Downloads & Free Reading Options - Results

The talk will consist of two parts. In the first part, I will present prior work aimed at developing new algorithms for materials science applications. I developed a novel numerical method to optimize the shape of mechanical parts and maximize their strength. This optimization problem was extremely challenging as it involved changing the topology and therefore classical optimization methods do not apply. A similar idea can be applied to model shape memory alloys and plasticity in metals. In this project, the optimization led to the construction of a tree of laminated microstructures. Constraints from mechanical equilibrium were used to construct an adaptive tree and to determine the optimal number of levels. The second part involves more recent work. I will present the implementation of a new heat flux algorithm to understand failures in micro-devices in LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator); LAMMPS is a high performance code which was benchmarked on Blue Gene L with 90% parallel efficiency. Also I am currently extending the capabilities of ParaDiS (Parallel Dislocation Simulator), another high performance code which has run on 135k processors of Blue Gene L. ©2008 Microsoft Corporation. All rights reserved.

Wiki - List of Open Problems in Sublinear Algorithms

Nathan Matias is a professor at Cornell University and leads the Citizens and Technology Lab. He believes that the strong tradition of scrappy, responsive, citizen science (which has led to positive changes in food safety and quality assurance regulations) can also bring positive changes to how algorithms impact our lives. The Citizens and Technology Lab, Cornell UniversityMozilla Foundation- volunteer opportunities  Algorithmic Justice League Joy Buolamwini, TED Talk, Fighting Bias in AlgorithmsThe MarkupConsumer ReportsThe History of the Good Housekeeping InstituteElinor Ostrom's Work on Governing The Commons: An Appreciation, LSEKurt Lewin, American Social Psychologist, Encyclopedia BritanicaDemocratic, Authoritarian, Laissez-Faire: What Type Of Leader Are You?, Forbes 2019 Learn more about your ad-choices at https://www.iheartpodcastnetwork.comSee omnystudio.com/listener for privacy information.

YouTube's algorithms are abhorrent in a new way, details on the next Playstation console, Google makes nice with developers, and three interesting sides to the TikTok story.Sponsors:EveryKey.com 20% off with promocode RIDE20 Mealime AppLinks: YouTube shows 9/11 link on live videos of unrelated Notre Dame fire (The Verge)EXCLUSIVE: WHAT TO EXPECT FROM SONY'S NEXT-GEN PLAYSTATION (Wired) 15 MONTHS OF FRESH HELL INSIDE FACEBOOK (Wired) Next major macOS version will include standalone Music, Podcasts, and TV apps, Books app gets major redesign (9to5Mac) Improving the update process with your feedback (Android Developer's Blog) AT&T sells Hulu stake, valuing the video streaming company at $15 billion (CNBC) Short video app TikTok extends reach in global markets, sees in-app purchases surge more than 200 per cent (South China Morning Post)TikTok downloads ordered to be blocked on iOS and Android in India over porn and other illegal content (TechCrunch) TikTok sensation Lil Nas X rewrites the rules of country music (Axios)

YouTube's algorithms are abhorrent in a new way, details on the next Playstation console, Google makes nice with developers, and three interesting sides to the TikTok story.Sponsors:EveryKey.com 20% off with promocode RIDE20 Mealime AppLinks: YouTube shows 9/11 link on live videos of unrelated Notre Dame fire (The Verge)EXCLUSIVE: WHAT TO EXPECT FROM SONY'S NEXT-GEN PLAYSTATION (Wired) 15 MONTHS OF FRESH HELL INSIDE FACEBOOK (Wired) Next major macOS version will include standalone Music, Podcasts, and TV apps, Books app gets major redesign (9to5Mac) Improving the update process with your feedback (Android Developer's Blog) AT&T sells Hulu stake, valuing the video streaming company at $15 billion (CNBC) Short video app TikTok extends reach in global markets, sees in-app purchases surge more than 200 per cent (South China Morning Post)TikTok downloads ordered to be blocked on iOS and Android in India over porn and other illegal content (TechCrunch) TikTok sensation Lil Nas X rewrites the rules of country music (Axios)

YouTube's algorithms are abhorrent in a new way, details on the next Playstation console, Google makes nice with developers, and three interesting sides to the TikTok story.Sponsors:EveryKey.com 20% off with promocode RIDE20 Mealime AppLinks: YouTube shows 9/11 link on live videos of unrelated Notre Dame fire (The Verge)EXCLUSIVE: WHAT TO EXPECT FROM SONY'S NEXT-GEN PLAYSTATION (Wired) 15 MONTHS OF FRESH HELL INSIDE FACEBOOK (Wired) Next major macOS version will include standalone Music, Podcasts, and TV apps, Books app gets major redesign (9to5Mac) Improving the update process with your feedback (Android Developer's Blog) AT&T sells Hulu stake, valuing the video streaming company at $15 billion (CNBC) Short video app TikTok extends reach in global markets, sees in-app purchases surge more than 200 per cent (South China Morning Post)TikTok downloads ordered to be blocked on iOS and Android in India over porn and other illegal content (TechCrunch) TikTok sensation Lil Nas X rewrites the rules of country music (Axios)

YouTube's algorithms are abhorrent in a new way, details on the next Playstation console, Google makes nice with developers, and three interesting sides to the TikTok story.Sponsors:EveryKey.com 20% off with promocode RIDE20 Mealime AppLinks: YouTube shows 9/11 link on live videos of unrelated Notre Dame fire (The Verge)EXCLUSIVE: WHAT TO EXPECT FROM SONY'S NEXT-GEN PLAYSTATION (Wired) 15 MONTHS OF FRESH HELL INSIDE FACEBOOK (Wired) Next major macOS version will include standalone Music, Podcasts, and TV apps, Books app gets major redesign (9to5Mac) Improving the update process with your feedback (Android Developer's Blog) AT&T sells Hulu stake, valuing the video streaming company at $15 billion (CNBC) Short video app TikTok extends reach in global markets, sees in-app purchases surge more than 200 per cent (South China Morning Post)TikTok downloads ordered to be blocked on iOS and Android in India over porn and other illegal content (TechCrunch) TikTok sensation Lil Nas X rewrites the rules of country music (Axios)

Data fusion in wireless sensor networks can improve the performance of a network by eliminating redundancy and power consumption, ensuring fault-tolerance between sensors, and managing e®ectively the available com- munication bandwidth between network components. This thesis considers a data fusion approach applied to wireless sensor networks based on fuzzy logic theory. In particular, a cluster-based hierarchical design in wire- less sensor networks is explored combined with two data fusion methods based on fuzzy logic theory. A data fusion algorithm is presented and tested using Mamdani and Tsukamoto fuzzy inference methods. In addition, a concept related to the appropriate queuing models is presented based on classical queuing theory. Results show that the Mamdani method gives better results than the Tsukamoto approach for the two implementations considered. We noted that the proposed algorithm requires low processing and computational power. As a result, it can be applied to WSNs to provide optimal data fusion and ensures maximum sensor lifetime and minimum time delay.

A piezoelectric shoe is a type of footwear that integrates piezoelectric materials within its sole and heel to generate electricity from mechanical pressure. These materials produce electrical energy when compressed by the wearers movement, converting kinetic energy into usable electrical power. This energy can then be harnessed to power electronic devices or charge batteries, offering a sustainable energy solution. The technology holds significant potential for applications in various fields, including sports and fitness tracking, military operations, and emergency response systems. As wearable technology continues to evolve, the piezoelectric shoe stands out as an innovative way to tap into the bodys natural energy. By transforming the mechanical energy produced from walking or running into electricity, it provides an efficient means of energy harvesting. This abstract highlights the core functionality, potential benefits, and future applications of piezoelectric shoes, demonstrating how they could revolutionize energy harvesting in wearable devices. Mariya Zareen "Phishing Website Detection using Machine Learning Algorithms: A Data-Driven Approach to Cybersecurity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-3 , June 2025, URL: https://www.ijtsrd.com/papers/ijtsrd79945.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/79945/phishing-website-detection-using-machine-learning-algorithms-a-datadriven-approach-to-cybersecurity/mariya-zareen

home

home

home

home

home

This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Shuffle Frog Leaping Algorithm (SFLA) and Particle Swarm Optimization are used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 45-bus radial distribution systems.

Random Structures & Algorithms 1996: Volume 9 , Issue Index. Digitized from IA1629815-03 . Previous issue: sim_random-structures-algorithms_1996-07_8_4 . Next issue: sim_random-structures-algorithms_1996_9_contents .

The IETF's standard congestion control schemes have been widely shown to be inadequate for various environments (e.g., high-speed networks). Recent research has yielded many alternate congestion control schemes that significantly differ from the IETF's congestion control principles. Using these new congestion control schemes in the global Internet has possible ramifications to both the traffic using the new congestion control and to traffic using the currently standardized congestion control. Therefore, the IETF must proceed with caution when dealing with alternate congestion control proposals. The goal of this document is to provide guidance for considering alternate congestion control algorithms within the IETF. This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements.

This document is intended to be a source of information about the Russian Federal standard for electronic encryption, decryption, and message authentication algorithms (GOST 28147-89), which is one of the Russian cryptographic standard algorithms called GOST algorithms). Recently, Russian cryptography is being used in Internet applications, and this document has been created as information for developers and users of GOST 28147-89 for encryption, decryption, and message authentication. This document is not an Internet Standards Track specification; it is published for informational purposes.

This document is intended to be a source of information about the Russian Federal standard for electronic encryption, decryption, and message authentication algorithms (GOST 28147-89), which is one of the Russian cryptographic standard algorithms called GOST algorithms). Recently, Russian cryptography is being used in Internet applications, and this document has been created as information for developers and users of GOST 28147-89 for encryption, decryption, and message authentication. This document is not an Internet Standards Track specification; it is published for informational purposes.

Do you ever long for the good old days? Nostalgia can be such a wonderful thing. We begin this episode with a look at why the past can seem so idyllic and wonderful and what the positive effects of looking back are. http://science.howstuffworks.com/life/inside-the-mind/human-brain/nostalgia4.htmDo you really understand what algorithms are and how they work? You probably should because algorithms are used so often to influence us in making decisions on what to buy, what movies to watch or who to date. Kartik Hosanagar is a professor of technology, digital business and marketing at the Wharton School at the University of Pennsylvania and author of the book A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in control (https://amzn.to/2JuStcy). Listen and hear the good and the bad about how algorithms have become part of everyday life."Sit up straight and don't slouch!" How many times have you heard that or said that to someone else? It turns out that posture is really important and I'll explain why. http://www.dailymail.co.uk/health/article-2295420/Stand-straight-stay-fightingfit-From-raised-blood-pressure-bloated-stomach-surprising-effectsbad-posture.html#ixzz2OBJ72FZQSome ideas really stick and others quickly fade away. Why? What makes an idea sticky? Chip Heath, author of the book Made to Stick : Why Some Ideas Thrive and Others Die (https://amzn.to/2Y9YaQu) joins me to talk about his research into what makes a really good idea resonate with people. The advice he gives is very practical and will help you create ideas that people will fall in love with. This Week's Sponsors-Skillshare. For 2 months free access to over 25,000 classes go to www.Skillshare.com/something-ADT. For more information on smart home security go to www.ADT.com -Capital One. Visit www.CapitalOne.com What's in your wallet? Learn more about your ad choices. Visit podcastchoices.com/adchoices

Do you ever long for the good old days? Nostalgia can be such a wonderful thing. We begin this episode with a look at why the past can seem so idyllic and wonderful and what the positive effects of looking back are. http://science.howstuffworks.com/life/inside-the-mind/human-brain/nostalgia4.htmDo you really understand what algorithms are and how they work? You probably should because algorithms are used so often to influence us in making decisions on what to buy, what movies to watch or who to date. Kartik Hosanagar is a professor of technology, digital business and marketing at the Wharton School at the University of Pennsylvania and author of the book A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in control (https://amzn.to/2JuStcy). Listen and hear the good and the bad about how algorithms have become part of everyday life."Sit up straight and don't slouch!" How many times have you heard that or said that to someone else? It turns out that posture is really important and I'll explain why. http://www.dailymail.co.uk/health/article-2295420/Stand-straight-stay-fightingfit-From-raised-blood-pressure-bloated-stomach-surprising-effectsbad-posture.html#ixzz2OBJ72FZQSome ideas really stick and others quickly fade away. Why? What makes an idea sticky? Chip Heath, author of the book Made to Stick : Why Some Ideas Thrive and Others Die (https://amzn.to/2Y9YaQu) joins me to talk about his research into what makes a really good idea resonate with people. The advice he gives is very practical and will help you create ideas that people will fall in love with. This Week's Sponsors-Skillshare. For 2 months free access to over 25,000 classes go to www.Skillshare.com/something-ADT. For more information on smart home security go to www.ADT.com -Capital One. Visit www.CapitalOne.com What's in your wallet? Learn more about your ad choices. Visit podcastchoices.com/adchoices

Do you ever long for the good old days? Nostalgia can be such a wonderful thing. We begin this episode with a look at why the past can seem so idyllic and wonderful and what the positive effects of looking back are. http://science.howstuffworks.com/life/inside-the-mind/human-brain/nostalgia4.htmDo you really understand what algorithms are and how they work? You probably should because algorithms are used so often to influence us in making decisions on what to buy, what movies to watch or who to date. Kartik Hosanagar is a professor of technology, digital business and marketing at the Wharton School at the University of Pennsylvania and author of the book A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in control (https://amzn.to/2JuStcy). Listen and hear the good and the bad about how algorithms have become part of everyday life."Sit up straight and don't slouch!" How many times have you heard that or said that to someone else? It turns out that posture is really important and I'll explain why. http://www.dailymail.co.uk/health/article-2295420/Stand-straight-stay-fightingfit-From-raised-blood-pressure-bloated-stomach-surprising-effectsbad-posture.html#ixzz2OBJ72FZQSome ideas really stick and others quickly fade away. Why? What makes an idea sticky? Chip Heath, author of the book Made to Stick : Why Some Ideas Thrive and Others Die (https://amzn.to/2Y9YaQu) joins me to talk about his research into what makes a really good idea resonate with people. The advice he gives is very practical and will help you create ideas that people will fall in love with. This Week's Sponsors-Skillshare. For 2 months free access to over 25,000 classes go to www.Skillshare.com/something-ADT. For more information on smart home security go to www.ADT.com -Capital One. Visit www.CapitalOne.com What's in your wallet? Learn more about your ad choices. Visit podcastchoices.com/adchoices

We welcome Kelvin and Vincent to the show to discuss Data Structures and Algorithms in Swift.

We welcome Kelvin and Vincent to the show to discuss Data Structures and Algorithms in Swift.

We welcome Kelvin and Vincent to the show to discuss Data Structures and Algorithms in Swift.

We welcome Kelvin and Vincent to the show to discuss Data Structures and Algorithms in Swift.

本教程主要介绍SIMCA 17中光谱预处理算法的扩展库 更多SIMCA软件视频教程，登录 科学软件网 www.sciencesoftware.com.cn 观看。

本教程主要介绍SIMCA 17中光谱预处理算法的扩展库 更多SIMCA软件视频教程，登录 科学软件网 www.sciencesoftware.com.cn 观看。

本教程主要介绍SIMCA 17中光谱预处理算法的扩展库 更多SIMCA软件视频教程，登录 科学软件网 www.sciencesoftware.com.cn 观看。

Although today's computer systems are robust compared to a few years ago (1), the tasks assigned to today's computers are much more complex, and therefore, it is of the utmost importance that the computer system, on the whole, is able to operate at optimal or near optimal performance.   One example would be the high CPU speed needed for graphics display in today's online games (2).   This paper will address the three main areas of optimization in modern computers: program optimization, algorithmic optimization, and cache optimization

Depression is the next level of negative emotions. When a person is in a sad mood or going through a difficult situation and it is not leaving him and giving him pain continuously and he is unable to bear it anymore, that situation is called depression. The last stage of depression occurs in suicide. According to the World Health Organization (WHO), Currently, 4.4% of people in the world are currently suffering from depression. In 2021, fourteen thousand people committed suicide all over the world and the rating of suicide is increasing day by day. So, our study is to find depressed people by their comments, posts, or texts on social media. We collected almost 10,000 data from Facebook posts, comments, and YouTube comments. Data mining and machine learning (ML) algorithms make our work easier and play a big role in easily detecting a person’s emotions. We applied six classifiers to predict depression & non-depression and found the best accuracy on a support vector machine (SVM).

Because Diversity™ means everyone MUST think alike about the agenda of 'diversity™' United Nations, Melissa Fleming says “They *own* the science on climate change”, and they have worked with Google to make sure the algorithms shows only UN information. "We own the science, and we think that the world should know it". 'Incredibly distorted information right at the top...'  means its information that doesn't fit OUR agenda. Globohomo plutocrats take for GRANTED the right to coerce you, manipulate what you see, control what you can research and find, and censor you systemically to pursue their agenda against the public.  They need to be punished, arrested, and fined. Not lauded and interviewed about it, ================== Only a fool thinks climate change politics has anything to do with climate change. The climate is changing, the climate is changing!!!' 'So?? ' 'So Hands UP!!! Gimme all your money. ' Tax. tax. tax, You work. Government takes with a gun at your back. NO MORE --------------------------- Posted for educative purposes under THE FAIR USE NOTICE: These Videos may contain copyrighted (©) material the use of which has not always been specifically authorized by the copyright owner. Such material is made available to advance understanding of ecological, political, human rights, economic, democracy, scientific, moral, ethical, and social justice issues, etc. It is believed that this constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the US Copyright Law. In accordance with Title 17 U.S.C. Section 107, this material is distributed without profit to those who have expressed a prior general interest in receiving similar information for research and educational purposes. For more information go to: http://www.law.cornell.edu/uscode​. "Copyright Disclaimer Under Section 107 of the Copyright Act 1976. (https://creativecommons.org/licenses/by-sa/3.0/legalcode)

The materials in this teacher's guide are designed for about 18 weeks of study by secondary school students. For maximum benefit, the student needs contact with a computer, primarily for verifying and trouble-shooting the algorithms which he or she has constructed. The course is usually taught for grade 11 or 12 students. The commentary contains background material, suggestions for use, and answers for exercises for each chapter of the student text. Comments indicate the course requires more preparation time for the teacher than most high school mathematics courses; use of a student assistant is recommended. (RH)

The purpose of this study was to ascertain whether children in grade 3 who differ in cognitive processing capacity add and subtract differently. The researchers drew upon information from three sources: individual results from a battery of 14 tests, an objective-referenced achievement test measuring a variety of arithmetic skills related to addition and subtraction, and coded strategy data for a set of verbal addition and subtraction problems administered in an interview setting. Eleven children starting third grade in Tasmania, Australia were involved in the study. The data suggested two notions: (1) there is a group of children who have the capacity to reason about quantitative problems, know the basic procedures of addition and subtraction, but see little reason to use those algorithmic procedures to find answers to verbal problems; (2) there is a second group of children whose capacity to reason about quantitative problems is suspect: they do not know the basic procedures to addition and subtraction and have not acquired other skills like modeling or counting which would help them solve verbal problems. It is suggested that educators need to reexamine the relationships between the algorithm and its application. (MNS)

Stanford Lecture Don Knuth The Analysis Of Algorithms

A new basic algorithm is discussed that may be used to do factor analysis by any of these three methods: (1) unweighted least squares, (2) generalized least squares, or (3) maximum likelihood. (CK)

A new basic algorithm is discussed that may be used to do factor analysis by any of these three methods: (1) unweighted least squares, (2) generalized least squares, or (3) maximum likelihood. (CK)

This book provides a historical inquiry into the quantification of needs in humanitarian assistance. Needs are increasingly seen as the lowest common denominator of humanity. Standard definitions of basic needs, however, set a minimalist version of humanity – both in the sense that they are narrow in what they compare, and that they set a low bar for satisfaction. The book argues that we cannot understand humanitarian governance if we do not understand how humanitarian agencies made human suffering commensurable across borders in the first place. The book identifies four basic elements of needs: As a concept, as a system of classification and triage, as a material apparatus, and as a set of standards. Drawing on a range of archival sources, including the United Nations Refugee Agency (UNHCR), Médecins sans Frontières (MSF), and the Sphere Project, the book traces the concept of needs from its emergence in the 1960s right through to the present day, and United Nations Secretary-General Ban Ki-moon’s call for “evidence-based humanitarianism.” Finally, the book assesses how the international governmentality of needs has played out in a recent humanitarian crisis, drawing on field research on Central African refugees in the Cameroonian borderland in 2014–2016. This important historical inquiry into the universal nature of human suffering will be an important read for humanitarian researchers and practitioners, as well as readers with an interest in international history and development.

This book provides a historical inquiry into the quantification of needs in humanitarian assistance. Needs are increasingly seen as the lowest common denominator of humanity. Standard definitions of basic needs, however, set a minimalist version of humanity – both in the sense that they are narrow in what they compare, and that they set a low bar for satisfaction. The book argues that we cannot understand humanitarian governance if we do not understand how humanitarian agencies made human suffering commensurable across borders in the first place. The book identifies four basic elements of needs: As a concept, as a system of classification and triage, as a material apparatus, and as a set of standards. Drawing on a range of archival sources, including the United Nations Refugee Agency (UNHCR), Médecins sans Frontières (MSF), and the Sphere Project, the book traces the concept of needs from its emergence in the 1960s right through to the present day, and United Nations Secretary-General Ban Ki-moon’s call for “evidence-based humanitarianism.” Finally, the book assesses how the international governmentality of needs has played out in a recent humanitarian crisis, drawing on field research on Central African refugees in the Cameroonian borderland in 2014–2016. This important historical inquiry into the universal nature of human suffering will be an important read for humanitarian researchers and practitioners, as well as readers with an interest in international history and development.

Automatic face recognition has ample significance in biometric research. Recent decades have witnessed enormous growth in this research area. Face-based identification is always considered more expedient as compared to other biometric authentications owing to its uniqueness and wide acceptance. The major contribution of this work is twofold; firstly, it comprises an extension of manual thresholding feature-based face recognition approach to an automatic feature-based supervised learning face recognition. Secondly, various new feature sets are proposed and tested on several classifiers for 2, 3, 4, and 5 persons. In addition, the use of slope features of facial components, such as the nose, right eye, left eye, and lips along with other conventional features for face recognition is also a unique contribution of this research. Multiple experiments were performed on the UMT face database. The results demonstrated a comparison of 5 different sets of feature-based approaches on 7 classifiers using the metrics of time efficiency and accuracy. They also depicted that the proposed approaches achieve a percentage accuracy of up to 95.5%.

Automatic face recognition has ample significance in biometric research. Recent decades have witnessed enormous growth in this research area. Face-based identification is always considered more expedient as compared to other biometric authentications owing to its uniqueness and wide acceptance. The major contribution of this work is twofold; firstly, it comprises an extension of manual thresholding feature-based face recognition approach to an automatic feature-based supervised learning face recognition. Secondly, various new feature sets are proposed and tested on several classifiers for 2, 3, 4, and 5 persons. In addition, the use of slope features of facial components, such as the nose, right eye, left eye, and lips along with other conventional features for face recognition is also a unique contribution of this research. Multiple experiments were performed on the UMT face database. The results demonstrated a comparison of 5 different sets of feature-based approaches on 7 classifiers using the metrics of time efficiency and accuracy. They also depicted that the proposed approaches achieve a percentage accuracy of up to 95.5%.

Automatic face recognition has ample significance in biometric research. Recent decades have witnessed enormous growth in this research area. Face-based identification is always considered more expedient as compared to other biometric authentications owing to its uniqueness and wide acceptance. The major contribution of this work is twofold; firstly, it comprises an extension of manual thresholding feature-based face recognition approach to an automatic feature-based supervised learning face recognition. Secondly, various new feature sets are proposed and tested on several classifiers for 2, 3, 4, and 5 persons. In addition, the use of slope features of facial components, such as the nose, right eye, left eye, and lips along with other conventional features for face recognition is also a unique contribution of this research. Multiple experiments were performed on the UMT face database. The results demonstrated a comparison of 5 different sets of feature-based approaches on 7 classifiers using the metrics of time efficiency and accuracy. They also depicted that the proposed approaches achieve a percentage accuracy of up to 95.5%.

Automatic face recognition has ample significance in biometric research. Recent decades have witnessed enormous growth in this research area. Face-based identification is always considered more expedient as compared to other biometric authentications owing to its uniqueness and wide acceptance. The major contribution of this work is twofold; firstly, it comprises an extension of manual thresholding feature-based face recognition approach to an automatic feature-based supervised learning face recognition. Secondly, various new feature sets are proposed and tested on several classifiers for 2, 3, 4, and 5 persons. In addition, the use of slope features of facial components, such as the nose, right eye, left eye, and lips along with other conventional features for face recognition is also a unique contribution of this research. Multiple experiments were performed on the UMT face database. The results demonstrated a comparison of 5 different sets of feature-based approaches on 7 classifiers using the metrics of time efficiency and accuracy. They also depicted that the proposed approaches achieve a percentage accuracy of up to 95.5%.

xx, 422 p. : 24 cm

Data Structures and Algorithms implementation in Go Data Structures and Algorithms Clean and simple implementation in Go Implementation There are several data structures and algorithms implemented in this project. The list will be replenished with time. Data structures Circular Buffer Linked List Doubly Linked List Stack Queue Searching algorithms Linear Search Binary Search Jump Search Interpolation Search Exponential Search Ternary Search Sorting algorithms Selection Sort Insertion Sort Bubble Sort Comb Sort Usage The library is not intended for direct use by importing. We strongly recommend copying the necessary implementations and adjusting to your case. You can download the source using go get command: go get github.com/floyernick/Data-Structures-and-Algorithms Don't forget about proverb: A little copying is better than a little dependency. Contribute We would be happy to receive your propositions of improvement ;) License This project is licensed under the MIT License . Authors Mykyta Paliienko - GitHub profile To restore the repository download the bundle wget https://archive.org/download/github.com-floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51/floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle and run: git clone floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle Source: https://github.com/floyernick/Data-Structures-and-Algorithms Uploader: floyernick Upload date: 2018-04-01

Data Structures and Algorithms implementation in Go Data Structures and Algorithms Clean and simple implementation in Go Implementation There are several data structures and algorithms implemented in this project. The list will be replenished with time. Data structures Circular Buffer Linked List Doubly Linked List Stack Queue Searching algorithms Linear Search Binary Search Jump Search Interpolation Search Exponential Search Ternary Search Sorting algorithms Selection Sort Insertion Sort Bubble Sort Comb Sort Usage The library is not intended for direct use by importing. We strongly recommend copying the necessary implementations and adjusting to your case. You can download the source using go get command: go get github.com/floyernick/Data-Structures-and-Algorithms Don't forget about proverb: A little copying is better than a little dependency. Contribute We would be happy to receive your propositions of improvement ;) License This project is licensed under the MIT License . Authors Mykyta Paliienko - GitHub profile To restore the repository download the bundle wget https://archive.org/download/github.com-floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51/floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle and run: git clone floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle Source: https://github.com/floyernick/Data-Structures-and-Algorithms Uploader: floyernick Upload date: 2018-04-01

Data Structures and Algorithms implementation in Go Data Structures and Algorithms Clean and simple implementation in Go Implementation There are several data structures and algorithms implemented in this project. The list will be replenished with time. Data structures Circular Buffer Linked List Doubly Linked List Stack Queue Searching algorithms Linear Search Binary Search Jump Search Interpolation Search Exponential Search Ternary Search Sorting algorithms Selection Sort Insertion Sort Bubble Sort Comb Sort Usage The library is not intended for direct use by importing. We strongly recommend copying the necessary implementations and adjusting to your case. You can download the source using go get command: go get github.com/floyernick/Data-Structures-and-Algorithms Don't forget about proverb: A little copying is better than a little dependency. Contribute We would be happy to receive your propositions of improvement ;) License This project is licensed under the MIT License . Authors Mykyta Paliienko - GitHub profile To restore the repository download the bundle wget https://archive.org/download/github.com-floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51/floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle and run: git clone floyernick-Data-Structures-and-Algorithms_-_2018-04-01_17-10-51.bundle Source: https://github.com/floyernick/Data-Structures-and-Algorithms Uploader: floyernick Upload date: 2018-04-01

The objective of this project is to improve the effectiveness and efficiency of advertising on various platforms by utilizing advanced algorithms, namely the Upper Confidence Bound and Thompson Sampling Algorithm. The project aims to find a balance between exploring new advertising strategies and exploiting proven high-performing approaches. By implementing these bandit algorithms, the project aims to dynamically optimize ad placements, formats, and targeting to maximize user engagement and ad revenue. The methodology involves an iterative process of data collection, analysis, and adaptation. The initial phases include defining project objectives, understanding the target audience, and reviewing the current ad strategy. The Upper Confidence Bound algorithm enables intelligent decision-making by assigning confidence bounds to different ad strategies, allowing for efficient exploration and exploitation. On the other hand, the Thompson Sampling algorithm, rooted in Bayesian principles, dynamically adapts based on observed outcomes, striking a balance between exploration and exploitation through probabilistic reasoning. In summary, this Ads Optimization Project utilizes the power of the Upper Confidence Bound and Thompson Sampling algorithms to create a data-driven, adaptive, and user-centric approach to advertising. The ultimate goal is to achieve optimal user engagement and ad revenue.

The objective of this project is to improve the effectiveness and efficiency of advertising on various platforms by utilizing advanced algorithms, namely the Upper Confidence Bound and Thompson Sampling Algorithm. The project aims to find a balance between exploring new advertising strategies and exploiting proven high-performing approaches. By implementing these bandit algorithms, the project aims to dynamically optimize ad placements, formats, and targeting to maximize user engagement and ad revenue. The methodology involves an iterative process of data collection, analysis, and adaptation. The initial phases include defining project objectives, understanding the target audience, and reviewing the current ad strategy. The Upper Confidence Bound algorithm enables intelligent decision-making by assigning confidence bounds to different ad strategies, allowing for efficient exploration and exploitation. On the other hand, the Thompson Sampling algorithm, rooted in Bayesian principles, dynamically adapts based on observed outcomes, striking a balance between exploration and exploitation through probabilistic reasoning. In summary, this Ads Optimization Project utilizes the power of the Upper Confidence Bound and Thompson Sampling algorithms to create a data-driven, adaptive, and user-centric approach to advertising. The ultimate goal is to achieve optimal user engagement and ad revenue.

This executive summary describes a larger report--the result of a national research effort exploring how much U.S. college-age students know about the way in which internet giants like Google, YouTube, Instagram, and Facebook work, and by extension, how they affect society. Amidst the daily flood of digital news, memes, opinion, advertising, and propaganda, there is growing concern about how these popular platforms, and the algorithms they employ, influence lives, deepen social divisions, and foment polarization, extremism, and distrust. The report builds on a decade of research from Project Information Literacy surveying the information habits of college students in an increasingly digital world. It examines how students conceptualize and navigate a volatile and ever-changing information landscape, and proposes programmatic ways to prepare them to contend with this new reality. Four detailed research takeaways are highlighted in this summary: (1) College students have an ambivalent bond with algorithm-driven platforms; (2) Students use defensive practices to protect their privacy; (3) Trust is dead for many students, and skepticism lives; and (4) Discussions of algorithms rarely make it into the classroom. [Additional funding for this report was provided by the School of Library and Information Science at the University of South Carolina. For the main report, see ED605109.]