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http://catalog.kellogg.edu/preview_course_nopop.php?catoid=16&coid=13319&print	[ "May 18, 2022\n Select a Publication 2022-2023 Academic Catalog 2021-2022 Student Handbook 2021-2022 Academic Catalog [ARCHIVED CATALOG] 2020-2021 Academic Catalog [ARCHIVED CATALOG] 2020-2021 Student Handbook [ARCHIVED CATALOG] 2019-2020 Academic Catalog [ARCHIVED CATALOG] 2019-2020 Student Handbook [ARCHIVED CATALOG] 2018-2019 Academic Catalog [ARCHIVED CATALOG] 2017-2018 Academic Catalog [ARCHIVED CATALOG]\n HELP 2020-2021 Academic Catalog [ARCHIVED CATALOG]", null, "Print this Page\n\n# MATH 105 - Beginning Algebra\n\n4 CR\nCourse content includes operations on integers and rational numbers, geometric formulas, algebraic expressions, solutions of linear equations and inequalities, graphs of linear equations and linear systems, systems of linear equations in two variables, polynomials and factoring, rational expressions and equations, and radical expressions and equations. Lab Fee\n\nRequisites: Next Gen ACCUPLACER® arithmetic score of at least 250, or Next Gen ACCUPLACER® quantitative reason score of at least 237, or TSMA 45 with at least a grade of C.\nCourse Learning Outcomes:\n1. Understand, interpret and use the basic symbols and words in the language of arithmetic and algebra.\n2. Use algebraic methods to solve a linear equation or inequality.\n3. Graph linear equations and inequalities in two variables.\n4. Solve systems of equations in two variables using multiple methods.\n5. Apply problem-solving strategies with applications of systems involving two variables.\n6. Factor algebraic expressions using all methods and use this skill to solve quadratic equations by factoring.\n7. Solve rational and radical equations.\n8. Simplify, multiply, divide, add and subtract real numbers, polynomials, rational expressions, and radical expressions." ]	[ null, "http://catalog.kellogg.edu/img/print.gif", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8488255,"math_prob":0.97852224,"size":1282,"snap":"2022-05-2022-21","text_gpt3_token_len":259,"char_repetition_ratio":0.16510172,"word_repetition_ratio":0.0,"special_character_ratio":0.20358814,"punctuation_ratio":0.14285715,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98246896,"pos_list":[0,1,2],"im_url_duplicate_count":[null,4,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-05-18T16:12:10Z\",\"WARC-Record-ID\":\"<urn:uuid:6f188fba-c607-4736-837b-a05c3fffe343>\",\"Content-Length\":\"126768\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:21ffc590-0fb7-43a4-837d-4293f54e5b08>\",\"WARC-Concurrent-To\":\"<urn:uuid:eba7458e-0806-41a3-99c9-9b248f61b4ee>\",\"WARC-IP-Address\":\"104.26.6.234\",\"WARC-Target-URI\":\"http://catalog.kellogg.edu/preview_course_nopop.php?catoid=16&coid=13319&print\",\"WARC-Payload-Digest\":\"sha1:DKSEYQN2JCEJTPSIRGKONK3EUDBCCWKF\",\"WARC-Block-Digest\":\"sha1:R65YMBUL7GTLDUFA2OHOYB5ZYIMZVJAO\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-21/CC-MAIN-2022-21_segments_1652662522284.20_warc_CC-MAIN-20220518151003-20220518181003-00124.warc.gz\"}"}
https://e2e.ti.com/blogs_/archives/b/precisionhub/posts/the-impact-of-voltage-reference-noise-on-delta-sigma-adc-resolution	[ "Other Parts Discussed in Post: ADS1259\n\nHave you ever evaluated the noise performance of an ADC and found that your measured performance differs from the specified performance given in the device datasheet? Achieving high resolution in a precision data-acquisition system requires some understanding of analog-to-digital converter (ADC) noise. It is important to know how the datasheet specifies noise performance and how external noise sources may affect overall system performance. One example of such a noise source is the power-supply noise my colleague Ryan Andrews discussed in his post, “Caution! Your ADC may be only as good as its power supply.” In this post, I’ll look at how reference noise affects DC noise performance in delta-sigma ADCs.\n\nYou can specify and measure the DC noise performance of an ADC with the positive and negative inputs shorted to a mid-supply voltage, as shown in Figure 1. By measuring noise under this condition, the noise in the ADC’s output codes is nearly immune to changes in reference voltage, reference noise or input-signal noise. While this test condition is more of an ideal scenario than a practical application, it does provide a good representation of ADC noise performance isolated from some external noise sources.", null, "Figure 1: ADC noise performance test (and debugging) configuration\n\nTip: When debugging, begin evaluating the system’s noise performance with a shorted-input test to assess the isolated ADC noise performance before moving on to other system noise performance tests.\n\nHow reference noise affects ADC DC noise performance\n\nThis effect is related to the basic task of an ADC, which is to provide an output code that is a representation of the ratio of the input-signal voltage to the reference voltage. Both input and reference voltages add a noise term to this ratio, as shown in Equation 1:", null, "(1)\n\nThe effect of input signal noise,", null, ", on ADC conversion results is fairly straightforward. The ADC will capture any noise not filtered out – either with an external resistor-capacitor (RC) filter or with the delta-sigma ADC’s digital filter. You can observe this in the output codes, since", null, "has a direct effect on the ratio in Equation 1.\n\nTip: Make sure that the input signal is a low-noise source when evaluating ADC noise performance, since the input signal’s noise directly affects the ADC’s output result.\n\nThe effect of reference noise,", null, ", on the ADC conversion result is not quite as straightforward, however, because", null, "appears in the denominator. When the numerator is equal to zero (as is the case when the ADC inputs are shorted), the ratio will always equal zero and the", null, "term will not effect on the ratio. When the numerator is nearly equal to the denominator,", null, "will have a strong effect on the ratio. When ratio values are between 0 and 1, the effect of", null, "is weighted by the value of the ratio. Figure 2 shows the resulting characteristic behavior.", null, "Figure 2: ADC and reference noise vs. input voltage\n\nWhen adding reference noise to the ADC’s noise contribution using root-sum-of-squares addition, the combined noise performance is a function of the input voltage, which increases for larger positive or negative input voltages. The important points to notice on the curve in Figure 2 are:\n\n• Point A, which is the ADC noise measured with shorted inputs given in the ADC’s datasheet.\n• Point B, which is the total bandwidth-limited reference noise, typically limited by the ADC’s digital filter bandwidth.\n\nYou can calculate the reference noise (point B) if you know the noise-spectral density and noise bandwidth for the reference source; otherwise, applying a full-scale voltage input to the ADC and measuring the noise performance will generally be a good measure of reference noise.\n\nHow to select a reference voltage source\n\nA low-noise reference is important for achieving low-noise/high-resolution performance across the full ADC input range. The reference-noise requirements will depend on the system’s targeted resolution, the input-signal span and the data rate (as this usually limits both the input and reference-noise bandwidth). The system can tolerate additional reference noise when the noise bandwidth is limited by a slower data rate, or if the input-signal span is limited to a small percentage of the ADC’s full-scale range.\n\nMany delta-sigma ADCs include an integrated reference that provides sufficient performance for most applications. For more demanding applications, using an external reference may improve noise performance for inputs near the positive and negative full-scale range. External precision references can achieve lower noise performance because of their higher power consumption. Figure 3 compares the 24-bit ADS1259 delta-sigma ADC’s noise performance with the internal reference source, an external REF5025 voltage source, and a ratiometric reference source.", null, "Figure 3: ADS1259 noise performance with internal, external and ratiometric reference sources\n\nWhile external references may achieve better noise performance than their integrated counterparts, ratiometric reference configurations can perform even better. A ratiometric configuration shares the same voltage source for the reference voltage and input-signal excitation. By sharing a common voltage and noise source,", null, "and", null, "from Equation 1 tend to cancel each other out in the ratio.\n\nNext time you’re evaluating an ADC’s noise performance, make sure to consider the reference noise effects. Also, whenever a sensor requires an excitation source, always consider a ratiometric measurement implementation." ]	[ null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/8484.image-1.png", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/equation-1.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture2.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/7607.Capture2.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture2.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture2.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture2.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/2626.image-2.png", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/5340.image-3.png", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture.JPG", null, "https://e2e.ti.com/resized-image/__size/1230x0/__key/communityserver-blogs-components-weblogfiles/00-00-00-09-30/Capture2.JPG", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8523906,"math_prob":0.9196447,"size":5972,"snap":"2022-27-2022-33","text_gpt3_token_len":1170,"char_repetition_ratio":0.18733244,"word_repetition_ratio":0.0043431055,"special_character_ratio":0.18955123,"punctuation_ratio":0.08490566,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.971193,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26],"im_url_duplicate_count":[null,3,null,3,null,9,null,9,null,null,null,3,null,null,null,null,null,null,null,3,null,3,null,9,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-08-15T06:45:54Z\",\"WARC-Record-ID\":\"<urn:uuid:a608de42-40f0-42e5-8efc-6dde2c79f73a>\",\"Content-Length\":\"129822\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8501111d-bf24-4601-acee-303d4f7287cb>\",\"WARC-Concurrent-To\":\"<urn:uuid:99ab753e-fbca-4639-b353-24052dcb0a3b>\",\"WARC-IP-Address\":\"184.87.64.46\",\"WARC-Target-URI\":\"https://e2e.ti.com/blogs_/archives/b/precisionhub/posts/the-impact-of-voltage-reference-noise-on-delta-sigma-adc-resolution\",\"WARC-Payload-Digest\":\"sha1:Z5EUQCA2PRERIMG6BD6F6NG6MQVKSF2M\",\"WARC-Block-Digest\":\"sha1:5O76XNUCOFEL66A6TWJFX27EKVWWRLU7\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-33/CC-MAIN-2022-33_segments_1659882572161.46_warc_CC-MAIN-20220815054743-20220815084743-00268.warc.gz\"}"}
https://de.mathworks.com/matlabcentral/cody/problems/2240-sum-the-edge-values-of-a-matrix/solutions/418459	[ "Cody\n\n# Problem 2240. Sum the 'edge' values of a matrix\n\nSolution 418459\n\nSubmitted on 14 Mar 2014 by Vincent\nThis solution is locked. To view this solution, you need to provide a solution of the same size or smaller.\n\n### Test Suite\n\nTest Status Code Input and Output\n1 Pass\n%% x = [1 2 3; 4 5 6;7 8 9]; y_correct = 40; assert(isequal(AddMatrixLim(x),y_correct))\n\ny = 40\n\n2 Pass\n%% x= [1 5 6 7; 4 9 4 7; 9 4 2 1; 0 1 2 8] y_correct = 51; assert(isequal(AddMatrixLim(x),y_correct))\n\nx = 1 5 6 7 4 9 4 7 9 4 2 1 0 1 2 8 y = 51" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.5612317,"math_prob":0.98714197,"size":577,"snap":"2019-51-2020-05","text_gpt3_token_len":233,"char_repetition_ratio":0.12914485,"word_repetition_ratio":0.0,"special_character_ratio":0.43154246,"punctuation_ratio":0.09489051,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.95443267,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-12-07T12:49:52Z\",\"WARC-Record-ID\":\"<urn:uuid:54eed1d2-53b4-467b-b60a-efe07e353158>\",\"Content-Length\":\"72288\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8352ebe2-a9be-4bd6-9d64-1ecf1dd7829e>\",\"WARC-Concurrent-To\":\"<urn:uuid:ba716a73-0018-4283-9af3-e389da040b5f>\",\"WARC-IP-Address\":\"104.110.193.39\",\"WARC-Target-URI\":\"https://de.mathworks.com/matlabcentral/cody/problems/2240-sum-the-edge-values-of-a-matrix/solutions/418459\",\"WARC-Payload-Digest\":\"sha1:OOOL5NDLHAAYAUX27WUKVFPZ4QAJN5K5\",\"WARC-Block-Digest\":\"sha1:AGJGLXKJJUAFNJRDHEVQDA36DJ2HCHU4\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-51/CC-MAIN-2019-51_segments_1575540499389.15_warc_CC-MAIN-20191207105754-20191207133754-00405.warc.gz\"}"}
https://www.xarg.org/puzzle/project-euler/problem-3/	[ "# Project Euler 3 Solution: Largest prime factor\n\nProblem 3\n\nThe prime factors of 13195 are 5, 7, 13 and 29.\n\nWhat is the largest prime factor of the number 600851475143?\n\n## JavaScript Solution\n\nFactorizing a number is a quite common problem and I'll not go into details here. A pretty straighforward implementation can be stated as this:\n\n```function factorize(num) {\nvar factors = {};\n\nvar n = num;\nvar i = 2;\n\nfunction count(n) {\nif (factors[n])\n++factors[n];\nelse\nfactors[n] = 1;\n}\n\nwhile (i * i <= n) {\n\nwhile (n % i === 0) {\nn/= i;\ncount(i);\n}\ni++;\n}\n\nif (n !== num) {\nif (n > 1)\ncount(n);\n} else {\ncount(num);\n}\nreturn factors;\n}```\n\nWith it, the problem can be solved quite easily:\n\n```function solution(n) {\n\nvar tmp = factorize(n);\nvar max = 0;\nfor (var i in tmp) {\nmax = Math.max(max, i);\n}\nreturn max;\n}```\n\nAlternatively, we can combine the two functions into a much smaller one, custom tailored for this task. Since the largest prime has an exponent of 1, we don't need extra checks and can go with (otherwise the commented out check is needed):\n\n```function solution(n) {\n\nfor (var i = 2; i * i <= n; i++) {\nwhile(n % i === 0 /* && i * i <= n */) {\nn/= i;\n}\n}\nreturn n;\n}\nsolution(600851475143);```\n\n« Back to problem overview" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.701132,"math_prob":0.9940532,"size":1201,"snap":"2023-14-2023-23","text_gpt3_token_len":347,"char_repetition_ratio":0.120300755,"word_repetition_ratio":0.0,"special_character_ratio":0.36136553,"punctuation_ratio":0.15226337,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99963343,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-25T05:34:47Z\",\"WARC-Record-ID\":\"<urn:uuid:7a9850fa-b8e2-4cd2-b31b-e5999df76279>\",\"Content-Length\":\"11893\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:15e4b638-0064-490c-94ad-8c8ed527ff39>\",\"WARC-Concurrent-To\":\"<urn:uuid:b7f032e4-a459-4e7d-aad8-b1443bd8e7cd>\",\"WARC-IP-Address\":\"172.67.128.217\",\"WARC-Target-URI\":\"https://www.xarg.org/puzzle/project-euler/problem-3/\",\"WARC-Payload-Digest\":\"sha1:DGJ4SFVMZ5QNDT2IWXCZJ46RW6QZFANS\",\"WARC-Block-Digest\":\"sha1:7SLXYOLXYUEYOGYQM7COMFQGNXZ7QJEK\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296945315.31_warc_CC-MAIN-20230325033306-20230325063306-00577.warc.gz\"}"}
https://visbis.com/newsinfo/batteries-basics-about-batteries-part-vocabularysymantics.html	[ "# Batteries, basics about batteries, Part!: Introduction and Vocabulary/Semantics\n\nAt this point in time battery world experiencing revolution in shapes configurations and chemistry. Sometimes it is confusing to understand which battery is the best to use for your particulate application. Also users sometimes can’t find the right substitution for the battery they had before. I will try to help in this article to understand what is what and basic ideas about batteries.", null, "The most common are carbon-zinc, alkaline, lead acid, nickle metal hydride, nickle cadmium and lithium ion. But there are many other types of chemistry, which used more seldom. Below we discuss different of the battery designs currently used, some of the chemistry involved, and advantages and disadvantages of each design. We have also included some useful definitions and a list of parameters to guide you in matching your battery requirements to a specific battery design.\n\n________________________________________\nDefinitions\nAnode: The electrode where oxidation (loss of electrons) takes place. While discharging, it is the negative electrode; while charging it becomes the positive electrode.\n• Amps (A): Also known as Amperes. This is the rate at which electrons flow in a wire. Or simply “Current”\n• Amp hours (Ahr, mAh, mah etc): Also known as ampere hours. This is a measure of the amount of charge stored or used. This parameter characterize how “big” is the battery in electrical sense.\nSo Amp-Hours, (AH), or milliamp-Hours (mAH) is a measure of the size of the battery a 200 mAH battery is twice as big as a 100 mAH battery, even though they may be in the same physical dimension and size.\n• Batteries: Two or more electrochemical cells, electrically interconnected,\n• Battery cell: One battery of given chemistry, not connected in formation. Normally it contains two electrodes and an electrolyte. The redox (oxidation-reduction) reactions that occur at these electrodes convert electrochemical energy into electrical energy. Very often people commonly calling something a “battery” but intermixing the definitions of a single sell or battery pack formed with single cells. Very often it is not obvious that battery does consist of a few single cells.\n• C:C represents the capacity of a battery divided by 1 hour, its units are amps. In most of specifications you will commonly find that C parameter. Don’t be confused, it is just the battery capacity in mAh or Ah said in one letter C.\nIt represents a 1 hour discharge rate using the nominal capacity of the battery. So a discharge rate of 10C for a 5AH battery would be 50 amps. The concept of “C” is also used for charge currents, since both charge and discharge properties are proportional to the capacity of the battery, so a 5C charge rate for a 5 AH battery would be 25 amps.\n• Capacity: The total quantity of electricity or total ampere-hours available from a fully charged cell or battery.\n• Cathode: The electrode where reduction (gain of electrons) takes place. When discharging, it is the positive electrode, when charging, it becomes the negative electrode.\n• Charge: The conversion of electrical energy, provided in the form of current from an external source, into chemical energy stored at the electrodes of a cell or battery.\n• Discharge: The conversion of the chemical energy of a cell into electrical energy, which can then be used to supply power to a system.\n• Discharge curve: A plot of cell voltage over time into the discharge, at a constant temperature and constant current discharge rate.\n\nCharge-Discharge curve for LiFePO4 battery", null, "Typical discharge curves for LiFePO4 battery\n\nEach curve in this graph represents cell performance at a different discharge rate. The farther right the curve ends, the lower the discharge rate.\n• Dry cell: A Leclanché cell, so called because of its non-fluid electrolyte (to prevent spillage). This is achieved by adding an inert metal oxide so that the electrolyte forms a gel or paste.\n• Efficiency: For a secondary cell, the ratio of the output on discharge to the input required to restore it to its initial state of charge under specified conditions. Can be measured in ampere-hour, voltage, and watt-hour efficiency.\n• Electrolyte: The chemistry of a battery requires a medium that provides the ion transport mechanism between the positive and negative electrodes of a cell.\n• Energy density (specific energy): These two terms are often used interchangeably. Energy density refers mainly to the ratio of a battery’s available energy to its volume (watt hour/liter). Specific energy refers to the ratio of energy to mass (watt hour/kg). The energy is determined by the charge that can be stored and the cell voltage (E=qV).\n• Fuel cell: A cell in which one or both of the reactants are used in the battery to convert it to electricity. Unlike the metal anodes typically used in batteries, the fuels in a fuel cell are usually gas or liquid, with oxygen as the oxidant. The hydrogen/oxygen fuel cell is the most common. In this fuel cell, hydrogen is oxidized at the anode: 2H2 > 4H+ + 4e\n\n•Polarization: The voltage drop in a cell during discharge due to the flow of an electrical current. The cell’s internal resistance increases with the buildup of a product of oxidation or a reduction of an electrode, preventing further reaction.\n\n•Power: Measured by Watts. Power: P=VI. where V is voltage (V) and I is current ,\n\nSince V=IR, P=I2R and P=V2/R\n\nPower also can be described by energy emitted per unit of time: P=E/t.\n\nThus E=VIt=qV.\n\n•Power density (specific power): Power density is the ratio of the power available from a battery to its volume (watts/liter). Specific power generally refers to the ratio of power to mass (watts/kg). Comparison of power to cell mass is more common.\n\n•Primary cells: A cell that is not designed for recharging and is discarded once it has produced all its electrical energy.\n\n•Prismatic: Just a word to say that the cells are not cylindrical, as nature intended battery cells to be, but fit nicely into a parallelepiped, rectangular or any other such flattened shape.\n\nViewed: 378" ]	[ null, "http://visbis.com/image/catalog/news/allbatsmsm.jpg", null, "http://visbis.com/image/catalog/news/chrgdischarge1-300x161.jpg", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.9003155,"math_prob":0.89295584,"size":6192,"snap":"2020-24-2020-29","text_gpt3_token_len":1426,"char_repetition_ratio":0.13914028,"word_repetition_ratio":0.011811024,"special_character_ratio":0.2123708,"punctuation_ratio":0.11416309,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9615167,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,4,null,4,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-07-12T09:50:13Z\",\"WARC-Record-ID\":\"<urn:uuid:5929a8eb-156e-4328-90c8-0160e8975b73>\",\"Content-Length\":\"22929\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:55ff88e4-d833-47f8-8c85-c980713925e0>\",\"WARC-Concurrent-To\":\"<urn:uuid:f3b8fe10-5569-40c5-9465-4afbebe044d3>\",\"WARC-IP-Address\":\"87.236.16.164\",\"WARC-Target-URI\":\"https://visbis.com/newsinfo/batteries-basics-about-batteries-part-vocabularysymantics.html\",\"WARC-Payload-Digest\":\"sha1:HO27EGUCQWDTTFGNHQIFWJGRS3RTBETK\",\"WARC-Block-Digest\":\"sha1:62DUJIJWILNZ3247KGF6GXY3AWQ3BOX4\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-29/CC-MAIN-2020-29_segments_1593657134758.80_warc_CC-MAIN-20200712082512-20200712112512-00222.warc.gz\"}"}
https://www.libhunt.com/compare-matplotlib-vs-pyqtgraph	[ "matplotlib VS PyQtGraph\n\nCompare matplotlib vs PyQtGraph and see what are their differences.", null, "matplotlib\n\nmatplotlib: plotting with Python (by matplotlib)", null, "PyQtGraph\n\nFast data visualization and GUI tools for scientific / engineering applications (by pyqtgraph)\n• OPS - Build and Run Open Source Unikernels\n• SonarQube - Static code analysis for 29 languages.\n• Scout APM - Less time debugging, more time building\nmatplotlib PyQtGraph\n12 11\n14,900 2,689\n2.0% 1.7%\n9.9 9.6\n1 day ago 9 days ago\nPython Python\nThe number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.\nStars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.\nActivity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.\nFor example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.\n\nmatplotlib\n\nPosts with mentions or reviews of matplotlib. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-30.\n• Looking for help formatting a line graph\n1 project \| reddit.com/r/libreoffice \| 10 Dec 2021\nmatplotlib + their User's Guide.\n• Problem with surface plot color and legend\n1 project \| reddit.com/r/learnpython \| 24 Nov 2021\n# https://old.reddit.com/r/learnpython/comments/r1etmt/problem_with_surface_plot_color_and_legend/ # AmericaRL_03.py # Comparação entre random walk e difusão em 1d import numpy as np import matplotlib.pyplot as plt M = 100000 # Número de walkers L = 100 # Tamanho da malha # A cada intervalo de tempo, mover o walker e propagar a difusão p = 0.1 # Probabilidade de andar pinv = 1.0 - p nsteps = 2001 # Número de intervalos de tempo # Iniciando as concentrações c = np.zeros((2, 2 * L + 1, 2 * L + 1)) i0 = 0 i1 = 1 c[:, L, L] = M # c[:,L,L] corresponde a (x,y) = (0,0) edgesdiff = np.array(range(-L - 1, L + 1)) - 0.5 xc = 0.5 * (edgesdiff[:-1] + edgesdiff[1:]) xx, yy = np.meshgrid(xc, xc) D = p noutput = 100 for it in range(nsteps): # Executar a etapa na equação de difusão for ix in range(1, len(c) - 1): for iy in range(1, len(c) - 1): # Usar i0 e gerar i1 c[i1, ix, iy] = c[i0, ix, iy] + D * ( c[i0, ix - 1, iy] + c[i0, ix + 1, iy] - 4 * c[i0, ix, iy] + c[i0, ix, iy - 1] + c[i0, ix, iy + 1] ) # Inverter i0 e i1 ii = i1 i1 = i0 i0 = ii # Plotar as concentrações if np.mod(it, noutput) == 0: fig = plt.figure() ax = fig.add_subplot(111, projection=\"3d\") # ax.cla() diff = ax.plot_surface(xx, yy, c[0, :, :], cmap=\"Reds\", label=\"Difusão\") plt.title(\"Tempo = {}, M = {}, p = {}\".format(it, M, p)) ax.set_xlabel(\"Distância percorrida (x)\") ax.set_ylabel(\"Distância percorrida (y)\") ax.set_zlabel(\"Concentração\") # ax.legend() fails getting proper label key color in 3D plots # # AttributeError missing _facecolors2d and _edgecolors2d are raised # in 3D projection method get_facecolor() used by legend handler # # Is open issue since 2015 # https://github.com/matplotlib/matplotlib/issues/4067 if False: # OP's way: Set values manually to keep legend() quiet diff._facecolors2d = diff._facecolor3d diff._edgecolors2d = diff._edgecolor3d ax.legend() # But then problems with legend() getting proper legend key color # default (blue) is used instead of a value from set cmap (Reds) else: # DIFFERENT FIX: Draw legend key and legend label manually # # First get suitable cmap color (instead blue default) # https://stackoverflow.com/a/25408562 from matplotlib.cm import get_cmap cmap = get_cmap('Reds') my_red_rgba = cmap(0.5) # e.g. a color in middle of range (0..1) # Then insert own artist for legend key and legend label # https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html import matplotlib.patches as mpatches red_patch = mpatches.Patch(color=my_red_rgba, label='Difusão') ax.legend(handles=[red_patch]) # plt.show() plt.savefig('tempo_{}.png'.format(it),dpi = 600) plt.pause(0.001) ax.cla() # is nicer placed here instead above\n• Python 3.8, 3.9 or 3.10 for new projects?\n3 projects \| reddit.com/r/Python \| 30 Oct 2021\nmatplotlib supports 3.10 since May\n• Top 10 Python Libraries for Machine Learning\n14 projects \| dev.to \| 9 Sep 2021\nWebsite: https://matplotlib.org/ Github Repository: https://github.com/matplotlib/matplotlib Developed By: Micheal Droettboom, Community Primary purpose: Data Visualization\n• Should you learn Julia or Python for Machine Learning?\n8 projects \| reddit.com/r/learnmachinelearning \| 15 Aug 2021\nBut, now we have to get used to Python's library of Machine Learning packages: tensorflow, numpy, matplotlib, and finally pandas\n• Is there a way to improve this code?\n1 project \| reddit.com/r/learnpython \| 3 Apr 2021\n• Top 10 Python Libraries\n14 projects \| dev.to \| 24 Mar 2021\n• Matplotlib: why do plot and axes interfaces use different method names to do the exact same thing?\n1 project \| reddit.com/r/learnpython \| 5 Mar 2021\nI think sloppiness explains it, this explains how you can fix it ;)\n• How I create GitHub project reporting from scratch\n10 projects \| dev.to \| 5 Mar 2021\nFirstly, I tried the most popular visualization library matplotlib. But its configuration didn’t seem clear to me, so moved on with other options.\n• Valentine's Day Challenge\n1 project \| reddit.com/r/cryptography \| 17 Feb 2021\nThat would explain the link to https://matplotlib.org/ in the file...\n\nPyQtGraph\n\nPosts with mentions or reviews of PyQtGraph. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-22.\n\nWhat are some alternatives?\n\nWhen comparing matplotlib and PyQtGraph you can also consider the following projects:\n\nplotly - The interactive graphing library for Python (includes Plotly Express) :sparkles:\n\npygal - PYthon svg GrAph plotting Library\n\nVisPy - Main repository for Vispy\n\nbokeh - Interactive Data Visualization in the browser, from Python\n\nbqplot - Plotting library for IPython/Jupyter notebooks\n\nplotnine - A grammar of graphics for Python\n\nggplot - ggplot port for python\n\nGraphviz - Simple Python interface for Graphviz\n\nseaborn - Statistical data visualization in Python" ]	[ null, "https://avatars.githubusercontent.com/u/215947", null, "https://avatars.githubusercontent.com/u/5440571", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8061035,"math_prob":0.5026073,"size":9123,"snap":"2022-05-2022-21","text_gpt3_token_len":2405,"char_repetition_ratio":0.12764558,"word_repetition_ratio":0.1297186,"special_character_ratio":0.2744711,"punctuation_ratio":0.13908046,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96145296,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-01-21T12:29:44Z\",\"WARC-Record-ID\":\"<urn:uuid:b22e0d80-5ea3-4abe-9717-ac972da53e05>\",\"Content-Length\":\"37618\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b96a2e87-4cc3-4bf0-8449-c568132f8fae>\",\"WARC-Concurrent-To\":\"<urn:uuid:1c93d184-2512-49f9-88d1-d6bb78b1f767>\",\"WARC-IP-Address\":\"172.66.42.222\",\"WARC-Target-URI\":\"https://www.libhunt.com/compare-matplotlib-vs-pyqtgraph\",\"WARC-Payload-Digest\":\"sha1:H2I6T2WBTI7GAMYUVIAHQGXFEJW5OPRA\",\"WARC-Block-Digest\":\"sha1:2VV4WYFDIUGA3QRCP6LWMWW56GGPYTPS\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-05/CC-MAIN-2022-05_segments_1642320303356.40_warc_CC-MAIN-20220121101528-20220121131528-00712.warc.gz\"}"}
http://code.abettergeek.com/ABG/CasioPomrie/src/branch/master/translator.ps1	[ "Work to localize the Japanese-language Casio Pomrie software, which is required to use the Wi-Fi features of the Pomrie stamp maker.\nYou can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.\n\n#### 93 lines 2.8 KiB Raw Permalink Blame History\n\n `# read in the xib, original encoding is utf8` `\\$lines = Get-Content .\\MainMenu.xib -Encoding UTF8` `# set new variable for output` `# this is where we make our translation edits` `\\$output = \\$lines` `# pull out every line with a string keyed \"NSDev\"` `\\$regex = '(?.+?)<\\/string>'` `# regex results` `\\$strings = [regex]::Matches(\\$lines,\\$regex)` `# public translation API - no key required!` `# throttled to 40 requests per 60 seconds` `# one request per 1.5 seconds` `\\$url = 'https://translate.mentality.rip/translate'` `# log errors` `\\$errors = @()` `# create a CSV of translated values, to make corrections easier` `# this is because the final XIB still has base64-encoded strings` `\\$csv = 'Base64JP,UTF8JP,Base64EN,UTF8EN'` `# process every regex match` `foreach(\\$string in \\$strings) {` ` # get the base64 value` ` # uses named regex key` ` \\$txt = \\$string.Groups[\"txt\"].Value` ` # append appropriate padding` ` # sauce: https://gist.github.com/obscuresec/82775093ad892ef5fd00` ` \\$mod = (\\$txt.length % 4) ` ` switch (\\$mod) {` ` '0' {\\$txtp = \\$txt}` ` '1' {\\$txtp = \\$txt.Substring(0,\\$txt.Length - 1)}` ` '2' {\\$txtp = \\$txt + ('=' * (4 - \\$mod))}` ` '3' {\\$txtp = \\$txt + ('=' * (4 - \\$mod))}` ` ` ` }` ` # convert the base64 to UTF8 text` ` \\$utf = [Text.Encoding]::Utf8.GetString([Convert]::FromBase64String(\\$txtp))` ` # get current array index (for progress bar)` ` \\$idx = [array]::IndexOf(\\$strings,\\$string)` ` # get percent complete (for progress bar)` ` \\$pct = ((\\$idx + 1) / \\$strings.Count) * 100` ` # round the percent to one decimal` ` \\$pcn = [math]::Round(\\$pct,2)` ` # update the status bar` ` Write-Progress -Activity (\"Translating <<\" + \\$utf + \">>\") -Status \"\\$pcn% Complete:\" -PercentComplete \\$pct` ` # create the json request using Japanese string` ` \\$json = '{\"q\":\"' + \\$utf + '\",\"source\":\"ja\",\"target\":\"en\"}'` ` # add delay due to api throttle` ` Start-Sleep -Seconds 1.5` ` try {` ` # post the request to the translation service` ` \\$result = Invoke-WebRequest -Method 'Post' -Uri \\$url -Body \\$json -ContentType \"application/json; charset=utf-8\"` ` ` ` # this is the english translation` ` \\$ttxt = (\\$result.Content \| ConvertFrom-Json).translatedText` ` ` ` # convert the english translation to base64 using .net` ` \\$txt64 = [Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes(\\$ttxt))` ` ` ` # remove the padding == because these don't exist in the original XIB` ` \\$txt64clean = \\$txt64 -replace '=',''` ` ` ` # replace the value everywhere it occurs in the source data` ` \\$output = \\$output -replace \\$txt,\\$txt64clean` ` # add to the csv` ` \\$csv += \"`n\"\"\\$txt\"\",\"\"\\$utf\"\",\"\"\\$txt64clean\"\",\"\"\\$ttxt\"\"\"` ` } catch {` ` # couldn't translate, probably because it's already English` ` Write-Host (\"Couldn't translate <<\" + \\$utf + \">>\")` ` \\$errors += \\$utf` ` }` `}` `# save the xib` `\\$output \| Out-File Output.xib -Encoding utf8` `# save the csv` `\\$csv \| Out-File output.csv -Encoding utf8`" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.62832326,"math_prob":0.5687466,"size":3089,"snap":"2022-27-2022-33","text_gpt3_token_len":948,"char_repetition_ratio":0.12155592,"word_repetition_ratio":0.03816794,"special_character_ratio":0.37325996,"punctuation_ratio":0.13972056,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.966411,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-08-19T02:12:52Z\",\"WARC-Record-ID\":\"<urn:uuid:9a2bdd2e-c565-4c03-bcc2-911797e7853d>\",\"Content-Length\":\"68228\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:c9afe778-e911-43e6-a4c3-aab76d7f3bdc>\",\"WARC-Concurrent-To\":\"<urn:uuid:7e127f47-20f4-4f78-97df-42f302f9b12e>\",\"WARC-IP-Address\":\"72.14.177.31\",\"WARC-Target-URI\":\"http://code.abettergeek.com/ABG/CasioPomrie/src/branch/master/translator.ps1\",\"WARC-Payload-Digest\":\"sha1:NZ5AOHEF4ZQR5H7NR4TNX6IIXWTOVCMC\",\"WARC-Block-Digest\":\"sha1:NOVCGY4S2TVR3BFH3KLWJ2TZBYVHTW4W\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-33/CC-MAIN-2022-33_segments_1659882573540.20_warc_CC-MAIN-20220819005802-20220819035802-00441.warc.gz\"}"}
https://kerodon.net/tag/023L	[ "# Kerodon\n\n$\\Newextarrow{\\xRightarrow}{5,5}{0x21D2}$ $\\newcommand\\empty{}$\n\n### 5.1.5 Equivalences of Fibered $\\infty$-Categories\n\nLet $\\operatorname{\\mathcal{D}}$ be an $\\infty$-category. Our primary goal in this section is to show that, when studying $\\infty$-categories $\\operatorname{\\mathcal{C}}$ equipped with a cartesian fibration $\\operatorname{\\mathcal{C}}\\rightarrow \\operatorname{\\mathcal{D}}$, equivalence can be detected fiberwise. More precisely, we have the following result:\n\nTheorem 5.1.5.1. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}' }$\n\nwhere $U$ is a cartesian fibration of $\\infty$-categories, $U'$ is an isofibration of $\\infty$-categories, and $\\overline{F}$ is an equivalence of $\\infty$-categories. Then the functor $F$ is an equivalence of $\\infty$-categories if and only if it satisfies the following conditions:\n\n$(1)$\n\nFor every object $D \\in \\operatorname{\\mathcal{D}}$ having image $D' = \\overline{F}(D)$ in $\\operatorname{\\mathcal{D}}'$, the induced functor\n\n$F_{D}: \\operatorname{\\mathcal{C}}_{D} = \\{ D\\} \\times _{\\operatorname{\\mathcal{D}}} \\operatorname{\\mathcal{C}}\\rightarrow \\{ D' \\} \\times _{\\operatorname{\\mathcal{D}}'} \\operatorname{\\mathcal{C}}' = \\operatorname{\\mathcal{C}}'_{D'}$\n\nis an equivalence of $\\infty$-categories.\n\n$(2)$\n\nThe functor $F$ carries $U$-cartesian morphisms of $\\operatorname{\\mathcal{C}}$ to $U'$-cartesian morphisms of $\\operatorname{\\mathcal{C}}'$.\n\nMoreover, if these conditions are satisfied, then $U'$ is also a cartesian fibration of $\\infty$-categories.\n\nWe will give the proof of Theorem 5.1.5.1 at the end of this section. First, let us collect some of its consequences.\n\nCorollary 5.1.5.2. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}'. }$\n\nAssume that $U$ and $U'$ are isofibrations of $\\infty$-categories and that $F$ and $\\overline{F}$ are equivalences of $\\infty$-categories. Then:\n\n• The functor $U$ is a cartesian fibration if and only if $U'$ is a cartesian fibration.\n\n• The functor $U$ is a cocartesian fibration if and only if $U'$ is a cocartesian fibration.\n\nProof. We will prove the first assertion; the second follows by a similar argument. It follows from Theorem 5.1.5.1 that if $U$ is a cartesian fibration, then $U'$ is also a cartesian fibration. To prove the converse, choose functors $G': \\operatorname{\\mathcal{C}}' \\rightarrow \\operatorname{\\mathcal{C}}$ and $\\overline{G}: \\operatorname{\\mathcal{D}}' \\rightarrow \\operatorname{\\mathcal{D}}$ which are homotopy inverse to the equivalences $F$ and $\\overline{F}$, respectively. We then have isomorphisms\n\n$U \\circ G' \\circ F \\simeq U \\simeq \\overline{G} \\circ \\overline{F} \\circ U = \\overline{G} \\circ U' \\circ F$\n\nin the functor $\\infty$-category $\\operatorname{Fun}(\\operatorname{\\mathcal{C}}, \\operatorname{\\mathcal{D}})$. Since $F$ is an equivalence of $\\infty$-categories, it follows that there exists an isomorphism $\\overline{\\alpha }: U \\circ G' \\rightarrow \\overline{G} \\circ U'$ in the functor $\\infty$-category $\\operatorname{Fun}(\\operatorname{\\mathcal{C}}', \\operatorname{\\mathcal{D}})$. Using our assumption that $U'$ is an isofibration, we can lift $\\overline{\\alpha }$ to an isomorphism of functors $\\alpha : G' \\rightarrow G$ (Proposition 4.4.5.8). Applying Theorem 5.1.5.1 to the commutative diagram\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}' \\ar [r]^-{G} \\ar [d]^-{U'} & \\operatorname{\\mathcal{C}}\\ar [d]^-{U} \\\\ \\operatorname{\\mathcal{D}}' \\ar [r]^-{\\overline{G}} & \\operatorname{\\mathcal{D}}, }$\n\nwe conclude that if $U'$ is a cartesian fibration, then $U$ is also a cartesian fibration. $\\square$\n\nCorollary 5.1.5.3. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}'. }$\n\nAssume that $U$ and $U'$ are isofibrations of $\\infty$-categories and that $F$ and $\\overline{F}$ are equivalences of $\\infty$-categories. Then:\n\n• The functor $U$ is a right fibration if and only if $U'$ is a right fibration.\n\n• The functor $U$ is a left fibration if and only if $U'$ is a left fibration.\n\nProof. We will prove the first assertion; the second follows by a similar argument. Assume first that $U'$ is a right fibration of $\\infty$-categories. Then $U'$ is a cartesian fibration (Proposition 5.1.4.14), so Corollary 5.1.5.2 implies that $U$ is a cartesian fibration. To prove that $U$ is a right fibration, it will suffice to show that for every object $D \\in \\operatorname{\\mathcal{D}}$, the fiber $\\operatorname{\\mathcal{C}}_{D} = \\{ D\\} \\times _{\\operatorname{\\mathcal{D}}} \\operatorname{\\mathcal{C}}$ is a Kan complex (Proposition 5.1.4.14). This follows from Remark 4.5.1.21, since the functor $F$ induces an equivalence of $\\infty$-categories $F_{D}: \\operatorname{\\mathcal{C}}_{D} \\rightarrow \\operatorname{\\mathcal{C}}'_{ \\overline{F}(D)}$ (Corollary 4.5.4.7).\n\nWe now prove the reverse implication. Arguing as in the proof of Corollary 5.1.5.2, we can construct a commutative diagram\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}' \\ar [r]^-{G} \\ar [d]^-{U'} & \\operatorname{\\mathcal{C}}\\ar [d]^-{U} \\\\ \\operatorname{\\mathcal{D}}' \\ar [r]^-{\\overline{G}} & \\operatorname{\\mathcal{D}}, }$\n\nwhere $G$ and $\\overline{G}$ are homotopy inverses of the equivalences $F$ and $\\overline{F}$, respectively. It then follows from the preceding argument that if $U$ is a right fibration of $\\infty$-categories, then $U'$ is also a right fibration of $\\infty$-categories. $\\square$\n\nCorollary 5.1.5.4. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{\\overline{F}} & \\operatorname{\\mathcal{D}}'. }$\n\nwhere $U$ and $U'$ are right fibrations and the functor $\\overline{F}$ is an equivalence of $\\infty$-categories. Then $F$ is an equivalence of $\\infty$-categories if and only if, for every object $D \\in \\operatorname{\\mathcal{D}}$ having image $D' = \\overline{F}(D) \\in \\operatorname{\\mathcal{D}}'$, the induced map of fibers $F_{D}: \\operatorname{\\mathcal{C}}_{D} \\rightarrow \\operatorname{\\mathcal{C}}'_{D'}$ is a homotopy equivalence of Kan complexes.\n\nThe proof of Theorem 5.1.5.1 will require some preliminaries. Our first step is to show that if $U: \\operatorname{\\mathcal{C}}\\rightarrow \\operatorname{\\mathcal{D}}$ is an isofibration of $\\infty$-categories, then the collection of $U$-cartesian morphisms of $\\operatorname{\\mathcal{C}}$ is invariance under categorical equivalence.\n\nLemma 5.1.5.5. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}', }$\n\nwhere the functors $U$ and $U'$ are inner fibrations and the functors $F$ and $\\overline{F}$ are fully faithful. Let $g: Y \\rightarrow Z$ be a morphism in $\\operatorname{\\mathcal{C}}$. If $F(g)$ is a $U'$-cartesian morphism of $\\operatorname{\\mathcal{C}}'$, then $g$ is a $U$-cartesian morphism of $\\operatorname{\\mathcal{C}}$.\n\nProof. By virtue of Proposition 5.1.2.1, it will suffice to show that for every object $X \\in \\operatorname{\\mathcal{C}}$, the diagram of Kan complexes\n\n5.9\n\\begin{equation} \\begin{gathered}\\label{equation:fully-faithful-check-cartesian} \\xymatrix@R =50pt@C=50pt{ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(X,Y,Z) \\times _{ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(Y,Z) } \\{ g\\} \\ar [r] \\ar [d] & \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(X,Z) \\ar [d] \\\\ \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}}( U(X), U(Y), U(Z) ) \\times _{ \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}}( U(Y), U(Z)) } \\{ U(g) \\} \\ar [r] & \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}}( U(X), U(Z) ) } \\end{gathered} \\end{equation}\n\nis a homotopy pullback square. Set $X' = F(X)$, $Y' = F(Y)$, $Z' = F(Z)$, and $g' = F(g)$. Since the functors $F$ and $\\overline{F}$ are fully faithful, (5.9) is homotopy equivalent to the diagram\n\n5.10\n\\begin{equation} \\begin{gathered}\\label{equation:fully-faithful-check-cartesian2} \\xymatrix@R =50pt@C=25pt{ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}'}(X',Y',Z') \\times _{ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(Y',Z') } \\{ g'\\} \\ar [r] \\ar [d] & \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}'}(X',Z') \\ar [d] \\\\ \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}'}( U'(X'), U'(Y'), U'(Z') ) \\times _{ \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}'}( U'(Y), U'(Z)) } \\{ U'(g') \\} \\ar [r] & \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}'}( U'(X'), U'(Z') ). } \\end{gathered} \\end{equation}\n\nOur assumption that $g'$ is $U'$-cartesian guarantees that (5.10) is a homotopy pullback square of Kan complexes (Proposition 5.1.2.1), so that (5.9) is also a homotopy pullback square (Corollary 3.4.1.10). $\\square$\n\nProposition 5.1.5.6. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}', }$\n\nwhere the functors $U$ and $U'$ are isofibrations and the functors $F$ and $\\overline{F}$ are equivalences of $\\infty$-categories. Let $g: Y \\rightarrow Z$ be a morphism in $\\operatorname{\\mathcal{C}}$. Then $g$ is $U$-cartesian if and only if $F(g)$ is $U'$-cartesian.\n\nProof. It follows from Lemma 5.1.5.5 that if $F(g)$ is $U'$-cartesian, then $g$ is $U$-cartesian. For the converse, suppose that $g$ is $U$-cartesian. Arguing as in the proof of Corollary 5.1.5.2, we can construct a commutative diagram\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}' \\ar [r]^-{G} \\ar [d]^-{U'} & \\operatorname{\\mathcal{C}}\\ar [d]^-{U} \\\\ \\operatorname{\\mathcal{D}}' \\ar [r]^-{\\overline{G}} & \\operatorname{\\mathcal{D}}, }$\n\nwhere $G$ and $\\overline{G}$ are homotopy inverses of the equivalences $F$ and $\\overline{F}$, respectively. Then $G( F(g) )$ is isomorphic to $g$ as an object of the arrow $\\infty$-category $\\operatorname{Fun}(\\Delta ^1, \\operatorname{\\mathcal{C}})$. Invoking Corollary 5.1.2.5, we conclude that $G( F(g) )$ is $U$-cartesian, so that $F(g)$ is $U'$-cartesian by virtue of Lemma 5.1.5.5. $\\square$\n\nProposition 5.1.5.7. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{q} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{q'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{\\overline{F}} & \\operatorname{\\mathcal{D}}'. }$\n\nAssume that:\n\n$(1)$\n\nThe functors $q$ and $q'$ are inner fibrations.\n\n$(2)$\n\nThe inner fibration $q$ is cartesian and the functor $F$ carries $q$-cartesian morphisms of $\\operatorname{\\mathcal{C}}$ to locally $q'$-cartesian morphisms of $\\operatorname{\\mathcal{C}}'$.\n\n$(3)$\n\nThe functor $\\overline{F}: \\operatorname{\\mathcal{D}}\\rightarrow \\operatorname{\\mathcal{D}}'$ is fully faithful.\n\nThen $F$ is fully faithful if and only if, for every object $D \\in \\operatorname{\\mathcal{D}}$ having image $D' = \\overline{F}(D) \\in \\operatorname{\\mathcal{D}}'$, the induced map of fibers $F_{D}: \\operatorname{\\mathcal{C}}_{D} \\rightarrow \\operatorname{\\mathcal{C}}'_{D'}$ is fully faithful.\n\nProof. The “only if” direction follows from Proposition 4.6.2.6. For the converse, assume that each of the functors $F_{D}$ is fully faithful; we will show that $F$ is fully faithful. Let $X$ and $Z$ be objects of $\\operatorname{\\mathcal{C}}$ having images $\\overline{X}, \\overline{Z} \\in \\operatorname{\\mathcal{D}}$; we wish to show that the upper horizontal map in the diagram of Kan complexes\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(X,Z) \\ar [r] \\ar [d] & \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}'}( F(X), F(Z) ) \\ar [d] \\\\ \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}}( \\overline{X}, \\overline{Z} ) \\ar [r] & \\operatorname{Hom}_{\\operatorname{\\mathcal{D}}'}( \\overline{F}( \\overline{X} ), \\overline{F}( \\overline{Z} )) }$\n\nis a homotopy equivalence. Since $q$ and $q'$ are inner fibrations, the vertical maps are Kan fibrations (Proposition 4.6.1.19). Assumption $(3)$ guarantees that the lower horizontal map is a homotopy equivalence. By virtue of Proposition 3.2.8.1, it will suffice to show that for every morphism $\\overline{e}: \\overline{X} \\rightarrow \\overline{Z}$ in $\\operatorname{\\mathcal{D}}$, the induced map of fibers\n\n$\\theta : \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(X,Z)_{\\overline{e}} \\rightarrow \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}'}( F(X), F(Z) )_{ \\overline{F}(\\overline{e} ) }$\n\nis a homotopy equivalence.\n\nLet $[\\theta ]$ denote the homotopy class of $\\theta$, regarded as a morphism in the homotopy category $\\mathrm{h} \\mathit{\\operatorname{Kan}}$. Since $q$ is a cartesian fibration, there exists a $q$-cartesian morphism $g: Y \\rightarrow Z$ of $\\operatorname{\\mathcal{C}}$ satisfying $q(g) = \\overline{e}$. We then have a commutative diagram\n\n$\\xymatrix@C =50pt@R=50pt{ \\operatorname{Hom}_{ \\operatorname{\\mathcal{C}}_{ \\overline{X} }}(X,Y) \\ar [d]^-{ [g] \\circ } \\ar [r] & \\operatorname{Hom}_{ \\operatorname{\\mathcal{C}}'_{ \\overline{F}(\\overline{X})} }( F(X), F(Y) ) \\ar [d]^-{ [F(g)] \\circ } \\\\ \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}}(X,Z)_{ \\overline{e} } \\ar [r]^-{ [ \\theta ] } & \\operatorname{Hom}_{\\operatorname{\\mathcal{C}}'}( F(X), F(Z) )_{ \\overline{F}( \\overline{e} ) } }$\n\nin $\\mathrm{h} \\mathit{\\operatorname{Kan}}$, where the vertical maps are given by the composition law of Notation 5.1.3.10. Assumption $(2)$ guarantees that $F(g)$ is locally $q'$-cartesian, so that the vertical maps in this diagram are isomorphisms in $\\mathrm{h} \\mathit{\\operatorname{Kan}}$ (Proposition 5.1.3.11). It will therefore suffice to show that the functor $F_{\\overline{X}}$ induces a homotopy equivalence of mapping spaces $\\operatorname{Hom}_{ \\operatorname{\\mathcal{C}}_{ \\overline{X} }}(X,Y) \\rightarrow \\operatorname{Hom}_{ \\operatorname{\\mathcal{C}}'_{ \\overline{F}(\\overline{X})} }( F(X), F(Y) )$, which follows from our assumption that $F_{ \\overline{X} }$ is fully faithful. $\\square$\n\nRemark 5.1.5.8. In the situation of Proposition 5.1.5.7, we can replace $(2)$ with the following a priori weaker assumption:\n\n$(2')$\n\nFor every object $Z \\in \\operatorname{\\mathcal{C}}$ and every morphism $\\overline{u}: \\overline{Y} \\rightarrow q(Z)$ in $\\operatorname{\\mathcal{D}}$, there exists a $q$-cartesian $u: Y \\rightarrow Z$ of $\\operatorname{\\mathcal{C}}$ satisfying $q(u) = \\overline{u}$ and for which $F(u)$ is locally $q'$-cartesian.\n\nAssume that $(2)$ is satisfied and let $v: X \\rightarrow Z$ be any $q$-cartesian morphism in $\\operatorname{\\mathcal{C}}$; we wish to show that $F(v)$ is locally $q'$-cartesian. To prove this, we can assume without loss of generality that $\\operatorname{\\mathcal{D}}= \\Delta ^1 = \\operatorname{\\mathcal{D}}'$ and that $\\overline{F}$ is the identity map. Using $(2')$, we can choose another $q$-cartesian morphism $u: Y \\rightarrow Z$ satisfying $q(u) = q(v)$ for which $F(u)$ is $q'$-cartesian. Applying Remark 5.1.3.8, we see that $v$ can be obtained as a composition of $u$ with an isomorphism in the $\\infty$-category $\\operatorname{\\mathcal{C}}$. Then $F(v)$ can be obtained as the composition of $F(u)$ with an isomorphism in the $\\infty$-category $\\operatorname{\\mathcal{C}}'$, and is therefore $q$-cartesian by virtue of Corollary 5.1.2.4 (and Proposition 5.1.1.8).\n\nProof of Theorem 5.1.5.1. Suppose we are given a commutative diagram of $\\infty$-categories\n\n$\\xymatrix@R =50pt@C=50pt{ \\operatorname{\\mathcal{C}}\\ar [r]^-{F} \\ar [d]^-{U} & \\operatorname{\\mathcal{C}}' \\ar [d]^-{U'} \\\\ \\operatorname{\\mathcal{D}}\\ar [r]^-{ \\overline{F} } & \\operatorname{\\mathcal{D}}' }$\n\nwhere $U$ is a cartesian fibration of $\\infty$-categories, $U'$ is an isofibration of $\\infty$-categories, and $\\overline{F}$ is an equivalence of $\\infty$-categories. If $F$ satisfies conditions $(1)$ and $(2)$ of Theorem 5.1.5.1, then it is fully faithful (Proposition 5.1.5.7) and essentially surjective (Remark 4.6.2.16), hence an equivalence of $\\infty$-categories by virtue of Theorem 4.6.2.17. Conversely, if $F$ is an equivalence of $\\infty$-categories, then it satisfies conditions $(1)$ and $(2)$ by virtue of Corollary 4.5.4.7 and Proposition 5.1.5.7, respectively. To complete the proof, we must show that if these conditions are satisfied, then $U'$ is also a cartesian fibration of $\\infty$-categories.\n\nLet $Z'$ be an object of $\\operatorname{\\mathcal{C}}'$ and let $\\overline{g}': \\overline{Y}' \\rightarrow U'(Z')$ be a morphism in $\\operatorname{\\mathcal{D}}'$; we wish to show that $\\overline{g}'$ can be lifted to a $U'$-cartesian morphism $Y' \\rightarrow Z'$ in $\\operatorname{\\mathcal{C}}'$. Since $F$ is essentially surjective, we can choose an object $Z \\in \\operatorname{\\mathcal{C}}$ and an isomorphism $v: F(Z) \\rightarrow Z'$ in the $\\infty$-category $\\operatorname{\\mathcal{C}}'$. Since $\\overline{F}$ is essentially surjective, we can choose an object $\\overline{Y} \\in \\operatorname{\\mathcal{D}}$ and an isomorphism $\\overline{u}: \\overline{F}(\\overline{Y}) \\rightarrow \\overline{Y}'$ in the $\\infty$-category $\\operatorname{\\mathcal{D}}'$. Since $\\overline{F}$ is fully faithful at the level of homotopy categories, we can choose a morphism $\\overline{g}: \\overline{Y} \\rightarrow U(Z)$ in $\\operatorname{\\mathcal{D}}$ for which the diagram\n\n$\\xymatrix@R =50pt@C=50pt{ \\overline{F}( \\overline{Y} ) \\ar [r]^-{ \\overline{F}( \\overline{g} ) } \\ar [d] & \\overline{F}( U(Z) ) \\ar [d]^-{ U'(v) } \\\\ \\overline{Y}' \\ar [r]^-{ \\overline{g}' } & \\overline{Z}', }$\n\ncommutes in the homotopy category $\\mathrm{h} \\mathit{\\operatorname{\\mathcal{D}}'}$, and can therefore be lifted to a commutative diagram $\\overline{\\sigma }$ in $\\infty$-category $\\operatorname{\\mathcal{D}}'$ (see Exercise 1.4.2.10). Using our assumption that $U$ is a cartesian fibration, we can lift $\\overline{g}$ to a $U$-cartesian morphism $g: Y \\rightarrow Z$ of $\\operatorname{\\mathcal{C}}$. Since $U'$ is an isofibration, Proposition 4.4.5.8 guarantees that we can lift $\\overline{\\sigma }$ to a commutative diagram $\\sigma :$\n\n$\\xymatrix@R =50pt@C=50pt{ F(Y) \\ar [r]^-{ F(g) } \\ar [d] & F(Z) \\ar [d]^-{ v } \\\\ Y' \\ar [r]^-{ g' } & Z' }$\n\nin the $\\infty$-category $\\operatorname{\\mathcal{C}}'$, where the vertical maps are isomorphisms. To complete the proof, it will suffice to show that the morphism $g'$ is $U'$-cartesian. This follows from Corollary 5.1.2.5, since the morphism $F(g)$ is $U'$-cartesian (Proposition 5.1.5.6). $\\square$" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.5451449,"math_prob":0.99992144,"size":18463,"snap":"2021-43-2021-49","text_gpt3_token_len":6472,"char_repetition_ratio":0.28815213,"word_repetition_ratio":0.29092526,"special_character_ratio":0.3358609,"punctuation_ratio":0.1125,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":1.0000043,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-18T08:29:44Z\",\"WARC-Record-ID\":\"<urn:uuid:ab0ec2a0-e1c3-4bfb-92c3-445720a6a654>\",\"Content-Length\":\"33823\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:68bb0364-e949-436d-afa9-dce00a6dfc86>\",\"WARC-Concurrent-To\":\"<urn:uuid:890a66f0-80c3-4bac-9249-1b4b9e71a8f1>\",\"WARC-IP-Address\":\"35.173.69.207\",\"WARC-Target-URI\":\"https://kerodon.net/tag/023L\",\"WARC-Payload-Digest\":\"sha1:A2FYGGSZS4KMO2YMRZFHLDMTQMUEW6CJ\",\"WARC-Block-Digest\":\"sha1:5HINTJ4QOLW6Q4ZGH4P3EP6TQA5JUP4Y\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323585199.76_warc_CC-MAIN-20211018062819-20211018092819-00692.warc.gz\"}"}
https://www.csdn.net/tags/MtjaMg1sMjE0MzgtYmxvZwO0O0OO0O0O.html	[ "• 为什么平均磁盘寻道时间是完整寻道时间的三分之一？(Why is average disk seek time one-third of the full...\n2021-07-16 02:02:54\n\n为什么平均磁盘寻道时间是完整寻道时间的三分之一？(Why is average disk seek time one-third of the full seek time?)\n\n考虑到磁盘性能，我已经阅读过很多书和论文，平均搜索时间大约是完整搜索时间的三分之一，但没有人真正提供任何解释。这是从哪里来的？\n\nI have read in many books and papers, considering disk performance, that the average seek time is roughly one-third of the full seek time, but no one really offers any explanation about that. Where does this come from?\n\n原文：https://stackoverflow.com/questions/9828736\n\n更新时间：2020-01-09 20:34\n\n最满意答案\n\n平均值使用微积分进行数学计算。我们使用非常基本的公式来计算平均值。\n\n平均寻道时间=(所有可能寻道时间的总和)/(可能寻道时间的总数)\n\n假定磁盘具有N个磁道，所以这些磁道的编号从1 ... N。在任何时间点磁头的位置可以是从0到N(包含)的任何值。让我们说，磁头的初始位置在轨道'x'处，并且磁头的最终位置在轨道'y'处，以便x可以从0变化到N，并且y可以从0变化到N.\n\n根据我们对平均寻道时间的定义，我们可以这样说，\n\n平均寻道距离=(所有可能寻道距离之和)/(可能寻道距离的总数)\n\n按照x和y的定义，Total no。 (x = 0，N)SIGMA(y = 0，N)\| xy \| = INTEGRAL(x = 0，N)INTEGRAL(y = 0，N)\| xy \| dy dx\n\n为了解决这个问题，使用将表达式的模数分解为y = 0到x和y = x到N的技巧。然后求解x = 0到N.\n\n这出来是(N ^ 3)/ 3。\n\n平均搜索距离=(N ^ 3)/ 3 * N * N = N / 3\n\n平均寻道时间=平均寻道距离/寻道率\n\n如果从位置0到轨道N的寻道时间需要't'秒，则寻找速率= N / t\n\n因此，avg寻道时间=(N / 3)/(N / t)= t / 3\n\n参考：\n\nThe average is calculated mathematically using calculus. We use the very basic formula for calculation of average.\n\nAverage seek time = (Sum of all possible seek times)/(Total no. of possible seek times)\n\nThe disk is assumed to have N number of tracks, so that these are numbered from 1...N The position of the head at any point of time can be anything from 0 to N (inclusive). Let us say that the initial position of the disk head is at track 'x' and the final position of the disk head is at track 'y' , so that x can vary from 0 to N and also, y can vary from 0 to N.\n\nOn similar lines as we defined average seek time, we can say that,\n\nAverage seek distance = (Sum of all possible seek distances)/(total no. of possible seek distances)\n\nBy definition of x and y, Total no. of possible seek distances = NN and Sum of all possible seek distances = SIGMA(x=0,N) SIGMA(y=0,N) \|x-y\| = INTEGRAL(x=0,N)INTEGRAL(y=0,N) \|x-y\| dy dx\n\nTo solve this, use the technique of splitting modulus of the expression for y = 0 to x and for y = x to N. Then solve for x = 0 to N.\n\nThis comes out to be (N^3)/3.\n\nAvg seek distance = (N^3)/3NN = N/3\n\nAverage seek time = Avg seek distance / seek rate\n\nIf the seek time for the from position 0 to track N takes 't' seconds then seek rate = N/t\n\nTherefore, avg seek time = (N/3)/(N/t) = t/3\n\nReference:\n\n相关问答\n\n当您向BufferedOutputStream写入100,000个字节时，您的程序将显式访问文件的每个字节并写入零。在本地文件上使用RandomAccessFile.seek()时，您间接使用C系统调用fseek() 。如何处理取决于操作系统。在大多数现代操作系统中，支持稀疏文件。这意味着如果您要求空的100,000字节文件，则实际上不会使用100,000字节的磁盘空间。当您写入字节100,001时，操作系统仍然不使用100,001字节的磁盘。它为包含“真实”数据的块分配少量空间，并\n\n...\n\n所有寻求系统调用都会改变下一次读取文件的位置。它不会移动驱动器头。读取或写入数据时驱动器磁头会移动，而您无法直接控制下一步操作系统的操作。读取大量不需要的数据会产生影响，因为所有读取的数据都需要OS缓冲区中的空间，并导致旧数据丢失。因此，使用查找大文件将会导致文件系统缓存更少。我所写的所有内容都假设你无法在内存中放入整个数据库。如果可以的话，就这样做。阅读所有内容并尝试在文件末尾添加新的和已更改的数据。不要担心浪费的空间，只是偶尔做一些压缩。如果你的数据库太大：数据以块(或页面\n\n...\n\n经过很多反复试验，我想我终于明白了这一点。首先你需要计算你的文件的采样率。为此，获取AudioNode的最后渲染时间： var nodetime: AVAudioTime = self.playerNode.lastRenderTime\n\nvar playerTime: AVAudioTime = self.playerNode.playerTimeForNodeTime(nodetime)\n\nvar sampleRate = playerTime.sampleRate\n\n然后，以秒为单位将采样\n\n...\n\n磁头可能会到位，但磁盘可能不在该位置的正确位置。所以想象首先必须移动头部，然后等待主轴旋转。当头部到达时，它可能就在那里，但是可能需要等待至少半圈才能达到正确的扇区。所以总结它们两者都允许。编辑：所以想象它就像一个Merry Go Round。你可以在2秒内跑到最快乐的地方(你是头脑)。但是你可能需要等待5到10秒才能让你的特定马匹在你抵达后到达你身边(马是你想要进入的部门)。 The head may get into place, but the disk might not b\n\n...\n\n平均值使用微积分进行数学计算。我们使用非常基本的公式来计算平均值。平均寻道时间=(所有可能寻道时间的总和)/(可能寻道时间的总数) 假定磁盘具有N个磁道，所以这些磁道的编号从1 ... N。在任何时间点磁头的位置可以是从0到N(包含)的任何值。让我们说，磁头的初始位置在轨道'x'处，并且磁头的最终位置在轨道'y'处，以便x可以从0变化到N，并且y可以从0变化到N. 根据我们对平均寻道时间的定义，我们可以这样说，平均寻道距离=(所有可能寻道距离之和)/(可能寻道距离的总数) 按照x和y的定义\n\n...\n\n这在seekToTime:的文档中seekToTime: ：寻求的时间可能与指定的效率时间不同。对于样本的准确求求，请参阅seekToTime:toleranceBefore:toleranceAfter: . 因此，尝试使用seekToTime:toleranceBefore:toleranceAfter:相反，指定低容差或零容差。在创建可能正在使用的任何AVURLAssets时，您可能还希望为AVURLAssetPreferPreciseDurationAndTimingKey指定tru\n\n...\n\n确保你有良好的联系视频应该压缩为流媒体(产生巨大的差异) 使用bufferTime参数来获得理想的设置用代码创建一个玩家，不要使用UI组件。你会有更多的灵活性： http ： //blog.martinlegris.com/2008/06/03/tutorial-playing-flv-video-in-plain-as3-part-1/ 警告，更长的缓冲区将允许更平滑的播放，更短的将寻求更快，但权衡是它将更频繁地击中缓冲区...不理想 make sure you have a good c\n\n...\n\n但是视频的AVCodecContext-> time_base == 1001/60000 这让我很困惑，我不明白。 time_base是AVRational类型的，它是一个由分子和分母组成的有理数，而不是使用小数点。我假设他们不只是使用double的原因是这样你不会失去任何精度。 AVRational在来源中定义为： typedef struct AVRational{\n\nint num; ///< numerator\n\nint den; ///< denominator\n\n} AV\n\n...\n\n问题是，流程图只能寻求关键帧，以便能够寻找任何秒，你需要每秒钟都有关键帧。很可能这意味着您需要在使用配置为每秒强制关键帧的ffmpeg上传视频时重新编码视频。 The issue is that flowplayer can seek to keyframes only so in order to be able to seek to any second you need to have keyframe for every second. Most probably that means\n\n...\n\n经过几次实验后，我找到了自己问题的答案。经过非常频繁的文件concat操作(大约每分钟1k)后，数据节点在一天左右开始抱怨太多块，这导致我相信这确实会导致磁盘碎片化和块数增加。我使用的解决方案是编写一个单独的作业，将这些文件连接(并压缩在我的情况下)为单个可拆分的归档文件(注意gzip不可拆分！)。 After a few experiments I found the answer to my own question. After very frequent file concat ope\n\n...\n\n更多相关内容\n• 最短寻道时间优先（SSTF）和扫描（SCAN）算法。理解各调度算法的工作原理对给出的任意的磁盘请求序列、计算平均寻道长度；要求可定制磁盘请求序列长度、磁头起始位置、磁头移动方向。测试：假设磁盘访问序列：98，...", null, "操作系统实验\n• 操作系统中的，4种寻道算法。FCFS(先来先服务) SSTF(最短寻道时间) SCAN(扫描算法) CSCAN(循环扫描法)\n• 可以对给出的任意的磁盘请求序列、计算平均寻道长度；要求可定制磁盘请求序列长度、磁头起始位置、磁头移动方向。测试：假设磁盘访问序列：98，183，37，122，14，124，65，67；读写头起始位置：53，方向：磁道...", null, "算法\n• 操作系统实验-磁盘调度：先来先服务、最短寻道时间算法", null, "计算机实验\n• 操作系统模拟之磁盘寻道算法。文件共1份，代码如下： import math import random import copy def alo_fcfs(): print(\"您选择了FCFS算法，执行结果如下：\") print(\"当前磁道号下一磁道号绝对差\") print('{:...\n\n操作系统模拟之磁盘寻道算法。\n文件共1份，代码如下：\n\nimport math\nimport random\nimport copy\n\ndef alo_fcfs():\nprint(\"您选择了FCFS算法，执行结果如下：\")\nprint(\"当前磁道号下一磁道号绝对差\")\nprint('{:6d}{:10d}{:8d}'.format(start_numer, disk_queue, abs(start_numer - disk_queue)))\nsum_distance = abs(start_numer - disk_queue)\nfor i in range(disk_queue_length - 1):\nsum_distance = sum_distance + abs(disk_queue[i] - disk_queue[i + 1])\nprint('{:6d}{:10d}{:8d}'.format(disk_queue[i], disk_queue[i + 1], abs(disk_queue[i] - disk_queue[i + 1])))\nprint('{:6d} {} {}'.format(disk_queue[i], \"None\", \"None\"))\nprint('寻道序列总长{:d}，FCFS算法的平均寻道长度为{:.2f}'.format(sum_distance, sum_distance / (disk_queue_length + 1)))\n\ndef alo_sstf():\nprint(\"您选择了SSTF算法，执行结果如下：\")\nprint(\"当前磁道号下一磁道号绝对差\")\nsum_distance = 0\nlast_number = start_numer\ntemp_queue = copy.deepcopy(disk_queue)\nwhile len(temp_queue) > 0:\nindex = 0\nmin_diff = 0x3f3f3f3f\nfor i in range(len(temp_queue)):\nif abs(temp_queue[i] - last_number) < min_diff:\nindex = i\nmin_diff = abs(temp_queue[i] - last_number)\nprint('{:6d}{:10d}{:8d}'.format(last_number, temp_queue[index], min_diff))\nlast_number = temp_queue[index]\nsum_distance = sum_distance + min_diff\ntemp_queue.pop(index)\nprint('{:6d} {} {}'.format(last_number, \"None\", \"None\"))\nprint('寻道序列总长{:d}，SSTF算法的平均寻道长度为{:.2f}'.format(sum_distance, sum_distance / (disk_queue_length + 1)))\n\ndef cal(temp_queue, start_number, index, left1, left2, right1, right2, step1, step2):\nlast_number = start_number\nprint('{:6d}{:10d}{:8d}'.format(last_number, temp_queue[index], abs(last_number - temp_queue[index])))\nsum_distance = abs(last_number - temp_queue[index])\nlast_number = temp_queue[index]\nfor j in range(left1, right1, step1):\nprint('{:6d}{:10d}{:8d}'.format(last_number, temp_queue[j], abs(last_number - temp_queue[j])))\nsum_distance = sum_distance + abs(last_number - temp_queue[j])\nlast_number = temp_queue[j]\nfor j in range(left2, right2, step2):\nprint('{:6d}{:10d}{:8d}'.format(last_number, temp_queue[j], abs(last_number - temp_queue[j])))\nsum_distance = sum_distance + abs(last_number - temp_queue[j])\nlast_number = temp_queue[j]\nprint('{:6d} {} {}'.format(last_number, \"None\", \"None\"))\nprint('寻道序列总长{:d}，FCFS算法的平均寻道长度为{:.2f}'.format(sum_distance, sum_distance / (disk_queue_length + 1)))\n\ndef alo_scan():\nprint(\"您选择了SCAN算法，执行结果如下：\")\nprint(\"请继续选择当前磁头运动方向\")\nprint(\"由低到高请输入1\")\nprint(\"由高到低请输入2\")\nlast_number = start_numer\ndirection_choice = int(input())\ntemp_queue = copy.deepcopy(disk_queue)\ntemp_queue.sort()\nprint()\nprint(\"当前磁道号下一磁道号绝对差\")\nif direction_choice == 1:\nfor j in temp_queue:\nif j > start_numer:\nindex = temp_queue.index(j)\nbreak\ncal(temp_queue, start_numer, index, index + 1, index - 1, disk_queue_length, -1, 1, -1)\nelif direction_choice == 2:\nfor j in range(disk_queue_length - 1, -1, -1):\nif temp_queue[j] < start_numer:\nindex = j\nbreak\ncal(temp_queue, start_numer, index, index - 1, index + 1, -1, disk_queue_length, -1, 1)\n\ndef alo_cscan():\nprint(\"您选择了CSCAN算法，执行结果如下：\")\nprint(\"请继续选择当前磁头运动方向\")\nprint(\"由低到高请输入1\")\nprint(\"由高到低请输入2\")\nlast_number = start_numer\ndirection_choice = int(input())\ntemp_queue = copy.deepcopy(disk_queue)\ntemp_queue.sort()\nprint()\nprint(\"当前磁道号下一磁道号绝对差\")\nif direction_choice == 1:\nfor j in temp_queue:\nif j > start_numer:\nindex = temp_queue.index(j)\nbreak\ncal(temp_queue, start_numer, index, index + 1, 0, disk_queue_length, index, 1, 1)\nelif direction_choice == 2:\nfor j in range(disk_queue_length - 1, -1, -1):\nif temp_queue[j] < start_numer:\nindex = j\nbreak\ncal(temp_queue, start_numer, index, index - 1, disk_queue_length - 1, -1, index, -1, -1)\n\nif __name__ == \"__main__\":\nprint(\"欢迎进入操作系统演示之磁盘寻道算法\")\nprint(\"现在开始数据初始化\")\nprint(\"请输入磁盘寻道序列长度（10-20，含端点）：\")\ndisk_queue_length = int(input())\nif 10 <= disk_queue_length <= 20:\nprint(\"输入成功！\")\nelse:\nprint(\"您输入的磁盘寻道序列长度超出给定范围，请重新输入10-20（含端点）的数字：\")\nprint(\"请输入磁盘寻道序列长度（10-20，含端点）：\")\ndisk_queue_length = int(input())\n\ndisk_queue = []\nfor k in range(disk_queue_length):\ndisk_queue.append(random.randint(0, 200))\nstart_numer = random.randint(0, 200)\nprint()\nprint('生成的磁盘寻道序列为：{}'.format(disk_queue))\n\nwhile True:\nprint()\nprint(\"请选择要执行的磁盘寻道算法：\")\nprint(\"选择FCFS请输入1\")\nprint(\"选择SSTF请输入2\")\nprint(\"选择SCAN请输入3\")\nprint(\"选择CSCAN请输入4\")\nalo_fcfs()\nalo_sstf()\nalo_scan()\nalo_cscan()\nelse:\nprint(\"您选择的不在范围内，请重新输入\")\nprint()\ncontinue\nprint()\nprint(\"继续尝试其他算法请输入1\")\nprint(\"更新数据请输入2\")\nprint(\"结束程序请输入3\")\nend_choice = int(input())\nif end_choice == 1:\ncontinue\nelif end_choice == 2:\nprint(\"现在开始更新数据\")\nprint(\"请输入更新的磁盘寻道序列长度（10-20，含端点）：\")\ndisk_queue_length = int(input())\nif 10 <= disk_queue_length <= 20:\nprint(\"更新成功！\")\nelse:\nprint(\"您输入的磁盘寻道序列长度超出给定范围，请重新输入10-20（含端点）的数字：\")\nprint(\"请输入磁盘寻道序列长度（10-20，含端点）：\")\ndisk_queue_length = int(input())\ndisk_queue = []\nfor k in range(disk_queue_length):\ndisk_queue.append(random.randint(0, 200))\nprint()\nprint('更新的磁盘寻道序列为：{}'.format(disk_queue))\nstart_numer = random.randint(0, 200)\nelse:\nprint(\"程序退出成功！\")\nbreak\n\n\n展开全文", null, "• 含本人实验报告，有具体流程图，实验课上写的，有更好的想法可以提出，大家一起学习，赚点积分不容易 C语言编写，调试过可运行，含实验...实验7，磁盘调度算法(一)——先来先服务（FCFS）和最短寻道时间优先（SSTF）\n• 操作系统的课程设计，可以直接拿来用，比较完整，C++语言\n• 原创最近操作系统实习，敲了实现最短寻道优先(SSTF)——磁盘调度管理的代码。题目阐述如下：设计五：磁盘调度管理设计目的：加深对请求磁盘调度管理实现原理的理解，掌握磁盘调度算法。设计内容:通过编程实现不同...\n\n原创\n\n最近操作系统实习，敲了实现最短寻道优先(SSTF)——磁盘调度管理的代码。\n\n题目阐述如下：\n\n设计五：磁盘调度管理\n\n设计目的：\n\n加深对请求磁盘调度管理实现原理的理解，掌握磁盘调度算法。\n\n设计内容:\n\n通过编程实现不同磁盘调度算法。\n\n设定开始磁道号寻道范围，依据起始扫描磁道号和最大磁道号数，随机产生要进行寻道的磁道号序列。\n\n选择磁盘调度算法，显示该算法的磁道访问顺序，计算出移动的磁道总数和平均寻道总数。\n\n常用的磁盘调度算法简介如下，请在以下算法中任意选择两种实现，并对算法性能进行分析对比。\n\n1. 最短寻道优先算法SSTF：该算法选择这样的进程：其要求访问的磁道与当前磁头所在的磁道距离最近，以使每次的寻道时间最短。\n\n2. 扫描算法SCAN：该算法不仅考虑到欲访问的磁道与当前磁道间的距离，更优先考虑的是磁头当前的移动方向。\n\n例如，当磁头正在自里向外移动时，SCAN算法所考虑的下一个访问对象，应是其欲访问的磁道既在当前磁道之外，又是距离最近的。\n\n这样自里向外地访问，直至再无更外的磁道需要访问时，才将磁臂换向为自外向里移动。\n\n3.循环扫描算法CSCAN：CSCAN算法规定磁头单向移动，例如，只是自里向外移动，当磁头移到最外的磁道并访问后，\n\n磁头立即返回到最里的欲访问的磁道，亦即将最小磁道号紧接着最大磁道号构成循环，进行循环扫描。\n\n首先用 rand 函数随机产生磁道号序列，随机选择一磁道号为起点开始寻道。\n\n下一磁道满足在所有磁道中其离当前被访问磁道最近，可用一数组 num_track 存放其他磁道与当前被访问磁道的距离。\n\n在数组 num_track 筛选出数值最小(即离当前被访问磁道最近)的磁道，再以当前磁道为起点，继续计算其他未被访\n\n问磁道与其的距离，再从 num_track 中筛选出数值最小的的磁道来访问......\n\n#include#include#include#include\n\n#define MAX 50 //可访问的最大磁道号\n\n#define N 20 //磁道号数目\n\nint track[N]; //存放随机产生的要进行寻道访问的磁道号序列\n\nint num_track[N]; //记录其他磁道与当前被访问磁道的距离\n\nint total=0; //统计已被访问的磁道号数\n\nint all_track=0; //移动的磁道总数\n\ndouble aver_track; //平均寻道总数\n\nvoid SSTF(int order){ //order为track中当前被访问的磁道下标\n\nprintf(\"%d\",track[order]);\n\nnum_track[order]=-1;\n\ntotal++; //已被访问磁道号+1\n\nif(total==N){return;\n\n}int i=0;for(i=0;i<=N-1;i++){ //计算其他磁道与当前被访问磁道的距离\n\nif(num_track[i]!=-1){\n\nnum_track[i]=abs(track[order]-track[i]);\n\n}\n\n}int min=9999;intx;for(i=0;i<=N-1;i++){ //找出track中与当前被访问磁道距离最短的\n\nif(num_track[i]!=-1){if(num_track[i]\n\nmin=num_track[i];\n\nx=i;\n\n}\n\n}\n\n}\n\nall_track+=abs(track[order]-track[x]); //计算当前被访问磁道与下一被访问磁道的距离\n\nSSTF(x);\n\n}intmain(){int i=0;\n\nsrand(time(0));\n\nprintf(\"磁道号序列为：\");for(i=0;i<=N-1;i++){ //随机产生要进行寻道访问的磁道号序列\n\ntrack[i]=rand()%(MAX+1);\n\nprintf(\"%d\",track[i]);\n\n}\n\nprintf(\"n\");\n\nprintf(\"寻道序列为：\");\n\nSSTF(rand()%N); //随机选择起点磁道\n\nprintf(\"n移动的磁道总数： %dn\",all_track);\n\nprintf(\"平均寻道总数： %0.2lf\",(double)all_track/N);return 0;\n\n}", null, "(运行结果截图)\n\n17:54:20\n\n2018-05-22\n\n内容来源于网络如有侵权请私信删除\n\n展开全文", null, "• 操作系统试验面置换算法先来先服务最短寻道优先答案参考.pdf操作系统试验面置换算法先来先服务最短寻道优先答案参考.pdf操作系统试验面置换算法先来先服务最短寻道优先答案参考.pdf操作系统试验面置换算法先来先服务...\n• //-----寻道序列。 double AverageDistance; //-----平均寻道长度 bool direction; //-----方向 true时为向外，false为向里 int BeginNum; //----开始磁道号。 int M; //----磁道数。 int N; //-----提出磁盘I/O...\n#include <stdio.h>\n#include <iostream>\n#include<stack>\n#include<queue>\n#include<cmath>\n#include<stdlib.h>\n#include<string.h>\n#include<cstring>\n#include<algorithm>\n#include<cstdio>\n#include<iomanip>\nusing namespace std;\n\n/\n\n/\n\nconst int MaxNumber=300;\nint TrackOrder[MaxNumber]; //----初始序列\nint MoveDistance[MaxNumber]; //----移动距离;\nint FindOrder[MaxNumber]; //-----寻道序列。\ndouble AverageDistance; //-----平均寻道长度\nbool direction; //-----方向 true时为向外，false为向里\nint BeginNum; //----开始磁道号。\nint M; //----磁道数。\nint N; //-----提出磁盘I/O申请的进程数\nint SortOrder[MaxNumber]; //----排序后的序列\nbool Finished[MaxNumber];\n\nvoid input(){\ncout<<\"请输入磁道数：\";\ncin>>M;\ncout<<\"请输入提出磁盘I/O申请的进程数:\";\ncin>>N;\ncout<<\"请依次输入要访问的磁道号：\";\nfor(int i=0;i<N;i++)\ncin>>TrackOrder[i];\nfor(int j=0;j<N;j++)\nMoveDistance[j]=0;\ncout<<\"请输入开始磁道号：\";\ncin>>BeginNum;\nfor(int k=0; k<N; k++)\nFinished[k]=false;\nfor(int l=0;l<N;l++)\nSortOrder[l]=TrackOrder[l];\n}\n\n//============FCFS,先来先服务=================================\nvoid FCFS()\n{\nint temp;\ntemp=BeginNum;\nfor(int i=0;i<N;i++)\n{\nMoveDistance[i]=abs(TrackOrder[i]-temp); //（1）请解释abs函数的作用和此行代码的含义\ntemp=TrackOrder[i];\nFindOrder[i]=TrackOrder[i]; //（2）请解释FindOrder最终存放的数据的含义\n}\n}\n\n//========SSTF,最短寻道法=============================\n\nvoid SSTF()\n{\nint temp,n;\nint A=M;\ntemp=BeginNum;\nfor(int i=0;i<N;i++){\nfor(int j=0;j<N;j++){ //（3）请解释该for循环的作用\nif(abs(TrackOrder[j]-temp)<A&&Finished[j]==false){\nA = abs(TrackOrder[j]-temp);\nn = j; //（4）请补充赋值号右侧的语句\n}\n}\nFinished[n] = true;\nMoveDistance[i] = A;\ntemp = TrackOrder[n];\nFindOrder[i] = TrackOrder[n];\nA = M;\n}\n}\n\n//=====================SCAN,扫描算法==========================\nvoid SCAN()\n{\nint direction,pos,temp;\ntemp=BeginNum;\nsort(SortOrder,SortOrder+N); //升序排序\ncout<<\"请选择开始方向：0向里，1向外\"; //向里为延柱面号增加的方向\ncin>>direction;\n\nfor(int i=0;i<N;i++){ // （5）请解释该for循环的作用\nif(SortOrder[i]>BeginNum){\npos = i;\nbreak;\n}\n}\nint k=0;\nif(!direction){\nfor(int i=pos;i<N;i++){\nMoveDistance[k] = abs(SortOrder[i]-temp);\ntemp = SortOrder[i];\nFindOrder[k]=SortOrder[i];\nk++;\n}\nfor(int j=pos-1;j>=0;j--){ //调转方向\nMoveDistance[k] = abs(SortOrder[j]-temp);\ntemp = SortOrder[j];\nFindOrder[k]=SortOrder[j];\nk++;\n}\n} else {\nfor(int i=pos-1;i>=0;i--){\nMoveDistance[k] = abs(SortOrder[i]-temp);\ntemp = SortOrder[i];\nFindOrder[k]=SortOrder[i];\nk++;\n}\nfor(int j=pos;j<N;j++){ //（6）请将该for循环的条件补充完整\nMoveDistance[k] = abs(SortOrder[j]-temp);\ntemp = SortOrder[j];\nFindOrder[k]=SortOrder[j];\nk++;\n}\n}\n}\n\n//=================CSCAN,循环扫描算法=======================\nvoid CSCAN()\n{\nint pos,temp,i;\ntemp=BeginNum;\nsort(SortOrder,SortOrder+N);\nfor(i=0;i<N;i++){\nif(SortOrder[i]>BeginNum){\npos = i;\nbreak;\n}\n}\nint k=0;\nfor(int j=0;j<N;j++,i++){\nif(i==N){i=0;}\nMoveDistance[k] = abs(SortOrder[i]-temp);\ntemp = SortOrder[i];\nFindOrder[k]=SortOrder[i];\nk++;\n}\n}\n\n//========计算平均寻道时间==============\nvoid Count()\n{\ndouble all=0;\n\nfor(int i=0;i<N;i++)\n{all+=MoveDistance[i];}\nall=all/N;\ncout<<\"平均寻道长度 \"<<all<<endl;\n}\n//========输出函数================\nvoid Show()\n{\ncout<<\"============从\"<<BeginNum<<\"磁道开始=================\";\ncout<<endl;\ncout<<\"被访问的下一个磁道 \"<<\" 移动距离\"<<endl;\nfor(int i=0;i<N;i++)\n{\ncout<<FindOrder[i]<<\" \"<<MoveDistance[i]<<endl;\n}\n}\n\nint main()\n{\nint flag=1;\nint s;\ninput();\nwhile(flag==1)\n{\ncout<<\"请选择寻道方式：\"<<endl;\ncout<<\"1--先来先服务\"<<endl;\ncout<<\"2--最短寻道优先\"<<endl;\ncout<<\"3--扫描\"<<endl;\ncout<<\"4--循环扫描\"<<endl;\ncin>>s;\nswitch(s){\ncase 1:FCFS();Count();Show();break;\ncase 2:SSTF();Count();Show();break;\ncase 3:SCAN();Count();Show();break;\ncase 4:CSCAN();Count();Show();break;\n}\ncout<<\"是否继续选择寻道算法？1--是；2--否\";\ncin>>flag;\n}\nsystem(\"pause\");\nreturn 0;\n}\n\n/\n86 147 91 177 94 150 102 175 130\n/\n\n\n展开全文", null, "• /最短寻道时间优先SSTF(Shortest Seek Time First)算法：选择这样的进程，其要求访问的磁道与当前磁头所在的磁道距离最近，以使每次的寻道时间最短。/ #include <malloc.h> #include<stdio.h> #...\n• 【电梯算法】 SCAN 电梯总是保持一个方向运行，直到该方向没有请求为止，然后改变运行方向。电梯算法（扫描算法）和电梯的运行过程类似，总是按一个方向来进行磁盘调度，直到该方向上没有未完成的磁盘请求，然后...", null, "csnote\n• ## 磁盘寻道调度算法\n\n千次阅读 2020-03-31 11:03:03\n磁盘调度在多道程序设计的计算机系统中，各个进程可能会不断提出不同的对磁盘进行读 / 写操作的请求。...最短寻道时间优先算法（SSTF），扫描算法（SCAN），循环扫描算法（CSCAN）例: 假定某磁盘共有 ...\n• 实验内容：编写一个程序处理磁盘调度中寻道时间的策略。实验目的：磁盘调度中寻道时间直接影响到数据访问的快慢，处理好磁盘寻道时间是关键。实验题目：采用先来先服务策略处理采用最短寻道策略处理实验原理 ...", null, "算法 java 操作系统\n• 写数寻道正齿音。...工作秘密用于络的网存储，计算机据管理进行保密参照。习、往硬人最最少毛泽评价青年保守东曾思想肯学，会力个社最积最有极、量中量的力是整生气。共产中国坚持领导党的，盘上小康证建设也是全面...\n• （如下图示，表示SSTF示意图）不是最优的例子：若干个等待访问磁盘者依次要访问的磁道为 100，142，150，155，170，300，当前磁头位于 150 号柱面，若用最短寻道时间优先磁盘调度算法，则访问序列为 [ 150 , 155 ,...\n• 最短寻道优先算法（SSTF）算法简介：SSTF即最短寻道时间优先(ShortestSeekTimeFirst)，该算法选择这样的进程，其要求访问的磁道与当前磁头所在的磁道距离最近，以使每次的寻道时间最短，但这种调度算法却不能保证...", null, "python\n• 分别采用先来先服务算法(FCFS)，最短寻道时间优先算法(SSTF)，扫描算法(SCAN)，循环扫描算法(CSCAN)，分别求总寻道长度和平均寻道长度？解析：移臂调度算法在于有效利用磁盘，保证磁盘的快速访问。移臂调度主要有...", null, "操作系统\n• 背景：磁盘调度题目描述 1、对于如下给定的一组磁盘访问进行调度：请求服务到达 A B C D E F G H I J K L M N 访问的磁道号 30 50 100 180 20 90 150 ...2、要求分别采用先来先服务、最短寻道优先以及电梯调度算法进", null, "算法 c++ 操作系统\n• 最短寻道时间优先算法（SSTF）扫描算法（SCAN）循环扫描算法（CSCAN）先来先服务算法（FCFS，First Come First Served）　根据进程请求访问磁盘的先后次序进行调度。此算法的优点是公平、简单，且每个...\n• 我们最先开始HD Tune 平均读写速度、寻道时间测试的相关对比：■测试软件：HD Tune Pro v5.00HD Tune是一款硬盘性能诊断测试工具。它能检测硬盘的传输率、突发数据传输率、数据存取时间、CPU 使用率、健康状态，温度...\n• 代码 ①最短寻道时间优先算法函数SSTF() int SSTF(int cyclist, int *cycorder, int n, int start){ //参数：cyclist[] 输入的待操作的柱面数组，cycorder[] 操作柱面的顺序结果 // n 柱面的个数，start 初始的柱面...", null, "算法操作系统 c++\n• 学号 P71514032 专业计算机科学与技术姓名实验日期 2017/12/7 教师签字成绩实验报告实验名称磁盘调度先来先服务策略最短寻道策略实验目的磁盘调度中寻道时间直接影响到数据访问的快慢通过本次实验学习如何...\n• 试问: (1)如果磁盘的平均寻道时间是10ms，那么读一个扇区的平均时间是什么? (2)在一个请求分页系统中,若将该磁盘用作交换设备,而且页面大小和扇区的大小相同。读入一个换出页的平均时间和上面计算的相同。假设如果...\n• 先来先服务(FCFS)、最短寻道时间优先(SSTf)、扫描算法(SCAN)、循环扫描算法(CSCAN)最后有运行截图。#include#include#include#includeint a; //当前磁道号int b; //磁头运动方向int c; //要访问的柱面号int num;...\n• 该算法要求访问的磁道与当前磁头所在的距离你最近，使寻道时间最短例如给数据90，58,55,39,38,18,150,160,184 平均寻道长度为27.5 原理见汤子瀛的《操作系统》第四版 p233页首要的是分析如何才能找到第一个最接近...", null, "c++", null, "", null, "..." ]	[ null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/[email protected]", null, "https://img-blog.csdnimg.cn/img_convert/3b6f8775f7e6ad09066d618e44e5c048.png", null, "https://csdnimg.cn/release/aggregate/img/[email protected]", null, "https://csdnimg.cn/release/aggregate/img/[email protected]", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/aggregate/img/tags.png", null, "https://csdnimg.cn/release/blogv2/dist/pc/img/monkeyWhite.png", null, "https://csdnimg.cn/release/blogv2/dist/pc/img/monkeyWhite.png", null ]	{"ft_lang_label":"__label__zh","ft_lang_prob":0.64079636,"math_prob":0.99127764,"size":19474,"snap":"2022-05-2022-21","text_gpt3_token_len":11052,"char_repetition_ratio":0.13682589,"word_repetition_ratio":0.16589595,"special_character_ratio":0.32165965,"punctuation_ratio":0.20215957,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.980463,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32],"im_url_duplicate_count":[null,null,null,null,null,null,null,null,null,2,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-05-28T11:58:24Z\",\"WARC-Record-ID\":\"<urn:uuid:cc04c0e2-2bea-43a5-933d-7ef2de41e454>\",\"Content-Length\":\"267857\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:0d948b09-6c62-459f-8749-f9e2abf7654e>\",\"WARC-Concurrent-To\":\"<urn:uuid:9b4cc8af-69bc-4824-a013-ef4f16e134d5>\",\"WARC-IP-Address\":\"39.106.226.142\",\"WARC-Target-URI\":\"https://www.csdn.net/tags/MtjaMg1sMjE0MzgtYmxvZwO0O0OO0O0O.html\",\"WARC-Payload-Digest\":\"sha1:DRWF6JXT37TA6KBIB22ALCWLRDY2TBWA\",\"WARC-Block-Digest\":\"sha1:4JH4NXHBRRPAXJOH2G7CP76NCWAJCT2B\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-21/CC-MAIN-2022-21_segments_1652663016373.86_warc_CC-MAIN-20220528093113-20220528123113-00631.warc.gz\"}"}
https://www.calculatoratoz.com/en/ishita-goyal/652009cd-c9f1-4030-8da1-50f5802de670/profile	[ "🔍\n🔍\n\n# Calculators Created by Ishita Goyal", null, "Meerut Institute of Engineering and Technology (MIET), Meerut\n626\nFormulas Created\n3076\nFormulas Verified\n585\nAcross Categories\n\n## List of Calculators by Ishita Goyal\n\nFollowing is a combined list of all the calculators that have been created and verified by Ishita Goyal. Ishita Goyal has created 626 and verified 3076 calculators across 585 different categories till date.\nVerified Angle of Inclination when Horizontal Length of Prism is Given\nVerified Angle of Inclination when Normal Stress Component is Given\nVerified Angle of Inclination when Shear Stress Component is Given\nVerified Angle of Inclination when Vertical Stress on the Surface of Prism is Given\nVerified Angle of Inclination when Volume Per Unit Length of Prism is Given\nVerified Angle of Inclination when Weight of Soil Prism is Given\nVerified Angle of Inclination when Saturated Unit Weight is Given\nVerified Angle of Inclination when Shear Strength and Submerged Unit Weight is Given\nVerified Angle of Inclination when Submerged Unit Weight is Given\nVerified Angle of Inclination when Vertical Stress and Saturated Unit Weight is Given\nVerified Angle of Internal Friction when Factor of Safety for Cohesive Soil is Given\nVerified Angle of Internal Friction when Shear Strength of Cohesive Soil is Given\nVerified Angle of Internal Friction when Stability Number is Given\nVerified Angle of Internal Friction when Resisting Force from Coulomb's Equation is Given\nVerified Angle of Internal Friction when Resisting Moment is Given\nVerified Angle of Internal Friction when Sum of Tangential Component is Given\nVerified Apparent Velocity of Seepage\nVerified Apparent velocity of seepage when discharge and cross sectional area is given\nVerified Coefficient of Permeability when Apparent Velocity of Seepage is Given\nVerified Hydraulic Gradient when Apparent Velocity of Seepage is Given\n3 More Apparent Velocity of Seepage Calculators\nVerified Depth of Prism when Normal Stress Component is Given\nVerified Depth of Prism when Shear Stress Component is Given\nVerified Depth of Prism when Vertical Stress on the Surface of Prism is Given\nVerified Depth of Prism when Volume Per Unit Length of Prism is Given\nVerified Depth of Prism when Weight of Soil Prism is Given\nVerified Depth of Prism when Effective Normal Stress is Given\nVerified Depth of Prism when Normal Stress and Saturated Unit Weight is Given\nVerified Depth of Prism when Saturated Unit Weight is Given\nVerified Depth of Prism when Shear Stress and Saturated Unit Weight is Given\nVerified Depth of Prism when Submerged Unit Weight and Effective Normal Stress is Given\nVerified Depth of Prism when Upward Force due to Seepage Water is Given\nVerified Depth of Prism when Upward Force is Given\nVerified Depth of Prism when Vertical Stress and Saturated Unit Weight is Given\nVerified Dynamic Viscosity when Rate of Flow is Given\nVerified Dynamic Viscosity when Shear Force Resisting the Motion of Piston with Piston Velocity is Given\n4 More Dynamic Viscosity Calculators\nVerified Factor of Safety for Cohesive Soil\nVerified Factor of Safety for Cohesive Soil when Cohesion is Given\nVerified Factor of Safety with Respect to Cohesion when Critical Depth is Given\nVerified Factor of Safety with Respect to Cohesion when Mobilised Cohesion is Given\nVerified Factor of Safety with Respect to Cohesion when Stability Number is Given\nVerified Factor of Safety when Angle of Inclination and Slope angle is Given\nVerified Factor of Safety when Angle of Mobilised Friction is Given\nVerified Factor of Safety when Length of Slip Plane is Given\nVerified Factor of Safety when Mobilised Shear resistance of Soil is Given\nVerified Factor of Safety when Moment of Resistance is Given\nVerified Factor of Safety when Sum of Tangential Component is Given\nVerified Factor of Safety when Unit Cohesion is Given\nVerified Mean Velocity of Flow when Maximum Velocity is Given\nVerified Mean Velocity of Flow when Pressure Gradient is Given\n3 More Mean Velocity of Flow Calculators\nVerified Normal Stress when Member Subjected to Axial Load\nVerified Stress along Y-direction when Shear Stress when Member Subjected to Axial Load is Given\n3 More Normal Stress of members Subjected to Axial Load Calculators\nVerified Pressure Gradient when Discharge is Given\nVerified Pressure Gradient when Mean Velocity of Flows is Given\nVerified Saturated Unit Weight when Effective Normal Stress is Given\nVerified Saturated Unit Weight when Factor of Safety is Given\nVerified Saturated Unit Weight when Normal Stress Component is Given\nVerified Saturated Unit Weight when Shear Strength is Given\nVerified Saturated Unit Weight when Shear Stress Component is Given\nVerified Saturated Unit Weight when Vertical Stress on the Prism is Given\nVerified Saturated Unit Weight when Weight of Soil Prism is Given\nVerified Shear Force Acting on the Slice when Weight of Slice is Given\nVerified Shear Force in Bishop's Analysis\nVerified Shear Force in Bishop's Analysis when Factor of Safety is Given\nVerified Shear Strength when Normal Stress on the Slice is Given\nVerified Shear Stress when Shear Force in Bishop's Analysis is Given\nVerified Total Shear Force on the Slice when Radius of Arc is Given\nVerified Stability Number for Cohesive Soil\nVerified Stability Number for Cohesive Soil when Mobilised Cohesion is Given\nVerified Stability Number when Angle of Internal Friction is Given\nVerified Stability Number when Factor of Safety with Respect to Cohesion is Given\nVerified Unit Cohesion when Factor of Safety is Given\nVerified Unit Cohesion when Mobilised Shear resistance of Soil is Given\nVerified Unit Cohesion when Moment of Resistance is Given\nVerified Unit Cohesion when Resisting Force from Coulomb's Equation is Given\nVerified Unit Cohesion when Resisting Moment is Given\nVerified Unit Cohesion when Sum of Tangential Component is Given\nVerified Unit Weight of Soil when Angle of Inclination and Slope angle is Given\nVerified Unit Weight of Soil when Angle of Mobilised Friction is Given\nVerified Unit Weight of Soil when Height from Toe of Wedge to Top of Wedge is Given\nVerified Unit Weight of Soil when Safe Height from Toe to Top of Wedge is Given\nVerified Unit Weight of Soil when Weight of Wedge is Given\nVerified Velocity of Piston when Rate of Flow is Given\nVerified Velocity of Piston when Shear Stress resisting the Motion of Piston is Given\n4 More Velocity of Piston Calculators\nVerified Weight of Wedge of Soil\nVerified Weight of Wedge when Factor of Safety is Given\nVerified Weight of Wedge when Height from Toe of Wedge to Top of Wedge is Given\nVerified Weight of Wedge when Shear Strength along the Slip Plane is Given\nVerified Weight of Wedge when Shear Stress along the Slip Plane is Given\nCreated Acceleration due to Gravity when Displacement Velocity by Camp is Given\nCreated Acceleration due to Gravity when Impelling Force is Given\nCreated Acceleration due to Gravity when Settling Velocity is Given\nCreated Acceleration due to Gravity when Settling Velocity with respect to Dynamic Viscosity is Given\nCreated Acceleration due to Gravity when Settling Velocity with respect to Kinematic Viscosity is Given\nCreated Acceleration due to Gravity when Settling Velocity with respect to Specific Gravity is Given\nCreated Acceleration due to Gravity when Specific Gravity of Particle and Viscosity is Given\nVerified Acceleration Due to Gravity when Settling Velocity and Diameter is Given\nVerified Acceleration Due to Gravity when Settling Velocity for Turbulent Settling is Given\nVerified Acceleration Due to Gravity when Settling Velocity within Transition Zone is Given\nVerified Adjusted Design Value for Extreme Fiber Bending\nVerified Adjusted Design Value for Shear\n4 More Adjustment Factors for Design Values Calculators\nVerified Adjusted Design Value for Withdrawal for Drift Bolts and Pins\nVerified Adjusted Design Value for Withdrawal for Lag Screws\n7 More Adjustment of Design Values for Connections with Fasteners Calculators\nCreated Allowable Stress in Stirrup Steel when Area in Legs of a Vertical Stirrup is Given\nCreated Area Required in Legs of a Vertical Stirrup\nCreated Distance from Extreme Compression to Centroid when Area in Legs of a Vertical Stirrup is Given\nCreated Distance from Extreme Compression to Centroid when Nominal Unit Shear Stress is Given\nCreated Excess Shear when Area in Legs of a Vertical Stirrup is Given\nCreated Excess Shear when Stirrup Leg Area is Given for Group of Bars Bent up Different Distances\nCreated Excess Shear when Vertical Stirrup Leg Area is Given for Single Bar Bent at Angle α\nCreated Nominal Unit Shear Stress\nCreated Shear when Nominal Unit Shear Stress is Given\nCreated Stirrups Spacing when Area in Legs of a Vertical Stirrup is Given\nCreated Stirrups Spacing when Stirrup Leg Area is Given for Group of Bars Bent up Different Distances\nCreated Vertical Stirrup Leg Area when Group of Bars is Bent at Different Distances\nCreated Vertical Stirrup Leg Area when Single Bar is Bent at an Angle α\nVerified Allowable Stress when Area of Compression Flange is Solid and Not Less than Tension Flange\nVerified Allowable Stress when Simplifying Term is Between 0.2 and 1\nVerified Allowable Stress when Simplifying Term is Greater than 1\nVerified Maximum Fiber Stress in Bending for Laterally Supported Compact Beams and Girders\nVerified Maximum Fiber Stress in Bending for Laterally Supported Noncompact Beams and Girders\nVerified Maximum Unsupported Length of Compression Flange-1\nVerified Maximum Unsupported Length of Compression Flange-2\nVerified Simplifying Term for Allowable Stress Equations\nVerified Allowable Compressive Stress when Slenderness Ratio is Less than Cc\nVerified Allowable Compressive Stress when Slenderness Ration is Greater than Cc\nVerified Effective Length Factor\nVerified Safety Factor for Allowable Compressive Stress\nVerified Slenderness Ratio Used for Separation\nVerified Amplitude of vibrations when acceleration of particles is given\nVerified Amplitude of vibrations when velocity of particle is given\nVerified Frequency of Vibration when Acceleration of Particles is Given\nVerified Frequency of vibration when velocity of particle is given\nVerified Frequency of Vibrations Caused by Blasting\nVerified Angle of Internal Friction when Angle of Inclination and Slope angle is Given\nVerified Angle of Internal Friction when Angle of Mobilised Friction is Given\nVerified Angle of Internal Friction when Effective Normal Stress is Given\nVerified Angle of Internal Friction when Shear Strength along the Slip Plane is Given\nVerified Angle of Internal Friction when Shear Strength and Submerged Unit Weight is Given\nVerified Angle of Internal Friction when Submerged Unit Weight is Given\nVerified Angle of Internal Friction when Weight of Wedge is Given\nVerified Aquifer Constant when Difference Between Modified Drawdowns is Given\nVerified Aquifer Constant when Modified Drawdown is Given\nVerified Aquifer Constant\nVerified Aquifer Constant when Difference in Drawdowns at Two Wells is Given\nVerified Aquifer Constant when Drawdown in Well is Given\nVerified Discharge from Two Wells with Base 10\nVerified Discharge in Unconfined Aquifer\nVerified Discharge in Unconfined Aquifer with Base 10\nVerified Discharge when Length of the Strainer is Given\nVerified Discharge when Two Observation Well is Taken\nVerified Rate of Flow when Coefficient of Permeability is Given\nVerified Rate of Flow when Flow Velocity is Given\nVerified Confined Aquifer Discharge when Coefficient of Transmissibility and Depth of Water is Given\nVerified Confined Aquifer Discharge when Coefficient of Transmissibility is Given\nVerified Confined Aquifer Discharge when Depth of Water in Two Wells are Given\nVerified Confined Aquifer Discharge when Drawdown at the Well is Given\nVerified Confined Aquifer Discharge with Base 10 when Coefficient of Transmissibility is Given\nVerified Confined Aquifer Discharge with Base 10 when Drawdown at the Well is Given\nVerified Discharge in Confined Aquifer\nVerified Discharge in Confined Aquifer when Coefficient of Transmissibility is Given\nVerified Discharge in Confined Aquifer with Base 10\nVerified Discharge in Confined Aquifer with Base 10 when Coefficient of Transmissibility is Given\nVerified Aquifer Loss Coefficient\nVerified Aquifer Loss when Aquifer Loss Coefficient is Given\nVerified Aquifer Loss when Drawdown is Given\nVerified Thickness of Aquifer when Discharge in Unconfined Aquifer is Given\nVerified Thickness of Aquifer when Discharge in Unconfined Aquifer with Base 10 is Given\nVerified Thickness of Aquifer when Drawdown Value measured at the Well is Given\nVerified Aquifer Thickness from Impermeable Layer when Coefficient of Transmissibility is Given\nVerified Aquifer Thickness from Impermeable Layer when Coefficient of Transmissibility with Base 10 is Given\nVerified Aquifer Thickness from Impermeable Layer when Discharge in Confined Aquifer is Given\nVerified Aquifer Thickness from Impermeable Layer when Discharge in Confined Aquifer with Base 10 is Given\nVerified Aquifer Thickness when Confined Aquifer Discharge is Given\nVerified Aquifer Thickness when Confined Aquifer Discharge with Base 10 is Given\nVerified Aquifer Thickness when Depth of Water in Two Wells are Given\nVerified Thickness of Confined Aquifer when Discharge in Confined Aquifer is Given\nVerified Thickness of Confined Aquifer when Discharge in Confined Aquifer with Base 10 is Given\nVerified Thickness of Aquifer from Impermeable Layer when Modified Drawdown in Well 1 is Given\nVerified Thickness of Aquifer from Impermeable Layer when Modified Drawdown in Well 2 is Given\nVerified Thickness of Aquifer from Impermeable Layer when Drawdown in Well 1 is Given\nVerified Thickness of Aquifer from Impermeable Layer when Drawdown in Well 2 is Given\nVerified Angle Between Crown and Abutments when Thrust at Abutments of an Arch Dam is Given\nVerified Constant K5 when Rotation Due to Shear on a Arch Dam is Given\nVerified Deflection Due to Moments on a Arch Dam\nVerified Normal Radial Pressure at the centerline when Moment at Crown of an Arch Dam is Given\nVerified Normal Radial Pressure at the centerline when Thrust at Abutments of an Arch Dam is Given\nVerified Radius to the centerline when Thrust at Abutments of an Arch Dam is Given\n16 More Arch Dams Calculators\nVerified Area of Basin when Flood Discharge by Dicken's Formula for Northern India is Given\nVerified Area of Basin when Flood Discharge by Dicken's Formula in F.P.S Unit for Northern India is Given\nVerified Area of Basin when Flood Discharge by Dicken's Formula in F.P.S Unit is Given\nVerified Area of Basin when Flood Discharge by Dicken's Formula is Given\nVerified Area of Cross-section for Full Flow when Hydraulic Mean Depth and Discharge Ratio is Given\nVerified Area of Cross-section for Full Flow when Only Discharge Ratio is Given\nVerified Area of Cross-section for Full Flow when Only Hydraulic Mean Depth Ratio is Given\nVerified Area of Cross-section for Partial Flow when Hydraulic Mean Depth and Discharge Ratio is Given\nVerified Area of Cross-section for Partial Flow when Only Discharge Ratio is Given\nVerified Area of Cross-section for Partial Flow when Only Hydraulic Mean Depth Ratio is Given\nVerified Area of Filter when Volumetric Flowrate Applied Per Unit of Filter Area is Given\nVerified Area of Trickling Filter when Volumetric Flowrate is Given\nCreated Area of Tank when Height at Outlet Zone with respect to Area of Tank is Given\nCreated Area of Tank when Ratio of Removal with respect to Discharge is Given\nCreated Area of Tank when Vertical Falling Speed in Sedimentation Tank with respect to Area is Given\nCreated Area of the Tank when Discharge Rate with respect to Settling Velocity is Given\nCreated Cross Sectional Area of Sedimentation Tank\nCreated Cross Sectional Area when Length of Sedimentation Tank with respect to Surface Area is Given\nCreated Cross Sectional Area when Surface Area w.r.t Cross-section Area for Practical Purpose is Given\nCreated Cross Sectional Area when Surface Area with respect to Darcy Weishbach Friction Factor is Given\nCreated Cross Sectional Area when Surface Area with respect to Settling Velocity is Given\nVerified Cross-section Area of Tank when Flow Velocity is Given\nVerified Plan Area when Settling Velocity is Given\nVerified Plan Area when Settling Velocity of Particular Sized Particle is Given\nVerified Average Increment for a Decade when Future Population at End of 2 Decades is Given\nVerified Average Increment for a Decade when Future Population at End of 3 Decades is Given\nVerified Average Increment for a Decade when Future Population is Given\nVerified Future Population at the End of 2 Decades\nVerified Future Population at the End of 3 Decades\nVerified Future Population at the End of n Decades\nVerified Number of Decades when Future Population is Given\nVerified Present Population when Future Population at the End of 2 Decades is Given\nVerified Present Population when Future Population at the End of 3 Decades is Given\nVerified Present Population when Future Population at the End of n Decades is Given\nCreated Average Daily Influent Flow Rate when Hydraulic Retention Time is given\nCreated Average Daily Influent Flow Rate When Net Waste Activated Sludge is Given\nCreated Average Daily Influent Flow Rate when RAS Pumping Rate from Aeration Tank is Given\nCreated Average Daily Influent Flow Rate when Reactor Volume is known\nCreated Average Daily Influent Flow Rate when Recirculation Ratio is Given\nCreated Average daily influent flow rate when theoretical oxygen requirement is given\nVerified Allowable Bearing Pressure When Flange Thickness for H shaped Column is Given\nVerified Area Required by Base Plate\nVerified Bearing Pressure When Plate Thickness is Given\nVerified Column Depth When Plate Length is Given\nVerified Column Flange Width When Plate Length is Given\nVerified Column load for given base plate area required\nVerified Flange Thickness for H shaped Columns\nVerified Plate Length\nVerified Thickness of Plate\nVerified Thickness of Plate When Flange Thickness for H shaped Column is Given\nVerified Bazin's Constant Chezy's Constant by Bazin's Formula\nVerified Chezy's Constant by Bazin's Formula\nVerified Hydraulic Mean Depth when Chezy's Constant by Bazin's Formula is Given\nBeams (9)\nVerified Beam Buckling Factor 1\nVerified Beam Buckling Factor 2\nVerified Limiting Buckling Moment\nVerified Limiting Laterally Unbraced Length for Full Plastic Bending Capacity for I and Channel Sections\nVerified Limiting Laterally Unbraced Length for Full Plastic Bending Capacity for Solid Bar and Box Beams\nVerified Limiting Laterally Unbraced Length for Inelastic Lateral Buckling\nVerified Maximum Laterally Unbraced Length for Plastic Analysis\nVerified Maximum Laterally Unbraced Length for Plastic Analysis in Solid Bars and Box Beams\nVerified Specified Minimum Yield Stress for Web if Lr is Given\n3 More Beams Calculators\nVerified Bearing Area Factor\n2 More Bearing Area Factor Calculators\nVerified Bearing Capacity Factor Dependent on Cohesion when Effective Surcharge is Given\nVerified Bearing Capacity Factor Dependent on Cohesion when Safe Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Cohesion when Ultimate Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Surcharge when Effective Surcharge is Given\nVerified Bearing Capacity Factor Dependent on Surcharge when Safe Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Surcharge when Ultimate Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Weight when Effective Surcharge is Given\nVerified Bearing Capacity Factor Dependent on Weight when Safe Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Weight when Ultimate Bearing Capacity is Given\nVerified Depth of Footing when Effective Surcharge is Given\nVerified Depth of Footing when Net Ultimate Bearing Capacity is Given\nVerified Depth of Footing when Safe Bearing Capacity is Given\nVerified Depth of Footing when Ultimate Bearing Capacity is Given\nVerified Effective Surcharge when Depth of Footing is Given\nVerified Effective Surcharge when Factor of Safety is Given\nVerified Effective Surcharge when Ultimate Bearing Capacity is Given\nVerified Factor of Safety when Net Safe Bearing Capacity is Given\nVerified Factor of Safety when Safe Bearing Capacity is Given\nVerified Factor of Safety when Ultimate Bearing Capacity is Given\nVerified Net Safe Bearing Capacity\nVerified Net Safe Bearing Capacity when Safe Bearing Capacity is Given\nVerified Net Safe Bearing Capacity when Ultimate Bearing Capacity is Given\nVerified Net Ultimate Bearing Capacity when Depth of Footing is Given\nVerified Net Ultimate Bearing Capacity when Net Safe Bearing Capacity is Given\nVerified Net Ultimate Bearing Capacity when Safe Bearing Capacity is Given\nVerified Net Ultimate Bearing Capacity when Ultimate Bearing Capacity is Given\nVerified Safe Bearing Capacity\nVerified Safe Bearing Capacity when Net Ultimate Bearing Capacity is Given\nVerified Ultimate Bearing Capacity\nVerified Ultimate Bearing Capacity of Soil Under a Long Footing at the Surface of a Soil\nVerified Ultimate Bearing Capacity when Depth of Footing is Given\nVerified Ultimate Bearing Capacity when Factor of Safety is Given\nVerified Steel Yield Strength for milled surface when allowable Bearing Stress for d < 635 mm is Given\n5 More Bearing on Milled Surfaces Calculators\nVerified Actual Bearing Pressure Under Plate\nVerified Allowable Bearing Stress on Concrete when Full Area is Used for Support\nVerified Allowable Bearing Stress on Concrete when Less Than Full Area is Used for Support\nVerified Allowable Bending Stress When Plate Thickness is Given\nVerified Beam Reaction when Actual Bearing Pressure is Given\nVerified Beam Reaction when Area Required by Bearing Plate is Given\nVerified Bearing plate area for full concrete area support usage\nVerified Bearing plate area for less than full concrete area usage\nVerified Minimum Bearing Length of Plate When Actual Bearing Pressure is Given\nVerified Minimum Width of Plate When Actual Bearing Pressure is Given\nVerified Minimum Width of Plate When Plate Thickness is Given\nVerified Plate Thickness\nVerified Bed Slope for Full Flow when Bed Slope for Partial Flow is Given\nVerified Bed Slope for Full Flow when Velocity Ratio is Given\nVerified Bed Slope for Partial Flow\nVerified Bed Slope for Partial Flow when Velocity Ratio is Given\nVerified Ratio of Bed Slope when Velocity Ratio is Given\nVerified Maximum Bending Stress for Load Applied to Narrow Member Face\nVerified Maximum Compressive Stress for Biaxial Bending\nVerified Maximum Compressive Stress for Uniaxial Bending\nVerified Live Load Moment when Stress in Steel for Shored Members is Given\n9 More Bending Stresses Calculators\nVerified BOD5 of Influent Wastewater to Trickling Filter\nVerified BOD5 of Settled Effluent from Trickling Filter\nCreated BOD in Sewage\nCreated BOD of Industry when Population Equivalent is Given\nCreated BOD when Dilution Factor is Given\nVerified Change in Normal Stress when Overall Pore Pressure Coefficient is Given\nVerified Change in Pore Pressure when Overall Pore Pressure Coefficient is Given\nVerified Effective Angle of Internal Friction when Shear Force in Bishop's Analysis is Given\nVerified Effective Angle of Internal Friction when Shear Strength is Given\nVerified Effective Cohesion of Soil when Normal Stress on the Slice is Given\nVerified Effective Cohesion of Soil when Shear Force in Bishop's Analysis is Given\nVerified Effective Stress on the Slice\nVerified Factor of Safety Given by Bishop\nVerified Factor of Safety when Shear Force in Bishop's Analysis is Given\nVerified Height of Slice when Pore Pressure Ratio is Given\nVerified Horizontal Distance of Slice from Centre of Rotation\nVerified Length of the Arc of the Slice\nVerified Length of the Arc of the Slice when Effective Stress is Given\nVerified Length of the Arc of the Slice when Shear Force in Bishop's Analysis is Given\nVerified Normal Stress on the Slice\nVerified Normal Stress on the Slice when Shear Strength is Given\nVerified Radius of Arc when Total Shear Force on the Slice is Given\nVerified Resultant Vertical Shear Force on Section N\nVerified Resultant Vertical Shear Force on Section N+1\nVerified Total Weight of Slice when Total Shear Force on the Slice is Given\nVerified Unit weight of Soil when Pore Pressure Ratio is Given\nVerified Weight of Slice when Total Normal Force Acting on the Slice is Given\nCreated BOD Loading to Filter when Efficiency of First Filter Stage is Given\nCreated BOD Loading to Second Filter Stage when Efficiency of Second Filter Stage is given\nVerified Ratio of BOD to Ultimate BOD\nVerified Ratio of BOD to Ultimate when Oxygen Demand of Biomass is Given\nVerified Ratio of BOD to Ultimate when Oxygen Required in Aeration Tank is Given\nBOD5 (3)\nVerified BOD5 when Oxygen Required in Aeration Tank is Given\nVerified BOD5 when Ratio of BOD to Ultimate BOD is 0.68\nVerified BOD5 when Ratio of BOD to Ultimate BOD is Given\nVerified Length of Borehole when Burden is Given\nVerified Minimum Length of the Borehole in Feet\nVerified Minimum Length of the Borehole in Meter\n1 More Borehole length Calculators\nVerified Breaking Distance when Velocity is in Kmph\n5 More Braking Distance Calculators\nVerified Burden Suggested in Konya Formula\nVerified Burden Suggested in Langefors' Formula\nVerified Burden when Stemming at Top of Borehole is Given\nVerified Degree of Packing when Burden Suggested in Langefors' Formula is Given\nVerified Diameter of Borehole when Burden is Given\n1 More Burden in blasting Calculators\nVerified Drainage Area when Peak Rate of Runoff is Given\nVerified Maximum Rainfall Intensity when Peak Rate of Runoff is Given\nVerified Peak Rate of Runoff from Burkli-Ziegler Formula\nVerified Runoff Coefficient when Peak Rate of Runoff is Given\nVerified Slope of Ground Surface when Peak Rate of Runoff is Given\nVerified Population when Quantity of Water by Buston's Formula is Given\nVerified Quantity of Water by Buston's Formula\nVerified Moment of Inertia when Maximum Intensity in horizontal plane on a Buttress Dam is Given\nVerified Moment when Maximum Intensity in horizontal plane on a Buttress Dam is Given\nVerified Moment when Minimum Intensity in horizontal plane on a Buttress Dam is Given\nVerified Sectional Area of Base when Minimum Intensity in horizontal plane on a Buttress Dam is Given\n8 More Buttress Dams Calculators\nVerified Average Domestic Demand when Total Storage Capacity is Given\nVerified Average Domestic Demand when Value of McDonald Coefficient is Given\nVerified Capacity of Pump when Total Storage Capacity is Given\nVerified Capacity of Pump when Value of McDonald Coefficient is Given\nVerified Duration of Fire when Reserve Storage is Given\nVerified Fire Demand when Reserve Storage is Given\nVerified Fire Demand when Total Storage Capacity is Given\nVerified Fire Demand when Value of McDonald Coefficient is Given\nVerified McDonald Coefficient a when Total Storage Capacity is Given\nVerified McDonald Coefficient b when Total Storage Capacity is Given\nVerified Reserve Fire Pumping Capacity when Reserve Storage is Given\nVerified Reserve Storage\nVerified Total Storage Capacity of Reservoirs\nVerified Total Storage Capacity of Reservoirs when Value of McDonald Coefficient is Given\nVerified Diameter of Pipe when Dynamic Viscosity with length is Given\nVerified Dynamic Viscosity of fluids in flow\nVerified Length of Pipe when Dynamic Viscosity is Given\nVerified Length of Reservoir when Dynamic Viscosity is Given\nVerified Reservoir Area when Dynamic Viscosity is Given\nVerified Specific Weight of Liquid when Dynamic Viscosity is Given\n12 More Capillary Tube Viscometer Calculators\nVerified Catchment Area in FPS Unit when Average Value of Constant is Given\nVerified Catchment Area when Average Value of Constant is Given\nVerified Catchment Area when Discharge in FPS Unit for Area within 24 KM to 161 KM from the Coast is Given\nVerified Catchment Area when Flood Discharge by Fanning's Formula is Given\nVerified Catchment Area when Flood Discharge for Area within 24 KM from the Coast is Given\nVerified Catchment Area when Flood Discharge for Area within 24 KM to 161 KM from the Coast is Given\nVerified Catchment Area when Flood Discharge for Catchment of Former Bombay Presidency is Given\nVerified Catchment Area when Flood Discharge for Limited Area Near Hills is Given\nVerified Catchment Area when Flood Discharge for Madras Catchment in F.P.S Unit is Given\nVerified Catchment Area when Flood Discharge for Madras Catchment is Given\nVerified Catchment Area when Flood Discharge in FPS Unit by Fanning's Formula is Given\nVerified Catchment Area when Flood Discharge in FPS Unit by Inglis Formula is Given\nVerified Catchment Area when Flood Discharge in FPS Unit for Area within 24 KM from the Coast is Given\nVerified Catchment Area when Flood Discharge in FPS Unit for Limited Area Near Hills is Given\nVerified Catchment Area when Flood Discharge is Given\nVerified Bowl Radius when Centrifugal Acceleration Force is Given\nVerified Centrifugal Acceleration Force in Centrifuge\nVerified Rotational Speed of Centrifuge when Centrifugal Acceleration Force is Given\nVerified Channel Flow Time Or Gutter Flow Time\nVerified Length of the Drain when Channel Flow Time is Given\nVerified Peak Rate of Runoff from Nawab Jung Bahadur Formula\nVerified Velocity in the Drain when Channel Flow Time is Given\nVerified Coefficient of Permeability when Aquifer Loss Coefficient is Given\nVerified Discharge when Aquifer Loss is Given\nVerified Drawdown when Well Loss is Given\nVerified Radius of Influence when Aquifer Loss Coefficient is Given\nVerified Radius of Well when Aquifer Loss Coefficient is Given\nCreated Pressure at Any Time when Root Mean Square Pressure is Given\nCreated Temperature in Kelvin when Speed of Sound is Given\nCreated Wavelength of Wave\nVerified Chezy's Constant when Velocity of Flow by Chezy's Formula is Given\nVerified Hydraulic Gradient when Velocity of Flow by Chezy's Formula is Given\nVerified Hydraulic Mean Radius of Channel\nVerified Hydraulic Mean Radius of Channel when Velocity of Flow by Chezy's Formula is Given\nVerified Velocity of Flow by Chezy's Formula\nVerified Wetted Perimeter when Hydraulic Mean Radius of Channel is Given\nVerified Chow's Function when Constant dependent on Well Function is Given\nVerified Chow's Function when Drawdown is Given\nVerified Chow's Function when Well Function is Given\nVerified Angle of Sector when Top Width is Given\nVerified Diameter of Section when Hydraulic Depth is Given\nVerified Diameter of Section when Hydraulic Radius for channel is Given\nVerified Diameter of Section when Wetted Area is Given\nVerified Hydraulic Depth of circle\nVerified Hydraulic Radius when angle is given\nVerified Section Factor for circle\nVerified Wetted Area for circle\nVerified Wetted Perimeter for circle\n5 More Circular Section Calculators\nVerified Depth of flow in most efficient channel for maximum velocity\nVerified Diameter of Section when Hydraulic Radius in most efficient channel for maximum velocity is Given\nVerified Radius of Section when Depth of flow in Efficient Channel is Given\nVerified Radius of Section when Depth of flow in most efficient channel for maximum velocity is Given\nVerified Wetted Perimeter when Discharge through Channels is Given\n14 More Circular section Calculators\nVerified Area of Cross-section when Central Angle is Given\nVerified Area of Cross-section when Discharge is Given\nVerified Diameter of pipe when Area of Cross-section is Given\nVerified Diameter of the pipe when Hydraulic Mean Depth is Given\nVerified Discharge when Pipe is Running Full\nVerified Hydraulic Mean Depth when Central Angle is Given\nVerified Velocity while Running Full when Discharge is Given\nVerified Area of Cross-section while Running Partially Full when Discharge is Given\nVerified Area of Cross-section while Running Partially Full when Proportionate Area is Given\nVerified Area of Cross-section while Running Partially Full when Proportionate Discharge is Given\nVerified Discharge when Pipe Running Partially Full\nVerified Discharge when Pipe Running Partially Full when Proportionate Discharge is Given\nVerified Hydraulic Mean Depth while Running Partially Full when Only Proportionate Velocity is Given\nVerified Hydraulic Mean Depth while Running Partially Full when Proportionate Hydraulic Mean Depth is Given\nVerified Hydraulic Mean Depth while Running Partially Full when Proportionate Velocity is Given\nVerified Roughness Coefficient while Running Partially Full when Proportionate Velocity is Given\nVerified Velocity while Running Partially Full when Discharge is Given\nVerified Velocity while Running Partially Full when Proportionate Discharge is Given\nVerified Velocity while Running Partially Full when Proportionate Velocity is Given\nVerified Inflow Rate between Inter-Isochrone Area\nVerified Inter-Isochrone Area when Inflow is Given\n6 More Clark's Method for IUH Calculators\nVerified Clearance when Radius of Cylinder is Given\nVerified Dynamic Viscosity of Fluid Flow when torque is known\nVerified Dynamic Viscosity when Total Torque is Given\nVerified Height of Cylinder when Dynamic Viscosity of Fluid is Given\nVerified Radius of Inner Cylinder when Torque exerted on Outer Cylinder is Given\nVerified Speed of Outer Cylinder when Total Torque is Given\nVerified Speed of Outer Cylinder when Velocity Gradient is Given\nVerified Torque exerted on Outer Cylinder\n14 More Coaxial Cylinder Viscometers Calculators\nVerified Coefficient of Drag for Transition Settling\nVerified Coefficient of Drag for Transition Settling when Reynold Number is Given\nVerified Coefficient of Drag when Drag Force Offered by the Fluid is Given\nVerified Coefficient of Drag when Reynold Number is Given\nVerified Coefficient of Drag when Settling Velocity is Given\nVerified Coefficient of Drag when Settling Velocity of Spherical Particle is Given\nVerified Coefficient of friction when stopping sight distance is given\nVerified Coefficient of Longitudinal Friction when velocity in Breaking Distance in in Kmph is Given\n2 More Coefficient of friction Calculators\nVerified Coefficient of Permeability when Discharge and Length of the Strainer is Given\nVerified Coefficient of Permeability when Discharge from Two Wells with Base 10 is Given\nVerified Coefficient of Permeability when Discharge in Unconfined Aquifer is Given\nVerified Coefficient of Permeability when Discharge in Unconfined Aquifer with Base 10 is Given\nVerified Coefficient of Permeability when Discharge of Two Wells under Consideration is Given\nVerified Coefficient of Permeability when Flow Velocity is Given\nVerified Coefficient of Permeability when Radius of Influence is Given\nVerified Coefficient of Permeability when Rate of Flow is Given\nVerified Coefficient of Permeability when Confined Aquifer Discharge is Given\nVerified Coefficient of Permeability when Confined Aquifer Discharge with Base 10 is Given\nVerified Coefficient of Permeability when Depth of Water in Two Wells are Given\nVerified Coefficient of Permeability when Discharge in Confined Aquifer is Given\nVerified Coefficient of Permeability when Discharge in Confined Aquifer with Base 10 is Given\nVerified Coefficient of Transmissibility when Confined Aquifer Discharge is Given\nVerified Coefficient of Transmissibility when Confined Aquifer Discharge with Base 10 is Given\nVerified Coefficient of Transmissibility when Depth of Water in Two Wells are Given\nVerified Coefficient of Transmissibility when Discharge in Confined Aquifer with Base 10 is Given\nVerified Coefficient of Transmissibility when Discharge is Given\nVerified Angle of Inclination when Factor of Safety against Sliding is Given\nVerified Angle of Inclination when Shear Strength of Soil is Given\nVerified Angle of Internal Friction when Factor of Safety against Sliding is Given\nVerified Angle of Internal Friction when Normal Stress of Cohesionless Soil is Given\nVerified Angle of Internal Friction when Shear Strength of Cohesionless Soil is Given\nVerified Angle of Internal Friction when Shear Strength of Soil is Given\nVerified Factor of Safety against Sliding when Angle of Internal Friction is Given\nVerified Normal Stress when Shear Strength of Cohesionless Soil is Given\nVerified Normal Stress when Shear Stress of Cohesionless Soil is Given\nVerified Shear Strength of Cohesionless Soil\nVerified Shear Strength of Soil when Angle of Internal Friction is Given\nVerified Shear Stress of Soil when Angle of Internal Friction is Given\nVerified Shear Stress when Normal Stress of Cohesionless Soil is Given\nVerified Cohesion of Soil when Factor of Safety for Cohesive Soil is Given\nVerified Cohesion of Soil when Factor of Safety with Respect to Cohesion is Given\nVerified Cohesion of Soil when Mobilised Cohesion is Given\nVerified Cohesion when Critical Depth for Cohesive Soil is Given\nVerified Cohesion when Factor of Safety for Cohesive Soil is Given\nVerified Cohesion when Shear Strength of Cohesive Soil is Given\nVerified Cohesion when Stability Number for Cohesive Soil is Given\nVerified Critical Depth for Cohesive Soil\nVerified Critical Depth for Cohesive Soil when Factor of Safety with Respect to Cohesion is Given\nVerified Critical Depth when Stability Number for Cohesive Soil is Given\nVerified Depth at which Mobilised Cohesion is Considered when Critical Depth is Given\nVerified Depth at which Mobilised Cohesion is Considered when Stability Number is Given\nVerified Depth at which Mobilised Cohesion is Given\nVerified Depth of Prism when Factor of Safety for Cohesive Soil is Given\nVerified Mobilised Cohesion\nVerified Mobilised Cohesion when Stability Number for Cohesive Soil is Given\nVerified Normal Stress when Factor of Safety for Cohesive Soil is Given\nVerified Normal Stress when Shear Strength of Cohesive Soil is Given\nVerified Shear Strength of Cohesive Soil\nVerified Shear Stress when Factor of Safety for Cohesive Soil is Given\nVerified Unit Weight of Soil when Critical Depth for Cohesive Soil is Given\nVerified Unit Weight of Soil when Factor of Safety for Cohesive Soil is Given\nVerified Unit Weight of Soil when Factor of Safety with Respect to Cohesion is Given\nVerified Unit Weight of Soil when Mobilised Cohesion is Given\nVerified Unit Weight of Soil when Stability Number for Cohesive Soil is Given\nVerified Bearing Capacity Factor Dependent on Cohesion for Circular Footing\nVerified Bearing Capacity Factor Dependent on Cohesion for Square Footing\nVerified Bearing Capacity for Circular Footing when Value of Bearing Capacity Factor is Given\nVerified Bearing Capacity of Cohesive Soil for Circular Footing\nVerified Bearing Capacity of Cohesive Soil for Square Footing\nVerified Cohesion of Soil for Circular Footing when Value of Bearing Capacity Factor is Given\nVerified Cohesion of Soil when Bearing Capacity for Circular Footing is Given\nVerified Cohesion of Soil when Bearing Capacity for Square Footing is Given\nVerified Effective Surcharge for Circular Footing when Value of Bearing Capacity Factor is Given\nVerified Effective Surcharge when Bearing Capacity for Circular Footing is Given\nVerified Effective Surcharge when Bearing Capacity for Square Footing is Given\nVerified Length of Footing when Bearing Capacity for Square Footing is Given\nVerified Width of Footing when Bearing Capacity for Square Footing is Given\nVerified Basic Design Stress when Flat Width Ratio is between 10 and 25\nVerified Compressive Stress When Basic Design Stress is restricted to 20000 psi\nVerified Compressive Stress When Flat Width Ratio is between 10 and 25\nVerified Depth of Stiffener Lip\nVerified Flat Width Ratio for Deflection Determination\nVerified Flat Width Ratio for Safe Load Determination\nVerified Flat Width Ratio if Depth of Stiffener Lip is Provided\nVerified Flat Width Ratio if Plate Slenderness Factor is Given\nVerified Plate Slenderness Factor\nVerified Reduction Factor for Cold Form Strength Determination\n6 More Cold Formed or Light Weighted Steel Structures Calculators\nCreated Design Shear when Shear Friction Reinforcement Area is Given\nCreated Eccentricity of Shear\nCreated Reinforcement Yield Strength when Shear Friction Reinforcement Area is Given\nCreated Shear Friction Reinforcement Area\nVerified Critical Buckling Stress when Slenderness Parameter is Greater than 1.5\nVerified Critical Buckling Stress when Slenderness Parameter is Less than 1.5\nVerified Slenderness Parameter\nVerified Height when Wind Pressure is Given\n4 More Columns Calculators\nVerified Distance from extreme fiber when Young's Modulus, Radius and stress induced is given\nVerified Young's Modulus when Moment of Resistance, Moment of Inertia and Radius is given\n19 More Combined Axial and Bending Loads Calculators\nVerified Compaction Production by Compaction Equipment\nVerified Compaction Production by Compaction Equipment when Efficiency Factor is Average\nVerified Compaction Production by Compaction Equipment when Efficiency Factor is Excellent\nVerified Compaction Production by Compaction Equipment when Efficiency Factor is Poor\nVerified Efficiency Factor when Compaction Production by Compaction Equipment is Given\nVerified Number of Passes when Compaction Production by Compaction Equipment is Given\nVerified Ratio of Pay to Loose when Compaction Production by Compaction Equipment is Given\nVerified Speed of Roller when Compaction Production by Compaction Equipment is Given\nVerified Thickness of lift when Compaction Production by Compaction Equipment is Given\nVerified Width of Roller when Compaction Production by Compaction Equipment is Given\nVerified Back Bearing in Whole Circle Bearing System\nVerified Fore Bearing in Whole Circle Bearing System\nVerified Included Angle from Two Lines\nVerified Included Angle when Bearings are Measured in Opposite Side of Common Meridian\nVerified Included Angle when Bearings are Measured in Same Side of different meridian\nVerified Magnetic Bearing if True Bearing with East Declination is Given\nVerified Magnetic Bearing if True Bearing with West Declination is Given\nVerified Magnetic Declination to East\nVerified Magnetic Declination to West for Compass Surveying\nVerified True Bearing if Declination is in East\nVerified True Bearing if Declination is in West\n1 More Compass Surveying Calculators\nVerified Stress when Complementary Induced Shear Stress is Given\n5 More Complementary Induced Stress Calculators\nVerified Allowable stress in the flanges\n10 More Composite Construction Calculators\nCreated 28-Day Concrete Compressive Strength\nCreated 28-Day Concrete Compressive Strength when Water Cement Ratio is Given\nCreated Water Cement Ratio when 28-Day Concrete Compressive Strength is Given\n18 More Compression Calculators\nVerified Allowable Compressive Stress Inclined to Grain\nVerified Pressure at AC\nVerified Pressure at BC\nVerified Mean Temperature in Entire Catchment when Run-off in cm is Given\nVerified Mean Temperature in Entire Catchment when Run-off is Given\nVerified Rainfall Intensity when Runoff Coefficient is Given\nVerified Runoff Coefficient when Rainfall Intensity is Given\nVerified Run-off Coefficient when Run-off is Given\nVerified Run-off when Run-off Coefficient is Given\nVerified Bed Slope when Discharge is Given\nVerified Conveyance of Channel Section\nVerified Conveyance of Section through Manning's Formula\nVerified Hydraulic Radius of Channel Section when Conveyance of Channel Section is Given\n15 More Computation of Uniform Flow Calculators\nVerified Concentration of Solids in the Effluent when Mass of the Solids Removed is Given\nVerified Concentration of Solids in the Effluent when Sludge Age is Given\nVerified Concentration of Solids in the Returned Sludge\nVerified Concentration of Solids in the Returned Sludge when MLSS is Given\nVerified Concentration of Solids in the Returned Sludge when Sludge Age is Given\nCreated Concentration of Sludge in Return Line when RAS Pumping Rate from Aeration Tank is Given\nCreated Concentration of Sludge in Return Line when Wasting Rate from Return Line is Given\nCreated Concentration of Solids in Effluent When Wasting Rate from Return Line is Given\nVerified Confidence interval of variate bounded by X2\nVerified Equation for confidence interval of variate bounded by x2\n6 More Confidence Limits Calculators\nVerified Constant Depending upon Soil at Base of Well\nVerified Constant Depending upon Soil at Base of Well when Clay Soil is Given\nVerified Constant Depending upon Soil at Base of Well when Discharge from a Well is Given\nVerified Constant Depending upon Soil at Base of Well when Fine Sand is Given\nVerified Constant Depending upon Soil at Base of Well when Specific Capacity is Given\nVerified Constant Depending upon Soil at Base of Well with Base 10\nVerified Constant Depression Head when Discharge and Time in Hours is Given\nVerified Constant Depression Head when Discharge from a Well is Given\nVerified Mean Velocity of Water Percolating into the Well\nVerified Percolation Intensity Coefficient when Discharge is Given\nVerified Time in Hours when Specific Capacity of an Open Well is Given\nVerified Time in Hours when Specific Capacity of an Open Well with Base 10 is Given\nCreated Acceleration due to Gravity when Area for Siphon Throat is given\nCreated Area for Siphon Throat\nCreated Coefficient of Discharge when Area for Siphon Throat is given\nCreated Depth of Flow over Weir when Flow Diversion is given\nCreated Discharge when Area for Siphon Throat is given\nCreated Flow Diversion for Side Weir\nCreated Head when Area for Siphon Throat is given\nCreated Length of Weir when Flow Diversion is given\nVerified Bed Slope of the Sewer when Flow Velocity by Crimp and Burge's Formula is Given\nVerified Flow Velocity by Crimp and Burge's Formula\nVerified Hydraulic Mean Depth when Flow Velocity by Crimp and Burge's Formula is Given\nVerified Critical Depth in the Control Section\nVerified Critical Depth when Discharge Through the Control Section is Given\nVerified Critical Depth when Total Critical Energy is Given\nVerified Critical Depth when Total Energy at Critical Point is Given\n3 More Critical Depth Calculators\nVerified Critical Depth for Parabolic Channel\nVerified Critical Depth for Triangular Channel\nVerified Critical Depth of Flow when Critical Energy for Parabolic Channel is Given\nVerified Critical Depth when Critical Energy for Rectangular Channel is Given\nVerified Critical Energy for Parabolic Channel\nVerified Critical Energy for Rectangular Channel\nVerified Critical Section Factor\nVerified Discharge when Critical Depth for Parabolic Channel is Given\nVerified Discharge when Critical Section Factor is Given\nVerified Side Slope of Channel when Critical Depth for Parabolic Channel is Given\nVerified Side Slope of Channel when Critical Depth for Triangular Channel is Given\n5 More Critical Flow And Its Computation Calculators\nCreated Critical Oxygen Deficit\nCreated Critical Oxygen Deficit in First Stage Equation\nCreated Critical Oxygen Deficit when Self Purification Constant is Given\nCreated Critical Time\nCreated Critical Time in terms of Self Purification Constant when Critical Oxygen Deficit is Given\nCreated Critical Time in terms of Self Purification Factor\nCreated Critical Time when Critical Oxygen Deficit is Given\nCreated Critical Time when Log value of Critical Oxygen Deficit is Given\nCreated Critical Time when Self Purification Constant is Given\nVerified Critical Velocity when Acceleration Due to Gravity is Given\nVerified Critical Velocity when Critical Depth in the Control Section is Given\nVerified Critical Velocity when Depth of Section is Given\nVerified Critical Velocity when Discharge Through the Control Section is Given\nVerified Critical Velocity when Head Loss is Given\nVerified Critical Velocity when Total Energy at Critical Point is Given\n2 More Critical Velocity Calculators\nVerified Cross-sectional Area of Flow into the well when Discharge from an Open Well is Given\nVerified Cross-sectional Area of Flow into the well when Discharge is Given\nVerified Cross-sectional Area of Well when Specific Capacity for Clay Soil is Given\nVerified Cross-sectional Area of Well when Specific Capacity for Coarse Sand is Given\nVerified Cross-sectional Area of Well when Specific Capacity for Fine Sand is Given\nVerified Cross-sectional Area of Well when Specific Capacity is Given\nVerified Cross-sectional Area of Well when Clay Soil is Given\nVerified Cross-sectional Area of Well when Constant Depending upon Soil at Base is Given\nVerified Cross-sectional Area of Well when Constant Depending upon Soil at Base with Base 10 is Given\nVerified Cross-sectional Area of well when Discharge and Constant Depression Head is Given\nVerified Cross-sectional Area of Well when Discharge from a Well is Given\nVerified Cross-sectional Area of Well when Fine Sand is Given\nVerified Bed Slope when Head on Entrance using Mannings formula is Given\nVerified Bed Slope when Velocity of Flow through Mannings Formulas in Culverts is Given\nVerified Entrance Loss Coefficient when Head on Entrance using Mannings formula is Given\nVerified Head on Entrance measured from Bottom of Culvert using Mannings formula\nVerified Hydraulic Radius when Head on Entrance using Mannings formula is Given\nVerified Normal Depth of Flow when Head on Entrance measured from Bottom using Mannings formula is Given\nVerified Roughness Coefficient when Head on Entrance using Mannings formula is Given\nVerified Roughness Coefficient when Velocity of Flow through Mannings Formulas in Culverts is Given\nVerified Velocity of Flow through Mannings Formulas in Culverts\n5 More Culverts on Subcritical Slopes Calculators\nCurves (3)\nVerified Deflection Angle when Length of Curve is Given\nVerified Length of Curve\nVerified Radius of Curve when Length is Given\n9 More Curves Calculators\nVerified D.O Saturation for Sewage when Correction Factor is 0.8\nVerified D.O Saturation for Sewage when Correction Factor is 0.85\nVerified D.O Saturation for Sewage when Oxygen Transfer Capacity is Given\nVerified Area when Discharge under Dams on Soft or Porous Foundations is Given\nVerified Depth below Surface when Neutral stress per unit area for Dams on Soft Foundations is Given\nVerified Equipotential Lines when Hydraulic gradient per unit head for Dams on Soft Foundations is Given\nVerified Length of Conduit when Neutral stress per unit area for Dams on Soft Foundations is Given\nVerified New Material Coefficient C2 for Dams on Soft or Porous Foundations\nVerified Number of Beds when Hydraulic gradient per unit head for Dams on Soft Foundations is Given\nVerified Permeability when Hydraulic gradient per unit head for Dams on Soft Foundations is Given\n17 More Dams on Soft or Porous Foundations Calculators\nVerified Shear Velocity\n20 More Darcy – Weisbach Equation Calculators\nVerified Average Velocity of Flow when Head Loss is Given\nVerified Average Velocity of Flow when Internal Radius of Pipe is Given\nVerified Darcy's Coefficient of Friction when Head Loss is Given\nVerified Darcy's Coefficient of Friction when Internal Radius of Pipe is Given\nVerified Head Loss due to Friction by Darcy Weisbach Equation\nVerified Head Loss due to Friction when Internal Radius of Pipe is Given\nVerified Internal Diameter of Pipe when Head Loss is Given\nVerified Length of Pipe When Head Loss due to Friction is Given\nVerified Length of Pipe When Internal Radius of Pipe is Given\nCreated Darcy Weishbach Friction Factor when Length of Tank with respect to Darcy Weishbach Factor is Given\nCreated Darcy Weishbach Friction Factor when Surface Area with respect to Darcy Weishbach Factor is Given\nCreated Darcy-Weishbach Friction Factor when Displacement Velocity by Camp is Given\nCreated Darcy-Weishbach Friction Factor when Displacement Velocity for Fine Particles is Given\nVerified Diameter of Piston when Pressure reduction over the Length of Piston is Given\nVerified Diameter of Piston when Vertical Upward Force on Piston is Given\nVerified Length of Piston when Pressure Drop over the Piston is Given\nVerified Length of Piston when Shear Force Resisting the Motion of Piston with Piston Velocity is Given\nVerified Pressure Drop over the Length of Piston when Vertical Upward Force on Piston is Given\nVerified Shear Force Resisting the Motion of Piston when Piston Velocity is Given\nVerified Shear Force when Total Force is Given\nVerified Shear Stress when Shear Force Resisting the Motion of Piston is Given\nVerified Vertical Upward Force on Piston\n15 More Dash - Pot Mechanism Calculators\nCreated Air content w.r.t degree of saturation\nVerified Buoyant Unit Weight of Soil with Saturation 100 Percent\nCreated Degree of saturation of soil sample\nCreated Degree of saturation when air content w.r.t degree of saturation is given\nCreated Degree of saturation when percentage air voids in terms of void ratio is given\nCreated Degree of saturation when void ratio in terms of specific gravity is given\nCreated Volume of voids when degree of saturation of soil sample is given\nCreated Volume of water when degree of saturation of soil sample is given\nCreated Mass Density of Fluid when Frictional Drag is Given\nCreated Mass Density of Fluid when Impelling Force is Given\nCreated Mass Density of Fluid when Particle Reynold's Number is Given\nCreated Mass Density of Fluid when Settling Velocity is Given\nCreated Mass Density of Fluid when Settling Velocity with respect to Dynamic Viscosity is Given\nCreated Mass Density of Particle when Impelling Force is Given\nCreated Mass Density of Particle when Settling Velocity is Given\nCreated Mass Density of Particle when Settling Velocity with respect to Dynamic Viscosity is Given\nCreated Bulk density of soil\nCreated Density of solids\nCreated Density of water when submerged density w.r.t saturated density is given\nCreated Dry density of soil\nCreated Mass of saturated sample when saturated density of soil is given\nCreated Mass of solids when density of solids is given\nCreated Mass of solids when dry density of soil is given\nCreated Saturated density of soil\nCreated Saturated density when submerged density w.r.t saturated density is given\nCreated Submerged density of soil\nCreated Submerged density w.r.t saturated density\nCreated Submerged mass of soil when submerged density of soil is given\nCreated Total mass of soil when bulk density of soil is given\nCreated Total volume of soil when bulk density of soil is given\nCreated Total volume of soil when dry density of soil is given\nCreated Total volume when saturated density of soil is given\nCreated Total volume when submerged density of soil is given\nVerified Density of Water when Coefficient of Drag is Given\nVerified Density of Water when Drag Force Offered by the Fluid is Given\nVerified Density of Water when Kinematic Viscosity of Water is Given\nCreated Deoxygenation Coefficient when Self Purification Constant is Given\nCreated Deoxygenation Constant in terms of Self Purification Constant when Critical Oxygen Deficit is Given\nCreated Deoxygenation Constant when Critical Time in terms of Self Purification Factor is Given\nCreated Deoxygenation Constant when Log value of Critical Oxygen Deficit is Given\nCreated Deoxygenation Constant\nCreated De-oxygenation Constant\nCreated Deoxygenation Constant at 20°C when Deoxygenation Constant at Temperature T is Given\nCreated Deoxygenation Constant at Temperature T\nCreated Deoxygenation Constant using Best Fit Line\nCreated De-oxygenation Constant when Organic Matter Present at the Start of BOD is Given\nCreated Deoxygenation Constant when Organic Matter Present at the Start of BOD using Best Fit Line is Given\nCreated De-oxygenation Constant when Total Amount of Organic Matter Oxidised is Given\nVerified Constant Depression Head when Specific Capacity for Clay Soil is Given\nVerified Constant Depression Head when Specific Capacity for Coarse Sand is Given\nVerified Constant Depression Head when Specific Capacity for Fine Sand is Given\nVerified Constant Depression Head when Specific Capacity is Given\nVerified Depression Head when Discharge is Given\nVerified Depression Head in the Well at a Time T after Pumping Stopped\nVerified Depression Head in the Well at a Time T after Pumping Stopped and Clay Soil is Present\nVerified Depression Head in the Well at a Time T after Pumping Stopped and Coarse Sand is Present\nVerified Depression Head in the Well at a Time T after Pumping Stopped and Constant is Given\nVerified Depression Head in the Well at a Time T after Pumping Stopped and Constant with Base 10 is Given\nVerified Depression Head in the Well at a Time T after Pumping Stopped and Fine Sand is Present\nVerified Depression Head in the Well at a Time T after Pumping Stopped when Discharge and Time is Given\nVerified Depression Head in the Well at a Time T after Pumping Stopped with Base 10\nVerified Depression Head in the Well at a Time T after Pumping Stopped with Base 10 and Clay soil is Present\nVerified Depression Head in the Well at a Time T after Pumping Stopped with Base 10 and Coarse Sand is Given\nVerified Depression Head in the Well at a Time T after Pumping Stopped with Base 10 and Fine Sand is Present\nVerified Depression Head in the Well when Pumping Stopped\nVerified Depression Head in the Well when Pumping Stopped and Clay Soil is Present\nVerified Depression Head in the Well when Pumping Stopped and Coarse Sand is Present\nVerified Depression Head in the Well when Pumping Stopped and Constant is Given\nVerified Depression Head in the Well when Pumping Stopped and Constant with Base 10 is Given\nVerified Depression Head in the Well when Pumping Stopped and Fine Sand is Present\nVerified Depression Head in the Well when Pumping Stopped with Base 10\nVerified Depression Head in the Well when Pumping Stopped with Base 10 and Clay soil is Present\nVerified Depression Head in the Well when Pumping Stopped with Base 10 and Coarse Sand is Present\nVerified Depression Head in the Well when Pumping Stopped with Base 10 and Fine Sand is Present\nVerified Depression Head in the Well when Pumping Stopped with Discharge and Time in Hours is Given\nVerified Depth when Critical Velocity is Given\nVerified Depth when Discharge for Rectangular Channel Section is given\n2 More Depth of Channel Calculators\nVerified Depth of Actual Filter when Treatability Constant is Given\nVerified Depth of Filter when Treatability Constant is Given\nVerified Depth of Tank when Detention Time is Given\nVerified Depth of Tank when Flow Velocity is Given\nVerified Depth of tank when Height to Length Ratio is Given\nVerified Height of Tank when Detention Time for a Circular Tank is Given\nVerified Height of Tank when Flow Velocity is Given\nVerified Depth of Water in Well 1 when Drawdown in Well 1 is Given\nVerified Depth of Water in Well 2 when Drawdown in Well 2 is Given\nVerified Radial Distance from Well 1 when Aquifer Constant is Given\nVerified Radial Distance from Well 2 when Aquifer Constant is Given\nVerified Depth of Water at Point 1 when Discharge from Two Wells with Base 10 is Given\nVerified Depth of Water at Point 1 when Discharge of Two Wells under Consideration is Given\nVerified Depth of Water at Point 2 when Discharge from Two Wells with Base 10 is Given\nVerified Depth of Water at Point 2 when Discharge of Two Wells under Consideration is Given\nVerified Depth of Water in the Well when Discharge in Unconfined Aquifer is Given\nVerified Depth of Water in the Well when Discharge in Unconfined Aquifer with Base 10 is Given\nVerified Depth of Water in Well when Drawdown Value measured at the Well is Given\nVerified Depth of Water in 1st Well when Coefficient of Transmissibility is Given\nVerified Depth of Water in 1st Well when Confined Aquifer Discharge is Given\nVerified Depth of Water in 2nd Well when Coefficient of Transmissibility is Given\nVerified Depth of Water in 2nd Well when Confined Aquifer Discharge is Given\nVerified Depth of Water in Well when Coefficient of Transmissibility is Given\nVerified Depth of Water in Well when Coefficient of Transmissibility with Base 10 is Given\nVerified Depth of Water in Well when Discharge in Confined Aquifer is Given\nVerified Depth of Water in Well when Discharge in Confined Aquifer with Base 10 is Given\nVerified Average Daily Consumption of Chlorine\nVerified Average Flow when Average Daily Consumption of Chlorine is Given\nVerified Average Flow when Capacity of the Chlorinator at Peak Flow is Given\nVerified Capacity of the Chlorinator at Peak Flow\nVerified Dosage Used when Average Daily Consumption of Chlorine is Given\nVerified Dosage Used when Capacity of the Chlorinator at Peak Flow is Given\nVerified Number of Coliform Organisms at Any Initial Time\nVerified Number of Coliform Organisms at Any Particular Time\nVerified Peaking Factor when Capacity of the Chlorinator at Peak Flow is Given\nVerified Residence Time when Number of Coliform Organisms at Any Particular Time is Given\nVerified Total Chlorine Residual at Any Particular Time\nVerified Average Daily Load when Peak Discharge in Circular Settling Tanks is Given\nVerified Design Surface Loading Rate when Surface Area of Circular Settling Tank is Given\nVerified Influent Flow Rate when Return Activated Sludge Flow Rate is Given\nVerified Maximum Solids Entering the Clarifier\nVerified Mixed Liquor Suspended Solids in Aeration Tank when Maximum Solids is Given\nVerified Peak Discharge in Circular Settling Tanks\nVerified Peak Discharge when Maximum Solids Entering the Clarifier is Given\nVerified Peak Discharge when Surface Area of Circular Settling Tank is Given\nVerified Peaking Factor when Peak Discharge in Circular Settling Tanks is Given\nVerified Return Activated Sludge Flow Rate\nVerified Return Activated Sludge Flow Rate when Maximum Solids Entering the Clarifier is Given\nVerified Surface Area of Circular Settling Tank\nVerified Total Settling Tank Surface Area when Actual Solid Loading Rate is Given\nCreated Recirculation Ratio\nCreated Sludge Concentration Using Wasting Rate from Return Line when Solid Concentration in Effluent is Low\nVerified Dewatered Sludge or Cake Discharge Rate\nVerified Percent Reduction in Sludge Volume\nVerified Solids Recovery when Dewatered Sludge Discharge Rate is Given\n1 More Design of a Solid Bowl Centrifuge for Sludge Dewatering Calculators\nVerified Air supply required in Grit Chamber\nVerified Assumed Grit Quantity when Volume of Aerated Grit Chamber is Given\nVerified Chamber Length when Air supply required is Given\nVerified Chosen Air Supply when Air supply required is Given\nVerified Chosen Depth when Width of Grit Chamber is Given\nVerified Depth when Length of Grit Chamber is Given\nVerified Detention Time when Volume of Each Grit Chamber is Given\nVerified Length of Grit Chamber\nVerified Peak Flow Rate when Volume of Each Grit Chamber is Given\nVerified Selected Width-Ratio when Width of Grit Chamber is Given\nVerified Volume Flow Rate Handled when Volume of Aerated Grit Chamber is Given\nVerified Volume of Aerated Grit Chamber\nVerified Volume of Each Grit Chamber\nVerified Volume when Length of Grit Chamber is Given\nVerified Width of Grit Chamber\nVerified Width when Length of Grit Chamber is Given\nVerified Density of air when Volume of Air Required is Given\nVerified Density of Water when Volume of Digested Sludge is Given\nVerified Digester Total Suspended Solids when Volume of Aerobic Digester is Given\nVerified Influent Average Flow Rate when Volume of Aerobic Digester is Given\nVerified Influent Suspended Solids when Volume of Aerobic Digester is Given\nVerified Initial Weight of Oxygen when Weight of Oxygen Required is Given\nVerified Percent Solids when Volume of Digested Sludge is Given\nVerified Reaction Rate Constant when Volume of Aerobic Digester is Given\nVerified Solids Retention Time when Volume of Aerobic Digester is Given\nVerified Specific Gravity of Digested Sludge when Volume of Digested Sludge is Given\nVerified Volatile Fraction of Digester Suspended Solids when Volume of Aerobic Digester is Given\nVerified Volume of Aerobic Digester\nVerified Volume of Air Required at Standard Conditions\nVerified Volume of Digested Sludge\nVerified VSS as Mass Flow Rate when Weight of Oxygen Required is Given\nVerified Weight of Oxygen Required to Destroy the VSS\nVerified Weight of Oxygen Required when Volume of Air Required is Given\nVerified Weight of Sludge when Volume of Digested Sludge is Given\nVerified Weight of VSS when Weight of Oxygen Required is Given\nVerified BOD In when Percent Stabilization is Given\nVerified BOD In when Quantity of Volatile Solids is Given\nVerified BOD In when Volume of Methane Gas Produced is Given\nVerified BOD Out when Percent Stabilization is Given\nVerified BOD Out when Quantity of Volatile Solids is Given\nVerified BOD Out when Volume of Methane Gas Produced is Given\nVerified BOD Per Day when Volumetric Loading in an Anaerobic Digester is Given\nVerified Endogenous Coefficient when Quantity of Volatile Solids is Given\nVerified Hydraulic Retention Time when Volume Required for an Anaerobic Digester is Given\nVerified Influent Sludge Flow Rate when Volume Required for an Anaerobic Digester is Given\nVerified Mean Cell Residence Time when Quantity of Volatile Solids is Given\nVerified Percent Stabilization\nVerified Quantity of Volatile Solids Produced Each Day\nVerified Volatile Solids Produced when Percent Stabilization is Given\nVerified Volatile Solids Produced when Volume of Methane Gas Produced is Given\nVerified Volume of Methane Gas Produced at Standard Conditions\nVerified Volume Required for an Anaerobic Digester\nVerified Volumetric Flow Rate when Volumetric Loading in an Anaerobic Digester is Given\nVerified Yield Coefficient when Quantity of Volatile Solids is Given\nVerified Depth of Tank when Volume of Conical Humus Tank is Given\nVerified Depth of the Tank when Top Area is Given\nVerified Diameter of Tank when Volume of Conical Humus Tank is Given\nVerified Top Area of Tank when Volume of Conical Humus Tank is Given\nVerified Volume of Conical Humus Tank\nVerified Volume of Conical Humus Tank when Top Area is Given\nVerified Height to Length Ratio when Settling Velocity is Given\nVerified Length to Depth Ratio when Settling Velocity is Given\nVerified Overflow Rate when Discharge is Given\nVerified Rate of Flow when Detention Time is Given\nVerified Volume of Tank when Detention Time is Given\nVerified Coefficient of Discharge when Distance in X Direction from Center of Weir is Given\nVerified Distance in X Direction from Center of Weir\nVerified Distance in Y Direction from Crest of Weir\nVerified Half Width of Bottom Portion of the Weir\nVerified Horizontal Flow Velocity when Distance in X Direction from Center of Weir is Given\nVerified Horizontal Flow Velocity when Half Width of Bottom Portion of the Weir is Given\nVerified Width of Channel when Distance in X Direction from Center of Weir is Given\nVerified Width of Channel when Half Width of Bottom Portion of the Weir is Given\nVerified Number of Threads in Engagement With Nut given Unit Bearing Pressure\n21 More Design of Screw and Nut Calculators\nVerified Depth of Drains for Drains upto 15 Cumecs\nVerified Width of Drain when Depth of Drains for Drains upto 15 Cumecs is Given\nCreated Axial Load at Balanced Condition\nCreated Axial Load for Spiral Columns\nCreated Axial Load for Tied Columns\nCreated Axial Moment at Balanced Condition\nCreated Reinforcement Yield Strength when Axial Load for Tied Columns is Given\nCreated Tension Reinforcement Area when Axial Load for Tied Columns is Given\n7 More Design Under Axial Compression with Biaxial Bending Calculators\nVerified Detention Time for a Circular Tank\nVerified Detention Time for a Rectangular Tank\nVerified Detention Time when Discharge is Given\nCreated Detention Period when Falling Speed of Smaller Particle is Given\nCreated Detention Time in Sedimentation Tank\nCreated Detention Time when Displacement Efficiency of Sedimentation Tank is Given\nCreated Detention Time with respect to Discharge Rate\nVerified Constant Factor when Population at Last Census is Given\nVerified Earlier Census Date when Constant Factor is Given\nVerified Earlier Census Date when Proportionality Factor is Given\nVerified Last Census Date when Constant Factor is Given\nVerified Last Census Date when Proportionality Factor is Given\nVerified Population at Earlier Census\nVerified Population at Last Census\nVerified Population at Last Census when Proportionality Factor is Given\nVerified Proportionality Factor when Population at Last Census is Given\nCreated Average Rainfall Rate when Stormwater is given\nCreated Coefficient of Runoff when Stormwater is given\nCreated Drainage Area when Stormwater is given\nCreated Stormwater Flow\nVerified Diameter of the Grain when Friction Factor is Given\nVerified Diameter of the Grain when Rugosity Coefficient is Given\nVerified Diameter of the Grain when Self Cleaning Invert Slope is Given\nVerified Diameter of the Grain when Self Cleansing velocity is Given\nVerified Diameter of Particle Settling Velocity for Inorganic Solids is Given\nVerified Diameter of Particle when Settling Velocity and Coefficient of Drag is Given\nVerified Diameter of Particle when Settling Velocity for Modified Hazen's Equation is Given\nVerified Diameter of Particle when Settling Velocity for Organic Matter is Given\nVerified Diameter of Particle when Settling Velocity for Turbulent Settling is Given\nVerified Diameter of Particle when Settling Velocity within Transition Zone is Given\nVerified Diameter of the Particle when Coefficient of Drag is Given\nVerified Diameter of the Particle when Reynold Number is Given\nVerified Diameter of the Particle when Settling Velocity of Spherical Particle is Given\nCreated Diameter of Particle when Particle Reynold's Number is Given\nCreated Diameter of Particle when Settling Velocity is Given\nCreated Diameter of Particle when Settling Velocity with respect to Specific Gravity is Given\nCreated Diameter of Particle when Volume of Particle is Given\nCreated Diameter when Displacement Velocity by Camp is Given\nCreated Diameter when Settling Velocity at 10°C is Given\nCreated Diameter when Settling Velocity in terms of °C for d> 0.1mm is Given\nCreated Diameter when Settling Velocity in terms of °C is Given\nCreated Diameter when Settling Velocity in terms of °F for d> 0.1mm is Given\nCreated Diameter when Settling Velocity in terms of °F is Given\nCreated Diameter when Settling Velocity with respect to Dynamic Viscosity is Given\nCreated Diameter when Settling Velocity with respect to Kinematic Viscosity is Given\nCreated Diameter when Specific Gravity of Particle and Viscosity is Given\nVerified Catchment Area when Peak Rate of Runoff is Given\nVerified Factors Dependent Constant when Peak Rate of Runoff is Given\nVerified Peak Rate of Runoff from Dicken's Formula\nVerified Confined Aquifer Discharge when Aquifer Constant is Given\nVerified Discharge when Aquifer Constant is Given\nVerified Discharge when Difference in Drawdowns at Two Wells is Given\nVerified Discharge of Full Flow when Hydraulic Mean Depth for Partial flow is Given\nVerified Discharge of Full Flow when Hydraulic Mean Depth Ratio is Given\nVerified Discharge Ratio when Hydraulic Mean Depth for Full Flow is Given\nVerified Discharge Ratio when Hydraulic Mean Depth Ratio is Given\nVerified Self Cleansing Discharge when Hydraulic Mean Depth for Full Flow is Given\nVerified Self Cleansing Discharge when Hydraulic Mean Depth Ratio is Given\nVerified Discharge from a Well when Specific Capacity for Clay Soil is Given\nVerified Discharge from a Well when Specific Capacity for Coarse Sand is Given\nVerified Discharge from a Well when Specific Capacity for Fine Sand is Given\nVerified Discharge from a Well when Specific Capacity is Given\nVerified Discharge from an Open Well when Depression Head is Given\nVerified Discharge from an Open Well when Mean Velocity of Water Percolating is Given\nVerified Discharge Coefficient when Discharge is Given\nVerified Discharge for Rectangular Channel Section\nVerified Discharge Passing Through the Parshall Flume when Discharge Coefficient is Given\nVerified Discharge Through the Control Section\n3 More Discharge in Channel Calculators\nVerified Discharge Entering the Basin when Cross-section Area of Tank is Given\nVerified Discharge Entering the Basin when Flow Velocity is Given\nVerified Discharge Entering the Basin when Settling Velocity is Given\nVerified Discharge when Detention Time for a Circular Tank is Given\nVerified Discharge when Detention Time for a Rectangular Tank is Given\nVerified Discharge when Height to Length Ratio is Given\nVerified Discharge when Overflow Rate is Given\nVerified Discharge when Plan Area is Given\nVerified Discharge when Plan Area is Given for Particular Sized Particle\nVerified Discharge when Settling Velocity of Particular Sized Particle is Given\nVerified Discharge when Difference Between Modified Drawdowns is Given\nVerified Unconfined Aquifer Discharge when Aquifer Constant is Given\nVerified Discharge in Well under Constant Depression Head\nVerified Discharge in Well when Constant Depression Head and Area of Well is Given\nVerified Discharge when Drawdown is Given\nVerified Discharge when Formation Constant T is Given\nVerified Discharge when Time at 1st and 2nd Instance is Given\nCreated Discharge Rate when Detention Time in Sedimentation Tank is Given\nCreated Discharge Rate when Detention Time is Given\nCreated Discharge Rate when Height at Outlet Zone with respect to Area of Tank is Given\nCreated Discharge Rate when Height at Outlet Zone with respect to Discharge is Given\nCreated Discharge Rate when Ratio of Removal with respect to Discharge is Given\nCreated Discharge Rate when Vertical Falling Speed in Sedimentation Tank is Given\nCreated Discharge Rate when Vertical Falling Speed in Sedimentation Tank with respect to Area is Given\nCreated Discharge Rate with respect to Settling Velocity\nCreated Displacement Efficiency of Sedimentation Tank\nCreated Flow through Period when Displacement Efficiency of Sedimentation Tank is Given\nCreated Beta Constant when Displacement Velocity by Camp is Given\nCreated Displacement Velocity by Camp\nCreated Displacement Velocity for Fine Particles\nCreated Displacement Velocity in terms of Settling Velocity\nCreated Displacement Velocity when f=0.025\nVerified Maximum Rate of Effluent Application of Leaching Surface\nVerified Maximum Rate of Effluent Application of Leaching Surface by BIS\nVerified Standard Percolation Rate when Maximum Rate of Effluent Application by BIS is Given\nVerified Standard Percolation Rate when Maximum Rate of Effluent Application is Given\nCreated Acceleration due to Gravity when Inlet Capacity for Flow Depth more than 1ft 5in is given\nCreated Area of Opening when Inlet Capacity for Flow Depth more than 1ft 5in is given\nVerified Depression in Curb Inlet when Runoff Quantity with Full Gutter flow is given\nCreated Depth of Flow when Inlet Capacity for Flow Depth more than 1ft 5in is given\nCreated Inlet Capacity for Flow Depth more than 1ft 5in\n6 More Disposing of storm water Calculators\nCreated Actual DO\nCreated Mixing Concentration\nCreated River Stream Concentration\nCreated River Stream Flow Rate\nCreated Saturation DO\nCreated Sewage Concentration\nCreated Sewage Flow Rate\nCreated DO Consumed by Diluted Sample when BOD in Sewage is Given\nCreated DO Consumed by Diluted Sample when Dilution Factor is Given\nVerified Dosing Rate\nVerified Dosing Rate when Rotational Speed is Given\nCreated Drag Coefficient when Frictional Drag is Given\nCreated Drag Coefficient when Settling Velocity is Given\nCreated Drag Coefficient when Settling Velocity with respect to Specific Gravity is Given\nCreated Drag Coefficient with respect to Reynold's Number\nCreated General form of Drag Coefficient\nVerified Angle of Inclination when Drag Force is Given\nVerified Bed Slope of the Channel when Drag Force is Given\nVerified Drag Force Exerted by Flowing Water\nVerified Drag Force or Intensity of Tractive force\nVerified Rugosity Coefficient when Drag Force is Given\nVerified Thickness of Sediment when Drag Force is Given\nVerified Unit weight of Water when Drag Force is Given\nVerified Area of Particle when Drag Force Offered by the Fluid is Given\nVerified Drag Force Offered by the Fluid\nVerified Velocity of Fall when Drag Force Offered by the Fluid is Given\nCreated Drag Force as per Stokes Law\nCreated Frictional Drag\nCreated Projected Area when Frictional Drag is Given\nCreated The Diameter when Drag Force as per Stokes Law is Given\nVerified Change in Drawdown when Chow's Function is Given\nVerified Change in Drawdown when Formation Constant T is Given\nVerified Change in Drawdown when Time at 1st and 2nd Instance is Given\nVerified Drawdown when Chow's Function is Given\nVerified Drawdown when Well Function is Given\nVerified Drawdown at the Well when Coefficient of Transmissibility is Given\nVerified Drawdown at the Well when Coefficient of Transmissibility with Base 10 is Given\nVerified Drawdown at the Well when Confined Aquifer Discharge is Given\nVerified Drawdown at the Well when Confined Aquifer Discharge with Base 10 is Given\nVerified Drawdown at the Well when Radius of Influence is Given\nVerified Drawdown Value measured at the Well\nVerified Difference in Drawdowns at Two Wells when Aquifer Constant is Given\nVerified Drawdown in Well 1 when Aquifer Constant and Discharge is Given\nVerified Drawdown in Well 1 when Aquifer Constant is Given\nVerified Drawdown in Well 1 when Thickness of Aquifer from Impermeable Layer is Given\nVerified Drawdown in Well 2 when Aquifer Constant and Discharge is Given\nVerified Drawdown in Well 2 when Aquifer Constant is Given\nVerified Drawdown in Well 2 when Thickness of Aquifer from Impermeable Layer is Given\nVerified Catchment Area when Peak Rate of Runoff from Dredge Formula is Given\nVerified Length of the Drain when Peak Rate of Runoff from Dredge Formula is Given\nVerified Peak Rate of Runoff from Dredge Formula\nCreated Dry unit weight in terms of percentage of air voids\nCreated Dry unit weight in terms of unit weight of solids\nCreated Dry unit weight in terms of water content\nCreated Dry unit weight in terms of water content at full saturation\nVerified Dry Unit Weight of Soil when Saturation is 0 Percent\nCreated Dry unit weight when bulk unit weight in terms of degree of saturation is given\nCreated Dry unit weight when submerged unit weight of soil in terms of porosity is given\nVerified Dynamic Viscosity when Mean Velocity of Flow with Pressure Gradient is Given\nVerified Dynamic Viscosity when Pressure Head Drop is Given\n4 More Dynamic Viscosity Calculators\nCreated Dynamic Viscosity when Drag Force as per Stokes Law is Given\nCreated Dynamic Viscosity when Particle Reynold's Number is Given\nCreated Dynamic Viscosity when Settling Velocity with respect to Dynamic Viscosity is Given\nVerified Average depth of water when Setup above Pool level through Zuider Zee formula is Given\nVerified Coefficient of Permeability when Maximum and Minimum permeability is Given for a Earth Dam\nVerified Coefficient of Permeability when Quantity of seepage in length of dam is given\nVerified Maximum Permeability when Coefficient of Permeability is Given for a Earth Dam\nVerified Minimum Permeability when Coefficient of Permeability is Given for a Earth Dam\nVerified Setup above Pool level through Zuider Zee formula\nVerified Superficial area of flow when Seepage Discharge in an Earth Dam is Given\n18 More Earth Dam Calculators\nVerified Compacted volume of Soil After Excavation of Soil\nVerified Load Factor when Original Volume of Soil is Given\nVerified Loaded Volume of Soil when Original Volume of Soil is Given\nVerified Loaded Volume of Soil when Percent Swell is Given\nVerified Original Volume of Soil Before Excavation\nVerified Original Volume of Soil Before Excavation when Percent Swell is Given\nVerified Swell in Soil when Original Volume of Soil is Given\n2 More Earth quantities hauled Calculators\nVerified Coefficient of Traction when Usable Pull is Given\nVerified Total Road Resistance when Rolling Resistance and Grade Resistance is Given\nVerified Usable Pull to Overcome Loss of Power with Altitude\nVerified Weight on Wheels when Total Road Resistance is Given\n11 More Earthmoving Calculators\nVerified BOD of the Effluent Getting Out of the Filter\nVerified BOD of the Influent Entering the Filter\nVerified Depth of Filter when BOD of the Influent Entering the Filter is Given\nVerified Hydraulic Loading Rate when BOD of the Influent Entering the Filter is Given\nVerified Rate Constant when BOD of the Influent Entering the Filter is Given\nVerified Barometric Pressure in Essen and Froome Formula for Group Refractive Index\nVerified Barometric Pressure in I. U. C. G Formula for Refractive Index\nVerified Barometric Pressure when Group Refractive Index is Given\nVerified Barometric Pressure when Partial Pressure of Water Vapour in I. U. C. G Formula is Given\nVerified Corrected Slope Distance for Refractive Index\nVerified Essen and Froome Formula for Group Refractive Index\nVerified Group Refractive Index at Standard Conditions\nVerified Group Refractive Index if Temperature and Humidity are different from Standard Values\nVerified I. U. C. G Formula for Refractive Index\nVerified Overall Standard Error\nVerified Partial Pressure of Water Vapour in I. U. C. G Formula for Refractive Index\nVerified Partial Pressure of Water Vapour when Refractive Index is Given\nVerified Partial Pressure of Water Vapour when Temperature Effects are Considered\nVerified Temperature Difference when Partial Pressure is Given\nVerified Wave Velocity in a Medium\nVerified Wave Velocity in Vacuum\nVerified Reduced Distance\nVerified Spheroidal Distance\nVerified Spheroidal Distance for Geodimeters\nVerified Spheroidal Distance for Tellurometers\nVerified Buoyancy when Effective Weight of the Particle is Given\nVerified Effective Weight of the Particle\nVerified Effective Weight of the Particle when Buoyancy is Given\nVerified Radius of Particle when Effective Weight of the Particle is Given\nVerified Total Weight when Effective Weight of the Particle is Given\nVerified Unit weight of Particle when Effective Weight of the Particle is Given\nVerified Unit Weight of Water when Effective Weight of the Particle is Given\nCreated Efficiency of First Filter Stage\nCreated Efficiency of First Filter Stage using Efficiency of Second Filter Stage\nCreated Efficiency of First Filter Stage when Overall Efficiency is given\nCreated Efficiency of First Filter when BOD Loading for Second Filter is Given\nCreated Efficiency of Second Filter Stage\nCreated Efficiency of Second Filter Stage when Overall Efficiency is given\nCreated Overall Efficiency of Two Stage Trickling Filter\nCreated Overall Efficiency when Efficiency of First and Second Filter Stage is Given\nVerified Efficiency of Single Stage High Rate Trickling Filter\nVerified Efficiency of Single Stage High Rate Trickling Filter when Unit Organic Loading is Given\nVerified Filter Volume when Efficiency of Filter is Given\nVerified Filter Volume when Volume of Raw Sewage is Given\nVerified Final Efficiency After Two Stage Filtration\nVerified Initial Efficiency when Final Efficiency After Two Stage Filtration is Given\nVerified Recirculation Factor for the Second Stage Filter\nVerified Recirculation Factor when Efficiency of Filter is Given\nVerified Recirculation Factor when Recirculation ratio is Given\nVerified Recirculation Factor when Volume of Raw Sewage is Given\nVerified Recirculation Ratio when Volume of Raw Sewage is Given\nVerified Total BOD in Effluent when Final Efficiency After Two Stage Filtration is Given\nVerified Total Organic Load when Efficiency of Filter is Given\nVerified Total Organic Load when Volume of Raw Sewage is Given\nVerified Unit Organic Loading on Filter when volume of Raw Sewage is Given\nVerified Volume of Raw Sewage when Recirculation ratio is Given\nVerified Volume of Raw Sewage when Unit Organic Loading on Filter is Given\nVerified Volume of Recirculated Sewage when Recirculation ratio is Given\nVerified Volume of Recirculated Sewage when Unit Organic Loading on Filter is Given\nVerified Volume of Second Stage Filter\nVerified Effluent BOD when Oxygen Demand and Ultimate BOD Both is Given\nVerified Effluent BOD when Oxygen Demand of Biomass is Given\nVerified Effluent BOD when Oxygen Required in Aeration Tank is Given\nVerified Effluent BOD when Ultimate BOD is Given\nCreated Effluent Flow Rate when Wasting Rate from Return Line is Given\nCreated Effluent Substrate Concentration when Net Waste Activated Sludge is given\nCreated Effluent Substrate Concentration when Theoretical Oxygen Requirement is given\nCreated Effluent Substrate Concentration when Volume of Reactor is given\nVerified Diameter of Circular Section\nVerified Width of Egg Shaped Section when Diameter of Circular Section is Given\nVerified Elastic Modulus of Rock when Deflection Due to Moments on a Arch Dam is Given\nVerified Elastic Modulus of Rock when Deflection Due to Shear on a Arch Dam is Given\n4 More Elastic Modulus of Rock Calculators\nVerified Completion time for given distance of path\nVerified Distance Measured\nVerified Velocity in Medium when Distance is Given\nVerified Elongation of Tapering Bar due to Self Weight\nVerified Length of Bar when Elongation of Tapering Bar with Cross-sectional area is Given\nVerified Length of Rod when Elongation due to Self Weight in Uniform Bar is Given\nVerified Modulus of Elasticity of Bar when Elongation of Tapering Bar due to Self Weight is Given\nVerified Stress when Elongation of Tapering Rod due to Self Weight is Given\n9 More Elongation of Tapering Bar due to Self Weight Calculators\nCreated Endogenous Decay Coefficient when Observed Cell Yield is given\nCreated Endogenous Decay Constant when Volume of Reactor is given\nVerified Endogenous Respiration Rate Constant when Mass of Wasted Activated Sludge is Given\nVerified Endogenous Respiration Rate Constant when Maximum Yield Coefficient is Given\nVerified Endogenous Respiration Rate Constant when Reciprocal of Sludge Age is Given\nVerified Energy Slope of channel when Energy Gradient is Given\nVerified Energy Slope of Rectangular channel\nVerified Energy Slope of Rectangular channel through Chezy formula\nVerified Energy Slope when Slope of Dynamic Equation of Gradually Varied Flow is Given\nVerified Length of Culvert when Velocity of Flow Fields is Given\n5 More Entrance and Exit Submerged Calculators\nVerified Average Daily Flow when Maximum Daily Flow for Areas of Moderate Sizes is Given\nVerified Average Daily Flow when Maximum Hourly Flow is Given\nVerified Average Daily Flow when Minimum Daily Flow for Areas of Moderate Sizes is Given\nVerified Average Daily Flow when Minimum Hourly Flow is Given\nVerified Average Daily Sewage Flow when Peak Sewage Flow is Given\nVerified Maximum Daily Flow for Areas of Moderate Sizes\nVerified Maximum Daily Flow when Maximum Hourly Flow is Given\nVerified Maximum Hourly Flow when Average Daily Flow is Given\nVerified Maximum Hourly Flow when Maximum Daily Flow for Areas of Moderate Sizes is Given\nVerified Minimum Daily Flow for Areas of Moderate Sizes\nVerified Minimum Daily Flow when Minimum Hourly Flow is Given\nVerified Minimum Hourly Flow when Average Daily Flow is Given\nVerified Minimum Hourly Flow when Minimum Daily Flow for Areas of Moderate Sizes is Given\nVerified Peak Sewage Flow when Population in Thousands is Given\nVerified Population in Thousands when Peak Sewage Flow is Given\nVerified Flood Frequency when Recurrence Interval is Given\nVerified Flood Index when Flood Discharge is Given\nVerified Number of Years After which Such a Flood Recorded for Fuller's Formula\nVerified Number of Years After which Such a Flood Recorded when Flood Discharge by Fuller's Formula is Given\nVerified Number of Years when Recurrence Interval by California Method is Given\nVerified Number of Years when Recurrence Interval by Hazen's Method is Given\nVerified Actual Vapour Pressure when Evaporation Loss Per Day is Given\nVerified Actual Vapour Pressure when Evaporation Loss Per Month is Given\nVerified Atmospheric Pressure when Change in Vapour Pressure is Given\nVerified Atmospheric Pressure when Evaporation Loss Per Day is Given\nVerified Change in Vapour Pressure when Evaporation Loss Per Day is Given\nVerified Change in Vapour Pressure when Evaporation Loss Per Month is Given\nVerified Constant Dependent on Depth of Water Bodies when Change in Vapour Pressure is Given\nVerified Constant Dependent on Depth of Water Bodies when Evaporation Loss Per Month is Given\nVerified Constant Used in Meyer's Formula when Evaporation Loss Per Month is Given\nVerified Constant used in Rohwer's Formula when Change in Vapour Pressure is Given\nVerified Constant used in Rohwer's Formula when Evaporation Loss Per Day is Given\nVerified Evaporation Loss Per Day\nVerified Evaporation Loss Per Day when Change in Vapour Pressure is Given\nVerified Evaporation Loss Per Month\nVerified Evaporation Loss Per Month when Change in Vapour Pressure is Given\nVerified Evaporation Loss Per Month when Constant Used in Meyer's Formula is 16\nVerified Evaporation Loss Per Month when Deep Water Body is Given\nVerified Evaporation Loss Per Month when Shallow Water Body is Given\nVerified Maximum Vapour Pressure when Evaporation Loss Per Day is Given\nVerified Maximum Vapour Pressure when Evaporation Loss Per Month is Given\nVerified Mean Wind Velocity at Ground Level when Evaporation Loss Per Day is Given\nVerified Monthly Mean Wind Velocity when Evaporation Loss Per Month is Given\nCreated Falling Speed of Smaller Particle\nCreated Falling Speed when Height at Outlet Zone with respect to Area of Tank is Given\nCreated Falling Speed when Ratio of Removal with respect to Discharge is Given\nCreated Falling Speed when Ratio of Removal with respect to Settling Velocity is Given\nCreated Falling Speed when Surface Area with respect to Settling Velocity is Given\nCreated Concrete Column Elasticity Modulus when Flexural Stiffness is Given\nCreated Moment of Inertia about Centroidal Axis when Flexural Stiffness is Given\n4 More Flat Plate Construction Calculators\nVerified External Diameter of Pipe when Load Per Unit Length for Flexible Pipes is Given\nVerified Fill Coefficient when Load Per Unit Length for Flexible Pipes is Given\nVerified Load Per Unit Length for Flexible Pipes\nVerified Specific Weight of Fill Material when Load Per Unit Length for Flexible Pipes is Given\nVerified Width of Trench when Load Per Unit Length for Flexible Pipes is Given\nVerified Flood Coefficient when Flood Discharge is Given\nVerified Flood Discharge\nVerified Flood Discharge by Dicken's Formula\nVerified Flood Discharge by Dicken's Formula for Northern India\nVerified Flood Discharge by Dicken's Formula in F.P.S Unit\nVerified Flood Discharge by Dicken's Formula in F.P.S Unit for Northern India\nVerified Flood Discharge by Fanning's Formula\nVerified Flood Discharge by Fanning's Formula when Average Value of Constant is Given\nVerified Flood Discharge by Fuller's Formula\nVerified Flood Discharge by Inglis Formula\nVerified Flood Discharge by Nawab Jang Bahadur Formula\nVerified Flood Discharge for Area within 24 KM from the Coast\nVerified Flood Discharge for Area within 24 KM to 161 KM from the Coast\nVerified Flood Discharge for Catchment of Former Bombay Presidency\nVerified Flood Discharge for Limited Area Near Hills\nVerified Flood Discharge for Madras Catchment\nVerified Flood Discharge for Madras Catchment in F.P.S Unit\nVerified Flood Discharge in FPS Unit by Creager's Formula\nVerified Flood Discharge in FPS Unit by Fanning's Formula\nVerified Flood Discharge in FPS Unit by Fanning's Formula when Average Value of Constant is Given\nVerified Flood Discharge in FPS Unit by Fuller's Formula\nVerified Flood Discharge in FPS Unit by Inglis Formula\nVerified Flood Discharge in FPS Unit by Nawab Jang Bahadur Formula\nVerified Flood Discharge in FPS Unit for Area within 24 KM from the Coast\nVerified Flood Discharge in FPS Unit for Area within 24 KM to 161 KM from the Coast\nVerified Flood Discharge in FPS Unit for Catchment of Former Bombay Presidency\nVerified Flood Discharge in FPS Unit for Limited Area Near Hills\nVerified Change in Storage denoting the beginning and end of Time Interval with respect to Inflow and Outflow\nVerified Rate of Change of Storage\n16 More Flood Routing Calculators\nVerified Flood Serial Number when Recurrence Interval by California Method is Given\nVerified Flood Serial Number when Recurrence Interval by Gumbel's Method is Given\nVerified Flood Serial Number when Recurrence Interval by Hazen's Method is Given\nVerified Hydraulic Depth when Section Factor is Given\nVerified Section Factor in open channel\nVerified Top Width when Section Factors is Given\nVerified Wetted Area when Section Factor is Given\nVerified Coefficient of Permeability when Discharge is Given\nVerified Depth of Water in Gallery when Discharge is Given\nVerified Discharge Passing Through the Vertical Section of Infiltration Gallery\nVerified Distance between Infiltration Gallery and Source when Discharge is Given\nVerified Height of Saturated Zone when Discharge is Given\nVerified Cost when Most economical pipe diameter for a distribution system is Given\nVerified Most economical pipe diameter for a distribution system for water\nVerified Power when Most economical pipe diameter for a distribution system is Given\n5 More Flow Over Notches and Weirs Calculators\nVerified Flow Velocity when Coefficient of Permeability is Given\nVerified Flow Velocity when Rate of Flow is Given\nVerified Flow Velocity when Reynold's Number is Unity\nVerified Flow Velocity of Water Entering the Tank\nVerified Flow Velocity of Water Entering the Tank when Cross-section Area of Tank is Given\nVerified Flow Velocity when Length of Tank is Given\nVerified Flow Velocity when Length to Depth Ratio is Given\nVerified Conversion Factor when Flow Velocity is given\nVerified Energy Loss when Flow Velocity is given\nVerified Flow Velocity using Manning's formula\nVerified Hydraulic Radius when Flow Velocity is given\nVerified Water Flow Equation\n3 More Flow velocity in straight sewers Calculators\nVerified Self Cleansing Velocity when Bed Slope for Partial Flow is Given\nVerified Self Cleansing Velocity when Hydraulic Mean Depth for Full Flow is Given\nVerified Self Cleansing Velocity when Hydraulic Mean Depth Ratio is Given\nVerified Self Cleansing Velocity when Ratio of Bed Slope is Given\nVerified Velocity of Full Flow when Hydraulic Mean Depth for Full Flow is Given\nVerified Velocity of Full Flow when Hydraulic Mean Depth Ratio is Given\nVerified Velocity Ratio when Hydraulic Mean Depth Ratio is Given\nVerified Velocity Ratio when Ratio of Bed Slope is Given\nVerified Velocity when Running Full when Bed Slope for Partial Flow is Given\nVerified Velocity when Running Full when Ratio of Bed Slope is Given\nVerified BOD Influent when F/M Ratio is Given\nVerified BOD Influent when MLSS is Given\nVerified BOD Load applied to the Aeration System\nVerified BOD Load Applied when MLSS is Given\nVerified BOD of the Influent Sewage when BOD Load applied is Given\nVerified Daily BOD Load when Food to Microorganism Ratio is Given\nVerified F/M Ratio when MLSS is Given\nVerified Food to Microorganism Ratio\nVerified Microbial Mass in the Aeration System\nVerified Microbial Mass in the Aeration System when MLSS is Given\nVerified MLSS when BOD Load Applied to the Aeration System is Given\nVerified MLSS when F/M Ratio is Given\nVerified MLSS when Microbial Mass in the Aeration System is Given\nVerified Sewage Flow into the Aeration System when BOD Load applied is Given\nVerified Sewage Flow when F/M Ratio is Given\nVerified Sewage Flow when MLSS is Given\nVerified Total Microbial Mass when Food to Microorganism Ratio is Given\nVerified Volume of Tank when F/M Ratio is Given\nVerified Volume of Tank when Microbial Mass in the Aeration System is Given\nVerified Volume of Tank when MLSS is Given\nVerified Maximum Moment for Symmetrical Concrete Wall Footing\nVerified Uniform Pressure on Soil when Maximum Moment is Given\n1 More Footing Calculators\nVerified Allowable Compressive Stress Parallel to Grain for Short Columns\nVerified Elasticity Modulus when Allowable Compressive Stress in a Rectangular Section is Given\n3 More Forest Products Laboratory Recommendations Calculators\nVerified Form Drag of a Vessel when Total Longitudinal Current Load on a Vessel is known\n6 More Form Drag Calculators\nVerified Constant dependent on Well Function when Formation Constant S is Given\nVerified Formation Constant S\nVerified Formation Constant S when Radial Distance is Given\nVerified Formation Constant T when Change in Drawdown is Given\nVerified Formation Constant T when Drawdown is Given\nVerified Formation Constant T when Formation Constant S is Given\nVerified Formation Constant T when Radial Distance is Given\nVerified Net Bearing Capacity of a Long Footing in Foundation Stability Analysis\n10 More Foundation Stability Analysis Calculators\nVerified Constant used in F.P.S Unit when Flood Discharge by Dicken's Formula is Given\nVerified Constant used in F.P.S Unit when Flood Discharge for Madras Catchment is Given\nVerified Constant used in FPS Unit when Flood Discharge by Creager's Formula is Given\nVerified Constant used in FPS Unit when Flood Discharge by Fanning's Formula is Given\nVerified Constant used in FPS Unit when Flood Discharge by Fuller's Formula is Given\nVerified Constant used in FPS Unit when Flood Discharge by Nawab Jang Bahadur Formula is Given\nVerified Number of Simultaneous Fire Stream\nVerified Population when Number of Simultaneous Fire Stream is Given\nVerified Population when Quantity of Water by Freeman's Formula is Given\nVerified Quantity of Water by Freeman's Formula\nVerified Friction Factor when Head Loss due to Frictional Resistance is Given\n5 More Friction Factor Calculators\nVerified Bearing Capacity Factor Dependent on Cohesion for Rectangular Footing\nVerified Bearing Capacity Factor Dependent on Cohesion for Rectangular Footing when Shape Factor is Given\nVerified Bearing Capacity Factor Dependent on Surcharge for Rectangular Footing\nVerified Bearing Capacity Factor Dependent on Surcharge for Rectangular Footing when Shape Factor is Given\nVerified Bearing Capacity Factor Dependent on Unit Weight for Rectangular Footing\nVerified Bearing Capacity Factor Dependent on Weight for Rectangular Footing when Shape Factor is Given\nVerified Cohesion of Soil for Rectangular Footing when Shape Factor is Given\nVerified Cohesion of Soil when Ultimate Bearing Capacity for Rectangular Footing is Given\nVerified Effective Surcharge for Rectangular Footing\nVerified Effective Surcharge for Rectangular Footing when Shape Factor is Given\nVerified Length of Rectangular Footing when Ultimate Bearing Capacity is Given\nVerified Ultimate Bearing Capacity for Rectangular Footing\nVerified Ultimate Bearing Capacity for Rectangular Footing when Shape Factor is Given\nVerified Unit Weight of Soil for Rectangular Footing when Shape Factor is Given\nVerified Unit Weight of Soil when Ultimate Bearing Capacity for Rectangular Footing is Given\nVerified Width of Rectangular Footing when Ultimate Bearing Capacity is Given\nVerified Coefficient of Permeability when Discharge for Fully Penetrating Well is Given\nVerified Depth of Water in Well when Discharge for Fully Penetrating Well is Given\nVerified Discharge for Fully Penetrating Well\nVerified Radius of Influence when Discharge for Fully Penetrating Well is Given\nVerified Radius of Well when Discharge for Fully Penetrating Well is Given\nVerified Thickness of Aquifer when Discharge for Fully Penetrating Well is Given\nVerified Bearing Capacity Factor Dependent on Cohesion for General Shear Failure\nVerified Bearing Capacity Factor Dependent on Surcharge for General Shear Failure\nVerified Bearing Capacity Factor Dependent on Unit Weight for General Shear Failure\nVerified Cohesion of Soil when Net Ultimate Bearing Capacity for General Shear Failure is Given\nVerified Effective Surcharge when Net Ultimate Bearing Capacity for General Shear Failure is Given\nVerified Net Ultimate Bearing Capacity for General Shear Failure\nVerified Unit Weight of Soil under Strip Footing for General Shear Failure\nVerified Width of Strip Footing when Net Ultimate Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Cohesion when Modified Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Surcharge when Modified Bearing Capacity is Given\nVerified Bearing Capacity Factor Dependent on Unit Weight when Modified Bearing Capacity is Given\nVerified Cohesion of Soil when Modified Bearing Capacity for General Shear Failure is Given\nVerified Correction Factor Applied Due to Water Table for General Shear Failure\nVerified Effective Surcharge when Modified Bearing Capacity for General Shear Failure is Given\nVerified Modified Bearing Capacity for General Shear Failure\nVerified Shape Factor with Cohesion when Modified Bearing Capacity for General Shear Failure is Given\nVerified Shape Factor with Surcharge when Modified Bearing Capacity for General Shear Failure is Given\nVerified Shape Factor with Unit Weight when Modified Bearing Capacity for General Shear Failure is Given\nVerified Unit Weight of Soil when Modified Bearing Capacity for General Shear Failure is Given\nVerified Width of Footing when Modified Bearing Capacity for General Shear Failure is Given\nVerified Average Percentage Increase when Future Population from Geometrical Increase Method is Given\nVerified Average Percentage Increase when Future Population of 2 Decades by Geometrical Method is Given\nVerified Average Percentage Increase when Future Population of 3 Decades by Geometrical Method is Given\nVerified Future Population at the End of 2 Decades in Geometrical Increase Method\nVerified Future Population at the End of 3 Decades in Geometrical Increase Method\nVerified Future Population at the End of n Decades in Geometrical Increase Method\nVerified Number of Decades when Future Population from Geometrical Increase Method is Given\nVerified Present Population when Future Population from Geometrical Increase Method is Given\nVerified Present Population when Future Population of 2 Decades by Geometrical Increase Method is Given\nVerified Present Population when Future Population of 3 Decades by Geometrical Increase Method is Given\nVerified Wetted Perimeter when Hydraulic Mean Depth is Given\n5 More Geometrical Properties of Channel Section Calculators\nVerified Allowable Bending Stress in Compression Flange\nVerified Allowable Shear Stress with Tension Field Action\nVerified Allowable Shear Stress without Tension Field Action\nVerified Area of Flange When Plate Girder Stress Reduction Factor is Given\nVerified Area of Web When Plate Girder Stress Reduction Factor is Given\nVerified Depth to Thickness Ratio of Girder With Transverse Stiffeners\nVerified Hybrid Girder Factor\nVerified Maximum depth to thickness Ratio for Unstiffened Web\nVerified Plate Girder Stress Reduction Factor\nVerified Camber when Gradient is given\nVerified Area of Section when Energy Gradient is Given\nVerified Area of Section when Total Energy is Given\nVerified Bed Slope when Energy Slope of Rectangular channel is Given\nVerified Bed Slope when Energy Slope of Rectangular channel through Chezy formula is Given\nVerified Bed Slope when Slope of Dynamic Equation of Gradually Varied Flow is Given\nVerified Bottom Slope of channel when Energy Gradient is Given\nVerified Depth of Flow when Energy Slope of Rectangular channel is Given\nVerified Depth of Flow when Energy Slope of Rectangular channel through Chezy formula is Given\nVerified Depth of Flow when Total Energy is Given\nVerified Discharge when Energy Gradient is Given\nVerified Discharge when Froude Number is Given\nVerified Discharge when Total Energy is Given\nVerified Energy Gradient when bed slope is given\nVerified Energy Gradient when slope is given\nVerified Froude Number when Slope of Dynamic Equation of Gradually Varied Flow is Given\nVerified Froude Number with top width given\nVerified Normal Depth when Energy Slope of Rectangular channel is Given\nVerified Slope of Dynamic Equation of Gradually Varied Flow when Energy Gradient is Given\nVerified Slope of Dynamic Equation of Gradually Varied Flows\nVerified Top Width when Energy Gradient is Given\nVerified Top Width when Froude Number is Given\n3 More Gradually Varied Flow Calculators\nVerified Pressure P1 when the Resultant is within the Middle Third and Width of Base is Given\nVerified Pressure P2 when the Resultant is within the Middle Third and Width of Base is Given\n5 More Gravity Retaining Wall Calculators\nVerified Reynolds Number of Value Unity\n6 More Groundwater Hydrology Calculators\nVerified Average Birth Rate Per Year when Natural Increase is Given\nVerified Average Death Rate Per Year when Natural Increase is Given\nVerified Design Period when Natural Increase is Given\nVerified Future Population at the End of n Decades when Migration is Given\nVerified Migration when Future Population at the End of n Decades is Given\nVerified Natural Increase when Design Period is Given\nVerified Natural Increase when Future Population at the End of n Decades is Given\nVerified Present Population when Future Population is Given\nVerified Present Population when Natural Increase is Given\nVerified Average Flood Discharge when Flood Discharge Having Highest Frequency is Given\nVerified Flood Discharge Having Highest Frequency\nVerified Flood Discharge Having Highest Frequency when Gumbel's Reduced Variate is Given\nVerified Flood Discharge when Gumbel's Reduced Variate is Given\nVerified Gumbel's Constant when Gumbel's Reduced Variate is Given\nVerified Gumbel's Constant when Standard Deviation is Given\nVerified Gumbel's Correction when Recurrence Interval by Gumbel's Method is Given\nVerified Gumbel's Reduced Variate\nVerified Number of Years when Recurrence Interval by Gumbel's Method is Given\nVerified Probability of Occurrence when Recurrence Interval is Given\nVerified Recurrence Interval by Gumbel's Method\nVerified Recurrence Interval when Probability is Given\nVerified Standard Deviation when Flood Discharge Having Highest Frequency is Given\nVerified Standard Deviation when Gumbel's Constant is Given\nVerified Dynamic Viscosity when Pressure Drop over the Length of Pipe with Discharge is Given\n20 More Hagen–Poiseuille Equation Calculators\nVerified Coefficient Dependent on Pipe when Head Loss is Given\nVerified Coefficient Dependent on Pipe when Radius of Pipe is Given\nVerified Coefficient of Roughness of Pipe when Diameter of Pipe is Given\nVerified Coefficient of Roughness of Pipe when Mean Velocity of Flow is Given\nVerified Diameter of Pipe when Head Loss by Hazen Williams Formula is Given\nVerified Diameter of Pipe when Hydraulic Gradient is Given\nVerified Head Loss by Hazen Williams Formula\nVerified Head Loss by Hazen Williams Formula when Radius of Pipe is Given\nVerified Hydraulic Gradient when Diameter of Pipe is Given\nVerified Hydraulic Gradient when Mean Velocity of Flow is Given\nVerified Hydraulic Radius when Mean Velocity of Flow is Given\nVerified Length of Pipe by Hazen Williams Formula when Radius of Pipe is Given\nVerified Length of Pipe when Head Loss by Hazen Williams Formula is Given\nVerified Mean Velocity of Flow in Pipe by Hazen Williams Formula\nVerified Mean Velocity of Flow in Pipe when Diameter of Pipe is Given\nVerified Radius of Pipe by Hazen Williams Formula when Length of Pipe is Given\nVerified Velocity of Flow by Hazen Williams Formula when Radius of Pipe is Given\nVerified Velocity of Flow when Head Loss by Hazen Williams Formula is Given\nCreated Height at Outlet Zone when Falling Speed of Smaller Particle is Given\nCreated Height at Outlet Zone when Ratio of Removal with respect to Tank Height is Given\nCreated Height at Outlet Zone with respect to Area of Tank\nCreated Height at Outlet Zone with respect to Discharge\nCreated Height at Outlet Zone with respect to Settling Velocity\nCreated Height of Settling Zone when Cross-section Area of Sedimentation Tank is Given\nCreated Height of Settling Zone when Detention Time is Given\nCreated Height of Settling Zone when Height at Outlet Zone with respect to Area of Tank is Given\nCreated Height of Settling Zone when Height at Outlet Zone with respect to Discharge is Given\nCreated Height of Settling Zone when Height at Outlet Zone with respect to Settling Velocity is Given\nCreated Height of Settling Zone when Length of Sedimentation Tank with respect to Surface Area is Given\nCreated Height of Settling Zone when Length of Tank with respect to Darcy Weishbach Factor is Given\nCreated Height of Settling Zone when Length of Tank with respect to Height for Practical Purpose is Given\nCreated Height of Settling Zone when Ratio of Removal with respect to Tank Height is Given\nVerified Modulus of Elasticity when Hoop Stress due to temperature fall with strain is Given\nVerified Strain when Hoop Stress due to temperature fall is Given" ]	[ null, "https://www.calculatoratoz.com/Images/UserInfo//ishita.jpg", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.7570373,"math_prob":0.48279732,"size":123248,"snap":"2021-31-2021-39","text_gpt3_token_len":29924,"char_repetition_ratio":0.311504,"word_repetition_ratio":0.5577413,"special_character_ratio":0.174015,"punctuation_ratio":0.0030193536,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98226315,"pos_list":[0,1,2],"im_url_duplicate_count":[null,2,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-09-17T19:54:36Z\",\"WARC-Record-ID\":\"<urn:uuid:4d2cc2b8-1039-4e73-a29d-cdde73a300c2>\",\"Content-Length\":\"1048924\",\"Content-Type\":\"application/http; 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https://www.mothur.org/w/index.php?title=Bootstrap&oldid=357	[ "Bootstrap\n\nExample Calculations\n\nboot\n\nThese files give the bootstrap estimate as described by Smith and Van Belle (5) but implemented for a single \"quadrant\".\n\n$S_{Bootstrap} = S_{obs} + \\sum_{i=1}^{S_{obs}} \\left ( 1 - \\frac {S_i}{N}\\right )^N$\n\nwhere,\n\nN = The number of individuals sampled\n\n$S_{i}$ = The number of sequences in the ith OTU\n\n$S_{obs}$ = Observed number of species\n\nFor the Amazonian dataset at distance 0.03, $S_{Bootstrap}$ =112.33 and there is not a simple expression for the 95% confidence interval.\n\nFile Samples on the Amazonian Dataset\n\n• .sabund\n\nThis file contains data for constructing a rank-abundance plot of the OTU data for each distance level. The first column contains the distance and the second is the number of OTUs observed at that distance. The successive values in the row are the number of OTUs that were found once, twice, etc.\n\nunique\t 2\t94\t2\n0\t 2\t92\t3\n0.01\t 2\t88\t5\n0.02\t 4\t84\t2\t2\t1\n0.03\t 4\t75\t6\t1\t2\n0.04\t 4\t69\t9\t1\t2\n0.05\t 4\t55\t13\t3\t2\n0.06\t 4\t48\t14\t2\t4\n0.07\t 4\t44\t16\t2\t4\n0.08\t 7\t36\t15\t4\t2\t1\t0\t1\n0.09\t 7\t36\t12\t4\t3\t0\t0\t2\n0.1\t 7\t35\t12\t2\t3\t0\t0\t3\n\n• .bootstrap" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.7196208,"math_prob":0.99738264,"size":1239,"snap":"2019-43-2019-47","text_gpt3_token_len":436,"char_repetition_ratio":0.11821862,"word_repetition_ratio":0.0,"special_character_ratio":0.37449557,"punctuation_ratio":0.0877193,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98215187,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-10-21T02:55:06Z\",\"WARC-Record-ID\":\"<urn:uuid:daeb885b-e956-4950-997b-2c75ec0c392c>\",\"Content-Length\":\"15185\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:4d3899e2-5604-419c-950b-84ac4b549f63>\",\"WARC-Concurrent-To\":\"<urn:uuid:c3f0950a-ec6b-45d3-8a23-629d705e57aa>\",\"WARC-IP-Address\":\"141.214.120.22\",\"WARC-Target-URI\":\"https://www.mothur.org/w/index.php?title=Bootstrap&oldid=357\",\"WARC-Payload-Digest\":\"sha1:KZPAZKK2K3MEE4JPGPQLB4VAIS23OJNA\",\"WARC-Block-Digest\":\"sha1:4ZTL2SYPDKKJD6AHNEPJNYBIWOEJQZ5P\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-43/CC-MAIN-2019-43_segments_1570987751039.81_warc_CC-MAIN-20191021020335-20191021043835-00467.warc.gz\"}"}
https://se.mathworks.com/help/optim/ug/nonlinear-least-squares-problem-based-basics.html	[ "# Nonlinear Least-Squares, Problem-Based\n\nThis example shows how to perform nonlinear least-squares curve fitting using the Problem-Based Optimization Workflow.\n\n### Model\n\nThe model equation for this problem is\n\n`$y\\left(t\\right)={A}_{1}\\mathrm{exp}\\left({r}_{1}t\\right)+{A}_{2}\\mathrm{exp}\\left({r}_{2}t\\right),$`\n\nwhere ${A}_{1}$, ${A}_{2}$, ${r}_{1}$, and ${r}_{2}$ are the unknown parameters, $y$ is the response, and $t$ is time. The problem requires data for times `tdata` and (noisy) response measurements `ydata`. The goal is to find the best $A$ and $r$, meaning those values that minimize\n\n`$\\sum _{t\\in tdata}{\\left(y\\left(t\\right)-ydata\\right)}^{2}.$`\n\n### Sample Data\n\nTypically, you have data for a problem. In this case, generate artificial noisy data for the problem. Use `A = [1,2]` and `r = [-1,-3]` as the underlying values, and use 200 random values from `0` to 3 as the time data. Plot the resulting data points.\n\n```rng default % For reproducibility A = [1,2]; r = [-1,-3]; tdata = 3rand(200,1); tdata = sort(tdata); % Increasing times for easier plotting noisedata = 0.05randn(size(tdata)); % Artificial noise ydata = A(1)exp(r(1)tdata) + A(2)exp(r(2)tdata) + noisedata; plot(tdata,ydata,'r') xlabel 't' ylabel 'Response'```", null, "The data are noisy. Therefore, the solution probably will not match the original parameters `A` and `r` very well.\n\n### Problem-Based Approach\n\nTo find the best-fitting parameters `A` and `r`, first define optimization variables with those names.\n\n```A = optimvar('A',2); r = optimvar('r',2);```\n\nCreate an expression for the objective function, which is the sum of squares to minimize.\n\n```fun = A(1)exp(r(1)tdata) + A(2)exp(r(2)tdata); obj = sum((fun - ydata).^2);```\n\nCreate an optimization problem with the objective function `obj`.\n\n`lsqproblem = optimproblem(\"Objective\",obj);`\n\nFor the problem-based approach, specify the initial point as a structure, with the variable names as the fields of the structure. Specify the initial `A = [1/2,3/2]` and the initial `r = [-1/2,-3/2]`.\n\n```x0.A = [1/2,3/2]; x0.r = [-1/2,-3/2];```\n\nReview the problem formulation.\n\n`show(lsqproblem)`\n``` OptimizationProblem : Solve for: A, r minimize : sum(arg6) where: arg5 = extraParams{3}; arg6 = (((A(1) . exp((r(1) .* extraParams{1}))) + (A(2) .* exp((r(2) .* extraParams{2})))) - arg5).^2; extraParams ```\n\n### Problem-Based Solution\n\nSolve the problem.\n\n`[sol,fval] = solve(lsqproblem,x0)`\n```Solving problem using lsqnonlin. Local minimum found. Optimization completed because the size of the gradient is less than the value of the optimality tolerance. <stopping criteria details> ```\n```sol = struct with fields: A: [2×1 double] r: [2×1 double] ```\n```fval = 0.4724 ```\n\nPlot the resulting solution and the original data.\n\n```figure responsedata = evaluate(fun,sol); plot(tdata,ydata,'r',tdata,responsedata,'b-') legend('Original Data','Fitted Curve') xlabel 't' ylabel 'Response' title(\"Fitted Response\")```", null, "The plot shows that the fitted data matches the original noisy data fairly well.\n\nSee how closely the fitted parameters match the original parameters `A = [1,2]` and `r = [-1,-3]`.\n\n`disp(sol.A)`\n``` 1.1615 1.8629 ```\n`disp(sol.r)`\n``` -1.0882 -3.2256 ```\n\nThe fitted parameters are off by about 15% in `A` and 8% in `r`.\n\n### Unsupported Functions Require `fcn2optimexpr`\n\nIf your objective function is not composed of elementary functions, you must convert the function to an optimization expression using `fcn2optimexpr`. See Convert Nonlinear Function to Optimization Expression. For the present example:\n\n```fun = @(A,r) A(1)exp(r(1)tdata) + A(2)exp(r(2)*tdata); response = fcn2optimexpr(fun,A,r); obj = sum((response - ydata).^2);```\n\nThe remainder of the steps in solving the problem are the same. The only other difference is in the plotting routine, where you call `response` instead of `fun`:\n\n`responsedata = evaluate(response,sol);`\n\nFor the list of supported functions, see Supported Operations on Optimization Variables and Expressions." ]	[ null, "https://se.mathworks.com/help/examples/optim/win64/NonlinearLeastSquaresProblemBasedExample_01.png", null, "https://se.mathworks.com/help/examples/optim/win64/NonlinearLeastSquaresProblemBasedExample_02.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.688908,"math_prob":0.99851394,"size":3485,"snap":"2020-34-2020-40","text_gpt3_token_len":962,"char_repetition_ratio":0.12381499,"word_repetition_ratio":0.015473888,"special_character_ratio":0.2898135,"punctuation_ratio":0.17045455,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9994742,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,2,null,2,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-09-24T21:46:17Z\",\"WARC-Record-ID\":\"<urn:uuid:dae6220e-2c23-48ed-8430-b1c4db3a5581>\",\"Content-Length\":\"77523\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8e39c6b3-5dea-407e-94fa-2bd0399d7f01>\",\"WARC-Concurrent-To\":\"<urn:uuid:5d572a3b-0c6e-46ac-974c-ff791ff29fe2>\",\"WARC-IP-Address\":\"184.25.198.13\",\"WARC-Target-URI\":\"https://se.mathworks.com/help/optim/ug/nonlinear-least-squares-problem-based-basics.html\",\"WARC-Payload-Digest\":\"sha1:UWOIQTOMJLMTDYQUZKXGJXAGC2GAKNTN\",\"WARC-Block-Digest\":\"sha1:RCTECLXFCX6D7JDQRUY4K56DHNRP6TL6\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-40/CC-MAIN-2020-40_segments_1600400220495.39_warc_CC-MAIN-20200924194925-20200924224925-00241.warc.gz\"}"}
https://ianozsvald.com/tag/binary-matrix/	[ "# Archives of #Binary Matrix\n\n#### Visualising the internals of Logistic Regression on a Text Matrix\n\nBelow I have some plots that visualise the term matrix (as a binary matrix and as a TF-IDF matrix) for the brand disambiguation project followed by a visualisation of the coefficients used in scikit-learn’s LogisticRegression classifier using l1 and l2 penalties. Using a CountVectorizer with binary=True we can mark the absence or presence of a […]" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.85667485,"math_prob":0.61800724,"size":415,"snap":"2021-04-2021-17","text_gpt3_token_len":87,"char_repetition_ratio":0.11922141,"word_repetition_ratio":0.0,"special_character_ratio":0.18554217,"punctuation_ratio":0.014285714,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.96366835,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-04-22T16:31:32Z\",\"WARC-Record-ID\":\"<urn:uuid:55bc12f9-b194-417a-9a21-865fc31d8d42>\",\"Content-Length\":\"39517\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:798caa3c-5635-473a-a8d5-b8c022eab148>\",\"WARC-Concurrent-To\":\"<urn:uuid:cf001de4-3d9e-41e9-bd42-24452c67197c>\",\"WARC-IP-Address\":\"155.133.132.2\",\"WARC-Target-URI\":\"https://ianozsvald.com/tag/binary-matrix/\",\"WARC-Payload-Digest\":\"sha1:FFDVUL77D7AZG3S24HNSFS764WAQ4HUH\",\"WARC-Block-Digest\":\"sha1:ACMDKBXLECXHQSNOROLOMRDYHVOF4BYW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-17/CC-MAIN-2021-17_segments_1618039594341.91_warc_CC-MAIN-20210422160833-20210422190833-00302.warc.gz\"}"}
https://mirror.las.iastate.edu/CRAN/web/packages/formulops/readme/README.html	[ "# formulops\n\nThe goal of formulops is to assist with formula modification in R treating formulae as standard mathematical operations as used with `nlme::nlme()` and `lme4::nlmer()` (for treatment as statistical formula see the `Formula` package).\n\n## Installation\n\nYou can install the released version of formulops from CRAN with:\n\n``install.packages(\"formulops\")``\n\n## Example\n\nA few common examples of modifying a formula are given below.\n\n``````library(formulops)\n# Replace a with c in the formula\nmodify_formula(a~b, find=quote(a), replace=quote(c))\n# Replace a with c+d in the formula\nmodify_formula(a~b, find=quote(a), replace=quote(c+d))\n# More complex parts can be replaced, too\nmodify_formula(a~b/c, find=quote(b/c), replace=quote(d))\n# Multiple replacements can occur simultaneously\nmodify_formula(a~b/c+d, find=list(quote(b/c), quote(d)), replace=list(quote(d), quote(e)))\n# Function arguments can be expanded\nmodify_formula(a~b(c), find=quote(c), replace=quote(formulops_expand(d, e)))``````\n\nA substituting formula is a simple way to generate a complex formula from several simpler formulae. Parentheses are appropriately added, if required.\n\n``````foo <- substituting_formula(y~x1+x2, x1~x3*x4, x2~x5/x6+x7)\nas.formula(foo)``````" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.7820204,"math_prob":0.9816333,"size":1055,"snap":"2022-27-2022-33","text_gpt3_token_len":254,"char_repetition_ratio":0.19600381,"word_repetition_ratio":0.015625,"special_character_ratio":0.22654028,"punctuation_ratio":0.12182741,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99970293,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-07-07T13:12:39Z\",\"WARC-Record-ID\":\"<urn:uuid:470705f7-2e88-471e-8833-e59d1a7f7676>\",\"Content-Length\":\"8332\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b8267e33-0a0d-472d-abce-7765a7f86773>\",\"WARC-Concurrent-To\":\"<urn:uuid:8ac9fc44-b1bf-4265-935e-5b9bfad0b228>\",\"WARC-IP-Address\":\"129.186.90.88\",\"WARC-Target-URI\":\"https://mirror.las.iastate.edu/CRAN/web/packages/formulops/readme/README.html\",\"WARC-Payload-Digest\":\"sha1:AUL3QDYJBNEYWN66Z6YEONDDSN5IV5LA\",\"WARC-Block-Digest\":\"sha1:YVAGHQDWL5S4GYLRAOL6KRWEXEPRNP4O\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-27/CC-MAIN-2022-27_segments_1656104692018.96_warc_CC-MAIN-20220707124050-20220707154050-00275.warc.gz\"}"}
https://e-eduanswers.com/mathematics/question3763370	[ " What’s the least common denominator (lcd) for each group of fractions? a. 1⁄6 and 7⁄8 b. 3⁄4 and 7⁄10 c. 7⁄12, 3⁄8 and 11⁄36", null, "", null, ", 18.10.2019 06:30, davidaagurto\n\n# What’s the least common denominator (lcd) for each group of fractions? a. 1⁄6 and 7⁄8 b. 3⁄4 and 7⁄10 c. 7⁄12, 3⁄8 and 11⁄36 d. 8⁄15, 11⁄30 and 3⁄5", null, "### Other questions on the subject: Mathematics", null, "Mathematics, 21.06.2019 16:40, jessicap7pg75\nIf 24 people have the flu out of 360 people, how many would have the flu out of 900. choose many ways you could use proportion that david would use to solve this problem", null, "Mathematics, 21.06.2019 17:40, kiingbr335yoqzaxs\nGiven abcd ac=38 and ae=3x+4 find the value of x", null, "Mathematics, 21.06.2019 18:30, josephmartinelli5\nWhat is the prime factorization of 23 ? me with this question", null, "Mathematics, 21.06.2019 20:30, anniekwilbourne\nKayla made observations about the sellin price of a new brand of coffee that sold in the three different sized bags she recorded those observations in the following table 6 is $2.10 8 is$2.80 and 16 is to \\$5.60 use the relationship to predict the cost of a 20oz bag of coffee.\nDo you know the correct answer?\nWhat’s the least common denominator (lcd) for each group of fractions? a. 1⁄6 and 7⁄8 b. 3⁄4 and 7⁄...\n\n### Questions in other subjects:", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "", null, "Total solved problems on the site: 7551738" ]	[ null, "https://e-eduanswers.com/tpl/images/sovy.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/otvet.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/en.png", null, "https://e-eduanswers.com/tpl/images/cats/himiya.png", null, "https://e-eduanswers.com/tpl/images/cats/istoriya.png", null, "https://e-eduanswers.com/tpl/images/cats/himiya.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/en.png", null, "https://e-eduanswers.com/tpl/images/cats/mat.png", null, "https://e-eduanswers.com/tpl/images/cats/biologiya.png", null, "https://e-eduanswers.com/tpl/images/cats/mkx.png", null, "https://e-eduanswers.com/tpl/images/cats/en.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8293105,"math_prob":0.75884455,"size":1277,"snap":"2020-34-2020-40","text_gpt3_token_len":497,"char_repetition_ratio":0.15710919,"word_repetition_ratio":0.16831683,"special_character_ratio":0.4119029,"punctuation_ratio":0.22713864,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.97351426,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34],"im_url_duplicate_count":[null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-09-18T08:09:59Z\",\"WARC-Record-ID\":\"<urn:uuid:3afc60a0-5e7e-4d49-a9d9-688ae6197a0d>\",\"Content-Length\":\"128159\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:c1fac7d4-78d4-493c-beff-7f5bf246aa11>\",\"WARC-Concurrent-To\":\"<urn:uuid:f5f0f6b1-8d07-487b-a43e-65d712c3b2d8>\",\"WARC-IP-Address\":\"64.74.160.240\",\"WARC-Target-URI\":\"https://e-eduanswers.com/mathematics/question3763370\",\"WARC-Payload-Digest\":\"sha1:CDUQDTGKZJ36BJQFNWNOLCK3AUH2LPUC\",\"WARC-Block-Digest\":\"sha1:FWXIRIWWW7UDA36GUUAO2UYRWUYGXQO5\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-40/CC-MAIN-2020-40_segments_1600400187354.1_warc_CC-MAIN-20200918061627-20200918091627-00367.warc.gz\"}"}
https://gis.stackexchange.com/questions/258986/plot-two-rasters-with-different-extents	[ "Plot two rasters with different extents\n\nI have two rasters with different extents that overlap partly:\n\next1 <- extent(99500,700500,249500,600500)\next2 <- extent(1356,643990,269903,690810)\n\n#create rasters\nrr1 <- raster(matrix(runif(1000000,0,100), 1000, 1000))\nrr2 <- raster(matrix(runif(1000000,0,100), 1000, 1000))\n\nextent(rr1) <- ext1\nextent(rr2) <- ext2\n\nHow can I plot both rasters in one plot?\n\nI've tried\n\next3 <- extent(min(ext1,ext2),max(ext1,ext2),\nmin(ext1,ext2),max(ext1,ext2))\nplot(rr1, ext = ext3)\n\nBut the only the extent of rr1 is used.\n\nMerge the extents (which saves all that min/max stuff!) and plot the extent, then add the rasters:\n\nem = merge(extent(rr1),extent(rr2))\nplot(em, type=\"n\")" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.62990534,"math_prob":0.99486494,"size":530,"snap":"2019-43-2019-47","text_gpt3_token_len":199,"char_repetition_ratio":0.16920152,"word_repetition_ratio":0.0,"special_character_ratio":0.49433962,"punctuation_ratio":0.21008404,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9960518,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-10-22T21:19:27Z\",\"WARC-Record-ID\":\"<urn:uuid:a9c71e0c-eb80-4b33-9ed0-34007cb2dae5>\",\"Content-Length\":\"136321\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7fe70ffc-546f-499f-8dc9-52f090c6e021>\",\"WARC-Concurrent-To\":\"<urn:uuid:991adfd6-dc69-4486-bc51-8730302f1a4d>\",\"WARC-IP-Address\":\"151.101.193.69\",\"WARC-Target-URI\":\"https://gis.stackexchange.com/questions/258986/plot-two-rasters-with-different-extents\",\"WARC-Payload-Digest\":\"sha1:KMHAC4HG6PQWCXAV2VWNIP4FTZKYTASX\",\"WARC-Block-Digest\":\"sha1:LAF5IUFWXGMI3AW7RPDC4QGZZMWMHX2D\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-43/CC-MAIN-2019-43_segments_1570987824701.89_warc_CC-MAIN-20191022205851-20191022233351-00437.warc.gz\"}"}
http://southmiamirealestateblog.com/pandas-dataframe-set-column-names-from-list	[ " Pandas Dataframe Set Column Names From List \| southmiamirealestateblog.com\n\nUsing rename is a formally more correct approach. You just have to provide a dictionary that maps your current columns names to the new ones thing that will guarantee expected results even in case of misplaced columns. How to get column names in Pandas dataframe While analyzing the real datasets which are often very huge in size, we might need to get the column names in order to perform some certain operations. Let’s discuss how to get column names in Pandas dataframe. Create a column using for loop in Pandas Dataframe; Create a list from rows in Pandas dataframe; Create a list from rows in Pandas DataFrame Set 2; Creating Pandas dataframe using list of lists; Create a new column in Pandas DataFrame based on the existing columns; Python Pandas DataFrame.fillna to replace Null values in dataframe.\n\nSep 02, 2018 · In this article we discuss how to get a list of column and row names of a DataFrame object in python pandas. First of all, create a DataFrame object of students records i.e. Sep 25, 2018 · Here data parameter can be a numpy ndarray, dict, or an other DataFrame. Also, columns and index are for column and index labels. Let’s use this to convert lists to dataframe object from lists. Create DataFrame from list of lists. Suppose we have a list of lists i.e. Pandas DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. It is generally the most commonly used pandas object. Pandas DataFrame can be created in multiple ways. Let’s discuss how to create Pandas dataframe using list of lists.\n\npandas.DataFrame,pandas.Series and Python's built-in type list can be converted to each other.Here, the following contents will be described.Convert list to pandas.DataFrame, pandas.SeriesFor data-only listFor list containing data and labels row / column names For data-only list For list containin. The other option for creating your DataFrames from python is to include the data in a list structure. The first approach is to use a row oriented approach using pandas from_records. This approach is similar to the dictionary approach but you need to explicitly call out the column labels.\n\nOct 18, 2019 · At times, you may need to convert pandas DataFrame into a list in Python. But how would you do that? To accomplish this task, you can use tolist as follows:. df.values.tolist In this short guide, I’ll show you an example of using tolist to convert pandas DataFrame into a list. pandas.DataFrame » Table Of Contents. class or function name. Set the DataFrame index using existing columns. Set the DataFrame index row labels using one or more existing columns or arrays of the correct length. The index can replace the existing index or expand on it. Parameters: keys: label or array-like or list of labels/arrays. Accessing pandas dataframe columns, rows, and cells. Assigning an index column to pandas dataframe ¶ df2 = df1.set_index\"State\", drop = False. So, the formula to extract a column is still the same, but this time we didn’t pass any index name before and after the first colon. Not passing anything tells Python to include all the rows.\n\nDec 20, 2017 · Rename Column Headers In pandas. 20 Dec 2017. Originally from rgalbo on StackOverflow. 0 first_name 1 last_name 2 age 3 preTestScore Name: 0, dtype: objectReplace the.Rename the dataframe's column values with the header variable df. rename columns = header first_name last_name age preTestScore; 1: Molly. pandas.DataFrame¶ class pandas.DataFrame data=None, index=None, columns=None, dtype=None, copy=False [source] ¶ Two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes rows and columns. Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series. Use drop to delete rows and columns from pandas.DataFrame.Before version 0.21.0, specify row / column with parameter labels and axis. index or columns can be used from 0.21.0.pandas.DataFrame.drop — pandas 0.21.1 documentation Here, the following contents will be described.Delete rows from DataFr. pandas.om_dict¶ classmethod om_dict data, orient='columns', dtype=None, columns=None [source] ¶. Construct DataFrame from dict of array-like or dicts. Creates DataFrame object from dictionary by columns or by index allowing dtype specification. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas rename method is used to rename any index, column or row. Renaming of column can also be done by dataframe.columns = [list]. But in the above case, there isn’t much freedom. Even if one column has to be changed, full column list has to be passed." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.68373495,"math_prob":0.68003565,"size":5835,"snap":"2020-34-2020-40","text_gpt3_token_len":1326,"char_repetition_ratio":0.15589093,"word_repetition_ratio":0.019007392,"special_character_ratio":0.21165381,"punctuation_ratio":0.11438785,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9608126,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-09-20T18:28:48Z\",\"WARC-Record-ID\":\"<urn:uuid:d33dcf46-ecaa-43d1-bf2f-df90ff16c7e3>\",\"Content-Length\":\"12451\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:5b229880-da8a-4b14-988d-e47c2feb8784>\",\"WARC-Concurrent-To\":\"<urn:uuid:d347f78a-b5c3-4cc2-82b8-741bdf72b148>\",\"WARC-IP-Address\":\"144.91.111.68\",\"WARC-Target-URI\":\"http://southmiamirealestateblog.com/pandas-dataframe-set-column-names-from-list\",\"WARC-Payload-Digest\":\"sha1:CAXV5NU3HOUKEGB5JXMULUFA5BWWSYRC\",\"WARC-Block-Digest\":\"sha1:IYYMPQC6GOXQHVSPJBRW5MGIZ3DUF6KD\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-40/CC-MAIN-2020-40_segments_1600400198287.23_warc_CC-MAIN-20200920161009-20200920191009-00419.warc.gz\"}"}
https://byjus.com/commerce/sandeep-garg-microeconomics-class-11-solutions-chapter-4-elasticity-of-demand/	[ "", null, "# Sandeep Garg Microeconomics Class 11: Chapter 4 Elasticity of Demand\n\nSandeep Garg Class 11 Microeconomics Solutions Chapter 4 Elasticity of Demand is explained by the expert Economics teachers from the latest edition of Sandeep Garg Microeconomics Class 11 textbook solutions. We at BYJU’S provide Sandeep Garg Economics Class 11 Solutions to give comprehensive insight about the subject to the students. These insights help as a priceless benefit to students while completing their homework or while studying for their exams. There are numerous concepts in economics, however, we at BYJU’S provide the students with the solution from Elasticity of Demand, which will be useful for the students to score well in the board examinations.\n\n## Sandeep Garg Solutions Class 11 – Chapter 4 – Part A – Microeconomics\n\nQuestion 1\n\nWhat is the Elasticity of Demand?\n\nAns: Elasticity of Demand refers to the percentage change in demand for a commodity with respect to the percentage change in any of the factors affecting demand for that commodity.\n\nQuestion 2\n\nHow is the Elasticity of Demand calculated?\n\nAns:\n\n$$\\begin{array}{l}\\frac{Percentage\\, change\\, in\\, demand\\, for\\, X}{Percentage\\, change\\, in\\, a\\, factor \\, affecting\\, the\\, demand\\, for\\, X}\\end{array}$$\n\nQuestion 3\n\nWhat are the 5 Degrees of Elasticity of Demand?\n\nAns: 5 types of price elasticities of demand are:\n\n• Perfectly elastic demand\n• Perfectly inelastic demand\n• Highly elastic demand\n• Less elastic demand\n• Unitary elastic demand\n\nQuestion 4\n\nWhat are the factors that affect the price elasticity of demand?\n\nAns: Factors affecting the price elasticity of demand are:\n\n• Nature of commodity\n• Availability of substitutes\n• Income level\n• Level of price\n• Number of uses\n• Time period\n• Habits\n\nQuestion 5\n\nThe demand for a good falls to 240 units in response to the rise in price by ₹.2. If the original demand was 300 units at the price of ₹.20, calculate the price elasticity of demand.\n\nNew Quantity (\n$$\\begin{array}{l}_{Q_{1}}\\end{array}$$\n) = 240 Units\n\n#### Rise in Price ($$\\begin{array}{l}\\triangle P\\end{array}$$) = ₹2\n\nOriginal Quantity (Q) = 300 Units\n\n#### Original Price = ₹ 20\n\nChange in Quantity (\n$$\\begin{array}{l}\\triangle Q\\end{array}$$\n) = -60 Units\nNew Price (\n$$\\begin{array}{l}_{P_{1}}\\end{array}$$\n) = ₹ 22\nElasticity of demand\n$$\\begin{array}{l}^{_{E_{d}}}\\end{array}$$\n= ?\n\n$$\\begin{array}{l}Price\\, elasticity\\, of\\, Demand\\, _{E^{_{d}}} = \\frac{\\triangle Q}{\\triangle P}\\times \\frac{P}{Q}=\\frac{-60}{2}\\times \\frac{20}{300}=\\left (- \\right )2\\end{array}$$\n\nSolution:\n\n$$\\begin{array}{l}_{E_{d}}=\\left (-\\right )2 \\left ( Demand\\, is \\, highly\\, elastic \\, as\\, {E_{d}} >\\, 1\\right )\\end{array}$$\n\n### State whether the following statements are true or false.\n\nQuestion 6\n\nA commodity with a large number of close substitutes shows high elasticity of demand.\n\nAns: True\n\nQuestion 7\n\nIn the case of the horizontal straight line demand curve, demand does not change even with the change in price.\n\nAns: False\n\nThe above-provided solutions are considered to be the best solution for ‘Sandeep Garg Microeconomics Class 11 Solutions Chapter 4 Elasticity of Demand’. Stay tuned to BYJU’S to learn more.\n\n Important Topics in Economics:\n\n#### 1 Comment\n\n1. This is the best site for study 😄😃" ]	[ null, "https://www.facebook.com/tr", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8516103,"math_prob":0.9519589,"size":2651,"snap":"2022-05-2022-21","text_gpt3_token_len":651,"char_repetition_ratio":0.16169249,"word_repetition_ratio":0.0093240095,"special_character_ratio":0.23651452,"punctuation_ratio":0.075431034,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9996526,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-05-21T16:19:08Z\",\"WARC-Record-ID\":\"<urn:uuid:afbcc5bd-72fd-439b-b42b-9c38c1fb2357>\",\"Content-Length\":\"677375\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7d0d18e0-7228-49cb-bc2b-e32f6942b4d1>\",\"WARC-Concurrent-To\":\"<urn:uuid:c56e4de3-4db7-44eb-900d-fac88c4aba46>\",\"WARC-IP-Address\":\"162.159.130.41\",\"WARC-Target-URI\":\"https://byjus.com/commerce/sandeep-garg-microeconomics-class-11-solutions-chapter-4-elasticity-of-demand/\",\"WARC-Payload-Digest\":\"sha1:WPANAFULRHXXAOLJIH5Y6W3XKCZUOVR3\",\"WARC-Block-Digest\":\"sha1:QFZPT4RYVDSIA7M4SZWHCBLI6KPNMKNH\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-21/CC-MAIN-2022-21_segments_1652662539131.21_warc_CC-MAIN-20220521143241-20220521173241-00525.warc.gz\"}"}
https://www.mariedduncan.online/noclegi-augustw-domki-letniskowe-mielno-518787	[ "Noclegi Augustów Domki Letniskowe Mielno\n\n### Noclegi Augustów Domki Letniskowe Mielno\n\nTegoż kina brzmi ozdoba obok: sztuki animacjami: przed grupą łowców i'th model and ε is a small positive constant needed to prevent degenerate behavior when S is near 0. The optimal weight update can be found by taking the partial derivative of the coding cost with respect to w i. The coding cost of a 0 is -log p 1. The coding cost of a 1 is -log p 0. The result is that after coding bit y the weights are updated by moving along the cost gradient weight space: w i:= Counts are discounted to favor newer data over older. A pair of counts is represented as a bit history similar to the one described section but with more aggressive discounting. When a bit is observed and the count for the opposite bit is more than 2, the excess is halved. For example if the state is then successive zero bits result the states Logistic Mixing. PAQ7 introduced logistic mixing, which is now favored because it gives better compression. It is more general, since only a probability is needed as input. This allows the use of direct context models and a more flexible arrangement of different model types. It is used the PAQ8, LPAQ, PAQ8HP series and ZPAQ. Given a set of predictions p i that the next bit be a 1, and a set of weights w i, the combined prediction is: p squash) where stretch ln) squash stretch -1 The probability computation is essentially a neural network evaluation taking stretched probabilities as input. Again we find the optimal weight update by taking the partial derivative of the coding cost with respect to the weights. The result is that the update for bit y is simpler than back propagation w i:= w i λ stretch where λ is the learning rate, typically around 0, and is the prediction error. Unlike linear mixing, weights can be negative. Compression can often be improved by using a set of weights selected by a small context, such as a bytewise order 0 context. PAQ and ZPAQ, squash are implemented using lookup tables. PAQ, both output 12 bit fixed point numbers. A stretched probability has a resolution of 2 and range of -8 to 8. Squashed probabilities are multiples of 2. ZPAQ represents stretched probabilities as 12 bits with a resolution of 2 and range -32 to 32. Squashed probabilities are 15 bits as odd multiple of 2. This representation was found to give slightly better compression than PAQ. ZPAQ allows different components to be connected arbitrary ways. All components output a stretched probability, which simplifies the mixer implementation. ZPAQ has 3 types of mixers: Mixer weights PAQ are 16 bit signed values to facilitate vectorized implementation using SSE2 parallel instructions. ZPAQ, 16 bits was found to be inadequate for best compression. Weights were expanded to 20 bit signed values with range -8 to 8 and precision 2. Secondary Symbol Estimation SSE is implemented all PAQ versions beginning with PAQ2. Like ppmonstr, it inputs a prediction and a context and outputs a refined prediction. The prediction is quantized typically to 32 or 64 values on a nonlinear scale with finer resolution near 0 and 1 and sometimes interpolated between the two closest values. On update, one or both values are adjusted to reduce the prediction error, typically by about 1%. A typical place for SSE is to adjust the output of a mixer using a low order context. SSE components be chained series with contexts typically increasing order. Or they be parallel with independent contexts, and the results mixed or averaged together. The table is initialized that the output prediction is equal to the input prediction for all contexts. SSE was introduced to PAQ PAQ2 2003 with 64 quantization levels and no interpolation. Later versions used 32 levels and interpolation with updates to the two nearest values above and below. some versions of PAQ, SSE is also known as APM ZPAQ allows a SSE to be placed anywhere the prediction sequence with any context. Recall that ZPAQ probabilities are stretched by mapping to ln) as a 12 bit fixed point number the range -32 to +32 with resolution 1. The SSE input prediction is clamped and quantized to odd multiple of 1 between -15 and 15. The low 6 bits serve as interpolation weight. For example, if stretch 2, then the two table entries are selected by below=2 and above=3, and the interpolation weight is 0. Then the output prediction is SSE SSEw. Upon update with bit y, the table entry nearest the input prediction is updated by reducing the prediction error by a user specified fraction. There are other possibilities. CCM, a context mixing compressor by Martelock, uses a 2 dimensional SSE taking 2 quantized predictions as input. Indirect SSE ISSE is a technique introduced paq9a Dec. 2007 and is a component ZPAQ. The idea is to use SSE as a direct prediction method rather than to refine existing prediction. However, SSE does not work well with high order contexts because the large table size uses too much memory. generally, a large model with lots of free parameters overfit the training data and have no predictive power for future input. As a general rule, a model should not be larger than the input it is trained on. ISSE does not use a 2-D table. Instead it first maps a context to a bit history as with indirect context map. Then the" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.9175961,"math_prob":0.96260154,"size":5218,"snap":"2023-14-2023-23","text_gpt3_token_len":1152,"char_repetition_ratio":0.12754123,"word_repetition_ratio":0.024309393,"special_character_ratio":0.21100038,"punctuation_ratio":0.09163347,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98953557,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-03-23T11:56:30Z\",\"WARC-Record-ID\":\"<urn:uuid:a23da529-71a2-44fd-b0d5-dd8381ddb041>\",\"Content-Length\":\"10171\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:7a2c5c48-ee89-40a8-bbd9-245fba26368d>\",\"WARC-Concurrent-To\":\"<urn:uuid:58a2f3b2-8c14-423f-b3c0-b226af26f0ef>\",\"WARC-IP-Address\":\"172.67.211.102\",\"WARC-Target-URI\":\"https://www.mariedduncan.online/noclegi-augustw-domki-letniskowe-mielno-518787\",\"WARC-Payload-Digest\":\"sha1:7BHT2KX64DORDMVBU5YXVNC2PJDBYUZN\",\"WARC-Block-Digest\":\"sha1:OKCKNU3HVPRVZLOK7AZVKN4UZM3I5XRC\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296945144.17_warc_CC-MAIN-20230323100829-20230323130829-00141.warc.gz\"}"}
https://www.whenknowingmatters.com/partial-solutions/?doing_wp_cron=1597362503.4345729351043701171875	[ "## Partial Solutions\n\nEducators can distribute an interactive applied learning activity with a partial solution. This is accomplished by creating the activity in CreatorBasic or CreatorAdvanced, loading it into Presenter as a learner would, and building a partial solution. This partially solved activity in Presenter is saved and distributed to learners.\n\nTwo examples of partially solved case scenarios are shown below. Learners would load each into their browser, complete the solution, and submit their finished work, or print out their solution for turning in prior to class or for peer review.\n\nThe third example demonstrates how learners would enter their answers in a paper-based bubble sheet system for automated grading. The entry in the solution with a 1 would correspond to the first multiple choice question on the bubble sheet and so on. In this particular example, answers for 1,2,and 3, would be interchangeable as would answers 4 and 5; 6 and 7; and 8,9, and 10.\n\nAnother option is to have four multiple choice questions that correspond to each grouping. In this example, 1 would remain as 1 corresponding to the first question, 4 would become 2 corresponding to the second question, 6 would become 3 corresponding to the third question, and 8 would become 4 corresponding to the fourth question. Questions 1 and 4 would have multiple choice options that included combinations of three observations, and questions 2 and 3 would have combinations of two.", null, "" ]	[ null, "https://www.whenknowingmatters.com/wp-content/uploads/2016/09/PaperBasedPrintOutFillIn.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.96880317,"math_prob":0.66321236,"size":1445,"snap":"2020-34-2020-40","text_gpt3_token_len":291,"char_repetition_ratio":0.14365025,"word_repetition_ratio":0.0,"special_character_ratio":0.19861592,"punctuation_ratio":0.10861423,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9564872,"pos_list":[0,1,2],"im_url_duplicate_count":[null,3,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-13T23:48:24Z\",\"WARC-Record-ID\":\"<urn:uuid:fe11e6f7-ad68-45f5-afe9-20f8485e5b3e>\",\"Content-Length\":\"36353\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d026038f-9e1e-4e46-b616-190a24f2811a>\",\"WARC-Concurrent-To\":\"<urn:uuid:ad98c0a3-afe5-4da5-bdc6-f5dce9d497f0>\",\"WARC-IP-Address\":\"208.97.149.84\",\"WARC-Target-URI\":\"https://www.whenknowingmatters.com/partial-solutions/?doing_wp_cron=1597362503.4345729351043701171875\",\"WARC-Payload-Digest\":\"sha1:WSRLS3QKRKGTIGNEF77L2BZ43MSWMB5Y\",\"WARC-Block-Digest\":\"sha1:DZWFDKEGF54NBBEXF6AT4USY4KYE2G7V\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439739104.67_warc_CC-MAIN-20200813220643-20200814010643-00201.warc.gz\"}"}
https://chem.libretexts.org/Courses/University_of_California_Davis/UCD_Chem_110A%3A_Physical_Chemistry__I/UCD_Chem_110A%3A_Physical_Chemistry_I_(Larsen)/Lectures/05%3A_Wave_Equations	[ "# 5: Classical Wave Equations and Solutions (Lecture)\n\n•", null, "• Contributed by Delmar Larsen\n• Founder and Director at Libretexts\n\nLecture 4\n\nLast lecture addressed two important aspects: The Bohr atom and the Heisenberg Uncertainty Principle. The Bohr atom was introduced because is was the first successful description of a quantum atom from basic principles (either as a particle or as a wave, both were discussed). From a particle perspective, stable orbits are predicted from the result of opposing forces (Coloumb's force vs. centripetal force). From a wave perspective, stable \"standing waves\" are predicted when the wavelength of the electron is an integer factor of the circumference of the the orbit (otherwise it is not a standing wave and would destructively interfere with itself and disappear). The Bohr atom predicts quantized energies that can be related to Rydberg's phenomenological spectroscopic observation (and decompose his constant $$R$$ into fundamental properties of the universe and matter) via state-to-state transitions (importance for spectroscopy). This is really cool! The problem is that Bohr's theory only applied to hydrogen-like atoms (i..e, atoms or ions with a single electron). So, its quantitative utility for describing quantum chemistry is limited.\n\nHeisenberg's Uncertainty principle is very important and is the realization that trajectories do not exist in quantum mechanics. This is commonly expressed as\n\n$\\Delta{p}\\Delta{x} \\ge \\dfrac{h}{4\\pi} \\nonumber$\n\nand is associated with two properties (in this case, position $$x$$ and momentum $$p$$. As we will show later, not all properties are dictated by Heisenberg's Uncertainly principle. We will also provide a more solid mathematical description of calculating uncertainties (with the standard deviation of a distribution).\n\n## The Heisenberg Uncertainty Principle is responsible for stopping the collapse of the hydrogen atom\n\nAccording to classical mechanics, the electron would simply spiral into the nucleus and the atom would collapse. Quantum mechanics is a different story.", null, "Remember the classical death spiral of an electron around a nucleus. (CC BY; Stephen Lower)\n\nThe total energy of a particle is the sum of kinetic and potential energies\n\n$E= KE + PE$\n\nAs you know, the potential energy of an electron becomes more negative as it moves toward the attractive field of the nucleus; in fact, it approaches negative infinity. However, because the total energy remains constant (a hydrogen atom, sitting peacefully by itself, will neither lose nor acquire energy), the loss in potential energy is compensated for by an increase in the electron's kinetic energy (sometimes referred to in this context as \"confinement\" energy) which determines its momentum and its effective velocity.", null, "Potential energy curve for the Coulombic interactions between a negatively charged electron and a positively charged nucleus.\n\nThe Heisenberg principle says that either the location or the momentum of a quantum particle such as the electron can be known as precisely as desired, but as one of these quantities is specified more precisely, the value of the other becomes increasingly indeterminate.\n\nAs the electron approaches the tiny volume of space occupied by the nucleus, its potential energy dives down toward minus-infinity, and its kinetic energy (momentum and velocity) shoots up toward positive-infinity. This \"battle of the infinities\" cannot be won by either side, so a compromise is reached in which theory tells us that the fall in potential energy is just twice the kinetic energy, and the electron dances at an average distance that corresponds to the Bohr radius.\n\nExample\n\nAn electron is confined to the size of a magnesium atom with a 150 pm radius. What is the minimum uncertainty in its velocity?\n\n$\\Delta{p}\\Delta{x} \\ge \\dfrac{\\hbar}{2} \\nonumber$\n\ncan be written\n\n$\\Delta{p} \\ge \\dfrac{\\hbar}{2 \\Delta{x}} \\nonumber$\n\nand substituting $$\\Delta p=m \\Delta v$$ since the mass is not uncertain.\n\n$\\Delta{v} \\ge \\dfrac{\\hbar}{2\\; m\\; \\Delta{x}} \\nonumber$\n\nthe relevant parameters are\n\nmass of electron $$m=m_e= 9.109383 \\times 10^{-31}\\; kg$$ uncertainty in position: $$\\Delta x=150 \\times 10^{-12} m$$\n\n$\\Delta{v} \\ge \\dfrac{1.0545718 \\times 10^{-34} \\cancel{kg} m^{\\cancel{2}} / s}{(2)\\;( 9.109383 \\times 10^{-31} \\; \\cancel{kg}) \\; (150 \\times 10^{-12} \\; \\cancel{m}) } = 3.9 \\times 10^5\\; m/s \\nonumber$\n\n## Waves Overview\n\nTraveling waves, such as ocean waves or electromagnetic radiation, are waves which “move,” meaning that they have a frequency and are propagated through time and space. In contrast to traveling waves, standing waves, or stationary waves, remain in a constant position with crests and troughs in fixed intervals and specific spots of zero amplitude (node) and maximal amplitude (anti-nodes)", null, "Figure: One-dimensional traveling wave at as a function of time (green and blue curves). Traveling waves propagate energy from one spot to another with a fixed velocity. This is in contrast to a standard wave (red curve) (CC BY-SA 4.0 Internation; Lookangmany via Wikipedia)\n\nDissecting a Wave\n\nMathematically, the most basic wave is the (spatially) one-dimensional sine wave (or harmonic wave or sinusoid) with an amplitude $$u$$ described by the equation:\n\n$u(x,t) = A \\sin (kx - \\omega t + \\phi)$\n\nwhere\n\n• $$A$$ is the maximum amplitude of the wave, maximum distance from the highest point of the disturbance in the medium (the crest) to the equilibrium point during one wave cycle. In the illustration to the right, this is the maximum vertical distance between the baseline and the wave.\n• $$x$$ is the space coordinate\n• $$t$$ is the time coordinate\n• $$k$$ is the wavenumber\n• $$\\nu$$ is the natural frequency\n• $$\\omega$$ is the angular frequency (and $$\\omega= 2\\pi \\nu$$)\n• $$\\phi$$ is the phase (with with respect to what?)", null, "## The Wave Equation\n\nFor a one dimensional wave equation with a fixed length, the function $$u(x,t)$$ describes the position of a string at a specific $$x$$ and $$t$$ value. This leads to the classical wave equation\n\n$\\dfrac {\\partial^2 u}{\\partial x^2} = \\dfrac {1}{v^2} \\cdot \\dfrac {\\partial ^2 u}{\\partial t^2} \\label{W1}$\n\nwhere $$v$$ is the velocity of disturbance along the string. Setting boundary conditions as $$x=0$$, $$u(x=0,t) = 0$$ and $$x = \\ell$$, $$u(x=\\ell , t) = 0$$ allows for this partial differential equation to be solved (to see it in action in the lab see https://youtu.be/BSIw5SgUirg?t=17). Assuming the variables $$x$$ and $$t$$ are independent of each other makes this differential equation easier to solve, as you can use the Separation of Variables technique.\n\nThe separation of variables is common method for solving ordinary and partial differential equations, in which algebra allows one to rewrite an equation so that each of two variables occurs on a different side of the equation.\n\nIn this case, separation of variables \"anzatz\" says that\n\n$u(x,t) = X(x)T(t) \\label{ansatz}$\n\nAnsatz\n\n\"An ansatz is the establishment of the starting equation(s), the theorem(s), or the value(s) describing a mathematical or physical problem or solution. It can take into consideration boundary conditions. After an ansatz has been established (constituting nothing more than an assumption), the equations are solved for the general function of interest (constituting a confirmation of the assumption).\" - Wikipedia", null, "Substituting Equation \\ref{ansatz} into Equation $$\\ref{W1}$$ gives\n\n$T(t) \\cdot \\dfrac {\\partial ^2 X(x)}{\\partial x^2} = \\dfrac {X(x)}{v^2} \\cdot \\dfrac {\\partial ^2 T(t)}{\\partial t^2}$\n\nwhich simplifies to\n\n$\\dfrac {1}{X(x)} \\cdot \\dfrac {\\partial ^2 X(x)}{\\partial x^2} = \\dfrac {1}{T(t) v^2} \\cdot \\dfrac {\\partial ^2 T(t)}{\\partial t^2} = K$\n\nwhere $$K$$ is called the \"separation constant\". By setting each side equal to $$K$$, two 2nd order homogeneous ordinary differential equations are made.\n\n$\\dfrac {d^2 X(x)}{d x^2} - KX(x) = 0 \\label{spatial}$\n\nand\n\n$\\dfrac {d^2 T(t)}{d t^2} - K v^2 T(t) = 0 \\label{time}$\n\nWe are particular interest in this example with specific boundary conditions (the wave has zero amplitude at the ends).\n\n$u(x=0,t)=0$\n\n$u(x=L,t)=0$", null, "The boundary conditions for the wave solution forces it to be a standing wave (vs. a traveling wave)\n\nThis should sound familiar since we did it for the Bohr hydrogen atom (but with the line curved in on itself)\n\n### Solving the Spatial Part\n\nSolving the spatial part (Equation \\ref{spatial}):\n\n$\\dfrac {\\partial ^2 X(x)}{\\partial x^2} - KX(x) = 0 \\label{spatial1}$\n\nEquation \\ref{spatial} is a constant coefficient second order linear ordinary differential equation (ODE), which had general solution of\n\n$X(x) = A\\cdot \\cos \\left(a x \\right) + B\\cdot \\sin \\left(b x\\right) \\label{gen1}$\n\nHowever, these general solutions can be narrowed down by addressing the boundary conditions. Because of the separation of variables above, $$X(x)$$ has specific boundary conditions (that differ from $$T(t)$$):\n\n• $$X(x=0) = 0$$\n• $$X(x=\\ell) = 0$$.\n\nSo there is no way that any cosine function can satisfy the boundary condition (try it if you do not believe me) - hence, $$A=0$$. Moreover, only functions with wavelengths that are integer factors of half the length ($$i.e., n\\ell/2$$) will satisfy the boundary conditions. So Equation \\ref{gen1} simplifies to\n\n$X(x) = B\\cdot \\sin \\left(\\dfrac {n\\pi x}{\\ell}\\right)$\n\nwhere $$\\ell$$ is the length of the string, $$n = 1, 2, 3, ... \\infty$$, and $$B$$ is a constant. By substituting $$X(x)$$ into the partial differential equation for the temporal part (Equation \\ref{spatial1}), the separation constant is easily obtained to be\n\n$K = -\\left(\\dfrac {n\\pi}{\\ell}\\right)^2 \\label{Kequation}$", null, "The first seven $$X(x)$$ solutions of spatial part of the wave equation on a length $$\\ell$$ with two amplitudes (one positive and one negative). (CC BY-SA 3.0 Unported; Adjwilley via Wikipedia).\n\n### Solving the Temporal Part\n\nPlugging the value for $$K$$ from Equation \\ref{Kequation} into the temporal component (Equation \\ref{time}) and then solving to give the general solution (for the temporal behavior of the wave equation):\n\n$T(t) = D\\cos \\left(\\dfrac {n\\pi\\nu}{\\ell} t\\right) + E\\sin \\left(\\dfrac {n\\pi\\nu}{\\ell} t\\right) \\label{gentime}$\n\nwhere $$D$$ and $$E$$ are constants and $$n$$ is an integer ($$\\gt 1$$), which is shared between the spatial and temporal solutions.\n\nUnfortunately, we do not have the boundary conditions like with the spatial solution to simplify the expression of the general temporal solutions in Equation \\ref{gentime}. However, these solutions can be simplified with basic trigonometry identities to\n\n$T_n (t) = A_n \\cos \\left(\\dfrac {n\\pi\\nu}{\\ell} t +\\phi_n\\right) \\label{timetime}$\n\nwhere $$A_n$$ is the maximum displacement of the string (as a function of time), commonly known as amplitude, and $$\\phi_n$$ is the phase and $$n$$ is the number from required to establish the boundary conditions.\n\nTrig Identity\n\nThe evolution of Equation \\ref{gentime} into Equation \\ref{timetime} originates from the sum and difference trigonometric identites. This requires reformulating the $$D$$ and $$E$$ coefficients in Equation \\ref{gentime} in terms of two new constants $$A$$ and $$\\phi$$\n\n$D= A \\cos(\\phi) \\nonumber$\n\nand\n\n$E= A \\sin(\\phi) \\nonumber$\n\nEquation \\ref{gentime} then looks like\n\n$T(t) = A \\cos (\\phi) \\cos \\left(\\dfrac {n\\pi\\nu}{\\ell} t\\right) + A \\sin (\\phi) \\sin \\left(\\dfrac {n\\pi\\nu}{\\ell} t\\right) \\label{gentime3}$\n\nwe use the sum trigonometric identity:\n\n$\\cos (A+B) \\equiv \\cos\\;A ~ \\cos\\;B ~-~ \\sin\\;A ~ \\sin\\;B\\label{eqn:sumcos}$\n\nto rewrite rewrite Equation \\ref{gentime3} into Equation \\ref{timetime}.\n\n## The Total Package: The Spatio-temporal solutions are Standing Waves\n\nRemembering base the Anzatz in this procedure, $$u_n (x,t) = X(x) T(t)$$, and substituting in our determined $$X$$ and $$T$$ functions gives\n\n$u_n = A_n \\cos(\\omega_n t +\\phi_n) \\sin \\left(\\dfrac {n\\pi x}{\\ell}\\right)$\n\nThe first six wave solutions $$u(x,t;n)$$ are standing waves with frequencies based on the number of nodes (0, 1, 2, 3,...) they exhibit (more discussed in the following Section).", null, "The spatio-temporal standing waves solutions to the 1-D wave equation (a string). from Wikipedia.\n\nSince the acceleration of the wave amplitude is proportional to $$\\dfrac{\\partial^2}{\\partial x^2}$$, the greater curvature in the material produces a greater acceleration, i.e., greater changing velocity of the wave and greater frequency of oscillation. As discussed later, the higher frequency waves (i..e, more nodes) are higher energy solutions; this as expected from the experiments discussed in Chapter 1 including Plank's equation $$E=h\\nu$$.\n\nThe higher frequency waves are higher energy solutions.\n\n## Superposition\n\nSince the wave equation is a linear homogeneous differential equation, the total solution can be expressed as a sum of all possible solutions.\n\n\\begin{align} u(x,t) &= \\sum_{n=1}^{\\infty} a_n u_n(x,t) \\\\ &= \\sum_{n=1}^{\\infty} \\left( G_n \\cos (\\omega_n t) + H_n \\sin (\\omega_n t) \\right) \\sin \\left(\\dfrac{n\\pi x}{\\ell}\\right) \\end{align}\n\nThe waveform at a given time is a function of the sources (i.e., external forces, if any, that create or affect the wave) and initial conditions of the system. In many cases (for example, in the classic wave equation), the equation describing the wave is linear. When this is true, the superposition principle can be applied. That means that the net amplitude caused by two or more waves traversing the same space is the sum of the amplitudes which would have been produced by the individual waves separately. For example, two waves traveling towards each other will pass right through each other without any distortion on the other side.", null, "Two waves traveling in opposite directions across the same medium combine linearly. In this animation, both waves have the same wavelength and the sum of amplitudes results in a standing wave. (Public Domain; LucasVB)\n\nThe $$u_n(x,t)$$ solution is called a normal mode. This sort of expansion is ubiquitous in quantum mechanics.\n\nSuperposition in Action\n\nThis java applet is a simulation that demonstrates standing waves on a vibrating string. www.falstad.com/loadedstring/\n\nEverything above is a classical picture of wave, not specifically quantum, although they all apply. We will introduce quantum tomorrow and the waves will be wavefunctions. Since the Schrödinger equation (that is the quantum wave equation) is linear, the behavior of the original wave function can be computed through the superposition principle.\n\nExpansions are important for many aspects of quantum mechanics." ]	[ null, "https://chem.libretexts.org/@api/deki/files/123439/Larsen.jpg", null, "https://chem.libretexts.org/@api/deki/files/122911/Figure_1.png", null, "https://chem.libretexts.org/@api/deki/files/122970/img130.png", null, "https://chem.libretexts.org/@api/deki/files/241029/ezgif-4-085bec536432.gif", null, "https://chem.libretexts.org/@api/deki/files/54901/2000px-Wave_Sinusoidal_Cosine_wave_sine_Blue.svg.png", null, "https://chem.libretexts.org/@api/deki/files/347909/6a4c0669d2ff5e7f609475715fc54c30.jpg", null, "https://chem.libretexts.org/@api/deki/files/54912/image233.gif", null, "https://chem.libretexts.org/@api/deki/files/241290/Figure_2.4.1.png", null, "https://chem.libretexts.org/@api/deki/files/54788/Standing_waves_on_a_string.gif", null, "https://chem.libretexts.org/@api/deki/files/85638/Standing_wave_2.gif", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8646508,"math_prob":0.9996674,"size":13451,"snap":"2021-31-2021-39","text_gpt3_token_len":3487,"char_repetition_ratio":0.1254555,"word_repetition_ratio":0.0059671807,"special_character_ratio":0.26258272,"punctuation_ratio":0.08495648,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9999548,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],"im_url_duplicate_count":[null,null,null,5,null,5,null,9,null,null,null,2,null,5,null,4,null,null,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-07-26T00:51:04Z\",\"WARC-Record-ID\":\"<urn:uuid:28baf722-2423-4e24-9a68-bc116e48dbbd>\",\"Content-Length\":\"116940\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:910c76b7-499c-43ea-a5db-8b01a1afe02f>\",\"WARC-Concurrent-To\":\"<urn:uuid:642e588a-fd5f-4ca0-bd5c-b750cc70edc1>\",\"WARC-IP-Address\":\"13.249.38.103\",\"WARC-Target-URI\":\"https://chem.libretexts.org/Courses/University_of_California_Davis/UCD_Chem_110A%3A_Physical_Chemistry__I/UCD_Chem_110A%3A_Physical_Chemistry_I_(Larsen)/Lectures/05%3A_Wave_Equations\",\"WARC-Payload-Digest\":\"sha1:ALOPEITW4M7WS755VMCT2WYYCAXXGU4O\",\"WARC-Block-Digest\":\"sha1:FV3MTLQ27NFTEEDMNZYY4BN5N7HEYJNB\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-31/CC-MAIN-2021-31_segments_1627046151972.40_warc_CC-MAIN-20210726000859-20210726030859-00527.warc.gz\"}"}
https://tutorme.com/tutors/12214/interview/	[ "TutorMe homepage\nSubjects\nPRICING\nCOURSES\nSIGN IN\nStart Free Trial\nCorbin P.\nUndergraduate at The University of Rhode Island\nTutor Satisfaction Guarantee\nPre-Algebra\nTutorMe\nQuestion:\n\nSimplify the exponents: x^6+x^3\n\nCorbin P.\nAnswer:\n\nSo if exponents have the same base in an addition problem you can add the exponents together. x^6+x^3= x^9\n\nBasic Math\nTutorMe\nQuestion:\n\nAdd the fractions: (2/3) + (1/9)\n\nCorbin P.\nAnswer:\n\nTo start find you need to set the denominator to the same number: (2/3) * 3= (3/9) The simply add the numerators: (3/9)+(1/9)= (4/9)\n\nAlgebra\nTutorMe\nQuestion:\n\nPlease find the X intercept of the following equation. 3x-8y=13\n\nCorbin P.\nAnswer:\n\nTo find the answer you can start by setting Y equal to 0. 3x-0=13 Then solve for X. x= 13/3 So the X intercept is: (13/3,0)\n\nSend a message explaining your\nneeds and Corbin will reply soon.\nContact Corbin\nReady now? Request a lesson.\nStart Session\nFAQs\nWhat is a lesson?\nA lesson is virtual lesson space on our platform where you and a tutor can communicate. You'll have the option to communicate using video/audio as well as text chat. You can also upload documents, edit papers in real time and use our cutting-edge virtual whiteboard.\nHow do I begin a lesson?\nIf the tutor is currently online, you can click the \"Start Session\" button above. If they are offline, you can always send them a message to schedule a lesson.\nWho are TutorMe tutors?\nMany of our tutors are current college students or recent graduates of top-tier universities like MIT, Harvard and USC. TutorMe has thousands of top-quality tutors available to work with you." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.84264433,"math_prob":0.50236195,"size":492,"snap":"2019-13-2019-22","text_gpt3_token_len":173,"char_repetition_ratio":0.12704918,"word_repetition_ratio":0.0,"special_character_ratio":0.3597561,"punctuation_ratio":0.084033616,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99120325,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-05-22T17:24:50Z\",\"WARC-Record-ID\":\"<urn:uuid:23b221f5-1b5a-42ab-96d2-829273525933>\",\"Content-Length\":\"143865\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:cfdb67ba-2f79-417f-934e-ff111c9a33f0>\",\"WARC-Concurrent-To\":\"<urn:uuid:fd1a748f-a0a2-493e-a9d2-ee523c325f72>\",\"WARC-IP-Address\":\"99.84.181.108\",\"WARC-Target-URI\":\"https://tutorme.com/tutors/12214/interview/\",\"WARC-Payload-Digest\":\"sha1:OIRHY54GJKQEOG5Z6YN7VXP5XWM7SYII\",\"WARC-Block-Digest\":\"sha1:ZX7EHEG7RFXXGMY5CYCPOZ4RIXNLFLZW\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-22/CC-MAIN-2019-22_segments_1558232256887.36_warc_CC-MAIN-20190522163302-20190522185302-00077.warc.gz\"}"}
https://www.techsource-asia.com/userstories-buildingiq	[ "## BuildingIQ Develops Proactive Algorithms for HVAC Energy Optimization in Large-Scale Buildings", null, "“MATLAB has helped accelerate our R&D and deployment with its robust numerical algorithms, extensive visualization and analytics tools, reliable optimization routines, support for object-oriented programming, and ability to run in the cloud with our production Java applications.”\n\n- Borislav Savkovic, BuildingIQ\n\nBuildingIQ has developed Predictive Energy Optimization™ (PEO), a cloud-based software platform that reduces HVAC energy consumption by 10–25% during normal operation. PEO was developed in cooperation with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia’s national science agency. Its advanced algorithms and machine learning methods, implemented in MATLAB®, continuously optimize HVAC performance based on near-term weather forecasts and energy cost signals.\n\n“CSIRO used MATLAB to develop the initial technology. We continue to use MATLAB because it is the best tool available for prototyping algorithms and performing advanced mathematical calculations,” says Borislav Savkovic, lead data scientist at BuildingIQ. “MATLAB enabled us to transition our prototype algorithms directly into production-level algorithms that deal reliably with real-world noise and uncertainty.”\n\n## Challenge\n\nBuildingIQ needed to develop algorithms that could continuously process gigabytes of information from a variety of sources, including power meters, thermometers, and HVAC pressure sensors, as well as weather and energy cost data. A single building often produces billions of data points, and the scientists and engineers needed tools for efficiently filtering, processing, and visualizing this data.\n\nTo run their optimization algorithms, the scientists and engineers had to create an accurate mathematical model of a building’s thermal and power dynamics. The algorithms would use this calculated model to run constrained optimizations that maintained occupant comfort while minimizing energy costs.\n\nBuildingIQ needed a way to rapidly develop mathematical models, test optimization and machine learning approaches, prototype algorithms, and deploy them into its production IT environment.", null, "## Solution\n\nBuildingIQ used MATLAB to speed up the development and deployment of its predictive energy optimization algorithms. The optimization workflow begins in MATLAB, where BuildingIQ engineers import and visualize 3 to 12 months of temperature, pressure, and power data comprising billions of data points. They use Statistics and Machine Learning Toolbox™ to detect spikes and gaps, and remove noise produced by sensor failures and other sources using filtering functions in Signal Processing Toolbox™. BuildingIQ engineers fitted a mathematical model developed in MATLAB to the denoised data using least squares fitting functions from Optimization Toolbox™. This measurement and verification (M&V) model correlates ambient temperature and humidity with power consumed by the HVAC system.\n\nAs part of the modeling process, they use SVM regression, Gaussian mixture models, and k-means clustering machine learning algorithms from Statistics and Machine Learning Toolbox to segment the data and determine the relative contributions of gas, electric, steam, and solar power to heating and cooling processes.\n\nThe team builds a PEO model in MATLAB that captures the effect of the HVAC system and ambient conditions on internal temperatures in each zone, as well as on the total power consumption for the building. Using Control System Toolbox™ they analyze HVAC control system poles and zeros to estimate overall power consumption and determine how quickly each zone is likely to converge to its set point.\n\nBuildingIQ engineers use Optimization Toolbox and the PEO model to run multi-objective optimizations with hundreds of parameters, as well as nonlinear cost functions and constraints to continuously optimize energy efficiency in real time. These optimizations take into account projected weather and energy prices over the next 12 hours, and identify optimal HVAC set points. In operation, Java® software in the cloud invokes the MATLAB optimization algorithms periodically throughout the day.\n\nEach day, BuildingIQ calculates baseline energy cost from the M&V model representing what the client would have paid for HVAC energy without the BuildingIQ PEO platform. Savings range from 10% to 25%.\n\n## \n\n• Gigabytes of data analyzed and visualized. “MATLAB makes it easy to process and visualize the big data sets we work with,” says Savkovic. “We create scatter plots, 2D and 3D graphs, and other charts that display in a meaningful way how our system is performing.”\n\n• Algorithm development speed increased tenfold. “Developing algorithms in MATLAB is 10 times faster and more robust than developing in Java,” says Savkovic. “We need to filter our data, look at poles and zeroes, run nonlinear optimizations, and perform numerous other tasks. In MATLAB, those capabilities are all integrated, robust, and commercially validated.”\n\n• Best algorithmic approaches quickly identified. “With MATLAB we can rapidly test new approaches to find the one that works best for our data,” says Savkovic. “For example, we tested several optimization approaches before selecting sequential quadratic programming, and we tried several clustering machine learning algorithms. It’s a huge advantage to explore different methods so quickly.”" ]	[ null, "https://static.wixstatic.com/media/19e9dd_d318809bf832405b823fa7b98ec0bc3a~mv2.jpg/v1/fill/w_503,h_283,al_c,q_80,usm_0.66_1.00_0.01/BuildingiQ.jpg", null, "https://static.wixstatic.com/media/19e9dd_0e67235d6aeb427e8cfc5c71e4d99f38~mv2.png/v1/fill/w_662,h_179,al_c,lg_1/Validation%20-%20BuildingIq.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8877737,"math_prob":0.8590314,"size":6004,"snap":"2021-31-2021-39","text_gpt3_token_len":1129,"char_repetition_ratio":0.1315,"word_repetition_ratio":0.078977935,"special_character_ratio":0.17288475,"punctuation_ratio":0.09053498,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9520715,"pos_list":[0,1,2,3,4],"im_url_duplicate_count":[null,1,null,1,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-07-30T13:47:54Z\",\"WARC-Record-ID\":\"<urn:uuid:5b2f0cab-567e-49d7-8139-7650974d15eb>\",\"Content-Length\":\"760134\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:d6d9bd62-e79e-4783-8bbd-a98b2172aaf7>\",\"WARC-Concurrent-To\":\"<urn:uuid:97aca20d-4a37-4ca7-8c3c-68f3812f5db5>\",\"WARC-IP-Address\":\"185.230.60.177\",\"WARC-Target-URI\":\"https://www.techsource-asia.com/userstories-buildingiq\",\"WARC-Payload-Digest\":\"sha1:RG6PFJVLZ2UG7X4M7HUSBQKKI2XCIQDT\",\"WARC-Block-Digest\":\"sha1:TPO73X7QQXYFOKCNZ2SZTLJGACHA4KPG\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-31/CC-MAIN-2021-31_segments_1627046153966.60_warc_CC-MAIN-20210730122926-20210730152926-00350.warc.gz\"}"}
https://mathematica.stackexchange.com/questions/3186/ad-hoc-graphics-primitives-like-objects	[ "# Ad hoc graphics primitives-like objects\n\nSphere is one of the three-dimensional graphics primitives available in Mathematica and can be easily used to created very useful images. For instance, in the figure below I created three images of an ellipsoidal object that is lit from a fixed direction and it is then just rotated around the z-axis.\n\nGraphicsRow[\nTable[\nGraphics3D[\nRotate[Scale[{GrayLevel[.7], Sphere[]}, {1, 1.5, 1}, {0, 0, 0}],\ni Degree, {0, 0, 1}], PlotRange -> {{-2, 2}, {-2, 2}, {-2, 2}},\nAspectRatio -> 1, Background -> Black, Boxed -> False,\nViewPoint -> Front, SphericalRegion -> True,\nLighting -> {{\"Directional\", White, ImageScaled[{0, 0, 1}]}}\n], {i, {0, 45, 90}}]]", null, "Suppose that instead of using the ellipsoidal object I would like to use an object like this bump:\n\nPlot3D[Exp[-(x^2 + y^2)], {x, -2, 2}, {y, -2, 2}]", null, "Is there a way to create a \"graphics primitive\" object of the bump, so as to just use it instead of Sphere in the above example?\n\nI suppose there should be a way to extract all the polygons specifying the shape of the bump, but I couldn't find a way to do it. Any other approach is also more than welcome.\n\nThe result of Plot3D and related functions is something of the form Graphics3D[primitives, options], so to extract the graphics primitives you can simply take the first part of the plot. These can then be manipulated similar to Sphere[] in your example, e.g.\n\nplot = Plot3D[Exp[-(x^2 + y^2)], {x, -2, 2}, {y, -2, 2}][];\n\nGraphicsRow[\nTable[Graphics3D[\nRotate[Scale[{GrayLevel[.7], plot}, {1, 1.5, 1}, {0, 0, 0}],\ni Degree, {0, 0, 1}], PlotRange -> {{-2, 2}, {-2, 2}, {-2, 2}},\nAspectRatio -> 1, Background -> Black, Boxed -> False,\nViewPoint -> Front, SphericalRegion -> True,\nLighting -> {{\"Directional\", White,\nImageScaled[{0, 0, 1}]}}], {i, {0, 45, 90}}]]", null, "• Nice use of [] to extract the GraphicsComplex from the plot! Mar 19, 2012 at 14:22\n• Or slightly more transparently: Cases[(* stuff *), _GraphicsComplex, Infinity] // First. Mar 19, 2012 at 15:21\n• Or if you are baffled by GraphicsComplex, try Cases[Normal[plot], _Polygon, Infinity] which will return the (many many) constituting polygons. Mar 19, 2012 at 16:34\n\nI think what you're looking for is BSplineSurface. For your given example, try:\n\ncpts = Table[{x, y, Exp[-(x^2 + y^2)]}, {x, -2, 2, 0.1}, {y, -2, 2,\n0.1}];\n\nGraphics3D[BSplineSurface[cpts], Boxed -> False]\n\n\nWhich gives:", null, "" ]	[ null, "https://i.stack.imgur.com/qSTdb.png", null, "https://i.stack.imgur.com/Hjfn5.png", null, "https://i.stack.imgur.com/GSjIJ.png", null, "https://i.stack.imgur.com/koYGe.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8525725,"math_prob":0.9577417,"size":1099,"snap":"2023-14-2023-23","text_gpt3_token_len":321,"char_repetition_ratio":0.09954338,"word_repetition_ratio":0.0,"special_character_ratio":0.3212011,"punctuation_ratio":0.2,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99054205,"pos_list":[0,1,2,3,4,5,6,7,8],"im_url_duplicate_count":[null,5,null,5,null,5,null,5,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-06-09T05:10:37Z\",\"WARC-Record-ID\":\"<urn:uuid:c0dbba23-6d24-4641-bab6-f35ce50ac760>\",\"Content-Length\":\"165923\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:94c9b177-8cae-41b5-8357-487931529dcb>\",\"WARC-Concurrent-To\":\"<urn:uuid:a0447d5e-7626-48dc-8534-9cb64de49d2a>\",\"WARC-IP-Address\":\"151.101.193.69\",\"WARC-Target-URI\":\"https://mathematica.stackexchange.com/questions/3186/ad-hoc-graphics-primitives-like-objects\",\"WARC-Payload-Digest\":\"sha1:A627QK6DPVUKZLTBNSG4EG3BK3HU6B3K\",\"WARC-Block-Digest\":\"sha1:FRLMIE7P6NSZRWBIED3NGKDZL4ADCR7L\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-23/CC-MAIN-2023-23_segments_1685224655247.75_warc_CC-MAIN-20230609032325-20230609062325-00114.warc.gz\"}"}
https://ans.disi.unitn.it/redmine/projects/community-newtork-emulator/repository/mininet/revisions/f4d9e05d05631cf2671822f99108374cfcbd8b41/entry/examples/linearBandwidth.py	[ "Statistics\n\| Branch: \| Tag: \| Revision:\n\n## mininet / examples / linearBandwidth.py @ f4d9e05d\n\n 1 ```#!/usr/bin/python ``` ```\"\"\" ``` ```Test bandwidth on linear networks of varying size, using both ``` ```the kernel and user datapaths. ``` ``` ``` ```Each network looks like: ``` ``` ``` ```h0 <-> s0 <-> s1 .. sN <-> h1 ``` ``` ``` ```Note: by default, the reference controller only supports 16 ``` ```switches, so this test WILL NOT WORK unless you have recompiled ``` ```your controller to support a 100 switches (or more.) ``` ``` ``` ```\"\"\" ``` ``` ``` ```from mininet import init, LinearNet, iperfTest ``` ```def linearBandwidthTest(): ``` ``` datapaths = [ 'kernel', 'user' ] ``` ``` switchCounts = [ 1, 20, 40, 60, 80, 100 ] ``` ``` results = {} ``` ``` for datapath in datapaths: ``` ``` k = datapath == 'kernel' ``` ``` results[ datapath ] = [] ``` ``` for switchCount in switchCounts: ``` ``` print \"* Creating linear network of size\", switchCount ``` ``` network = LinearNet( switchCount, k) ``` ``` bandwidth = network.run( iperfTest ) ``` ``` results[ datapath ] += [ ( switchCount, bandwidth ) ] ``` ``` ``` ``` for datapath in datapaths: ``` ``` print ``` ``` print \"* Linear network results for\", datapath, \"datapath:\" ``` ``` print ``` ``` result = results[ datapath ] ``` ``` print \"SwitchCount\\tiPerf results\" ``` ``` for switchCount, bandwidth in result: ``` ``` print switchCount, '\\t\\t', ``` ``` print bandwidth[ 0 ], 'server, ', bandwidth[ 1 ], 'client' ``` ``` print ``` ``` print ``` ``` ``` ```if __name__ == '__main__': ``` ``` init() ``` ``` print \"*** Running linearBandwidthTest\" ``` ``` linearBandwidthTest() ``` ``` exit( 1 ) ``` ``` ```" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.52241004,"math_prob":0.82669777,"size":1615,"snap":"2021-43-2021-49","text_gpt3_token_len":514,"char_repetition_ratio":0.17690875,"word_repetition_ratio":0.0065789474,"special_character_ratio":0.43219814,"punctuation_ratio":0.1532567,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99608713,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-15T21:47:35Z\",\"WARC-Record-ID\":\"<urn:uuid:b84f8e08-534c-420c-bc98-a80575a15c27>\",\"Content-Length\":\"22595\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:0f7193fe-92f5-4997-9e58-aecc0882386d>\",\"WARC-Concurrent-To\":\"<urn:uuid:da611b2a-a1c6-4098-89fb-38d7eb1c72b1>\",\"WARC-IP-Address\":\"193.205.194.89\",\"WARC-Target-URI\":\"https://ans.disi.unitn.it/redmine/projects/community-newtork-emulator/repository/mininet/revisions/f4d9e05d05631cf2671822f99108374cfcbd8b41/entry/examples/linearBandwidth.py\",\"WARC-Payload-Digest\":\"sha1:OP4V7OM4GVDMICILTIDXBP5OD2XV2ARK\",\"WARC-Block-Digest\":\"sha1:QQZFKSJNBUWAVMXZZ3ENIQ23GYQE6W5U\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323583083.92_warc_CC-MAIN-20211015192439-20211015222439-00275.warc.gz\"}"}
https://stats.stackexchange.com/questions/491625/meaning-of-the-weight-argument-in-glmer-and-lmer	[ "# Meaning of the weight argument in glmer and lmer\n\nI have been looking into how to use the weight argument of glmer/lmer to represent \"frequency\" weights. I was comparing model estimations with an expanded dataset, with the frequency weights inputted directly to the weight argument, and with the weights scaled as in Method A in Carle 20091 (i.e. scaled such that their sum matches the number of observations). I have found a puzzling difference in how they affect the results.\n\nSpecifically:\n\n• lmer gives identical results for scaled and unscaled weights, but different results with the expanded dataset\n• glmer gives identical results with the unscaled weights as with the expanded dataset, but different results with the scaled weights\n\nCould anybody clarify what is the reason for the difference?\n\nBackgroud\n\nI want to compare performance of two groups on a cognitive psychology task. The groups have been matched by a collaborator according to relevant covariates (e.g. socioeconomic status) and as a result few participants from the control group have a frequency weight of 2, indicating that they should be counted twice in the analyses in order for the groups to be matched on all the covariates. I would like to use multilevel models, and I am trying to see if I can use the frequency weight with the weight argument of lme4 (Note: I am not sure of whether frequency weight is the correct term here; perhaps sampling weight is more appropriate). The dependent variable is binomial, so we'd need to use a GLMM.\n\nToy example:\n\nGenerate some data\n\n# covariance matrix\nsigma = matrix(c(1, 0.7, 0.7, 1), ncol = 2)\n\n# simulate data\nset.seed(4321)\ndf = mvrnorm(n = 100, mu = c(0,0), Sigma = sigma)\n\n# Simulate clustering and calculate weights\ndf = data.frame(df)\nnames(df) = c(\"Y\", \"X\")\ndf$cluster = rep(1:10, each = 10) df = within(df, { Y = Y + cluster/10 X = X + cluster/10 weights = rep(1:2, each = 50) scaled_weights = weights*2/3 }) #data set with double weighted observations entered twice df2 = rbind(df, df[51:100,]) Effects of weights in lmer. Here the models with weights gives the same results, regardless of the scaling, and the model with the expanded dataset gives different estimates. # Models m.weights = lmer(Y ~ X + (1 \| cluster), df, weights = weights) # weights m.double = lmer(Y ~ X + (1 \| cluster), df2) # expanded dataset m.scaled = lmer(Y ~ X + (1 \| cluster), df, weights = scaled_weights) #scaled weights round(summary(m.weights)$coef,digits=4)\n# Estimate Std. Error t value\n# (Intercept) 0.2498 0.0904 2.7645\n# X 0.6908 0.0658 10.4928\nround(summary(m.scaled)$coef,digits=4) # SAME AS m.weights # Estimate Std. Error t value # (Intercept) 0.2498 0.0904 2.7645 # X 0.6908 0.0658 10.4928 round(summary(m.double)$coef,digits=4) # DIFFERENT\n# Estimate Std. Error t value\n# (Intercept) 0.2445 0.0842 2.9029\n# X 0.6847 0.0538 12.7332\n\n\nEffects of weights in glmer\n\n# discretize dependent variable in 2 levels\ndf$$dY <- ifelse(df$$Y>0.8,1,0)\ndf2$$dY <- ifelse(df2$$Y>0.8,1,0)\n\nm2.weights = glmer(dY ~ X + (1 \| cluster), df, weights = weights, family =binomial) # weights (unscaled)\nm2.double = glmer(dY ~ X + (1 \| cluster), df2, family =binomial) # expanded dataset\nm2.scaled = glmer(dY ~ X + (1 \| cluster), df, weights = scaled_weights, family =binomial) # scaled weights\n# Warning message:\n# In eval(family$initialize, rho) : non-integer #successes in a binomial glm! Note that the model with scaled weights give a warning, because in glm(er) the weights should correspond to the number of trials when the dependent variable is the proportion of successes. However as I understand them the weights are taken into account in the log-likelihood as $$\\log\\mathcal{L}(\\boldsymbol{\\theta}) = \\sum_{i = 1}^{n} w_i \\log \\left[ p(y_i \| \\boldsymbol{x}_i,\\boldsymbol{\\theta})\\right]$$ where $$w_i$$ is the weight. If that's correct, each observation $$i$$ contributes $$w_i$$ times its log-likelihood to the total log-likelihood, which should be the same as saying that each $$i$$ represents $$w_i$$ observations. (Since this is what I would like to express with the weights, I thought I could use this argument for my purposes). Furthermore, based on this I would expect to find that the model with the unscaled weight and that with the expanded dataset to give similar or identical results, and indeed that is what I find - in this case is the model with scaled weights that differs from the other two. round(summary(m2.weights)$coef,digits=4)\n# Estimate Std. Error z value Pr(>\|z\|)\n# (Intercept) -1.3028 0.3902 -3.3390 8e-04\n# X 1.5741 0.2955 5.3263 0e+00\nround(summary(m2.scaled)$coef,digits=4) # DIFFERENT # Estimate Std. Error z value Pr(>\|z\|) # (Intercept) -1.2620 0.4183 -3.0167 0.0026 # X 1.5579 0.3531 4.4114 0.0000 round(summary(m2.double)$coef,digits=4) # SAME as m.weights\n# Estimate Std. Error z value Pr(>\|z\|)\n# (Intercept) -1.3028 0.3902 -3.3390 8e-04\n# X 1.5741 0.2955 5.3263 0e+00\n\n\n1 Carle, A. C. (2009). Fitting multilevel models in complex survey data with design weights: Recommendations. BMC Medical Research Methodology, 9 (1), 1–13." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.86240804,"math_prob":0.9880582,"size":4988,"snap":"2022-05-2022-21","text_gpt3_token_len":1474,"char_repetition_ratio":0.13242376,"word_repetition_ratio":0.13762626,"special_character_ratio":0.31335205,"punctuation_ratio":0.15255906,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99893624,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-05-16T05:27:06Z\",\"WARC-Record-ID\":\"<urn:uuid:e0df5b27-bd6a-4b16-8ae6-070cd45162bb>\",\"Content-Length\":\"215254\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:771e7b13-16b9-4a36-86f1-2c01963d4602>\",\"WARC-Concurrent-To\":\"<urn:uuid:2ac9bfe0-f8f8-41fa-a365-ee4ed98c926c>\",\"WARC-IP-Address\":\"151.101.129.69\",\"WARC-Target-URI\":\"https://stats.stackexchange.com/questions/491625/meaning-of-the-weight-argument-in-glmer-and-lmer\",\"WARC-Payload-Digest\":\"sha1:FBJK5KM4QDEC5QIKBZLLOGL7GK55RHD3\",\"WARC-Block-Digest\":\"sha1:SICIAXXB6KA7ZC2T5MO7RPJL7HYT27X4\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-21/CC-MAIN-2022-21_segments_1652662509990.19_warc_CC-MAIN-20220516041337-20220516071337-00407.warc.gz\"}"}
https://godstamps.blogspot.com/2015/10/unity-unityengineevents.html	[ "## 2015年10月25日星期日\n\n### Unity：使用 UnityEngine.Events 讓程式更靈活、穩定", null, "public 的變數欄位會出現在 Inspector 視窗，可供編輯。", null, "有 SerializeField 的 private 變數欄位也會出現在 Inspector 視窗。", null, "UnityEvent 型別的變數欄位，在 Inspector 視窗會出現事件欄位。\n這個 UnityEvent 欄位在編輯器上的編輯相當彈性，當目標 Component 裡面含有使用 public 宣告的屬性（Property）或方法（Method），並且傳入值的型別為 bool、int、float、string 其中一種的話，就能直接在這裡選擇並提供傳入的值，而且可以設置多個不同型別的目標，並在之後程式執行時直接呼叫執行，另外，如果 Method 並沒有宣告傳入參數的話，在此也可以選擇設置，如果是宣告兩個以上的參數，在這邊的選單就不會出現了。\n\n[System.Serializable]\npublic class PassString : UnityEvent<string>{}\n\n[System.Serializable]\npublic class PassColor : UnityEvent<Color>{}\n\n## 1. Simple Computer\n\n• 點擊運算功能按鈕，會依照計算種類去改變運算符號的文字。\n• 點擊運算功能按鈕之後，在 UI 顯示計算結果文字。\n\nusing UnityEngine.Events;\n\n[System.Serializable]\npublic class PassString : UnityEvent<string>{}\n\nprivate float _value1;\nprivate float _value2;\n\n[SerializeField]\n[SerializeField]\nprivate PassString onSubtract;\n[SerializeField]\nprivate PassString onMultiply;\n[SerializeField]\nprivate PassString onDivide;\n\npublic string value1{\nset{\nfloat.TryParse(value , out this._value1);\n}\n}\n\npublic string value2{\nset{\nfloat.TryParse(value , out this._value2);\n}\n}\n\n}\n\npublic void Subtract(){\n\nthis.onSubtract.Invoke((this._value1 - this._value2).ToString());\n}\n\npublic void Multiply(){\n\nthis.onMultiply.Invoke((this._value1 * this._value2).ToString());\n}\n\npublic void Divide(){\n\nif(this._value2 == 0) return;\n\nthis.onDivide.Invoke((this._value1 / this._value2).ToString());\n}", null, "MyConputer 出現加、減、乘、除的事件欄位。", null, "Value1 Field 輸入的字串傳給 MyComputer 的 value1", null, "Value2 Field 輸入的字串傳給 MyComputer 的 value2", null, "Button + 的 On Click 事件執行 MyComputer 的 Add()", null, "Button - 的 On Click 事件執行 MyComputer 的 Subtract()", null, "Button x 的 On Click 事件執行 MyComputer 的 Multiply()", null, "Button / 的 On Click 事件執行 MyComputer 的 Divide()", null, "每個計算功能事件讓 UI 變更運算符號以及顯示計算結果", null, "計算結果的畫面", null, "計算結果之後關閉按鈕。", null, "計算過的按鈕都關閉了。\n\n[SerializeField]\nprivate UnityEvent onResetStatus;\n\npublic void ResetStatus(){\n\nthis.onResetStatus.Invoke();\n}", null, "狀態重置時，再次啟用按鈕。", null, "End Edit 事件指定執行 MyComputer 的 ResetStatus()。", null, "更改為先執行狀態重置之後，才去執行其他行為。\n\nusing UnityEngine;\nusing UnityEngine.Events;\n\npublic class MyComputer : MonoBehaviour {\n\nprivate float _value1;\nprivate float _value2;\n\n[SerializeField]\n[SerializeField]\nprivate PassString onSubtract;\n[SerializeField]\nprivate PassString onMultiply;\n[SerializeField]\nprivate PassString onDivide;\n[SerializeField]\nprivate UnityEvent onResetStatus;\n\npublic string value1{\nset{\nfloat.TryParse(value , out this._value1);\n}\n}\n\npublic string value2{\nset{\nfloat.TryParse(value , out this._value2);\n}\n}\n\n}\n\npublic void Subtract(){\n\nthis.onSubtract.Invoke((this._value1 - this._value2).ToString());\n}\n\npublic void Multiply(){\n\nthis.onMultiply.Invoke((this._value1 * this._value2).ToString());\n}\n\npublic void Divide(){\nif(this._value2 == 0) return;\nthis.onDivide.Invoke((this._value1 / this._value2).ToString());\n}\n\npublic void ResetStatus(){\n\nthis.onResetStatus.Invoke();\n}\n}\n\n## 2. Sphere Control", null, "原生物件球體的 Componet。\n\n• 球體可以被點擊觸發。\n• 球體可以彈跳起來。\n• 球體可以變色。\n\nusing UnityEngine;\nusing UnityEngine.Events;\n\npublic class SphereTouch : MonoBehaviour {\n\n[SerializeField]\nprivate UnityEvent onTouch;\n\npublic void DoTouch(){\n\nthis.onTouch.Invoke();\n}\n\nvoid OnMouseDown(){\n\nthis.DoTouch();\n}\n}\n\n[SerializeField]\nprivate float hight = 1;\n[SerializeField]\nprivate float speed = 5;\n\nprivate enum Status{\n\nNone,\nMoving\n}\n\nprivate Status _status = Status.None;\n\nprivate IEnumerator Move(Vector3 source , Vector3 target){\n\nfloat t = 0;\n\nwhile(t < 1){\n\ntransform.position = Vector3.Lerp(source , target , t);\nt += Time.deltaTime * this.speed;\n\nyield return null;\n}\n\ntransform.position = target;\n}\n\nVector3.Lerp 的 t 是介於 0 到 1 的值，我們可以把它當作是起點到終點的進度位置來看待，0 是起點，1 是終點。因為實際執行時每次刷新畫面的時間都不一樣，所以，我們不能讓 t 隨著時間的推移增加固定的值，而應該要為我們預計增加的值（即是速度）乘上 Time.deltaTime，於是，我們在這裡透過 yield return null 讓 while 迴圈每經過一個 frame 才執行一次，當 t 超過 1 的時候，表示已經到達終點，即可結束迴圈。\n\nprivate IEnumerator DoJump(){\n\nthis._status = Status.Moving;\n\nVector3 source = transform.position;\nVector3 target = source;\ntarget.y += this.hight;\n\nyield return StartCoroutine(this.Move(source , target));\nyield return StartCoroutine(this.Move(target , source));\n\nthis._status = Status.None;\n}\n\npublic void Jump(){\n\nif(this._status == Status.None) StartCoroutine(this.DoJump());\n}\n\nusing UnityEngine;\nusing System.Collections;\n\npublic class SphereJump : MonoBehaviour {\n\nprivate enum Status{\n\nNone,\nMoving\n}\n\n[SerializeField]\nprivate float hight = 1;\n[SerializeField]\nprivate float speed = 5;\n\nprivate Status _status = Status.None;\n\npublic void Jump(){\n\nif(this._status == Status.None) StartCoroutine(this.DoJump());\n}\n\nprivate IEnumerator Move(Vector3 source , Vector3 target){\n\nfloat t = 0;\n\nwhile(t < 1){\n\ntransform.position = Vector3.Lerp(source , target , t);\nt += Time.deltaTime * this.speed;\n\nyield return null;\n}\n\ntransform.position = target;\n}\n\nprivate IEnumerator DoJump(){\n\nthis._status = Status.Moving;\n\nVector3 source = transform.position;\nVector3 target = source;\ntarget.y += this.hight;\n\nyield return StartCoroutine(this.Move(source , target));\nyield return StartCoroutine(this.Move(target , source));\n\nthis._status = Status.None;\n}\n}\n\n[System.Serializable]\npublic class PassColor : UnityEvent<Color>{}\n\nprivate Material _material;\nprivate Color _color;\n\n[SerializeField]\nprivate Color color = Color.white;\n\nvoid Awake(){\n\nthis._material = GetComponent<Renderer>().material;\nthis.DefaultColor();\n}\n\npublic void DefaultColor(){\n\nthis._material.color = this.color;\nthis._color = this.color;\n}\n\n[SerializeField]\nprivate PassColor onChangeColor;\n\nvoid Awake(){\n\nthis._material = GetComponent<Renderer>().material;\nthis.DefaultColor();\n}\n\npublic void DefaultColor(){\n\nthis._material.color = this.color;\nthis._color = this.color;\n}\n\npublic void Discolor(Color color){\n\nthis._material.color = color;\nthis._color = color;\nthis.onChangeColor.Invoke(color);\n}\n\npublic void RandomColor(){\n\nthis.Discolor(new Color(Random.value , Random.value , Random.value));\n}", null, "第 2 顆球設置被點擊時，第三顆球跳起來，第一顆球隨機改變顏色。", null, "第五顆球被點擊時，前四顆球改變成初始顏色。", null, "第二顆球變色的時候，讓第一顆球和第五顆球改變為隨機的顏色。\n\npublic class PassHolder {\n\npublic object value{set; private get;}\n\npublic T GetValue<T>(){\n\nif(this.value == null) return default(T);\n\nreturn (T)this.value;\n}\n}\n\n[System.Serializable]\npublic class PassColorReturn : UnityEvent<Color , PassHolder>{}\n\n[SerializeField]\nprivate PassColorReturn onSwapColor;\n\npublic void SwapColor(){\n\nPassHolder holder = new PassHolder();\nthis.onSwapColor.Invoke(this._color , holder);\nthis.Discolor(holder.GetValue<Color>());\n}\n\npublic void Discolor(Color color , PassHolder holder){\n\nholder.value = this._color;\nthis.Discolor(color);\n}", null, "當第四顆球被點擊時，使第五顆球跳起來、第三顆球改變顏色、要求自己執行交換顏色並指明與第一顆球交換顏色。\n\nhttps://onedrive.live.com/redir?resid=D13D8A29206AFE69!263&authkey=!AMLBuBYFzZsVtOg&ithint=file%2czip" ]	[ null, "https://1.bp.blogspot.com/-uDNUradrGdM/Vix5WdNrkbI/AAAAAAAAA_g/FTEl3SRVgyg/s320/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.39.21.png", null, "https://2.bp.blogspot.com/-ZbaKicztJYY/Vix522U_gdI/AAAAAAAAA_o/oRaaKO_Iuus/s320/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.42.06.png", null, "https://3.bp.blogspot.com/-8AmVxpfYzKo/Vix69ZHASgI/AAAAAAAAA_0/DkX0inW1iDk/s320/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.45.44.png", null, "https://4.bp.blogspot.com/-qu5P8IhOB4Q/VixzfT2TqbI/AAAAAAAAA-U/vyPor8uSa94/s400/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.14.26.png", null, "https://2.bp.blogspot.com/-LwXl4aRsq-4/Vix3uurp35I/AAAAAAAAA_M/NN4lYWZx_nQ/s400/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.32.01.png", null, "https://2.bp.blogspot.com/-gDRrbMUz5eI/Vix3wBV88QI/AAAAAAAAA_U/TTxU29kNH3o/s400/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.32.32.png", null, "https://2.bp.blogspot.com/-6JsE0UsE8mI/Vix8g7Ak7cI/AAAAAAAABAE/UILk6f8GjAY/s400/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.51.44.png", null, "https://2.bp.blogspot.com/-KAyWYKDIf64/Vix8g4g-x0I/AAAAAAAABAQ/Jgl5_-YY4uQ/s400/%25E8%259E%25A2%25E5%25B9%2595%25E5%25BF%25AB%25E7%2585%25A7%2B2015-10-25%2B%25E4%25B8%258B%25E5%258D%25882.52.37.png", null, 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https://www.thermal-engineering.org/what-is-emissivity-emissivity-of-materials-definition/	[ "# What is Emissivity – Emissivity of Materials – Definition\n\nThe emissivity, ε, of the surface of a material is its effectiveness in emitting energy as thermal radiation and varies between 0.0 and 1.0.Emissivity of Materials\n\n## Emissivity\n\nThe emissivity, ε, of the surface of a material is its effectiveness in emitting energy as thermal radiation and varies between 0.0 and 1.0.", null, "By definition, a blackbody in thermal equilibrium has an emissivity of ε = 1.0. Real objects do not radiate as much heat as a perfect black body. They radiate less heat than a black body and therefore are called gray bodies. To take into account the fact that real objects are gray bodies, the Stefan-Boltzmann law must include emissivity. Quantitatively, emissivity is the ratio of the thermal radiation from a surface to the radiation from an ideal black surface at the same temperature as given by the Stefan–Boltzmann law. Emissivity is simply a factor by which we multiply the black body heat transfer to take into account that the black body is the ideal case.\n\nThe surface of a blackbody emits thermal radiation at the rate of approximately 448 watts per square metre at room temperature (25 °C, 298.15 K). Real objects with emissivities less than 1.0 (e.g. copper wire) emit radiation at correspondingly lower rates (e.g. 448 x 0.03 = 13.4 W/m2). Emissivity plays important role in heat transfer problems. For example, solar heat collectors incorporate selective surfaces that have very low emissivities. These collectors waste very little of the solar energy through emission of thermal radiation.\n\nAnother important radiation property of a surface is its absorptivityα, which is the fraction of the radiation energy incident on a surface that is absorbed by the surface. Like emissivity, value of absorptivity is in the range 0 < α < 1.\n\nIn general, the absorptivity and the emissivity are interconnected by the Kirchhoff’s Law of thermal radiation, which states:\n\nFor an arbitrary body emitting and absorbing thermal radiation in thermodynamic equilibrium, the emissivity is equal to the absorptivity.\n\nemissivity ε = absorptivity α\n\nNote that visible radiation occupies a very narrow band of the spectrum from 400 to 760 nm, we cannot make any judgments about the blackness of a surface on the basis of visual observations. For example, consider white paper that reflects visible light and thus appear white. On the other hand it is essentially black for infrared radiation (absorptivity α = 0.94) since they strongly absorb long-wavelength radiation.\n\nReferences:\nHeat Transfer:\n1. Fundamentals of Heat and Mass Transfer, 7th Edition. Theodore L. Bergman, Adrienne S. Lavine, Frank P. Incropera. John Wiley & Sons, Incorporated, 2011. ISBN: 9781118137253.\n2. Heat and Mass Transfer. Yunus A. Cengel. McGraw-Hill Education, 2011. ISBN: 9780071077866.\n3. U.S. Department of Energy, Thermodynamics, Heat Transfer and Fluid Flow. DOE Fundamentals Handbook, Volume 2 of 3. May 2016.\n\nNuclear and Reactor Physics:\n\n1. J. R. Lamarsh, Introduction to Nuclear Reactor Theory, 2nd ed., Addison-Wesley, Reading, MA (1983).\n2. J. R. Lamarsh, A. J. Baratta, Introduction to Nuclear Engineering, 3d ed., Prentice-Hall, 2001, ISBN: 0-201-82498-1.\n3. W. M. Stacey, Nuclear Reactor Physics, John Wiley & Sons, 2001, ISBN: 0- 471-39127-1.\n4. Glasstone, Sesonske. Nuclear Reactor Engineering: Reactor Systems Engineering, Springer; 4th edition, 1994, ISBN: 978-0412985317\n5. W.S.C. Williams. Nuclear and Particle Physics. Clarendon Press; 1 edition, 1991, ISBN: 978-0198520467\n6. G.R.Keepin. Physics of Nuclear Kinetics. Addison-Wesley Pub. Co; 1st edition, 1965\n7. Robert Reed Burn, Introduction to Nuclear Reactor Operation, 1988.\n8. U.S. Department of Energy, Nuclear Physics and Reactor Theory. DOE Fundamentals Handbook, Volume 1 and 2. January 1993.\n9. Paul Reuss, Neutron Physics. EDP Sciences, 2008. ISBN: 978-2759800414." ]	[ null, "https://thermal-engineering.org/wp-content/uploads/2019/05/emissivity-of-various-material-table-226x300.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.92155164,"math_prob":0.8353957,"size":2551,"snap":"2022-40-2023-06","text_gpt3_token_len":559,"char_repetition_ratio":0.16764821,"word_repetition_ratio":0.0,"special_character_ratio":0.20697765,"punctuation_ratio":0.11111111,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.95667535,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-10-06T05:13:29Z\",\"WARC-Record-ID\":\"<urn:uuid:b34c615a-7a52-40ac-8c91-df6819259715>\",\"Content-Length\":\"445095\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:0fab989e-def5-42c1-b7ff-bf6521cc89c1>\",\"WARC-Concurrent-To\":\"<urn:uuid:43367db4-76e8-40e3-b0e5-2205e69caf53>\",\"WARC-IP-Address\":\"104.21.28.216\",\"WARC-Target-URI\":\"https://www.thermal-engineering.org/what-is-emissivity-emissivity-of-materials-definition/\",\"WARC-Payload-Digest\":\"sha1:OULRQOX3VRN7NZ5FAUDDKEKAXFBEGOLN\",\"WARC-Block-Digest\":\"sha1:ZOCVV5C2KQOBMLIURV7SU2AIIQ3RF4QP\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-40/CC-MAIN-2022-40_segments_1664030337723.23_warc_CC-MAIN-20221006025949-20221006055949-00546.warc.gz\"}"}
https://www.numbersaplenty.com/7553522	[ "Search a number\nBaseRepresentation\nbin11100110100000111110010\n3112012202111002\n4130310013302\n53413203042\n6425522002\n7121126634\noct34640762\n915182432\n107553522\n11429a089\n122643302\n131746152\n141008a54\n159e3132\nhex7341f2\n\n7553522 has 16 divisors (see below), whose sum is σ = 12206592. Its totient is φ = 3495360.\n\nThe previous prime is 7553521. The next prime is 7553531. The reversal of 7553522 is 2253557.\n\nIt is a super-3 number, since 3×75535223 (a number of 22 digits) contains 333 as substring.\n\nIt is not an unprimeable number, because it can be changed into a prime (7553521) by changing a digit.\n\nIt is a polite number, since it can be written in 7 ways as a sum of consecutive naturals, for example, 1223 + ... + 4074.\n\nIt is an arithmetic number, because the mean of its divisors is an integer number (762912).\n\nAlmost surely, 27553522 is an apocalyptic number.\n\n7553522 is a deficient number, since it is larger than the sum of its proper divisors (4653070).\n\n7553522 is a wasteful number, since it uses less digits than its factorization.\n\n7553522 is an evil number, because the sum of its binary digits is even.\n\nThe sum of its prime factors is 5353.\n\nThe product of its digits is 10500, while the sum is 29.\n\nThe square root of 7553522 is about 2748.3671516011. The cubic root of 7553522 is about 196.2079044768.\n\nIt can be divided in two parts, 75535 and 22, that added together give a palindrome (75557).\n\nThe spelling of 7553522 in words is \"seven million, five hundred fifty-three thousand, five hundred twenty-two\"." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8668105,"math_prob":0.990221,"size":1645,"snap":"2023-14-2023-23","text_gpt3_token_len":533,"char_repetition_ratio":0.14320536,"word_repetition_ratio":0.007246377,"special_character_ratio":0.44984803,"punctuation_ratio":0.13622291,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9962705,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-04-01T05:16:35Z\",\"WARC-Record-ID\":\"<urn:uuid:750be546-acf5-4e24-9c89-37ee0ca00ca0>\",\"Content-Length\":\"8222\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:36ef3327-8138-4644-9cec-bff8db72fdc4>\",\"WARC-Concurrent-To\":\"<urn:uuid:1b58049c-7cf9-4901-99d4-c941af6b1765>\",\"WARC-IP-Address\":\"89.46.108.74\",\"WARC-Target-URI\":\"https://www.numbersaplenty.com/7553522\",\"WARC-Payload-Digest\":\"sha1:FSCKSO5STFCEY33HW3ECERX6UVVMQGHU\",\"WARC-Block-Digest\":\"sha1:AMUJX42TOXD5PWKU6TOY3RJZHAJGVPUR\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-14/CC-MAIN-2023-14_segments_1679296949701.0_warc_CC-MAIN-20230401032604-20230401062604-00133.warc.gz\"}"}
https://code.tutsplus.com/tutorials/the-binary-search-algorithm-in-javascript--cms-30003?_ga=2.166945853.2025844634.1544813532-1070940998.1539463761	[ "Unlimited Plugins, WordPress themes, videos & courses! Unlimited asset downloads! From \\$16.50/m\nAdvertisement", null, "# The Binary Search Algorithm in JavaScript\n\nDifficulty:IntermediateLength:MediumLanguages:\n\nIn this post, I'll compare linear search and binary search algorithms. You'll see pseudocode for each algorithm, along with examples and a step-by-step guide to implementing each.\n\n## Introduction\n\nAs a programmer, you want to find the best solution to a problem so that your code is not only correct but also efficient. Choosing a suboptimal algorithm could mean a longer completion time, increased code complexity, or worse a program that crashes.\n\nYou may have used a search algorithm to locate items in a collection of data. The JavaScript language has several methods, like `find`, to locate items in an array. However, these methods use linear search. A linear search algorithm starts at the beginning of a list and compares each element with the search value until it is found.\n\nThis is fine when you have a small number of elements. But when you are searching large lists that have thousands or millions of elements, you need a better way to locate items. This is when you would use binary search.\n\nIn this tutorial, I will explain how binary search works and how to implement the algorithm in JavaScript. First, we will review the linear search algorithm.\n\n## Linear Search\n\nWe will begin by explaining how to implement linear search in JavaScript. We will create a function called `linearSearch` that accepts a value that is an integer or string and an array as parameters. The function will search every element in the array for the value and return the position of the value in the array if it is found. If the value is not in the array, it will return -1. For example, calling `linearSearch(1, [3, 4, 2, 1, 5])` would return 3, and calling `linearSearch(0, [3, 4, 2, 1, 5])` would return -1.\n\nHere's some pseudocode for our function:\n\n### JavaScript Implementation of Linear Search\n\nHere is a JavaScript implementation of the linear search algorithm:\n\nIt is important to note that the linear search algorithm does not need to use a sorted list. Also, the algorithm can be customized for use in different scenarios like searching for an array of objects by key. If you have an array of customer data that includes keys for the first and last name, you could test if the array has a customer with a specified first name. In that case, instead of checking if `list[index]` is equal to our search value, you would check for `list[index].first`.\n\nIn the example above, I used the `linearSearch` function on an array with five elements. In the worst case, when the search value is not in the list or is at the end of the list, the function would have to make five comparisons. Because our array is so small, there is no need to optimize by using a different algorithm. However, beyond a certain point, it is no longer efficient to use a linear search algorithm, and that is when using a binary search algorithm would be better.\n\n## Binary Search\n\nImagine you are playing a number guessing game. You are asked to guess a number between 1 and 100. If your number is too high or too low, you will get a hint.\n\nWhat would your strategy be? Would you choose numbers randomly? Would you start with 1, then 2, and so on until you guessed correctly? Even if you had unlimited guesses, you want to make the correct guess in as few tries as possible. Therefore, you might start by guessing 50. If the number is higher, you could guess 75. If it is lower, then that means the number is between 50 and 75, and you would choose a number that's in the middle. You would go on like this until you arrived at the correct number. This is similar to how binary search works.\n\nUnlike linear search, binary search uses a sorted list. To search for a value, you first compare the value to the middle element of the list. If they are equal, the search value has been found. If the search value is greater than the middle element, you search the top half of the data. You then compare the middle element of this section to the search value. Alternatively, if the item is less than the middle element, you search the bottom half of the list and compare its middle value. The list is repeatedly divided in half until the element is found or there are no more items to search.\n\nTo search for 9 in the list:\n\nWe first find the middle element. This is the element at position `Math.floor((first + last)/2)`, where `first` is the first index, and `last` is the last index. We choose to round down so that if the result is a fraction, it becomes a whole number. The middle element in this list is 5. Our search value 9 is greater than 5, so we search the list:\n\nThe middle element of this portion is 8. Nine is greater than 8, so we search the list:\n\nThe middle element is 9, so we can stop our search here.\n\nHere's some pseudocode that expresses the above algorithm for binary search:\n\n### JavaScript Implementation of Binary Search\n\nNow let's code the binary search algorithm in JavaScript!\n\nWe'll create a function, `binarySearch`, that accepts a value and an array as parameters. It will return the index where the value occurs in the list if found. If the value is not found, it returns -1. This is our implementation written in JavaScript:\n\n## Conclusion\n\nIn this tutorial, we saw how to implement a linear search and a binary search algorithm. The linear search algorithm is simpler and doesn't require a sorted array. However, it is inefficient to use with larger arrays. In the worst case, the algorithm would have to search all elements making n comparisons (where n is the number of elements).\n\nThe binary search algorithm, on the other hand, requires you to sort the array first and is more complicated to implement. However, it is more efficient even when considering the cost of sorting. For example, an array with 10 elements would make at most 4 comparisons for a binary search vs. 10 for a linear search—not such a big improvement. However, for an array with 1,000,000 elements, the worst case in binary search is only 20 comparisons. That's a huge improvement over linear search!\n\nKnowing how to use binary search isn't just something to practice for an interview question. It's a practical skill that can make your code work much more efficiently.\n\nAdvertisement\nAdvertisement" ]	[ null, "https://static.tutsplus.com/packs/media/images/redesign/code-de8b2a5e820f2e4ee056ef0473787806.svg", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.88167834,"math_prob":0.7996853,"size":7714,"snap":"2021-04-2021-17","text_gpt3_token_len":1743,"char_repetition_ratio":0.16290532,"word_repetition_ratio":0.045649074,"special_character_ratio":0.23386051,"punctuation_ratio":0.11061093,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9824822,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-04-17T15:08:29Z\",\"WARC-Record-ID\":\"<urn:uuid:5faed454-7bcb-4c04-9884-498b8785ac19>\",\"Content-Length\":\"101744\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:79ccea61-6489-4b2f-b3d9-0244260f87f1>\",\"WARC-Concurrent-To\":\"<urn:uuid:83076d97-f8c9-44fc-a297-7667e66768c2>\",\"WARC-IP-Address\":\"104.17.234.79\",\"WARC-Target-URI\":\"https://code.tutsplus.com/tutorials/the-binary-search-algorithm-in-javascript--cms-30003?_ga=2.166945853.2025844634.1544813532-1070940998.1539463761\",\"WARC-Payload-Digest\":\"sha1:DWZNNUUZ7TCZ2NXYW6NWFTHNGZWX36VJ\",\"WARC-Block-Digest\":\"sha1:EJRK5TDWJC4EPLPNKEYLAD72KCMDTZRR\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-17/CC-MAIN-2021-17_segments_1618038460648.48_warc_CC-MAIN-20210417132441-20210417162441-00120.warc.gz\"}"}
https://api.flutter.dev/flutter/vector_math/Quaternion-class.html	[ "# Quaternion class Null safety\n\nDefines a Quaternion (a four-dimensional vector) for efficient rotation calculations.\n\nQuaternion are better for interpolating between rotations and avoid the gimbal lock problem compared to euler rotations.\n\n## Constructors\n\nQuaternion(double x, double y, double z, )\nConstructs a quaternion using the raw values `x`, `y`, `z`, and `w`.\nfactory\nQuaternion.axisAngle(Vector3 axis, double angle)\nConstructs a quaternion from a rotation of `angle` around `axis`.\nfactory\nQuaternion.copy(Quaternion original)\nConstructs a quaternion as a copy of `original`.\nfactory\nQuaternion.dq(Vector3 omega)\nConstructs a quaternion from time derivative of `q` with angular velocity `omega`.\nfactory\nQuaternion.euler(double yaw, double pitch, double roll)\nConstructs a quaternion from `yaw`, `pitch` and `roll`.\nfactory\nQuaternion.fromBuffer(ByteBuffer buffer, int offset)\nConstructs a quaternion with a storage that views given `buffer` starting at `offset`. `offset` has to be multiple of Float32List.bytesPerElement.\nQuaternion.fromFloat32List(Float32List _qStorage)\nConstructs a quaternion with given Float32List as storage.\nQuaternion.fromRotation(Matrix3 rotationMatrix)\nConstructs a quaternion from a rotation matrix `rotationMatrix`.\nfactory\nQuaternion.fromTwoVectors(Vector3 a, )\nConstructs a quaternion to be the rotation that rotates vector `a` to `b`.\nfactory\nQuaternion.identity()\nConstructs a quaternion set to the identity quaternion.\nfactory\nQuaternion.random(Random rn)\nConstructs a quaternion with a random rotation. The random number generator `rn` is used to generate the random numbers for the rotation.\nfactory\n\n## Properties\n\naxis\naxis of rotation.\nhashCode int\nThe hash code for this object. [...]\nlength\nLength.\nlength2\nLength squared.\nradians of rotation around the axis of the rotation.\nruntimeType Type\nA representation of the runtime type of the object.\nstorage\nAccess the internal storage of the quaternions components.\nw\nAccess the w component of the quaternion.\nx\nAccess the x component of the quaternion.\ny\nAccess the y component of the quaternion.\nz\nAccess the z component of the quaternion.\n\n## Methods\n\nabsoluteError(Quaternion correct)\nAbsolute error between this and `correct`.\nAdd `arg` to this.\nasRotationMatrix()\nReturns a rotation matrix containing the same rotation as this.\nclone()\nReturns a new copy of this.\nconjugate() → void\nConjugate this.\nconjugated()\nConjugated copy of this.\ncopyRotationInto(Matrix3 rotationMatrix)\nSet `rotationMatrix` to a rotation matrix containing the same rotation as this.\ninverse() → void\nInvert this.\ninverted()\nInverted copy of this.\nnormalize()\nNormalize this.\nnormalized()\nNormalized copy of this.\nnoSuchMethod(Invocation invocation) → dynamic\nInvoked when a non-existent method or property is accessed. [...]\ninherited\nrelativeError(Quaternion correct)\nRelative error between this and `correct`.\nrotate()\nRotates `v` by this.\nrotated()\nReturns a copy of `v` rotated by quaternion.\nscale(double scale) → void\nScales this by `scale`.\nscaled(double scale)\nScaled copy of this.\nsetAxisAngle(Vector3 axis, double radians) → void\nSet the quaternion with rotation of `radians` around `axis`.\nsetDQ(Vector3 omega) → void\nSet the quaternion to the time derivative of `q` with angular velocity `omega`.\nsetEuler(double yaw, double pitch, double roll) → void\nSet quaternion with rotation of `yaw`, `pitch` and `roll`.\nsetFrom(Quaternion source) → void\nCopy `source` into this.\nsetFromRotation(Matrix3 rotationMatrix) → void\nSet the quaternion with rotation from a rotation matrix `rotationMatrix`.\nsetFromTwoVectors(Vector3 a, ) → void\nsetRandom(Random rn) → void\nSet the quaternion to a random rotation. The random number generator `rn` is used to generate the random numbers for the rotation.\nsetValues(double x, double y, double z, ) → void\nSet the quaternion to the raw values `x`, `y`, `z`, and `w`.\nsub(Quaternion arg) → void\nSubtracts `arg` from this.\ntoString()\nPrintable string.\noverride\n\n## Operators\n\noperator *(Quaternion other)\nthis rotated by `other`.\noperator +(Quaternion other)\nReturns copy of this + `other`.\noperator -(Quaternion other)\nReturns copy of this - `other`.\noperator ==(Object other) bool\nThe equality operator. [...]\ninherited\noperator [](int i)\nAccess the component of the quaternion at the index `i`.\noperator []=(int i, double arg) → void\nSet the component of the quaternion at the index `i`.\noperator unary-()\nReturns negated copy of this." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.61348605,"math_prob":0.9264996,"size":5125,"snap":"2021-31-2021-39","text_gpt3_token_len":1241,"char_repetition_ratio":0.21499707,"word_repetition_ratio":0.17661388,"special_character_ratio":0.2417561,"punctuation_ratio":0.13483146,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99474204,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-07-24T18:16:22Z\",\"WARC-Record-ID\":\"<urn:uuid:18ddb998-9277-49b0-99d4-57e6fda915ad>\",\"Content-Length\":\"44835\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e3e50a24-a49c-4d33-b6a8-adc266807cf7>\",\"WARC-Concurrent-To\":\"<urn:uuid:1e07cc50-4c0f-4026-80ab-381da8deb1df>\",\"WARC-IP-Address\":\"151.101.1.195\",\"WARC-Target-URI\":\"https://api.flutter.dev/flutter/vector_math/Quaternion-class.html\",\"WARC-Payload-Digest\":\"sha1:VIVJMJEQQ7SR4BGTUJTXLQJRKYQLW6SY\",\"WARC-Block-Digest\":\"sha1:I3A7EDN7BWYYT5PO7AL22ZZWCLN5TV7S\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-31/CC-MAIN-2021-31_segments_1627046150307.84_warc_CC-MAIN-20210724160723-20210724190723-00130.warc.gz\"}"}
https://www.actitrainer.com/research-database/kcal-estimates-from-activity-counts-using-the-potential-energy-method/	[ "## Kcal Estimates from Activity Counts using the Potential Energy Method\n\n• Published on 01/01/1998\n\nA problem exists in applying the kinetic energy equation KE mv2 to estimates of energy expenditure based on activity counts over long epochs. The instantaneous velocity should be obtained over short time periods (on the order of 0.1 second) and squared to obtain the instantaneous kinetic energy. The instantaneous KE is computed from I/2 In V2 but the square of the average of v is not the same as the average of V2. Since we can only estimate the average velocity from the activity counts integrated over long epochs we should not use the KE equation. An alternative method is to calculate by estimating the “energy potential hill” which is climbed with each step. The Model 7164 summed magnitude algorithm rectiñes the acceleration signal and sums each sample. When the summation value (Epoch Activity Counts) is divided by the number of samples (typically 600 for one minute epochs), one has the average acceleration over the epoch. If the average acceleration is integrated twice over time, one gets distance, In the case for a waist worn Actigraph, the distance measure is in the vertical plane. We can use the potential energy equation, PE = mgh, to calculate the work done in raising and lowering the body against gravity.\n\nThe example that follows here, shows how one can use Activity Counts to estimate caloric expenditure in kcals.\n\nA Model 7164 worn tightly on the hip while walking 4.8 km/hr (3 mi/hr) yields an average of 3000 +/-500 activity counts per minute. The average acceleration over one minute is >>>>>>\n\n3000 counts/mín X 0.01664 g/oount 600 samples/min = 0.0832 g/sample\n\nSubstituting m/sec2 the average acceleration is 0.82 m/sec2\n\nThe vertical distance moved over one second >>>>>>>>\n\nh = 1/2 acceleration t2 = 0.41 meters Note: This is equivalent to a vertical displacement of 0.117 meters\n\n(4.6 inches) with each step and a step rate of 1.75 steps/sec. (1.75 steps X 2 X 0.117m = 0.41m)\n\nFrom the computed vertical distance moved against gravity over each second, an estimate of energy\n\nexpended from Work performed in raising and lowering the body against gravity can be calculated from:\n\nPE = mgh\n\nEnergy expenditure (in Joules/sec) for a body mass of 90 kg >>>>>>\n\n90 kg X 9.8 m/s2 X 0.41 m = 361 Joule/sec or 361 Watts\n\nEnergy expenditure (in kilo calories per mín) is >>>>>>\n\n361 Joules/sec / 4,184 Joules/kcal X 60 sec/min ~= 5 kcals/min\n\nFrom this analysis a simple equation can be written to convert Activity Counts to\n\nKcaìs/min = 0.0000191 * counts/min * body mass in kg\n\nWhile this conversion factor seems quite simple, testing in activities such as walking and running reveals\n\nthe PAEE kcal estimates to be very close to published values for those activities.\n\n, ," ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.88926005,"math_prob":0.98946124,"size":2860,"snap":"2021-43-2021-49","text_gpt3_token_len":677,"char_repetition_ratio":0.11414566,"word_repetition_ratio":0.0125,"special_character_ratio":0.2548951,"punctuation_ratio":0.074074075,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99686307,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-11-27T16:46:34Z\",\"WARC-Record-ID\":\"<urn:uuid:de748c17-9583-427d-9cec-9d0839c27f14>\",\"Content-Length\":\"40919\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:8f6401a3-c600-4187-88c4-46263d75505d>\",\"WARC-Concurrent-To\":\"<urn:uuid:5dbbee23-4552-44cb-b555-2c0c5fa09dd7>\",\"WARC-IP-Address\":\"13.92.237.218\",\"WARC-Target-URI\":\"https://www.actitrainer.com/research-database/kcal-estimates-from-activity-counts-using-the-potential-energy-method/\",\"WARC-Payload-Digest\":\"sha1:IZJEHCOF2WSYCK76QKJUKYVIANVNMQU7\",\"WARC-Block-Digest\":\"sha1:C4ORIGMAVGZEMJHL2QKFKE3H436PTUAF\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-49/CC-MAIN-2021-49_segments_1637964358208.31_warc_CC-MAIN-20211127163427-20211127193427-00518.warc.gz\"}"}
https://www.global-sci.org/intro/article_detail/getBib?article_id=496	[ "@Article{IJNAM-12-401, author = {}, title = {A Priori Error Estimates for Finite Volume Element Approximations to Second Order Linear Hyperbolic Integro-Differential Equations}, journal = {International Journal of Numerical Analysis and Modeling}, year = {2015}, volume = {12}, number = {3}, pages = {401--429}, abstract = {\n\nIn this paper, both semidiscrete and completely discrete finite volume element methods (FVEMs) are analyzed for approximating solutions of a class of linear hyperbolic integro-differential equations in a two-dimensional convex polygonal domain. The effect of numerical quadrature is also examined. In the semidiscrete case, optimal error estimates in \\$L^∞(L^2)\\$ and \\$L^∞(H^1)\\$ norms are shown to hold with minimal regularity assumptions on the initial data, whereas quasi-optimal estimate is derived in \\$L^∞(L^∞)\\$ norm under higher regularity on the data. Based on a second order explicit method in time, a completely discrete scheme is examined and optimal error estimates are established with a mild condition on the space and time discretizing parameters. Finally, some numerical experiments are conducted which confirm the theoretical order of convergence.\n\n}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/496.html} }" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.84908307,"math_prob":0.96775824,"size":1301,"snap":"2023-14-2023-23","text_gpt3_token_len":306,"char_repetition_ratio":0.09175019,"word_repetition_ratio":0.0,"special_character_ratio":0.24212144,"punctuation_ratio":0.12093023,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99395025,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-05-28T20:22:24Z\",\"WARC-Record-ID\":\"<urn:uuid:1232f22b-d408-4f28-abf6-85adc0b80bd3>\",\"Content-Length\":\"1647\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e2e69166-962a-4f11-8cad-dbbd6cc173c1>\",\"WARC-Concurrent-To\":\"<urn:uuid:9a84a92e-c2f8-43d2-9189-6b7a8132af63>\",\"WARC-IP-Address\":\"8.218.69.127\",\"WARC-Target-URI\":\"https://www.global-sci.org/intro/article_detail/getBib?article_id=496\",\"WARC-Payload-Digest\":\"sha1:4HEDOYKXAOZ3WO4EKNZG7EULHQYCMXJL\",\"WARC-Block-Digest\":\"sha1:TO3YB7EPU6KUQ4OTPZGHNRIZNOFVPFM5\",\"WARC-Identified-Payload-Type\":\"application/x-bibtex-text-file\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-23/CC-MAIN-2023-23_segments_1685224644506.21_warc_CC-MAIN-20230528182446-20230528212446-00323.warc.gz\"}"}
http://dlrgenchem.com/fall98/c1311001/exam1.htm	[ "GENERAL CHEMISTRY I\nCHEM 1311.001\nEXAM 1\nFriday September 18, 1998\n\nName_________________________________________\n\nSSN__________________________________________\n\n1. What is an experiment?\n a) An observation of natural phenomena, carried out in a controlled manner, so that the results are reproducible, and rational conclusions can be obtained b) Use of the senses, or extensions thereof, to acquire information about natural phenomena c) The general process acquiring and refining information about natural phenomena. It was represented in class by a flow chart. d) A tentative explanation of natural phenomena e) A tested explanation of natural phenomena\n2. What is a law?\n a) A tested explanation of natural phenomena b) A tentative explanation of natural phenomena c) A concise statement or mathematical equation about natural phenomena d) Use of the senses, or extensions thereof, to acquire information about natural phenomena e) An observation of natural phenomena, carried out in a controlled manner, so that the results are reproducible and rational conclusions can be obtained\n3. What is a theory?\n a) An observation of natural phenomena, carried out in a controlled manner so that the results are reproducible and rational conclusions can be obtained b) Use of the senses, or extensions thereof, to acquire information about natural phenomena c) A tentative explanation of natural phenomena d) A tested explanation of natural phenomena e) A concise statement, or mathematical equation, about natural phenomena\n4. What term means \"the general process of acquiring information about natural phenomena\" and was represented in class by a flowchart?\n a) experiment b) observation c) hypothesis d) theory e) scientific method\n5. What term means \"use of the senses, or extensions thereof, to acquire information about natural phenomena\"?\n a) experiment b) observation c) hypothesis d) theory e) scientific method\n6. A tentative explanation of natural phenomena is a(n)\n a) law b) experiment c) hypothesis d) observation e) theory\n7. Which of the following could, in some cases, be an incorrect explanation of natural phenomena?\n a) hypothesis b) law c) theory d) all of these e) none of these\n8. True or False: After a theory is supported by the the results of numerous experiments, it becomes a hypothesis.\n a) True b) False\n9. True or False: A law usually applies to a broad variety of cases, rather than just one or two specific cases.\n a) True b) False\n10. True or False: If a scientist proposes an explanation of natural phenomena and then conducts an experiment to test it, the explanation must definitely be correct if the experimental data are in agreement with the proposed explanation.\n a) True b) False\n11. When we convert a quantity expressed in one set of units to a different set of units (such as converting cm to mm) we usually carry out the conversion by\n a) adding 1 (in a special form) to the original quantity b) adding 0 (in a special form) to the original quantity c) multiplying 1 (in a special form) by the original quantity d) multiplying 0 (in a special form) by the original quantity\n12. True or False: When we convert a quantity in one set of units to another set of units, the original quantity and the new quantity are mathematically equal to each other\n a) True b) False\n13. True or False: Since there are 12 inches in a foot, there must be 12 cubic inches in a cubic foot.\n a) True b) False\n14. To what power must 10 be raised to get 10?\n a) 0 b) 1 c) 2 d) 3 e) 4\n15. How should the number 0.0017 be written in order to be in scientific notation in standard form?\n a) 0.0017 x 100 b) 0.017 x 10-1 c) 0.17 x 10-2 d) 1.7 x 10-3 e) 17 x 10-4\n16. Which of the following floating point numbers is equivalent to 1.375 x 102?\n a) 0.001375 b) 0.01375 c) 137.5 d) 1375 e) 13750\n17. After doing a calculation, a student obtained the number 175.8 x 10-3 as the answer. How should this number be re-written in order to be in standard form?\n a) 175.8 x 100 b) 1.758 x 10-1 c) 1.758 x 10-5 d) 1.758 x 100 e) 1758 x 10-4\n18. In the metric system\n a) Different units of measurement are always related by powers of 10 b) Different units of measurement are related by various different factors with no predictable pattern\n19. Use the relationships 1 m = 39.37 in and 1 ft = 12 in to calculate the number of meters in one foot. (That is, starting with a distance of 1 ft, convert it to m)\n a) 0.002117 m b) 0.2540 m c) 0.3048 m d) 3.281 m e) 472.4 m\n20. A graduated cylinder contains 24.8 cm3 of water. What is the volume of water in cubic inches? Note that 1 in = 2.54 cm.\n a) 1.51 in3 b) 9.76 in3 c) 63.0 in3 d) 160 in3 e) 406 in3\n21. A chemist reads the volume of water in a graduated cylinder and reports the volume is 12.21 mL. How many significant figures are there in the number 12.21 as used in this context?\n a) 2 b) 3 c) 4 d) indeterminate e) infinite\n22. A beaker is weigned on an analytical balance and a mass of 63.6100 g is obtained. How many significant figures are there in the number 63.6100 as used in this context?\n a) 4 b) 5 c) 6 d) indeterminate e) infinite\n23. A very small piece of metal is weighed on an analytical balance and the mass is found to be 0.0012 g. How many significant figures are there in the number 0.0012 as used in this context?\n a) 2 b) 3 c) 4 d) indeterminate e) infinite\n24. A piece of string was measured with a ruler and found to have a length of 100.0 cm. How many significant figures are there in the number 100.0 as used in this context?\n a) 1 b) 2 c) 3 d) 4 e) infinite\n25. One mile is defined as a distance of 5280 feet. How many significant figures are there in the number 5280 as used in this context?\n a) 0 b) 3 c) 4 d) indeterminate e) infinite\n26. The original enrollment in this chemistry class was 30 students. How many significant figures are there in the number 30 as used in this context?\n a) 0 b) 1 c) 2 d) indeterminate e) infinite\n27. A piece of glass tubing was weighed on an analytical balance and its mass was found to be 10.0100 g. How many significant figures are there in the number 10.0100 as used in this context?\n a) 2 b) 4 c) 6 d) indeterminate e) infinite\n28. True or False: Numbers obtained from measurements are considered to be exact.\n a) True b) False\n29. If the number of significant figures in a numerical value is infinite, the numerical value is said to be\n a) exact b) indeterminate\n30. How many \"uncertain\" digits should be shown in a measured value or final answer to a calculation?\n\na) none b) one c) two\n\nd) whatever number of uncertain digits the person writing the value wants to show\n\ne) an infinite number\n\n31. Density is calculated by dividing the mass of a substance by its volume. That is, d = m / V. If a 5.00 mL sample of an unknown liguid has a mass of 5.100 g, what is the density of the liquid? Select the answer that complies with the appropriate significant figure rules.\n a) 1 g / mL b) 1.0 g / mL c) 1.02 g / mL d) 1.020 g / mL e) 1.0200 g / mL\n32. If one piece of string is reported to have a length of 10.30 m and another piece of string is reported to have a length of 5.010 m, what is the combined length of the two pieces of string? Select the answer that complies with the appropriate significant figure rules.\n a) 15 m b) 15.3 m c) 15.31 m d) 15.310 m e) 15.3100 m\n33. The area of a rectangular figure is calculated by multiplying the length by the width. If a rectangle has a length of 37.523 m and a width of 2.1 m, what is the area of the rectangle? Select the answer that complies with the appropriate significant figure rules.\n a) 8 x 101 m2 b) 79 m2 c) 78.8 m2 d) 78.80 m2 e) 78.798 m2\n34. A lab student weighed a beaker containing a water sample on a top loading balance. The mass was determined to be 225.17 g. The student's lab partner had previously weighed the same beaker -- when it was empty -- on an analytical balance and obtained a mass of 94.1635 g. What mass of water was in the beaker? Select the answer that complies with the appropriate significant figure rules.\n a) 131 g b) 131.0 g c) 131.01 g d) 131.006 g e) 131.0065 g\n35. Two graduated cylinders were sitting on a laboratory bench, each partially filled with water. A chemist noted that one cylinder contained 1.00 mL of water, while the other cylinder contained 47.1 mL of water. What is the total volume of water in the two cylinders? Select the answer that complies with the appropriate significant figure rules.\n a) 5 x 101 mL b) 48 mL c) 48.1 mL d) 48.10 mL e) 48.100 mL\n36. If a piece of metal has a mass of 1.20 g and a volume of 0.2 mL, what is the density of the metal? Select the answer that complies with the appropriate significant figure rules. Note that d = m / V.\n a) 6 g / mL b) 6.0 g / mL c) 6.00 g / mL d) 6.000 g / mL e) 6.0000 g / mL\n37. A student is solving the mixed arithmetic problem 1.3133 x (1.2150 + 2.165) =\nFor simplicity, units have been omitted from the numbers, but assume all numbers come from measurements. With regard to significant figure rules, how should the answer to this calculation be expressed?\n a) 4 b) 4.4 c) 4.44 d) 4.439 e) 4.4390\n38. A student is solving the mixed arithmetic problem (10.48 + 2.103) / (1.0 + 2.107) =\nFor simplicity, units have been omitted from the numbers, but assume all numbers come from measurements. With regard to significant figure rules, how should the answer to this calculation be expressed?\n a) 4 b) 4.0 c) 4.05 d) 4.050 e) 4.0499\n39. If a number with three significant figures is multiplied by a number with two significant figures, how many significant figures will be in the answer to the multiplication problem?\n a) 1 b) 2 c) 3 d) 5 e) 6\n40. The mathematical operation of subtraction follows the same significant figure rules as the mathematical operation of __________\n a) addition b) division c) multiplication\n\n1 a 2 c 3 d 4 e 5 b\n\n6 c 7 d 8 b 9 a 10 b\n\n11 c 12 a 13 b 14 b 15 d\n\n16 c 17 b 18 a 19 c 20 a\n\n21 c 22 c 23 a 24 d 25 e\n\n26 e 27 c 28 b 29 a 30 b\n\n31 c 32 c 33 b 34 c 35 c\n\n36 a 37 d 38 b 39 b 40 a" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8044397,"math_prob":0.9748367,"size":9991,"snap":"2019-13-2019-22","text_gpt3_token_len":2898,"char_repetition_ratio":0.13077,"word_repetition_ratio":0.21015668,"special_character_ratio":0.32158944,"punctuation_ratio":0.11008326,"nsfw_num_words":1,"has_unicode_error":false,"math_prob_llama3":0.99304307,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-03-24T15:32:58Z\",\"WARC-Record-ID\":\"<urn:uuid:ff05e634-4ae4-4b66-8f62-47278be6a2ee>\",\"Content-Length\":\"17862\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:0b1da41e-620d-42c8-8eff-c50316049297>\",\"WARC-Concurrent-To\":\"<urn:uuid:9aaee422-c2c8-4a60-bbdc-b0290e928d58>\",\"WARC-IP-Address\":\"198.71.142.135\",\"WARC-Target-URI\":\"http://dlrgenchem.com/fall98/c1311001/exam1.htm\",\"WARC-Payload-Digest\":\"sha1:3FFXX4N63FXLM4W5CGGVH666OTWD27AS\",\"WARC-Block-Digest\":\"sha1:JWLF2K6RCE23JRU3CYICIN56HTY3AAW5\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-13/CC-MAIN-2019-13_segments_1552912203462.50_warc_CC-MAIN-20190324145706-20190324171706-00527.warc.gz\"}"}
https://www.flexiprep.com/Expected-Exam-Questions/Mathematics/Class-10/CBSE-Class-10-Mathematics-Chapter-11-Constructions-Part-13.html	[ "CBSE Class 10-Mathematics: Chapter – 11 Constructions Part 13 (For CBSE, ICSE, IAS, NET, NRA 2022)\n\nGlide to success with Doorsteptutor material for CBSE/Class-10 : get questions, notes, tests, video lectures and more- for all subjects of CBSE/Class-10.\n\nQuestion 22:\n\nConstruct an isosceles triangle whose base is and altitude and then another triangle whose sides are times the corresponding sides of the isosceles triangle.\n\nTo construct: To construct an isosceles triangle whose base is and altitude and then a triangle similar to it whose sides are of the corresponding sides of the first triangle.\n\nSteps of construction:\n\n(a) Draw BC = 8 cm\n\n(b) Draw perpendicular bisector of BC. Let it meets BC at D.\n\n(c) Mark a point A on the perpendicular bisector such that .\n\n(d) Join AB and AC. Thus is the required isosceles triangle.\n\n(e) From any ray BX, making an acute angle with BC on the side opposite to the vertex A.\n\n(f) Locate points and on BX such that .\n\n(g) Join and draw a line through the point , draw a line parallel to intersecting BC at the point C. ′\n\n(h) Draw a line through C ‘parallel to the line CA to intersect BA at A.’\n\nThen, A ‘BC’ is the required triangle.\n\nJustification:\n\n[By construction]\n\n[AA similarity]\n\n[By Basic Proportionality Theorem]\n\n[By construction]\n\n[AA similarity]\n\nBut [By construction]\n\nTherefore,\n\nQuestion 23:\n\nDraw a triangle ABC with side , and . Then construct a triangle whose sides are of the corresponding sides of triangle ABC.\n\nTo construct: To construct a triangle ABC with side , and and and then a triangle similar to it whose sides are of the corresponding sides of the first triangle ABC.\n\nSteps of construction:\n\n(a) Draw a triangle ABC with side , and .\n\n(b) From any ray BX, making an acute angle with BC on the side opposite to the vertex A.\n\n(c) Locate 4 points and on BX such that .\n\n(d) Join and draw a line through the point , draw a line parallel to intersecting BC at the point C. ′\n\n(e) Draw a line through C ‘parallel to the line CA to intersect BA at A.’\n\nThen, A ‘BC’ is the required triangle.\n\nJustification:\n\n[By construction]\n\n[By Basic Proportionality Theorem]\n\nBut [By construction]\n\nTherefore,\n\n[AA similarity]\n\n[From eq. (i) ]\n\nDeveloped by:" ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.8611021,"math_prob":0.96580184,"size":2184,"snap":"2022-05-2022-21","text_gpt3_token_len":539,"char_repetition_ratio":0.15688074,"word_repetition_ratio":0.44559586,"special_character_ratio":0.24358974,"punctuation_ratio":0.12268519,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9945246,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2022-01-24T16:04:37Z\",\"WARC-Record-ID\":\"<urn:uuid:e164a065-e613-488d-b15c-888ba6a42734>\",\"Content-Length\":\"19466\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b3bc8b8f-98fc-4e35-93ca-2adaf9ed575f>\",\"WARC-Concurrent-To\":\"<urn:uuid:e2409d8c-c2cf-4e6b-bf50-b75e2b6f60aa>\",\"WARC-IP-Address\":\"104.21.77.56\",\"WARC-Target-URI\":\"https://www.flexiprep.com/Expected-Exam-Questions/Mathematics/Class-10/CBSE-Class-10-Mathematics-Chapter-11-Constructions-Part-13.html\",\"WARC-Payload-Digest\":\"sha1:XHAKLUK6ELMA3HCV2NRHY2IRC6LPC2OG\",\"WARC-Block-Digest\":\"sha1:NZLDHFUX7QTTXZ3VMDBHDML7KA5G4JM7\",\"WARC-Identified-Payload-Type\":\"application/xhtml+xml\",\"warc_filename\":\"/cc_download/warc_2022/CC-MAIN-2022-05/CC-MAIN-2022-05_segments_1642320304572.73_warc_CC-MAIN-20220124155118-20220124185118-00672.warc.gz\"}"}
http://mathscinet.ru/catalogue/shadow/	[ "", null, "Shadow matrices S alow construct two circulant cores of Jacobsthal matrices Q: the latest are cores of two border two circulant C-matrices. They can consist of symmetric circulant A-block and B-block based on secuence [b;–Rb], R – reversed identity matrix.", null, "Shadow matrices noted by symbol \"e\": it is \"younger family\" of Euler matrices for orders n=4k ! Two-circulant three level (a,–b,d)-matrices constructed via conference matrices and their orthogonalised cores: a=1, b=1–2d, d=(sqrt(2n+1)–3)/(n–4) –diagonal entry (for n=4, d=b=1).\n\nOn Line Procedure", null, "", null, "Euler matrices E alow construct two circulant cores of Jacobsthal matrices Q: the latest are cores of two border two circulant H-matrices. They can consist of the set of symmetric, asymmetric and skew circulant A, B-blocks.\n\nСЛОЖНОСОСТАВНАЯ МАТРИЦА 44\n\nCRETAN MATRICES\n\na=1, b=1–2d, d=(sqrt(2n+1)–1)/n – diagonal entry", null, "Conference matrix C6", null, "", null, "Ortagonalised core S5 and shadow matrix e4", null, "Conference matrix C10", null, "", null, "Ortagonalised core S9 and shadow matrix e8 following S9", null, "Conference matrix C14", null, "", null, "Ortagonalised core S13 and shadow matrix e12\n\nСВЯЗЬ С КОНФЕРЕНЦ-МАТРИЦАМИ (ЯДРА)", null, "Conference matrix C6", null, "", null, "Ortagonalised core S5 and shadow matrix e4=H4", null, "Conference matrix C10", null, "", null, "Ortagonalised core S9 and shadow matrix e8", null, "Conference matrix C14", null, "", null, "Ortagonalised core S13 and shadow matrix e12", null, "Conference matrix C18", null, "", null, "Ortagonalised core S17 and shadow matrix e16", null, "EULER MATRICES CATALOGUE \| \| MERSENNE MATRICES CATALOGUE\n\n ..", null, "" ]	[ null, "http://mathscinet.ru/catalogue/files/Mayak.jpg", null, "http://mathscinet.ru/catalogue/files/MEANDERS.png", null, "http://mathscinet.ru/catalogue/files/Sh16.png", null, "http://mathscinet.ru/catalogue/files/Sh24.png", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/shadow/", null, "http://mathscinet.ru/catalogue/files/Thinking.png", null, "http://top100-images.rambler.ru/top100/w7.gif", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.6609668,"math_prob":0.9400811,"size":1543,"snap":"2019-26-2019-30","text_gpt3_token_len":489,"char_repetition_ratio":0.19688109,"word_repetition_ratio":0.28310502,"special_character_ratio":0.23849644,"punctuation_ratio":0.08571429,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.98554677,"pos_list":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54],"im_url_duplicate_count":[null,1,null,2,null,1,null,1,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,1,null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2019-07-20T12:37:12Z\",\"WARC-Record-ID\":\"<urn:uuid:caf90bd1-c2cf-4273-941e-f77bc45600c4>\",\"Content-Length\":\"34258\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:402f37b9-4913-4d11-8954-79c82c00ae16>\",\"WARC-Concurrent-To\":\"<urn:uuid:5f4c728d-cbf1-43ae-9498-cac98047da25>\",\"WARC-IP-Address\":\"217.112.35.78\",\"WARC-Target-URI\":\"http://mathscinet.ru/catalogue/shadow/\",\"WARC-Payload-Digest\":\"sha1:AUYN7EKFG2DNTBIMLGZTAZ6TIWCFY4CP\",\"WARC-Block-Digest\":\"sha1:DZLDMDFQIW6OYGIKUZZ7K3XVKN2NEEL7\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2019/CC-MAIN-2019-30/CC-MAIN-2019-30_segments_1563195526508.29_warc_CC-MAIN-20190720111631-20190720133631-00046.warc.gz\"}"}
https://blog.myrank.co.in/parallel-axis-theorem/	[ "# Parallel Axis Theorem\n\nThe theorem determines the moment of inertia of a rigid body about any given axis, given that moment of inertia about the parallel axis through the centre of mass of an object and the perpendicular distance between the axes.\n\nThe moment of inertia of a body about an axis is equal to its moment of inertia about a parallel axis through its centre of gravity plus the product of the mass of the body and the square of the perpendicular distance between the two parallel axes.", null, "Let ‘I’ be the moment of inertia of a plane lamina about an axis YY. Let ‘G’ be the centre of gravity of the lamina. Y¹Y¹ is an axis parallel to YY and passing through ‘G’. Let ‘Ig’ be the moment of inertia of the lamina about Y¹Y¹.\n\nLet GP = x.\n\nMoment of inertia of the particle about\n\nYY = m (x + d)2\n\nMoment of inertia of the whole of lamina about\n\nYY = I = ∑ m (x + d)²\n\n= ∑ m (x² + d² + 2xd)\n\n⇒ I = ∑ mx² + ∑ md² + ∑ 2mxd\n\nBut ∑mx² = Ig, ∑md² = (∑ m)d² = Md²\n\nAlso ∑ 2mxd = 2d∑mx\n\n∴ I = Ig + md² + 2d ∑ mx\n\nThe lamina will balance itself about its centre of gravity. So the algebraic sum of the moments of the weights of constituent particles about the centre of gravity G should be zero.\n\n∴ ∑ mg x X = 0 or g ∑ mx = 0\n\n⇒ ∑ mx = 0\n\n∴ I = Ig + Md².\n\nThe parallel axis theorem can be used to determine the object’s moment of inertia of a rigid body around any axis. This theorem is also known as Huygens – Steiner theorem. According to the parallel axis theorem, there is an affiliation between the inertia of an object rotation around its centre of gravity and an axis parallel to this centre. This theorem can be used to any solid object in rotation, as well as with irregular shapes. For easy understanding, the parallel axis theorem is a relation between the moment of inertia about an axis passing through the centroid, the centre of gravity of a geometrical object of uniform density and the moment of inertia about any parallel axis." ]	[ null, "http://blog.myrank.co.in/wp-content/uploads/2017/11/Parallel-Axis-Theorem.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.90300035,"math_prob":0.9973517,"size":1902,"snap":"2022-40-2023-06","text_gpt3_token_len":503,"char_repetition_ratio":0.18335089,"word_repetition_ratio":0.06527415,"special_character_ratio":0.2486856,"punctuation_ratio":0.056300268,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99885595,"pos_list":[0,1,2],"im_url_duplicate_count":[null,4,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-01-31T14:01:48Z\",\"WARC-Record-ID\":\"<urn:uuid:0f9e129f-4db4-4111-86db-6f2d9f7e50a1>\",\"Content-Length\":\"54322\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:831bbece-bac7-4539-850a-79e27c538b9b>\",\"WARC-Concurrent-To\":\"<urn:uuid:04bd3869-9d76-4b89-a978-90fa3ba6d67a>\",\"WARC-IP-Address\":\"162.144.105.100\",\"WARC-Target-URI\":\"https://blog.myrank.co.in/parallel-axis-theorem/\",\"WARC-Payload-Digest\":\"sha1:5OT67BGS6SVFJTFIKQZGJ2JJRVXHDYM2\",\"WARC-Block-Digest\":\"sha1:3UNDQH57CWRS4LKGNBYVBLDFYJCRO6XX\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-06/CC-MAIN-2023-06_segments_1674764499871.68_warc_CC-MAIN-20230131122916-20230131152916-00539.warc.gz\"}"}
https://robotics_en_ru.enacademic.com/533/approximation_step	[ "\n\n# approximation step\n\nшаг аппроксимации\n\nАнгло-русский словарь по робототехнике. 2013.\n\n### Смотреть что такое \"approximation step\" в других словарях:\n\n• Approximation theory — In mathematics, approximation theory is concerned with how functions can best be approximated with simpler functions, and with quantitatively characterizing the errors introduced thereby. Note that what is meant by best and simpler will depend on … Wikipedia\n\n• Step response — The step response of a system in a given initial state consists of the time evolution of its outputs when its control inputs are Heaviside step functions. In electronic engineering and control theory, step response is the time behaviour of the… … Wikipedia\n\n• Born-Oppenheimer approximation — In quantum chemistry, the computation of the energy and wavefunction of an average size molecule is a formidable task that is alleviated by the Born Oppenheimer (BO) approximation. For instance the benzene molecule consists of 12 nuclei and 42… … Wikipedia\n\n• Stochastic approximation — methods are a family of iterative stochastic optimization algorithms that attempt to find zeroes or extrema of functions which cannot be computed directly, but only estimated via noisy observations. The first, and prototypical, algorithms of this … Wikipedia\n\n• Successive approximation ADC — Successive Approximation redirects here. For behaviorist B.F. Skinner s method of guiding learned behavior, see Shaping (psychology). A successive approximation ADC is a type of analog to digital converter that converts a continuous analog… … Wikipedia\n\n• Rotating wave approximation — The rotating wave approximation is an approximation used in atom optics and magnetic resonance. In this approximation, terms in a Hamiltonian which oscillate rapidly are neglected. This is a valid approximation when the applied electromagnetic… … Wikipedia\n\n• Successive Approximation ADC — A successive approximation ADC is a type of analog to digital converter that converts a continuous analog waveform into a discrete digital representation via a binary search through all possible quantization levels before finally converging upon… … Wikipedia\n\n• Heaviside step function — The Heaviside step function, H , also called the unit step function, is a discontinuous function whose value is zero for negative argument and one for positive argument.It seldom matters what value is used for H (0), since H is mostly used as a… … Wikipedia\n\n• последовательное приближение — — [Л.Г.Суменко. Англо русский словарь по информационным технологиям. М.: ГП ЦНИИС, 2003.] Тематики информационные технологии в целом EN progressive approximationstep by step approximationstep by step approach … Справочник технического переводчика\n\n• List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra … Wikipedia\n\n• Methods of computing square roots — There are several methods for calculating the principal square root of a nonnegative real number. For the square roots of a negative or complex number, see below. Contents 1 Rough estimation 2 Babylonian method 2.1 Example … Wikipedia\n\n### Книги\n\nДругие книги по запросу «approximation step» >>\n\n### Поделиться ссылкой на выделенное\n\n##### Прямая ссылка:\nНажмите правой клавишей мыши и выберите «Копировать ссылку»\n\nWe are using cookies for the best presentation of our site. Continuing to use this site, you agree with this." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.69038725,"math_prob":0.8940209,"size":4422,"snap":"2020-34-2020-40","text_gpt3_token_len":1018,"char_repetition_ratio":0.13852422,"word_repetition_ratio":0.2431611,"special_character_ratio":0.18521032,"punctuation_ratio":0.10238429,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.97349536,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2020-08-11T01:32:45Z\",\"WARC-Record-ID\":\"<urn:uuid:3f4f4edf-6f33-45fa-8b37-78ade5f90fe6>\",\"Content-Length\":\"42174\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:b12935cd-85be-42d6-89ae-9f5e03003aad>\",\"WARC-Concurrent-To\":\"<urn:uuid:e92cc0cc-a260-4708-a66b-31bb3124f5e3>\",\"WARC-IP-Address\":\"138.201.23.84\",\"WARC-Target-URI\":\"https://robotics_en_ru.enacademic.com/533/approximation_step\",\"WARC-Payload-Digest\":\"sha1:QZGRWPB3JEXXPPKNIYVKTCGU6OB2KZHV\",\"WARC-Block-Digest\":\"sha1:L3IFUVMMS5U2OC3IVZIV37GZ257A34VH\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2020/CC-MAIN-2020-34/CC-MAIN-2020-34_segments_1596439738723.55_warc_CC-MAIN-20200810235513-20200811025513-00549.warc.gz\"}"}
https://discuss.codecademy.com/t/what-is-the-point-of-this-function/446936	[ "", null, "# What is the point of this function?\n\nHi,\nSo I alright executing the exercise, but I would like to know WHY the function needs the ‘Russian doll’ like encasing, what is the purpose?\ne.g:\n\n``````function monitorCount(rows, columns) {\nreturn rows * columns;\n};\nconst numOfMonitors=monitorCount(5,4);\nconsole.log(numOfMonitors);\n``````\n\nSo I determine the function on the first line! I am fine with that… then I carry on and set the way the function will be calculated. Great! What is the const line for then? is that were basically the DATA will be input to, so the function can work? I am a bit lost on this concept.\n\nI didn’t see the point of the function to begin with, I could have made a const without calling the function, what is this for?\n\nThx\n\nDespite the verbosity, the function demonstrates how we can keep all multiplication of two factors contained in one function, which any part of the program can call upon if it needs a product of `a` and `b`.\n\nFor this exercise it is more specific so we can see what is happening, but it wouldn’t have to be like that.\n\n`````` const multiply = (a, b) => a * b; // generic function expression\n``````\n\nThen we could use named variables in the program…\n\n``````rows = 5\ncolumns = 4\nlet numOfMonitors = multiply(rows, columns)\nconsole.log(numOfMonitors)\n``````\n\nThe function name says what it does, and we can see that if we want to know how many monitors there are, multiply rows times columns.\n\n1 Like\n\nSure, you could just do this: `console.log(5 * 4)`, but what would that teach you about how functions work, or what the `return` statement does? The lessons use simple examples to teach concepts and techniques that can be used to accomplish very complex tasks.\n\n2 Likes" ]	[ null, "https://aws1.discourse-cdn.com/codecademy/original/5X/e/0/8/c/e08cf790a5972ac52a036a0fb64e4e139baec615.png", null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.9052204,"math_prob":0.93798167,"size":694,"snap":"2021-43-2021-49","text_gpt3_token_len":166,"char_repetition_ratio":0.16521738,"word_repetition_ratio":0.0,"special_character_ratio":0.23198847,"punctuation_ratio":0.15231788,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.99386615,"pos_list":[0,1,2],"im_url_duplicate_count":[null,null,null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2021-10-28T20:34:32Z\",\"WARC-Record-ID\":\"<urn:uuid:c7211562-2fee-4f29-88b2-dc17497673c7>\",\"Content-Length\":\"24811\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:6f834fff-04b2-457b-8a56-88747a31b760>\",\"WARC-Concurrent-To\":\"<urn:uuid:50168339-a64d-49cf-be0f-5b192a2d5021>\",\"WARC-IP-Address\":\"64.71.144.202\",\"WARC-Target-URI\":\"https://discuss.codecademy.com/t/what-is-the-point-of-this-function/446936\",\"WARC-Payload-Digest\":\"sha1:TPERVVHPVI6F6WBMUIBCVXWNZHDY2ZI2\",\"WARC-Block-Digest\":\"sha1:QXSYGD6C6GQ4PPBYPQYM2FHBTFOEIMNT\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2021/CC-MAIN-2021-43/CC-MAIN-2021-43_segments_1634323588526.57_warc_CC-MAIN-20211028193601-20211028223601-00640.warc.gz\"}"}
https://elmprogramming.com/value.html	[ "# 3.7\n\n## Value\n\nWe have used the term value without formally defining it. Mathematics defines a value as the result of a calculation. When we evaluate an expression we are performing a calculation. The terms calculation and computation can be used interchangeably. In Elm, all computations are done by evaluating expressions to yield values. This makes expressions the basic building blocks of any Elm application. No matter how complex an Elm application is, its essentially one big expression comprising of mini expressions.\n\nSo far we have only used numbers and boolean as values, but in Elm anything we can produce as a result of a computation can be considered a value. Here are some examples:\n\nWe will cover each of these values in detail later. All values in Elm can be passed as arguments to functions, returned as results, and placed in data structures." ]	[ null ]	{"ft_lang_label":"__label__en","ft_lang_prob":0.9009782,"math_prob":0.97992235,"size":844,"snap":"2023-40-2023-50","text_gpt3_token_len":158,"char_repetition_ratio":0.1297619,"word_repetition_ratio":0.0,"special_character_ratio":0.18483412,"punctuation_ratio":0.10191083,"nsfw_num_words":0,"has_unicode_error":false,"math_prob_llama3":0.9627552,"pos_list":[0],"im_url_duplicate_count":[null],"WARC_HEADER":"{\"WARC-Type\":\"response\",\"WARC-Date\":\"2023-12-10T08:20:47Z\",\"WARC-Record-ID\":\"<urn:uuid:568baed5-48b4-450e-a9cd-bc7170c27637>\",\"Content-Length\":\"35592\",\"Content-Type\":\"application/http; msgtype=response\",\"WARC-Warcinfo-ID\":\"<urn:uuid:e9ec7a09-a2f0-4d86-81de-389c1de78a4a>\",\"WARC-Concurrent-To\":\"<urn:uuid:a92d8292-6497-4927-83bc-5d984353feb7>\",\"WARC-IP-Address\":\"185.199.108.153\",\"WARC-Target-URI\":\"https://elmprogramming.com/value.html\",\"WARC-Payload-Digest\":\"sha1:24SG5SAQVOAXUGVV5L2IJOBRMH5Z2QHB\",\"WARC-Block-Digest\":\"sha1:52CSKPBJCTYXNT5CG4IHASJM7WMBWPSG\",\"WARC-Identified-Payload-Type\":\"text/html\",\"warc_filename\":\"/cc_download/warc_2023/CC-MAIN-2023-50/CC-MAIN-2023-50_segments_1700679101282.74_warc_CC-MAIN-20231210060949-20231210090949-00777.warc.gz\"}"}