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Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis
by Ethan Bueno de Mesquita Anthony FowlerAn engaging introduction to data science that emphasizes critical thinking over statistical techniquesAn introduction to data science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives.Among much else, the book teaches how to assess whether an observed relationship in data reflects a genuine relationship in the world and, if so, whether it is causal; how to make the most informative comparisons for answering questions; what questions to ask others who are making arguments using quantitative evidence; which statistics are particularly informative or misleading; how quantitative evidence should and shouldn’t influence decision-making; and how to make better decisions by using moral values as well as data. Filled with real-world examples, the book shows how its thinking tools apply to problems in a wide variety of subjects, including elections, civil conflict, crime, terrorism, financial crises, health care, sports, music, and space travel.Above all else, Thinking Clearly with Data demonstrates why, despite the many benefits of our data-driven age, data can never be a substitute for thinking.An ideal textbook for introductory quantitative methods courses in data science, statistics, political science, economics, psychology, sociology, public policy, and other fieldsIntroduces the basic toolkit of data analysis—including sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuityUses real-world examples and data from a wide variety of subjectsIncludes practice questions and data exercises
Thinking Collaboratively: Learning in a Community of Inquiry
by D. Randy GarrisonThinking Collaboratively is a theoretical and practical guide to thinking and learning in deep and meaningful ways within purposeful communities of inquiry. Critical thinking has long been recognized as an important educational goal but, until now, has largely been conceived and operationalized as an individual attitude and ability. Increasingly, however, a more relevant and complete cognitive construct has been emerging: thinking collaboratively. Thinking collaboratively is the means to inquire, test, and apply new understandings, and to make sense of the information that bombards us continuously. In short, thinking collaboratively is required to flourish in our highly connected world and, in this book based on more than a decade of research, Garrison provides an essential introduction to this vital concept.
Thinking Data Science: A Data Science Practitioner’s Guide (The Springer Series in Applied Machine Learning)
by Poornachandra SarangThis definitive guide to Machine Learning projects answers the problems an aspiring or experienced data scientist frequently has: Confused on what technology to use for your ML development? Should I use GOFAI, ANN/DNN or Transfer Learning? Can I rely on AutoML for model development? What if the client provides me Gig and Terabytes of data for developing analytic models? How do I handle high-frequency dynamic datasets? This book provides the practitioner with a consolidation of the entire data science process in a single “Cheat Sheet”.The challenge for a data scientist is to extract meaningful information from huge datasets that will help to create better strategies for businesses. Many Machine Learning algorithms and Neural Networks are designed to do analytics on such datasets. For a data scientist, it is a daunting decision as to which algorithm to use for a given dataset. Although there is no single answer to this question, a systematic approach to problem solving is necessary. This book describes the various ML algorithms conceptually and defines/discusses a process in the selection of ML/DL models. The consolidation of available algorithms and techniques for designing efficient ML models is the key aspect of this book. Thinking Data Science will help practising data scientists, academicians, researchers, and students who want to build ML models using the appropriate algorithms and architectures, whether the data be small or big.
Thinking Functionally With Haskell
by Richard BirdRichard Bird is famed for the clarity and rigour of his writing. His new textbook, which introduces functional programming to students, emphasises fundamental techniques for reasoning mathematically about functional programs. By studying the underlying equational laws, the book enables students to apply calculational reasoning to their programs, both to understand their properties and to make them more efficient. The book has been designed to fit a first- or second-year undergraduate course and is a thorough overhaul and replacement of his earlier textbooks. It features case studies in Sudoku and pretty-printing, and over 100 carefully selected exercises with solutions. This engaging text will be welcomed by students and teachers alike.
Thinking Like a Computer: An Introduction to Digital Reality
by George TownerThinking Like a Computer is the result of a detailed 30-year study of how computers imitate life.Although they are machines, computers are designed to act like human beings. Software is specifically created to help accomplish human-like tasks and to be understood in human terms. Yet unlike human life, computer operations can be analyzed in detail because we build the machines that accomplish them and we know the design decisions that make them work.With every choice made during the evolution of digital technology, computer architects have intuitively or consciously incorporated truths of human functioning into their designs.Thinking Like a Computer is based on these truths, assembling them into a new explanation of human knowledge. In addition, it provides insights into the foundations of theoretical science because much of digital technology is dedicated to creating new realities.
Thinking Like a Human: The Power of Your Mind in the Age of AI
by David WeitznerA bright and timely book that celebrates the value of the human mind AI is at the forefront of everyone's minds: from students and artists, to CEO's and service workers. But what exactly is AI, and how does it influence our everyday lives? And more than that, what does it mean for our future? Is there a way for us to retain our "humanness" in a world ever-reliant on tech?This groundbreaking book argues that the key technology we use to make strategic, political, and ethical decisions is flawed. As we race headlong into a future where we outsource all of our problem solving to artificial intelligence, the greatest threat to humanity is not superintelligent machinery, but a lack of trust in the power of our own minds. This book offers a new way forward—what Dr. Weitzner calls "artful intelligence"—a philosophy that celebrates our humanness and can help each of us make better decisions and create a healthier relationship with the world around us.In these pages, the author walks us through how AI often fails and how that affects our lives. But readers will also meet the rockstars, inventors, and business leaders who embody artful intelligence and are changing our world for the better in an era rampant with AI malpractice—while being taught how to do the same.
Thinking Machines: The Quest for Artificial Intelligence--and Where It's Taking Us Next
by Luke DormehlA fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner.When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to widen to include intelligent machines.From the Trade Paperback edition.
Thinking Skills for the Digital Generation
by Balu H. Athreya Chrystalla MouzaThis important text synthesizes the state of knowledge related to thinking and technology and provides strategies for helping young people cultivate thinking skills required to navigate the new digital landscape. The rise of technology has resulted in new ways of searching and communicating information among youth, often creating information "overload". We do not know how the new technologies will affect the ways young people learn and think. There are plenty of warnings about the dangers of information technology, but there is also enormous potential for technology to aid human thinking, which this book explores from an open-minded perspective. Coverage Includes: - An up to date review of the literature on thinking skills in general, and in relation to technology. - Practical guidelines for thinking with technology. - A scholarly review of the characteristics of the digital generation. - A discussion of the various steps involved in the thinking process. - A historical context of the Information Age and the transition from oral history, to printing press, to the Internet. Thinking Skills for the Digital Generation: The Development of Thinking and Learning in the Age of Information is an invaluable reference for educators and research professionals particularly interested in educational technology, and improving thinking and problem-solving skills.
Thinking Swarms
by Simon Ng Hussein A. Abbass Jason Beaufort ScholzThis open access book is a multidisciplinary examination of swarm systems including swarm robotics. The book starts with a multidisciplinary consultation performed by the editors with participants from academia, industry and government. The consultation suggested four themes forming parts one to four and grouping the first 16 chapters. Part 1 contains definitions, categorisations and metaphors of swarm systems. Part 2 zooms-in with a behavioural lens on interpretations, narrative theory, and legal frameworks. Part 3 sheds a topological light on cognitive architectures and formations. Part 4 illumes cognitive dimensions on swarm lifelong and curriculum learning and hyper-teaming of swarm systems. The book concludes with future research directions in Part 5. The book is suitable for graduate students and researchers looking for inspiration and novel ideas to explore, or those attempting to understand the diversity of challenges in advanced swarm systems.
Thinking Through Data: How Outliers, Aggregates, and Patterns Shape Perception (Sensing Media: Aesthetics, Philosophy, and Cultures of Media)
by Maja Bak HerrieWe encounter digital data processing on a range of platforms and in a multitude of contexts today: in the predictive algorithms of the financial sector, in drones, insurance, and risk management, in smart cities, biometrics, medicine, and more. This fascinating book explores the historical context of the current data-driven paradigm and explains how elusive yet crucial statistical concepts such as outliers, aggregates, and patterns form how we sense and make sense of data. From the sixteenth century's embodied measurements of the foot, through the blurred facial features of L'Homme Moyen, to the image aggregates of today's security systems, the examples collected in this book illustrate the central role of aesthetics throughout the history of statistical knowledge production. Taking its point of departure in analyses and discussions of contemporary artistic experiments by Rossella Biscotti, Stéphanie Solinas, and Adam Broomberg and Oliver Chanarin, the book broadens our understanding of the structures of knowledge and methods in statistical computation beyond optimistic narratives of calculative power. Venturing out into the tails of the distributions—to the systemically overlooked and excluded—this book challenges us to embrace an alternative view of modern data processing.
Thinking Through Digital Media
by Dale Hudson Patricia R. ZimmermannThinking through Digital Media offers a means of conceptualizing digital media by looking at projects that think through digital media, migrating between documentary, experimental, narrative, animation, video game, and live performance. Hudson and Zimmermann analyze projects at the intersections of imbedded technologies, transitory micropublics, human-machine interface, and critical cartographies to forward a set of speculations about how things work together rather than what they represent. The book frames debates on participation/surveillance, outsourcing, global warming, migrations, GMOs, and war across some of the most dynamic, innovative sites for digital media, including Brazil, Canada, China, Germany, India, Indonesia, Italy, Kenya, Nigeria, Palestine, Saudi Arabia, Singapore, and the United States.
Thinking about Video Games
by David S. HeinemanThe growth in popularity and complexity of video games has spurred new interest in how games are developed and in the research and technology behind them. David Heineman brings together some of the most iconic, influential, and interesting voices from across the gaming industry and asks them to weigh in on the past, present, and future of video games. Among them are legendary game designers Nolan Bushnell (Pong) and Eugene Jarvis (Defender), who talk about their history of innovations from the earliest days of the video game industry through to the present; contemporary trailblazers Kellee Santiago (Journey) and Casey Hudson (Mass Effect), who discuss contemporary relationships between those who create games and those who play them; and scholars Ian Bogost (How to Do Things With Videogames) and Edward Castronova (Exodus to the Virtual World), who discuss how to research and write about games in ways that engage a range of audiences. These experts and others offer fascinating perspectives on video games, game studies, gaming culture, and the game industry more broadly.
Thinking and Learning with ICT: Raising Achievement in Primary Classrooms
by Lyn Dawes Rupert WegerifPrimary teachers need to incorporate the use of computers in their daily lesson plans, but how can this be done most effectively to promote learning skills in the classroom? In this fascinating book, Lyn Dawes and Rupert Wegerif outline a strategy for enhancing the effectiveness of computers for teaching and learning with an emphasis on: * raising pupil achievement in the core subject areas* developing collaborative learning in small groups* using group discussions as a way of improving general communication, as well as thinking and reasoning skills. The approach is to use computers as a support for collaborative learning in small groups and this book presents ways to prepare pupils for talking, learning and thinking together around computers. Excerpts from pupils' discussions illustrate the main issues and guidance on lesson planning and developing and choosing appropriate software is also provided. Thinking and Learning with ICT will be a valuable resource for primary teachers and student teachers.
Thinking as Computation: A First Course (The\mit Press Ser.)
by Hector J. LevesqueStudents explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought. This book guides students through an exploration of the idea that thinking might be understood as a form of computation. Students make the connection between thinking and computing by learning to write computer programs for a variety of tasks that require thought, including solving puzzles, understanding natural language, recognizing objects in visual scenes, planning courses of action, and playing strategic games. The material is presented with minimal technicalities and is accessible to undergraduate students with no specialized knowledge or technical background beyond high school mathematics. Students use Prolog (without having to learn algorithms: “Prolog without tears!”), learning to express what they need as a Prolog program and letting Prolog search for answers.After an introduction to the basic concepts, Thinking as Computation offers three chapters on Prolog, covering back-chaining, programs and queries, and how to write the sorts of Prolog programs used in the book. The book follows this with case studies of tasks that appear to require thought, then looks beyond Prolog to consider learning, explaining, and propositional reasoning. Most of the chapters conclude with short bibliographic notes and exercises. The book is based on a popular course at the University of Toronto and can be used in a variety of classroom contexts, by students ranging from first-year liberal arts undergraduates to more technically advanced computer science students.
Thinking in LINQ
by Sudipta MukherjeeLINQ represents a paradigm shift for developers used to an imperative/object oriented programming style, because LINQ draws on functional programming principles. Thinking in LINQ addresses the differences between these two by providing a set of succinct recipes arranged in several groups, including: Basic and extended LINQ operators Text processing Loop refactoring Monitoring code health Reactive Extensions (Rx. NET) Building domain-specific languages Using the familiar "recipes" approach, Thinking in LINQ shows you how to approach building LINQ-based solutions, how such solutions are different from what you already know, and why they're better. The recipes cover a wide range of real-world problems, from using LINQ to replace existing loops, to writing your own Swype-like keyboard entry routines, to finding duplicate files on your hard drive. The goal of these recipes is to get you "thinking in LINQ," so you can use the techniques in your own code to write more efficient and concise data-intensive applications. What you'll learn Basic and extended LINQ operators Text processing Loop refactoring Monitoring code health Reactive Extensions (Rx. NET) Building domain-specific languages Who this book is for . NET programmers who are comfortable with some high level programming language like C++/C#. Prior knowledge of LINQ is helpful but not required. Table of Contents 1. Thinking Functionally 2. Series Generation 3. Text Processing 4. Refactoring with LINQ 5. Refactoring with MoreLINQ 6. Creating DSL using LINQ 7. Static Code Analysis 8. Exploratory Data Analysis 9. Interacting with the File System Appendix A: Lean LINQ Tips Appendix B: Taming Streaming Data with Rx. NET
Thinking in Pandas: How to Use the Python Data Analysis Library the Right Way
by Hannah StepanekUnderstand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, by exploring its underlying implementation and data structures. Thinking in Pandas introduces the topic of big data and demonstrates concepts by looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects by size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered.By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects by utilizing pandas—the right way.What You Will LearnUnderstand the underlying data structure of pandas and why it performs the way it does under certain circumstancesDiscover how to use pandas to extract, transform, and load data correctly with an emphasis on performanceChoose the right DataFrame so that the data analysis is simple and efficient.Improve performance of pandas operations with other Python libraries Who This Book Is ForSoftware engineers with basic programming skills in Python keen on using pandas for a big data analysis project. Python software developers interested in big data.
Thinking in Promises: Designing Systems for Cooperation
by Mark BurgessImagine a set of simple principles that could help you to understand how parts combine to become a whole, and how each part sees the whole from its own perspective. If such principles were any good, it shouldn’t matter whether we’re talking about humans on a team, birds in a flock, computers in a datacenter, or cogs in a Swiss watch. A theory of cooperation ought to be pretty universal, so we should be able to apply it both to technology and to the workplace.Such principles are the subject of Promise Theory, and the focus of this insightful book. The goal of Promise Theory is to reveal the behavior of a whole from the sum of its parts, taking the viewpoint of the parts rather than the whole. In other words, it is a bottom-up, constructionist view of the world. Start Thinking in Promises and find out why this discipline works for documenting system behaviors from the bottom-up.
Thinking with Data: How to Turn Information into Insights
by Max ShronMany analysts are too concerned with tools and techniques for cleansing, modeling, and visualizing datasets and not concerned enough with asking the right questions. In this practical guide, data strategy consultant Max Shron shows you how to put the why before the how, through an often-overlooked set of analytical skills.Thinking with Data helps you learn techniques for turning data into knowledge you can use. You’ll learn a framework for defining your project, including the data you want to collect, and how you intend to approach, organize, and analyze the results. You’ll also learn patterns of reasoning that will help you unveil the real problem that needs to be solved.Learn a framework for scoping data projectsUnderstand how to pin down the details of an idea, receive feedback, and begin prototypingUse the tools of arguments to ask good questions, build projects in stages, and communicate resultsExplore data-specific patterns of reasoning and learn how to build more useful argumentsDelve into causal reasoning and learn how it permeates data workPut everything together, using extended examples to see the method of full problem thinking in action
Thinking, Drawing, Modelling: GEOMETRIAS 2017, Coimbra, Portugal, June 16–18 (Springer Proceedings in Mathematics & Statistics #326)
by Vera Viana Vítor Murtinho João Pedro XavierThis book presents a selection of papers from the International Conference Geometrias’17, which was hosted by the Department of Architecture at the University of Coimbra from 16 to 18 June 2017. The Geometrias conferences, organized by Aproged (the Portuguese Geometry and Drawing Teachers’ Association), foster debate and exchange on practical and theoretical research in mathematics, architecture, the arts, engineering, and related fields.Geometrias’17, with the leitmotif “Thinking, Drawing, Modelling”, brought together a group of recognized experts to discuss the importance of geometric literacy and the science of representation for the development of scientific and technological research and professional practices. The 12 peer-reviewed papers gathered here show how geometry, drawing, stereotomy, and the science of representation are still at the core of every act leading to the conception and materialization of form, and highlight their continuing relevance for scholars and professionals in the fields of architecture, engineering, and applied mathematics.
Third Congress on Intelligent Systems: Proceedings of CIS 2022, Volume 1 (Lecture Notes in Networks and Systems #608)
by K. Balachandran Sandeep Kumar Jagdish Chand Bansal Joong Hoon Kim Harish SharmaThis book is a collection of selected papers presented at the Third Congress on Intelligent Systems (CIS 2022), organized by CHRIST (Deemed to be University), Bangalore, India, under the technical sponsorship of the Soft Computing Research Society, India, during September 5–6, 2022. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as the Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision-making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human-computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.
Third Congress on Intelligent Systems: Proceedings of CIS 2022, Volume 2 (Lecture Notes in Networks and Systems #613)
by K. Balachandran Sandeep Kumar Jagdish Chand Bansal Joong Hoon Kim Harish SharmaThis book is a collection of selected papers presented at the Third Congress on Intelligent Systems (CIS 2022), organized by CHRIST (Deemed to be University), Bangalore, India, under the technical sponsorship of the Soft Computing Research Society, India, during September 5–6, 2022. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as the Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision-making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human-computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.
Third Generation Internet Revealed: Reinventing Computer Networks with IPv6
by Lawrence E. HughesThis book covers the inexorable exhaustion of the IPv4 address space, the interim fix to this based on Network Address Translation (NAT) and Private Addresses, and the differences between IPv4 and IPv6. It will help you understand the limitations and problems introduced by the use of NAT and introduce you to the far simpler network and software designs possible, using a larger, unified address space.IPv6, a mature and viable replacement for IPv4, is currently used by more than 36% of all global Internet traffic. Wireless telephone service providers in many countries have migrated their networks to IPv6 with great success. The elimination of NAT and Private Addresses has vastly simplified network design and implementation. Further, there are now enough public addresses allocated to accommodate all anticipated uses for the foreseeable future. Most networking products and software, especially open-source software, are already fully IPv6 compliant. Today, no business should purchase obsolete products that support only IPv4. The global IPv6 Forum estimates that there are millions of networking professionals still needing to learn the fundamentals of IPv6 technologies to move forward. This book is for them. With plans in place for a shutdown of IPv4 on global networks (“Sunset IPv4”) the time to learn is now. If you want a job in IT, especially network hardware or software, and you don’t know IPv6, you are already obsolete. What You Will Learn This book serves as a guide to all relevant Internet Engineering Task Force (IETF) standards Request for Comments (RFCs), organized by topic and discussed in plain language Understand how IPv6 makes viable technologies such as multicast (for efficient global audio/video streaming), IPsec VPNs (for better security), and simpler VoIP Take “edge computing” to the limit by eliminating intermediary servers made necessary by IPv4 NAT–for example, making connections directly from my node to yours Discover how organizations can introduce IPv6 into existing IPv4 networks (“Dual Stack”), and then eliminate the legacy IPv4 aspects going forward (“Pure IPv6”) for the mandates going into place now (for example, US DoD requirements to move all networks to Pure IPv6)Recognize that 5G networking (the Grand Convergence of conventional networks and wireless service) depends heavily on the advanced features IPv6 Who This Book Is ForNetworking professionals. Readers should have at least some familiarity with the precursor protocol (IPv4) and legacy TCP/IP based networks. Some knowledge of network models, such as DoD four-layer model or OSI 7-layer model, is helpful to understand where the Internet Protocol fits into the larger picture. For network software developers using the Sockets API (in UNIX, Windows, etc.), this book will help you to understand the extensions to that API needed to work with IPv6.
Third International Conference on Image Processing and Capsule Networks: ICIPCN 2022 (Lecture Notes in Networks and Systems #514)
by João Manuel R. S. Tavares Joy Iong-Zong Chen Fuqian ShiThis book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations. Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.
Third International Congress on Information and Communication Technology: ICICT 2018, London (Advances in Intelligent Systems and Computing #797)
by Xin-She Yang Nilanjan Dey Amit Joshi Simon SherrattThe book includes selected high-quality research papers presented at the Third International Congress on Information and Communication Technology held at Brunel University, London on February 27–28, 2018. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IOT), and e-mining. Written by experts and researchers working on ICT, the book is suitable for new researchers involved in advanced studies.
Third World Citizens and the Information Technology Revolution
by Nivien SalehThis book challenges the widely-held view that the information technology (IT) revolution has empowered people in the Third World. Tracing the making of the global IT regime, it shows that governments and corporations of the wealthy countries dominated this process, systematically excluding representatives of low-income countries.