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becoming teenage parents. Despite them being forced into adulthood, Starr sees their senior prom as sort of a full-circle event, because prom is where it all began for them. In late 2010, it is announced that Brandon Buddy would be departing from the series with his character, Cole being sent back to prison for violating his probation. Alderson compares her attraction to James to her prior attraction to Schuyler; because Cole is going to be in jail for the next several years, Starr leans on James. Alderson revealed that James being around Starr's age would be a real threat to her relationship with Cole "because unlike Schuyler, this is what James wants. Schuyler did not want to get with Starr at any point. He felt feelings for her like a friend. He cared about her, but James not only cares about Starr; he really does have feelings for her and wants to be with her." Starr ends her relationship with Cole in early 2011 and soon begins dating James. The relationship is quickly threatened
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with the introduction of James's ex-girlfriend, Deanna and Starr's music producer, Baz Moreau. Baz seems to have feelings for Starr, but she quickly rejects him because she is dating James. After causing a bit of trouble for the couple, and breaking up Starr's sister Danielle's relationship with Nate, Deena leaves town. Upon the serial's cancellation, many began speculate that Cole would return to the series in time for the finale. However, the show is forced to abandon those plans and quickly recast the role with actor Van Hughes due to Buddy being unable to continue taping.
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Losing Cole and Hope Upon Alderson's introduction as Starr on General Hospital, it was assumed by fans and critics that Starr would be paired with Michael Corinthos (Chad Duell). However, many wondered what would happen to Cole and Hope. Viewers are shocked in late February when Starr survives a fatal car accident that kills Cole and Hope. Alderson responded to the decision on Twitter urging fans not to blame head-writer Ron Carlivati revealing that both Buddy and Hughes were unavailable to continue in the role of Cole. Alderson promised her fans that the storyline would definitely lead to greater possibilities for Starr. Starr goes on the war path when Michael's father, Sonny is arrested in connection to the shooting which led to the car accident. At the time, Michael is also grieving the loss of his girlfriend, and according to Alderson he is the "only person that could really understand what Starr is going through."
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Storylines 1996–2005
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Upon birth, baby Starr is kidnapped by her presumed dead father to make her mother after finding her with another man. When Starr is diagnosed with aplastic anemia Alex Olanov willingly donates her bone marrow to save her life. When Todd returns from being on the run, he and Starr team up and successfully ruin Blair's marriage to Max Holden. Starr becomes a big sister in 2001 when her parents adopt a little boy named, Jack who is later revealed to be her biological brother. In 2003, Starr is kidnapped by Mitch Laurence and Blair exchanges her freedom for Starr's. When Starr and Jack are sent to Atlanta for their own safety, Starr steals her cousin Cassie’s credit card and finds her way back to Llanview. Blair is now dating Mitch's brother, Walker and Walker reveals that he is actually Todd with plastic surgery. Later, Todd is sentenced to prison when Blair falsely accuses him of rape; Starr and friend, Matthew find the prison van during transport and try to set Todd free only for
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Matthew to be kidnapped by Troy McIver. Though Matthew is rescued, Starr is sentenced to community service at the hospital. Starr meets Travis O’Connell in a chat room and tricks Blair into going to meet him in New York City where the teens run off together. Starr is later kidnapped and held for ransom by Laser. She is rescued and returns home; Travis soon follows and Todd reluctantly allows Starr to see him. The teens later use the family newspaper, The Banner to print malicious information about Starr's cousin, and Todd's rival, Kevin Buchanan. Starr and Travis would share their first kiss before he must go back to New York with his family. When Todd disappears, Blair begins dating Dr. Spencer Truman despite Starr's disapproval. Todd is later sentenced to death for the murder of Margaret Cochran and her unborn child. He flatlines after lethal injection only to be revived it is proved that Margaret faked her death.
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2006–12
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Starr befriends Langston Wilde when she fakes amnesia in order to get her parents back together. They soon start high school where Starr makes enemies with Britney Jennings when football player Cole Thornhart rejects her for Starr. Britney slips steroids into Cole's drink at a party leading to him attacking Starr. Despite disapproval of their parents, Starr and Cole refuse to stop seeing one another. Starr does her best to comfort a grieving Cole when his mother Marty Saybrooke appears to be killed in a car explosion. Meanwhile, Todd and Blair remarry to gain custody of his son, Sam, from Michael and Marcie McBain. Todd suddenly wants to move the family to Hawaii prompting Cole and Starr to make love for the first time; they are caught by Todd who beats Cole to near incapacitation. When Starr learns she is pregnant, after contemplating an abortion, the couple runs away together where they plan to raise the baby. They are found and forced to go back home where Starr ultimately decides
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let Michael and Marcie adopt the baby, much to the dismay of Todd and Cole. The baby dies shortly after birth. It later revealed that Todd planned to kidnap the child and raise it with an amnesiac Marty, who is alive, and Todd is put on trial. With encouragement from her former stepmother, Téa Delgado, Starr changes her statement allowing for Todd be exonerated, driving a bigger wedge between her and Cole. On the rebound from Cole, Starr briefly develops feelings for her teacher, Schuyler Joplin. The truth is revealed about the baby switch and the teens are allowed to raise their child, Hope, when Marcie changes her mind. Starr and Cole almost marry when Cole is nearly sent to prison for drug possession. Starr must tell Todd the truth about Cole going undercover and they end up getting kidnapped by the criminals running the drug ring. Upon her 18th birthday, Starr meets her sister, Danielle as Hannah O'Connor begins causing trouble for Starr. On prom night, Dorian arranges for Cole to
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be temporarily released from prison to attend the dance with Starr. When Cole refuses to allow Starr to continue seeing him in jail, she is comforted by James Ford. After Starr ends her relationship with Cole, she and James admit their feelings for each other and start dating. The couple makes love for the first time in August 2011. Starr later signs a record deal with Rick Powers and Baz Moreau. Meanwhile, the man everyone believed to be Todd with plastic surgery is revealed to be Todd's twin, Victor. Victor is murdered and Todd is the prime suspect.
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On New Year's Starr and Cole are reunited during a prison break. Hannah soon follows and takes Starr hostage at gunpoint. Cole takes a bullet for Starr and James realizes she will always love him, so he ends their relationship. Todd helps Cole fake his death so he can go be with his parents. But once Starr and Hope are in LA, Cole shows up having been sent by Todd to be Starr's "bodyguard".
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2012–13
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Upon Cole and Hope's deaths in Port Charles, New York, the setting of General Hospital, Starr is rescued by Michael Corinthos. Blair soon arrives to tell Starr that her family is gone. The main suspect in their deaths is Sonny Corinthos, Michael's father. Michael lets Starr stay at his apartment during the trial. When Sonny is acquitted, a distraught Starr takes him hostage at gunpoint; Michael is able to talk her out of it but later has her arrested. However, Todd later blackmails Sonny and Michael into dropping the charges. Johnny Zacchara blackmails Rick Powers into letting Starr out of her contract and she signs another deal with him. Starr and Michael soon begin dating and he disapproves of her new roommate, Trey Mitchell. Starr initially clashes with Michael's sister, and Trey's girlfriend, Kristina Davis. Starr and Michael follow Trey and Kristina to Las Vegas and are shocked to find Kristina and Trey have eloped as a publicity stunt for their reality show. It is later revealed
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that Kate Howard's alternate personality, Connie, was the shooter the night of Starr's accident. Starr severs all ties with Johnny when it is revealed that he secretly married Connie to keep her from being committed and helped cover up her involvement in the shooting. Todd soon confides in Starr about his involvement in the switching of Téa's stillborn son with Sam Morgan's living child. Starr and Michael nearly make love for the first time on Halloween when he is confronted by his presumed dead biological father, . She begins sleeping on Michael's couch when she and Trey get evicted from the apartment. As she offers supports to Michael, Starr blackmails Todd into helping Sam's sister, Molly Lansing get her book published. Starr and Michael make love for the first time on Christmas Eve. In January 2013, Johnny finally admits that he was behind Hope and Cole's accident. When Johnny is sent to prison, he gives Starr his half of the Haunted Star making her partners with Michael's cousin
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and sister-in-law, Lulu Spencer-Falconeri.
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Starr is seen grieving on the anniversary of Cole and Hope's death, as well as lamenting the day she met Michael and starting a relationship. As they leave the gravesite, an unknown figure walks forward and gazes sadly at Cole and Hope's gravestones. It is heavily suggested that it is Cole and he survived the accident; however, it remains unknown. On March 20, 2013, Starr receives an emergency call from Langston, telling her to return to Los Angeles immediately. She leaves Michael and tells him she will be back soon. A few days later, Starr calls Michael and tells him she is not returning to Port Charles, and breaks up with him without an explanation. It is implied that Hope and Cole turned up alive in Los Angeles and Starr went into hiding with them.
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Reception
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Alderson received fan mail from fans all over in response to her portrayal of pregnant teenaged Starr, "[…] the most important thing is that we've gotten teenagers and their parents to really talk about the issue and ask the important questions. 'Do you have a plan? What are you going to do? Is this the right time for you?' And they have gotten so much closer to their parents and it warms out hearts to hear that," Alderson revealed in an interview. Amy Kramer also commented on the success of Alderson's online blog about the storyline; "Kristen had hundreds of comments on the blog during the pregnancy — people sharing their own stories about their own relationships with their boyfriends or their parents, or [writing] how they felt about it." Kramer also applauded the series for the strong portrayal of Starr's mother during her pregnancy.One Life's Executive producer, Frank Valentini was honored by HeartShare Human Services of New York at their annual spring gala for his work in Starr's
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pregnancy storyline. Valentini, Alderson, Kramer along with ABC's Sue Johnson were invited to participate in a symposium at Hofstra University "[highlighting] the unique role entertainment can play in dealing with social and health issues that affect woman in the country and around the world."
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In August 2008, Soap Opera Digest featured an interview on their website with Ashley Wilkens who made a guest appearance as the assistant at Starr's obstetrician's office; Wilkens was also a teenage mom who began working with the campaign to raise awareness. Wilkens could identify with Starr who had made the choice to put her baby up for adoption, despite her family's disapproval. Michael Fairman applauded Alderson for her performance during the storyline and expressed how displeased he would be if she didn't win an Emmy for her portrayal of Starr. Alderson also applauded the storyline saying "[…] it is written so that it never ends. It’s written in a way that has explored everything, and has not been cut short, and nothing has been left out, or any important moments or decisions that characters have to make. It’s an actors dream to be on a show where you can develop the character in its entirety."
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In November 2010, Alderson and costar Brandon Buddy were honored by Michael Fairman giving them the "Power Performance of the Week" when Starr and Cole were forced to say goodbye after he is sentenced to 10 years in prison. Alderson and Nic Robuck were also featured on Chelsea Handler's late night talk show, Chelsea Lately, in which Handler poked fun at the list of reason's James gives for not having sex with Starr when she is still grieving from Cole being sent to prison. Alderson earned her first Daytime Emmy Award nomination and win in 2013 for her portrayal of Starr on General Hospital'' in the category of Outstanding Younger Actress. References External links Starr Manning profile – ABC.com Starr Manning profile – SoapCentral.com Starr Manning profile – Soaps.com
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Television characters introduced in 1996 One Life to Live characters General Hospital characters Crossover characters in television Fictional characters from Pennsylvania Fictional singers Female characters in television Fictional teenage parents
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The third season of Tawag ng Tanghalan was an amateur singing competition currently aired as a segment of the noontime show It's Showtime from June 25, 2018 to September 28, 2019. Hosts and judges Rey Valera returned as the head coach for the third season, with Gary Valenciano, Louie Ocampo, Jaya, Ogie Alcasid, Yeng Constantino serving as fill-in for Valera. Judges Karylle, Karla Estrada, K Brosas, Nyoy Volante, Mitoy Yonting, Erik Santos, Kyla, Jed Madela and Jolina Magdangal returned as judges for the third season. OPM Legends Dulce, Randy Santiago and Zsa Zsa Padilla (March 11, 2019 – present) were added to the panel of judges this season. Dulce also serves as the head judge in some episodes.
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Vhong Navarro, Anne Curtis, Amy Perez-Castillo, and Vice Ganda reprised their roles as hosts for the third season, with Ryan Bang, Jhong Hilario, Teddy Corpuz, and Jugs Jugueta serving as co-hosts as well as the Gong. Mariel Rodriguez-Padilla returned to fulfill her hosting duties this season. Kim Chiu, Maja Salvador, Robi Domingo, Bela Padilla and Billy Crawford served as guest hosts in the absence of the main hosts. Season changes Coinciding with the third year of TNT, the show unveiled three new changes in the competition. Updated judging criteria The judging criteria has been updated to further improve the quality of the competition itself. It will only be based on two criterion standards alone: Voice Quality (50%) and Overall Performance (50%). The first criterion includes Intonation, Enunciation, Voice Projection, and Technique. On the other hand, Timing, Mastery of Lyrics, Stage Presence, and Audience Impact comprise the second criterion.
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Tawag ng Tahanan Starting June 29, 2018, this segment will be for the lucky home viewer who will correctly predict the winner in the face-off round between the Daily Winner and Defending Champion. The viewers must be able to call the designated number flashed on-screen for a chance to win ₱5,000. It will be done every day. The segment was conceptualized due to the high public participation last season in social media. Judge's Instant Resbak This season, every judge will now have the power to return a losing Defending Champion from the Face-off Round using the Instant Resbak. The contestant who is given this power will then be saved and moves on to the Instant Resbak Week for a slot in the rounds of the week-long Grand Finals which also known as "Ang Huling Tapatan". However, each judge is only entitled one save per season only (For example, if the judge uses his/her power in Quarter I, he/she can't use it again in the succeeding Quarters). Daily Rounds Quarter I Quarter II
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Quarter III Quarter IV Semifinals The semifinals will take place at the end of the each quarter which will determine the two grand finalists that will take place in 2019. The two grand finalists will receive a medal and an additional 150,000 cash, while the remaining contenders will receive additional 25,000. The score will be composed of 50% coming from the judges and 50% from the text and/or online votes. A semi-finalist may be "gonged" during this stage and be eliminated from the competition. Summary of Semifinalists Contender's Information Results Details Semifinal Results Color Key: Quarter I Results The first quarter of the contest covered the months from June to September. The week-long showdown took place on October 1–6, 2018. Ranillo Enriquez (Visayas) and Elaine Duran (Mindanao) were declared as the first two grand finalists.
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Quarter II Results The second quarter of the contest covered the months from October 2018 to January 2019. The week-long showdown took place on January 21–26, 2019. Group Performance: ("What's Up?") John Mark Saga (Luzon) and John Michael dela Cerna (Mindanao) were announced as the 3rd and 4th grand finalists. Quarter III Results The third quarter of the contest covered the months from February to March. The week-long showdown took place on April 1-6, 2019. Group Performance: ("April Boy Regino Medley"), with guest performer, April Boy Regino Charizze Arnigo (Mindanao) and Jonas Oñate (Visayas) were announced as the 5th and 6th grand finalists. Quarter IV Results The fourth and final quarter of the contest covered the months originally from April to June later from April to August. The week-long showdown originally took place on June 24-29, 2019 later reschedule on August 26-31, 2019.
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Violeta Bayawa (Mindanao) and Julius Cawaling (Luzon) were announced as the 7th and 8th grand finalists. Instant Resbak This season, every judge will now have the power to return a losing Defending Champion from the Face-off Round using the Instant Resbak. The contestant who is given this power will then be saved and moves on to the Instant Resbak Week for a chance to participate in the rounds of the week-long grand finals (Ang Huling Tapatan). However, each judge is only entitled one save per season only (For example, if the judge uses his/her power in Quarter I, he/she can't use it again in the succeeding Quarters). Billy Crawford, Karla Estrada and Dulce did not award their Instant Resbak flags throughout the season. The Instant Resbak Round follows the mechanics below:
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For the judges, they are not allowed to join the panel in the days that their contender will participate. They will personally coach their hand-picked contenders and watch them during the performance. Four contenders will face each day and two will be selected by the non-participating judges to advance to the next round. The top two will select one song from three songs prepared. The higher scorer will perform first. The winner will be decided by the average public and judge's score to advance to the final day. The Instant Resbak week aired on September 2-6, 2019. Summary of Instant Resbakers Color Key: Results Details: Instant Resbak Details Daily Rounds (September 2-5, 2019) Final Day (September 6, 2019) Shaina Mae Allaga (Mindanao) and Rafaello Cañedo (Mindanao) were announced as the 9th and 10th grand finalists.
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Instant Resbak flag Dulce, Karla Estrada and Billy Crawford did not use their flags to someone throughout the daily rounds. They have an opportunity to select two contenders each to advance for the Ultimate Resbak. Ultimate Resbak Losing semifinalists who are not gonged, and Instant Resbakers saved by the judges after the results, may still go forward to the week-long Grand Finals dubbed as "Ang Huling Tapatan" through the Ultimate Resbak Week as wildcards. All 16 Contenders will pick their songs and performed to get two slots for the Seat of Power who earned the Highest Text Votes and Judges Scores, and It will aired on the YouTube Channel of It's Showtime Online September 6, 2019, 6:00 PM. The Ultimate Resbak started immediately after the final day of Instant Resbak Round, aired from September 7 to 14, 2019. It uses the same format as the second season, where it follows a last man standing format.
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Before the aired episodes, the semifinalists were pitted against each other to claim one of the two Seat of Powers. The Seat of Powers serves as immunity against the other contenders and gives them opportunity to select two semifinalists to pit against each other. The two contenders garnering the highest combined score from the public and judges will claim the Seat of Power. In the case where the judge's choice and the public's choice are the same person, the second placing contender for the public's choice will become the public's choice.
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In the aired episodes, the two semifinalists who are in the Seat of Power picks one semifinalist each. The picked semifinalists will be pitted against each other for a chance to dethrone the semifinalists in the Seat of Powers. The winner of the first round is selected by the majority of the judges. The winner will now challenge one of the semifinalists in the Seat of Powers to go in a sing-off. The winner is based on 50% public vote and 50% judges' score. If the challenger wins, he/she dethrones the seated semifinalist. If the seated semifinalist wins, she/he remains in the Seat of Power. The remaining contenders in the Seat of Power will move forward to the week long Grand-Finals dubbed as "Ang Huling Tapatan" while the other contenders are eliminated.
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Emil Sinagpulo (Luzon, Quarter II), Rose Ganda Sanz (Luzon, Quarter II), Marco Adobas (Metro Manila, Quarter III), Alliyah Cadeliña (Metro Manila, Quarter IV) and Shantal Cuizon (Luzon, Quarter IV) chose not to compete for the Ultimate Resbak due to their other priorities. Summary of Ultimate Resbakers Color Key: Results Details: *Inclusive of bonus prizes Seat of Power Round Color Key and Details: Ultimate Resbak Week Color Key: Jermaine Apil (Luzon) and Mariko Ledesma (Luzon) were announced as the 11th and 12th grand finalists. Final Resbak Due to the popularity of the Instant and Ultimate Resbak Rounds, the show added another phase, dubbed as Final Resbak. This will open one more slot for the Grand Finals, dubbed as "Ang Huling Tapatan". It follows the mechanics below:
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The resbakers were pitted against each other to claim the only Seat of Power. The Seat of Power serves as immunity against the other contenders. The contender garnering the highest combined score from the public will claim the Seat of Power. In the aired episodes, the resbaker who is in the Seat of Power picks three resbaker. The picked resbaker will be pitted against each other for a chance to dethrone the resbaker in the Seat of Power. The winner of the first round is selected by the majority of the judges. The winner will now challenge the resbaker in the Seat of Power to go in a sing-off. The winner is based on 50% public vote and 50% judges' score. If the challenger wins, he/she dethrones the seated resbaker. If the seated resbaker wins, she/he remains in the Seat of Power. The remaining contender in the Seat of Power will move forward to the week long Grand-Finals dubbed as "Ang Huling Tapatan" while the other contenders are eliminated.
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Mariane Osabel from Mindanao withdrew to participate from the competition due to health problems. Summary of Final Resbakers Final Seat of Power Round Color Key and Details: Final Resbak Round Color Key: Kim Nemenzo (Visayas) was announced as the 13th grand finalist (now 12th grand finalist). Ang Huling Tapatan (Grand Finals) After the Ultimate Resbak round, the week-long Grand Finals, dubbed as "Ang Huling Tapatan" (The Final Face-off), was originally scheduled from September 16 - 21 but was rescheduled to September 23 - 28, 2019, due to the addition of the new phase of the competition, the Final Resbak. It is the same as the previous season, but with modified results, used by voting percentages. The 13 finalists (now 12) from the 4 quarters and the resbak rounds will now compete for the title Grand Champion. This is the first grand finals of the regular version without a finalist from Metro Manila, and the first one that with one contender withdrew.
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Mariko Ledesma from Luzon withdrew to participate from the competition due to her personal reasons. Summary of Grand Finalists Color Key: Results Details *Inclusive of bonus prizes Daily Rounds (September 23-27, 2019) Results Details: Round 1 (September 23 and 24) Note: This is a two-day episode of this round. The results will be announced on Tuesday, September 24. Theme: Homecoming Song Round 2 (September 25) Theme: Fight Song Round 3 (September 26) Theme: Fast and Groovy Song Round 4 (September 27) Theme: Now or Never Song Live Finale (September 28, 2019) Results Details: Top 6 Theme: Journey Song Final 3 Theme: Medley Songs Elaine Duran from Mindanao emerged as the Grand Champion, followed by John Mark Saga as the second placer and John Michael dela Cerna as the third placer. Guest Performances Elimination table Color Key: Results Details
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Prize won only indicate their recent victor, not their cumulative prize won in the entirety of the season. (Example: If a contender returns as a resbaker, their prize won is reverted to zero) Tawag ng Tanghalan (TNT) Record Holder Defending champions who manages to make 10 straight wins is now a record holder and has the opportunity to select a bonus prize.
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Notable contestants Tawag ng Tanghalan Seasons 1, 2, and Kids (incomplete) John Mark Digamon appeared on Season 1 as a daily contender. He appeared again for Season 2 and became a four-time defending champion before continuing his streak for Season 3. Mary Grace Lor, Epigil Moleje, Jeffrey Dela Torre, Janine Pialan, Crismille Vallente, Ken Mariscal, Mayleah Gom-os, Ramoncito Ricafrente, Yanna Delos Reyes, Zaira Mae Alquizalas, Behnaz Denani, Gerlyn Abaño, Arnel Nadonza, Ruben Tejano, Jun Barcela, Marvin Melgar, Noreen Gamos, Claire Anne Yongco, Mariel Panillon, Marianne Rivera, Marilou Brual, Ferli Joy Oyao, Jestonie Divino, Jannine Cartagena, Erlindo Son, Queenie Joy Ocampos, Reymar Mejares and Germi Angel Salcon appeared in Season 1
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Aizel Ruga, Mara Santos, James Matthew Alfafara, Pinky Mari, Jhanewin Melo, Tom Cesar Vergara, Gwen Rea Nacionales, JM Joven, Marlou Flores, Prolifer Fesalbon, Krisna Gold Bawiin, Rodel Montecillo, Julius Cawaling, Romel Colao, Raymundo Alvarez, Evelyn Cinco, Kristel Budomo, Jelu Sarilla, Alki Dignos, Jennifer Ariate, Yessamin Temperatura, Honey Roche, Ariel Campungan, Daryl Coloma, Klarisse Claro, Dan Kristofer Ferrer, Janine Lauron, Ferlyn Suela and Paolo Marquez appeared in Season 2. Jehramae Trangia appeared twice in Season 2. On her first appearance, she dethroned semifinalist Aila Santos and became a defending champion for a day before being dethroned by Lalainne Clarisse Araña. On her second appearance, she dethroned semifinalist Douglas Dagal in season 2 and became a defending champion for three days before she was dethroned by Mau Marcelo.
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John Mark Saga was a semifinalist in Season 2 but lost in the semifinal round. He did not participate in the Ultimate Resbak round. He holds the record for having the most days of being a defending champion (15 days). Shaina Mae Allaga was a semifinalist in Tawag ng Tanghalan Kids but lost in the third round. Dominador Alviola, Jr. was a semifinalist in Season 1 but lost in the semifinal round. He participated in the Ultimate Resbak round but lost in the final round. The Voice of the Philippines / The Voice Kids / The Voice Teens Romel Colao appeared on the first season of The Voice of the Philippines, but did not receive a chair turn in the auditions. Sir Lord Lumibao appeared on the first season of The Voice of the Philippines, joining Team apl.de.ap. He was eliminated in the battles Kevin Ibañez appeared in the second season of The Voice of the Philippines, but did not receive a chair turn in the auditions.
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Karl Aris Tanhueco appeared in the second season of The Voice of the Philippines, joining Team Lea. He was eliminated in the Battles. Isaac Zamudio appeared on the first season of the Voice Kids, received three-chair turns and joined Team Sarah. He was eliminated in the Battle Rounds to Lyca Gairanod. Emil Sinagpulo appeared in the second season of The Voice of the Philippines, joining Team Lea. He was eliminated in the Battles. Don Wilson Mojado appeared on the first season of the Voice Kids, but did not receive a chair turn in the auditions. Nisha Bedaña appeared on the first season of the Voice Teens, gained three-chair turns and joined Team Sarah. She was eliminated in the Live Semifinals to Jona Marie Soquite. Alessandra Galvez appeared on the first season of the Voice Teens, gained two-chair turns and joined Team Sharon. She was eliminated in the first night of Live Shows. I Can See Your Voice
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John Andrew Manzano was selected by Vice Ganda as the winner of I Can See Your Voice. Manuel Macapugay, Jr. was selected by Claire dela Fuente as the winner of I Can See Your Voice. Kyran Oliver was selected by Salbakutah as the winner of I Can See Your Voice. JM Santos was selected by Bea Alonzo as the winner of I Can See Your Voice. Jenelyn Refulgente was selected by Gloc-9 as the winner of I Can See Your Voice. Ernesto Paredes was selected by Yassi Pressman and Sam Concepcion as the winner of I Can See Your Voice. Pilipinas Got Talent Rowell Quizon appeared on the third season of Pilipinas Got Talent. He lost the judges' votes in the semifinals. ASAP Natin 'To Yong Yting appeared on the show's new segment where viral online sensations are featured to perform with ASAP's main performers. Richard Estanes appeared on the show's new segment where viral online sensations are featured to perform with ASAP's main performers with guest performer, April Boy Regino
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Roy Limcaoco appeared on the show's new segment where viral online sensations are featured to perform with ASAP's main performers Jemril Martin appeared as a part of the band, Jammer's Session on the show's new segment where viral online sensations are featured to perform with ASAP's main performers. John Gonzaga appeared as part of the band, Jammer's Session on the show's new segment where viral online sensations are featured to perform with ASAP's main performers.
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References Notes Scores Sources External links Tawag ng Tanghalan Tawag ng Tanghalan seasons 2018 Philippine television seasons 2019 Philippine television seasons
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The Landing Craft Air Cushion (LCAC) is a class of air-cushion vehicle (hovercraft) used as landing craft by the United States Navy's Assault Craft Units and the Japan Maritime Self-Defense Force (JMSDF). They transport weapons systems, equipment, cargo and personnel of the assault elements of the Marine Air/Ground Task Force both from ship to shore and across the beach. It is to be replaced by the Ship-to-Shore Connector (SSC). Design and development Concept design for the present day LCAC began in the early 1970s with the full-scale Amphibious Assault Landing Craft (AALC) test vehicle. During the advanced development stage, two prototypes were built. JEFF A was designed and built by Aerojet General in California, with four rotating ducted propellers. JEFF B was designed and built by Bell Aerospace in New Orleans, Louisiana.
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JEFF B had two ducted rear propellers similar to the proposed SK-10 which was derived from the previous Bell SK-5 / SR.N5 hovercraft tested in Vietnam. These two craft confirmed the technical feasibility and operational capability that ultimately led to the production of the LCAC. JEFF B was selected as the design basis for today's LCAC. The JEFF A was later modified for Arctic use and deployed in Prudhoe Bay to support offshore oil drilling. The first 33 were included in the FY82-86 defense budgets, 15 in FY89, 12 each in FY90, FY91 and FY92, while seven were included in FY93. The first LCAC was delivered to the Navy in 1984 and Initial Operational Capability (IOC) was achieved in 1986. Approval for full production was granted in 1987.
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After an initial 15-craft competitive production contract was awarded to each of two companies, Textron Marine & Land Systems (TMLS) of New Orleans, La, and Avondale Gulfport Marine, TMLS was selected to build the remaining craft. A total of ninety-one LCAC have now been built. The final craft, LCAC 91, was delivered to the U.S. Navy in 2001. On June 29, 1987, approval was granted for full LCAC production. Forty-eight air-cushion landing craft were authorized and appropriated through FY 89. Lockheed Shipbuilding Company was competitively selected as a second source. The FY 1990 budget request included $219.3 million for nine craft. The FY 1991 request included full funding for 12 LCACs and advance procurement in support of the FY 1992 program (which was intended to be nine craft). The remaining 24 were funded in FY92.
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IOC - Initial Operating Capability The LCAC first deployed in 1987 aboard . LCACs are transported in and operate from all the U.S. Navy's amphibious-well deck ships including LHA, LHD, LSD and LPD. Ships capable of carrying the LCAC include the (3 LCACs), (1), (4), (1), (4–5), (2), and (2) classes. All of the planned 91 craft have been delivered to the Navy. Of these 91 LCACs, seventeen have been disassembled for Government-Furnished Equipment (GFE) or otherwise terminated for cost reasons, two are held for R&D, and 36 are in use on each coast at Little Creek, Virginia and Camp Pendleton, California. Eight minesweeping kits were acquired in 1994–1995. A service-life extension program (SLEP) to extend service life from 20 to 30 years for the remaining 72 active LCACs was begun in 2000 and is scheduled to be completed by 2018.
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The craft operates with a crew of five. In addition to beach landing, LCAC provides personnel transport, evacuation support, lane breaching, mine countermeasure operations, and Marine and Special Warfare equipment delivery. The four main engines are all used for lift and all used for main propulsion. The craft can continue to operate, at reduced capability, with two engines inoperable. They are interchangeable for redundancy. A transport model can seat 180 fully equipped troops. The LCAC's cargo capacity is . The LCAC is capable of carrying a 60 short-ton payload (up to 75 tons in an overload condition), including one M-1 Abrams tank, at speeds over 40 knots. Fuel capacity is 5000 gallons. The LCAC uses an average of 1000 gallons per hour.
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Maneuvering considerations include requiring 500 yards or more to stop and 2000 yards or more turning radius. The bow ramp is wide while the stern ramp is wide. Noise and dust levels are high with this craft. If disabled the craft is difficult to tow. In recent years spray suppression has been added to the craft's skirt to reduce interference with driver's vision. The LCAC is a dramatic innovation in modern amphibious warfare technology. It provides the capability to launch amphibious assaults from points over the horizon (OTH) from up to offshore. This decreases the risk to ships and personnel and generates greater uncertainty in the enemy's mind as to the location and timing of an assault, thereby maximizing its prospects of success. The LCAC propulsion system makes it less susceptible to mines than other assault craft or vehicles. Due to its tremendous over-the-beach capability, the LCAC can access more than 80% of the world's coastlines.
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Previously, landing craft had a top speed of approximately and could cross only 17% of the world's beach area. Assaults were made from a few miles off-shore. Its high speed complements a joint assault with helicopters, so personnel and equipment can be unloaded beyond the beach in secure landing areas. For 20 years, helicopters have provided the partial capability to launch over-the-horizon amphibious assaults. Now, with the LCAC, landing craft complement helicopters in terms of speed, tactical surprise and without exposing ships to enemy fire. The similarities between a Navy LCAC and an airplane are substantial. The craftmaster sits in a "cockpit" or command module with a headset radio on. He talks to air traffic control which for LCAC's is well-deck control located near a ship's sterngate. The ride feels like a plane in high turbulence. The craftmaster steers with a yoke, his feet are on rudder controls.
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The LCAC is similar to a helicopter in that it has six dimensions of motion. Operating the LCAC demands unique perceptual and psychomotor skills. In addition, with a machine as expensive and inherently dangerous as the LCAC, sound judgment and decision-making also play an important role.Concerns over escalating training cost, projections for an increased number of LCAC vehicles and crew, and a high attrition rate in training highlighted the importance of developing a more accurate means of selecting candidates. Attrition of operators and engineers has dropped from an initial high of 40% in 1988 to approximately 10–15% today. SLEP In Fiscal Year 2000 the Navy started an LCAC Service Life Extension Program (SLEP) to add 10 years of design life to each craft. The SLEP will be applied to 72 LCACs, extending their service life from 20 to 30 years, delaying the need to replace these versatile craft.
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Without a SLEP the first LCAC would face retirement in 2004, based on a 20-year lifespan. Naval Sea Systems Command (NAVSEA) has been working with Textron Marine and Land Systems since April 1996 on LCAC SLEP research and development. The actual SLEP modifications are planned to be conducted in two phases. Phase I. Over a period of several years electronics system recapitalization will take place at each Assault Craft Unit (ACU), where the craft are physically located. This will involve replacing current electronics components, which are increasingly becoming obsolete and unsupportable, with an open electronics architecture using easily upgraded, Commercial Off-The-Shelf (COTS) components. The new electronics suite will be more reliable and less costly to operate and maintain.
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Phase II. Buoyancy box replacement will be conducted at the Textron Marine and Land Systems facility in New Orleans, LA, where Textron will use design changes, coatings, and changes in materials to increase the LCACs resistance to corrosion. Phase II will also include the electronics upgrade of Phase I, until the entire active fleet is outfitted with the new configuration. The new buoyancy box will incorporate improvements to damage stability and trim control of the LCACs. NAVSEA transitioned from the research and development effort to the SLEP in 1999. Concurrently NAVSEA also considered additional SLEP options, including an enhanced engine to provide improved operation in excessively hot environments and an advanced skirt that is more reliable and cost effective.
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The Navy continued the LCAC Service Life Extension Program in Fiscal Year 2001. This program combines major structural improvements with Command, Control, Communications, Computer and Navigation upgrades and adds 10 years to the service life, extending it to 30 years. In FY 2001, it was funded at $19.9 million and extended the service life of 1 craft. The SLEP is planned for a total of 72 craft.
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The near-term focus will be on the "C4N" [Command, Control, Communications, Computers, and Navigation] program, to replace the crafts' obsolete equipment. This will focus on replacement of LN-66 radars with modern, high-power P-80 radar systems. Additionally, the SLEP will include an open-architecture concept, relying on modern commercial-off-the-shelf (COTS) equipment, which will allow much easier incorporation of later technology changes, such as the precision navigation system and communications systems ¾ fully interoperable with in-service and near-term future Joint systems ¾ now planned. The C4N program is to complete by 2010.
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Through 2016, the Navy will look to incorporate other important service-life enhancements: Engine upgrades (ETF-40B configuration) that will provide additional power and lift particularly in hot (, and higher) environments, reduced fuel consumption, reduced maintenance needs, and reduced lift footprint; Replacement of the buoyancy box to solve corrosion problems, incorporate hull improvements, and "reset" the fatigue-limit "clock"; Incorporation of a new (deep) skirt that will reduce drag, increase performance envelope over water and land, and reduce maintenance requirements.
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As of September 2012, there are 80 LCACs in the U.S. Navy inventory. Of these 80 LCACs, 39 LCACs have undergone the SLEP conversion, 7 more SLEP conversions are in progress and 4 are awaiting induction. The FY 2013 budget authorized 4 SLEP conversions per year through FY 2018. The last of the 72 SLEP conversions will be delivered to the Navy in FY 2020. A number of LCACs are under development and testing at the Naval Support Activity Panama City in Panama City, Florida. When the first SLEP LCAC reached its 30 years of design service in 2015, it was to gradually be retired. In 2019, at which point the inventory of LCACs had fallen to 50, the USN began receiving the new Ship-to-Shore Connector (SSC), the LCAC-100.
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The USN inventory of LCACs will continue to fall, as the SLEP LCACs are retired, until 2023, when the inventory will reach a low of 40 SLEP LCACs and SSC LCAC-100s. The inventory will remain at 40 until 2026 when the production of SSC LCAC-100s will begin to outnumber the retirement of SLEP LCACs. Current projections foresee the inventory rising to 60 SSC LCAC-100s in 2031 and 72 SSC LCAC-100s on 2034. Ship-to-Shore Connector
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The SSC LCAC-100 will have an increased payload of 73 short tons. It will have Pilot/Co-Pilot Dual Controls with a smaller crew (5) and a new Command, Control, Communications, Computers & Navigation (C4N) suite. It will also have engines offering 20% more power with new Full Authority Digital Engine Control (FADEC), a simpler and more efficient drive train with one gearbox per side, and a new Heating, Ventilation and Air Conditioning (HVAC) system. It will be constructed out of aluminum alloy 5083 which offers a lighter, stronger and performance in extreme environments, plus better corrosion resistance. Other improvements include an immersion grade wet deck coating system and its gear shaft and fan blades will be constructed with extensive composites. It will be able to operate with a 74 short ton load at a sustained speed of in NATO Sea State 3–4 (waves heights of 4.1 to 8.2 feet, averaging 6.2 feet). Japanese operations
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Six LCAC are in use by the Japan Maritime Self-Defense Force. Approval for the sale was given by the United States Government on 8 April 1994. The craft were built by Textron Marine & Land Systems in New Orleans, Louisiana. Purchase of the first craft was included in the FY93 budget, second in FY95, third and fourth in FY99 and fifth and sixth in FY00. Operators Japan Maritime Self-Defense Force (6 units) United States Navy (74 units). Assault Craft Unit 4 Assault Craft Unit 5 Naval Beach Unit 7 (Sasebo, Japan) Specifications (LCAC 1)
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Builder: Textron Marine and Land Systems/Avondale Gulfport Marine Date Deployed: 1982 Propulsion: Legacy: 4 Lycoming/AlliedSignal TF-40B gas turbines (2 for propulsion / 2 for lift); 16,000 hp sustained; 2-shrouded reversible pitch airscrews; 4-double-entry fans, centrifugal or mixed flow (lift) Service Life Extension Program (SLEP): 4 Vericor Power Systems ETF-40B gas turbines with Full Authority Digital Engine Control Length: Beam: Displacement: 87.2 long tons (88.6 metric tons) light; 170–182 long tons (173–185 metric tons) full load Speed: 40+ knots (46+ mph; 74+ km/h) with full load, 70+ knots maximum speed Range: 200 nmi at 40 knots (370 km at 75 km/h) with payload300 nmi at 35 knots (550 km at 65 km/h) with payload Crew: Five Load: 60 long tons/75 long tons overload (54/68 metric tons) Military lift: 180 troops or one MBT
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Armament: Two 12.7 mm machine guns. Gun mounts can support the M2HB .50 cal machine gun, Mk 19 Mod 3 40 mm grenade launcher, or the M60 machine gun. Tests conducted with GAU-13 30 mm gatling gun. Radar: Navigation: Marconi LN-66; I-band Source: LCAC U.S. Navy Fact File
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See also Air-cushioned landing craft Engin de débarquement amphibie rapide Lebed-class LCAC Type 726 LCAC Solgae-class LCAC Tsaplya-class LCAC – Three in service with ROKN Zubr-class LCAC References General Saunders, Stephen (RN). Jane's Fighting Ships, 2003–2004. . External links LCAC U.S. Navy Fact File Textron Marine & Land Systems LCAC page LCAC specifications on GlobalSecurity.org LCAC page on Fas.org Landing craft of the United States Navy Military hovercraft Textron
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The Fisher–Yates shuffle is an algorithm for generating a random permutation of a finite sequence—in plain terms, the algorithm shuffles the sequence. The algorithm effectively puts all the elements into a hat; it continually determines the next element by randomly drawing an element from the hat until no elements remain. The algorithm produces an unbiased permutation: every permutation is equally likely. The modern version of the algorithm is efficient: it takes time proportional to the number of items being shuffled and shuffles them in place. The Fisher–Yates shuffle is named after Ronald Fisher and Frank Yates, who first described it, and is also known as the Knuth shuffle after Donald Knuth. A variant of the Fisher–Yates shuffle, known as Sattolo's algorithm, may be used to generate random cyclic permutations of length n instead of random permutations. Fisher and Yates' original method
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The Fisher–Yates shuffle, in its original form, was described in 1938 by Ronald Fisher and Frank Yates in their book Statistical tables for biological, agricultural and medical research. Their description of the algorithm used pencil and paper; a table of random numbers provided the randomness. The basic method given for generating a random permutation of the numbers 1 through N goes as follows: Write down the numbers from 1 through N. Pick a random number k between one and the number of unstruck numbers remaining (inclusive). Counting from the low end, strike out the kth number not yet struck out, and write it down at the end of a separate list. Repeat from step 2 until all the numbers have been struck out. The sequence of numbers written down in step 3 is now a random permutation of the original numbers.
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Provided that the random numbers picked in step 2 above are truly random and unbiased, so will be the resulting permutation. Fisher and Yates took care to describe how to obtain such random numbers in any desired range from the supplied tables in a manner which avoids any bias. They also suggested the possibility of using a simpler method — picking random numbers from one to N and discarding any duplicates—to generate the first half of the permutation, and only applying the more complex algorithm to the remaining half, where picking a duplicate number would otherwise become frustratingly common.
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The modern algorithm The modern version of the Fisher–Yates shuffle, designed for computer use, was introduced by Richard Durstenfeld in 1964 and popularized by Donald E. Knuth in The Art of Computer Programming as "Algorithm P (Shuffling)". Neither Durstenfeld's article nor Knuth's first edition of The Art of Computer Programming acknowledged the work of Fisher and Yates; they may not have been aware of it. Subsequent editions of Knuth's The Art of Computer Programming mention Fisher and Yates' contribution.
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The algorithm described by Durstenfeld differs from that given by Fisher and Yates in a small but significant way. Whereas a naïve computer implementation of Fisher and Yates' method would spend needless time counting the remaining numbers in step 3 above, Durstenfeld's solution is to move the "struck" numbers to the end of the list by swapping them with the last unstruck number at each iteration. This reduces the algorithm's time complexity to compared to for the naïve implementation. This change gives the following algorithm (for a zero-based array). -- To shuffle an array a of n elements (indices 0..n-1): for i from n−1 downto 1 do j ← random integer such that 0 ≤ j ≤ i exchange a[j] and a[i] An equivalent version which shuffles the array in the opposite direction (from lowest index to highest) is: -- To shuffle an array a of n elements (indices 0..n-1): for i from 0 to n−2 do j ← random integer such that i ≤ j < n exchange a[i] and a[j]
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Examples Pencil-and-paper method As an example, we'll permute the letters from A to H using Fisher and Yates' original method. We'll start by writing the letters out on a piece of scratch paper: Now we roll a random number k from 1 to 8—let's make it 3—and strike out the kth (i.e. third) letter on the scratch pad and write it down as the result: Now we pick a second random number, this time from 1 to 7: it turns out to be 4. Now we strike out the fourth letter not yet struck off the scratch pad—that's letter E—and add it to the result: Now we pick the next random number from 1 to 6, and then from 1 to 5, and so on, always repeating the strike-out process as above: Modern method We'll now do the same thing using Durstenfeld's version of the algorithm: this time, instead of striking out the chosen letters and copying them elsewhere, we'll swap them with the last letter not yet chosen. We'll start by writing out the letters from A to H as before:
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For our first roll, we roll a random number from 1 to 8: this time it is 6, so we swap the 6th and 8th letters in the list: The next random number we roll from 1 to 7, and turns out to be 2. Thus, we swap the 2nd and 7th letters and move on: The next random number we roll is from 1 to 6, and just happens to be 6, which means we leave the 6th letter in the list (which, after the swap above, is now letter H) in place and just move to the next step. Again, we proceed the same way until the permutation is complete: At this point there's nothing more that can be done, so the resulting permutation is G E D C A H B F. Variants The "inside-out" algorithm The Fisher–Yates shuffle, as implemented by Durstenfeld, is an in-place shuffle. That is, given a preinitialized array, it shuffles the elements of the array in place, rather than producing a shuffled copy of the array. This can be an advantage if the array to be shuffled is large.
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To simultaneously initialize and shuffle an array, a bit more efficiency can be attained by doing an "inside-out" version of the shuffle. In this version, one successively places element number i into a random position among the first i positions in the array, after moving the element previously occupying that position to position i. In case the random position happens to be number i, this "move" (to the same place) involves an uninitialised value, but that does not matter, as the value is then immediately overwritten. No separate initialization is needed, and no exchange is performed. In the common case where source is defined by some simple function, such as the integers from 0 to n − 1, source can simply be replaced with the function since source is never altered during execution.
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To initialize an array a of n elements to a randomly shuffled copy of source, both 0-based: for i from 0 to n − 1 do j ← random integer such that 0 ≤ j ≤ i if j ≠ i a[i] ← a[j] a[j] ← source[i] The inside-out shuffle can be seen to be correct by induction. Assuming a perfect random number generator, every one of the n! different sequences of random numbers that could be obtained from the calls of random will produce a different permutation of the values, so all of these are obtained exactly once. The condition that checks if j ≠ i may be omitted in languages that have no problems accessing uninitialized array values. This eliminates n conditional branches at the cost of the Hn ≈ ln n + γ redundant assignments.
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Another advantage of this technique is that n, the number of elements in the source, does not need to be known in advance; we only need to be able to detect the end of the source data when it is reached. Below the array a is built iteratively starting from empty, and a.length represents the current number of elements seen. To initialize an empty array a to a randomly shuffled copy of source whose length is not known: while source.moreDataAvailable j ← random integer such that 0 ≤ j ≤ a.length if j = a.length a.append(source.next) else a.append(a[j]) a[j] ← source.next Sattolo's algorithm
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A very similar algorithm was published in 1986 by Sandra Sattolo for generating uniformly distributed cycles of (maximal) length n. The only difference between Durstenfeld's and Sattolo's algorithms is that in the latter, in step 2 above, the random number j is chosen from the range between 1 and i−1 (rather than between 1 and i) inclusive. This simple change modifies the algorithm so that the resulting permutation always consists of a single cycle. In fact, as described below, it is quite easy to accidentally implement Sattolo's algorithm when the ordinary Fisher–Yates shuffle is intended. This will bias the results by causing the permutations to be picked from the smaller set of (n−1)! cycles of length N, instead of from the full set of all n! possible permutations.
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The fact that Sattolo's algorithm always produces a cycle of length n can be shown by induction. Assume by induction that after the initial iteration of the loop, the remaining iterations permute the first n − 1 elements according to a cycle of length n − 1 (those remaining iterations are just Sattolo's algorithm applied to those first n − 1 elements). This means that tracing the initial element to its new position p, then the element originally at position p to its new position, and so forth, one only gets back to the initial position after having visited all other positions. Suppose the initial iteration swapped the final element with the one at (non-final) position k, and that the subsequent permutation of first n − 1 elements then moved it to position l; we compare the permutation π of all n elements with that remaining permutation σ of the first n − 1 elements. Tracing successive positions as just mentioned, there is no difference between π and σ until arriving at position k. But
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then, under π the element originally at position k is moved to the final position rather than to position l, and the element originally at the final position is moved to position l. From there on, the sequence of positions for π again follows the sequence for σ, and all positions will have been visited before getting back to the initial position, as required.
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As for the equal probability of the permutations, it suffices to observe that the modified algorithm involves (n−1)! distinct possible sequences of random numbers produced, each of which clearly produces a different permutation, and each of which occurs—assuming the random number source is unbiased—with equal probability. The (n−1)! different permutations so produced precisely exhaust the set of cycles of length n: each such cycle has a unique cycle notation with the value n in the final position, which allows for (n−1)! permutations of the remaining values to fill the other positions of the cycle notation. A sample implementation of Sattolo's algorithm in Python is: from random import randrange def sattolo_cycle(items) -> None: """Sattolo's algorithm.""" i = len(items) while i > 1: i = i - 1 j = randrange(i) # 0 <= j <= i-1 items[j], items[i] = items[i], items[j] Comparison with other shuffling algorithms
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The asymptotic time and space complexity of the Fisher–Yates shuffle are optimal. Combined with a high-quality unbiased random number source, it is also guaranteed to produce unbiased results. Compared to some other solutions, it also has the advantage that, if only part of the resulting permutation is needed, it can be stopped halfway through, or even stopped and restarted repeatedly, generating the permutation incrementally as needed. Naïve method The naïve method of swapping each element with another element chosen randomly from all elements is biased and fundamentally broken. Different permutations will have different probabilities of being generated, for every , because the number of different permutations, , does not evenly divide the number of random outcomes of the algorithm, . In particular, by Bertrand's postulate there will be at least one prime number between and , and this number will divide but not divide . from random import randrange
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def naive_shuffle(items) -> None: """A naive method. This is an example of what not to do -- use Fisher-Yates instead.""" n = len(items) for i in range(n): j = randrange(n) # 0 <= j <= n-1 items[j], items[i] = items[i], items[j]
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Sorting An alternative method assigns a random number to each element of the set to be shuffled and then sorts the set according to the assigned numbers. The sorting method has the same asymptotic time complexity as Fisher–Yates: although general sorting is O(n log n), numbers are efficiently sorted using Radix sort in O(n) time. Like the Fisher–Yates shuffle, the sorting method produces unbiased results. However, care must be taken to ensure that the assigned random numbers are never duplicated, since sorting algorithms typically don't order elements randomly in case of a tie. Additionally, this method requires asymptotically larger space: O(n) additional storage space for the random numbers, versus O(1) space for the Fisher–Yates shuffle. Finally, we note that the sorting method has a simple parallel implementation, unlike the Fisher–Yates shuffle, which is sequential.
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A variant of the above method that has seen some use in languages that support sorting with user-specified comparison functions is to shuffle a list by sorting it with a comparison function that returns random values. However, this is an extremely bad method: it is very likely to produce highly non-uniform distributions, which in addition depends heavily on the sorting algorithm used.
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For instance suppose quicksort is used as sorting algorithm, with a fixed element selected as first pivot element. The algorithm starts comparing the pivot with all other elements to separate them into those less and those greater than it, and the relative sizes of those groups will determine the final place of the pivot element. For a uniformly distributed random permutation, each possible final position should be equally likely for the pivot element, but if each of the initial comparisons returns "less" or "greater" with equal probability, then that position will have a binomial distribution for p = 1/2, which gives positions near the middle of the sequence with a much higher probability for than positions near the ends. Randomized comparison functions applied to other sorting methods like merge sort may produce results that appear more uniform, but are not quite so either, since merging two sequences by repeatedly choosing one of them with equal probability (until the choice is
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forced by the exhaustion of one sequence) does not produce results with a uniform distribution; instead the probability to choose a sequence should be proportional to the number of elements left in it. In fact no method that uses only two-way random events with equal probability ("coin flipping"), repeated a bounded number of times, can produce permutations of a sequence (of more than two elements) with a uniform distribution, because every execution path will have as probability a rational number with as denominator a power of 2, while the required probability 1/n! for each possible permutation is not of that form.
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In principle this shuffling method can even result in program failures like endless loops or access violations, because the correctness of a sorting algorithm may depend on properties of the order relation (like transitivity) that a comparison producing random values will certainly not have. While this kind of behaviour should not occur with sorting routines that never perform a comparison whose outcome can be predicted with certainty (based on previous comparisons), there can be valid reasons for deliberately making such comparisons. For instance the fact that any element should compare equal to itself allows using them as sentinel value for efficiency reasons, and if this is the case, a random comparison function would break the sorting algorithm. Potential sources of bias
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Care must be taken when implementing the Fisher–Yates shuffle, both in the implementation of the algorithm itself and in the generation of the random numbers it is built on, otherwise the results may show detectable bias. A number of common sources of bias have been listed below. Implementation errors
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A common error when implementing the Fisher–Yates shuffle is to pick the random numbers from the wrong range. The flawed algorithm may appear to work correctly, but it will not produce each possible permutation with equal probability, and it may not produce certain permutations at all. For example, a common off-by-one error would be choosing the index j of the entry to swap in the example above to be always strictly less than the index i of the entry it will be swapped with. This turns the Fisher–Yates shuffle into Sattolo's algorithm, which produces only permutations consisting of a single cycle involving all elements: in particular, with this modification, no element of the array can ever end up in its original position.
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Similarly, always selecting j from the entire range of valid array indices on every iteration also produces a result which is biased, albeit less obviously so. This can be seen from the fact that doing so yields nn distinct possible sequences of swaps, whereas there are only n! possible permutations of an n-element array. Since nn can never be evenly divisible by n! when n > 2 (as the latter is divisible by n−1, which shares no prime factors with n), some permutations must be produced by more of the nn sequences of swaps than others. As a concrete example of this bias, observe the distribution of possible outcomes of shuffling a three-element array [1, 2, 3]. There are 6 possible permutations of this array (3! = 6), but the algorithm produces 27 possible shuffles (33 = 27). In this case, [1, 2, 3], [3, 1, 2], and [3, 2, 1] each result from 4 of the 27 shuffles, while each of the remaining 3 permutations occurs in 5 of the 27 shuffles.
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The matrix to the right shows the probability of each element in a list of length 7 ending up in any other position. Observe that for most elements, ending up in their original position (the matrix's main diagonal) has lowest probability, and moving one slot backwards has highest probability. Modulo bias
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Doing a Fisher–Yates shuffle involves picking uniformly distributed random integers from various ranges. Most random number generators, however — whether true or pseudorandom — will only directly provide numbers in a fixed range from 0 to RAND_MAX, and in some libraries, RAND_MAX may be as low as 32767. A simple and commonly used way to force such numbers into a desired range is to apply the modulo operator; that is, to divide them by the size of the range and take the remainder. However, the need in a Fisher–Yates shuffle to generate random numbers in every range from 0–1 to 0–n almost guarantees that some of these ranges will not evenly divide the natural range of the random number generator. Thus, the remainders will not always be evenly distributed and, worse yet, the bias will be systematically in favor of small remainders.
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For example, assume that your random number source gives numbers from 0 to 99 (as was the case for Fisher and Yates' original tables), and that you wish to obtain an unbiased random number from 0 to 15. If you simply divide the numbers by 16 and take the remainder, you'll find that the numbers 0–3 occur about 17% more often than others. This is because 16 does not evenly divide 100: the largest multiple of 16 less than or equal to 100 is 6×16 = 96, and it is the numbers in the incomplete range 96–99 that cause the bias. The simplest way to fix the problem is to discard those numbers before taking the remainder and to keep trying again until a number in the suitable range comes up. While in principle this could, in the worst case, take forever, the expected number of retries will always be less than one.
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A related problem occurs with implementations that first generate a random floating-point number—usually in the range [0,1]—and then multiply it by the size of the desired range and round down. The problem here is that random floating-point numbers, however carefully generated, always have only finite precision. This means that there are only a finite number of possible floating point values in any given range, and if the range is divided into a number of segments that doesn't divide this number evenly, some segments will end up with more possible values than others. While the resulting bias will not show the same systematic downward trend as in the previous case, it will still be there. Pseudorandom generators
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An additional problem occurs when the Fisher–Yates shuffle is used with a pseudorandom number generator or PRNG: as the sequence of numbers output by such a generator is entirely determined by its internal state at the start of a sequence, a shuffle driven by such a generator cannot possibly produce more distinct permutations than the generator has distinct possible states. Even when the number of possible states exceeds the number of permutations, the irregular nature of the mapping from sequences of numbers to permutations means that some permutations will occur more often than others. Thus, to minimize bias, the number of states of the PRNG should exceed the number of permutations by at least several orders of magnitude.
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For example, the built-in pseudorandom number generator provided by many programming languages and/or libraries may often have only 32 bits of internal state, which means it can only produce 232 different sequences of numbers. If such a generator is used to shuffle a deck of 52 playing cards, it can only ever produce a very small fraction of the 52! ≈ 2225.6 possible permutations. It is impossible for a generator with less than 226 bits of internal state to produce all the possible permutations of a 52-card deck.
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No pseudorandom number generator can produce more distinct sequences, starting from the point of initialization, than there are distinct seed values it may be initialized with. Thus, a generator that has 1024 bits of internal state but which is initialized with a 32-bit seed can still only produce 232 different permutations right after initialization. It can produce more permutations if one exercises the generator a great many times before starting to use it for generating permutations, but this is a very inefficient way of increasing randomness: supposing one can arrange to use the generator a random number of up to a billion, say 230 for simplicity, times between initialization and generating permutations, then the number of possible permutations is still only 262.
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A further problem occurs when a simple linear congruential PRNG is used with the divide-and-take-remainder method of range reduction described above. The problem here is that the low-order bits of a linear congruential PRNG with modulo 2e are less random than the high-order ones: the low n bits of the generator themselves have a period of at most 2n. When the divisor is a power of two, taking the remainder essentially means throwing away the high-order bits, such that one ends up with a significantly less random value. Different rules apply if the LCG has prime modulo, but such generators are uncommon. This is an example of the general rule that a poor-quality RNG or PRNG will produce poor-quality shuffles. See also RC4, a stream cipher based on shuffling an array Reservoir sampling, in particular Algorithm R which is a specialization of the Fisher–Yates shuffle References External links An interactive example
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Combinatorial algorithms Randomized algorithms Permutations Monte Carlo methods Articles with example pseudocode Articles with example Python (programming language) code
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is a Japanese shōjo manga series by Min Ayahana. It was serialized by Shueisha in the manga magazine Ribon from 1992 to 2000 and collected in 13 bound volumes. The series is loosely based on the fairy tale Little Red Riding Hood and follows the adventures of a fumbling student magician named Chacha, who habitually wears a red hooded cloak. A 74-episode anime television series based on the manga was produced by NAS and TV Tokyo and animated by Gallop. It was first broadcast on TV Tokyo from 7 January 1994 to 30 June 1995. This was followed by a sequel original video animation (OVA) series of three episodes released between 6 December 1995 and 6 March 1996. In 1998, Cartoon Network aired an English dub of the Akazukin Chacha anime in Southeast Asia and Mandarin-speaking countries. In the anime, Chacha seeks the truth about her family and defend the kingdom against its enemies.
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Two new one-shot manga titled Akazukin Chacha N were published in the May 2011 and January 2012 issues of Cookie. Akazukin Chacha N became a monthly series published from 2012 to 2019. This version of the story takes place in modern-day Tokyo.
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Story Akazukin Chacha is the story of a young magical girl named Chacha. She lives in a cottage on Mochi-mochi Mountain with Seravy, her guardian and teacher, who is the world's greatest magician. Chacha is clumsy in casting her spells, frequently mistaking homonyms, such as summoning spiders ( in Japanese) instead of a cloud (also ). When she and her friends are in trouble, however, her spells do work. Living on the same mountain is a boy named Riiya, gifted with enormous strength, who comes from a family of werewolves. Far away from Mochi-mochi Mountain is Urizuri Mountain where Dorothy, a well known magician that has a past with Seravy, lives in a castle with her student, Shiine. Shiine is a young wizard, who is adept at casting spells and barriers, as well as transformations.