This document summarizes a computer programming assignment on sorting algorithms in Visual Basic. It includes pseudocode and source code for performing set operations (intersection, union, complement) on string arrays and sorting the results using selection sort. The program displays the results in list boxes and text boxes for testing and demonstration purposes.
Error Estimates for Multi-Penalty Regularization under General Source Conditioncsandit
In learning theory, the convergence issues of the regression problem are investigated with
the least square Tikhonov regularization schemes in both the RKHS-norm and the L 2
-norm.
We consider the multi-penalized least square regularization scheme under the general source
condition with the polynomial decay of the eigenvalues of the integral operator. One of the
motivation for this work is to discuss the convergence issues for widely considered manifold
regularization scheme. The optimal convergence rates of multi-penalty regularizer is achieved
in the interpolation norm using the concept of effective dimension. Further we also propose
the penalty balancing principle based on augmented Tikhonov regularization for the choice of
regularization parameters. The superiority of multi-penalty regularization over single-penalty
regularization is shown using the academic example and moon data set.
Fixed points of contractive and Geraghty contraction mappings under the influ...IJERA Editor
In this paper, we prove the existence of fixed points of contractive and Geraghty contraction maps in complete metric spaces under the influence of altering distances. Our results extend and generalize some of the known results.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
THE WEAK SOLUTION OF BLACK-SCHOLE’S OPTION PRICING MODEL WITH TRANSACTION COSTmathsjournal
This paper considers the equation of the type
− + + = , ( , ) ∈ ℝ × (0, );
which is the Black-Scholes option pricing model that includes the presence of transaction cost. The
existence, uniqueness and continuous dependence of the weak solution of the Black-Scholes model with
transaction cost are established.The continuity of weak solution of the parameters was discussed and
similar solution as in literature obtained.
Error Estimates for Multi-Penalty Regularization under General Source Conditioncsandit
In learning theory, the convergence issues of the regression problem are investigated with
the least square Tikhonov regularization schemes in both the RKHS-norm and the L 2
-norm.
We consider the multi-penalized least square regularization scheme under the general source
condition with the polynomial decay of the eigenvalues of the integral operator. One of the
motivation for this work is to discuss the convergence issues for widely considered manifold
regularization scheme. The optimal convergence rates of multi-penalty regularizer is achieved
in the interpolation norm using the concept of effective dimension. Further we also propose
the penalty balancing principle based on augmented Tikhonov regularization for the choice of
regularization parameters. The superiority of multi-penalty regularization over single-penalty
regularization is shown using the academic example and moon data set.
Fixed points of contractive and Geraghty contraction mappings under the influ...IJERA Editor
In this paper, we prove the existence of fixed points of contractive and Geraghty contraction maps in complete metric spaces under the influence of altering distances. Our results extend and generalize some of the known results.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
THE WEAK SOLUTION OF BLACK-SCHOLE’S OPTION PRICING MODEL WITH TRANSACTION COSTmathsjournal
This paper considers the equation of the type
− + + = , ( , ) ∈ ℝ × (0, );
which is the Black-Scholes option pricing model that includes the presence of transaction cost. The
existence, uniqueness and continuous dependence of the weak solution of the Black-Scholes model with
transaction cost are established.The continuity of weak solution of the parameters was discussed and
similar solution as in literature obtained.
Applications of Homotopy perturbation Method and Sumudu Transform for Solving...IJRES Journal
In this paper, we make use of the properties of the Sumudu transform to find the exact solution of
fractional initial-boundary value problem (FIBVP) and fractional KDV equation. The method, namely,
homotopy perturbation Sumudu transform method, is the combination of the Sumudu transform and the
HPM using He’s polynomials. This method is very powerful and professional techniques for solving different
kinds of linear and nonlinear fractional differential equations arising in different fields of science and
engineering. We also present two different examples to illustrate the preciseness and effectiveness of this
method.
2017-12, Keio University, Projection-based Regularized Dual Averaging for Sto...asahiushio1
This talk is about `Projection-based Regularized Dual Averaging (PDA)`, which is a stochastic optimizer we proposed in 2017 ICASSP paper [1]. This is also the presentation for my master thesis defense at Keio University.
[1] Asahi Ushio, Masahiro Yukawa “Projection-based Dual Averaging for Stochastic Sparse Optimization” Proceedings of ICASSP 2017
International journal of engineering and mathematical modelling vol2 no3_2015_2IJEMM
Mixed nite element approximation of reaction front propagation model in porous media is presented. The model consists of system of reaction-diffusion equations coupled with the equations of motion under the Darcy law. The existence of solution for the semi-discrete problem is established. The stability of the fully-discrete problem is
analyzed. Optimal error estimates are proved for both semi-discrete and fully-discrete approximate schemes.
2017-03, ICASSP, Projection-based Dual Averaging for Stochastic Sparse Optimi...asahiushio1
We present a variant of the regularized dual averaging (RDA) algorithm for stochastic sparse optimization. Our approach differs from the previous studies of RDA in two respects. First, a sparsity-promoting metric is employed, originated from the proportionate-type adaptive filtering algorithms. Second, the squared-distance function to a closed convex set is employed as a part of the objective functions. In the particular application of online regression, the squared-distance function is reduced to a normalized version of the typical squared-error (least square) function. The two differences yield a better sparsity-seeking capability, leading to improved convergence properties. Numerical examples show the advantages of the proposed algorithm over the existing methods including ADAGRAD and adaptive proximal forward-backward splitting (APFBS).
Paper Introduction: Combinatorial Model and Bounds for Target Set SelectionYu Liu
The paper Combinatorial Model and Bounds for Target Set Selection by Eyal Ackerman, Oren Ben-Zwi, Guy Wolfovitz:
1. a combinatorial model for the dynamic activation process of
influential networks;
2. representing Perfect Target Set Selection Problem and its
variants by linear integer programs;
3. combinatorial lower and upper bounds on the size of the
minimum Perfect Target Set
2017-07, Research Seminar at Keio University, Metric Perspective of Stochasti...asahiushio1
In this talk, I explain several major stochastic optimizers from the perspective of the metric, that is the definition of the parameter space of the model.
Fuzzy soft set is one of the recent topics developed for dealing with the uncertainties present
in most of our real life situations. The parameterization tool of soft set theory enhances the flexibility of
its application. In this paper, we have studied membership grade, power set,
-cut set , strong fuzzy
-
cut set ,some standard operation fuzzy soft set, degree of subset hood and proposed some results with
examples.
Errors in the Discretized Solution of a Differential Equationijtsrd
We study the error in the derivatives of an unknown function. We construct the discretized problem. The local truncation and global errors are discussed. The solution of discretized problem is constructed. The analytical and discretized solutions are compared. The two solution graphs are described by using MATLAB software. Wai Mar Lwin | Khaing Khaing Wai "Errors in the Discretized Solution of a Differential Equation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27937.pdfPaper URL: https://www.ijtsrd.com/mathemetics/applied-mathamatics/27937/errors-in-the-discretized-solution-of-a-differential-equation/wai-mar-lwin
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
A COMPARISON OF PARTICLE SWARM OPTIMIZATION AND DIFFERENTIAL EVOLUTIONijsc
Two modern optimization methods including Particle Swarm Optimization and Differential Evolution are
compared on twelve constrained nonlinear test functions. Generally, the results show that Differential
Evolution is better than Particle Swarm Optimization in terms of high-quality solutions, running time and
robustness.
On the Application of a Classical Fixed Point Method in the Optimization of a...BRNSS Publication Hub
This work on classical optimization reveals the Newton’s fixed point iterative method as involved in
the computation of extrema of convex functions. Such functions must be differentiable in the Banach
space such that their solution exists in the space on application of the Newton’s optimization algorithm
and convergence to the unique point is realized. These results analytically were carried as application
into the optimization of a multieffect evaporator which reveals the feasibility of theoretical and practical
optimization of the multieffect evaporator.
Applications of Homotopy perturbation Method and Sumudu Transform for Solving...IJRES Journal
In this paper, we make use of the properties of the Sumudu transform to find the exact solution of
fractional initial-boundary value problem (FIBVP) and fractional KDV equation. The method, namely,
homotopy perturbation Sumudu transform method, is the combination of the Sumudu transform and the
HPM using He’s polynomials. This method is very powerful and professional techniques for solving different
kinds of linear and nonlinear fractional differential equations arising in different fields of science and
engineering. We also present two different examples to illustrate the preciseness and effectiveness of this
method.
2017-12, Keio University, Projection-based Regularized Dual Averaging for Sto...asahiushio1
This talk is about `Projection-based Regularized Dual Averaging (PDA)`, which is a stochastic optimizer we proposed in 2017 ICASSP paper [1]. This is also the presentation for my master thesis defense at Keio University.
[1] Asahi Ushio, Masahiro Yukawa “Projection-based Dual Averaging for Stochastic Sparse Optimization” Proceedings of ICASSP 2017
International journal of engineering and mathematical modelling vol2 no3_2015_2IJEMM
Mixed nite element approximation of reaction front propagation model in porous media is presented. The model consists of system of reaction-diffusion equations coupled with the equations of motion under the Darcy law. The existence of solution for the semi-discrete problem is established. The stability of the fully-discrete problem is
analyzed. Optimal error estimates are proved for both semi-discrete and fully-discrete approximate schemes.
2017-03, ICASSP, Projection-based Dual Averaging for Stochastic Sparse Optimi...asahiushio1
We present a variant of the regularized dual averaging (RDA) algorithm for stochastic sparse optimization. Our approach differs from the previous studies of RDA in two respects. First, a sparsity-promoting metric is employed, originated from the proportionate-type adaptive filtering algorithms. Second, the squared-distance function to a closed convex set is employed as a part of the objective functions. In the particular application of online regression, the squared-distance function is reduced to a normalized version of the typical squared-error (least square) function. The two differences yield a better sparsity-seeking capability, leading to improved convergence properties. Numerical examples show the advantages of the proposed algorithm over the existing methods including ADAGRAD and adaptive proximal forward-backward splitting (APFBS).
Paper Introduction: Combinatorial Model and Bounds for Target Set SelectionYu Liu
The paper Combinatorial Model and Bounds for Target Set Selection by Eyal Ackerman, Oren Ben-Zwi, Guy Wolfovitz:
1. a combinatorial model for the dynamic activation process of
influential networks;
2. representing Perfect Target Set Selection Problem and its
variants by linear integer programs;
3. combinatorial lower and upper bounds on the size of the
minimum Perfect Target Set
2017-07, Research Seminar at Keio University, Metric Perspective of Stochasti...asahiushio1
In this talk, I explain several major stochastic optimizers from the perspective of the metric, that is the definition of the parameter space of the model.
Fuzzy soft set is one of the recent topics developed for dealing with the uncertainties present
in most of our real life situations. The parameterization tool of soft set theory enhances the flexibility of
its application. In this paper, we have studied membership grade, power set,
-cut set , strong fuzzy
-
cut set ,some standard operation fuzzy soft set, degree of subset hood and proposed some results with
examples.
Errors in the Discretized Solution of a Differential Equationijtsrd
We study the error in the derivatives of an unknown function. We construct the discretized problem. The local truncation and global errors are discussed. The solution of discretized problem is constructed. The analytical and discretized solutions are compared. The two solution graphs are described by using MATLAB software. Wai Mar Lwin | Khaing Khaing Wai "Errors in the Discretized Solution of a Differential Equation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27937.pdfPaper URL: https://www.ijtsrd.com/mathemetics/applied-mathamatics/27937/errors-in-the-discretized-solution-of-a-differential-equation/wai-mar-lwin
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
A COMPARISON OF PARTICLE SWARM OPTIMIZATION AND DIFFERENTIAL EVOLUTIONijsc
Two modern optimization methods including Particle Swarm Optimization and Differential Evolution are
compared on twelve constrained nonlinear test functions. Generally, the results show that Differential
Evolution is better than Particle Swarm Optimization in terms of high-quality solutions, running time and
robustness.
On the Application of a Classical Fixed Point Method in the Optimization of a...BRNSS Publication Hub
This work on classical optimization reveals the Newton’s fixed point iterative method as involved in
the computation of extrema of convex functions. Such functions must be differentiable in the Banach
space such that their solution exists in the space on application of the Newton’s optimization algorithm
and convergence to the unique point is realized. These results analytically were carried as application
into the optimization of a multieffect evaporator which reveals the feasibility of theoretical and practical
optimization of the multieffect evaporator.
Dynamic Programming is an algorithmic paradigm that solves a given complex problem by breaking it into subproblems and stores the results of subproblems to avoid computing the same results again.
Fixed Point Theorem in Fuzzy Metric Space Using (CLRg) Propertyinventionjournals
The object of this paper is to establish a common fixed point theorem for semi-compatible pair of self maps by using CLRg Property in fuzzy metric space.
string searching algorithms. Given two strings P and T over the same alphabet E, determine whether P occurs as a substring in T (or find in which position(s) P occurs as a substring in T). The strings P and T are called pattern and target respectively.
The simplest and most common form of mathematical induction infers that a statement involving a natural number n (that is, an integer n ≥ 0 or 1) holds for all values of n. The proof consists of two steps:
The base case (or initial case): prove that the statement holds for 0, or 1.
The induction step (or inductive step, or step case): prove that for every n, if the statement holds for n, then it holds for n + 1. In other words, assume that the statement holds for some arbitrary natural number n, and prove that the statement holds for n + 1
Young Tom Selleck: A Journey Through His Early Years and Rise to Stardomgreendigital
Introduction
When one thinks of Hollywood legends, Tom Selleck is a name that comes to mind. Known for his charming smile, rugged good looks. and the iconic mustache that has become synonymous with his persona. Tom Selleck has had a prolific career spanning decades. But, the journey of young Tom Selleck, from his early years to becoming a household name. is a story filled with determination, talent, and a touch of luck. This article delves into young Tom Selleck's life, background, early struggles. and pivotal moments that led to his rise in Hollywood.
Follow us on: Pinterest
Early Life and Background
Family Roots and Childhood
Thomas William Selleck was born in Detroit, Michigan, on January 29, 1945. He was the second of four children in a close-knit family. His father, Robert Dean Selleck, was a real estate investor and executive. while his mother, Martha Selleck, was a homemaker. The Selleck family relocated to Sherman Oaks, California. when Tom was a child, setting the stage for his future in the entertainment industry.
Education and Early Interests
Growing up, young Tom Selleck was an active and athletic child. He attended Grant High School in Van Nuys, California. where he excelled in sports, particularly basketball. His tall and athletic build made him a standout player, and he earned a basketball scholarship to the University of Southern California (U.S.C.). While at U.S.C., Selleck studied business administration. but his interests shifted toward acting.
Discovery of Acting Passion
Tom Selleck's journey into acting was serendipitous. During his time at U.S.C., a drama coach encouraged him to try acting. This nudge led him to join the Hills Playhouse, where he began honing his craft. Transitioning from an aspiring athlete to an actor took time. but young Tom Selleck became drawn to the performance world.
Early Career Struggles
Breaking Into the Industry
The path to stardom was a challenging one for young Tom Selleck. Like many aspiring actors, he faced many rejections and struggled to find steady work. A series of minor roles and guest appearances on television shows marked his early career. In 1965, he debuted on the syndicated show "The Dating Game." which gave him some exposure but did not lead to immediate success.
The Commercial Breakthrough
During the late 1960s and early 1970s, Selleck began appearing in television commercials. His rugged good looks and charismatic presence made him a popular brand choice. He starred in advertisements for Pepsi-Cola, Revlon, and Close-Up toothpaste. These commercials provided financial stability and helped him gain visibility in the industry.
Struggling Actor in Hollywood
Despite his success in commercials. breaking into large acting roles remained a challenge for young Tom Selleck. He auditioned and took on small parts in T.V. shows and movies. Some of his early television appearances included roles in popular series like Lancer, The F.B.I., and Bracken's World. But, it would take a
240529_Teleprotection Global Market Report 2024.pdfMadhura TBRC
The teleprotection market size has grown
exponentially in recent years. It will grow from
$21.92 billion in 2023 to $28.11 billion in 2024 at a
compound annual growth rate (CAGR) of 28.2%. The
teleprotection market size is expected to see
exponential growth in the next few years. It will grow
to $70.77 billion in 2028 at a compound annual
growth rate (CAGR) of 26.0%.
At Digidev, we are working to be the leader in interactive streaming platforms of choice by smart device users worldwide.
Our goal is to become the ultimate distribution service of entertainment content. The Digidev application will offer the next generation television highway for users to discover and engage in a variety of content. While also providing a fresh and
innovative approach towards advertainment with vast revenue opportunities. Designed and developed by Joe Q. Bretz
Tom Selleck Net Worth: A Comprehensive Analysisgreendigital
Over several decades, Tom Selleck, a name synonymous with charisma. From his iconic role as Thomas Magnum in the television series "Magnum, P.I." to his enduring presence in "Blue Bloods," Selleck has captivated audiences with his versatility and charm. As a result, "Tom Selleck net worth" has become a topic of great interest among fans. and financial enthusiasts alike. This article delves deep into Tom Selleck's wealth, exploring his career, assets, endorsements. and business ventures that contribute to his impressive economic standing.
Follow us on: Pinterest
Early Life and Career Beginnings
The Foundation of Tom Selleck's Wealth
Born on January 29, 1945, in Detroit, Michigan, Tom Selleck grew up in Sherman Oaks, California. His journey towards building a large net worth began with humble origins. , Selleck pursued a business administration degree at the University of Southern California (USC) on a basketball scholarship. But, his interest shifted towards acting. leading him to study at the Hills Playhouse under Milton Katselas.
Minor roles in television and films marked Selleck's early career. He appeared in commercials and took on small parts in T.V. series such as "The Dating Game" and "Lancer." These initial steps, although modest. laid the groundwork for his future success and the growth of Tom Selleck net worth. Breakthrough with "Magnum, P.I."
The Role that Defined Tom Selleck's Career
Tom Selleck's breakthrough came with the role of Thomas Magnum in the CBS television series "Magnum, P.I." (1980-1988). This role made him a household name and boosted his net worth. The series' popularity resulted in Selleck earning large salaries. leading to financial stability and increased recognition in Hollywood.
"Magnum P.I." garnered high ratings and critical acclaim during its run. Selleck's portrayal of the charming and resourceful private investigator resonated with audiences. making him one of the most beloved television actors of the 1980s. The success of "Magnum P.I." played a pivotal role in shaping Tom Selleck net worth, establishing him as a major star.
Film Career and Diversification
Expanding Tom Selleck's Financial Portfolio
While "Magnum, P.I." was a cornerstone of Selleck's career, he did not limit himself to television. He ventured into films, further enhancing Tom Selleck net worth. His filmography includes notable movies such as "Three Men and a Baby" (1987). which became the highest-grossing film of the year, and its sequel, "Three Men and a Little Lady" (1990). These box office successes contributed to his wealth.
Selleck's versatility allowed him to transition between genres. from comedies like "Mr. Baseball" (1992) to westerns such as "Quigley Down Under" (1990). This diversification showcased his acting range. and provided many income streams, reinforcing Tom Selleck net worth.
Television Resurgence with "Blue Bloods"
Sustaining Wealth through Consistent Success
In 2010, Tom Selleck began starring as Frank Reagan i
Hollywood Actress - The 250 hottest galleryZsolt Nemeth
Hollywood Actress amazon album eminent worldwide media, female-singer, actresses, alhletina-woman, 250 collection.
Highest and photoreal-print exclusive testament PC collage.
Focused television virtuality crime, novel.
The sheer afterlife of the work is activism-like hollywood-actresses point com.
173 Illustrate, 250 gallery, 154 blog, 120 TV serie logo, 17 TV president logo, 183 active hyperlink.
HD AI face enhancement 384 page plus Bowker ISBN, Congress LLCL or US Copyright.
_7 OTT App Builders to Support the Development of Your Video Applications_.pdfMega P
Due to their ability to produce engaging content more quickly, over-the-top (OTT) app builders have made the process of creating video applications more accessible. The invitation to explore these platforms emphasizes how over-the-top (OTT) applications hold the potential to transform digital entertainment.
Experience the thrill of Progressive Puzzle Adventures, like Scavenger Hunt Games and Escape Room Activities combined Solve Treasure Hunt Puzzles online.
Matt Rife Cancels Shows Due to Health Concerns, Reschedules Tour Dates.pdfAzura Everhart
Matt Rife's comedy tour took an unexpected turn. He had to cancel his Bloomington show due to a last-minute medical emergency. Fans in Chicago will also have to wait a bit longer for their laughs, as his shows there are postponed. Rife apologized and assured fans he'd be back on stage soon.
https://www.theurbancrews.com/celeb/matt-rife-cancels-bloomington-show/
Scandal! Teasers June 2024 on etv Forum.co.zaIsaac More
Monday, 3 June 2024
Episode 47
A friend is compelled to expose a manipulative scheme to prevent another from making a grave mistake. In a frantic bid to save Jojo, Phakamile agrees to a meeting that unbeknownst to her, will seal her fate.
Tuesday, 4 June 2024
Episode 48
A mother, with her son's best interests at heart, finds him unready to heed her advice. Motshabi finds herself in an unmanageable situation, sinking fast like in quicksand.
Wednesday, 5 June 2024
Episode 49
A woman fabricates a diabolical lie to cover up an indiscretion. Overwhelmed by guilt, she makes a spontaneous confession that could be devastating to another heart.
Thursday, 6 June 2024
Episode 50
Linda unwittingly discloses damning information. Nhlamulo and Vuvu try to guide their friend towards the right decision.
Friday, 7 June 2024
Episode 51
Jojo's life continues to spiral out of control. Dintle weaves a web of lies to conceal that she is not as successful as everyone believes.
Monday, 10 June 2024
Episode 52
A heated confrontation between lovers leads to a devastating admission of guilt. Dintle's desperation takes a new turn, leaving her with dwindling options.
Tuesday, 11 June 2024
Episode 53
Unable to resort to violence, Taps issues a verbal threat, leaving Mdala unsettled. A sister must explain her life choices to regain her brother's trust.
Wednesday, 12 June 2024
Episode 54
Winnie makes a very troubling discovery. Taps follows through on his threat, leaving a woman reeling. Layla, oblivious to the truth, offers an incentive.
Thursday, 13 June 2024
Episode 55
A nosy relative arrives just in time to thwart a man's fatal decision. Dintle manipulates Khanyi to tug at Mo's heartstrings and get what she wants.
Friday, 14 June 2024
Episode 56
Tlhogi is shocked by Mdala's reaction following the revelation of their indiscretion. Jojo is in disbelief when the punishment for his crime is revealed.
Monday, 17 June 2024
Episode 57
A woman reprimands another to stay in her lane, leading to a damning revelation. A man decides to leave his broken life behind.
Tuesday, 18 June 2024
Episode 58
Nhlamulo learns that due to his actions, his worst fears have come true. Caiphus' extravagant promises to suppliers get him into trouble with Ndu.
Wednesday, 19 June 2024
Episode 59
A woman manages to kill two birds with one stone. Business doom looms over Chillax. A sobering incident makes a woman realize how far she's fallen.
Thursday, 20 June 2024
Episode 60
Taps' offer to help Nhlamulo comes with hidden motives. Caiphus' new ideas for Chillax have MaHilda excited. A blast from the past recognizes Dintle, not for her newfound fame.
Friday, 21 June 2024
Episode 61
Taps is hungry for revenge and finds a rope to hang Mdala with. Chillax's new job opportunity elicits mixed reactions from the public. Roommates' initial meeting starts off on the wrong foot.
Monday, 24 June 2024
Episode 62
Taps seizes new information and recruits someone on the inside. Mary's new job
From the Editor's Desk: 115th Father's day Celebration - When we see Father's day in Hindu context, Nanda Baba is the most vivid figure which comes to the mind. Nanda Baba who was the foster father of Lord Krishna is known to provide love, care and affection to Lord Krishna and Balarama along with his wife Yashoda; Letter’s to the Editor: Mother's Day - Mother is a precious life for their children. Mother is life breath for her children. Mother's lap is the world happiness whose debt can never be paid.
Skeem Saam in June 2024 available on ForumIsaac More
Monday, June 3, 2024 - Episode 241: Sergeant Rathebe nabs a top scammer in Turfloop. Meikie is furious at her uncle's reaction to the truth about Ntswaki.
Tuesday, June 4, 2024 - Episode 242: Babeile uncovers the truth behind Rathebe’s latest actions. Leeto's announcement shocks his employees, and Ntswaki’s ordeal haunts her family.
Wednesday, June 5, 2024 - Episode 243: Rathebe blocks Babeile from investigating further. Melita warns Eunice to stay clear of Mr. Kgomo.
Thursday, June 6, 2024 - Episode 244: Tbose surrenders to the police while an intruder meddles in his affairs. Rathebe's secret mission faces a setback.
Friday, June 7, 2024 - Episode 245: Rathebe’s antics reach Kganyago. Tbose dodges a bullet, but a nightmare looms. Mr. Kgomo accuses Melita of witchcraft.
Monday, June 10, 2024 - Episode 246: Ntswaki struggles on her first day back at school. Babeile is stunned by Rathebe’s romance with Bullet Mabuza.
Tuesday, June 11, 2024 - Episode 247: An unexpected turn halts Rathebe’s investigation. The press discovers Mr. Kgomo’s affair with a young employee.
Wednesday, June 12, 2024 - Episode 248: Rathebe chases a criminal, resorting to gunfire. Turf High is rife with tension and transfer threats.
Thursday, June 13, 2024 - Episode 249: Rathebe traps Kganyago. John warns Toby to stop harassing Ntswaki.
Friday, June 14, 2024 - Episode 250: Babeile is cleared to investigate Rathebe. Melita gains Mr. Kgomo’s trust, and Jacobeth devises a financial solution.
Monday, June 17, 2024 - Episode 251: Rathebe feels the pressure as Babeile closes in. Mr. Kgomo and Eunice clash. Jacobeth risks her safety in pursuit of Kganyago.
Tuesday, June 18, 2024 - Episode 252: Bullet Mabuza retaliates against Jacobeth. Pitsi inadvertently reveals his parents’ plans. Nkosi is shocked by Khwezi’s decision on LJ’s future.
Wednesday, June 19, 2024 - Episode 253: Jacobeth is ensnared in deceit. Evelyn is stressed over Toby’s case, and Letetswe reveals shocking academic results.
Thursday, June 20, 2024 - Episode 254: Elizabeth learns Jacobeth is in Mpumalanga. Kganyago's past is exposed, and Lehasa discovers his son is in KZN.
Friday, June 21, 2024 - Episode 255: Elizabeth confirms Jacobeth’s dubious activities in Mpumalanga. Rathebe lies about her relationship with Bullet, and Jacobeth faces theft accusations.
Monday, June 24, 2024 - Episode 256: Rathebe spies on Kganyago. Lehasa plans to retrieve his son from KZN, fearing what awaits.
Tuesday, June 25, 2024 - Episode 257: MaNtuli fears for Kwaito’s safety in Mpumalanga. Mr. Kgomo and Melita reconcile.
Wednesday, June 26, 2024 - Episode 258: Kganyago makes a bold escape. Elizabeth receives a shocking message from Kwaito. Mrs. Khoza defends her husband against scam accusations.
Thursday, June 27, 2024 - Episode 259: Babeile's skillful arrest changes the game. Tbose and Kwaito face a hostage crisis.
Friday, June 28, 2024 - Episode 260: Two women face the reality of being scammed. Turf is rocked by breaking
Meet Dinah Mattingly – Larry Bird’s Partner in Life and Loveget joys
Get an intimate look at Dinah Mattingly’s life alongside NBA icon Larry Bird. From their humble beginnings to their life today, discover the love and partnership that have defined their relationship.
1. MAKALAH PEMROGRAMAN KOMPUTER 1
Disusun untuk memenuhi tugas Ujian Tengah Semester
Mata Kuliah Pemrogaman Komputer 1
Dosen Pengampu:
Wildan Suharso. S.Si
Oleh :
Muhammad Sukron 10610067
JURUSAN MATEMATIKA
FAKULTAS SAINS DAN TEKNOLOGI
UNIVERSITAS ISLAM NEGERI MAULANA MALIK
IBRAHIM MALANG
2012
2. BAB I
FLOWCHART
1.1 Irisan, Gabungan dan Komplemen
Start
dipilih() as char
nilai, nilai2 as integer
f, g,h as string
A()as string = a.Split(pecah)
B()as string = b.Split(pecah)
S()as string = s.Split(pecah)
f = TextBox1.Text
g = TextBox2.Text
h = TextBox3.Text
For i = 0 To Ubound(A)
For j = 0 To Ubound(B)
If A (i)= B (j)
B A C
3. B A C
ListBox1.Items.Add(A (i))
for i=0 to Ubound (A)
ListBox2.Items.Add(A(i))
for j = 0 to Ubound (B)
for k = 0 to Ubound (A)
If B(j) < > A(k)
E D F
4. E D F
nilai = nilai + 1
If nilai > A.Length - 1
ListBox2.Items.Add(B(j))
nilai = 0
for i = 0 to Ubound (S)
for j = 0 to Ubound (A)
I H J
5. I H J
If S(i) <> A(j)
Nilai2 += 1
If x > A.Length -
1
ListBox3.Items.Add(S(i))
Nilai2 = 0
Stop
6. 1.2 Selection Sort irisan A dan B
Start
i, r , q, m, n As Integer
r = ListBox1.Items.Count - 1
selec_irisan(r) As Integer
For i = 0 To r
Selec_irisan(i) = ListBox1.Items(i)
For i = 0 To
selec_irisan. length
1
m = i
For q = i + 1 To
selec_irisan.Length- 1
M K N
7. M K N
If selec_ irisan (q) <
selec_irisan(m)
m=q
If m <> i
n = selec_irisan (i)
selec_irisan(i) = selec_irisan(m)
selec_irisan(m) = n
For p = 0 To
selec_irisan.Length - 1
TextBox4.AppendText(CStr(se
lec_irisan(p)) & " ")
Stop
8. 1.3 Selection Sort Gabungan A dan B
Start
min, temp, y As Integer
y = ListBox2.Items.Count - 1
gabunganAB(x) As Integer
For i = 0 To y
Selec_gabungan (i) = ListBox2.Items(i)
For i = 0 To
Selc_gabungn.Length-1
min = i
For j = i + 1 To
Selec_gabungan.Length - 1
P O Q
9. P O Q
If Selec_gabungan (j)
< Selec_gabungan
(min)
min = j
If min <> i
temp = Selec_gabungan (i)
Selec_gabungan (i) = Selec_gabungan(m)
Selec_gabungan (min) = temp
For p= 0 To
Selec_gabungan.Length
-1
TextBox4.AppendText(CStr(ga
Selec_gabungan (p)) & " ")
Stop
10. 1.4 Selection Sort komplemen A terhadap S
Start
km, kp, z As Integer
z = ListBox3.Items.Count - 1
selec_komplemn(z) As Integer
For i = 0 To z
selec_komplemn (i) = ListBox3.Items(i)
For i = 0 To
selc_komplmn.Length-1
km = i
For j = i + 1 To
selec_komplemn.Length - 1
S R T
11. P O Q
If selec_komplemn (j)
< selc_komplmn (km)
km = j
If km < > i
kp = selec_komplemn (i)
selec_komplmn (i) = selc_komplmn (km)
selec_komplemn (km) = kp
For p= 0 To
selec_komplemn.Length
-1
TextBox4.AppendText(CStr(k
selec_komplemn (p)) & " ")
Stop
12. BAB II
PESEUDOCODE
2.1 Irisan
For i = 0 to Ubound[A] {
For j = 0 to Ubound[B]
If A[i]=B[j]
}
}
2.2 Gabungan
For i = 0 to Ubound[B] {
For j = 0 to Ubound[A]
If B[i]< >A[j]
Nilai = nilai + 1
If nilai > A.length – 1
Nilai = 0
}
}
2.3 Komplemen
For i = 0 to Ubound[S] {
13. For j = 0 to Ubound[A]
If S[i]< >A[j]
Nilai2 + = 1
If nilai2 > A.length – 1
Nilai2 = 0
}
}
2.4 Selection Irisan
For i = 0 to selec_irisan.length – 1{
m=i
for q = i + 1 to selec_irisan.length – 1
if selec_irisan [q] < selec_irisan [m]
m=0
if m < > i
n= selec_irisan [i]
selec_irisan [i] = selec_irisan [m]
selec_irisan [m] = n
}
}
14. 2.5 Selection Gabungan
For i = 0 to selec_gabungan.length – 1{
min = i
for j = i + 1 to selec_gabunga.length – 1
if selec_gabungan [j] < selec_gabungan [min]
min = j
if min < > i
temp = selec_gabungan [i]
selec_ gabungan [i] = selec_gabungan [min]
selec_ gabungan [min] = temp
}
}
2.6 Selection Komplemen
For i = 0 to selec_komplemen.length – 1{
km = i
for j = i + 1 to selec_komplemen.length – 1
if selec_komplemen [j] < selec_komplemen [km]
km = j
15. if km < > i
kp = selec_komplemen [i]
selec_komplemen [i] = selec_komplemen [km]
selec_komplemen [km] = kp
}
}
17. BAB IV
SOURCE
Public Class Form1
Private Sub Button1_Click(ByVal sender As
System.Object, ByVal e As System.EventArgs) Handles
Button1.Click
Dim dipilih() As Char = {".", ",", "*", " "}
Dim f, g, h As String
Dim nilai, nilai2 As Integer
nilai = 0
nilai2 = 0
f = TextBox1.Text
g = TextBox2.Text
h = TextBox3.Text
Dim A() As String = f.Split(dipilih)
Dim B() As String = g.Split(dipilih)
Dim S() As String = h.Split(dipilih)
'irisan
For i = 0 To UBound(A)
For j = 0 To UBound(B)
If A(i) = B(j) Then
ListBox1.Items.Add(A(i))
End If
Next
Next
'gabungan
For i = 0 To UBound(A)
ListBox2.Items.Add(A(i))
Next
For i = 0 To UBound(B)
For j = 0 To UBound(A)
If B(i) <> A(j) Then
nilai = nilai + 1
End If
Next
If nilai > A.Length - 1 Then
ListBox2.Items.Add(B(i))
End If
nilai = 0
Next
'komplemen
18. For i = 0 To UBound(S)
For j = 0 To UBound(A)
If S(i) <> A(j) Then
nilai2 += 1
End If
Next
If nilai2 > A.Length - 1 Then
ListBox3.Items.Add(S(i))
End If
nilai2 = 0
Next
End Sub
Private Sub Label13_Click(ByVal sender As
System.Object, ByVal e As System.EventArgs) Handles
Label13.Click
Refresh()
TextBox1.Text = ""
TextBox2.Text = ""
TextBox3.Text = ""
TextBox4.Text = ""
TextBox5.Text = ""
TextBox6.Text = ""
ListBox1.Text = ""
ListBox2.Text = ""
ListBox3.Text = ""
End Sub
Private Sub Label15_Click(ByVal sender As
System.Object, ByVal e As System.EventArgs) Handles
Label15.Click
MsgBox("muhammad sukron" + vbCrLf + "10610067")
End Sub
Private Sub Button2_Click(ByVal sender As
System.Object, ByVal e As System.EventArgs) Handles
Button2.Click
'sort irirsan
Dim i, r, q, m, n As Integer
r = ListBox1.Items.Count - 1
Dim selec_irisan(r) As Integer
For i = 0 To r
selec_irisan(i) = ListBox1.Items(i)
Next
For i = 0 To selec_irisan.Length - 1
m = i
For q = i + 1 To selec_irisan.Length - 1
19. If selec_irisan(q) < selec_irisan(m) Then
m = q
End If
Next
If m <> i Then
n = selec_irisan(i)
selec_irisan(i) = selec_irisan(m)
selec_irisan(m) = n
End If
Next
For p = 0 To selec_irisan.Length - 1
TextBox4.AppendText(" " +
CStr(selec_irisan(p)))
Next
'sort gabungan
Dim min, temp, y As Integer
y = ListBox2.Items.Count - 1
Dim selec_gabungan(y) As Integer
For i = 0 To y
selec_gabungan(i) = ListBox2.Items(i)
Next
For i = 0 To selec_gabungan.Length - 1
min = i
For j = i + 1 To selec_gabungan.Length - 1
If selec_gabungan(j) <
selec_gabungan(min) Then
min = j
End If
Next
If min <> i Then
temp = selec_gabungan(i)
selec_gabungan(i) = selec_gabungan(min)
selec_gabungan(min) = temp
End If
Next
For p = 0 To selec_gabungan.Length - 1
TextBox5.AppendText(" " +
CStr(selec_gabungan(p)))
Next
'sort komplemen
Dim km, kp, z As Integer
z = ListBox3.Items.Count - 1
Dim selec_komplemen(z) As Integer
20. For i = 0 To z
selec_komplemen(i) = ListBox3.Items(i)
Next
For i = 0 To selec_komplemen.Length - 1
km = i
For j = i + 1 To selec_komplemen.Length - 1
If selec_komplemen(j) <
selec_komplemen(km) Then
km = j
End If
Next
If km <> i Then
kp = selec_komplemen(i)
selec_komplemen(i) = selec_komplemen(km)
selec_komplemen(km) = kp
End If
Next
For p = 0 To selec_komplemen.Length - 1
TextBox6.AppendText(" " +
CStr(selec_komplemen(p)))
Next
End Sub
End Class