [u32]) {\nfor i in 1..arr2.len() {\narr2[i] += arr2[i - 1];\narr1[i] += arr2[i];\n}\n}\n``````\n\nIt is not auto-vectorized in llvm: Compiler Explorer\n\nBut the second statement in the loop:\n\n`````` arr1[i] += arr2[i];\n``````\n\nBy analyzing the mir structure, we know that this statement can do automatic vector optimization in rustc.\n\nAnd this function too: Compiler Explorer\n\n``````pub fn func1(arr1: &mut [u32], arr2: &[u32]) {\nfor i in 0..arr1.len() {\nif arr1[i] > 100 {\narr1[i] = arr2[i];\n}\n}\n}\n``````\n\nBy analyzing mir, we can easily do auto-vectorization. For example on x86_64 use a combination of `_mm_cmplt_*` and `_mm_blendv_*`\n\nIt's not clear to me what it takes to get llvm's auto-vectorization to support these scenarios, but we can easily get what we want by mir optimizations.\n\n1 Like\n\nThe general thing that both those examples are hitting is that they can panic when one of the arrays is not long enough. So LLVM is carefully maintaining the partial work that is done before the panic in the cases where that panic is hit in the middle of the loop. We would have to do this in MIR too.\n\nIf you assert up-front that things are long enough, then the loops become canonical again and it optimizes them better: https://rust.godbolt.org/z/4c9v5WKvb\n\n``````pub fn func1_earlycheck(arr1: &mut [u32], arr2: &mut [u32]) {\nlet n = arr2.len();\nlet (arr1, arr2) = (&mut arr1[..n], &mut arr2[..n]);\nfor i in 1..n {\narr2[i] += arr2[i - 1];\narr1[i] += arr2[i];\n}\n}\n``````\n\n\"reslicing\" like that is a good general technique to encourage removal of bounds checks. It's what I used in MIRI says `reverse` is UB, so replace it with something LLVM can vectorize by scottmcm · Pull Request #90821 · rust-lang/rust · GitHub to get that to vectorize, for example.\n\n(Autovectorizing this stuff is easier in C since the compiler can just assume everything is always long enough, as out-of-bounds indexing is UB.)\n\nOf course, often the best approach is just to use iterators instead. If we write that second example like so: https://rust.godbolt.org/z/eG8sc6fhs\n\n``````pub fn func1_just_use_iter(arr1: &mut [u32], arr2: &[u32]) {\nstd::iter::zip(arr1, arr2)\n.for_each(|(a, b)| {\nif *a > 100 {\n*a = *b;\n}\n})\n}\n``````\n\nThen it does get vectorized:\n\n`````` %13 = icmp ugt <8 x i32> %wide.load, <i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100>, !dbg !75\n%14 = icmp ugt <8 x i32> %wide.load8, <i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100>, !dbg !75\n%15 = icmp ugt <8 x i32> %wide.load9, <i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100>, !dbg !75\n%16 = icmp ugt <8 x i32> %wide.load10, <i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100, i32 100>, !dbg !75\n%17 = getelementptr [0 x i32], [0 x i32]* %arr2.0, i64 0, i64 %index, !dbg !83\n%18 = bitcast i32* %17 to <8 x i32>*, !dbg !94\n%wide.masked.load = call <8 x i32> @llvm.masked.load.v8i32.p0v8i32(<8 x i32>* %18, i32 4, <8 x i1> %13, <8 x i32> poison), !dbg !94, !noalias !89\n%19 = getelementptr i32, i32* %17, i64 8, !dbg !94\n%20 = bitcast i32* %19 to <8 x i32>*, !dbg !94\n%wide.masked.load11 = call <8 x i32> @llvm.masked.load.v8i32.p0v8i32(<8 x i32>* %20, i32 4, <8 x i1> %14, <8 x i32> poison), !dbg !94, !noalias !89\n%21 = getelementptr i32, i32* %17, i64 16, !dbg !94\n%22 = bitcast i32* %21 to <8 x i32>*, !dbg !94\n%wide.masked.load12 = call <8 x i32> @llvm.masked.load.v8i32.p0v8i32(<8 x i32>* %22, i32 4, <8 x i1> %15, <8 x i32> poison), !dbg !94, !noalias !89\n%23 = getelementptr i32, i32* %17, i64 24, !dbg !94\n%24 = bitcast i32* %23 to <8 x i32>*, !dbg !94\n%wide.masked.load13 = call <8 x i32> @llvm.masked.load.v8i32.p0v8i32(<8 x i32>* %24, i32 4, <8 x i1> %16, <8 x i32> poison), !dbg !94, !noalias !89\n%25 = bitcast i32* %5 to <8 x i32>*, !dbg !95\ncall void @llvm.masked.store.v8i32.p0v8i32(<8 x i32> %wide.masked.load, <8 x i32>* %25, i32 4, <8 x i1> %13), !dbg !95, !alias.scope !84, !noalias !89\n%26 = bitcast i32* %7 to <8 x i32>*, !dbg !95\ncall void @llvm.masked.store.v8i32.p0v8i32(<8 x i32> %wide.masked.load11, <8 x i32>* %26, i32 4, <8 x i1> %14), !dbg !95, !alias.scope !84, !noalias !89\n%27 = bitcast i32* %9 to <8 x i32>*, !dbg !95\ncall void @llvm.masked.store.v8i32.p0v8i32(<8 x i32> %wide.masked.load12, <8 x i32>* %27, i32 4, <8 x i1> %15), !dbg !95, !alias.scope !84, !noalias !89\n%28 = bitcast i32* %11 to <8 x i32>*, !dbg !95\ncall void @llvm.masked.store.v8i32.p0v8i32(<8 x i32> %wide.masked.load13, <8 x i32>* %28, i32 4, <8 x i1> %16), !dbg !95, !alias.scope !84, !noalias !89\n``````\n\nLoops with indexes are often an anti-pattern in Rust -- see `needless_range_loop` in clippy -- so I'd be particularly sad if we got any feature that only worked with them.\n\n12 Likes\n\nThank you for the explanation. Based on the above discussion, I think maybe we can continue to do auto-vectorization mir-opt from another direction. We don't call SIMD intrinsics directly in mir, but just adjust the structure of the loop to be recognized by llvm's auto-vectorization mechanism. For example the above example:\n\n``````pub fn func1(arr1: &mut [u32], arr2: &mut [u32]) {\nfor i in 1..arr2.len() {\narr2[i] += arr2[i - 1];\narr1[i] += arr2[i];\n}\n}\n``````\n\nIt's not currently optimized by llvm's auto-vectorization, but if we go through mir analysis and adjust its structure to something like this:\n\n``````pub fn func1(arr1: &mut [u32], arr2: &mut [u32]) {\nfor i in 1..arr2.len() {\narr2[i] += arr2[i - 1];\n}\nfor i in 1..arr2.len() {\narr1[i] += arr2[i];\n}\n}\n``````\n\nThen it's easily auto-vector-optimized by llvm: Compiler Explorer\n\nLikewise, for the following example:\n\n``````pub fn func1(arr1: &mut [u32], arr2: &[u32]) {\nfor i in 0..arr1.len() {\nif arr1[i] > 100 {\narr1[i] = arr2[i];\n}\n}\n}\n``````\n\nIt can also be auto-vectorized by llvm if we tweak it a bit through mir-opt: Compiler Explorer\n\n``````pub fn func1(arr1: &mut [u32], arr2: &[u32]) {\nfor i in 0..arr1.len() {\nlet x = arr1[i];\nlet y = arr2[i];\nif x > 100 {\narr1[i] = y;\n}\n}\n}\n``````\n\nI don't think those are valid transformations:\n\n• In the first one `arr1[i]` could panic, and this changes the result of the function because in that case not all `arr2` elements will be changed;\n\n• In the second one `arr2[i]` could panic even if `arr1[i]` didn't (consider for example `func1(&mut [101, 0], &)`, this doesn't panic, but with your transformation it would).\n\nEdit: compile -> panic typo, not sure what I was thinking at that time.\n\n5 Likes\n\nI think this is also the reason why sometimes developers have to use SIMD intrinsics manually - developers themselves need to be responsible for the correctness of the program.\n\nI think we can declare some optimization pass as unsound first. This at least provides developers with some choice - if they can guarantee the correctness of the program from the overall logic themselves.\n\nNote that that first loop is a prefix sum, which has data dependencies that make it non-trivial: https://en.wikipedia.org/wiki/Prefix_sum#Parallel_algorithms\n\nLLVM will unroll it, but it doesn't vectorize it in either index or iterator forms: https://rust.godbolt.org/z/1vdErE8jE\n\nThere are a multitude of possible choices for how to go about it, with different cache and parallelism tradeoffs.\n\nEDIT: I stumbled on this great chart demonstrating that from Prefix Sum with SIMD - Algorithmica\n\n4 Likes\n\nMost of the time you can \"solve\" the problem that makes those transformation by adding an explicit assert at the start which guarantess that the later assertions will always succeed if the first assert succeed. In contrast the current behaviour is a sequence of asserts that could all fail even if the previous ones succeed, and this is what makes many transformations (and thus optimizations) invalid.\n\nUnfortunately this is something that needs to be done why the programmer writing the code, not the compiler.\n\nI feel like this could be a footgun. If you know the algorithm is right, then `unsafe` is already an option and makes what's happening pretty clear. Relying on some obscure optimization doing what you expect feels much more fragile.\n\n3 Likes\n\nIt seems that I'm heading in the wrong direction entirely. Thank you all for taking the time and pointing out. I think I won't go any further in this regard.\n\nThis topic was automatically closed 90 days after the last reply. New replies are no longer allowed." ]
[ null ]
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https://www.liquisearch.com/entropy/thermodynamical_and_statistical_descriptions
[ "# Entropy - Thermodynamical and Statistical Descriptions\n\nThermodynamical and Statistical Descriptions\n\nAny method involving the notion of entropy, the very existence of which depends on the second law of thermodynamics, will doubtless seem to many far-fetched, and may repel beginners as obscure and difficult of comprehension.\n\nWillard Gibbs, Graphical Methods in the Thermodynamics of Fluids\n\nThere are two related definitions of entropy: the thermodynamic definition and the statistical mechanics definition. The thermodynamic definition was developed in the early 1850s by Rudolf Clausius and essentially describes how to measure the entropy of an isolated system in thermodynamic equilibrium. Importantly, it makes no reference to the microscopic nature of matter. The statistical definition was developed by Ludwig Boltzmann in the 1870s by analyzing the statistical behavior of the microscopic components of the system. Boltzmann showed that this definition of entropy was equivalent to the thermodynamic entropy to within a constant number which has since been known as Boltzmann's constant. In summary, the thermodynamic definition of entropy provides the experimental definition of entropy, while the statistical definition of entropy extends the concept, providing an explanation and a deeper understanding of its nature.\n\nThermodynamic entropy is a non-conserved state function that is of great importance in the sciences of physics and chemistry. Historically, the concept of entropy evolved in order to explain why some processes (permitted by conservation laws) occur spontaneously while their time reversals (also permitted by conservation laws) do not; systems tend to progress in the direction of increasing entropy. For isolated systems, entropy never decreases. This fact has several important consequences in science: first, it prohibits \"perpetual motion\" machines; and second, it implies the arrow of entropy has the same direction as the arrow of time. Increases in entropy correspond to irreversible changes in a system, because some energy is expended as waste heat, limiting the amount of work a system can do.\n\nIn statistical mechanics, entropy is a measure of the number of ways in which a system may be arranged, often taken to be a measure of \"disorder\" (the higher the entropy, the higher the disorder). This definition describes the entropy as being proportional to the natural logarithm of the number of possible microscopic configurations of the individual atoms and molecules of the system (microstates) which could give rise to the observed macroscopic state (macrostate) of the system. The constant of proportionality is the Boltzmann constant." ]
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https://discuss.pytorch.org/t/model-eval-gives-incorrect-loss-for-model-with-batchnorm-layers/7561
[ "# Model.eval() gives incorrect loss for model with batchnorm layers\n\nI tried to train a model with batchnorm layers. During the training, I set model.train(). Every 100 iteration, I validate the accuracy and set model.eval(). However, the validation is not correct. I don’t think this is due to overfitting because even if I use the same image as training, the testing loss is also quite different from the training loss. Also, if I still set model.train() during testing, the testing loss is correct. But such usage does not make sense because my model contains batchnorm layers.\n\nBelow is my training code:\n\n``````for epoch in range(num_epochs):\nepoch_loss = 0.0\noptimizer = lr_scheduler(optimizer, epoch)\n\nfor iteration, data in enumerate(dataloader, 0):\niter_index += 1\nlabel_patch = data['label_patch']\nresidue_patch = data['residue_patch']\nstacked_patch = data['stacked_patch']\nmicroshift_patch = data['train_patch']\n\n# set model to train mode (before zero grad)\nmodel.train()\n\n# forward\noutputs = model(inputs)\nloss = criterion(outputs, residues)\n\n# backward + optimize only if in training phase\nloss.backward()\noptimizer.step()\n\n# statistics\nepoch_loss += loss.data\n\n# test the model every 100 iterations\nif iter_index % logging_iter == 0:\nloss_test, psnr_test = test_model(model)\n\n# checkpoint for each epoch\nmodel_out_path = \"checkpoints/model_epoch_{}_residue.pth\".format(epoch)\ntorch.save(model, model_out_path)``````\n5 Likes\n\nThe testing code which is called every 100 training iters is as following:\n\n``````def test_model(model):\npsnr_test_avg = 0\nloss_test_avg = 0\nmodel.eval()\n\nfor iteration, test_data in enumerate(dataloader_test, 0):\nlabel_test = test_data['label_patch']\nresidue_test = test_data['residue_patch']\nstacked_test = test_data['stacked_patch']\nmicroshift_test = test_data['train_patch']\noutputs_test = model(inputs_test)\nloss_mse_test = criterion_mse(outputs_test + microshifts_test, labels_test).data.cpu().numpy()\nloss_l1_test = criterion(outputs_test, residues_test).data.cpu().numpy()\npsnr_test = 10 * np.log10(255 * 255 / loss_mse_test)\nloss_test_avg += loss_l1_test\npsnr_test_avg += psnr_test\n\nloss_test_avg /= (iteration + 1)\npsnr_test_avg /= (iteration + 1)\n\nreturn loss_test_avg, psnr_test_avg``````\n\nit is possible that your training in general is unstable, so BatchNorm’s `running_mean` and `running_var` dont represent true batch statistics.\n\nhttp://pytorch.org/docs/master/nn.html?highlight=batchnorm#torch.nn.BatchNorm1d\n\nTry the following:\n\n• change the `momentum` term in BatchNorm constructor to higher.\n• before you set `model.eval()`, run a few inputs through `model` (just forward pass, you dont need to backward). This will help stabilize the running_mean / running_std values.\n\nHope this helps.\n\n13 Likes\n\nThanks for your reply. I tried them but still get the error. I found that using the same code, sometimes the model.eval() can be correct but sometimes incorrect. I will try further and update if I found a solution.\n\n1 Like\n\nSame problem with latest 0.3.0 release here. Have you find any solution? @zhangboknight\nChange `momentum` won’t solve the problem @smth\n\n1 Like\n\nI’m having the same issue. Really a bummer to have to use train mode for validation/testing.\n\n1 Like\n\nI also have the same problem and haven’t figured out the reason.\n\n1 Like\n\nAny update regarding this problem. I already posted the same question. it seems to me that many are facing the same problem. Could pytorch community react to this problem ?\n\n1 Like\n\nI have the same problem.\n\nI’m trying to load caffe weights in a pytorch model with batchnorm layers, each time I load the weights from the caffemodel file, the result for the same input is different even in eval mode.\n\nI’m actually updating the running_mean and running_var from the caffemodel weights, so there shouldn’t be any issue with bad running_means during inference.\n\n@meetshah1995 the meaning of Caffe’s running_mean might be different from pytorch’s running_mean.\n\n1 Like\n\n@falmasri I wrote above in the comment here: Model.eval() gives incorrect loss for model with batchnorm layers with a working answer.\n\nIt’s not a problem in the sense that it’s not a software bug.\n\nIt’s a problem in the sense that if you have a non-stationary training, you will see this behavior unless you adjust your momentum term of the BatchNorm. We set the `momentum` to 0.1 because for most workloads that we use it was sufficient. Play around with it.\n\n@smth Agreed that running_mean may mean different things in Caffe and PyTorch. However in eval mode, I guess only these 5 things - (running_mean, running_var, weight, bias, eps) should affect the final output.\n\nI’ll try to see if I can come up with a minimal reproducible example for this.\n\n@smth What do you mean by non stationary training ?\n\n@falmasri means the statistics of activations change rapidly during training, such that the running_mean and running_std statistics for BatchNorm at the momentum of 0.1 are not valid anymore.\n\nIs it theoretically incorrect though?\n\nNice, setting the momentum to 0.5 seems to make loss calculated using model.eval() similar to the loss computed using model.train(), but only after few epochs of differing results.\n\nDoes the second suggestion work only when we are loading the model for eval? It should not affect the loss calculation, correct or incorrect, if we are training the network and running validation every nth step.\n\nI also met this problem in my project (See my answer at https://github.com/xingyizhou/pytorch-pose-hg-3d/issues/16 and https://github.com/bearpaw/pytorch-pose/issues/33). In short, down-grading pytorch version to 0.1.12 will resolve the problem. But I really don’t know what happens to the BN implementation from 0.1.12 to the later versions …\n\n1 Like\n\nI replied on the issue, but running stats is unstable in nature with batch size only being 1.\n\nThanks for the reply! The training batch size is 6 instead of 1. Actually I have also tried later batch size (32) with other architectures (upsampling on ResNet18) but the bug remains. My major question is I don’t understand why pytorch 0.1.12 works while >= 0.2 does not.\n\n4 Likes\n\nI think this is not about the `momentum`. I have the same problem. when I call\n\n``````model.eval()\nmodel(input)\nmodel.train()\nmodel(input)\nmodel.eval()\nmodel(input)\nmodel.train()\nmodel(input)\n``````\n\nevery call of `model(input)` is almost the same if it is after `model.train()` , but differs with what follows `model.eval()`.\n\n4 Likes" ]
[ null ]
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http://garden.irmacs.sfu.ca/category/fibonacci
[ "# Fibonacci\n\n## Wall-Sun-Sun primes and Fibonacci divisibility ★★\n\nAuthor(s):\n\nConjecture   For any prime", null, ", there exists a Fibonacci number divisible by", null, "exactly once.\n\nEquivalently:\n\nConjecture   For any prime", null, ",", null, "does not divide", null, "where", null, "is the Legendre symbol.\n\nKeywords: Fibonacci; prime", null, "" ]
[ null, "http://garden.irmacs.sfu.ca/files/tex/928cd9d544fdea62f88a627aaee28c416c4366c0.png", null, "http://garden.irmacs.sfu.ca/files/tex/928cd9d544fdea62f88a627aaee28c416c4366c0.png", null, "http://garden.irmacs.sfu.ca/files/tex/a9737aaa01b2918b7e8ab9f12ab0a7c463381427.png", null, "http://garden.irmacs.sfu.ca/files/tex/8f6ab14c3cc11c005c9b97778062620c197ff66d.png", null, "http://garden.irmacs.sfu.ca/files/tex/e1a04059df8fc3e49db781f306092d0d564732e3.png", null, "http://garden.irmacs.sfu.ca/files/tex/d8d0b3deced8bb07e56b3da3337f2d8c7db060a1.png", null, "http://garden.irmacs.sfu.ca/misc/feed.png", null ]
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https://quant.stackexchange.com/questions/7558/central-limit-theorem-and-l%C3%A9vy-processes
[ "# Central Limit Theorem and Lévy processes\n\nLévy processes are self-decomposable and independent on any non-overlapping interval, so how come the distribution of the process at time T,$\\phi(T)$, which is the sum of N i.i.d with law $\\phi(T/N)$ is not normally distributed ? I cannot find what am I missing here ?\n\n## 3 Answers\n\nI believe your problem is that you're assuming all Lévy processes are stable with exponent $2$. Here is what happens if we try to use your argument: Let $X$ be a Lévy process (that is a martingale, for simplicity). At time $t$, for any $N$, we have $$X_t \\sim\\sum_{i=1}^N X^i \\left(\\frac{t}{N}\\right),$$ with each $X^i \\left(\\frac{t}{N}\\right)$ i.i.d. and distributed like $X_{\\frac{t}{N}}$. In order to apply the Central Limit Theorem, to deduce the alleged normality of $X_t$, what we would want is $$X^i \\left(\\frac{t}{N} \\right) \\sim \\frac{1}{\\sqrt{N}} X^i,$$ where now the $X^i$ are a sequence of i.i.d random variables which don't depend on $N$ anymore (i.e. each $X^i \\sim X_t$) This is critical, because the CLT only applies to a fixed sequence of random variables. This then would yield $$X_t \\sim \\frac{1}{\\sqrt{N}} \\sum_{i=1}^N X^i,$$ which, as $N \\rightarrow \\infty$, would fit the template of the Central Limit Theorem (of course up to variance conditions)\n\nThis property (that $X_{\\frac{t}{N}} \\sim \\frac{1}{\\sqrt{N}} X_t$), however, is not enjoyed by an arbitrary Lévy martingale (although it is satisfied by Brownian Motion). Consequently, if you carried out this argument in general, you would have to use a triangular array of random variables, (see my comment below on these objects) which give rise to stable distributions through a generalization of the CLT.\n\nThe more general scaling property for a Lévy process is that $X$ satisfies $$X_t / t^{1/\\alpha} \\sim X_1,$$ with $\\alpha$ being known as the exponent of the process. This is the basic property of the stable processes, which are a subset of the Lévy processes. The Poisson Process, for example, isn't stable, while the Cauchy process is stable with exponent $1$. A $2$-stable process must be Gaussian\n\nEDIT:\n\nI'd like to add a new argument, which attempts to explain the following fact: If $X$ is a Levy process, then it is Gaussian if and only if it has continuous paths. This is a technical argument, and indeed it basically constitutes half of the Levy decomposition theorem.\n\nLet $\\xi_{nj}$ be a triangular null array of independent random variables. This means $\\xi_{nj}$ is defined, for $1 \\leq j \\leq m_n$, for each $n \\in \\mathbb{N}$, and $\\sup_j E\\left[ |\\xi_{nj}| \\wedge 1 \\right] \\rightarrow 0$ as $n \\rightarrow \\infty$. This is like a uniform convergence in probability to zero, as $n \\rightarrow \\infty$. I'm going to cite a Theorem due to Feller and Levy. I found it in \"Foundations of Modern Probability\" by Kallenberg.\n\nTheorem Let $\\xi_{nj}$ be a triangular null array. $\\sum_j \\xi_{nj}$ converges to a normal r.v. $\\xi \\sim N(b,c)$ if and only if the following three conditions hold:\n\n$$\\sum_j P(|\\xi_{nj}| > \\epsilon) \\rightarrow 0 \\text{ for all } \\epsilon > 0,$$ $$\\sum_j E \\left[\\xi_{nj} ; |\\xi_{nj}| \\leq 1 \\right] \\rightarrow b,$$ $$\\sum_j var \\left[\\xi_{nj} ; |\\xi_{nj}| \\leq 1 \\right] \\rightarrow c$$\n\nThe proof of this theorem is not easy. Message me if you'd like to get more details. However, the upshot is that, assuming this theorem, we see that path continuity is essentially equivalent to the first condition, with $\\xi_{nj}$ representing the $j^{th}$ increment of $X$ with the $n^{th}$ grid. Mean and variance control are the second and third conditions, respectively.\n\n• I am not persuaded yet. For instance, I believe that VG process has first 4 moments and is self-decomposable, so each T can be devided to T/N intervals with characteristic function of power T/N. you can increase N enough to get CLT for any length of T so the process should be gaussian but it is VG. What am I missing? – Amir Yousefi Mar 21 '13 at 21:08\n• For any Levy process, you can write $X_t \\sim \\sum_{i=1}^N X^i(t/N)$. This by itself isn't enough. To apply CLT, you need a fixed sequence of random variables: the CLT then says that when you sum $N$ of them and divided by $\\sqrt{N}$, that converges weakly to a normal as $N \\rightarrow \\infty$. BUT, in order to work with a fixed sequence of random variables (namely identical copies of $X_t$, say), you need to have the proper scaling property. The $\\sqrt{\\cdot}$ in the central limit theorem corresponds exactly to the $2$-exponent particular to Brownian Motion. – quasi Mar 21 '13 at 21:47\n• To add some more info if you're interested, if you don't make any assumption of scalability, what you get when you let $N$ tend to infinity is a triangular collection of random variables, in the sense that for each $N$, you have $N$ i.i.d random variables. There is a generalization of the CLT which says that stable distributions (and every Levy process of course has a stable distribution) arise from such arrays. See the [wikipedia page on triangular arrays](en.wikipedia.org/wiki/Infinite_divisibility_(probability) for example. – quasi Mar 21 '13 at 21:54\n• What I think the OP is asking is whether in the limit of $t \\rightarrow \\infty$ the distribution of $X_t$ will converge to Gaussian (assuming finite second moment of the marginal Levy distribution). My understating is that it will by the CLT, no? – Confounded May 21 '20 at 10:46\n\nThe Lévy theorem states that the conditions that have to be met for $M(t)$ to be a Brownian motion (and hence be normally distributed):\n\n• $M(t)$, for $t>0$, be a martingale relative to some filtration $F(t), t>0$.\n• $M(0)= 0$\n• $M(t)$ has continuous paths\n• $[M,M](t) = t$ for all $t\\geq0$;\n\nSo, to test each condition you simply differentiate your Lévy process (using Itô Calculus), change to the integrated form and you notice that at $t=0$ the stochastic integral takes the value zero, hence the expectation is always zero (at $t=0$). When you take the expectation of the stochastic integral you can isolate the following moment generating function:\n\n$$\\mathbb{E}\\left[\\mathrm{exp}\\left(uM(t)\\right)\\right] = \\mathrm{exp}\\left(\\frac{1}{2} u^2t\\right)$$\n\nwhich is the MGF for the normal distribution with zero mean and variance $t$. Therefore your $M(t)$ Lévy process follows the same distribution and you just showed that also an $M(t)$ process follows normality.\n\nIf your Levy process does not satisfy above conditions but still follows the general definition of a Levy processes as stated here:\n\nhttp://almostsure.wordpress.com/2010/11/23/levy-processes/\n\nthen you can utilize the characteristic functions. Since the characteristic function of a convolution is the product of the characteristic functions of the densities involved, the central limit theorem has yet another restatement: the product of the characteristic functions of a number of density functions becomes close to the characteristic function of the normal density as the number of density functions increases without bound, under the conditions stated above. However, to state this more precisely, an appropriate scaling factor needs to be applied to the argument of the characteristic function.\n\nThe following shows how those scaling factors and drift adjustments can be made:\n\nhttp://www.stats.ox.ac.uk/~winkel/lp1.pdf\n\n• Bob, thanks a lot for the edit. My apologies again – Matt Mar 20 '13 at 6:11\n• You're welcome. The edit wasn't any trouble at all. – Bob Jansen Mar 20 '13 at 10:20\n• let me reword my question, I am still not convinced in that how central limit theorem fails for all those Levy processes which have not normal distribution ( VG process as an example). I believe CLT needs many i.i.d distributions to be summed. Self-decomposablity says for time T you can break it down to sum of N many T/N distributions. So I say that how sum of these N i.i.d is not normal? – Amir Yousefi Mar 21 '13 at 1:31\n• @AmirYousefi, I edited my answer to also include the case when a Levy process is not a Brownian motion. – Matt Mar 21 '13 at 3:16\n• I retracted my up vote because I think compared to my own answer your answer complicates things unnecessarily. I find it difficult to check it is even correct. – Bob Jansen Mar 21 '13 at 10:29\n\nA very good question. In other words you ask why the central limit theorem does not hold, right? A sum of iid should be somehow normal, right? Looking at the Levy-Kinchin representation we see the Gaussian part, which comes from increments of a continuous process, and the rest from the jumps. So one answer (which is not mathematically rigorous) is the presence of jumps. Another reason is that a Levy process can have infinite moments (also because of the jumps).\n\nIf we the process is continuous then it is Gaussian (if and only if). The jumps enrich the model but of course make if much more complicated.\n\n• Right, I have an elementary understanding of these processes so correct me if I am wrong. The only condition for the iid distributions is having finite variance, so for example VG process has finite variance and it is self-decomposable ( so you can divide it to N iid over a period). Why it is not normal? I mean should not it contradict itself? – Amir Yousefi Mar 21 '13 at 1:52\n• I like the question very much. The reason must but that it has jumps (because of time jumps due to the Gamma subordinator). But I can not tell you a rigorous reasoning. If there are jumps then it is not Gaussian. I will try to find something. – Ric Mar 21 '13 at 10:15" ]
[ null ]
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https://www.geeksforgeeks.org/check-if-the-xor-of-an-array-of-integers-is-even-or-odd/amp/?ref=rp
[ "# Check if the XOR of an array of integers is Even or Odd\n\nGiven an array arr containing integers of size N, the task is to check if the XOR of this array is even or odd\n\nExamples:\n\nInput: arr[] = { 2, 4, 7}\nOutput: Odd\nExplanation:\nXOR of array = 2 ^ 4 ^ 7 = 1, which is odd\n\nInput: arr[] = { 3, 9, 12, 13, 15 }\nOutput: Even\n\n## Recommended: Please try your approach on {IDE} first, before moving on to the solution.\n\nNaive Solution: First find the XOR of the given array of integers, and then check if this XOR is even or odd.\n\nTime Complexity: O(N)\n\nEfficient Solution: A better Solution is based on bit manipulation fact, that:\n\n• Bitwise XOR of any two even or any two odd numbers is always even.\n• Bitwise XOR of an even and an odd number is always odd.\n\nTherefore if the count of odd numbers in the array is odd, then the final XOR will be odd and if it is even, then final XOR will be even.\n\nBelow is the implementation of the above approach:\n\n `// C++ program to check if the XOR ` `// of an array is Even or Odd ` ` `  `#include ` `using` `namespace` `std; ` ` `  `// Function to check if the XOR of ` `// an array of integers is Even or Odd ` `string check(``int` `arr[], ``int` `n) ` `{ ` `    ``int` `count = 0; ` ` `  `    ``for` `(``int` `i = 0; i < n; i++) { ` ` `  `        ``// Count the number ` `        ``// of odd elements ` `        ``if` `(arr[i] & 1) ` `            ``count++; ` `    ``} ` ` `  `    ``// If count of odd elements ` `    ``// is odd, then XOR will be odd ` `    ``if` `(count & 1) ` `        ``return` `\"Odd\"``; ` ` `  `    ``// Else even ` `    ``else` `        ``return` `\"Even\"``; ` `} ` ` `  `// Driver Code ` `int` `main() ` `{ ` `    ``int` `arr[] = { 3, 9, 12, 13, 15 }; ` `    ``int` `n = ``sizeof``(arr) / ``sizeof``(arr); ` ` `  `    ``// Function call ` `    ``cout << check(arr, n) << endl; ` ` `  `    ``return` `0; ` `} `\n\n `// Java rogram to check if the XOR ` `// of an array is Even or Odd ` `import` `java.util.*; ` ` `  `class` `GFG{ ` ` `  `// Function to check if the XOR of ` `// an array of integers is Even or Odd ` `static` `String check(``int` `[]arr, ``int` `n) ` `{ ` `    ``int` `count = ``0``; ` ` `  `    ``for` `(``int` `i = ``0``; i < n; i++) { ` ` `  `        ``// Count the number ` `        ``// of odd elements ` `        ``if` `((arr[i] & ``1``)!=``0``) ` `            ``count++; ` `    ``} ` ` `  `    ``// If count of odd elements ` `    ``// is odd, then XOR will be odd ` `    ``if` `((count & ``1``)!=``0``) ` `        ``return` `\"Odd\"``; ` ` `  `    ``// Else even ` `    ``else` `        ``return` `\"Even\"``; ` `} ` ` `  `// Driver Code ` `public` `static` `void` `main(String args[]) ` `{ ` `    ``int` `[]arr = { ``3``, ``9``, ``12``, ``13``, ``15` `}; ` `    ``int` `n = arr.length; ` ` `  `    ``// Function call ` `    ``System.out.println(check(arr, n)); ` `} ` `} ` ` `  `// This code is contributed by Surendra_Gangwar `\n\n `# Python3 program to check if the XOR ` `# of an array is Even or Odd ` ` `  `# Function to check if the XOR of ` `# an array of integers is Even or Odd ` `def` `check(arr, n): ` `    ``count ``=` `0``; ` ` `  `    ``for` `i ``in` `range``(n): ` ` `  `        ``# Count the number ` `        ``# of odd elements ` `        ``if` `(arr[i] & ``1``): ` `            ``count ``=` `count ``+` `1``; ` `     `  `    ``# If count of odd elements ` `    ``# is odd, then XOR will be odd ` `    ``if` `(count & ``1``): ` `        ``return` `\"Odd\"``; ` ` `  `    ``# Else even ` `    ``else``: ` `        ``return` `\"Even\"``; ` ` `  `# Driver Code ` `if` `__name__``=``=``'__main__'``:  ` ` `  `    ``arr ``=` `[ ``3``, ``9``, ``12``, ``13``, ``15` `] ` `    ``n ``=` `len``(arr) ` ` `  `    ``# Function call ` `    ``print``(check(arr, n)) ` ` `  ` `  `# This code is contributed by Princi Singh `\n\n `// C# program to check if the XOR ` `// of an array is Even or Odd ` `using` `System; ` `using` `System.Collections.Generic; ` `using` `System.Linq; ` `  `  `class` `GFG  ` `{ ` ` `  `// Function to check if the XOR of ` `// an array of integers is Even or Odd ` `static` `String check(``int` `[]arr, ``int` `n) ` `{ ` `    ``int` `count = 0; ` ` `  `    ``for` `(``int` `i = 0; i < n; i++) { ` ` `  `        ``// Count the number ` `        ``// of odd elements ` `        ``if` `(arr[i] == 1) ` `            ``count++; ` `    ``} ` ` `  `    ``// If count of odd elements ` `    ``// is odd, then XOR will be odd ` `    ``if` `(count == 1) ` `        ``return` `\"Odd\"``; ` ` `  `    ``// Else even ` `    ``else` `        ``return` `\"Even\"``; ` `} ` ` `  `// Driver Code ` `    ``public` `static` `void` `Main(String[] args)  ` `    ``{ ` `    ``int` `[]arr= { 3, 9, 12, 13, 15 }; ` `    ``int` `n = arr.Length;  ` ` `  `    ``// Function call ` `    ``Console.Write(check(arr, n)); ` `} ` `} ` ` `  `// This code is contributed by shivanisinghss2110 `\n\nOutput:\n```Even\n```\n\nTime Complexity: O(N)\n\nAttention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready.\n\nArticle Tags :" ]
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https://www.peel520.net/what-is-estat-imtest-stata/
[ "# What is estat Imtest Stata?\n\n## What is estat Imtest Stata?\n\nThe estat imtest command runs the Cameron-Trivedi decomposition (which includes a test for heteroskedasticity). Additionally, estat imtest displays tests for skew and kurtosis. Useful for cases the heteroskedasticity might not be linear, it is less powerful in cases where simpler tests will work. …\n\n## How do you test for heteroskedasticity in Stata?\n\nFigure 5: Testing for Heteroscedasticity Using the Postestimation Selector Dialog Box in Stata. Click on “Tests for heteroskedasticity” and press Launch to produce a second dialog box, “estat – Postestimation statistics for regress.” In the box at the top,”Tests for heteroskedasticity (hettest)” should be highlighted.\n\nWhat is the difference between Breusch-Pagan and White test?\n\nWhite’s test is used to test for heteroscedastic (“differently dispersed”) errors in regression analysis. The only different between White’s test and the Breusch-Pagan is that its auxiliary regression doesn’t include cross-terms or the original squared variables. Other than that, the steps are exactly the same.\n\nHow do you interpret heteroskedasticity?\n\nFurther Analyzing Heteroskedasticity One of the most common ways of checking for heteroskedasticity is by plotting a graph of the residuals. Visually, if there appears to be a fan or cone shape in the residual plot, it indicates the presence of heteroskedasticity.\n\n### Do you want heteroskedasticity and homoscedasticity?\n\nThere are two big reasons why you want homoscedasticity: While heteroscedasticity does not cause bias in the coefficient estimates, it does make them less precise. This effect occurs because heteroscedasticity increases the variance of the coefficient estimates but the OLS procedure does not detect this increase.\n\n### Which test is best for heteroskedasticity?\n\nFirst, test whether the data fits to Gaussian (Normal) distribution. If YES, then Bartlett test is most powerful to detect heteroskedasticity. If there is MINOR DEVIATION (see the Q-Q plot from test for normality) from normality, then use Levene test for heteroskedasticity.\n\nWhat does the Ramsey Reset test do?\n\nIn statistics, the Ramsey Regression Equation Specification Error Test (RESET) test is a general specification test for the linear regression model. More specifically, it tests whether non-linear combinations of the fitted values help explain the response variable.\n\nWhat would a chi square significance value of P 0.05 suggest?\n\nWhat is a significant p value for chi squared? The likelihood chi-square statistic is 11.816 and the p-value = 0.019. Therefore, at a significance level of 0.05, you can conclude that the association between the variables is statistically significant." ]
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https://leanprover-community.github.io/mathlib4_docs/Mathlib/Order/Iterate.html
[ "# Documentation\n\nMathlib.Order.Iterate\n\n# Inequalities on iterates #\n\nIn this file we prove some inequalities comparing f^[n] x and g^[n] x where f and g are two self-maps that commute with each other.\n\nCurrent selection of inequalities is motivated by formalization of the rotation number of a circle homeomorphism.\n\n### Comparison of two sequences #\n\nIf $f$ is a monotone function, then $∀ k, x_{k+1} ≤ f(x_k)$ implies that $x_k$ grows slower than $f^k(x_0)$, and similarly for the reversed inequalities. If $x_k$ and $y_k$ are two sequences such that $x_{k+1} ≤ f(x_k)$ and $y_{k+1} ≥ f(y_k)$ for all $k < n$, then $x_0 ≤ y_0$ implies $x_n ≤ y_n$, see Monotone.seq_le_seq.\n\nIf some of the inequalities in this lemma are strict, then we have $x_n < y_n$. The rest of the lemmas in this section formalize this fact for different inequalities made strict.\n\ntheorem Monotone.seq_le_seq {α : Type u_1} [] {f : αα} {x : α} {y : α} (hf : ) (n : ) (h₀ : x 0 y 0) (hx : ∀ (k : ), k < nx (k + 1) f (x k)) (hy : ∀ (k : ), k < nf (y k) y (k + 1)) :\nx n y n\ntheorem Monotone.seq_pos_lt_seq_of_lt_of_le {α : Type u_1} [] {f : αα} {x : α} {y : α} (hf : ) {n : } (hn : 0 < n) (h₀ : x 0 y 0) (hx : ∀ (k : ), k < nx (k + 1) < f (x k)) (hy : ∀ (k : ), k < nf (y k) y (k + 1)) :\nx n < y n\ntheorem Monotone.seq_pos_lt_seq_of_le_of_lt {α : Type u_1} [] {f : αα} {x : α} {y : α} (hf : ) {n : } (hn : 0 < n) (h₀ : x 0 y 0) (hx : ∀ (k : ), k < nx (k + 1) f (x k)) (hy : ∀ (k : ), k < nf (y k) < y (k + 1)) :\nx n < y n\ntheorem Monotone.seq_lt_seq_of_lt_of_le {α : Type u_1} [] {f : αα} {x : α} {y : α} (hf : ) (n : ) (h₀ : x 0 < y 0) (hx : ∀ (k : ), k < nx (k + 1) < f (x k)) (hy : ∀ (k : ), k < nf (y k) y (k + 1)) :\nx n < y n\ntheorem Monotone.seq_lt_seq_of_le_of_lt {α : Type u_1} [] {f : αα} {x : α} {y : α} (hf : ) (n : ) (h₀ : x 0 < y 0) (hx : ∀ (k : ), k < nx (k + 1) f (x k)) (hy : ∀ (k : ), k < nf (y k) < y (k + 1)) :\nx n < y n\n\n### Iterates of two functions #\n\nIn this section we compare the iterates of a monotone function f : α → α to iterates of any function g : β → β. If h : β → α satisfies h ∘ g ≤ f ∘ h, then h (g^[n] x) grows slower than f^[n] (h x), and similarly for the reversed inequality.\n\nThen we specialize these two lemmas to the case β = α, h = id.\n\ntheorem Monotone.le_iterate_comp_of_le {α : Type u_1} {β : Type u_2} [] {f : αα} {g : ββ} {h : βα} (hf : ) (H : h g f h) (n : ) :\nh g^[n] f^[n] h\ntheorem Monotone.iterate_comp_le_of_le {α : Type u_1} {β : Type u_2} [] {f : αα} {g : ββ} {h : βα} (hf : ) (H : f h h g) (n : ) :\nf^[n] h h g^[n]\ntheorem Monotone.iterate_le_of_le {α : Type u_1} [] {f : αα} {g : αα} (hf : ) (h : f g) (n : ) :\nf^[n] g^[n]\n\nIf f ≤ g and f is monotone, then f^[n] ≤ g^[n].\n\ntheorem Monotone.le_iterate_of_le {α : Type u_1} [] {f : αα} {g : αα} (hg : ) (h : f g) (n : ) :\nf^[n] g^[n]\n\nIf f ≤ g and g is monotone, then f^[n] ≤ g^[n].\n\n### Comparison of iterations and the identity function #\n\nIf $f(x) ≤ x$ for all $x$ (we express this as f ≤ id in the code), then the same is true for any iterate of $f$, and similarly for the reversed inequality.\n\ntheorem Function.id_le_iterate_of_id_le {α : Type u_1} [] {f : αα} (h : id f) (n : ) :\nid f^[n]\n\nIf $x ≤ f x$ for all $x$ (we write this as id ≤ f), then the same is true for any iterate f^[n] of f.\n\ntheorem Function.iterate_le_id_of_le_id {α : Type u_1} [] {f : αα} (h : f id) (n : ) :\nf^[n] id\ntheorem Function.monotone_iterate_of_id_le {α : Type u_1} [] {f : αα} (h : id f) :\nMonotone fun m => f^[m]\ntheorem Function.antitone_iterate_of_le_id {α : Type u_1} [] {f : αα} (h : f id) :\nAntitone fun m => f^[m]\n\n### Iterates of commuting functions #\n\nIf f and g are monotone and commute, then f x ≤ g x implies f^[n] x ≤ g^[n] x, see Function.Commute.iterate_le_of_map_le. We also prove two strict inequality versions of this lemma, as well as iff versions.\n\ntheorem Function.Commute.iterate_le_of_map_le {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} (hx : f x g x) (n : ) :\nf^[n] x g^[n] x\ntheorem Function.Commute.iterate_pos_lt_of_map_lt {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} (hx : f x < g x) {n : } (hn : 0 < n) :\nf^[n] x < g^[n] x\ntheorem Function.Commute.iterate_pos_lt_of_map_lt' {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} (hx : f x < g x) {n : } (hn : 0 < n) :\nf^[n] x < g^[n] x\ntheorem Function.Commute.iterate_pos_lt_iff_map_lt {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} {n : } (hn : 0 < n) :\nf^[n] x < g^[n] x f x < g x\ntheorem Function.Commute.iterate_pos_lt_iff_map_lt' {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} {n : } (hn : 0 < n) :\nf^[n] x < g^[n] x f x < g x\ntheorem Function.Commute.iterate_pos_le_iff_map_le {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} {n : } (hn : 0 < n) :\nf^[n] x g^[n] x f x g x\ntheorem Function.Commute.iterate_pos_le_iff_map_le' {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} {n : } (hn : 0 < n) :\nf^[n] x g^[n] x f x g x\ntheorem Function.Commute.iterate_pos_eq_iff_map_eq {α : Type u_1} [] {f : αα} {g : αα} (h : ) (hf : ) (hg : ) {x : α} {n : } (hn : 0 < n) :\nf^[n] x = g^[n] x f x = g x\ntheorem Monotone.monotone_iterate_of_le_map {α : Type u_1} [] {f : αα} {x : α} (hf : ) (hx : x f x) :\nMonotone fun n => f^[n] x\n\nIf f is a monotone map and x ≤ f x at some point x, then the iterates f^[n] x form a monotone sequence.\n\ntheorem Monotone.antitone_iterate_of_map_le {α : Type u_1} [] {f : αα} {x : α} (hf : ) (hx : f x x) :\nAntitone fun n => f^[n] x\n\nIf f is a monotone map and f x ≤ x at some point x, then the iterates f^[n] x form an antitone sequence.\n\ntheorem StrictMono.strictMono_iterate_of_lt_map {α : Type u_1} [] {f : αα} {x : α} (hf : ) (hx : x < f x) :\nStrictMono fun n => f^[n] x\n\nIf f is a strictly monotone map and x < f x at some point x, then the iterates f^[n] x form a strictly monotone sequence.\n\ntheorem StrictMono.strictAnti_iterate_of_map_lt {α : Type u_1} [] {f : αα} {x : α} (hf : ) (hx : f x < x) :\nStrictAnti fun n => f^[n] x\n\nIf f is a strictly antitone map and f x < x at some point x, then the iterates f^[n] x form a strictly antitone sequence." ]
[ null ]
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https://wphealthnews.com/how-many-billions-are-in-a-sextillion/
[ "# How Many Billions Are In A Sextillion?\n\nSextillion is a number equal to a 1 followed by 21 zeros. 1,000,000,000,000,000,000,000 is an example of a sextillion. The number represented by 1 followed by 21 zeros.\n\n## What is Duotrigintillion?\n\nDuotrigintillion. A unit of quantity equal to 1099 (1 followed by 99 zeros).\n\n## What is 1×10 100 called?\n\nThe scientific notation for a googol is 1 x 10100.\n\n“Googol” got its name in 1938, when nine-year-old Milton Sirotta came up with the name and suggested it to his uncle, mathematician Edward Kasner.\n\n### Is Google bigger than infinity?\n\nIt’s way bigger than a measly googol! Googolplex may well designate the largest number named with a single word, but of course that doesn’t make it the biggest number. … True enough, but there is nothing as large as infinity either: infinity is not a number. It denotes endlessness.\n\n### Is Septillion or sextillion bigger?\n\nAfter a billion, of course, is trillion. Then comes quadrillion, quintrillion, sextillion, septillion, octillion, nonillion, and decillion.\n\n### Why is it called sextillion?\n\nFrom the prefix sext- (six) + -illion (from million); ie the sixth power of a million, 1036.\n\n### What is the biggest number?\n\nThe biggest number referred to regularly is a googolplex (10googol), which works out as 1010^100.\n\n### Is Jillion a real word?\n\nA jillion is an enormous number of something. … The word is modeled on actual numbers like million and billion, so it almost sounds like a real quantity. But like zillion, jillion is imprecise. Its origin is vague too, described as an “arbitrary coinage” first used around 1940.\n\n### Is gazillion bigger than bazillion?\n\nIf not then a zillion has to be at least larger than a googolplex. … A Bazillion can then have at least a zillion zeroes, and a Gazillion at least a bazillion zeroes.\n\n### What is a number with 36 zeros called?\n\nThe integer 1000000000000000000000000000000000000 (or 1036, a 1 followed by 36 zeros) is called a Undecillion.\n\n### What is the biggest number in the universe?\n\nGoogol. It is a large number, unimaginably large. It is easy to write in exponential format: 10100, an extremely compact method, to easily represent the largest numbers (and also the smallest numbers)." ]
[ null ]
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https://jharkhand.pscnotes.com/mathematics-and-stastics/contribution-of-aryabhatta-in-mathematics-2/
[ "# Contribution Of Aryabhatta In Mathematics\n\n?\n\nContribution of aryabhatta in mathematics\n\nNumber notation\n\nNumerical values\n\nHe made a notation system in which digits are denoted with the help of alphabet numerals e.g., 1 = ka, 2 = Kha, etc.\n\nAryabhatta assigned numerical values to the 33 consonants of the Indian alphabet to represent 1,2,3…25,30,40,50,60,70,80,90,100.\n\nNotation system", null, "He invented a notation system consisting of alphabet numerals Digits were denoted by alphabet numerals. In this system devanagiri script contain varga letters (consonants) and avarga letters (vowels).1-25 are denoted by 1st 25 varga letters.\n\nPlace-value: Aryabhatta was familiar with the place-value system.\n\nSquare root & cube root\n\nHis calculations on square root and cube root would not have been possible without the knowledge of place values system and zero. He has given methods of extracting square root cube root along with their explanation.\n\nAlgebra\n\nInteger solutions: Aryabhatta was the first one to explore integer solutions to the equations of the form by =ax+c and by =ax-c, where a,b,c are integers. He used kuttuka method to solve problems.\n\nIndeterminate equations: He gave general solutions to linear indeterminate equations ax+by+c= 0 by the method of continued fraction.\n\nIdentities: He had dealt with identities like (a+b)2=a2+2ab+b2 and ab={(a+b)2-(a2-b2)}/2\n\nAlgebraic quantities: He has given the method of addition, subtraction, multiplication of simple and compound algebraic quantities.\n\nGeometry\n\nDiscover the P  Value\n\nThe credit for discovering the exact values P may be ascribed to the celebrated mathematician Aryabhatta.\n\nRule: Add 4 to 100, multiply by 8, add 62000. The result is approximately the circumference of a circle of diameter twenty thousand. By this rule the relation of the circumference to diameter is given.\n\nTrigonometry\n\nSine Table: Aryabhatta gave a table of sines for calculating the approximate values at intervals of 90/24 = 3 45’. This was done using the formula for sin (n+1)x –  sin nx in terms of sin nx and sin (n-1) x.\n\nVersine: He introduced the versine (versin = 1-cosine) into trigonometry.\n\nAryabhatta was one of those ancient scholars of India who is hardly surpassed by any one else of his time in his treatise on mathematics and astronomy. In appreciation of his great contributions to mathematics and astronomy, the government of India named the first satellite sent into space on 19-4-1975 as aryabhatta, after him.\n\nContribution of Varaha mihira in mathematics\n\nVarahamihira (505 – 587) was an Indian astrologer whose main work was a treatise on mathematical astronomy which summarised earlier astronomical treatises. He discovered a version of Pascal’s triangle and worked on magic squares. He was aware of gravity over a millennium before Isaac Newton.\n\nVarahamihira worked as one of the Navaratnas for Chandragupta Vikramaditya. His book Pancasiddhantika (or Pancha-Siddhantika, The Five Astronomical Canons) dated 575 AD gives us information about older Indian texts which are now lost. The work is a treatise on mathematical astronomy and it summarises five earlier astronomical treatises, namely the Surya, Romaka, Paulisa, Vasistha and Paitamaha siddhantas.\n\nVarahamihira is said to have origins from Eastern Iran from a sect known as Maga Brahmins.(Quote: Ramesh Chitor). In more ways than one, the Surya Siddhanta or Treatise on Sun hints that Mihira was from Iran as Iran was the only South Asian country following the practice of SUN worship. Varaha was a name coined by Vikramaditya- king of Ujjain. Mihira(meaning “friend” in Persian)accurately predicted death of Vikramidtya’s son during the 18th year. The entire army, intelligence and the king could not save this fatal incident. This will remain as the greatest astrological prediction ever made by Mihira. VarahaMihira’s painting can be found in the Indian Parliament alongside Aryabhatta.\n\nSome important trigonometric results attributed to Varahamihira", null, "", null, "", null, "JPSC Notes brings Prelims and Mains programs for JPSC Prelims and JPSC Mains Exam preparation. Various Programs initiated by JPSC Notes are as follows:- For any doubt, Just leave us a Chat or Fill us a querry––\n\nJPSC Mains Test Series 2022\n\nSubscribe our Test Series program to get access to 20 Quality mock tests for JPSC Preparation." ]
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http://tabs.panahy.nl/Rythms.aspx
[ "## Rythms\n\nThese are some nice rithms to play with:\n\n## 4/4\n\nBasic rithm:\n``` G D\n|- - - - |- - - -|\nv v v v v v v v\n```\nThe \"v\" from now on denotes a downstroke and a \"^\" denotes an upstroke.\n```G D\n|- - - - |- - - - |\nv^v^v^v^ v^v^v^v^```\nIrani\n```|- - - - |- - - - |\nv ^s^v^v v^^s^v^v\ni Ps iii iPPs iii\n```\ns is mute with palm followed by side of the hand up wards." ]
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https://www.quizzes.cc/calculator/length/millimeters/64
[ "### How much is 64 millimeters?\n\nConvert 64 millimeters. How far is 64 millimeters? What is 64 millimeters in other units? Convert to cm, km, in, ft, meters, mm, yards, and miles. To calculate, enter your desired inputs, then click calculate. Some units are rounded since conversions between metric and imperial can be messy.\n\n### Summary\n\nConvert 64 millimeters to cm, km, in, ft, meters, mm, yards, and miles.\n\n#### 64 millimeters to Other Units\n\n 64 millimeters equals 6.4 centimeters 64 millimeters equals 0.2099737533 feet 64 millimeters equals 2.519685039 inches 64 millimeters equals 6.4E-5 kilometers\n 64 millimeters equals 0.064 meters 64 millimeters equals 3.97677563E-5 miles 64 millimeters equals 64 millimeters 64 millimeters equals 0.06999125109 yards" ]
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https://www.daniweb.com/programming/software-development/threads/383933/can-t-figure-it-out-why-not-printing-the-number-assembly-newby
[ "I have this assembly project (mips) but I think I have an overflow problem....\n\nThe problem is that the answer is ok until number 99 but at 100 it prints with a - infront of the number. The projects just ask me to calculate a sum (x+a)^2 (x= 1 to 100) and a= (1+2y) (y= 1 to x)\n\nResult: -2088573816\n\nI post the code:\n\n``````.data # data segment. We Define the Constants here\nintro: .asciiz \"\\n\\t\\t\\t\\tCalculate Sum-Test\\n\\n\"\nmsgIn: .asciiz \"\\nPlease give an integer between 1 - 100: \"\nerror: .asciiz \"\\nInvalid Number: Integer must be between 1-100\\n\\n\"\nthx: .asciiz \"\\n\\nThank you for using our program\"\nres: .asciiz \"\\nThe result is: \"\nmo: .asciiz \"\\nThe average is: \"\nrest: .asciiz \"\\nThe modulo is: \"\n\n######################################…\n.text # text segment\n.globl main\n\nmain:\n#constants\nli \\$t0, 100\nli \\$t1, 1\nli \\$t2, 2\n\n#counters\nli \\$t3, 1 #counter for the first loop\nli \\$t4, 1 #counter for the second/nested loop\n\n#sum\nli \\$s1, 0 #\\$s1 is the a value\nli \\$s2, 0 #\\$s2 holds the final result\n\n# Print on consule the intro message\nla \\$a0, intro # Message that indicates the title of the current program\nli \\$v0, 4 # System code for print string\nsyscall # Print String\nj loop1\n\nerror_msg:\n# Print on consule the error message\nla \\$a0, error # Message that indicates the error of the current program\nli \\$v0, 4 # System code for print string\nsyscall # Print String\n\nloop1:\n# Print on consule the instruction message\nla \\$a0, msgIn # Message that indicates the instructions of the current program\nli \\$v0, 4 # System code for print string\nsyscall # Print String\n\nli \\$v0, 5 # System code for reading an integer\nmove \\$s0,\\$v0 # Save integer in \\$s0\n\n# By this time the value should be in \\$s0 register\n\n######################################…\n# This is code that checks if the integer is between 1 - 100\n######################################…\n\n#Checks if integer>100\nbgt \\$s0, \\$t0, error_msg #pseudoinstruction, \\$s0>\\$t0 (user_int>100)\n\n#Checks if integer<1\nblt \\$s0, \\$t1, error_msg #pseudoinstruction, \\$s0<\\$t1 (user_int<1)\n\n######################################…\n# This is code generates the a value of the serie\n######################################…\n\n#This loop calculates the final result\nfor_loop_x:\n\n#Checks if first_loop_counter<user_value\nbgt \\$t3, \\$s0, loop_out #pseudoinstruction, \\$t3<\\$s0 (counter<user_int)\n\nfor_loop_a:\n\n#Checks if second_loop_counter<first_loop_counter\nbgt \\$t4, \\$t3, calculate #pseudoinstruction, \\$t4<\\$t3 (second_loop_counter<first_loop_…\n\n#Calculate the a value\nmulou \\$t5, \\$t2, \\$t4 #multiply \\$t5=\\$t2*\\$t4 (\\$t5= 2*second_loop_counter => 2*y)\naddu \\$s1, \\$s1, \\$s5 #add immitiade \\$s1=\\$s1+\\$s5 (\\$s1= \\$s1+\\$s5 => sum=prev_value+(1+2*y)) ==> This is the a value\naddiu \\$t4, \\$t4, 1 #increase counter by one (\\$t4=\\$t4+1)\nj for_loop_a #Check the condition again\n\ncalculate:\n\nmulou \\$t7, \\$t6, \\$t6 #calculate square root \\$t7=\\$t6*\\$t6 (((x+a)^2)\naddu \\$s2, \\$s2, \\$t7 #calculate the final sum \\$s2=\\$s2+\\$t7\n\naddiu \\$t3, \\$t3, 1 #increase counter by one (\\$t3=\\$t3+1)\n\nj for_loop_x #Check the condition again\n\nloop_out:\n\n# Print on consule the result message\nla \\$a0, res # Message that indicates the results of the current program\nli \\$v0, 4 # System code for print string\nsyscall # Print String\n\n#Printing results on consule\nmove \\$a0, \\$s2 #moves the final result to the argument 1\nli \\$v0, 1 #System code for printing an integer\nsyscall #Print Integer\n\nend:\n######################################…\n# Print on consule the \"thank you\" message\n\nla \\$a0, thx\nli \\$v0, 4\nsyscall\n\n#Exiting system\nli \\$v0, 10 # exit system call\nsyscall``````" ]
[ null ]
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https://allonlinetools.com/hourly-to-monthly-salary-calculator/
[ "# Convert Hourly To Monthly Salary Calculator\n\nThis online calculator can help you to calculate your monthly salary by calculating your per-hour salary. You can convert UK, Canada, Philippines, South Africa, Australia, and any other countries wage.\n\nHow to use this hourly to monthly wage calculator:\n\n• Input per hour salary\n• Input hours per day\n• Input days per week\n• Input holiday per year\n• Input vacation per year\n\n## Hourly To Monthly Salary Calculator\n\nPer Hour Salary\nHours per day\nDays per week\nHours per week\nHoliday per year\nVacation per year\nTotal Result Salary:\nHourly\nDaily\nWeekly\nBi-Weekly\nMonthly\nAnnual Total\n\n## How To Convert Hourly To Monthly Salary?\n\nYou can convert hourly to monthly salary if you follow the below rules, though it’s a complex task, but if you want, you can do it manually or use our free calculator and calculate it with just little steps.\n\nSuppose you have to work 8 hours per day and your hourly salary is \\$10, there is 52 week in a year, and you have to work 5 days in a week, 10 holiday per year, 15 vacations per year.\n\nSo, now if you convert hourly salary to monthly salary then you need to follow the formula:\n\n= Per hour salary x Hours per day x ( 52 x Days per week – (Holiday per year + Vacation per day)) ÷ 12\n\nExplanation: We used 52 for yearly 52 weeks and divided the whole calculation by 12 for a yearly 12 months.\n\nExample:\n\n= 10 x 8 x ( 52 x 5 – (10 + 15)) ÷ 12\n\n= 18800 ÷ 12\n\n= 1566.67\n\n### How To Calculate Hourly Salary To Weekly?\n\nYou can calculate hourly wage to weekly by the following formula:\n\nHourly Salary To Weekly wage= per hour salary x hours per day x days per week\n\nOR, if you want to calculate based on your yearly salary then follow the below formula:\n\n= Per hour salary x Hours per day x ( 52 x Days per week – (Holiday per year + Vacation per day)) ÷ 52\n\n52 for yearly 52 week\n\n### How To Calculate Hourly Salary To Annual?\n\nYou can calculate hourly to yearly salary following the above formula just avoiding the 52 weeks or 12 months divide.\n\nHourly to annual wage = Per hour salary x Hours per day x ( 52 x Days per week – (Holiday per year + Vacation per day))\n\nIf you’ve been using the above formula has the correct results\n\n## How To Calculate Monthly Salary in Excel?\n\nIf you want to calculate monthly exact salary in excel or spreadsheet then take these rows:\n\nScreenshot for better understand, how we calculate it.\n\n1. #### What is the average monthly salary in south Africa\n\nSouth Africa monthly average salary is R22,500.\n\n2. #### What is the average monthly salary in Canada?\n\n\\$2,600‬ per month average salary in Canada.\n\n3. #### What is the average monthly salary in the US?\n\n\\$7,900 per month average salary in US.\n\n4. #### What is the average monthly salary in Australia?\n\n\\$3,426 per month average salary in Australia.\n\n5. #### What is the average monthly salary in India?\n\n31,900 INR per month average salary in India.\n\n6. #### What is the average monthly salary in South Korea?\n\n3,890,000 KRW per month average salary in South Korea.\n\n7. #### What is the average monthly salary in the UK?\n\n£1,950 per month average salary in UK.\n\n8. #### What is the average monthly salary in Japan?\n\n515,000 JPY per month average salary in Japan.\n\n9. #### What is the average monthly salary in The Philipines?\n\n44,600 PHP per month average salary in Philippines.\n\n10. #### What is the average monthly salary in Nigeria?\n\nAround 339,000 NGN per month average salary in Nigeria." ]
[ null ]
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https://math.libretexts.org/Bookshelves/Algebra/Book%3A_Beginning_Algebra_(Redden)/05%3A_Polynomials_and_Their_Operations/5.06%3A_Negative_Exponents
[ "$$\\newcommand{\\id}{\\mathrm{id}}$$ $$\\newcommand{\\Span}{\\mathrm{span}}$$ $$\\newcommand{\\kernel}{\\mathrm{null}\\,}$$ $$\\newcommand{\\range}{\\mathrm{range}\\,}$$ $$\\newcommand{\\RealPart}{\\mathrm{Re}}$$ $$\\newcommand{\\ImaginaryPart}{\\mathrm{Im}}$$ $$\\newcommand{\\Argument}{\\mathrm{Arg}}$$ $$\\newcommand{\\norm}{\\| #1 \\|}$$ $$\\newcommand{\\inner}{\\langle #1, #2 \\rangle}$$ $$\\newcommand{\\Span}{\\mathrm{span}}$$\n\n# 5.6: Negative Exponents\n\n$$\\newcommand{\\vecs}{\\overset { \\rightharpoonup} {\\mathbf{#1}} }$$\n\n$$\\newcommand{\\vecd}{\\overset{-\\!-\\!\\rightharpoonup}{\\vphantom{a}\\smash {#1}}}$$\n\nLearning Objectives\n\n• Simplify expressions with negative integer exponents.\n• Work with scientific notation.\n\n## Negative Exponents\n\nIn this section, we define what it means to have negative integer exponents. We begin with the following equivalent fractions:\n\n$$\\frac{1}{8}=\\frac{4}{32}$$\n\nNotice that $$4, 8$$, and $$32$$ are all powers of $$2$$. Hence we can write $$4=2^{2}, 8=2^{3}, and 32=2^{5}$$.\n\n$$\\frac{1}{2^{3}}=\\frac{1}{8}=\\frac{4}{32}=\\frac{2^{2}}{2^{5}}$$\n\nIf the exponent of the term in the denominator is larger than the exponent of the term in the numerator, then the application of the quotient rule for exponents results in a negative exponent. In this case, we have the following:\n\n$$\\color{Cerulean}{\\frac{1}{2^{3}}}\\color{black}{=\\frac{1}{8}=\\frac{4}{32}=\\frac{2^{2}}{2^{5}}=2^{2-5}=}\\color{Cerulean}{2^{-3}}$$\n\nWe conclude that $$2^{−3}=\\frac{1}{2}^{3}$$. This is true in general and leads to the definition of negative exponents. Given any integer $$n$$ and $$x≠0$$, then\n\n$x^{-n}=\\frac{1}{x^{n}}$\n\nHere $$x≠0$$ because \\frac{1}{0}\\) is undefined. For clarity, in this section, assume all variables are nonzero.\n\nSimplifying expressions with negative exponents requires that we rewrite the expression with positive exponents.\n\nExample $$\\PageIndex{1}$$\n\nSimplify:\n\n$$10^{-2}$$.\n\nSolution:\n\n\\begin{aligned} 10^{-2}&=\\frac{1}{10^{2}} \\\\ &=\\frac{1}{100} \\end{aligned}\n\n$$\\frac{1}{100}$$\n\nExample $$\\PageIndex{2}$$\n\nSimplify:\n\n$$(-3)^{-1}$$.\n\nSolution:\n\n\\begin{aligned} (-3)^{-1}&=\\frac{1}{(-3)^{1}} \\\\ &=-\\frac{1}{3} \\end{aligned}\n\n$$-\\frac{1}{3}$$\n\nExample $$\\PageIndex{3}$$\n\nSimplify:\n\n$$\\frac{1}{y^{-3}}$$.\n\nSolution:\n\n\\begin{aligned} \\frac{1}{y^{-3}} &=\\frac{1}{\\frac{1}{y^{3}}} \\\\ &=1\\cdot \\frac{y^{3}}{1} \\\\ &=y^{3} \\end{aligned}\n\n$$y^{3}$$\n\nAt this point we highlight two very important examples,\n\nIf the grouped quantity is raised to a negative exponent, then apply the definition and write the entire grouped quantity in the denominator. If there is no grouping, then apply the definition only to the base preceding the exponent.\n\nExample $$\\PageIndex{4}$$\n\nSimplify:\n\n$$(2ab)^{-3}$$.\n\nSolution:\n\nFirst, apply the definition of −3 as an exponent and then apply the power of a product rule.\n\n\\begin{aligned} (2ab)^{-3} &=\\frac{1}{(2ab)^{3}} \\qquad\\color{Cerulean}{Apply\\:the\\:negative\\:exponent.} \\\\ &=\\frac{1}{2^{3}a^{3}b^{3}} \\qquad\\color{Cerulean}{Apply\\:the\\:power\\:rule\\:for\\:a\\:product.} \\\\ &=\\frac{1}{8a^{3}b^{3}} \\end{aligned}\n\n$$\\frac{1}{8a^{3}b^{3}}$$\n\nExample $$\\PageIndex{5}$$\n\nSimplify:\n\n$$(-3xy^{3})^{-2}$$.\n\nSolution:\n\n\\begin{aligned} (-3xy^{3})^{-2}&=\\frac{1}{(-3xy^{3})^{2}} \\\\&=\\frac{1}{(-3)^{2}x^{2}(y^{3})^{2}} \\\\ &=\\frac{1}{9x^{2}y^{6}} \\end{aligned}\n\n$$\\frac{1}{9x^{2}y^{6}}$$\n\nExample $$\\PageIndex{6}$$\n\nSimplify:\n\n$$\\frac{x^{-3}}{y^{-4}}$$.\n\nSolution:\n\n$$\\frac{x^{-3}}{y^{-4}}=\\frac{\\frac{1}{x^{3}}}{\\frac{1}{y^{4}}}=\\frac{1}{x^{3}}\\cdot\\frac{y^{4}}{1}=\\frac{y^{4}}{x^{3}}$$\n\n$$\\frac{y^{4}}{x^{3}}$$\n\nThe previous example suggests a property of quotients with negative exponents. If given any integers $$m$$ and $$n$$, where $$x≠0$$ and $$y≠0$$, then\n\n$\\frac{x^{-n}}{y^{-m}}=\\frac{y^{m}}{x^{n}}$\n\nIn other words, negative exponents in the numerator can be written as positive exponents in the denominator, and negative exponents in the denominator can be written as positive exponents in the numerator.\n\nExample $$\\PageIndex{7}$$\n\nSimplify:\n\n$$\\frac{-2x^{-5}y^{3}}{z^{-2}}$$.\n\nSolution:\n\nTake care with the coefficient $$−2$$; recognize that this is the base and that the exponent is actually $$+1:\\: −2=(−2)^{1}$$. Hence the rules of negative exponents do not apply to this coefficient; leave it in the numerator.\n\n\\begin{aligned} \\frac{-2x^{-5}y^{3}}{z^{-2}}&=\\frac{-2\\color{Cerulean}{x^{-5}}\\color{black}{y^{3}}}{\\color{OliveGreen}{z^{-2}}} \\\\ &=\\frac{-2y^{3}\\color{OliveGreen}{z^{2}}}{\\color{Cerulean}{x^{5}}} \\end{aligned}\n\n$$\\frac{-2y^{3}z^{2}}{x^{5}}$$\n\nExample $$\\PageIndex{8}$$\n\nSimplify:\n\n$$\\frac{(-3x^{-4})^{-3}}{y^{-2}}$$.\n\nSolution:\n\n\\begin{aligned} \\frac{(-3x^{-4})^{-3}}{y^{-2}}&=\\frac{(-3)^{-3}(x^{-4})^{-3}}{y^{-2}} &\\color{Cerulean}{Apply\\:the\\:product\\:to\\:a\\:power\\:rule.} \\\\ &=\\frac{(-3)^{-3}x^{12}}{y^{-2}} &\\color{Cerulean}{Power\\:rule} \\\\ &=\\frac{x^{12}y^{2}}{(-3)^{3}} &\\color{Cerulean}{Negative\\:exponents} \\\\ &=\\frac{x^{12}y^{2}}{-27} \\\\ &-\\frac{x^{12}y^{2}}{27} \\end{aligned}\n\n$$-\\frac{x^{12}y^{2}}{27}$$\n\nExample $$\\PageIndex{9}$$\n\nSimplify:\n\n$$\\frac{(3x^{2})^{-4}}{(-2y^{-1}z^{3})^{-2}}$$.\n\nSolution:\n\n\\begin{aligned} \\frac{(3x^{2})^{-4}}{(-2y^{-1}z^{3})^{-2}}&=\\frac{3^{-4}(x^{2})^{-4}}{(-2)^{-2}(y^{-1})^{-2}(z^{3})^{-2}} &\\color{Cerulean}{Product\\:to\\:a\\:power\\:rule} \\\\ &=\\frac{3^{-4}x^{-8}}{(-2)^{-2}y^{2}z^{-6}} &\\color{Cerulean}{Power\\:rule} \\\\ &=\\frac{(-2)^{2}z^{6}}{3^{4}x^{8}y^{2}} &\\color{Cerulean}{Negative\\:exponents} \\\\&=\\frac{4z^{6}}{81x^{8}y^{2}} \\end{aligned}\n\n$$\\frac{4z^{6}}{81x^{8}y^{2}}$$\n\nExample $$\\PageIndex{10}$$\n\nSimplify:\n\n$$\\frac{(5x^{2}y)^{3}}{x^{-5}y^{-3}}$$.\n\nSolution:\n\nFirst, apply the power of a product rule and then the quotient rule.\n\n$$\\frac{(5x^{2})^{3}}{x^{-5}y^{-3}} = \\frac{5^{3}x^{6}y^{3}}{x^{-5}y^{-3}}=5^{3}x^{6-(-5)}y^{3-(-3)}=5^{3}x^{6+5}y^{3+3}=125x^{11}y^{6}$$\n\n$$125x^{11}y^{6}$$\n\nTo summarize, we have the following rules for negative integer exponents with nonzero bases:\n\nNegative exponents: $$x^{-n}=\\frac{1}{x^{n}}$$ $$\\frac{x^{-n}}{y^{-m}}=\\frac{y^{m}}{x^{n}}$$\n\nTable 5.6.1\n\nExercise $$\\PageIndex{1}$$\n\nSimplify:\n\n$$\\frac{(-5xy^{-3})^{-2}}{5x^{4}y^{-4}}$$.\n\n$$\\frac{y^{10}}{125x^{6}}$$\n\n## Scientific Notation\n\nReal numbers expressed in scientific notation have the form\n\n$$a\\times 10^{n}$$\n\nwhere $$n$$ is an integer and $$1≤a<10$$. This form is particularly useful when the numbers are very large or very small. For example,\n\n$$\\begin{array}{cc}{9,460,000,000,000,000m=9.46\\times 10^{15}m}&{\\color{Cerulean}{One\\:light\\:year}}\\\\{0.000000000025m=2.5\\times 10^{-11}m}&{\\color{Cerulean}{Radius\\:of\\:a\\:hydrogen\\:atom}} \\end{array}$$\n\nIt is cumbersome to write all the zeros in both of these cases. Scientific notation is an alternative, compact representation of these numbers. The factor $$10^{n}$$ indicates the power of $$10$$ to multiply the coefficient by to convert back to decimal form:\n\nThis is equivalent to moving the decimal in the coefficient fifteen places to the right. A negative exponent indicates that the number is very small:\n\nThis is equivalent to moving the decimal in the coefficient eleven places to the left.\n\nConverting a decimal number to scientific notation involves moving the decimal as well. Consider all of the equivalent forms of $$0.00563$$ with factors of $$10$$ that follow:\n\n\\begin{aligned} 0.00563&=0.0563\\times 10^{-1} \\\\ &=0.563\\times 10^{-2} \\\\&\\color{Cerulean}{=5.63\\times 10^{-3}} \\\\&=56.3\\times 10^{-4} \\\\&=563\\times 10^{-5} \\end{aligned}\n\nWhile all of these are equal, $$5.63×10^{−3}$$ is the only form considered to be expressed in scientific notation. This is because the coefficient $$5.63$$ is between $$1$$ and $$10$$ as required by the definition. Notice that we can convert $$5.63×10^{−3}$$ back to decimal form, as a check, by moving the decimal to the left three places.\n\nExample $$\\PageIndex{11}$$\n\nWrite $$1,075,000,000,000$$ using scientific notation.\n\nSolution:\n\nHere we count twelve decimal places to the left of the decimal point to obtain the number $$1.075$$.\n\n$$1,075,000,000,000=1.075\\times 10^{12}$$\n\n$$1.075\\times 10^{12}$$\n\nExample $$\\PageIndex{12}$$\n\nWrite $$0.000003045$$ using scientific notation.\n\nSolution:\n\nHere we count six decimal places to the right to obtain $$3.045$$.\n\n$$0.000003045=3.045\\times 10^{-6}$$\n\n$$3.045\\times 10^{-6}$$\n\nOften we will need to perform operations when using numbers in scientific notation. All the rules of exponents developed so far also apply to numbers in scientific notation.\n\nExample $$\\PageIndex{13}$$\n\nMultiply:\n\n$$(4.36×10^{−5})(5.3×10^{12})$$.\n\nSolution:\n\nUse the fact that multiplication is commutative and apply the product rule for exponents.\n\n\\begin{aligned} (4.36×10^{−5})(5.3×10^{12})&=(4.36\\cdot 5.30)\\times (10^{-5}\\cdot 10^{12}) \\\\&=\\color{Cerulean}{23.108}\\color{black}{\\times 10^{-5+12}} \\\\&=\\color{Cerulean}{2.3108\\times 10^{1}}\\color{black}{\\times 10^{7}} \\\\&=2.3108\\times 10^{1+7} \\\\ &=2.3108\\times 10^{8} \\end{aligned}\n\n$$2.3108\\times 10^{8}$$\n\nExample $$\\PageIndex{14}$$\n\nDivide:\n\n$$(3.24\\times 10^{8})\\div (9.0\\times 10^{-3})$$.\n\nSolution:\n\n\\begin{aligned} \\frac{(3.24\\times 10^{8})}{(9.0\\times 10^{-3})}&= \\left( \\frac{3.24}{9.0} \\right) \\times \\left( \\frac{10^{8}}{10^{-3}} \\right) \\\\ &=0.36\\times 10^{8-(-3)} \\\\&=\\color{Cerulean}{0.36}\\color{black}{\\times 10^{8+3}} \\\\&=\\color{Cerulean}{3.6\\times 10^{-1}}\\color{black}{\\times 10^{11}} \\\\&=3.6\\times 10^{-1+11} \\\\ &=3.6\\times 10^{10} \\end{aligned}\n\n$$3.6\\times 10^{10}$$\n\nExample $$\\PageIndex{15}$$\n\nThe speed of light is approximately $$6.7×10^{8}$$ miles per hour. Express this speed in miles per second.\n\nSolution:\n\nA unit analysis indicates that we must divide the number by $$3,600$$.\n\n\\begin{aligned} 6.7\\times 10^{8} \\:mph &=\\frac{6.7\\times 10^{8}miles}{1\\cancel{\\color{red}{hour}}}\\color{black}{\\cdot}\\left( \\frac{1\\cancel{\\color{red}{hour}}}{60\\cancel{\\color{OliveGreen}{minutes}}} \\right)\\cdot \\left( \\frac{1\\cancel{\\color{OliveGreen}{minutes}}}{60 seconds} \\right) \\\\&=\\frac{6.7\\times 10^{8}miles}{3600 seconds} \\\\&=\\left(\\frac{6.7}{3600} \\right)\\times 10^{8} \\\\ &\\approx\\color{Cerulean}{0.0019}\\color{black}{\\times 10^{8}} \\qquad\\color{Cerulean}{Rounded\\:to\\:two\\:significant\\:digits} \\\\ &=\\color{Cerulean}{1.9\\times 10^{-3}}\\color{black}{\\times 10^{8}} \\\\ &=1.9\\times 10^{-3+8} \\\\ &=1.9\\times 10^{5} \\end{aligned}\n\nThe speed of light is approximately $$1.9×10^{5}$$ miles per second.\n\nExample $$\\PageIndex{16}$$\n\nBy what factor is the radius of the sun larger than the radius of earth?\n\n\\begin{aligned} 6,300,000m &=6.3\\times 10^{6}m\\qquad\\color{Cerulean}{Radius\\:of\\:Earth} \\\\ 700,000,000m &=7.0\\times 10^{8}m\\qquad\\color{Cerulean}{Radius\\:of\\:the\\:Sun} \\end{aligned}\n\nSolution:\n\nWe want to find the number that when multiplied times the radius of earth equals the radius of the sun.\n\n\\begin{aligned}n\\cdot \\color{Cerulean}{radius\\:of\\:the\\:Earth}&=\\color{OliveGreen}{radius\\:of\\:the\\:Sun} \\\\n&=\\frac{\\color{OliveGreen}{radius\\:of\\:the\\:Sun}}{\\color{Cerulean}{radius\\:of\\:the\\:Earth}} \\end{aligned}\n\nTherefore,\n\n\\begin{aligned} n&=\\frac{7.0\\times 10^{8}m}{6.3\\times 10^{6}m} \\\\ &=\\frac{7.0}{6.3}\\times\\frac{10^{8}}{10^{6}} \\\\ &\\approx 1.1\\times 10^{8-6} \\\\ &=1.1\\times 10^{2} \\\\ &=110 \\end{aligned}\n\nExercise $$\\PageIndex{2}$$\n\nDivide:\n\n$$(6.75\\times 10^{-8})\\div (9\\times 10^{-17})$$.\n\n$$7.5\\times 10^{8}$$\n\n## Key Takeaways\n\n• Expressions with negative exponents in the numerator can be rewritten as expressions with positive exponents in the denominator.\n• Expressions with negative exponents in the denominator can be rewritten as expressions with positive exponents in the numerator.\n• Take care to distinguish negative coefficients from negative exponents.\n• Scientific notation is particularly useful when working with numbers that are very large or very small.\n\nExercise $$\\PageIndex{3}$$ Negative Exponents\n\nSimplify. (Assume variables are nonzero.)\n\n1. $$5^{−1}$$\n2. $$5^{−2}$$\n3. $$(−7)^{−1}$$\n4. $$−7^{−1}$$\n5. $$\\frac{1}{2}^{−3}$$\n6. $$\\frac{5}{3}^{−2}$$\n7. $$(\\frac{3}{5})^{−2}$$\n8. $$(\\frac{1}{2})^{−5}$$\n9. $$(−\\frac{2}{3})^{−4}$$\n10. $$(−\\frac{1}{3})^{−3}$$\n11. $$x^{−4}$$\n12. $$y^{−1}$$\n13. $$3x^{−5}$$\n14. $$(3x)^{−5}$$\n15. $$\\frac{1}{y^{−3}}$$\n16. $$\\frac{5}{2}x^{−1}$$\n17. $$\\frac{x^{−1}}{y^{−2}}$$\n18. $$\\frac{1}{(x−y)^{−4}}$$\n19. $$\\frac{x^{2}y^{−3}}{z^{−5}}$$\n20. $$\\frac{x}{y^{−3}}$$\n21. $$(ab)^{−1}$$\n22. $$\\frac{1}{(ab)^{−1}}$$\n23. $$−5x^{−3}y^{2}z^{−4}$$\n24. $$\\frac{3}{−2x^{3}y^{−5}z}$$\n25. $$3x^{-4}y^{2}\\cdot 2x^{-1}y^{3}$$\n26. $$−10a^{2}b^{3}⋅2a^{−8}b^{−10}$$\n27. $$(2a^{−3})^{−2}$$\n28. $$(−3x^{2})^{−1}$$\n29. $$(5a^{2}b^{−3}c)^{−2}$$\n30. $$(7r^{3}s^{−5}t)^{−3}$$\n31. $$(−2r^{2}s^{0}t^{−3})^{−1}$$\n32. $$(2xy^{−3}z^{2})^{−3}$$\n33. $$(−5a^{2}b^{−3}c^{0})^{4}$$\n34. $$(−x^{−2}y^{3}z^{−4})^{−7}$$\n35. $$(\\frac{1}{2}x^{−3})^{−5}$$\n36. $$(2xy^{2})^{−2}$$\n37. $$(x^{2}y^{−1})^{−4}$$\n38. $$(−3a^{2}bc^{5})^{−5}$$\n39. $$(\\frac{20x^{−3}y^{2}}{5yz^{−1}})^{−1}$$\n40. $$(\\frac{4r^{5}s^{−3}t^{4}}{2r^{3}st^{0}})^{−3}$$\n41. $$(\\frac{2xy^{3}z^{−1}}{y^{2}z^{3}})^{−3}$$\n42. $$(−\\frac{3a^{2}bc}{ab^{0}c^{4}})^{2}$$\n43. $$(\\frac{−xyz}{x^{4}y^{−2}z^{3}})^{−4}$$\n44. $$(−\\frac{125x^{−3}y^{4}z^{−5}}{5x^{2}y^{4}(x+y)^{3}})^{0}$$\n45. $$(x^{n})^{−2}$$\n46. $$(x^{n}y^{n})^{−2}$$\n\n1. $$\\frac{1}{5}$$\n\n3. $$−\\frac{1}{7}$$\n\n5. $$8$$\n\n7. $$\\frac{25}{9}$$\n\n9. $$\\frac{81}{16}$$\n\n11. $$\\frac{1}{x^{4}}$$\n\n13. $$3x^{5}$$\n\n15. $$y^{3}$$\n\n17. $$\\frac{y^{2}}{x}$$\n\n19. $$\\frac{x^{2}z^{5}}{y^{3}}$$\n\n21. $$\\frac{1}{ab}$$\n\n23. $$\\frac{−5y^{2}}{x^{3}z^{4}}$$\n\n25. $$\\frac{6y^{5}}{x^{5}}$$\n\n27. $$\\frac{a^{6}}{4}$$\n\n29. $$\\frac{b^{6}}{25a^{4}c^{2}}$$\n\n31. $$−\\frac{t^{3}}{2r^{2}}$$\n\n33. $$\\frac{625a^{8}}{b^{12}}$$\n\n35. $$32x^{15}$$\n\n37. $$\\frac{y^{4}}{x^{8}}$$\n\n39. $$\\frac{x^{3}}{4yz}$$\n\n41. $$\\frac{z^{12}}{8x^{3}y^{3}}$$\n\n43. $$\\frac{x^{12}z^{8}}{y^{12}}$$\n\n45. $$\\frac{1}{x^{2n}}$$\n\nExercise $$\\PageIndex{4}$$ Negative Exponents\n\nThe value in dollars of a new MP3 player can be estimated by using the formula $$V=100(t+1)^{−1}$$, where $$t$$ is the number of years after purchase.\n\n1. How much was the MP3 player worth new?\n2. How much will the MP3 player be worth in $$1$$ year?\n3. How much will the MP3 player be worth in $$4$$ years?\n4. How much will the MP3 player be worth in $$9$$ years?\n5. How much will the MP3 player be worth in $$99$$ years?\n6. According to the formula, will the MP3 ever be worthless? Explain.\n\n1. $$$100$$ 3.$$$20$$\n\n5. \\$$$1$$\n\nExercise $$\\PageIndex{5}$$ Scientific Notation\n\nConvert to a decimal number.\n\n1. $$9.3×10^{9}$$\n2. $$1.004×10^{4}$$\n3. $$6.08×10^{10}$$\n4. $$3.042×10^{7}$$\n5. $$4.01×10^{−7}$$\n6. $$1.0×10^{−10}$$\n7. $$9.9×10^{−3}$$\n8. $$7.0011×10^{−5}$$\n\n1. $$9,300,000,000$$\n\n3. $$60,800,000,000$$\n\n5. $$0.000000401$$\n\n7. $$0.0099$$\n\nExercise $$\\PageIndex{6}$$ Scientific Notation\n\nRewrite using scientific notation.\n\n1. $$500,000,000$$\n2. $$407,300,000,000,000$$\n3. $$9,740,000$$\n4. $$100,230$$\n5. $$0.0000123$$\n6. $$0.000012$$\n7. $$0.000000010034$$\n8. $$0.99071$$\n\n1. $$5×10^{8}$$\n\n3. $$9.74×10^{6}$$\n\n5. $$1.23×10^{−5}$$\n\n7. $$1.0034×10^{−8}$$\n\nExercise $$\\PageIndex{7}$$ Scientific Notation\n\nPerform the indicated operations.\n\n1. $$(3×10^{5})(9×10^{4})$$\n2. $$(8×10^{−22})(2×10^{−12})$$\n3. $$(2.1×10^{−19})(3.0×10^{8})$$\n4. $$(4.32×10^{7})(1.50×10^{−18})$$\n5. $$9.12×10^{−9}3.2×10^{10}$$\n6. $$1.15×10^{9}2.3×10^{−11}$$\n7. $$1.004×10^{−8}2.008×10^{−14}$$\n8. $$3.276×10^{25}5.2×10^{15}$$\n9. $$59,000,000,000,000 × 0.000032$$\n10. $$0.0000000000432 × 0.0000000000673$$\n11. $$1,030,000,000,000,000,000 ÷ 2,000,000$$\n12. $$6,045,000,000,000,000 ÷ 0.00000005$$\n13. The population density of earth refers to the number of people per square mile of land area. If the total land area on earth is $$5.751×10^{7}$$ square miles and the population in 2007 was estimated to be $$6.67×10^{9}$$ people, then calculate the population density of earth at that time.\n14. In 2008 the population of New York City was estimated to be $$8.364$$ million people. The total land area is $$305$$ square miles. Calculate the population density of New York City.\n15. The mass of earth is $$5.97×10^{24}$$ kilograms and the mass of the moon is $$7.35×10^{22}$$ kilograms. By what factor is the mass of earth greater than the mass of the moon?\n16. The mass of the sun is $$1.99×10^{30}$$ kilograms and the mass of earth is $$5.97×10^{24}$$ kilograms. By what factor is the mass of the sun greater than the mass of earth? Express your answer in scientific notation.\n17. The radius of the sun is $$4.322×10^{5}$$ miles and the average distance from earth to the moon is $$2.392×10^{5}$$ miles. By what factor is the radius of the sun larger than the average distance from earth to the moon?\n18. One light year, $$9.461×10^{15}$$ meters, is the distance that light travels in a vacuum in one year. If the distance to the nearest star to our sun, Proxima Centauri, is estimated to be $$3.991×10^{16}$$ meters, then calculate the number of years it would take light to travel that distance.\n19. It is estimated that there are about $$1$$ million ants per person on the planet. If the world population was estimated to be $$6.67$$ billion people in 2007, then estimate the world ant population at that time.\n20. The sun moves around the center of the galaxy in a nearly circular orbit. The distance from the center of our galaxy to the sun is approximately $$26,000$$ light years. What is the circumference of the orbit of the sun around the galaxy in meters?\n21. Water weighs approximately $$18$$ grams per mole. If one mole is about $$6×10^{23}$$ molecules, then approximate the weight of each molecule of water.\n22. A gigabyte is $$1×10^{9}$$ bytes and a megabyte is $$1×10^{6}$$ bytes. If the average song in the MP3 format consumes about $$4.5$$ megabytes of storage, then how many songs will fit on a $$4$$-gigabyte memory card?\n\n1. $$2.7×10^{10}$$\n\n3. $$6.3×10^{−11}$$\n\n5. $$2.85×10^{−19}$$\n\n7. $$5×10^{5}$$\n\n9. $$1.888×10^{9}$$\n\n11. $$5.15×10^{11}$$\n\n13. About $$116$$ people per square mile\n\n15. $$81.2$$\n\n17. $$1.807$$\n\n19. $$6.67×10^{15}$$ ants\n\n21. $$3×10^{−23}$$ grams" ]
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{"ft_lang_label":"__label__en","ft_lang_prob":0.60039645,"math_prob":1.0000088,"size":17485,"snap":"2019-51-2020-05","text_gpt3_token_len":6733,"char_repetition_ratio":0.16846862,"word_repetition_ratio":0.071541294,"special_character_ratio":0.48430082,"punctuation_ratio":0.12947427,"nsfw_num_words":2,"has_unicode_error":false,"math_prob_llama3":1.0000056,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-12-08T19:33:34Z\",\"WARC-Record-ID\":\"<urn:uuid:0235f11c-32d6-4c69-a802-78408457d642>\",\"Content-Length\":\"102992\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e8c874ee-eebf-4131-89d5-2b0baed529c3>\",\"WARC-Concurrent-To\":\"<urn:uuid:1430f081-1b08-4600-aff3-27f5f68350cf>\",\"WARC-IP-Address\":\"34.232.212.106\",\"WARC-Target-URI\":\"https://math.libretexts.org/Bookshelves/Algebra/Book%3A_Beginning_Algebra_(Redden)/05%3A_Polynomials_and_Their_Operations/5.06%3A_Negative_Exponents\",\"WARC-Payload-Digest\":\"sha1:DUF3HGJ7VYSETYADHY4P6TGJQZPEM7M3\",\"WARC-Block-Digest\":\"sha1:TQFFLT22PWAV3VWI6UA3NNCBXW2LGVH4\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-51/CC-MAIN-2019-51_segments_1575540514475.44_warc_CC-MAIN-20191208174645-20191208202645-00362.warc.gz\"}"}
https://avidemia.com/pure-mathematics/curves-in-a-plane/
[ "We have hitherto used the notation $\\begin{equation*} y = f(x) \\tag{1}\\end{equation*}$ to express functional dependence of $$y$$ upon $$x$$. It is evident that this notation is most appropriate in the case in which $$y$$ is expressed explicitly in terms of $$x$$ by means of a formula, as when for example $y = x^{2},\\quad \\sin x,\\quad a\\cos^{2}x + b\\sin^{2}x.$\n\nWe have however very often to deal with functional relations which it is impossible or inconvenient to express in this form. If, for example, $$y^{5} – y – x = 0$$ or $$x^{5} + y^{5} – ay = 0$$, it is known to be impossible to express $$y$$ explicitly as an algebraical function of $$x$$. If $x^{2} + y^{2} + 2Gx + 2Fy+ C = 0,$ $$y$$ can indeed be so expressed, viz. by the formula $y = -F + \\sqrt{F^{2} – x^{2} – 2Gx – C};$ but the functional dependence of $$y$$ upon $$x$$ is better and more simply expressed by the original equation.\n\nIt will be observed that in these two cases the functional relation is fully expressed by equating a function of the two variables $$x$$ and $$y$$ to zero,  by means of an equation $\\begin{equation*} f(x, y) = 0. \\tag{2}\\end{equation*}$\n\nWe shall adopt this equation as the standard method of expressing the functional relation. It includes the equation  as a special case, since $$y – f(x)$$ is a special form of a function of $$x$$ and $$y$$. We can then speak of the locus of the point $$(x, y)$$ subject to $$f(x, y) = 0$$, the graph of the function $$y$$ defined by $$f(x, y) = 0$$, the curve or locus $$f(x, y) = 0$$, and the equation of this curve or locus.\n\nThere is another method of representing curves which is often useful. Suppose that $$x$$ and $$y$$ are both functions of a third variable $$t$$, which is to be regarded as essentially auxiliary and devoid of any particular geometrical significance. We may write $\\begin{equation*} x = f(t),\\quad y = F(t). \\tag {3}\\end{equation*}$ If a particular value is assigned to $$t$$, the corresponding values of $$x$$ and of $$y$$ are known. Each pair of such values defines a point $$(x, y)$$. If we construct all the points which correspond in this way to different values of $$t$$, we obtain the graph of the locus defined by the equations . Suppose for example $x = a\\cos t,\\quad y = a\\sin t.$ Let $$t$$ vary from $$0$$ to $$2\\pi$$. Then it is easy to see that the point $$(x, y)$$ describes the circle whose centre is the origin and whose radius is $$a$$. If $$t$$ varies beyond these limits, $$(x, y)$$ describes the circle over and over again. We can in this case at once obtain a direct relation between $$x$$ and $$y$$ by squaring and adding: we find that $$x^{2} + y^{2} = a^{2}$$, $$t$$ being now eliminated.\n\nExamples XVIII\n\n1. The points of intersection of the two curves whose equations are $$f(x, y) = 0$$, $$\\phi(x, y) = 0$$, where $$f$$ and $$\\phi$$ are polynomials, can be determined if these equations can be solved as a pair of simultaneous equations in $$x$$ and $$y$$. The solution generally consists of a finite number of pairs of values of $$x$$ and $$y$$. The two equations therefore generally represent a finite number of isolated points.\n\n2. Trace the curves $$(x + y)^{2} = 1$$, $$xy = 1$$, $$x^{2} – y^{2} = 1$$.\n\n3. The curve $$f(x, y) + \\lambda\\phi(x, y) = 0$$ represents a curve passing through the points of intersection of $$f = 0$$ and $$\\phi = 0$$.\n\n4. What loci are represented by $(\\alpha) x = at + b,\\quad y = ct + d,\\qquad (\\beta) x/a = 2t/(1 + t^{2}),\\quad y/a = (1 – t^{2})/(1 + t^{2}),$ when $$t$$ varies through all real values?" ]
[ null ]
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https://www.exceltip.com/excel-functions/how-to-use-the-aggregate-function-in-excel.html
[ "# How to Use Excel AGGREGATE Function\n\nThe Excel AGGREGATE function of excel is an advanced version of Excel SUBTOTAL function. The AGGREGATE function was introduced in Excel 2010. It used to do simple operations on data set, like SUM, AVERAGE, MAX, etc same as SUBTOTAL.", null, "Then why use AGGREGATE function? The reason is, while the SUBTOTAL function consists of only 11 operations AGGREGATE handles 19 operations with more control. With control, I mean that you can control which values to be calculated in range or database. We will see how soon in this article.\nSyntax of AGGREGATE Function\n\n=AGGREGATE(function num, options, array,[k])    (Array Form)\n=AGGREGATE(function num, options, ref1, ref2...) (Reference Form)\n\nThere are two forms of AGGREGATE Function in excel. Array Form and Reference Form. When we want to supply data as a range (eg A1:A3), we use array form. When we need to supply different references (eg, A1, B3, C11 etc) than we use Reference Form.\nFunction Num: From number 1 to 19, each number is associated with some operation. We provide the number of the function we want to use on range or database. Here is the list.\n\n Function Num Function Name 1 AVERAGE 2 COUNT 3 COUNTA 4 MAX 5 MIN 6 PRODUCT 7 STDEV.S 8 STDEV.P 9 SUM 10 VAR.S 11 VAR.P 12 MEDIAN 13 MODE.SNGL 14 LARGE 15 SMALL 16 PERCENTILE.INC 17 QUARTILE.INC 18 PERCENTILE.EXC 19 QUARTILE.EXC\n\nOptions: The control I was talking about, this options is that control. It enables you to choose, how you want to calculate. What you want to consider while calculating and what not. The list of available options is as below.\n\n Num Options 0 Ignore nested SUBTOTAL and AGGREGATE functions 1 Ignore nested SUBTOTAL, AGGREGATE functions, and hidden rows 2 Ignore nested SUBTOTAL, AGGREGATE functions, and error values 3 Ignore nested SUBTOTAL, AGGREGATE functions, hidden rows & error values 4 Ignore nothing 5 Ignore hidden rows 6 Ignore error values 7 Ignore hidden rows and error values\n\nArray or Ref: This the range on which you want to perform operations. It can be a database, single-cell or series of unlinked cells.\n\n[k]: It is an optional argument. It is must be used with the functions that require a key. Like SMALL, LARGE,  etc.\nLet’s see an example to make things clear.\n\n### Example: Sum visible range, ignore errors using AGGREGATE function\n\nHere I have a small set of numbers that I want to sum. Now the condition is, I want to sum values that are visible only. I want to ignore any errors, SUBTOTAL and AGGREGATE formulas in-between range.", null, "Write this formula in cell B8.\n\n=AGGREGATE(9,3,B2:B7)\n\nAbove AGGREGATE formula will return the correct answer as we expect.", null, "If you use the SUBTOTAL function, it will handle the hidden rows but it will fail to handle errors.\n\nYou can also get nth SMALLEST or nth LARGEST value too using AGGREGATE formula in excel.\n\n=AGGREGATE(14,3,B2:B7,2)\n\nThe above formula will return the second largest value in range B2:B7. Which is 40 here.\n\n=AGGREGATE(4,3,B7,B3)\n\nThe above AGGREGATE formula is reference type and used to get max value between B7 and B3.\n\nNotes:\n\n• If a function does not require a key [k], and, AGGREGATE will return a #VALUE error.\n• If a function requires a key [k], and you don’t provided it, AGGREGATE will return a #VALUE error.\n\nRelated Articles:\n\nHow to Use SUBTOTAL Function in Excel\n\nHow to use the Excel LOG10 function\n\nHow to use the IMEXP Function in Excel\n\nHow to use the IMCONJUGATE Function in Excel\n\nHow to use the IMARGUMENT Function in Excel\n\nPopular Articles\n\nEdit a dropdown list\n\nIf with conditional formatting\n\nIf with wildcards\n\nVlookup by date\n\nTerms and Conditions of use\n\nThe applications/code on this site are distributed as is and without warranties or liability. In no event shall the owner of the copyrights, or the authors of the applications/code be liable for any loss of profit, any problems or any damage resulting from the use or evaluation of the applications/code." ]
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http://rudmet.ru/journal/1858/article/31627/
[ "Journals →  Chernye Metally →  2019 →  #10 →  Back\n\n Heating and heat treatmwnt ArticleName The linear heat conduction problem for bodies with a regular shape under boundary conditions of the third kind ArticleAuthor I. A. Levitskiy ArticleAuthorData National University of Science and Technology “MISiS” (Moscow, Russia): Levitskiy I. A., Cand. Eng., Assocoate Prof., Dept. “Power-efficient and resourcesaving industrial technologies”, e-mail: [email protected] Abstract The solution of the linear one-dimensional heat conduction problem for bodies with a regular shape — plate, cylinder, and ball — has been described. An algorithm was proposed and programmatically implemented in the VBA MS Office Excel 2003 environment for solving direct and inverse one-dimensional heat conduction problems. An algorithm for solving the direct and inverse heat conduction problems for a cylinder of finite height and a parallelepiped of finite dimensions (as applied to any point of these bodies specifi ed by the user) was also developed and software implemented. keywords One-dimensional and multidimensional linear heat conduction problems, nomograms for heating a body, superposition principle, direct and inverse problems References 1. Lykov А. V. Heat conduction theory. Moscow: Vysshaya shkola, 1967. 600 p.2. Arutyunov V. А., Bukhmirov V. V., Krupennikov S. А. Mathematical modeling of the thermal performance of industrial furnaces. Moscow: Metallurgiya, 1990. 239 p.3. Vlasova Е. А., Zarubin V. S., Kuvyrkin G. N. Mathematical models of heat conduction processes: tutorial. Moscow: Izdatelstvo MGTU imeni N. E. Baumana, 2016. 124 p.4. Karpovich D. S., Susha О. N., Korovkina N. P., Kobrinets V. P. Analytical and numerical methods for solving the heat equation. Trudy BGTU. 2015. No. 6. pp. 122–127.5. Kudinov V. А., Kudinov I. V. Methods for solving parabolic and hyperbolic heat equations. Moscow: Knizhny dom «Librokom», 2012. 280 p.6. Egorov V. I. Exact methods for solving heat conduction problems: tutorial. Saint-Peterburg: SPbGU ITMO, 2006. 48 p.7. Arutyunov V. А., Krupennikov S. А., Levitsky I. А. Application of numerical methods for solving heat transfer problems. Laboratory practice. Moscow: MISiS, 2001. 75 p.8. John H. Mathews. Computer Derivations of Numerical Differentiation Formulae (Classroom Notes). International Journal of Mathematics Education in Science and Technology. 2003. Vol. 34(2). pp. 280–287.9. Jiin-Yuh, Jang Jun-Bo Huang. Optimization of a slab heating pattern for minimum energy consumption in a walking-beam type reheating furnace. Applied Thermal Engineering. 2015. Vol. 85. pp. 313–321.10. Singh V. K., Talukdar P. Comparisons of different heat transfer models of a walking beam type reheat furnace. International Communications in Heat and Mass Transfer. 2013. Vol. 47. pp. 20–26.11. Guangwu Tang, BinWu, Yufeng Wang et al. CFD modeling and validation of a dynamic slab heating process in an industrial walking beam reheating furnace. Applied Thermal Engineering. 2018. Vol. 132. pp. 779–789.12. Guangwu Tang, BinWu, Dengqi Bai et al. Modeling of the slab heating process in a walking beam reheating furnace for process optimization. International Journal of Heat and Mass Transfer. 2017. Vol. 113. pp. 1142–1151.13. Jiin-Yuh, Jang Jun-Bo Huang. Optimization of a slab heating pattern for minimum energy consumption in a walking-beam type reheating furnace. Applied Thermal Engineering. 2015. Vol. 85. pp. 313–321.14. Sang Heon Han, Daejun Chang, Chang Young Kim. A numerical analysis of slab heating characteristics in a walking beam type reheating furnace. International Journal of Heat and Mass Transfer. 2010. Vol. 53. Iss. 19–20. pp. 3855–3861.15. Mayr B., Prieler R., Demuth M. et al. CFD analysis of a pusher type reheating furnace and the billet heating characteristic. Applied Thermal Engineering. 2017. Vol. 115(25). pp. 986–994.16. Landfahrer M., Schluck C. Numerical and experimental investigation of scale formation on steel tubes in a real-size reheating furnace. International Journal of Heat and Mass Transfer. 2019. Vol. 129. pp. 460–467.17. Tang L., Liu J., Rong A., Yang Z. An effective heuristic algorithm to minimise stack shuffles in selecting steel slabs from the slab yard for heating and rolling. Journal of the Operational Research Society. 2001. Vol. 52(10). pp. 1091–1097.18. Kurnosov V. V., Levitskii I. A., Pribytkov I. A. Heating of massive blanks at different rates in periodic furnaces. Steel in Translation. 2012. Vol. 42(9). pp. 682–686.19. Kurnosov V. V., Levitskii I. A. Heating of blanks in accordance with a specified graph. Steel in Translation. 2012. Vol. 42(7). pp. 569–571.20. Dorokhina O. G., Karvetskii A. A., Arutyunov V. A. et al. Simulation of the gas dynamics and heat transfer in a high-precision furnace. Steel in translation. 2012. Vol. 42(3). pp. 230–232.21. Lange E. Innovative technological models for optimization of flat rolling. Chernye Metally. 2017. No. 9. pp. 42–45.22. Reifferscheid М. Ideas, techniques and decisions for application of digital technologies in ferrous metallurgy. Chernye Metally. 2018. No. 6. pp. 62–67. Language of full-text russian Full content Buy\nBack" ]
[ null ]
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https://math.stackexchange.com/questions/1744929/the-exponent-of-11-in-the-prime-factorization-of-300-is
[ "# The exponent of $11$ in the prime factorization of $300!$ is___.\n\nThe exponent of $11$ in the prime factorization of $300!$ is\n\n1. $27$\n2. $28$\n3. $29$\n4. $30$\n\nMy attempt:\n\n$\\left\\lfloor\\dfrac{300}{11}\\right\\rfloor+\\left\\lfloor\\dfrac{300}{11^2}\\right\\rfloor=27+2=29$\n\nCan you explain in alternative/formal way? Please.\n\n• Do you mean to imply that the given method is not formal? – Hagen von Eitzen Apr 16 '16 at 12:35\n• @Hagen Thanks. No, I'm agree with given explanation, but I'm looking to understand in other way, if there. – 1 0 Apr 16 '16 at 12:41\n\nSee the terms having factor $11$ are $11,22,33,..121,...220,..297$ so excluding $121,242$ we have $25$ numbers which give only one $11$ and $121,242$ gives two $11$ so total exponent is $11^{25}.11^4=11^{29}$\n• Yes, $121=11\\times 11$ and $242=11\\times 11\\times 2$ will be include in exactly two times $11$, but other $25$ number included $11$ exactly once. – 1 0 Apr 16 '16 at 12:56\n• The general formula for the largest exponent of the prime $p$ in $n!$ is $\\sum_{j=1}^{\\infty}[np^{-j}]$, where $[x]$ denotes the largest integer not exceeding $x$. Note that only finitely many terms in the summation are non-zero. We can replace the supscript \"$j=\\infty$\" with \"$j=n$\". – DanielWainfleet Apr 16 '16 at 14:32" ]
[ null ]
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https://math.stackexchange.com/questions/2287867/how-to-think-about-theories-that-prove-their-own-inconsistency
[ "# How to think about theories that prove their own inconsistency?\n\nThere are consistent first-order theories that prove their own inconsistency. For example, construct one like this:\n\nAssuming their is a consistent and sufficiently expressive first-order theory at all, call it $T'$. The incompleteness theorem gives us that $\\mathrm{Con}(T')$ (the consistency of $T'$) is not provable in $T'$. Hence $T=T'+\\neg\\mathrm{Con}(T')$ is consistent. Since $T$ proves that we can derive a contradiction from $T'$ alone, it also proves that we can derive it from $T$ (because $T'\\subset T$). So $T$ is consistent but proves $\\neg\\mathrm{Con}(T)$.\n\nHow to think about such a strange theory? Obviously the theory $T$ is lying about itself. But what does this lying mean mathematically? Are the formulas and deductive rules interpretet in the language of $T$ different from the one in my meta theory? Can I trust $T$'s ability to express logic, deduction and arithmetic at all?\n\nNote that a theory $T$ as above is just an example to demonstrate that such strange theories might exist. It might be hard to argue about the usefulness of a theory with such a complicated and highly dubious axiom as $\\neg\\mathrm{Con}(T')$. But not all such self-falsifying theories must be so obvious and artificial. For example, it could be that ZFC can prove $\\neg\\mathrm{Con(ZFC)}$ while still being consistent. But how can we trust in a theory that fails to mirror our logic even when we try to implement it carefully. How can we be sure that all other theorems on logic derived in ZFC are trustworthy despite ZFC proves at least one wrong statement (wrong in the sense that our meta logic gives us a different result than the internal proof logic of ZFC).\n\n• If ZFC proves $\\lnot Con(ZFC)$ then ZFC is inconsistent, since we have completeness in first order logic. What the above means is that there exists a model of ZFC such that the model satisfies $\\lnot Con(ZFC)$. The idea is that in that model there might exist non-standard numbers. These \"numbers\" code a \"proof\" of the inconsistency. – Apostolos May 19 '17 at 14:47\n• @Apostolos Isn't the completeness theorem formalized in ZFC itself? So a proof of inconsistency via the completeness theorem will just prove $\\neg\\mathrm{Con}(ZFC)$ as I stated is possible while still being consistent? I think this is also not special to ZFC but whatever the completeness theorem is formalized in. – M. Winter May 19 '17 at 15:19\n• Completeness \"says\" that what you prove is true. This means that if ZFC could prove the inconsistency of ZFC then the inconsistency of ZFC is true. Therefore if ZFC proved its own inconsistency it would be inconsistent. What Godel's second incompleteness implies is that there exists models of ZFC where the formula \"ZFC is inconsistent\" holds, which is much weaker than saying that that ZFC proves $\\lnot Con(ZFC)$ which would imply that in all models of ZFC the formula holds. – Apostolos May 19 '17 at 15:24\n• @Apostolos I know this. But this does not adress my comment. At leats I cannot see how. How is the completeness theorem proven? It cannot be proven from thin air. It must be proven inside some first-order theory. – M. Winter May 19 '17 at 15:44\n• @Apostolos Your first comment is false, at least without additional assumptions. It's perfectly possible that ZFC could prove $\\neg Con(ZFC)$ without being inconsistent. To rule this out we need some extra assumption on ZFC, such as $\\omega$-consistency. – Noah Schweber May 19 '17 at 17:17\n\nIf I understand correctly you problem the key to solve it is to think carefully to the concept of encoding.\n\nFor simplicity allow me to consider the case where $T'$ is PA (Peano Arithmetic).\n\nThe internalization of the syntactic properties of PA in itself uses an encoding which is roughly a mapping that associates to formulas and proofs constant terms (their encodings) and to meta-theoretical properties (\"$x$ is a proof of $y$ in PA\", \"$x$ is provable in PA\", etc) formulas in the language of $T$ in such a way the following holds:\n\nif $RS$ is a syntactic (meta-theoretic) property and $O_1,\\dots,O_n$ are syntactic objects (formulas or proofs) then $RS(O_1,\\dots,O_n)$ holds if and only if $PA \\vdash Enc(RS)(Enc(O_1),\\dots,Enc(O_n))$, where $Enc$ is the mapping that associates to syntactic objects their encodings in $PA$'s language.\n\nThe important thing to keep in mind is that this encoding-condition is required to hold only for encodings.\n\nNow let consider a theory $T=PA+\\neg Enc(Con(PA))$ in the language of arithmetic.\n\nClearly $T \\vdash \\neg Enc(Con(PA))$ but what does this mean? By soundness and completeness this is equivalent to say that in every arithmetic structure $M$ which is a model of $T$ it must hold $M \\models \\neg Enc(Con(PA))$. We have that $$Enc(Con(PA))\\equiv \\neg \\exists x\\ Enc(\\text{*is a proof*})(x,Enc(\\bot))$$ hence $$\\neg Enc(Con(PA)) \\equiv \\exists x\\ Enc(\\text{* is a proof *})(x,Enc(\\bot))$$ so in each model $M$ of $T$ there is an element $m \\in M$ such that $$M \\models Enc(\\text{* is a proof *})(m,Enc(\\bot))$$ the problem is that this $m$ is not an encoding, it is not even required to be the interpretation of a constant term, hence there is no way that we could decode this term to a proof (in PA) of $\\bot$.\n\nThe point is that the formula $Enc(\\text{* is proof of*})$ define a relation for each arithmetic structure but it has its intended meaning only when applied to encodings: meaning that $Enc(\\text{*is a proof of*})(m,n)$ expresses that $m$ is the encoding of a proof of the formula encoded by $n$ only when $m$ and $n$ are encoding.\n\nThe argument shown here should be easy to adapt to other kind of theories such as the ones you described.\n\nI hope this helps.\n\n• Very interesting! Is the following conclusion correct? If we assume that PA is consistent and our encoding (of proofs) is sound and surjective on the standard numbers, then we could be sure that $\\neg\\mathrm{Con(PA)}$ can not be provable. This is because then at least the standard model can have no element $x$ which is not an encoding of a proof. And because of soundness no $x$ can encode a proof of inconsistency. – M. Winter May 21 '17 at 15:41\n• @M.Winter I would say that you are actually proving that $PA$ cannot prove $Enc(\\neg Con(PA))$, which is even stronger than saying that $\\neg Con(PA)$ cannot be proven (that would follow just by the requirement that $Con(PA)$ holds). – Giorgio Mossa May 21 '17 at 20:20\n• Yes of course ;) That's what I want to say. – M. Winter May 21 '17 at 21:39\n\nWhen we think about theories like ZFC or PA, we often view them foundationally: in particular, we often suppose that they are true. Truth is very strong. Although it's difficult to say exactly what it means for ZFC to be \"true\" (on the face of it we have to commit to the actual existence of a universe of sets!), some consequences of being true are easy to figure out: true things are consistent, and - since their consistency is true - don't prove that they are inconsistent.\n\nHowever, this makes things like PA + $\\neg$Con(PA) seem mysterious. So how are we to understand these?\n\nThe key is to remember that - assuming we work in some appropriate meta-theory - a theory is to be thought of as its class of models. A theory is consistent iff it has a model. So when we say PA + $\\neg$Con(PA) is consistent, what we mean is that there are ordered semirings (= models of PA without induction) with some very strong properties.\n\nOne of these strong properties is the induction scheme, which can be rephrased model-theoretically as saying that these ordered semirings have no definable proper cuts.\n\nIt's very useful down the road to get a good feel for nonstandard models of PA as structures in their own right as oppposed to \"incorrect\" interpretations of the theory; Kaye's book is a very good source here.\n\nThe other is that they satisfy $\\neg$Con(PA). This one seems mysterious since we think of $\\neg$Con(PA) as asserting a fact on the meta-level. However, remember that the whole point of Goedel's incompleteness theorem in this context is that we can write down a sentence in the language of arithmetic which we externally prove is true iff PA is inconsistent. Post-Goedel, the MRDP theorem showed that we may take this sentence to be of the form \"$\\mathcal{E}$ has a solution\" where $\\mathcal{E}$ is a specific Diophantine equation. So $\\neg$Con(PA) just means that a certain algebraic behavior occurs.\n\nSo models of PA+$\\neg$Con(PA) are just ordered semirings with some interesting properties - they have no proper definable cuts, and they have solutions to some Diophantine equations which don't have solutions in $\\mathbb{N}$. This demystifies them a lot!\n\nSo now let's return to the meaning of the arithmetic sentence we call \"$\\neg$Con(PA).\" In the metatheory, we have some object we call \"$\\mathbb{N}$\" and we prove:\n\nIf $T$ is a recursively axiomatizable theory, then $T$ is consistent iff $\\mathbb{N}\\models$ \"$\\mathcal{E}_T$ has no solutions.\"\n\n(Here $\\mathcal{E}_T$ is the analogue of $\\mathcal{E}$ for $T$; remember that by the MRDP theorem, we're expressing \"$\\neg$Con(T)\" as \"$\\mathcal{E}_T$ has no solutions\" for simplicity.) Note that this claim is specific to $\\mathbb{N}$: other ordered semirings, even nice ones!, need not work in place of $\\mathbb{N}$. In particular, there will be lots of ordered semirings which our metatheory proves satisfy PA, but for which the claim analogous to the one above fails.\n\nIt's worth thinking of an analogous situation in non-foundationally-flavored mathematics. Take a topological space $T$, and let $\\pi_1(T)$ and $H_1(T)$ be the fundamental group and the first homology group (with coefficients in $\\mathbb{Z}$, say) respectively. Don't pay attention too much to what these are, the point is just that they're both groups coding the behavior of $T$ which are closely related in many ways. I'm thinking of $\\pi_1(T)$ as the analogue of $\\mathbb{N}$ and $H_1(T)$ as the analogue of a nonstandard model satisfying $\\neg$Con(PA), respectively.\n\nNow, the statement \"$\\pi_1(T)$ is abelian\" (here, my analogue of $\\neg$Con(PA)) tells us a lot about $T$ (take my word for us). But the statement \"$H_1(T)$ is abelian\" does not tell us the same things (actually it tells us nothing: $H_1(T)$ is always abelian :P).\n\nWe have a group $G$, and some other group $H$ similar to $G$ in lots of ways, and a property $p$; and if $G$ has $p$, we learn something, but if $H$ has $p$ we don't learn that thing. This is exactly what's going on here. It's not the property by itself that carries any meaning, it's the statement that the property holds of a specific object that carries meaning useful to us. We often conflate these two, since there's a clear notion of \"truth\" for arithmetic sentences, but thinking about it in these terms should demystify theories like PA+$\\neg$Con(PA) a bit.\n\n• Also a very interesting point of view. Thank you for this answer! – M. Winter May 22 '17 at 8:25" ]
[ null ]
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http://www.numbersaplenty.com/11205032
[ "Search a number\nBaseRepresentation\nbin101010101111…\n…100110101000\n3210002021102012\n4222233212220\n510332030112\n61040055052\n7164145506\noct52574650\n923067365\n1011205032\n116363563\n123904488\n1324241c7\n1416b9676\n15eb5022\nhexaaf9a8\n\n11205032 has 16 divisors (see below), whose sum is σ = 21137760. Its totient is φ = 5568304.\n\nThe previous prime is 11205031. The next prime is 11205059. The reversal of 11205032 is 23050211.\n\nAdding to 11205032 its reverse (23050211), we get a palindrome (34255243).\n\nIt is a happy number.\n\nIt is a junction number, because it is equal to n+sod(n) for n = 11204998 and 11205016.\n\nIt is not an unprimeable number, because it can be changed into a prime (11205031) by changing a digit.\n\nIt is a pernicious number, because its binary representation contains a prime number (13) of ones.\n\nIt is a polite number, since it can be written in 3 ways as a sum of consecutive naturals, for example, 2858 + ... + 5529.\n\nIt is an arithmetic number, because the mean of its divisors is an integer number (1321110).\n\nAlmost surely, 211205032 is an apocalyptic number.\n\nIt is an amenable number.\n\n11205032 is a deficient number, since it is larger than the sum of its proper divisors (9932728).\n\n11205032 is a wasteful number, since it uses less digits than its factorization.\n\n11205032 is an odious number, because the sum of its binary digits is odd.\n\nThe sum of its prime factors is 8560 (or 8556 counting only the distinct ones).\n\nThe product of its (nonzero) digits is 60, while the sum is 14.\n\nThe square root of 11205032 is about 3347.3918205074. The cubic root of 11205032 is about 223.7712907968.\n\nThe spelling of 11205032 in words is \"eleven million, two hundred five thousand, thirty-two\"." ]
[ null ]
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https://benchpartner.com/type-of-productivity-in-operation-management/
[ "# Types of Productivity in Operation Management\n\nBasically, there are following three types of productivity in Operation Management or types of productivity measurements. 3 Types of Productivity are Total Productivity, Partial Productivity and Factor Productivity available in operation management.\n\n## Types of Productivity in Operation Management\n\n1. Partial productivity\n2. Total factor productivity\n3. Total productivity\n\n### 1. Partial Productivity\n\nPartial productivity is the ratio of output to partial input. It measures the productivity of each input.\n\nIt determines the contribution of each factor in producing and generating output. It can be measured as follows.\n\nPP = O/PI\n\nWhere,\n\nPP = Partial Productivity\n\nO = Total Output\n\nPI = Partial Input\n\nDifferent partial inputs can be Labor, Capital, Energy, Machinery and materials, etc.\n\nSome examples of partial productivity measurements are given below:\n\nLabor Productivity = Total Output / Labor Input\n\nCapital Productivity = Total Output / Captial Input\n\nMaterial Productivity = Total Output / Total raw material used\n\nEnergy Productivity = Total Output / Total energy used\n\nMachinery Productivity = Total Output / Total machine hour used\n\nThe partial productivity is easy to understand compute and can be highlighted to management.\n\nThese partial productivity data are available with a similar organization in the industry.\n\nIt makes easy to compare. It is thus a good diagnostic tool to pin point areas for productivity improvements.\n\nHowever, partial productivity is misleading if done or used alone. It doesn’t explain the overall cost. So, increasing productivity via focusing on the new single area may not give a good result.\n\nExample if an organization wants to increase labor productivity, simultaneously energy and material productivity have to be increased because these are associated with each other.\n\n### 2. Total Factor Productivity\n\nThis is the ratio between total output on the one hand and labor and capital on the other hand. It can be expressed as:\n\nTFP = O/L+C\n\nWhere,\n\nTFP = Total factor productivity\n\nO = Total Output\n\nL = Labor\n\nC = Capital\n\nTotal factor productivity has the benefit of easy calculation and more useful form economic view points.\n\n### 3. Total Productivity\n\nTotal productivity is the ratio of total output to the sum of all inputs.\n\nThus, total productivity measures reflect the joint impact of all the inputs in producing and generating output.\n\nTP = O/I\n\nWhere,\n\nTP = Total Productivity\n\nO = Total Output\n\nI = Total Input\n\nThe total productivity considers all quantifiable factors and output.\n\nIt is more accurate to represent the real economic conditions. Control through total productivity measure is a tremendous benefit to top management.\n\nTotal productivity is easy to relate to total cost.\n\nHowever, the data computation for total productivity is very difficult.\n\nIt does not consider intangible factors of outputs and inputs like partial and productivity measure." ]
[ null ]
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http://mathhelpforum.com/discrete-math/280560-set-question-please-help.html
[ "Given sets A and B, so that |A|=m and |B|=n and |A∩B|=k, and p(S) the Power Set of S, what is the value of |p(A∪B)-(p(A) ∪ p(B)) |?\n\nhow do i solve it.\n\nWhat is in $p (A\\cup B)$ that is not in $p (A)\\cup p (B)$\n\nThat's gonna be $p(A\\Delta B)-p (A-B)-p (B-A)$ where $\\Delta$ is symmetric difference.\n\n$|A\\Delta B|=|A-B|+|B-A|=(m-k)+(n-k)$\n\nCan you finish from here?\n\nI've not checked my work, but I think the final answer is $2^{m+n-2k}-2^{m-k}-2^{n-k}$\n\nthis doesn't work, you have more options then you mentioned\n\nYou are right. Let's look at sets in $p (A\\cup B)$ and ones in $p (A)\\cup p (B)$\n\nSo, consider the intersection of $p (A)\\cap p (B)$. It is precisely $p (A\\cap B)$\n\nSo $|p (A\\cup B)-(p (A)\\cup p (B))|-|p (A\\cup B)|-|p (A)|-|p (B)|+|p (A\\cap B)|=2^{m+n}-2^m-2^n+2^k$ by Inclusion/Exclusion", null, "Originally Posted by eden", null, "Given sets A and B, so that |A|=m and |B|=n and |A∩B|=k, and p(S) the Power Set of S, what is the value of |p(A∪B)-(p(A) ∪ p(B)) |?\n\nhow do i solve it.", null, "Originally Posted by SlipEternal", null, "You are right. Let's look at sets in $p (A\\cup B)$ and ones in $p (A)\\cup p (B)$\nSo, consider the intersection of $p (A)\\cap p (B)$. It is precisely $p (A\\cap B)$\nSo $|p (A\\cup B)-(p (A)\\cup p (B))|-|p (A\\cup B)|-|p (A)|-|p (B)|+|p (A\\cap B)|=2^{m+n}-2^m-2^n+2^k$ by Inclusion/Exclusion\nLet $A=\\{a,b\\}~\\&~B=\\{b,c\\}$ thus $m=n=2~\\&~k=1$\n\n$\\mathcal{P}(A\\cup B)-[\\mathcal{P}(A)\\cup\\mathcal{P}(B)]=\\{\\{a,c\\},\\{a,b,c\\}\\}$\n\nIn this example $\\left|\\mathcal{P}(A\\cup B)-[\\mathcal{P}(A)\\cup\\mathcal{P}(B)]\\right|=2$\n\nDid I not understand the question?", null, "Originally Posted by Plato", null, "Let $A=\\{a,b\\}~\\&~B=\\{b,c\\}$ thus $m=n=2~\\&~k=1$\n$\\mathcal{P}(A\\cup B)-[\\mathcal{P}(A)\\cup\\mathcal{P}(B)]=\\{\\{a,c\\},\\{a,b,c\\}\\}$\nIn this example $\\left|\\mathcal{P}(A\\cup B)-[\\mathcal{P}(A)\\cup\\mathcal{P}(B)]\\right|=2$\nSorry, $|p(A\\cup B)| = 2^{m+n-k}$. So, $|p(A\\cup B) - (p(A)\\cup P(B))| = 2^{m+n-k}-2^m-2^n+2^k$\nIn your case, we have $2^{2+2-1}-2^2-2^2+2^1 = 2$, just as you found. I just miswrote the formula. You understood the question." ]
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https://www.gradesaver.com/textbooks/math/algebra/college-algebra-10th-edition/chapter-r-section-r-7-rational-expressions-r-7-assess-your-understanding-page-71/56
[ "## College Algebra (10th Edition)\n\nLCM = $(x-4)^{2}(x+3)$\nStep 1: Factor each polynomial completely. For $x^{2}+bx+c$, we search for factors of c whose sum is b: $x^{2}-x-12...\\qquad$...-4 and +3 $=(x-4)(x+3)$ $x^{2}-8x+16=...\\qquad$...-4 and -4 $=(x-4)^{2}$ Step 2: The LCM is the product of each of these factors raised to a power equal to the greatest number of times that the factor occurs in the polynomials. LCM = $(x-4)^{2}(x+3)$" ]
[ null ]
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https://www.mathgoodies.com/lessons/decimals/add
[ "Example 1: Add: 52.3 + 973.41\n\nAnalysis: Let's use our knowledge of mixed numbers to help us analyze this problem.\n\n52.3 =", null, "and  973.41=", null, "Recall that a decimal number can have a whole-number part and a fractional part. When adding decimals, you must first line up all the decimal points in a column. Lining up the decimal points ensures that each digit is in the proper place-value position. Once each digit is in the proper place-value position, the whole-number parts are lined up with each other, and the fractional parts are lined up with each other. This is shown in the table below.\n\n PLACE VALUE AND DECIMALS", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "5 2 . 3 9 7 3 . 4 1 ----------- Whole-Number Part ----------- ---------- Fractional Part -----------\n\nNow that we have lined up the decimal points, you will notice that the numbers being added do not have the same number of decimal digits. Let's look at this problem on paper without a place-value chart.\n\n52.3\n\n+  973.41\n\nYou can write an extra zero to the right of the last digit of the first decimal so that both decimals have the same number of decimal digits.\n\n52.30\n\n+  973.41\n\nJust as with whole numbers, start on the right, and add each column in turn. Note that you are adding digits in the same place-value position.\n\n52.30\n\n+  973.41\n1025.71\n\nPlace the decimal point in the sum.\n\n52.30\n\n+  973.41\n1025.71\n\nAnswer: The sum of 52.3 and 973.41 is 1025.71.\n\nExample 2: Add: 0.078 + 3.09 + 0.6\n\n0.078\n\n3.090\n\n+  0.600\n\nAnalysis: If you need to carry (i.e. if a columns adds up to more than 9), remember to add the tens digit of that column to the next column.\n\n1\n\n0.078\n\n3.090\n\n+  0.600\n3.768\n\nAnswer: The sum of 0.078 and 3.09 and 0.6 is 3.768.", null, "Example 3: Add: \\$77.23 and \\$88\n\nAnalysis: Each of these numbers represents money; however, the second is written as a whole number. Change the second number so that it has two decimal digits, and then perform the addition.\n\n\\$  77.23\n\n+ \\$  88.00\n\\$165.23\n\nAnswer: The sum of \\$77.23 and \\$88 is \\$165.23.", null, "Procedure: To add decimals, follow these steps:\n\n1. Line up all the decimal points in a column.\n2. When needed, write one or more extra zeros to the right so that both decimals have the same number of decimal digits.\n3. Start on the right, and add each column in turn. (Add digits in the same place-value position.)\n4. If you need to carry, remember to add the tens digit of that column to the next column.\n5. Place the decimal point in the sum.\n\nExample 4: Add: 28.5 + 34.5\n\nAnalysis: You will need to carry more than once. Accordingly, the addition will be divided into three steps to show the process of carrying.\n\n 1                   1 1               1 1    28.5               28.5             28.5+ 34.5            + 34.5          + 34.5        .0", null, "3.0", null, "63.0\n\nAnswer: The sum of 28.5 and 34.5 is 63.\n\nExample 5: Add: 3.986 + 37 + 25.902\n\n 1                     1 1                   1 1      3.986                3.986             3.986    37.000               37.000           37.000+ 25.902            + 25.902         +25.902        .888", null, "6.888", null, "66.888\n\nAnswer: The sum of 28.5 and 34.5 is 66.888.\n\nExample 6: Add: \\$12.95 + \\$67.89 + \\$54.55\n\n 1                   2  1               1  2  1    \\$  12.95          \\$  12.95          \\$  12.95    \\$  67.89          \\$  67.89          \\$  67.89+ \\$  54.55       + \\$  54.55      +  \\$  54.55    .39", null, "\\$    5.39", null, "\\$135.39\n\nAnswer: The sum of \\$12.95 and \\$67.89 and \\$54.55 is \\$135.39.", null, "Example 7: A dime rolled 5.8794 cm and then rolled 7.48 cm. How far did it roll altogether?\n\n 1                     1  1                  1 1  1    5.8794               5.8794             5.8794+ 7.4800            + 7.4800          + 7.4800      .3594", null, "3.3594", null, "13.3594\n\nAnswer: The sum of 5.8794 cm and 7.48 cm is 13.3594 cm.\n\nSummary: When adding decimals, you must first line up all the decimal points in a column. Lining up the decimal points ensures that each digit is in the proper place-value position. You can then add digits in the same place-value position to find the sum.\n\n### Exercises\n\nDirections: Read each question below. You may use paper and pencil to help you add. Click once in an ANSWER BOX and type in your answer; then click ENTER. After you click ENTER, a message will appear in the RESULTS BOX to indicate whether your answer is correct or incorrect. To start over, click CLEAR." ]
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https://www.physicsforums.com/threads/need-help-with-something-very-odd.5669/
[ "# Need help with something very odd.\n\nOk, we are given the known equation that momentum = mass times velocity.\n\np=mv.\n\nWhat is dp/dr physically representing?\n\nGiven:\n\nr = position.\n\ndr/dt = v.\n\nso\n\np = mdr/dt.\n\ndp/dr = m/dt ? If so, that remains constant (or zero?) correct?\n\nRelated Other Physics Topics News on Phys.org\nHallsofIvy\nHomework Helper\nOkay, momentum equals mass times velocity.\n(That's basically the definition of momentum rather than a \"known equation\".)\n\np= mv.\n\nIF m is a constant then dp/dt= m dv/dt= m a (mass times acceleration).\n\nIf m is not a constant (a very important consideration) then\ndp/dt= m dv/dt+ dm/dt v.\n\ndp/dt is, of course, \"force\"- that's basically, the definition of force.\n\ndp/dr= (dp/dt)(dt/dr) (chain rule) or\n\ndp/dr= (dp/dt)/(dr/dt)= (1/v)*force\n\nAssuming constant mass, dp/dr= (m a)/v\n\nI don't know that that \"physically represents\" anything in particular. I'm pretty sure it doesn't have a specific name.\n\nAs far as \"dp/dr = m/dt\" is concerned, that makes no sense at all- you have an \"unattached\" dt on the right.\n\nThat's what I am all confused about. Whether it represents anything at all, or if it will be a constant. A better way to visualize this is to imagine the mass is in an orbit.\n\nStaff Emeritus\nGold Member\nDearly Missed\ndp/dt= m dv/dt+ dm/dt v.\n\nThis is the force law for a rocket. The force dp/dt has rwo components, current mass times acceleration (m dv/dt) and rate of change of mass times current speed (v dm/dt). This latter is due to the exhaust; dm/dt is the rate that reaction mass is being shot out the back. Note that the higher v is, the more that a given dm/dt contributes to the force on the rocket.\n\nYes, that much I knew. But this is the question:\n\np =mv.\n\ndp/dt =mdv/dt (m is constant in this case)\n\ndp = mdv\n\ndp/dr = mdv/dr\n\nNow, dv = dr/dt so we get 1/dt\n\ndp/dr = m/dt.\n\nI am just interested in this. The change in momentum with respect to distance, or mass with respect to time. In an orbit (notice this condition) would this quantity whatever it is, be constant, or zero?\n\nStaff Emeritus\nGold Member\nDearly Missed\nYou can't just divide out the dr's. derivatives like dr/dt aren't quotients exactly, they are the limits of quotients. It's allowable to multiply through, such as dr/dt = K, yields dr = Kdt ready for integration, but dividing out doesn't make sense.\n\nAlright then.\n\ndp = mdv\n\nWhat does\n\ndp/dr = mdv/dr represent?\n\nkrab\n\nYou said dv=dr/dt. That is quite wrong. v=dr/dt (as you said in a previous post). Therefore, dv=d(dr/dt)=d^2r/dt. So you are misunderstanding the math.\n\nYou are using v=dr/dt. This is only true for 1-dimensional motion, for example, a mass moving along a straight line. In that case, what Hallsofivy said is right. dp/dr=F/v; in words, dp/dr is the ratio of force applied, to the velocity attained. It's not zero and not constant. For example, if the force is pushing the mass in the direction opposite to its motion, the mass will slow down, stop, and reverse. At the point at which it has stopped, v=0 so dp/dr=F/v is infinite.\n\nIf you are thinking of something like a central force problem like planetary motion, and r is the distance between the masses, then the speed v is NOT dr/dt in general. The motion is 2-dimensional so you need another coordinate besides r to locate the mass. Usually use angle theta. Then the velocity has 2 components, dr/dt and\nr*d(theta)/dt, and v is the square root of the sum of the squares of these 2 components.\n\nGot it, thanks!\n\nas for the dv = dr/dt thing, that was a mistype on my part. I was getting a bit type happy with d's and other things. Sorry for the math error!" ]
[ null ]
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https://www.inflationtool.com/us-dollar/2015-to-present-value
[ "# Value of 2015 US Dollars today\n\n\\$100 in 2015\n\n\\$107.03 in 2019\n\nThe inflation rate in the United States between 2015 and today has been 7.03%, which translates into a total increase of \\$7.03. This means that 100 dollars in 2015 are equivalent to 107.03 dollars in 2019. In other words, the purchasing power of \\$100 in 2015 equals \\$107.03 today. The average annual inflation rate has been 1.37%.\n\n## Inflation timeline in the United States (2015-2019)\n\nThe following chart depicts the equivalence of \\$100 throughout the years due to inflation and CPI changes. All values are equivalent in terms of purchasing power, which means that for each year the same goods or services could be bought with the indicated amount of money.\n\nAll calculations are performed in the local currency (USD) and using 6 decimal digits. Results show only up to 2 decimal digits to favour readability. Inflation data is provided by governments and international institutions on a monthly basis. Today's values were obtained by estimating figures from recent trends.\n\nThe following table contains relevant indicators:\n\nIndicator Value\nTotal Inflation (2015-2019) 6.99%\nTotal Inflation* 7.03%\nAnnual inflation avg. (2015-2019) 1.7%\nAnnual inflation avg.* 1.37%\nCPI 2015 99.07\nCPI 2019 106\nCPI today* 106.03\n\\$1 in 2015 \\$1.07 in 2019\n\n* Values extrapolated from the last official data to obtain today's values.\n\n## How to calculate today's value of money after inflation?\n\nThere are several ways to calculate the time value of money. Depending on the data available, results can be obtained by using the compound interest formula or the Consumer Price Index (CPI) formula.\n\n#### Using the compound interest formula\n\nGiven that money changes in time as a result of an inflation rate that acts as a compound interest, the following formula can be used: FV = PV (1 + i)n, where:\n\n• FV: Future Value\n• PV: Present Value\n• i: Interest rate (inflation)\n• n: Number of times the interest is compounded (i.e. # of years)\n\nIn this case, the future value represents the final amount obtained after applying the inflation rate to our initial value. In other words, it indicates how much are \\$100 worth today. There are 4 years between 2015 and 2019 and the average inflation rate has been 1.3675%. Therefore, we can resolve the formula like this:\n\nFV = PV (1 + i)n = \\$100 * (1 + 0.01)4 = \\$106.99\n\n#### Using the CPI formula\n\nWhen the CPI for both start and end years is known, the following formula can be used:\n\nFinal value = Initial value *\nCPI final/CPI initial\n\nIn this case, the CPI in 2015 was 99.07 and the CPI today is 106.03. Therefore,\n\nFinal value = Initial value *\nCPI final/CPI initial\n= \\$100 *\n106/99.07\n= \\$106.99\n\n### USA inflation - Conversion table\n\nInitial Value Equivalent value\n\\$1 dollar in 2015 \\$1.07 dollars today\n\\$5 dollars in 2015 \\$5.35 dollars today\n\\$10 dollars in 2015 \\$10.7 dollars today\n\\$50 dollars in 2015 \\$53.51 dollars today\n\\$100 dollars in 2015 \\$107.03 dollars today\n\\$500 dollars in 2015 \\$535.14 dollars today\n\\$1,000 dollars in 2015 \\$1,070.27 dollars today\n\\$5,000 dollars in 2015 \\$5,351.37 dollars today\n\\$10,000 dollars in 2015 \\$10,702.73 dollars today\n\\$50,000 dollars in 2015 \\$53,513.67 dollars today\n\\$100,000 dollars in 2015 \\$107,027.33 dollars today\n\\$500,000 dollars in 2015 \\$535,136.66 dollars today\n\\$1,000,000 dollars in 2015 \\$1,070,273.32 dollars today\n\nPeriod Value\n2015 100\n2016 100.73\n2017 102.82\n2018 104.99\n2019 106.99\nToday 107.03" ]
[ null ]
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https://thegoodbean.com/article/cox-proportional-hazards-model-sas-example-e4c13b
[ "���}�����S[ؒ8���k��~m̸���J���Gd\\�nQ=P��%�endstream The function survfit() estimates the survival proportion, by default at the mean values of covariates. Consequently, the Cox model is a proportional-hazards model: the hazard of the event in any group is a constant multiple of the hazard in any other. In the multivariate Cox analysis, the covariates sex and ph.ecog remain significant (p < 0.05). endobj {�~��s~���E��|;�LӰ,� 9��[]|�GM��a$^�=m�?��\\}�ܹ�n���*;ci� �x�>��y0rY���q.��͎�$ć��{��^t�{4ui� ٘ce�:��^;�#d3��o�\"�RI�ٿ?��7���������? Course: Machine Learning: Master the Fundamentals, Course: Build Skills for a Top Job in any Industry, Specialization: Master Machine Learning Fundamentals, Specialization: Software Development in R, The need for multivariate statistical modeling, Basics of the Cox proportional hazards model, R function to compute the Cox model: coxph(), Visualizing the estimated distribution of survival times, Courses: Build Skills for a Top Job in any Industry, IBM Data Science Professional Certificate, Practical Guide To Principal Component Methods in R, Machine Learning Essentials: Practical Guide in R, R Graphics Essentials for Great Data Visualization, GGPlot2 Essentials for Great Data Visualization in R, Practical Statistics in R for Comparing Groups: Numerical Variables, Inter-Rater Reliability Essentials: Practical Guide in R, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, Practical Statistics for Data Scientists: 50 Essential Concepts, Hands-On Programming with R: Write Your Own Functions And Simulations, An Introduction to Statistical Learning: with Applications in R. the definition of hazard and survival functions, the construction of Kaplan-Meier survival curves for different patient groups, the logrank test for comparing two or more survival curves, A covariate with hazard ratio > 1 (i.e. << /Author (Laine Thomas, Eric M. Reyes) /CreationDate (D:20141024194022+02'00') /Creator (LaTeX with hyperref package) /Keywords (time-dependent covariates, time-varying coefficients, Cox proportional-hazards model, survival estimation, SAS, R) /ModDate (D:20141024194022+02'00') /PTEX.Fullbanner (This is pdfTeX, Version 3.14159265-2.6-1.40.15 $$TeX Live 2014/Debian$$ kpathsea version 6.2.0) /Producer (pdfTeX-1.40.15) /Subject (Journal of Statistical Software \\205 Code Snippets) /Title (Tutorial: Survival Estimation for Cox Regression Models with Time-Varying Coefficients Using SAS and R) /Trapped /False >> And, we don’t have to assume that 0(t) follows an expo-nential model, or a Weibull model, or any other particular parametric model. Most commonly, this examination entails the speci cation of a linear-like model for the log hazard. The corresponding hazard function can be simply written as follow, $Examples Tree level 6. �V tZ++ Z��#�-1�. ?���w����%�����-��AbP�n5j6G]k���s{� �\"^�~�/�L�Bw[�3�}ۃq�Cdq� endobj 6АFl�@!h����Rl/ m�K5. These tests evaluate the omnibus null hypothesis that all of the betas ($$\\beta$$) are 0. Examples: Proportional Hazards Regression. %PDF-1.5 ;�I#��ꔌHB^�i4.⒳pZb�a2T� G'�Ay�i���L�5�A Cox proportional hazards regression model The Cox PH model • is a semiparametric model • makes no assumptions about the form of h(t) (non-parametric part of model) • assumes parametric form for the effect of the predictors on the hazard In most situations, we are more interested in the parameter estimates than the shape of the hazard. The default ‘efron’ is generally preferred to the once-popular “breslow” method. To answer to this question, we’ll perform a multivariate Cox regression analysis. The regression coefficients. A positive sign means that the hazard (risk of death) is higher, and thus the prognosis worse, for subjects with higher values of that variable. Right Censoring. INTRODUCTION Cox proportional-hazards regression models are used widely for analyzing survival data and a key assumption in the Cox models is that the effect of any predictor variable is constant over time. Hence, when investigating survival in relation to any one factor, it is often desirable to adjust for the impact of others. Node 17 of 26 . Additionally, Kaplan-Meier curves and logrank tests are useful only when the predictor variable is categorical (e.g. For example, being female (sex=2) reduces the hazard by a factor of 0.59, or 41%. Using hazard ratio statements in SAS 9.4, I get a hazard ratio for 1) a at the mean of b, and 2) b at the mean of a. h_{k'}(t) = h_0(t)e^{\\sum\\limits_{i=1}^n{\\beta x'}}$. g0��Y���aL���rA�%�U0;ȋX��� �KX�������o1B.���5�F���Q��0B(�ft�\"�p����2����fĤ y� ��� yx��T�����aL�a\"�\\6�Ƽ�aR�1���#L SAS First, we run a proportional hazards regression to assess the effects of treatment on the time to linkage with primary care. 27 0 obj The survival function of the Cox proportional hazards model (1) is given by S(t ... For example in SAS, uniformly distributed random numbers can be generated by means of the function RANUNI . The wald statistic evaluates, whether the beta ($$\\beta$$) coefficient of a given variable is statistically significantly different from 0. The Cox proportional hazards model is estimated in SAS using the PHREG procedure. \\]. Enjoyed this article? The Cox proportional-hazards model (Cox, 1972) is essentially a regression model commonly used statistical in medical research for investigating the association between the survival time of patients and one or more predictor variables. Node 5 of 6 . This video provides a demonstration of the use of the Cox proportional hazards model using SPSS. Statistical model is a frequently used tool that allows to analyze survival with respect to several factors simultaneously. The next section introduces the basics of the Cox regression model. If we have two groups, one receiving the standard treatment and the other receiving the new treatment, and the proportional hazards assu… The estimated coefficients in the Cox proportional hazards regression model, b 1, for example, represent the change in the expected log of the hazard ratio relative to a one unit change in X 1, holding all other predictors constant. There are a number of basic concepts for testing proportionality but the implementation of these concepts differ across statistical packages. It is demonstrated how the rates of convergence depend on the regularization parameter in the penalty function. Thanks! Thus, older age and higher ph.ecog are associated with poorer survival, whereas being female (sex=2) is associated with better survival. : treatment A vs treatment B; males vs females). For example, holding the other covariates constant, being female (sex=2) reduces the hazard by a factor of 0.58, or 42%. If one of the groups also contains older individuals, any difference in survival may be attributable to genotype or age or indeed both. status: censoring status 1=censored, 2=dead, ph.ecog: ECOG performance score (0=good 5=dead), ph.karno: Karnofsky performance score (bad=0-good=100) rated by physician, pat.karno: Karnofsky performance score as rated by patient, Cox DR (1972). The Cox proportional hazards model makes sevral assumptions. This assumption of proportional hazards should be tested. We conclude that, being female is associated with good prognostic. SAS Viya Analytics Procedures Tree level 2. For instance, suppose two groups of patients are compared: those with and those without a specific genotype. Hazard ratios. << /Type /ObjStm /Length 1244 /Filter /FlateDecode /N 24 /First 175 >> 3 The Cox Proportional-Hazards Model Survival analysis typically examines the relationship of the survival distribution to covariates. We present a new SAS macro %pshreg that can be used to fit a proportional subdistribution hazards model for survival data subject to competing risks. The Cox PH model is well-suited to this goal. (Data were read in and observations with missing values removed in example 7.40.) In other words, if an individual has a risk of death at some initial time point that is twice as high as that of another individual, then at all later times the risk of death remains twice as high. For example, when a two-level (dichotomous) covariate with a value of 0=no and 1=yes is observed, the hazard ratio becomes eβwhere β is the parameter estimate from the regression. Our macro first modifies the input data set appropriately and then applies SAS's standard Cox regression procedure, PROC PHREG, using weights and counting-process style of specifying survival times to the modified data set. They don’t work easily for quantitative predictors such as gene expression, weight, or age. 26 0 obj We’ll fit the Cox regression using the following covariates: age, sex, ph.ecog and wt.loss. It is the most commonly used regression model for survival data. As a result, new variable selection procedures for these two commonly-used models are proposed. The “exact” method is much more computationally intensive. To apply the univariate coxph function to multiple covariates at once, type this: The output above shows the regression beta coefficients, the effect sizes (given as hazard ratios) and statistical significance for each of the variables in relation to overall survival. As the variable ph.karno is not significant in the univariate Cox analysis, we’ll skip it in the multivariate analysis. This assumption implies that, as mentioned above, the hazard curves for the groups should be proportional and cannot cross. We may wish to display how estimated survival depends upon the value of a covariate of interest. In clinical investigations, there are many situations, where several known quantities (known as covariates), potentially affect patient prognosis. Cox’s Proportional Hazards Model In this unit we introduce Cox’s proportional hazards (Cox’s PH) model, give a heuristic development of the partial likelihood function, and discuss adapta- tions to accommodate tied observations. Having fit a Cox model to the data, it’s possible to visualize the predicted survival proportion at any given point in time for a particular risk group. x��W�n�F}�Ẉ��{��v�� ��-����������;�%�]Rt��왙s��%�! The hazard ratios of covariates are interpretable as multiplicative effects on the hazard. Garnier Soft Black Before And After, How Long Does Rabies Post Exposure Prophylaxis Last, The Three Sheep And Monster, Unrenovated Warehouse Melbourne, Applejack Recipe With Everclear, Asparagus In Swahili, Angel Of Independence Vandalism, Audio-technica Ath-m20x Vs M40x, Garda Recruitment 2020, Giant Bean Bag Chair Amazon, \" />\nSelect Page\n\nThe variables sex, age and ph.ecog have highly statistically significant coefficients, while the coefficient for ph.karno is not significant. Survival Estimation to Cox Proportional Hazard Regression Models with Time-varying Coefficients Abstract ox proportional hazard model is one of the most used statistical methods in survival analysis, and is highly relied on the proportional hazards (PH) assumption - the hazard ratios should be constant. This assumption of proportional hazards should be tested. COMPARISON BETWEEN WEIBULL AND COX PROPORTIONAL HAZARDS MODELS by ANGELA MARIA CRUMER B.S., Southeast Missouri State University, 2008 A REPORT submitted in partial fulfillment of the requirements for the degree MASTER OF SCIENCE Department of Statistics College of Arts and Sciences KANSAS STATE UNIVERSITY Manhattan, Kansas 2011 Approved by: Major Professor Dr. James … This analysis has been performed using R software (ver. Violations of the proportional hazard assumption may cause bias in the estimated coefficients as well as incorrect inference regarding significance of effects. )�7�U��tH�‡��#�(B3ih&$�A�K���sYxey���S9�S�/˽}8�f����,[��Y����� a�E���^\\*|�k���㉏t�I���q�(v��q_�����#��@�6I�$dH��]��A��ᶌ|qh�q_�6I���Ζ�G8!�Z�ƒ�ӱ�};�6���}��l*��L}�ԲȗE�|/԰��Q��G�]t��x�6���JC�< ��Y���A-����&x��r=��_�}~�$g6����H�lCt�a4��iL.Z�\"��f~&d1�DJ��j�M$Y����)�3g�]2�c� c}��K���&g�_����n���̒y�ɩ�䤀�̲y��QQ�t����8��b���h�s���q��?U�>���}�����S[ؒ8���k��~m̸���J���Gd\\�nQ=P��%�endstream The function survfit() estimates the survival proportion, by default at the mean values of covariates. Consequently, the Cox model is a proportional-hazards model: the hazard of the event in any group is a constant multiple of the hazard in any other. In the multivariate Cox analysis, the covariates sex and ph.ecog remain significant (p < 0.05). endobj {�~��s~���E��|;�LӰ,� 9��[]|�GM��a$^�=m�?��\\}�ܹ�n���*;ci� �x�>��y0rY���q.��͎�$ć��{��^t�{4ui� ٘ce�:��^;�#d3��o�\"�RI�ٿ?��7���������? Course: Machine Learning: Master the Fundamentals, Course: Build Skills for a Top Job in any Industry, Specialization: Master Machine Learning Fundamentals, Specialization: Software Development in R, The need for multivariate statistical modeling, Basics of the Cox proportional hazards model, R function to compute the Cox model: coxph(), Visualizing the estimated distribution of survival times, Courses: Build Skills for a Top Job in any Industry, IBM Data Science Professional Certificate, Practical Guide To Principal Component Methods in R, Machine Learning Essentials: Practical Guide in R, R Graphics Essentials for Great Data Visualization, GGPlot2 Essentials for Great Data Visualization in R, Practical Statistics in R for Comparing Groups: Numerical Variables, Inter-Rater Reliability Essentials: Practical Guide in R, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, Practical Statistics for Data Scientists: 50 Essential Concepts, Hands-On Programming with R: Write Your Own Functions And Simulations, An Introduction to Statistical Learning: with Applications in R. the definition of hazard and survival functions, the construction of Kaplan-Meier survival curves for different patient groups, the logrank test for comparing two or more survival curves, A covariate with hazard ratio > 1 (i.e. << /Author (Laine Thomas, Eric M. Reyes) /CreationDate (D:20141024194022+02'00') /Creator (LaTeX with hyperref package) /Keywords (time-dependent covariates, time-varying coefficients, Cox proportional-hazards model, survival estimation, SAS, R) /ModDate (D:20141024194022+02'00') /PTEX.Fullbanner (This is pdfTeX, Version 3.14159265-2.6-1.40.15 $$TeX Live 2014/Debian$$ kpathsea version 6.2.0) /Producer (pdfTeX-1.40.15) /Subject (Journal of Statistical Software \\205 Code Snippets) /Title (Tutorial: Survival Estimation for Cox Regression Models with Time-Varying Coefficients Using SAS and R) /Trapped /False >> And, we don’t have to assume that 0(t) follows an expo-nential model, or a Weibull model, or any other particular parametric model. Most commonly, this examination entails the speci cation of a linear-like model for the log hazard. The corresponding hazard function can be simply written as follow, $Examples Tree level 6. �V tZ++ Z��#�-1�. ?���w����%�����-��AbP�n5j6G]k���s{� �\"^�~�/�L�Bw[�3�}ۃq�Cdq� endobj 6АFl�@!h����Rl/ m�K5. These tests evaluate the omnibus null hypothesis that all of the betas ($$\\beta$$) are 0. Examples: Proportional Hazards Regression. %PDF-1.5 ;�I#��ꔌHB^�i4.⒳pZb�a2T� G'�Ay�i���L�5�A Cox proportional hazards regression model The Cox PH model • is a semiparametric model • makes no assumptions about the form of h(t) (non-parametric part of model) • assumes parametric form for the effect of the predictors on the hazard In most situations, we are more interested in the parameter estimates than the shape of the hazard. The default ‘efron’ is generally preferred to the once-popular “breslow” method. To answer to this question, we’ll perform a multivariate Cox regression analysis. The regression coefficients. A positive sign means that the hazard (risk of death) is higher, and thus the prognosis worse, for subjects with higher values of that variable. Right Censoring. INTRODUCTION Cox proportional-hazards regression models are used widely for analyzing survival data and a key assumption in the Cox models is that the effect of any predictor variable is constant over time. Hence, when investigating survival in relation to any one factor, it is often desirable to adjust for the impact of others. Node 17 of 26 . Additionally, Kaplan-Meier curves and logrank tests are useful only when the predictor variable is categorical (e.g. For example, being female (sex=2) reduces the hazard by a factor of 0.59, or 41%. Using hazard ratio statements in SAS 9.4, I get a hazard ratio for 1) a at the mean of b, and 2) b at the mean of a. h_{k'}(t) = h_0(t)e^{\\sum\\limits_{i=1}^n{\\beta x'}}$. g0��Y���aL���rA�%�U0;ȋX��� �KX�������o1B.���5�F���Q��0B(�ft�\"�p����2����fĤ y� ��� yx��T�����aL�a\"�\\6�Ƽ�aR�1���#L SAS First, we run a proportional hazards regression to assess the effects of treatment on the time to linkage with primary care. 27 0 obj The survival function of the Cox proportional hazards model (1) is given by S(t ... For example in SAS, uniformly distributed random numbers can be generated by means of the function RANUNI . The wald statistic evaluates, whether the beta ($$\\beta$$) coefficient of a given variable is statistically significantly different from 0. The Cox proportional hazards model is estimated in SAS using the PHREG procedure. \\]. Enjoyed this article? The Cox proportional-hazards model (Cox, 1972) is essentially a regression model commonly used statistical in medical research for investigating the association between the survival time of patients and one or more predictor variables. Node 5 of 6 . This video provides a demonstration of the use of the Cox proportional hazards model using SPSS. Statistical model is a frequently used tool that allows to analyze survival with respect to several factors simultaneously. The next section introduces the basics of the Cox regression model. If we have two groups, one receiving the standard treatment and the other receiving the new treatment, and the proportional hazards assu… The estimated coefficients in the Cox proportional hazards regression model, b 1, for example, represent the change in the expected log of the hazard ratio relative to a one unit change in X 1, holding all other predictors constant. There are a number of basic concepts for testing proportionality but the implementation of these concepts differ across statistical packages. It is demonstrated how the rates of convergence depend on the regularization parameter in the penalty function. Thanks! Thus, older age and higher ph.ecog are associated with poorer survival, whereas being female (sex=2) is associated with better survival. : treatment A vs treatment B; males vs females). For example, holding the other covariates constant, being female (sex=2) reduces the hazard by a factor of 0.58, or 42%. If one of the groups also contains older individuals, any difference in survival may be attributable to genotype or age or indeed both. status: censoring status 1=censored, 2=dead, ph.ecog: ECOG performance score (0=good 5=dead), ph.karno: Karnofsky performance score (bad=0-good=100) rated by physician, pat.karno: Karnofsky performance score as rated by patient, Cox DR (1972). The Cox proportional hazards model makes sevral assumptions. This assumption of proportional hazards should be tested. We conclude that, being female is associated with good prognostic. SAS Viya Analytics Procedures Tree level 2. For instance, suppose two groups of patients are compared: those with and those without a specific genotype. Hazard ratios. << /Type /ObjStm /Length 1244 /Filter /FlateDecode /N 24 /First 175 >> 3 The Cox Proportional-Hazards Model Survival analysis typically examines the relationship of the survival distribution to covariates. We present a new SAS macro %pshreg that can be used to fit a proportional subdistribution hazards model for survival data subject to competing risks. The Cox PH model is well-suited to this goal. (Data were read in and observations with missing values removed in example 7.40.) In other words, if an individual has a risk of death at some initial time point that is twice as high as that of another individual, then at all later times the risk of death remains twice as high. For example, when a two-level (dichotomous) covariate with a value of 0=no and 1=yes is observed, the hazard ratio becomes eβwhere β is the parameter estimate from the regression. Our macro first modifies the input data set appropriately and then applies SAS's standard Cox regression procedure, PROC PHREG, using weights and counting-process style of specifying survival times to the modified data set. They don’t work easily for quantitative predictors such as gene expression, weight, or age. 26 0 obj We’ll fit the Cox regression using the following covariates: age, sex, ph.ecog and wt.loss. It is the most commonly used regression model for survival data. As a result, new variable selection procedures for these two commonly-used models are proposed. The “exact” method is much more computationally intensive. To apply the univariate coxph function to multiple covariates at once, type this: The output above shows the regression beta coefficients, the effect sizes (given as hazard ratios) and statistical significance for each of the variables in relation to overall survival. As the variable ph.karno is not significant in the univariate Cox analysis, we’ll skip it in the multivariate analysis. This assumption implies that, as mentioned above, the hazard curves for the groups should be proportional and cannot cross. We may wish to display how estimated survival depends upon the value of a covariate of interest. In clinical investigations, there are many situations, where several known quantities (known as covariates), potentially affect patient prognosis. Cox’s Proportional Hazards Model In this unit we introduce Cox’s proportional hazards (Cox’s PH) model, give a heuristic development of the partial likelihood function, and discuss adapta- tions to accommodate tied observations. Having fit a Cox model to the data, it’s possible to visualize the predicted survival proportion at any given point in time for a particular risk group. x��W�n�F}�Ẉ�`�{��v�� ��-����������;�%�]Rt��왙s��%�! The hazard ratios of covariates are interpretable as multiplicative effects on the hazard." ]
[ null ]
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http://slideplayer.com/slide/7895509/
[ "", null, "# Five Steps Factoring Polynomials Completely Step 1 Step 2 Step 3\n\n## Presentation on theme: \"Five Steps Factoring Polynomials Completely Step 1 Step 2 Step 3\"— Presentation transcript:\n\nFive Steps Factoring Polynomials Completely Step 1 Step 2 Step 3\nThese are the steps to … Factoring Polynomials Completely Make Sure that each Polynomial is factored completely. If you have tried steps 1 – 4 and the polynomial cannot be factored, the polynomial is Prime. Step 5 Four Terms: Grouping Group two terms together that have a GCF. Factor out the GCF from each pair. Look for common binomial. Re-write with common binomial times other factors in a binomial. Example: 5t4 + 20t3 + 6t = (t + 4) (5t3 + 6) Step 4 Five Steps Factor out the GCF Example: 2x3- 6x2 = 2x2 ( x – 3) Always make sure the remaining polynomial(s) are factored. Two Terms : Check for “DOTS” (Difference of Two Squares) Two terms Difference A and C are perfect squares Example: x2 – 4 = (x – 2 ) (x + 2) see if the binomials will factor again. Check Using FOIL Three Terms: Check for “PST” Check for “PST” m2 + 2mn + n2 or m2 – 2mn + n2 . Factor using short cut No “PST” , Factor Using Ratio or Trial and error method Check Using FOIL Example PST: c c + 25 = (c + 5)2 For examples of # 2, See Ratio-Trial/Error Method GO* Step 1 Step 2 Step 3 Name Why are these steps important? Following these steps will allow one to factor any polynomial that is not prime. Factoring allows one to find the x-intercepts and in turn graph the polynomial.\n\nFive Steps factor Ax2 + Bx + C Ratio Method\nThese are the steps to … F factor Ax2 + Bx + C Ratio Method Write the first ratio in the first binomial and the second ratio in the second binomial (3x – 1) ( x – 1) Check using FOIL. Step 5 Write the ratio A/ Factor. Write the ratio Factor / C. Reduce. 3/ / are reduced. Step 4 Five Steps Example: 24m2 – 32m + 8 Factor out the GCF (3m2 – 4m + 1) Write two binomials ( ) ( ) Signs: + C signs will be the same sign as the sign of b . - C negative and positive 8( ) ( ) Find AC AC = 3 Find the factors of AC that will add or subtract (depends on the sign of c) to give u B. 3 and 1 are the factors of AC that will add (note c is +) to give B. Step 1 Step 2 Step 3 Name Why are these steps important? Following these steps will allow one to factor any polynomial that is not prime. Factoring a quadratic trinomial enable one to determine the x-intercepts of the parabola. Factoring also enables one to use the x-intercepts to graph.\n\n“DOTS” = Difference of Two Squares\nThese are the steps to … Factor A2 - B2 “DOTS” = Difference of Two Squares Check for DOTS in DOTS 3(x ) ( x2 - 4) 3(x ) ( x + 2)(x - 2) Check using FOIL. Step 5 Write the numbers and variables before they were squared in the binomials. (Note: Any even power on a variable is a perfect square. . . just half the exponent when factoring) 3(x ) ( x2 - 4) Step 4 Five Steps Example: 3x4 - 48 Factor out the GCF ( x4 – 16) Check for : 1.) 2 terms 2.) Minus Sign 3.) A and C are perfect squares Write two binomials Signs: One + ; One ( ) ( ) Step 1 Step 2 Step 3 Name Why are these steps important? Following these steps will allow one to factor any polynomial that is not prime. Factoring a quadratic trinomial enables one to determine the x-intercepts of a parabola. Factoring also enables one to use the x-intercepts to graph.\n\nFive Steps Factor Ax2 + Bx + C Trial and Error. Step 1\nThese are the steps to … Factor Ax2 + Bx + C Trial and Error. Check using FOIL (3x2 – 3x – x + 1) = 8(3x2 – 4x + 1 ) = 24x2 – 32 x + 8 Step 5 If C is positive, determine the factor combination of A and B that will add to give B. If C is negative, determine the factor combination of A and B that will subtract to give B. Since C is positive add to get B : 8 ( 3x – 1) ( x – 1) Step 4 Five Steps Example: 24m2 – 32m + 8 Factor out the GCF (3m2 – 4 m + 1) Write two binomials Signs: + c signs will be the same sign as the sign of b c one negative and one positive ( ) ( ) List the factors of A and the Factors of B. A = 3 B = 1 1, , 1 Step 1 Step 2 Step 3 Name Why are these steps important? Following these steps will allow one to factor any polynomial that is not prime. Factoring a quadratic trinomial enables one to determine the x-intercepts of the parabola. Factoring also enables one to use the x-intercepts to graph.\n\nDownload ppt \"Five Steps Factoring Polynomials Completely Step 1 Step 2 Step 3\"\n\nSimilar presentations" ]
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http://ccrl.chessdom.com/ccrl/4040/cgi/engine_details.cgi?match_length=30&amp;print=Details&amp;each_game=1&amp;eng=SmarThink%201.98%2064-bit
[ "Contents: CCRL 40/40 Downloads and Statistics October 19, 2019 Testing summary: Total: 1'092'341 games played by 2'556 programs 149261 CPU days (X2 4600+) White wins: 378'952 (34.7%) Black wins: 281'710 (25.8%) Draws: 431'679 (39.5%) White score: 54.5%\n\nEngine Details\n\n Options Show each game results\nSmarThink 1.98 64-bit#48‑49  (3027+13\n−13\n)Quote\n Author: Sergei Markoff (Russia) Link: Homepage\nThis is one of the 15 SmarThink versions we tested: Compare them!\n Opponent Elo Diff Results Score LOS Perf –   Houdini 6 64-bit 3335 +10−9 (+308) 0 − 1(+0−1=0) 0.0%0.0 / 1 0.0% −INF 0 –   Andscacs 0.94 64-bit 4CPU 3264 +18−18 (+237) 0.5 − 1.5(+0−1=1) 25.0%0.5 / 2 0.0% +79 0 = –   Komodo 12.2.2 MCTS 64-bit 3214 +16−16 (+187) 12.5 − 27.5(+4−19=17) 31.3%12.5 / 40 0.0% +69 = = 0 0 0 0 = = 0 1 = = 1 = 0 0 0 1 0 = = 0 = 1 0 0 0 = 0 0 0 = = = = 0 0 0 = = –   Andscacs 0.95 64-bit 3184 +11−11 (+157) 11.5 − 30.5(+4−23=15) 27.4%11.5 / 42 0.0% +4 = = 0 = 0 = 0 0 0 1 0 = 0 0 0 = 0 = 0 = 0 = = 0 0 0 = 0 1 = 0 0 0 = 0 = 0 1 = 1 0 0 –   RofChade 2.0 64-bit 4CPU 3177 +21−21 (+150) 8.5 − 23.5(+2−17=13) 26.6%8.5 / 32 0.0% 0 0 1 0 0 = = = = = 0 = 0 0 0 = = 0 1 0 = 0 0 0 0 0 = = = 0 0 0 = –   Andscacs 0.93 64-bit 3171 +13−13 (+144) 3 − 11(+0−8=6) 21.4%3.0 / 14 0.0% −42 = 0 = 0 0 0 0 0 = 0 = = = 0 –   Nemorino 5.00 64-bit 4CPU 3153 +19−19 (+126) 8.5 − 27.5(+3−22=11) 23.6%8.5 / 36 0.0% −58 0 = 0 0 0 = 0 0 0 1 0 0 = = 0 0 = = 0 1 0 0 = = 0 = = 0 0 0 = 0 0 0 1 0 –   Roc 1.0 64-bit 3120 +21−21 (+93) 1 − 4(+0−3=2) 20.0%1.0 / 5 0.0% −97 = = 0 0 0 –   Roc 0.7 64-bit 3116 +11−11 (+89) 6.5 − 9.5(+1−4=11) 40.6%6.5 / 16 0.0% +38 = 1 0 = = = 0 = 0 = = 0 = = = = –   Chiron 4 64-bit 3115 +9−9 (+88) 6 − 11(+1−6=10) 35.3%6.0 / 17 0.0% +4 = = = = = = = = 1 0 0 0 0 = = 0 0 –   Schooner 2.0.34 64-bit 3111 +12−12 (+84) 10.5 − 17.5(+5−12=11) 37.5%10.5 / 28 0.0% +3 0 0 = 1 = 1 1 0 = 1 0 = = 0 0 0 0 0 = 0 = = 0 1 = 0 = = –   NirvanaChess 2.4 64-bit 3102 +9−9 (+75) 8.5 − 12.5(+3−7=11) 40.5%8.5 / 21 0.0% +23 = 0 = = = 0 0 1 1 0 0 = = 0 = = 1 = = = 0 –   Fritz 16 64-bit 3102 +11−11 (+75) 5 − 11(+2−8=6) 31.3%5.0 / 16 0.0% −48 = = 0 0 0 = 1 = 0 0 = 0 = 0 0 1 –   Roc 0.8 64-bit 3101 +21−21 (+74) 1.5 − 2.5(+0−1=3) 37.5%1.5 / 4 0.0% +6 = = 0 = –   Equinox 3.20 64-bit 3096 +9−9 (+69) 6 − 8(+1−3=10) 42.9%6.0 / 14 0.0% +32 = = = 0 1 = = = 0 0 = = = = –   Vajolet2 2.7 64-bit 3096 +15−15 (+69) 12 − 19(+5−12=14) 38.7%12.0 / 31 0.0% 0 = = = 0 = 0 1 = 0 0 = 0 1 = 1 = = 0 0 = 1 0 = = = 1 = 0 0 0 0 –   Xiphos 0.3 64-bit 3094 +19−19 (+67) 10.5 − 14.5(+3−7=15) 42.0%10.5 / 25 0.0% +25 0 1 0 = 1 = = = = = = 1 = 0 0 = 0 = = = = = = 0 0 –   Ethereal 10.00 64-bit 3093 +15−15 (+66) 11.5 − 18.5(+5−12=13) 38.3%11.5 / 30 0.0% −7 1 = 0 = = 0 1 = = 0 0 0 = = 0 1 0 0 = = = = = 0 0 0 0 = 1 1 –   Nemorino 5.00 64-bit 3088 +14−14 (+61) 2.5 − 5.5(+1−4=3) 31.3%2.5 / 8 0.0% −62 = 0 0 0 1 = = 0 –   Arasan 21.1 64-bit 3083 +19−19 (+56) 7 − 17(+1−11=12) 29.2%7.0 / 24 0.0% −68 0 0 = = = 0 0 0 = 0 0 = 0 = = = 0 = = 1 0 = 0 = –   RofChade 2.0 64-bit 3083 +18−19 (+56) 9 − 15(+2−8=14) 37.5%9.0 / 24 0.0% −13 = = 0 0 = = 0 1 = 0 0 = 0 = 0 = = = 0 1 = = = = –   Komodo 12.1.1 MCTS 64-bit 3081 +15−15 (+54) 14.5 − 25.5(+8−19=13) 36.3%14.5 / 40 0.0% −40 0 0 0 1 0 0 0 = 0 = 1 = 0 0 0 0 = = 0 0 0 0 1 1 = = 0 1 = = = 1 0 = 0 1 0 = 1 = –   Hannibal 1.7 64-bit 3081 +9−10 (+54) 8.5 − 10.5(+2−4=13) 44.7%8.5 / 19 0.0% +24 = 0 = = = = = 0 1 = = = 0 1 0 = = = = –   Arasan 21.2 64-bit 3079 +16−16 (+52) 11.5 − 22.5(+7−18=9) 33.8%11.5 / 34 0.0% −64 = = = 0 0 1 1 0 0 0 = = = 0 = 1 = 0 1 0 = 0 0 0 1 0 0 0 0 0 0 1 0 1 –   Texel 1.07 64-bit 3076 +12−12 (+49) 12.5 − 15.5(+4−7=17) 44.6%12.5 / 28 0.0% +18 = = 1 0 = = 1 = = = 0 = 0 1 = = = 0 = = = = = 1 0 = 0 0 –   Bouquet 1.8 64-bit 3075 +9−9 (+48) 1.5 − 0.5(+1−0=1) 75.0%1.5 / 2 0.0% +191 1 = –   Laser 1.5 64-bit 3073 +15−15 (+46) 6 − 14(+2−10=8) 30.0%6.0 / 20 0.0% −79 0 = 0 0 0 = 0 = = = = 0 0 = 1 0 0 = 1 0 –   RubiChess 1.3 64-bit 4CPU 3066 +22−22 (+39) 14.5 − 17.5(+7−10=15) 45.3%14.5 / 32 0.2% +11 = = 0 = = 0 1 = 0 0 = 0 = 0 1 = 0 1 1 = = 0 = 1 = 1 = = 0 = 1 0 –   ChessBrainVB 3.72 3063 +15−15 (+36) 6 − 6(+4−4=4) 50.0%6.0 / 12 0.0% +32 0 = 1 = = = 0 1 1 0 1 0 –   Vajolet2 2.6 64-bit 3061 +15−15 (+34) 7 − 5(+5−3=4) 58.3%7.0 / 12 0.0% +88 1 0 1 1 = 0 1 = 0 = = 1 –   Critter 1.2 32-bit 3061 +15−15 (+34) 7 − 7(+3−3=8) 50.0%7.0 / 14 0.0% +31 1 1 = = = 0 = = = 0 1 0 = = –   Pedone 1.8 64-bit 3060 +16−16 (+33) 11 − 23(+4−16=14) 32.4%11.0 / 34 0.1% −79 0 = = 0 1 1 0 0 0 1 0 = 0 0 = = 0 0 0 1 0 = = 0 0 = = = = 0 = = 0 = –   Protector 1.9.0 64-bit 3059 +9−10 (+32) 8 − 11(+4−7=8) 42.1%8.0 / 19 0.0% −18 = 1 1 0 0 0 0 = = = = 0 = = 0 = 1 1 0 –   Wasp 3.75 64-bit 3058 +30−30 (+31) 2 − 2(+0−0=4) 50.0%2.0 / 4 3.0% +31 = = = = –   BlackMamba 2.0 64-bit 3057 +10−10 (+30) 2 − 1(+1−0=2) 66.7%2.0 / 3 0.0% +126 1 = = –   chess22k 1.12 64-bit 3050 +16−16 (+23) 15.5 − 18.5(+7−10=17) 45.6%15.5 / 34 1.0% −4 0 = 1 = 0 1 0 1 = 0 0 0 = 0 = 1 = = 1 = 0 = 1 = = 1 = = = 0 = = = 0 –   Komodo 5 32-bit 3048 +16−16 (+21) 6 − 8(+3−5=6) 42.9%6.0 / 14 2.1% −20 1 0 1 1 = = 0 = 0 = = = 0 0 –   ChessBrainVB 3.70 3045 +23−23 (+18) 6 − 13(+3−10=6) 31.6%6.0 / 19 8.9% −105 = 0 1 = 0 0 = 0 = 0 1 = 1 0 0 = 0 0 0 –   Ethereal 9.65 64-bit 3042 +17−17 (+15) 16 − 18(+7−9=18) 47.1%16.0 / 34 8.1% 0 = 0 0 0 1 = = = = 1 = = 0 = = 1 0 = = = = 1 1 0 0 = = 0 0 = = 1 = 1 –   iCE 3.0 64-bit 3042 +12−12 (+15) 7.5 − 10.5(+4−7=7) 41.7%7.5 / 18 3.4% −39 0 1 = 1 0 = 0 = = = 0 0 0 1 0 1 = = –   Arasan 21.0 64-bit 3042 +17−17 (+15) 19.5 − 18.5(+12−11=15) 51.3%19.5 / 38 6.9% +21 = 1 = = 1 = 1 1 1 0 = 1 0 1 1 = 0 1 0 1 1 = 0 1 0 = 0 = = 0 0 = 0 = = 0 = = –   Nemorino 4.00 64-bit 3040 +17−17 (+13) 11.5 − 12.5(+6−7=11) 47.9%11.5 / 24 9.6% −2 = = 0 = = 0 1 = = 0 0 1 0 1 0 = 0 = 1 = = 1 = 1 –   Arasan 20.4.1 64-bit 3038 +16−16 (+11) 8.5 − 11.5(+5−8=7) 42.5%8.5 / 20 14.8% −38 1 = = 1 0 = 1 = 0 1 0 = 0 1 = 0 0 = 0 0 –   Sting SF 9.99 64-bit 3038 +28−28 (+11) 1 − 3(+1−3=0) 25.0%1.0 / 4 23.0% −215 0 0 0 1 –   Senpai 2.0 64-bit 3037 +12−12 (+10) 18 − 21(+9−12=18) 46.2%18.0 / 39 12.4% −9 = 0 = 1 = 0 = = 1 0 0 = 0 0 0 = = = 1 1 0 1 0 = = = = 1 = 0 = = 0 1 = 1 1 0 = –   ChessBrainVB 3.66 3036 +23−23 (+9) 7.5 − 12.5(+3−8=9) 37.5%7.5 / 20 23.7% −68 0 = 0 = 0 0 0 = 0 1 0 = = = 1 1 = = = 0 –   Lc0 0.22.0 wLD2 64-bit 3036 +85−83 (+9) 0.5 − 3.5(+0−3=1) 12.5%0.5 / 4 41.3% −269 0 = 0 0 –   Sting SF 15 64-bit 3033 +25−25 (+6) 3 − 1(+2−0=2) 75.0%3.0 / 4 32.7% +156 = = 1 1 –   Demolito 2019-07-15 64-bit 3029 +26−26 (+2) 1.5 − 2.5(+1−2=1) 37.5%1.5 / 4 43.4% −80 1 = 0 0 –   ChessBrainVB 3.68 3026 +21−21 (−1) 12.5 − 9.5(+6−3=13) 56.8%12.5 / 22 51.5% +36 1 0 = 1 = 1 1 = 0 = = = = = 1 1 = = = 0 = = –   Arasan 20.5 64-bit 3025 +20−20 (−2) 9 − 7(+6−4=6) 56.3%9.0 / 16 53.8% +37 1 = 1 0 1 0 = = = 0 = 1 1 1 = 0 –   Xiphos 0.2 64-bit 3024 +18−18 (−3) 17.5 − 16.5(+9−8=17) 51.5%17.5 / 34 58.2% +5 0 = = 0 = = 1 0 = 0 0 1 0 = 1 = 1 0 = 0 = = 1 = = = = 1 1 1 = = 1 = –   Pirarucu 2.7.4 64-bit 4CPU 3022 +21−22 (−5) 16 − 16(+8−8=16) 50.0%16.0 / 32 64.1% −6 = 0 1 0 = = 0 1 = 0 = 1 1 = = = 1 = 0 = 0 1 0 = 1 = = 1 0 = = = –   Deep Fritz 14 64-bit 1CPU 3019 +11−11 (−8) 17.5 − 26.5(+11−20=13) 39.8%17.5 / 44 81.1% −77 0 0 0 0 = = = 0 0 1 0 = = 1 = 1 = 0 0 = 0 1 0 0 0 = 1 = 1 1 = 1 0 0 0 1 0 1 0 = 1 0 = 0 –   Pedone 1.7 64-bit 3014 +17−17 (−13) 14 − 14(+7−7=14) 50.0%14.0 / 28 88.4% −14 = 1 = = 1 1 = = = = = 0 0 0 1 1 1 0 0 = = 0 0 = = 1 = = –   chess22k 1.10 64-bit 4CPU 3014 +22−22 (−13) 18.5 − 21.5(+11−14=15) 46.3%18.5 / 40 82.4% −39 0 0 = = 0 = 0 = 0 0 1 0 0 1 = 0 0 = 1 = 1 1 0 = 0 1 = = = = 1 = 0 1 1 1 = = 1 0 –   Naum 4.6 64-bit 3013 +12−12 (−14) 2 − 1(+2−1=0) 66.7%2.0 / 3 93.5% +120 1 0 1 –   Stockfish 2.0.1 32-bit 3013 +17−17 (−14) 8 − 6(+5−3=6) 57.1%8.0 / 14 89.0% +33 1 1 0 1 = = 0 = = = 1 = 1 0 –   Pirarucu 3.0.7 64-bit 3012 +22−22 (−15) 4.5 − 3.5(+2−1=5) 56.3%4.5 / 8 87.4% +16 0 = = = 1 = 1 = –   Sting SF 9.9 64-bit 3010 +17−17 (−17) 19 − 17(+14−12=10) 52.8%19.0 / 36 93.9% +4 = = 1 = = 1 1 1 0 0 0 1 1 0 0 1 0 1 = 1 0 1 = 0 = = 0 1 1 0 1 = = 0 0 1 –   Ethereal 9.30 64-bit 3005 +26−25 (−22) 10.5 − 1.5(+10−1=1) 87.5%10.5 / 12 93.1% +322 1 0 1 1 1 1 1 1 1 = 1 1 –   Vajolet2 2.5 64-bit 3002 +18−18 (−25) 3.5 − 4.5(+2−3=3) 43.8%3.5 / 8 98.7% −62 1 = = = 1 0 0 0 –   Rodent III 0.281 64-bit 2999 +22−22 (−28) 2.5 − 5.5(+0−3=5) 31.3%2.5 / 8 98.5% −132 = 0 = 0 0 = = = –   Hakkapeliitta TCEC v2 64-bit 2999 +13−13 (−28) 32 − 24(+21−13=22) 57.1%32.0 / 56 99.9% +18 1 1 1 0 1 = = 1 = 0 = 0 1 0 = 0 1 1 0 = 1 1 1 1 1 = 1 = 1 1 0 = = = 1 1 0 = = = = = 0 = = 0 0 1 = 1 = 1 0 0 = = –   Defenchess 1.1f 64-bit 2998 +12−12 (−29) 21.5 − 14.5(+15−8=13) 59.7%21.5 / 36 99.9% +35 = 1 = 1 0 1 1 = = = 1 1 1 1 0 0 0 = 0 1 = 1 = = 1 = 1 0 1 1 1 = 0 = 0 = –   Sting SF 16 64-bit 2996 +82−82 (−31) 3 − 1(+2−0=2) 75.0%3.0 / 4 76.5% +114 = 1 1 = –   chess22k 1.11 64-bit 2990 +20−20 (−37) 11.5 − 6.5(+6−1=11) 63.9%11.5 / 18 99.9% +42 1 1 = = 1 = = = = = 0 1 = 1 = 1 = = –   ChessBrainVB 3.61 2988 +27−27 (−39) 9 − 9(+4−4=10) 50.0%9.0 / 18 99.5% −41 = = = 0 = = 0 1 1 = = = = = 1 1 0 0 –   Rodent III 0.275 64-bit 2987 +15−15 (−40) 5 − 3(+2−0=6) 62.5%5.0 / 8 100.0% +23 = = = = = 1 1 = –   Xiphos 0.1 64-bit 2987 +20−20 (−40) 17 − 13(+11−7=12) 56.7%17.0 / 30 100.0% +6 0 1 = 1 1 1 = 0 0 1 = 1 = = = 1 0 = = 1 0 0 = 1 = 1 = = 1 0 –   Demolito 2019-04-27 64-bit 2986 +19−19 (−41) 22 − 10(+18−6=8) 68.8%22.0 / 32 100.0% +94 1 = = 1 = 1 1 1 1 = = 1 0 1 1 1 0 0 1 1 0 1 1 1 0 = 1 = 1 0 1 = –   Wasp 3.0 64-bit 2985 +12−12 (−42) 15.5 − 16.5(+6−7=19) 48.4%15.5 / 32 100.0% −50 = = = = 0 = = = 1 = = = 1 0 0 0 1 1 = 0 = = = = 0 1 = 1 = = = 0 –   Rodent III 0.238 64-bit 2983 +15−14 (−44) 13 − 9(+7−3=12) 59.1%13.0 / 22 100.0% +9 0 = 1 = = = 1 = 0 = = = = = = 1 0 1 1 1 = 1 –   Demolito 2018-10-29 64-bit 2979 +15−15 (−48) 18.5 − 11.5(+13−6=11) 61.7%18.5 / 30 100.0% +26 1 0 = 1 1 1 1 1 1 1 0 1 = = 0 1 0 = 0 1 = = 1 = = = 0 = = 1 –   Pirarucu 2.9.5 64-bit 2967 +19−19 (−60) 2.5 − 1.5(+2−1=1) 62.5%2.5 / 4 100.0% +32 1 = 0 1 –   Rybka 2.3.2a 64-bit 2962 +11−11 (−65) 10 − 4(+7−1=6) 71.4%10.0 / 14 100.0% +71 = = 1 = 1 = 1 1 1 1 = 0 1 = –   Naum 4 64-bit 2955 +14−14 (−72) 8.5 − 5.5(+6−3=5) 60.7%8.5 / 14 100.0% −3 1 0 = = 1 = 1 1 0 0 = 1 = 1 –   Amoeba 3.0 64-bit 2954 +18−18 (−73) 8 − 4(+5−1=6) 66.7%8.0 / 12 100.0% +29 = 0 1 = = = 1 = 1 1 1 = –   Deuterium 2019.1.36.50 64-bit 2954 +17−17 (−73) 4.5 − 3.5(+3−2=3) 56.3%4.5 / 8 100.0% −30 1 = 0 0 1 = = 1 –   Wasp 2.6 64-bit 2948 +13−13 (−79) 2.5 − 1.5(+2−1=1) 62.5%2.5 / 4 100.0% +13 = 1 1 0 –   chess22k 1.8 64-bit 2931 +21−21 (−96) 21.5 − 12.5(+16−7=11) 63.2%21.5 / 34 100.0% −11 = 1 1 = 0 0 1 1 1 1 0 = 1 = 1 1 1 1 1 = = 1 0 1 0 = 0 = 1 = 0 = 1 = –   Crafty 25.2 64-bit 2931 +11−11 (−96) 14 − 4(+10−0=8) 77.8%14.0 / 18 100.0% +80 1 1 1 1 1 = 1 = = 1 1 = = 1 1 = = = –   Amoeba 2.8 64-bit 2927 +13−13 (−100) 21.5 − 8.5(+17−4=9) 71.7%21.5 / 30 100.0% +49 = 1 0 1 0 1 = = 0 1 1 1 1 1 1 1 = 1 0 = 1 1 = 1 1 1 1 = = = –   Bobcat 8.0 64-bit 2924 +13−13 (−103) 13.5 − 8.5(+9−4=9) 61.4%13.5 / 22 100.0% −28 0 = 1 1 1 = 1 = 0 0 = 1 1 = 0 = 1 = 1 = 1 = –   Cheng 4.39 64-bit 2922 +11−11 (−105) 9.5 − 4.5(+6−1=7) 67.9%9.5 / 14 100.0% 0 = = 1 = = 1 1 0 = 1 = 1 1 = –   Dirty CUCUMBER 64-bit 2920 +14−14 (−107) 7 − 5(+4−2=6) 58.3%7.0 / 12 100.0% −53 1 1 1 = 1 0 = = = = = 0 –   Deuterium 2018.1.35.514 64-bit 2914 +13−13 (−113) 31 − 11(+24−4=14) 73.8%31.0 / 42 100.0% +48 1 1 1 = = 1 = 1 1 1 0 1 = 1 1 1 1 = = 1 1 = = 1 = = = 1 0 1 1 1 0 1 1 1 1 = 0 1 = = –   Amoeba 2.6 64-bit 2913 +20−20 (−114) 12 − 2(+10−0=4) 85.7%12.0 / 14 100.0% +147 1 1 = 1 1 1 1 = 1 1 1 1 = = –   Quazar 0.4 64-bit 2906 +10−10 (−121) 11 − 4(+9−2=4) 73.3%11.0 / 15 100.0% +46 1 1 = = 1 1 1 = = 0 1 1 0 1 1 –   Amoeba 2.7 64-bit 2906 +14−14 (−121) 1.5 − 2.5(+1−2=1) 37.5%1.5 / 4 100.0% −213 = 0 0 1 –   Atlas 3.91 64-bit 2902 +14−14 (−125) 5.5 − 2.5(+4−1=3) 68.8%5.5 / 8 100.0% −3 1 1 0 1 1 = = = –   chess22k 1.7 64-bit 2900 +22−22 (−127) 11 − 3(+9−1=4) 78.6%11.0 / 14 100.0% +75 1 1 1 1 1 1 = = 1 = = 1 1 0 –   Winter 0.5 64-bit 2895 +17−17 (−132) 3 − 1(+2−0=2) 75.0%3.0 / 4 100.0% +25 1 = 1 = –   Ethereal 8.62 64-bit 2885 +24−24 (−142) 8 − 6(+5−3=6) 57.1%8.0 / 14 100.0% −97 = 0 = = 1 0 = = 1 1 1 = 0 1 –   Crafty 25.3 64-bit 2885 +74−76 (−142) 2 − 2(+1−1=2) 50.0%2.0 / 4 100.0% −151 1 = 0 = –   Nemo 1.0.1 64-bit 2848 +12−12 (−179) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Tucano 7.07 64-bit 2843 +17−17 (−184) 32 − 8(+27−3=10) 80.0%32.0 / 40 100.0% +38 1 1 = 1 0 1 0 = 1 1 = 1 = = 1 1 = = = 1 = 1 1 1 0 1 1 1 1 1 1 1 1 1 = 1 1 1 1 1 –   Bison 9.11 64-bit 2756 +13−13 (−271) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   GreKo 2018.02 64-bit 2650 +24−24 (−377) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Colossus 2008b 2644 +13−13 (−383) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Counter 2.6 64-bit 2634 +25−25 (−393) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   K2 0.87 2584 +18−17 (−443) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Ufim 8.02 2544 +12−12 (−483) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Eeyore 1.52 64-bit 2445 +18−18 (−582) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Ifrit m1.8 64-bit 2412 +18−18 (−615) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Anechka 0.08 2300 +19−19 (−727) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Zeus 1.29 2299 +20−20 (−728) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Zevra 1.8.4 r650 64-bit 2236 +26−26 (−791) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   Uralochka 1.1b 2218 +18−18 (−809) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1 –   ChessAlex 2.0r4 2205 +21−21 (−822) 1 − 0(+1−0=0) 100.0%1.0 / 1 100.0% +INF 1\n\nRating changes by day", null, "Rating changes with played games", null, "Created in 2005-2013 by CCRL team Last games added on October 19, 2019" ]
[ null, "http://ccrl.chessdom.com/ccrl/4040/rating-history-by-day-graphs/SmarThink_1_98_64-bit.png", null, "http://ccrl.chessdom.com/ccrl/4040/rating-history-by-day-graphs-2/SmarThink_1_98_64-bit.png", null ]
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http://www.conversion-website.com/speed/speed-of-light-to-kilometer-per-hour.html
[ "# Speed of light to kilometers per hour (c to km/h)\n\n## Convert speed of light to kilometers per hour\n\nSpeed of light to kilometers per hour converter above calculates how many kilometers per hour are in 'X' speed of light (where 'X' is the number of speed of light to convert to kilometers per hour). In order to convert a value from speed of light to kilometers per hour (from c to km/h) just type the number of c to be converted to km/h and then click on the 'convert' button.\n\n## Speed of light to kilometers per hour conversion factor\n\n1 speed of light is equal to 1079252847.9366 kilometers per hour\n\n## Speed of light to kilometers per hour conversion formula\n\nSpeed(km/h) = Speed (c) × 1079252847.9366\n\nExample: Consider a speed of 301 speed of light. Below are the steps to convert them to kilometers per hour.\n\nSpeed(km/h) = 301 ( c ) × 1079252847.9366 ( km/h / c )\n\nSpeed(km/h) = 324855107228.92 km/h or\n\n301 c = 324855107228.92 km/h\n\n301 speed of light equals 324855107228.92 kilometers per hour\n\n## Speed of light to kilometers per hour conversion table\n\nspeed of light (c)kilometers per hour (km/h)\n77554769935.5562\n99713275631.4294\n1111871781327.303\n1314030287023.176\n1516188792719.049\n1718347298414.922\n1920505804110.795\n2122664309806.669\n2324822815502.542\n2526981321198.415\n2729139826894.288\n2931298332590.161\n3133456838286.035\n3335615343981.908\n3537773849677.781\nspeed of light (c)kilometers per hour (km/h)\n250269813211984.15\n350377738496777.81\n450485663781571.47\n550593589066365.13\n650701514351158.79\n750809439635952.45\n850917364920746.11\n9501025290205539.8\n10501133215490333.4\n11501241140775127.1\n12501349066059920.7\n13501456991344714.4\n14501564916629508.1\n15501672841914301.7\n16501780767199095.4\n\nVersions of the speed of light to kilometers per hour conversion table. To create a speed of light to kilometers per hour conversion table for different values, click on the \"Create a customized speed conversion table\" button.\n\n## Related speed conversions\n\nBack to speed of light to kilometers per hour conversion\n\nTableFormulaFactorConverterTop" ]
[ null ]
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https://www.real-world-physics-problems.com/forces.html
[ "# Forces\n\nThe concept of forces is fundamental for solving statics and dynamics problems. If we know the forces that are acting on an object we can determine how it moves. Conversely, if we know how an object moves we can calculate the forces acting on it.\n\nThis latter point needs to be expanded on. In order to accurately determine the forces acting on an object we must know how the object is moving relative to an inertial reference frame. Equations of motion have been developed which relate the forces acting on an object to its motion (in particular, the acceleration), as measured from an inertial reference frame.\n\nIf the sum of the forces acting on an object is zero, then that object has zero acceleration relative to an inertial reference frame. Conversely, if the sum of the forces acting on an object is not zero, then that object is accelerating relative to an inertial reference frame.\n\nThe reverse is also true. If an object has zero acceleration relative to an inertial reference frame, the sum of the forces acting on that object is zero. Conversely, if an object is accelerating relative to an inertial reference frame, the sum of the forces acting on that object is not zero.\n\nThe fundamental nature of forces is broken down in Newton's Laws.\n\nThe force or forces acting on an object is always due to: (1) Contact with another object, and/or (2) A body force acting on it, such as gravity, or a magnetic field.\n\nForces are always depicted as vectors acting at some location on an object, as shown below (for example). The forces are given as: F1, F2,..., Fn.", null, "However, representing forces as vectors is merely a mathematical convenience for solving problems using the equations of motion.\n\nBut, forces don’t actually exist as vectors in real-world problems. To understand the reason for this we must look back at points (1) and (2), listed above.\n\nWhen an object touches another object there is contact, not at an infinitely small point, but over an area of finite size. Thus, it is more suitable to speak in terms of a pressure that acts on the objects over the contact area. This pressure in turn, when multiplied by the contact area, gives the resultant force acting on each object. So, the force acting on an object (due to contact with another object) is actually a resultant force (based on pressure times area), which is commonly represented as a vector in the equations of motion. This is done for mathematical convenience.\n\nFor example, let’s say we have a man sitting on the edge of a crate. We represent his weight by a resultant force vector F (as shown).", null, "In addition, there is also a resultant contact force acting on the bottom of the crate (and pushing upwards) due to contact with the floor. As explained before, this resultant force is the result of a pressure that acts over the area in contact with the floor. The bottom of the crate is the contact area with the floor. Let's look more closely at this pressure distribution.\n\nThe pressure distribution acting on the bottom of the crate might look something like this:", null, "We can replace this pressure distribution with an equivalent resultant force (FR) acting at a certain distance a from the right edge, as shown below:", null, "To illustrate by way of example, let’s assume that the pressure distribution on the bottom of the crate only varies in the x-direction, as shown in the diagram below.", null, "Assume that the width of the crate into the page is b, and that the length (along the x-direction) is L.\n\nThe resultant force FR is calculated using integration over the contact area:", null, "The distance a is the distance to the centroid of the pressure curve P(x). This is calculated using the following formula:", null, "The resultant force FR acting at distance a can replace the pressure distribution acting on the bottom of the crate, as shown below.", null, "If we were to apply the equations of motion to the crate, the force FR would be added to the force balance of the force equations, and the moment (caused by FR) would be added to the moment balance of the moment equations. The moment (caused by FR) is calculated knowing the magnitude of FR and its line of action, which is at a distance a from the right edge. For example, let's take the moment of FR about point O. Using the sign convention shown, this moment is equal to (La)FR. This would be added to the moment balance of the moment equations.\n\nComing back to point (2) from before, if a body force such as gravity is acting on an object, the body force “pulls” equally on all the mass elements in it. For the sake of mathematical convenience, the total gravity force pulling on the entire body is also represented as a single resultant force vector acting at a certain location inside the object (and pointing in the direction of gravity). The location of this resultant gravity force (Fg) is at the center of mass G of the object, as shown below.", null, "The magnitude of the vector Fg is equal to mg, where m is the mass of the object and g is the acceleration due to gravity.\n\nKnowing the magnitude and direction of vector Fg, and the location of the center of mass G of the object, we can correctly account for it in the force and moment equations used for solving statics and dynamics problems." ]
[ null, "https://www.real-world-physics-problems.com/images/forces_1b.png", null, "https://www.real-world-physics-problems.com/images/forces_2b.png", null, "https://www.real-world-physics-problems.com/images/forces_3b.png", null, "https://www.real-world-physics-problems.com/images/forces_4b.png", null, "https://www.real-world-physics-problems.com/images/forces_5b.png", null, "https://www.real-world-physics-problems.com/images/forces_6b.png", null, "https://www.real-world-physics-problems.com/images/forces_7b.png", null, "https://www.real-world-physics-problems.com/images/forces_8b.png", null, "https://www.real-world-physics-problems.com/images/forces_9b.png", null ]
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http://marc-abramowitz.com/archives/2006/06/15/perl-is-evil/
[ "# Perl is evil\n\nWhat other language would let you do this?\n\n``` ''=~( '(?{' .('`' |'%') .('[' ^'-')\n.('`' |'!') .('`' |',') .'\"'. '\\\\\\$'\n.'==' .('[' ^'+') .('`' |'/') .('['\n^'+') .'||' .(';' &'=') .(';' &'=')\n.';-' .'-'. '\\\\\\$' .'=;' .('[' ^'(')\n.('[' ^'.') .('`' |'\"') .('!' ^'+')\n.'_\\\\{' .'(\\\\\\$' .';=('. '\\\\\\$=|' .\"\\|\".( '`'^'.'\n).(('`')| '/').').' .'\\\\\"'.+( '{'^'['). ('`'|'\"') .('`'|'/'\n).('['^'/') .('['^'/'). ('`'|',').( '`'|('%')). '\\\\\".\\\\\"'.( '['^('(')).\n'\\\\\"'.('['^ '#').'!!--' .'\\\\\\$=.\\\\\"' .('{'^'['). ('`'|'/').( '`'|\"\\&\").(\n'{'^\"\\[\").( '`'|\"\\\"\").( '`'|\"\\%\").( '`'|\"\\%\").( '['^(')')). '\\\\\").\\\\\"'.\n('{'^'[').( '`'|\"\\/\").( '`'|\"\\.\").( '{'^\"\\[\").( '['^\"\\/\").( '`'|\"\\(\").(\n'`'|\"\\%\").( '{'^\"\\[\").( '['^\"\\,\").( '`'|\"\\!\").( '`'|\"\\,\").( '`'|(',')).\n'\\\\\"\\\\}'.+( '['^\"\\+\").( '['^\"\\)\").( '`'|\"\\)\").( '`'|\"\\.\").( '['^('/')).\n'+_,\\\\\",'.( '{'^('[')). ('\\\\\\$;!').( '!'^\"\\+\").( '{'^\"\\/\").( '`'|\"\\!\").(\n'`'|\"\\+\").( '`'|\"\\%\").( '{'^\"\\[\").( '`'|\"\\/\").( '`'|\"\\.\").( '`'|\"\\%\").(\n'{'^\"\\[\").( '`'|\"\\\\$\").( '`'|\"\\/\").( '['^\"\\,\").( '`'|('.')). ','.(('{')^\n'[').(\"\\[\"^ '+').(\"\\`\"| '!').(\"\\[\"^ '(').(\"\\[\"^ '(').(\"\\{\"^ '[').(\"\\`\"|\n')').(\"\\[\"^ '/').(\"\\{\"^ '[').(\"\\`\"| '!').(\"\\[\"^ ')').(\"\\`\"| '/').(\"\\[\"^\n'.').(\"\\`\"| '.').(\"\\`\"| '\\$').\"\\,\".( '!'^('+')). '\\\\\",_,\\\\\"' .'!'.(\"\\!\"^\n'+').(\"\\!\"^ '+').'\\\\\"'. ('['^',').( '`'|\"\\(\").( '`'|\"\\)\").( '`'|\"\\,\").(\n'`'|('%')). '++\\\\\\$=\"})' );\\$:=('.')^ '~';\\$~='@'| '(';\\$^=')'^ '[';\\$/='`';\n```\n\n(from 99 Bottles of Beer).\n\nYes, this is a valid Perl program! Paste it into a text file and run it – don’t worry, it won’t nuke all your files.\n\nA work of art. A completely and utterly unmaintainable work of art.\n\nSick.", null, "## 8 thoughts on “Perl is evil”\n\n1.", null, "Neil on said:\n\nThat is totally sick! I am not a perl fan, but man that rocks!\n\n2.", null, "glenn on said:\n\nWhat comes up? Can we get a screen capture???\n\n3. You can take any program and paint it into any shape using Acme::Eyedrops from the CPAN. So, this wasn’t that hard to do, once someone had already done the hard part. 🙂\n\n4.", null, "Mario on said:\n\nI can’t believe that works.\n\n5.", null, "Alpheus on said:\n\nThis is impressive, in a sick sort of way. There are those who believe that this shows the power of Perl, to which I would have to say: Brainf*** must be a powerful language, too! but I’m not going to use it any time soon (for any serious work, at least…).\n\n6.", null, "Jason on said:\n\nThis is absolutely nuts. What, did it descend from the seventh heaven on the night of Al-Kadr? Just the sort of excuse I need to run from Perl.\n\n7.", null, "Graham Nicholls on said:\n\n@Jason. You shouldn’t need any further excuse to run from Perl. With Python, Lua, my favourite Ruby, and other languages around, Perl is as obsolete as the floppy disk." ]
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https://www.westernsydney.edu.au/crm/colloquia/past_colloquia
[ "## Past Colloquia\n\nAutomaton semigroups: new examples and non-examples  Tara Brough  - Thursday, 11 February 2016\n\nAutomaton semigroups are semigroups of endomorphisms of rooted trees generated by the actions of Mealy automata (deterministic synchronous transducers).  They act by 'self-similar' endomorphisms, are finitely generated, residually finite and have solvable word problem. Until recently, only one finitely generated residually finite semigroup had been shown not to be an automaton semigroup.  I will prove in this talk that no subsemigroup of the natural numbers (under addition) is an automaton semigroup, thus giving an infinite family of new residually finite non-examples. I will also give an overview of some new ways to build automaton semigroups from known examples, using various standard semigroup constructions such as free products, wreath products and strong semilattices. This is joint work with Alan Cain (Universidade Nova de Lisboa).\n\nMinimal faithful permutation representations of groups  David Easdown, University of Sydney  -  Wednesday, 23 September 2015\n\nThe minimal faithful degree mu(G) of a finite group G is the least nonnegative integer n such that G embeds in the symmetric group on n letters. We sketch a proof of what appears to be the nontrivial fact that mu(G x G)= mu(G) if and only if G is trivial. The proof relies on a theorem of Wright that mu(G x H)=mu(G)+mu(H) if G x H is nilpotent. We also construct a finite group G that does not decompose nontrivially as a direct product, but such that mu(G x H) = mu(G) for an arbitrarily large direct product H of elementary abelian groups (with mixed primes). A simplification of the construction depends on the existence of infinitely many primes that do not have the Mersenne property, which itself appears to be nontrivial, and a consequence of the Green-Tao theorem.  (A prime p is Mersenne with respect to an integer q if p = 1+q+...+q^k for some k.)\n\nEquitable and Fair Colourings of Graphs and Graph Decompositions  Chris Rodger, Auburn University (US)  -  Thursday, 6 August 2015\n\nIt is often useful to partition mathematical objects so that some sort of fair division is the result. In this talk, several notions of fairness will be discussed in the realm of edge-colourings and block-colourings of graph decompositions. In particular, equitable colourings require that at each vertex the colours be shared as evenly as possible among the incident structures (edges or blocks), and some recent results in this area will be presented. Also, fair decompositions attempt to share edges between different elements of a vertex partition of a graph as evenly as possible among the colour classes, and again recent results will be discussed, one of which surprisingly gives rise to symmetric versions of Sudoku squares.\n\nSelection against off-target ncRNA:mRNA interactions explains protein expression levels  Paul Gardner, University of Canterbury (NZ)  -  Wednesday, 8 July 2015\n\nThat messenger RNA (mRNA) abundances should broadly correlate with protein abundance is a critical assumption in transcriptomics. However, protein and mRNA abundances show low correlation. In principle, much of the variation in protein and mRNA levels should be predictable from genomic sequences. Some variation can be accounted for by mRNA secondary structure and codon usage, both of which influence protein abundance. However, these features only partially explain this discrepancy. Here we present evidence that a third process impacts mRNA translation: interactions between noncoding RNAs and mRNAs. We show that there has been strong selection for avoidance of off-target ncRNA:mRNA interactions across prokaryotes, and that, such interactions have a greater impact on protein abundance than either mRNA secondary structure or codon usage. By generating synonymously variant green fluorescent protein (GFP) mRNAs with different levels of ncRNA:mRNA crosstalk, we show that GFP levels correlate well with modelled protein abundances. Taking crosstalk interactions into account enables precise modulation of protein abundance.\n\nSolving word equations  Murray Elder (University of Newcastle)  -  Wednesday, 13 May 2015\n\nAbstract for first talk:  If I give you two strings of letters (called \"words\") - abbbaaa and abbaaa - and ask you to decide if they are identical, you can do that pretty easily. Now if I say X, Y are \"unknowns\" that you are allowed to replace by any words to get identical words in aXXb and YbX, that is a problem. In this case: Y has to start with a, and X has to end with b or be replaced by nothing (you are allowed to do that, a string of length 0). So, for instance, [Y = abb; X = bb] and [Y = a; X = nothing] are solutions. One would like to answer the following questions:\n1. In general (for any two words with unknowns of any length), is there a procedure to answer YES or NO if there is any solution?\n2. Formulate a procedure (an algorithm) to find all solutions.\n3. Express the set of all solutions in some reasonable way, that is, give some systematic description.\n\n1. was answered by Makanin in 1977; before that it was thought maybe the problem was undecidable (meaning that no algorithm exists; there are similar problems which are undecidable), but his answer was really complicated: you couldn't practically use the procedure he described; is was a purely theoretical result.\n\n2. was answered by Razborov in 1980s, building on Makanin's result, so again complicated.\n\nWe answered 1,2,3 giving a much simpler algorithm, which runs in very low space complexity (we claim optimal), that is, the amount of computer memory required is as small as you could expect for any algorithm that solves the problem. Makanin-Razborov's solution needed exponential space (which is practically infeasible for a computer). Our description of all solutions is really nice: we give a finite graph that you follow around to produce all solutions. In addition, we really solved a (seemingly harder) problem where the letters a, b, ... have \"inverses\" a-1, b-1, ... which cancel out: aa-1 -> nothing, and a-1a -> nothing. So, for instance, baa-1a-1b-1bb-1 cancels to ba-1b-1. So the equation aXXb = YbX also has the solution X = b-1Y = ab-1 (and many more). Our proof uses data compression (the same as when you send a file in an email as a zip file to make it smaller), probability and algebra. It builds on previous work by Plandowski, and Jez. This is joint work with Laura Ciobanu, Neuchatel and Volker Diekert, Stuttgart.\n\nAbstract for second talk:  I will give some details of the proof of our result - that the set of all solutions to an equation over a free group or free monoid has a simple description encoded by a finite graph, that can be constructed in space O(n log n):\n\n- reduction from an equation over a free group to an equation over a free monoid with involution with constraints,\n- extended equations and partial commutation,\n- construction of the finite graph encoding all solutions,\n- two propositions: any path in the graph from an initial to final vertex is a solution; and any solution is realised by a finite path in the graph from an initial to final vertex, - algorithm to prove the second proposition - block and pair compression. This is joint work with Laura Ciobanu, Neuchatel and Volker Diekert, Stuttgart.\n\nGenome Rearrangements and the Hultman Numbers  Pedro Feijao (University of Bielefeld)  -  Wednesday, 22 April 2015\n\nGenomes are subject to mutations and rearrangements in the course of evolution. Large-scale rearrangements can change the number of chromosomes and/or the positions and orientations of large blocks of DNA. A classical problem in comparative genomics is to compute the rearrangement distance, that is, the minimum number of rearrangements required to transform a given genome into another genome. The breakpoint graph is a discrete structure that has proven to be effective in solving\nrearrangement distance problems, and the number of cycles in its cycle decomposition is directly related to many rearrangement distances. For a fixed \\$k\\$, the number of linear unichromosomal genomes (signed or unsigned) with \\$n\\$ elements such that the induced breakpoint graph has \\$k\\$ disjoint cycles, known as the Hultman number, has been already determined. In this talk I will show how to extend these results to multichromosomal genomes and discuss how these series can be used to calculate the distribution and expected value of the rearrangement distance between random genomes.\n\nSymbolic dynamics and Leavitt path algebras  Pere Ara (University of Autonoma, Barcelona)  -  Tuesday, 11 November 2014\n\nThis is a survey talk, covering the recent new connections between the two topics of symbolic dynamics and Leavitt path algebras.\n\nExceptional Quotients of Permutation Groups  Neil Saunders (University of Bristol)  -  Monday, 13 October 2014\n\nThe minimal permutation degree of a finite group G is the smallest non-negative integer n such that G embeds inside Sym(n). This invariant is easy to define but very difficult to calculate in general. Moreover, it doesn't behave well under algebraic constructions such as direct product and homomorphic image. For example, it is possible for the minimal degree of a homomorphic image to be strictly larger than that of the group -- such groups are called 'exceptional'. In this talk, I will describe how this invariant may be calculated by a greedy algorithm for nilpotent groups and report on recent work with Britnell and Skyner on the classification of exceptional groups of order p5.\n\nMatrices that *almost* commute  Adam Peder Wie Sørensen (University of Wollongong)  -  Monday, 25 August 2014\n\nIn this talk we will look at square matrices A and B that satisfy that AB is close to BA. That is to say, matrices A and B that almost commute. I will explain what it means (to operator algebraists) that two matrices are close. We will look at the questions of whether one can find exactly commuting matrices close to almost commuting ones. We also look at how this question changes if we impose additional conditions on our matrices, say that they are unitary or real or something else.\nThe question has drawn interest from some mathematicians just because it is a natural question. Lately questions of this form has also drawn interest from physicists due to its application in the field of so-called topological insulators. I will attempt to justify the connection to physics. I will only assume basic knowledge a of linear algebra and little familiarity with continuity.\n\nAn introduction to higher rank graphs and their C*-algebras  Alex Kumjian (University of Nevada, Reno)  -  Tuesday, 19 August 2014\n\nHigher rank graphs were introduced more than a decade ago as a generalization of directed graphs for the purpose of enlarging the class of C*-algebras associated to directed graphs. This was inspired by the examples of C*-algebras arising from certain group actions on buildings in the work of Roberts and Steger. We discuss some examples and fundamental properties of higher rank graphs and define the associated C*-algeras. If time permits we will discuss the homology and cohomology theory of these objects.\n\nWhen Artin groups are sufficiently large...  Sarah Rees (University of Newcastle, UK)  -  Monday, 14 July 2014\n\nThe family of Artin groups contains a wide range of groups, including braid groups, free groups, free abelian groups and much else, and its members exhibit a wide range of behaviour. Many problems remain open for the family as a whole, including the word problem, but are solved for particular subfamilies. The groups of finite type (mapping onto finite Coxeter groups), right-angled type (with each mij ∈ {2, ∞}), large and extra-large type (with each mij ≥ 3 or 4), FC type (every complete subgraph of the Coxeter graph corresponds to a finite type subgroup) have been particularly studied. After introducing Artin groups and surveying what is known, I will describe recent work with Derek Holt and (sometimes) Laura Ciobanu, Eddy Godelle, dealing with a big collection of Artin groups, containing all the large groups, which we call 'sufficiently large'. For those Artin groups Holt and I have elementary descriptions of the sets of geodesic and shortlex geodesic words, and can reduce any input word to either form. So we can solve the word problem, and prove the groups shortlex automatic. And, following Appel and Schupp we can solve the conjugacy problem in extra-large groups in cubic time. For many of the large Artin groups, including all extra-large groups, Holt, Ciobanu and I can deduce the rapid decay property and verify the Baum- Connes conjecture. And although our methods are quite different from those of Godelle and Dehornoy for spherical-type groups, we can pool our resources and derive a weak form of hyperbolicity for many, many Artin groups. I'll explain some background for the problems we attach, and outline their solution.\n\nDiagram algebras and representations   Peter Jarvis (School of Physical Sciences, University of Tasmania)  -  Thursday, 27 February 2014\n\nAn informal introduction to some aspects of matrix groups and their characters, in the context of Schur-Weyl duality, related to recent investigations of an interesting `triapsid' monoid. Joint work with Nick Ham, Des Fitzgerald, Bertfried Fauser and Ronald King.\n\nHomogenisation for deterministic maps and multiplicative noise  Georg Gottwald (University of Sydney)  -  Monday, 21 October 2013\n\nWhereas diffusion limits of stochastic multi-scale systems have a long and successful history, the case of constructing stochastic parameterisations of chaotic deterministic systems has been much less studied. We present rigorous results of convergence of a chaotic slow-fast system to a stochastic differential equation with multiplicative noise. Furthermore we present rigorous results for chaotic slow-fast maps, occurring as numerical discretisations of continuous time systems. This raises the issue of how to interpret certain stochastic integrals; surprisingly the resulting integrals of the stochastic limit system are generically neither of Stratonovich nor of Ito type in the case of maps. It is shown that the limit system of a numerical discretisation is different to the associated continuous time system. This has important consequences when interpreting the statistics of long time simulations of multi-scale systems - they may be very different to the one of the original continuous time system which we set out to study.\n\nComputing with infinite groups  Murray Elder (University of Newcastle)  -  Monday, 04 November 2013\n\nI will talk about two projects. The first is a recently submitted paper on counting the number of words of generators that equal the identity in a group, in this case the Baumslag-Solitar groups. Using some techniques and tricks from enumerative combinatorics and statistical physics, we prove that the generating function Σcnzn (where cn is the number of words of length n equal to the identity) is D-finite, and find asymptotic growth rates for these numbers. The second is a paper that appeared earlier this year on computing normal forms for group elements in low space complexity. We found many groups for which there is an algorithm that takes input a word in the generators and puts it into a standard (normal) form that runs in logspace. I will give some examples and maybe the audience can add some more. The first part is joint work with Andrew Rechnitzer, Buks van Rensburg, Tom Wong; the second with Gillian Elston and Gretchen Ostheimer.\n\nGeometric modular representation theory  Anthony Henderson (University of Sydney)  -  Monday, 19 August 2013\n\nRepresentation theory is one of the oldest areas of algebra, but many basic questions in it are still unanswered. This is especially true in the modular case, where one considers vector spaces over a field F of positive characteristic; typically, complications arise for particular small values of the characteristic. For example, from a vector space V one can construct the symmetric square S2(V), which is one easy example of a representation of the group GL(V). One would like to say that this representation is irreducible, but that statement is not always true: if F has characteristic 2, there is a nontrivial invariant subspace. Even for GL(V), we do not know the dimensions of all irreducible representations in all characteristics. In this talk, I will introduce some of the main ideas of geometric modular representation theory, a more recent approach which is making progress on some of these old problems. Essentially, the strategy is to re-formulate everything in terms of homology of various topological spaces, where F appears only as the field of coefficients and the spaces themselves are independent of F; thus, the modular anomalies in representation theory arise because homology with modular coefficients is detecting something about the topology that rational coefficients do not.\n\nResidues and duality in algebraic geometry  Amnon Neeman (Australian National University)  -  Monday, 5 August 2013\n\nOn a compact Riemann surface the sum of the residues of a meromorphic function must vanish.  Starting with this simple observation once can develop an \"obstruction theory\" to the existence of functions with prescribed local behaviour, and this leads one to several theorems. We will develop the theory starting at an elementary level, but hopefully reach some statements of current research interest.\n\nComputing with finite semigroups James Mitchell (University of St Andrews)  -  Friday, 5 July 2013\n\nIn this talk I will discuss the problem of how to compute a finite semigroup. What does it mean to 'compute' a finite semigroup? It means to find structural information about that semigroup, for example, calculating their Green's classes, size, elements, group of units, minimal ideal, small generating sets, testing membership, finding the inverses of a regular element, factorizing elements over the generators, and so on. I will review what is known about computing with finite semigroups and give an overview of recently developed functionality in the computer algebra system GAP. No prior knowledge of computing or of semigroup theory will be assumed. Time permitting, I will demonstrate the Semigroups software package for computing with semigroups of transformations and partial permutations, and describe some recent theoretical advances that will allow the methods in Semigroups to be applied to several other natural types of semigroup including monoids of partitions.\n\nThe lattice of subsemigroups of the semigroup of all mappings on an infinite set James Mitchell (University of St Andrews)  -  Friday, 5 July 2013\n\nIn this talk I will review some recent results relating to the lattice of subgroups of the symmetric group and its semigroup theoretic counterpart, the lattice of subsemigroups of the full transformation semigroup on an infinite set. As might be expected, these lattices are extremely complicated. I will discuss several results that make this comment more precise, and shed light on the maximal proper sub(semi)groups in the lattice. I will also discuss a natural related partial order, introduced by Bergman and Shelah, which is obtained by restricting the type of sub(semi)groups and considering classes of, rather than individual, (semi)groups. In the case of the symmetric group, this order is very simple but in the case of the full transformation semigroup it is again very complex.\n\nAssociation and aggregation for contingency table analysis Eric Beh (University of Newcastle)  -  Monday, 15 April 2013\n\nFor reasons of confidentiality, government departments and other agencies often release information to the public that has been aggregated.  When working with aggregated data it is important to ensure that one keeps in mind any loss of information (due to the aggregation process) when making conclusions at the individual level. There are a variety of techniques that exist which analyse aggregate data and these generally lie within the family of ecological inference techniques. This presentation is not about those techniques.  Rather, we shall consider a very simple illustrative example to highlight the loss of information due to aggregation and show how correspondence analysis can be used as a means of visually identifying the source of such loss. This presentation will explore the impact of aggregation using the standard statistical techniques of simple linear regression and the chi-squared test of independence.\n\nAdventures with group theory: counting and constructing polynomial invariants for applications in quantum entanglement and molecular phylogenetics [or: the Power of Plethysm]  Peter Jarvis (University of Tasmania)  -  Monday, 21 January 2013\n\nIn many modelling problems in mathematics and physics, a standard challenge is dealing with several repeated instances of a system under study.  If linear transformations are involved, then the mathematical machinery of tensor products steps in, and it is the job of group theory to control how the relevant symmetries lift from a single system, to having many copies.  At the level of group characters, the construction which does this is called PLETHYSM. In this talk all this will be contextualised via two case studies: entanglement invariants for multipartite quantum systems, and Markov invariants for tree reconstruction in molecular phylogenetics.  By the end of the talk, listeners will have understood why Alice, Bob and Charlie love Cayley's hyperdeterminant, and they will know why the three squangles -- polynomial beasts of degree 5 in 256 variables, with a modest 50,000 terms or so -- can tell us a lot about quartet trees!\n\nHigher homotopy, higher groupoids  Steve Lack (Macquarie University)  -  Monday, 15 October 2012\n\nTopology is a branch of geometry in which objects are regarded as being the same if one can be transformed into the other by bending or stretching (tearing and glueing are not allowed). It is sometimes also called \"rubber sheet geometry\". Homotopy theory is a part of topology in which the geometric objects (called spaces) are studied via algebraic ones, such as groups and groupoids. In this talk, I shall describe groupoids, and how to associate to any space a groupoid, called the fundamental groupoid, which can be seen as measuring the \"one-dimensional holes\" in the space. I shall then go on to describe higher-dimensional analogues of groupoids, and how they can be used to measure the higher-dimensional holes in spaces.\n\nThe Breaking of JN-25  John Mack (The University of Sydney)  -  Monday, 20 August 2012\n\nJN-25 was the name given by the Allies to the main operational code used by the Imperial Japanese Navy (IJN) during World War II. It was broken into almost immediately after its introduction in mid-1939 by John Tiltman, one of the greatest World War II British code breakers. It continued to be broken throughout the war, and yielded by far the majority of useful signals intelligence regarding IJN operations available to the Allies. At the same time, the Imperial Japanese Army (IJA), using the same cryptographic systems, maintained their security until early 1943, when only one important system was broken. All others defied attack. The talk will describe the coding system used, why the IJN was insecure, and how this was exploited." ]
[ null ]
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https://coasterpedia.net/wiki/Coasterpedia:Manual_of_Style/Products
[ "# Coasterpedia:Manual of Style/Products\n\nThis Manual of Style article covers the standard format for product pages on Coasterpedia.\n\n## Creating a park article\n\nTemplate for coaster products\n```{{Infobox product\n|image =\n|name =\n|status =\n|introduced =\n|discontinued =\n|no-built =\n|first-built =\n|latest-built =\n|last-built =\n|cost =\n|restriction =\n|manufacturer =\n|builder =\n|designer =\n|category1 =\n|category2 =\n|category3 =\n|category4 =\n|dimension1 =\n|dimension2 =\n|riders/train =\n|riders/hour =\n|lift/launch =\n|height =\n|drop =\n|speed =\n|length =\n|duration =\n|inversions =\n|angle =\n|g-force =\n|power =\n}}\nWrite an introduction here!\n==History==\n==Completed attractions==\n{| class=\"wikitable sortable\"\n!Name\n!Park\n!Country\n!Opened\n!Status\n|-\n|}\n```\nTemplate for ride products\n```{{Infobox product\n|image =\n|name =\n|status =\n|introduced =\n|discontinued =\n|no-built =\n|first-built =\n|latest-built =\n|last-built =\n|cost =\n|restriction =\n|manufacturer =\n|builder =\n|designer =\n|category1 =\n|category2 =\n|category3 =\n|category4 =\n|dimension1 =\n|dimension2 =\n|riders/hour =\n|capacity =\n|height =\n|speed =\n|length =\n|angle =\n|g-force =\n|power =\n}}\nWrite an introduction here!\n==History==\n==Completed attractions==\n{| class=\"wikitable sortable\"\n!Name\n!Park\n!Country\n!Opened\n!Status\n|-\n|}\n```" ]
[ null ]
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https://cwiki.apache.org/confluence/display/Hive/Cost-based+optimization+in+Hive
[ "##### Child pages\n• Cost-based optimization in Hive\nGo to start of banner\n\n# Abstract\n\nApache Hadoop is a framework for the distributed processing of large data sets using clusters of computers typically composed of commodity hardware. Over last few years Apache Hadoop has become the de facto platform for distributed data processing using commodity hardware. Apache Hive is a popular SQL interface for data processing using Apache Hadoop.\n\nUser submitted SQL query is converted by Hive to physical operator tree which is optimized and converted to Tez Jobs and is then executed on Hadoop cluster. Distributed SQL query processing in Hadoop differs from conventional relational query engine when it comes to handling of intermediate result sets. Hive query processing often requires sorting and reassembling of intermediate result set; this is called shuffling in Hadoop parlance.\n\nMost of the existing query optimizations in Hive are about minimizing shuffling cost. Currently user would have to submit an optimized query to Hive with right join order for query to be executed efficiently. Logical optimizations in Hive are limited to filter push down, projection pruning and partition pruning. Cost based logical optimizations can significantly improve Apache Hive’s query latency and ease of use.\n\nJoin reordering and join algorithm selection are few of the optimizations that can benefit from a cost based optimizer. Cost based optimizer would free up user from having to rearrange joins in the right order or from having to specify join algorithm by using query hints and configuration options. This can potentially free up users to model their reporting and ETL needs close to business process without having to worry about query optimizations.\n\nCalcite is an open source cost based query optimizer and query execution framework. Calcite currently has more than fifty query optimization rules that can rewrite query tree, and an efficient plan pruner that can select cheapest query plan in an optimal manner. In this paper we discuss how Calcite can be used to introduce Cost Based Logical Optimizer (CBO) in to Apache Hive.\n\nCBO will be introduced in to Hive in a Phased manner. In the first phase, Calcite would be used to reorder joins and to pick right join algorithm so as to reduce query latency. Table cardinality and Boundary statistics will be used for this cost based optimizations.\n\n# 1. INTRODUCTION\n\nHive is a data-warehousing infrastructure on top of Apache Hadoop. Hive takes advantage of Hadoop’s massive scale out and fault tolerance capabilities for data storage and processing on commodity hardware. Hive is designed to enable easy data summarization, ad-hoc querying and analysis of large volumes of data. Hive SQL is the declarative query language, which enables users familiar with SQL to do ad-hoc querying, summarization and data analysis easily.\n\nIn past Hadoop jobs tended to have high latencies and incurred substantial overheads in job submission and scheduling. As a result - latency for Hive queries was generally very high even when data sets involved were very small. As a result Hive was typically used for ETL and not much for interactive queries. With Hadoop2 and Tez the overheads for job submission and job scheduling have gone down significantly. In Hadoop version one, the jobs that could be executed could only be Map-Reduce Jobs.  With Hadoop2 and Tez that limitation no longer apply.\n\nIn Hadoop the output of mapper is sorted and sometimes persisted on the local disk of the mapper. This sorted mapper output is then send to appropriate reducer which then combines sorted results from different mappers.  While executing multiple map-reduce jobs where output of one job needs to be consumed by the successive map-reduce job, the output of preceding map-reduce job needs to be persisted into HDFS; this persistence is costly as the data needs to be copied to other nodes based on the replication factor of HDFS.\n\nHive on top of Hadoop version 1 often had to submit multiple map-reduce jobs to complete query processing. This Map-Reduce job pipeline degraded performance, as the intermediate result set now needs to be persisted to fault tolerant HDFS. Also submitting jobs and scheduling them were relatively costly operations. With Hadoop2 and Tez the cost of job submission and scheduling is minimized. Also Tez does not restrict the job to be only Map followed by Reduce; this implies all of the query execution can be done in a single job without having to cross job boundaries. This would result in a significant cost savings, as the intermediate result sets need not be persisted to HDFS or to even local disk.\n\nQuery optimizations in a relational query engine can be broadly classified as logical query optimizations and physical query optimizations. Logical query optimizations generally refer to query optimizations that can be derived based on relational algebra independent of the physical layer in which query is executed. Physical query optimizations are query optimizations that are cognizant of physical layer primitives. For Hive, the physical layer implies Map-Reduce and Tez primitives.\n\nCurrently logical query optimizations in Hive can be broadly categorized as follows:\n\n• Projection Pruning\n• Deducing Transitive Predicates\n• Predicate Push down\n• Merging of Select-Select, Filter-Filter in to single operator\n• Multi-way Join\n• Query Rewrite to accommodate for Join skew on some column values\n\nPhysical optimizations in Hive can be broadly classified as follows:\n\n• Partition Pruning\n• Scan pruning based on partitions and bucketing\n• Scan pruning if query is based on sampling\n• Apply Group By on the map side in some cases\n• Perform Join on the Mapper\n• Optimize Union so that union can be performed on map side only\n• Decide which table to stream last, based on user hint, in a multi way join\n• Remove unnecessary reduce sink operators\n• For queries with limit clause, reduce the number of files that needs to be scanned for the table.\n• For queries with Limit clause, restrict the output coming from mapper by restricting what Reduce Sink operator generates.\n• Reduce the number of Tez jobs needed for answering user submitted SQL query\n• Avoid Map-Reduce jobs in case of simple fetch query\n• For simple fetch queries with aggregation, perform aggregation without Map-Reduce tasks\n• Rewrite Group By Query to use index table instead of original table\n• Use Index scans when predicates above table scan is equality predicates and columns in predicate have indexes on it.\n\nIn Hive most of the optimizations are not based on the cost of query execution. Most of the optimizations do not rearrange the operator tree except for filter push down and operator merging.  Most of the operator tree mutation is for removing reduce-sink and reducer operator.  Listed below are some of optimization decisions that can benefit from a CBO:\n\n• How to order Join\n• What algorithm to use for a given Join\n• Should the intermediate result be persisted or should it be recomputed on operator failure.\n• The degree of parallelism at any operator (specifically number of reducers to use).\n• Semi Join selection\n\nCalcite is an open source, Apache Licensed, query planning and execution framework. Many pieces of Calcite are derived from Eigenbase Project. Calcite has optional JDBC server, query parser and validator, query optimizer and pluggable data source adapters. One of the available Calcite optimizer is a cost based optimizer based on volcano paper. Currently different pieces of Calcite is used in following projects/products:\n\n• Apache Drill\n• Lucid DB\n• Mondrian/Pentaho", null, "Calcite currently has over fifty cost based optimization rules. Some of the prominent cost based optimization rules are listed below:\n\n• Push Join through Union\n• Push Filter past Table Function\n• Join Reordering\n• Semi Join selection\n• Push Aggregate through Union\n• Pull Aggregate through Union\n• Pull Constants through Aggregate\n• Merge Unions\n\nIn this document we propose to use Calcite’s cost based optimizer, Volcano, to perform Cost Based Optimizations in Hive. We propose to implement Calcite based CBO in a phased manner. Note here that proposal is to use Calcite’s optimizer only and nothing else. Listed below are the envisioned stages of introducing CBO in to Hive using Calcite:\n\n• Phase1 – Join Reordering & Join algorithm Selection\n• Table cardinality and boundary statistics will be used to compute operator cardinality.\n• Hive operator tree will be converted to Calcite operator tree.\n• Volcano optimizer in Calcite will be used to rearrange joins and to pick the join algorithm.\n• Optimized Calcite operator tree would be converted back to Hive AST and will be executed as before. So all of the Hive’s existing optimizations would run on top of Calcite optimized SQL.\n• Phase2 – Add support for Histograms, use other optimizations in Calcite\n• Introduce space efficient histograms\n• Change operator cardinality computation to use histograms\n• Register additional optimization rules available in Calcite like the ones listed above.\n• Phase3 – Code restructuring so that Calcite generates optimized Hive Operator tree\n• Unlike phase1 Hive AST would be directly translated into Calcite operator tree.\n• Optimize Calcite operator tree using Volcano optimizer.\n• Convert optimized Calcite operator tree back into Hive Operator tree. This is unlike phase1 where optimized Calcite operator tree is converted to Hive AST.\n\n# 2. RELATED WORK\n\n## PAPERS\n\n• Query Optimization for Massively Parallel Data Processing\n\nSai Wu, Feng Li, Sharad Mehrotra, Beng Chin Ooi\n\nSchool of Computing, National University of Singapore, Singapore, 117590\n\nSchool of Information and Computer Science, University of California at Irvine\n\n• Profiling, What-if Analysis, and Cost-based Optimization of MapReduce Programs\n\nHerodotos Herodotou Duke University, Shivnath Babu Duke University\n\n• Optimizing Joins in a Map-Reduce Environment\n\nFoto N. Afrati, National Technical University of Athens, Greece\n\nJeffrey D. Ullman, Stanford University USA\n\n• Efficient and scalable statistics gathering for large databases in Oracle 11g\n\nSunil Chakkappen, Thierry Cruanes, Benoit Dageville, Linan Jiang, Uri Shaft, Hong Su, Mohamed Zait , Oracle Redwood Shores CA\n\nhttp://dl.acm.org/citation.cfm?doid=1376616.1376721\n\n• Estimating Distinct (Postgress SQL)\n\nhttp://wiki.postgresql.org/wiki/Estimating_Distinct\n\n• The History of Histograms\n\nYannis Ioannidis, Department of Informatics and Telecommunications, University of Athens\n\nhttp://www.vldb.org/conf/2003/papers/S02P01.pdf\n\n# 3. BACKGROUND\n\n## Hive Query optimization issues\n\nHive converts user specified SQL statement to AST that is then used to produce physical operator tree. All of the query optimizations are performed on the physical operator tree. Hive keeps semantic info separate from query operator tree. Semantic info is extracted during plan generation that is then looked up often during down stream query optimizations. Adding new query optimizations into Hive is often made difficult by the lack of proper logical query plan and due to Semantic info and query tree separation.\n\n## Join algorithms in Hive\n\nHive only supports equi-Join currently. Hive Join algorithm can be any of the following:\n\n### Multi way Join\n\nIf multiple joins share the same driving side join key then all of those joins can be done in a single task.\n\nExample: (R1 PR1.x=R2.a  - R2) PR1.x=R3.b - R3) PR1.x=R4.c - R4\n\nAll of the join can be done in the same reducer, since R1 will already be sorted based on join key x.\n\n### Common Join\n\nUse Mappers to do the parallel sort of the tables on the join keys, which are then passed on to reducers. All of the tuples with same key is given to same reducer. A reducer may get tuples for more than one key. Key for tuple will also include table id, thus sorted output from two different tables with same key can be recognized. Reducers will merge the sorted stream to get join output.\n\n### Map Join\n\nUseful for star schema joins, this joining algorithm keeps all of the small tables (dimension tables) in memory in all of the mappers and big table (fact table) is streamed over it in the mapper. This avoids shuffling cost that is inherent in Common-Join. For each of the small table (dimension table) a hash table would be created using join key as the hash table key.\n\n### Bucket Map Join\n\nIf the joining keys of map-join are bucketed then instead of keeping whole of small table (dimension table) in every mapper, only the matching buckets will be kept. This reduces the memory footprint of the map-join.\n\n### SMB Join\n\nThis is an optimization on Bucket Map Join; if data to be joined is already sorted on joining keys then hash table creation is avoided and instead a sort merge join algorithm is used.\n\n### Skew Join\n\nIf the distribution of data is skewed for some specific values, then join performance may suffer since some of the instances of join operators (reducers in map-reduce world) may get over loaded and others may get under utilized. On user hint, hive would rewrite a join query around skew value as union of joins.\n\nExample R1 PR1.x=R2.a  - R2 with most data distributed around x=1 then this join may be rewritten as (R1 PR1.x=R2.a and PR1.x=1    - R2) union all (R1 PR1.x=R2.a and PR1.x<>1    - R2)\n\n# 4. Implementation details\n\nCBO will be introduced in to Hive in three different phases. Following provides high-level overview of these phases:\n\n## Phase 1", null, "Statistics:\n\n• Table Cardinality\n• Column Boundary Stats: min, max, avg, number of distinct values\n\nCost Based Optimizations:\n\n• Join ordering\n• Join Algorithm\n\nRestrictions:\n\n• Calcite CBO will be used only for select expressions\n• Calcite CBO won’t be used if select expression contains any of the following operators:\n• Sort By\n\nHive supports both total ordering (order by) and partial ordering (sort by). Partial ordering cannot be represented in relational algebra and SQL. In future we may represent Sort By as a table function.\n\n• Map/Reduce/Transform\n\nHive allows users to specify map/reduce/transform operator in the sql; data would be transformed using provided mapper/reducer scripts. There is no direct translation for these operators to relational algebra. We may represent them as table function in future.\n\n• Cluster By/Distribute By\n\nCluster By and Distribute By are used mainly with the Transform/Map-Reduce Scripts. But, it is sometimes useful in SELECT statements if there is a need to partition and sort the output of a query for subsequent queries. Cluster By is a short-cut for both Distribute By and Sort By. Hive uses the columns in Distribute By to distribute the rows among reducers. All rows with the same Distribute By columns will go to the same reducer. However, Distribute By does not guarantee clustering or sorting properties on the distributed keys.\n\n• Table Sample\n\nThe TABLESAMPLE clause allows the users to write queries for samples of the data instead of the whole table. The TABLESAMPLE clause can be added to any table in the FROM clause. In future we may represent Table Sample as table function.\n\n• Lateral Views\n\nLateral view is used in conjunction with user-defined table generating functions such as explode(). UDTF generates one or more output rows for each input row. A lateral view first applies the UDTF to each row of base table and then joins resulting output rows to the input rows to form a virtual table having the supplied table alias.\n\n• UDTF (Table Functions)\n• PTF (Partitioned Table Functions)\n\nCalcite related enhancements:\n\n• Introduce Operators to represent hive relational operators. Table Scan, Join, Union, Select, Filter, Group By, Distinct, Order By. These operators would implement a calling convention with physical cost for each of these operators.\n• Introduce rules to convert Joins from CommonJoin to MapJoin, MapJoin to BucketJoin, BucketJoin to SMBJoin, CommonJoin to SkewJoin.\n• Introduce rule to merge joins so that a single join operator will represent multi-way join (similar to MergedJoin in Hive).\n• Merged-Join in Hive will be translated to MultiJoinRel in Calcite.\n\n## Phase 2", null, "Statistics:\n\n• Histograms\n\nCost Based Optimizations:\n\n• Join ordering based on histograms\n• Join Algorithm – histograms are used for estimating join selectivity\n• Take advantage of additional optimizations in Calcite. The actual rules to use is TBD.\n\n## Phase 3", null, "## Configuration\n\nThe configuration parameter hive.cbo.enable determines whether cost-based optimization is enabled or not.\n\n## Proposed Cost Model\n\nHive employs parallel-distributed query execution using Hadoop cluster. This implies for a given query operator tree different operators could be running on different nodes. Also same operator may be running in parallel on different nodes in the cluster, processing different partitions of the original relation. This parallel execution model induces high I/O and CPU costs. Hive query execution cost tends to be more I/O centric due to following reasons.\n\n• Shuffling cost\n\nData needed by an operator from its child operator in query tree requires assembling data from all instances of child operator. This data then needs to be sorted and chopped up so that a partition of the relation is presented to an instance of the operator.\n\nThis shuffling cost involves cost of writing intermediate result set to local file system, cost of reading data back from local file system, and cost of transferring intermediate result set to the node that is operating child processor. In addition to I/O cost, shuffling also requires sorting of data that should be counted towards CPU cost.\n\nReading and writing data to HDFS is more costly compared to local FS. In Map-Reduce framework Table Scan would typically read data from HDFS and would write data to HDFS when switching between two Map-Reduce jobs. In Tez all of the operators should work with in a single Tez Job and hence we shouldn’t have to pay the cost of writing intermediate result set to HDFS.\n\nCost based optimizations in Hive will keep track of cost in terms of\n\n• CPU usage\n• IO Usage\n• Cardinality\n• Average size of the tuple in the relation.\n\nAverage size of the tuple in relation and cardinality of the relation will be used to estimate resources needed to hold a relation in memory. Memory needed to hold a relation is used to decide whether certain join algorithms, like Map/Bucket Join, can be used.\n\nVolcano optimizer in Calcite compares cost of two equivalent query plans by getting cost of each operator in the tree and summing them up to find cumulative cost. Plan with lowest cumulative cost is picked as the best plan to execute the query. “VolcanoCost” is the Java class representing cost for Calcite’s Volcano optimizer. “VolcanoCost” comparison operators seem to take into consideration only the number of rows to decide if one cost is less than other.\n\nFor Hive we want to consider CPU and IO usage first before comparing cardinality.\n\nWe propose to introduce a new “RelOptCost” implementation “HiveVolcanoCost” derived from “VolcanoCost”. “HiveVolcanoCost” will keep CPU, I/O, Cardinality, and average size of tuple. Cost comparison algorithm will give importance to CPU and IO cost before paying attention to cardinality. CPU and IO cost will be stored in nano seconds granularity. Following is the pseudo code for “RelOptCost.isLe” function:\n\nClass HiveVolcanoCost extends VolcanoCost {\n\nDouble m_sizeOfTuple;\n\n@Override\n\npublic boolean isLe(RelOptCost other) {\n\nVolcanoCost that = (VolcanoCost) other;\n\nif (((this.dCpu + this.dIo) < (that.dCpu + that.dIo))\n\n|| ((this.dCpu + this.dIo) == (that.dCpu + that.dIo)\n\n&& this.dRows <= that.dRows)) {\n\nreturn true;\n\n} else {\n\nreturn false;\n\n}\n\n}\n\n}\n\nDesign Choice:\n\nIn the absence of histograms, cardinality can be assumed to follow uniform distribution on the distinct values. With this approach cardinality/distinct computation could always follow same code path (Histograms). Alternative is to use heuristics when histograms are not available (like the one described by Hector Garcia Molina, Jeffrey D. Ullman and Jennifer Widom in “Database Systems”). Currently Hive statistics doesn’t keep track of the distinct values for an attribute (only the number of distinct values is kept); however from min, max,number of distinct values, and table cardinality uniformly distributed histogram can be constructed. Following describes formulas for a uniform histogram construction.\n\nNumber of buckets = (Max-Min)/No of distinct values.\n\nBucket width = (Max- Min)/ Number of buckets.\n\nBucket Height = Table cardinality/ Number of buckets.\n\nIn this paper for the cost formula, in the absence of histogram, we will follow heuristics described by Hector Garcia Molina, Jeffrey D. Ullman and Jennifer Widom in the book “Database Systems”.\n\nFollowing are the cost variables that will be used in cost computation:\n\n• Hr - This is the cost of Reading 1 byte from HDFS in nano seconds.\n• Hw - This is the cost of Writing 1 byte to HDFS in nano seconds.\n• Lr - This is the cost of Reading 1 byte from Local FS in nano seconds.\n• Lw - This is the cost of writing 1 byte to Local FS in nano seconds.\n• NEt – This is the average cost of transferring 1 byte over network in the Hadoop cluster from any node to any node; expressed in nano seconds.\n• T(R) - This is the number of tuples in the relation.\n• Tsz – Average size of the tuple in the relation\n• V(R, a) –The number of distinct values for attribute a in relation R\n• CPUc – CPU cost for a comparison in nano seconds\n\nAssumptions:\n\n• Relative cost of Disk, HDFS, and Network read/write with each other is more important than the exact true cost.\n• We assume uniform cost regardless of hardware type, locality, and size of data involved in I/O, type of I/O scatter/gather vs. sequential read/write. This is obviously over simplification, but we are more interested in relative cost of operations.\n• This cost model ignores the number of disk blocks that needs to be read/written from/to and instead look at number of bytes that needs to be read/written. This is an obvious oversimplification of I/O cost.\n• This cost model also ignores storage layout, column store vs. others.\n• We assume all of the tuples to be of uniform size.\n• No colocation of tasks is assumed and hence we consider network transfer cost.\n• For CPU cost, only comparison cost is considered. It is assumed that each comparison will cost 1 nano second.\n• Each vertex in Tez is a different process\n• HDFS read is assumed to be 1.5 times of local disk read and HDFS write is assumed to be 10 times of local disk write.\n\nFollowing are the assumed values for cost variables:\n\n• CPUc = 1 nano sec\n• NEt = 150 * CPUc nano secs\n• Lw = 4 * NEt\n• Lr = 4 * NEt\n• Hw = 10 * Lw\n• Hr = 1.5 * Lr\n\n### Table Scan\n\nT(R) = Consult Metadata to get cardinality;\n\nTsz = Consult Metadata to get average tuple size;\n\nCPU Usage = 0;\n\nIO Usage = Hr * T(R) * Tsz\n\n### Common Join\n\nT(R) = Join Cardinality estimation\n\nTsz = Consult Metadata to get average tuple size based on join schema;\n\nCPU Usage = Sorting Cost for each of the relation + Merge Cost for sorted stream\n\n= (T(R1) * log T(R1) * CPUc + T(R2) * log T(R2) * CPUc + … + T(Rm) * log T(Rm) * CPUc) + (T(R1) + T(R2) + …+ T(Rm)) * CPUc nano seconds;\n\nIO Usage = Cost of writing intermediate result set in to local FS for shuffling + Cost of reading from local FS for transferring to Join operator node + Cost of transferring mapped output to Join operator node\n\n= Lw * (T(R1) * Tsz1 + T(R2) * Tsz2 + …+ T(Rm) * Tszm)  + Lr * (T(R1) * Tsz1 + T(R2) * Tsz2 + …+ T(Rm) * Tszm) + NEt *  (T(R1) * Tsz1 + T(R2) * Tsz2 + … + T(Rm) * Tszm)\n\nR1, R2… Rm is the relations involved in join.\n\nTsz1, Tsz2… Tszm are the average size of tuple in relations R1, R2…Rm.\n\n### Map Join\n\nNumber of Rows = Join Cardinality estimation\n\nSize of tuple = Consult Metadata to get average tuple size based on join schema\n\nCPU Usage =HashTable Construction cost + Cost of Join\n\n= (T(R2) + …+ T(Rm)) + (T(R1) + T(R2) + …+ T(Rm)) * CPUc nano seconds\n\nIO Usage = Cost of transferring small tables to Join Operator Node * Parallelization of the join\n\n= NEt *  (T(R2) * Tsz2 + … + T(Rm) * Tszm) * number of mappers\n\nR1, R2… Rm is the relations involved in join and R1 is the big table that will be streamed.\n\nTsz2… Tszm are the average size of tuple in relations R1, R2…Rm.\n\n### Bucket Map Join\n\nNumber of Rows = Join Cardinality estimation\n\nSize of tuple = Consult Metadata to get average tuple size based on join schema;\n\nCPU Usage =Hash Table Construction cost + Cost of Join\n\n= (T(R2) + …+ T(Rm)) * CPUc + (T(R1) + T(R2) + …+ T(Rm)) * CPUc nano seconds\n\nIO Usage = Cost of transferring small tables to Join * Parallelization of the join\n\n= NEt *  (T(R2) * Tsz2 + … + T(Rm) * Tszm) * number of mappers\n\nR1, R2… Rm is the relations involved in join.\n\nTsz2… Tszm are the average size of tuple in relations R2…Rm.\n\n### SMB Join\n\nNumber of Rows = Join Cardinality estimation\n\nSize of tuple = Consult Metadata to get average tuple size based on join schema;\n\nCPU Usage = Cost of Join\n\n= (T(R1) + T(R2) + …+ T(Rm)) * CPUc nano seconds\n\nIO Usage = Cost of transferring small tables to Join * Parallelization of the join\n\n= NEt *  (T(R2) * Tsz2 + … + T(Rm) * Tszm) * number of mappers\n\nR1, R2… Rm is the relations involved in join.\n\nTsz2… Tszm are the average size of tuple in relations R2…Rm.\n\n### Skew Join\n\nQuery will be rewritten as union of two joins. We will have a rule to rewrite query tree for skew join. Rewritten query will use the cost model for the join and union operators.\n\n### Distinct/Group By\n\nNumber of Rows = Based on Group-By selectivity = V(R, a,b,c..) where a,b,c are the group by keys\n\nSize of tuple = Consult Metadata to get average tuple size based on schema\n\nCPU Usage = Cost of Sorting + Cost of categorizing into group\n\n= (T(R) * log T(R) + T(R)) * CPUc nano seconds;\n\nIO Usage = Cost of writing intermediate result set in to local FS for shuffling + Cost of reading from local FS for transferring to GB reducer operator node + Cost of transferring data set to GB Node\n\n= Lw * T(R) * Tsz + Lr * T(R) * Tsz + NEt * T(R) * Tsz\n\n### Union All\n\nNumber of Rows = Number of Rows from left + Number of Rows from right\n\nSize of tuple = avg of (avg size of left, avg size of right)\n\nCPU Usage = 0\n\nIO Usage = Cost of writing intermediate result set in to HDFS + Cost of reading from HDFS for transferring to UNION mapper node + Cost of transferring data set to Mapper Node\n\n= (T(R1) * Tsz1  + T(R2) * Tsz2) * Hw + (T(R1) * Tsz1 + T(R2) * Tsz2) * Hr + (T(R1) * Tsz1 + T(R2) * Tsz2) * NEt\n\nR1, R2 is the relations involved in join.\n\nTsz1, Tsz2 is the average size of tuple in relations R1, R2.\n\n### Filter/Having\n\nNumber of Rows = Filter Selectivity * Number of Rows from Child\n\nSize of tuple = size of tuple from child operator\n\nCPU Usage = T(R) * CPUc nano seconds\n\nIO Usage = 0\n\n### Select\n\nNumber of Rows = Number of Rows from Child\n\nSize of tuple = size of tuple from child operator\n\nCPU Usage = 0\n\nIO Usage = 0\n\n### Filter Selectivity\n\n#### Without Histogram\n\n• Equality Predicates where one side is a literal = 1/V(R, A)\n• Equality Predicate when both sides are not literals = 1/max (V(R, A), V(R, B))\n• In Equality Predicates (Less/Greater than) = 1/3\n• Not Equal = (V(R, A) -1)/V(R, A)\n• OR Condition = n*(1 –(1-m1/n)(1-m2/n)) where n is the total number of tuples from child and m1 and m2 is the expected number of tuples from each part of the disjunction predicate.\n• AND condition = product of selectivity of individual leaf predicates in the conjunctive predicate\n\n### Join Cardinality (without Histogram)\n\n• Inner Join = Product of cardinalities of child relations * Join selectivity\n• One side Outer Join = max (Selectivity of filter rejecting non joined inner tuples * (Product of cardinalities of child relations), Cardinality of Outer side)\n\nExample: C(R1  a=b R2) = max (C(R2.b=R1.a C(R1 X R2)), C(R1))\n\n• Full Outer Join = max (Selectivity of filter rejecting non joined inner tuples * (Product of cardinalities of child relations), sum of cardinalities of left and right relation)\n\n= C(R1 a=b R2) = max (C(R1.a=R1.b C(R1 X R2)), C(R1) + C(R2))\n\n• For multi-way join algorithm, join would be decomposed to number of different joins for cardinality and cost estimation.\n\n#### Join Selectivity (without Histogram)\n\n• Single Attribute  = 1/max (V(R1, a), V(R2, a))  where join predicate is R1.a=R2.a\n• Multiple Attributes = 1/(max (V(R1, a), V(R2, a))   * max (V(R1, b), V(R2, b)) ) where join predicate is R1.a=R2.a and R1.b = R2.b\n\n### Distinct Estimation\n\n#### Inner Join - Distinct Estimation\n\n• V(J, a) = V(R1, a) if attribute a comes only from one side of join; J is the relation representing Join output and R1 one of the relation involved.\n• V(J, a) = max(V(R1, a), V(R2, a)) if attribute a is present in both sides of join; J is the relation representing Join output and R1, R2 are the relations involved in join.\n• V(J, a) = V(R1, a) if attribute a comes only from one side of join; J is the relation representing Join output output and R1 is the relation from which attribute “a” comes from.\n• V(J, a) = V(Ro, a) where Ro is the relation for the outer side; J is the relation representing Join output and Ro is the outer relation of the join.\n• V(J, a) = V(R1, a) if attribute “a” comes only from one side of join; J is the relation representing Join output and R1 is the relation from which attribute a comes from.\n• V(J, a) = max (V(R1, a), V(R2, a)) where J is the relation representing Join output and R1, R2 are the relations involved in join.\n• V(U, a) = max (V(R1, a), V(R2, a)) where U is the relation representing Union All output and R1, R2 are the relations involved in union.\n\n#### GB - Distinct Estimation\n\n• V(G, a) = V(R, a) where G is the relation representing Group-By output and R is the child relation of Group-By. It is assumed attribute “a” is part of grouping keys.\n• V(G, a,b,c) = max (V(R,a), V(R,b), V(R,c)) where G is the relation representing Group-By output and R is the child relation of Group-By. It is assumed attribute “a”, “b”, “c” is part of grouping keys.\n\n#### Filter - Distinct Estimation\n\n• V(F, a) = V(R, a) where F is the relation representing filter output and R is the child relation of the filter.\n\n# 5. Phase 1 – Work Items\n\n1. Walk the Hive OP tree and make sure that OP tree doesn’t contain any op that cannot be translated into Calcite (Lateral Views, PTF, Cubes & Rollups, Multi Table Insert).\n2. Walk the Hive OP tree and introduce cast functions to make sure that all of the comparisons (implicit & explicit) are strictly type safe (the type must be same on both sides).\n3. Implement Calcite operators specific to Hive that would do cost computation and cloning.\n4. Convert the Hive OP tree to Calcite OP tree.\n1. Convert Hive Types to Calcite types\n2. Convert Hive Expressions to Calcite expressions\n3. Convert Hive Operator to Calcite operator\n4. Handle Hidden Columns\n5. Handle columns introduced by ReduceSink (for shuffling)\n6. Handle Join condition expressions stashed in Reducesink op\n7. Handle filters in Join Conditions\n8. Convert Hive Semi Join to Calcite\n9. Attach cost to operators\n10. Alias the top-level query projections to query projections that user expects.\n5. Optimize the Calcite OP tree using Volcano Optimizer.\n1. Implement Rules to convert Joins to Hive Join algorithms.\n1. Common Join -> Map Join\n2. Map Join -> Bucket Map Join\n3. Common Join -> Bucket Map Join\n4. Bucket Map Join ->  SMB Join\n5. Common Join -> Skew Join\n6. Walk the Optimized Calcite OP tree and introduce derived tables to convert OP tree to SQL.\n1. Generate unique table (including derived table) aliases\n7. Walk the OP tree and convert in to AST.\n1. Stash Join algorithm in AST as query Hints\n8. Modify Plan Generator to pay attention to Calcite query hints\n9. Rerun Hive optimizer and generate the execution plan (this second pass would not invoke Calcite optimizer).\n\n# Open Issues\n\n1. CBO needs to differentiate between types of IPC (Durable-Local-FS vs, Durable-HDFS, Memory vs. Streaming)\n\n# Reference\n\n1. Database Systems The Complete Book, Second Edition, Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer Widom\n2. Query Optimization for Massively Parallel Data Processing\n\nSai Wu, Feng Li, Sharad Mehrotra, Beng Chin Ooi\n\nSchool of Computing, National University of Singapore, Singapore, 117590\n\nSchool of Information and Computer Science, University of California at Irvine\n\n• No labels" ]
[ null, "https://cwiki.apache.org/confluence/download/attachments/42566775/CalciteArchitectureOverview.jpg", null, "https://cwiki.apache.org/confluence/download/attachments/42566775/Phase1.jpg", null, "https://cwiki.apache.org/confluence/download/attachments/42566775/Phase2.jpg", null, "https://cwiki.apache.org/confluence/download/attachments/42566775/Phase3.jpg", null ]
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https://myjava.in/Core-Java/Java-Equality-and-Relational-Operators.aspx
[ "# Java Equality and Relational Operators\n\nThe equality and relational operators determine if one operand is greater than, less than, equal to, or not equal to another operand. The majority of these operators will probably look familiar to you as well.\n\nKeep in mind that you must use \"==\", not \"=\", when testing if two primitive values are equal.and also when we need to compare the results of two expressions or operands in a program then the equality and relational operators are used\n\nOperatorDescription\n==Equal to\n!=Not equal to\n>Greater than\n>=Greater than or equal to\n<Less than\n<=Less than or equal to\n\n### Screenshots of Equality and Relational Operator Program\n\n#### Simple Java Program ComparisonOp, tests the comparison operators:\n\n``````\n\npublic class ComparisonOp {\n\npublic static void main(String[] args){\nint num1 = 50;\nint num2 = 20;\nif(num1 == num2)\nSystem.out.println(\"num1 is equal == num2\");\nif(num1 != num2)\nSystem.out.println(\"num1 is not equal != num2\");\nif(num1 > num2)\nSystem.out.println(\"num1 is greater then > num2\");\nif(num1 < num2)\nSystem.out.println(\"num1 is less then < num2\");\nif(num1 <= num2)\nSystem.out.println(\"num1 is Less than or equal to <= num2\");\n}\n}\n\n``````\n\n### Output Here In cmd Window\n\nReferences : oracle share on :        :\n\nLove to hear your Views / Guidance / Recommendations on this Post…\n\nExplore the Technology World\n\nCall / Visit for New Batch\n\nServices\n\n• ➯ Free Demo Classes\n• ➯ No Registration Fee\n• ➯ Interview Questions\n• ➯ Study Materials\n• ➯ Softwares\n• ➯ Aptitude & Reasoning\n• ➯ Placement Assitance" ]
[ null ]
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http://mathhelpforum.com/pre-calculus/28518-graph-point-passes-through-line.html
[ "# Thread: graph of a point that passes through a line\n\n1. ## graph of a point that passes through a line\n\nno clue what to do, help please\n\nwrite an equation for a line tha tasses through (5,4) and is perpinducular to the graph of 2x - 3y = 1\n\nthank you!!!1\n\n2.", null, "Originally Posted by Ilovemath123", null, "no clue what to do, help please\n\nwrite an equation for a line tha tasses through (5,4) and is perpinducular to the graph of 2x - 3y = 1\n\nthank you!!!1\nYou need to find two things: the gradient of the line and a point on the line.\n\nGet those two things and substitute into the general equation\n\n$\\displaystyle y - y_1 = m(x - x_1)$\n\nwhere m is the gradient and $\\displaystyle \\, (x_1, \\, y_1)\\,$ is a point on the line.\n\nThe point on the line is given on a platter. It's (5, 4).\n\nAs for the gradient, you know that it's perpendicular to the line $\\displaystyle 2x - 3y = 1 \\Rightarrow 2x - 1 = 3y \\Rightarrow y = \\frac{2}{3} x - \\frac{1}{3}$.\n\nTherefore: $\\displaystyle m \\times \\frac{2}{3} = -1 \\Rightarrow m = .....$\n\n(You do know that when two lines are perpendicular, the product of their gradients is equal to -1, right?)\n\n3.", null, "Originally Posted by Ilovemath123", null, "no clue what to do, help please\n\nwrite an equation for a line tha tasses through (5,4) and is perpinducular to the graph of 2x - 3y = 1\n\nthank you!!!1\nTwo lines are perpendicular to another if their slopes are the negative reciprocals of each other.\n\ny=mx+b where m is the slope, b is y-intercept.\ny=(2/3)x-(1/3)\nm=2/3\n\nthe line you want has slope -(3/2).\ny=-(3/2)x+b\n\nplug in (5,4) to solve for b.\n\n4=-(3/2)5+b\nb=11.5\n\nyour line is y=-(3/2)x+11.5\n\n4.", null, "Originally Posted by Ilovemath123", null, "write an equation for a line tha tasses through (5,4) and is perpinducular to the graph of 2x - 3y = 1\nUnfortunately I have no chance against all those fast-typers...\n\nSo you get a drawing\n\n#### Search Tags\n\ngraph, line, passes, point", null, "" ]
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