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Gender Codes: Why Women Are Leaving Computing
by Thomas J. MisaThe computing profession faces a serious gender crisis. Today, fewer women enter computing than anytime in the past 25 years. This book provides an unprecedented look at the history of women and men in computing, detailing how the computing profession emerged and matured, and how the field became male coded. Women's experiences working in offices, education, libraries, programming, and government are examined for clues on how and where women succeeded—and where they struggled. It also provides a unique international dimension with studies examining the U.S., Great Britain, Germany, Norway, and Greece. Scholars in history, gender/women's studies, and science and technology studies, as well as department chairs and hiring directors will find this volume illuminating.
Gender Differences in Computer and Information Literacy: An In-depth Analysis of Data from ICILS (IEA Research for Education #8)
by Eveline Gebhardt Sue Thomson John Ainley Kylie HillmanThis open access book presents a systematic investigation into internationally comparable data gathered in ICILS 2013. It identifies differences in female and male students’ use of, perceptions about, and proficiency in using computer technologies. Teachers’ use of computers, and their perceptions regarding the benefits of computer use in education, are also analyzed by gender. When computer technology was first introduced in schools, there was a prevailing belief that information and communication technologies were ‘boys’ toys’; boys were assumed to have more positive attitudes toward using computer technologies. As computer technologies have become more established throughout societies, gender gaps in students’ computer and information literacy appear to be closing, although studies into gender differences remain sparse. The IEA’s International Computer and Information Literacy Study (ICILS) is designed to discover how well students are prepared for study, work, and life in the digital age. Despite popular beliefs, a critical finding of ICILS 2013 was that internationally girls tended to score more highly than boys, so why are girls still not entering technology-based careers to the same extent as boys? Readers will learn how male and female students differ in their computer literacy (both general and specialized) and use of computer technology, and how the perceptions held about those technologies vary by gender.
Gender in AI and Robotics: The Gender Challenges from an Interdisciplinary Perspective (Intelligent Systems Reference Library #235)
by Jordi VallverdúWhy AI does not include gender in its agenda? The role of gender in AI, both as part of the community of agents creating such technologies, as well as part of the contents processed by such technologies is, by far, conflictive. Women have been, again, obliterated by this fundamental revolution of our century. Highly innovative and the first step in a series of future studies in this field, this book covers several voices, topics, and perspectives that allow the reader to understand the necessity to include into the AI research agenda such points of view and also to attract more women to this field. The multi-disciplinarity of the contributors, which uses plain language to show the current situation in this field, is a fundamental aspect of the value of this book. Any reader with a genuine interest in the present and future of AI should read it.
Gender Reboot: Reprogramming Gender Rights in the Age of AI
by Eleonore Fournier-TombsThis book explores gender norms and women’s rights in the age of AI. The author examines how gender dynamics have evolved in the spheres of work, self-image and safety, and education, and how these might be reflected in current challenges in AI development. The book also explores opportunities in AI to address issues facing women, and how we might harness current technological developments for gender equality. Taking a narrative tone, the book is interwoven with stories and a reflection on the raising young children during the COVID-19 pandemic. It includes both expert and personal interviews to create a nuanced and multidimensional perspective on the state of women’s rights and what might be done to move forward.
Gene Expression Analysis: Methods and Protocols (Methods in Molecular Biology #2880)
by Nalini Raghavachari Natalia Garcia-ReyeroThis second edition volume expands on the previous edition with updates on the latest methodologies in the transcriptomics field. The chapters in this book cover topics such as spatial omics, long-read sequencing technology, tissue microarrays, analysis of saliva and extracellular vesicles, machine learning and artificial intelligence-based approaches for analysis of singe cells transcriptome, and large sets of data on multi-omics including transcriptomics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and practical, Gene Expression Analysis: Methods and Protocols, Second Edition is a valuable resource for advanced undergraduate and graduate students studying gene expression analysis, and scientists interested in learning more about this rapidly advancing field.
Gene Expression Data Analysis: A Statistical and Machine Learning Perspective
by Dhruba Kumar Bhattacharyya Jugal Kumar Kalita Pankaj BarahDevelopment of high-throughput technologies in molecular biology during the last two decades has contributed to the production of tremendous amounts of data. Microarray and RNA sequencing are two such widely used high-throughput technologies for simultaneously monitoring the expression patterns of thousands of genes. Data produced from such experiments are voluminous (both in dimensionality and numbers of instances) and evolving in nature. Analysis of huge amounts of data toward the identification of interesting patterns that are relevant for a given biological question requires high-performance computational infrastructure as well as efficient machine learning algorithms. Cross-communication of ideas between biologists and computer scientists remains a big challenge. Gene Expression Data Analysis: A Statistical and Machine Learning Perspective has been written with a multidisciplinary audience in mind. The book discusses gene expression data analysis from molecular biology, machine learning, and statistical perspectives. Readers will be able to acquire both theoretical and practical knowledge of methods for identifying novel patterns of high biological significance. To measure the effectiveness of such algorithms, we discuss statistical and biological performance metrics that can be used in real life or in a simulated environment. This book discusses a large number of benchmark algorithms, tools, systems, and repositories that are commonly used in analyzing gene expression data and validating results. This book will benefit students, researchers, and practitioners in biology, medicine, and computer science by enabling them to acquire in-depth knowledge in statistical and machine-learning-based methods for analyzing gene expression data. Key Features: An introduction to the Central Dogma of molecular biology and information flow in biological systems A systematic overview of the methods for generating gene expression data Background knowledge on statistical modeling and machine learning techniques Detailed methodology of analyzing gene expression data with an example case study Clustering methods for finding co-expression patterns from microarray, bulkRNA, and scRNA data A large number of practical tools, systems, and repositories that are useful for computational biologists to create, analyze, and validate biologically relevant gene expression patterns Suitable for multidisciplinary researchers and practitioners in computer science and biological sciences
Gene Network Inference
by Alberto FuenteThis book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e. g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
GeNeDis 2018: Computational Biology and Bioinformatics (Advances in Experimental Medicine and Biology #1194)
by Panayiotis VlamosThe 3rd World Congress on Genetics, Geriatrics, and Neurodegenerative Disease Research (GeNeDis 2018), focuses on recent advances in genetics, geriatrics, and neurodegeneration, ranging from basic science to clinical and pharmaceutical developments. It also provides an international forum for the latest scientific discoveries, medical practices, and care initiatives. Advanced information technologies are discussed, including the basic research, implementation of medico-social policies, and the European and global issues in the funding of long-term care for elderly people.
GeNeDis 2020: Geriatrics (Advances in Experimental Medicine and Biology #1337)
by Panayiotis VlamosThe 4th World Congress on Genetics, Geriatrics and Neurodegenerative Diseases Research (GeNeDis 2020) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. The increase in the average length of life leads to the development of various diseases in the elderly population. This volume focuses on the sessions from the conference on Geriatrics.
GeNeDis 2020: Genetics and Neurodegenerative Diseases (Advances in Experimental Medicine and Biology #1339)
by Panayiotis VlamosThe 4th World Congress on Genetics, Geriatrics, and Neurodegenerative Diseases Research (GeNeDis 2020) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. The relation between genetics and its effect on several diseases are thoroughly examined in this volume. This volume focuses on the sessions from the conference on Genetics and Neurodegenerative Diseases.
GeNeDis 2020: Computational Biology and Bioinformatics (Advances in Experimental Medicine and Biology #1338)
by Panayiotis VlamosThe 4th World Congress on Genetics, Geriatrics and Neurodegenerative Diseases Research (GeNeDis 2020) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. Computational methodologies for implementation on the discovery of biomarkers for neurodegenerative diseases are extensively discussed. This volume focuses on the sessions from the conference regarding computational biology and bioinformatics.
General Aspects of Applying Generative AI in Higher Education: Opportunities and Challenges
by Mohamed Lahby Yassine Maleh Antonio Bucchiarone Satu Elisa SchaefferThis book explores the transformative impact of generative artificial intelligence (GenAI) on teaching and learning, examining how recent advancements in GenAI are revolutionizing educational practices across disciplines. The book is organized into three parts: an overview of GenAI in education, its application in diverse educational contexts, and future perspectives on how educators and GenAI can interface. The first part addresses the pressing concerns within the educational landscape, both the bridges GenAI allows us to build and the remaining as well as the emerging gaps. The middle part explores specific academic disciplines, such as history, sports medicine, mathematics, engineering, and the humanities, dissecting the influence of GenAI on each. The final part looks ahead, discussing the ethical implications, the evolving role of prompting, and innovative frameworks for personalized learning. By presenting a balanced view of the opportunities that are now within reach through GenAI and the challenges such leaps pose to the way we learn and teach, this book allows interested educators to learn from the early-adopting contributors to fruitfully and responsibly integrate such technologies into their pedagogical practices. It serves as a resource for anyone interested in the future of educational practices and research of education, offering insights that can spark further exploration and discussion within the academic community and educational policy makers.
A General Framework for Reasoning On Inconsistency (SpringerBriefs in Computer Science)
by V. S. Subrahmanian Maria Vanina Martinez Leila Amgoud Cristian MolinaroThis SpringerBrief proposes a general framework for reasoning about inconsistency in a wide variety of logics, including inconsistency resolution methods that have not yet been studied. The proposed framework allows users to specify preferences on how to resolve inconsistency when there are multiple ways to do so. This empowers users to resolve inconsistency in data leveraging both their detailed knowledge of the data as well as their application needs. The brief shows that the framework is well-suited to handle inconsistency in several logics, and provides algorithms to compute preferred options. Finally, the brief shows that the framework not only captures several existing works, but also supports reasoning about inconsistency in several logics for which no such methods exist today.
A General Theory of Entropy: Fuzzy Rational Foundations of Information-Knowledge Certainty (Studies in Fuzziness and Soft Computing #384)
by Kofi Kissi DompereThis book presents an epistemic framework for dealing with information-knowledge and certainty-uncertainty problems within the space of quality-quantity dualities. It bridges between theoretical concepts of entropy and entropy measurements, proposing the concept and measurement of fuzzy-stochastic entropy that is applicable to all areas of knowing under human cognitive limitations over the epistemological space. The book builds on two previous monographs by the same author concerning theories of info-statics and info-dynamics, to deal with identification and transformation problems respectively. The theoretical framework is developed by using the toolboxes such as those of the principle of opposites, systems of actual-potential polarities and negative-positive dualities, under different cost-benefit time-structures. The category theory and the fuzzy paradigm of thought, under methodological constructionism-reductionism duality, are used in the fuzzy-stochastic and cost-benefit spaces to point to directions of global application in knowing, knowledge and decision-choice actions. Thus, the book is concerned with a general theory of entropy, showing how the fuzzy paradigm of thought is developed to deal with the problems of qualitative-quantitative uncertainties over the fuzzy-stochastic space, which will be applicable to conditions of soft-hard data, fact, evidence and knowledge over the spaces of problem-solution dualities, decision-choice actions in sciences, non-sciences, engineering and planning sciences to abstract acceptable information-knowledge elements.
General Type-2 Fuzzy Logic in Dynamic Parameter Adaptation for the Harmony Search Algorithm (SpringerBriefs in Applied Sciences and Technology)
by Oscar Castillo Fevrier Valdez Cinthia PerazaThis book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic.This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems – four of the Mamdani type: the problem of filling a water tank, the problem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.
General Will 2.0
by John Person Hiroki AzumaAccording to Azuma, the collective will and the general social contract has changed the world's political landscape over the last couple of years. Azuma looks back at Rousseau and Freud then forward to Twitter and Google to express how man deals with their part of the collective will through time. Azuma challenges society's perceptions of general will by looking at three philosophies through both time and technology. Azuma's unique analysis can be as compelling as fiction while making readers feel enlightened in the process.
The Generalist Advantage: Proven Framework to Explore the Potential of 4 Types of Generalists at Work
by Mansoor SoomroTransition from a specialist into a generalist to meet the demands of the new world of business It is a game-changing book for our era of specialization! – Des Dearlove, Thinkers50 The Generalist Advantage is a useful framework for firms in transition, preparing themselves for a high-tech future. – Yuri Bender, Financial Times The Generalist Advantage: Proven Framework to Explore the Potential of 4 Types of Generalists at Work delivers a compelling argument as to why generalists—those with diverse skill sets and broad industry exposure—hold a unique advantage in shaping the future of work. This book provides actionable insights for those who are still going down the path of the specialist, in this age of AI. Some of the topics explored in this book include: The learning loop, covering lifelong learning as a generalist, building your personal learning ecosystem, and embracing failure as a path to growth The leadership spectrum, covering diverse leadership styles in the age of AI, the generalist leader's toolkit, and the importance of flexibility and adaptability Future ready skills for the generalist leader, covering creative problem solving, complex decision making and multidisciplinary learning The Generalist Advantage: Proven Framework to Explore the Potential of 4 Types of Generalists at Work is a timely, essential read for all business leaders, executives, and middle managers seeking to adopt a superior approach to the way they do business and help lead their organizations through a tumultuous transformative period. Soomro makes the timely and valuable case that specialization in academia and business has gone too far. – Martin Reeves, Boston Consulting Group Henderson Institute Dr. Mansoor delivers a masterful guide and offers a powerful framework for embracing versatility in the AI era. – Dr. Marshall Goldsmith, NYT bestselling author of What Got You Here Won't Get You There I cherish this book because it puts words on the life I have lived. Mansoor validates why it is important to be a generalist. – Professor Dave Ulrich, University of Michigan
Generalized Barycentric Coordinates in Computer Graphics and Computational Mechanics
by Kai Hormann N. SukumarIn Generalized Barycentric Coordinates in Computer Graphics and Computational Mechanics, eminent computer graphics and computational mechanics researchers provide a state-of-the-art overview of generalized barycentric coordinates. Commonly used in cutting-edge applications such as mesh parametrization, image warping, mesh deformation, and finite as well as boundary element methods, the theory of barycentric coordinates is also fundamental for use in animation and in simulating the deformation of solid continua. Generalized Barycentric Coordinates is divided into three sections, with five chapters each, covering the theoretical background, as well as their use in computer graphics and computational mechanics. A vivid 16-page insert helps illustrating the stunning applications of this fascinating research area. <P><P>Key Features: <li>Provides an overview of the many different types of barycentric coordinates and their properties. <li>Discusses diverse applications of barycentric coordinates in computer graphics and computational mechanics. <li>The first book-length treatment on this topic
Generalized Intuitionistic Multiplicative Fuzzy Calculus Theory and Applications (Uncertainty and Operations Research)
by Shan Yu Zeshui XuThis book mainly introduces the latest development of generalized intuitionistic multiplicative fuzzy calculus and its application. The book pursues three major objectives: (1) to introduce the calculus models with concrete mathematical expressions for generalized intuitionistic multiplicative fuzzy information; (2) to introduce new information fusion methods based on the definite integral models; and (3) to clarify the involved approaches bymilitary case. The book is especially valuable for readers to understand how the theoretical framework of generalized intuitionistic multiplicative fuzzy calculus is constructed, not only discrete or continuous but also correlative (generalized) intuitionistic (multiplicative) fuzzy information is aggregated based on the definite integral models and the theory with a military practice is integrated, which would deepen the understanding and give researchers more inspiration in practical decision analysis under uncertainties.
Generalized Linear Models With Examples in R (Springer Texts in Statistics)
by Peter K. Dunn Gordon K. SmythThis textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed through the use of these data sets and numerous case studies. The authors include a set of practice problems both at the end of each chapter and at the end of the book. Each example in the text is cross-referenced with the relevant data set, so that readers can load the data and follow the analysis in their own R sessions. The balance between theory and practice is evident in the list of problems, which vary in difficulty and purpose.This book is designed with teaching and learning in mind, featuring chapter introductions and summaries, exercises, short answers, and simple, clear examples. Focusing on the connections between generalized linear models (GLMs) and linear regression, the book also references advanced topics and tools that have not typically been included in introductions to GLMs to date, such as Tweedie family distributions with power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, and randomized quantile residuals. In addition, the authors introduce the new R code package, GLMsData, created specifically for this book. Generalized Linear Models with Examples in R balances theory with practice, making it ideal for both introductory and graduate-level students who have a basic knowledge of matrix algebra, calculus, and statistics.
Generalized Normalizing Flows via Markov Chains (Elements in Non-local Data Interactions: Foundations and Applications)
by Paul Lyonel Hagemann Johannes Hertrich Gabriele SteidlNormalizing flows, diffusion normalizing flows and variational autoencoders are powerful generative models. This Element provides a unified framework to handle these approaches via Markov chains. The authors consider stochastic normalizing flows as a pair of Markov chains fulfilling some properties, and show how many state-of-the-art models for data generation fit into this framework. Indeed numerical simulations show that including stochastic layers improves the expressivity of the network and allows for generating multimodal distributions from unimodal ones. The Markov chains point of view enables the coupling of both deterministic layers as invertible neural networks and stochastic layers as Metropolis-Hasting layers, Langevin layers, variational autoencoders and diffusion normalizing flows in a mathematically sound way. The authors' framework establishes a useful mathematical tool to combine the various approaches.
Generalized Statistical Thermodynamics: Thermodynamics of Probability Distributions and Stochastic Processes (Understanding Complex Systems)
by Themis MatsoukasThis book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions. Extending Gibbs's notion of ensemble, the Author imagines the ensemble of all possible probability distributions and assigns probabilities to them by selection rules that are fairly general. The calculus of the most probable distribution in the ensemble produces the entire network of mathematical relationships we recognize as thermodynamics. The first part of the book develops the theory for discrete and continuous distributions while the second part applies this thermodynamic calculus to problems in population balance theory and shows how the emergence of a giant component in aggregation, and the shattering transition in fragmentation may be treated as formal phase transitions. While the book is intended as a research monograph, the material is self-contained and the style sufficiently tutorial to be accessible for self-paced study by an advanced graduate student in such fields as physics, chemistry, and engineering.
Generalized Sylvester Equations: Unified Parametric Solutions
by Guang-Ren DuanProvides One Unified Formula That Gives Solutions to Several Types of GSEsGeneralized Sylvester equations (GSEs) are applied in many fields, including applied mathematics, systems and control, and signal processing. Generalized Sylvester Equations: Unified Parametric Solutions presents a unified parametric approach for solving various types of GSEs
Generalizing from Limited Resources in the Open World: Second International Workshop, GLOW 2024, Held in Conjunction with IJCAI 2024, Jeju, South Korea, August 3, 2024, Proceedings (Communications in Computer and Information Science #2160)
by Jinyang Guo Yuqing Ma Yifu Ding Ruihao Gong Xingyu Zheng Changyi He Yantao Lu Xianglong LiuThis book presents the Proceedings from the Second International Workshop GLOW 2024 held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI 2024, in Jeju Island, South Korea, in August 2024. The 11 full papers and 4 short papers included in this book were carefully reviewed and selected from 22 submissions. They were organized in topical sections as follows: efficient methods for low-resource hardware; efficient fintuning with limited data; advancements in multimodal systems; recognition and reasoning in the open world.
Generating a New Reality: From Autoencoders and Adversarial Networks to Deepfakes
by Micheal LanhamThe emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects.By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new.What You Will LearnKnow the fundamentals of content generation from autoencoders to generative adversarial networks (GANs)Explore variations of GANUnderstand the basics of other forms of content generationUse advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2Who This Book Is ForMachine learning developers and AI enthusiasts who want to understand AI content generation techniques