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Summary: A hands-on, readable guide to machine learning with R. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights and make new predictions. The 3rd edition features newer and better libraries, advice on ethical and bias issues, and an introduction to deep learning.

Summary: "This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"-- Provided by publisher.

Summary: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage.

Summary: Database System Concepts presents the fundamental concepts of database management in an intuitive manner geared toward allowing students to begin working with databases as quickly as possible. A familiarity with basic data structures, computer organization, and a high-level programming language are the only prerequisites. Important theoretical results are covered, but formal proofs are omitted. In place of proofs, figures and examples are used to suggest why a result is true. Extensive coverage of Big Data systems, from the user perspective, as well as from an internal perspective with extensive additions and modifications

Summary: Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the potential to outperform the classical first-principles modeling paradigm. This book bridges this transition, connecting the theory of probability, stochastic processes, functional analysis, numerical analysis, and differential geometry. It describes two classes of computational methods to leverage data for modeling dynamical systems. The first is concerned with data fitting algorithms to estimate parameters in parametric models that are postulated on the basis of physical or dynamical laws. The second is on operator estimation, which uses the data to nonparametrically approximate the operator generated by the transition function of the underlying dynamical systems. This self-contained book is suitable for graduate studies in applied mathematics, statistics, and engineering. Carefully chosen elementary examples with supplementary MATLAB® codes and appendices covering the relevant prerequisite materials are provided, making it suitable for self-study.-- Source other than the Library of Congress.

Summary: This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.

Summary: Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You'll Learn: Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.

Summary: It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.

Summary: Dive headfirst into Microsofts Computer Vision APIs through sample-driven scenarios! Imagine an app that describes to the visually impaired the objects around them, or reads the Sunday paper, a favorite magazine, or a street sign. Or an app that is capable of monitoring what is happening inside an area without human control, and then makes a decision based on interpreting an occurrence detected with a live camera. This book teaches developers Microsoft's Computer Vision APIs, a service capable of understanding and interpreting the content of any image. Author Del Sole begins by providing a succinct need to knowoverview of the service with descriptions. You then learn from hands-on demonstrations that show how basic C# code examples can be re-used across platforms. From there you will be guided through two different kinds of applications that interact with the service in two different ways: the more common means of calling a REST service to get back JSON data, and via the .NET libraries that Microsoft has been building to simplify the job (this latter one with Xamarin).רat Youll Learn Understand AIs role and how devices and applications use sophisticated algorithms to improve peoples lives and business tasks. Analyze images for Optical Character Recognition to detect written words and sentences Think about the next-generation applications in relation to your customersneeds Get up-to-speed on the latest version of the Computer Vision service, which now comes through Azure Set up an Azure subscription in order to access the Cognitive Services within the portal After reading this book, you will be able to get started with AI services from Microsoft in order to begin building powerful new apps for your company or customers.רo This Book Is Forĥvelopers just getting familiar with artificial intelligence. A minimal knowledge of C# is required.

Summary: Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You'll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. You will: Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code.

Summary: Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation. In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system. The book emphasizes four important topics: The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. Deep-dive topics will include Spark, H20, Vopal Wabbit (NLP), Stanford NLP, and other appropriate toolkits and plugins. Best practices and structured design principles. This will include strategic topics as well as the how to example portions. The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples. Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system.

Summary: This book presents a coherent, novel vision of Smart Cities, built around a value-driven architecture. It describes the limitations of the contemporary notion of the Smart City and argues that the next developmental step must actively include not only the physical infrastructure, but information technology and human infrastructure as well, requiring the intensive integration of technical solutions from the Internet of Things (IoT) and social computing. The book is divided into five major parts, the first of which provides both a general introduction and a coherent vision that ties together all the components that are required to realize the vision for Smart Cities. Part II then discusses the provisioning and governance of Smart City systems and infrastructures. In turn, Part III addresses the core technologies and technological enablers for managing the social component of the Smart City platform. Both parts combine state-of-the-art research with cutting-edge industrial efforts in the respective fields. Lastly, Part IV details a road map to achieving Cyber-Human Smart Cities. Rounding out the coverage, it discusses the concrete technological advances needed to move beyond contemporary Smart Cities and toward the Smart Cities of the future. Overall, the book provides an essential overview of the latest developments in the areas of IoT and social computing research, and outlines a research roadmap for a closer integration of the two areas in the context of the Smart City. As such, it offers a valuable resource for researchers and graduate students alike.

Summary: Conceptual modeling has always been one of the main issues in information systems engineering as it aims to describe the general knowledge of the system at an abstract level that facilitates user understanding and software development. This collection of selected papers provides a comprehensive and extremely readable overview of what conceptual modeling is and perspectives on making it more and more relevant in our society. It covers topics like modeling the human genome, blockchain technology, model-driven software development, data integration, and wiki-like repositories and demonstrates the general applicability of conceptual modeling to various problems in diverse domains. Overall, this book is a source of inspiration for everybody in academia working on the vision of creating a strong, fruitful and creative community of conceptual modelers. With this book the editors and authors want to honor Prof. Antoni Olivé for his enormous and ongoing contributions to the conceptual modeling discipline. It was presented to him on the occasion of his keynote at ER 2017 in Valencia, a conference that he has contributed to and supported for over 20 years. Thank you very much to Antoni for so many years of cooperation and friendship.

Summary: One of the definitive leaps in the progress of science and technology in the past few decades has been the development of machines which exhibit intelligence. This intelligence displayed by machines is known as artificial intelligence. The capabilities classified as artificial intelligence are the competence of understanding human speech, understanding complex data, etc. Artificial intelligence in the 21st century has become an integral part of the industrial sector as it helps in solving a number of issues. The various advancements in artificial intelligence are glanced at in this book, and their applications as well as ramifications are looked at in detail. With state-of-the-art inputs by acclaimed experts of this field, this book targets students and professionals.

Summary: The various sub-fields of robotics along with technological progress that have future implications are glanced at in this book. This discipline is multidisciplinary in nature borrowing from fields such as mechanical engineering and computer science that deals with the design, construction, operation and use of robots. This book elucidates the concepts and innovative models around prospective developments with respect to robotics and biomimetics. The text also provides a broad spectrum of topics to its readers for a better understanding of the subject with state-of-the-art inputs by acclaimed experts of this field, this book targets students and professionals. From theories to research to practical applications case studies related to all contemporary topics of relevance to this field have been included in this book.

Summary: Robotics is concerned with the design, operation, construction and use of robots. It is an umbrella field which includes concepts from various disciplines such as electronic engineering, computer science, mechanical engineering and information engineering. Robotics is also involved in the usage and designing of computer systems for information processing and controlling robots. Some of the important components of robots are power course, actuators, sensors and manipulators. Robots are used in dangerous environments like bomb detection and deactivation. There are various kinds of robots such as military robots, agricultural robots, medical robots, industrial robots, collaborative robots, nanorobots, domestic robots, and autonomous drones. This book presents the complex subject of robotics in the most comprehensible and easy to understand language. Most of the topics introduced herein cover new techniques and the applications of this discipline. The book is appropriate for those seeking detailed information in this area.

Summary: The branch of computer science which studies the intelligence demonstrated by machines is known as artificial intelligence. It has helped in developing solutions in the field of computer science. Some of the tools used in the process are search and optimization, probabilistic methods for uncertain reasoning, classifiers and statistical learning methods, etc. Artificial intelligence is mainly used in autonomous vehicles, medical diagnosis, video games, security surveillance, search engines, etc. This book unravels the recent studies in the field of artificial intelligence. For all those who are interested in artificial intelligence, this book can prove to be an essential guide. It will serve as a valuable source of reference for graduate and postgraduate students.

Summary: Artificial intelligence and knowledge management have transformed the process of knowledge circulation and database management in different business enterprises and corporate organizations. Some of the significant topics discussed in the chapters of this book are AI planning strategies and tools, AI tools for information processing, data mining, knowledge-based systems, etc. It explores the innovative concepts and advancements in these emerging fields. The book is an invaluable source of knowledge for students and researchers involved in this field at various levels.

Summary: The intelligence displayed by machines is known as artificial intelligence. It aims to advance the reasoning, processing and learning abilities of machines through statistical models, computational intelligence, etc. Artificial intelligence has applications in multiple industries such as healthcare, automotive, finance, etc. This book unfolds the innovative aspects of artificial intelligence that will be crucial for the progress of this field in the future. The extensive content of this book provides the readers with a thorough understanding of the subject. As this field is emerging at a rapid pace, the contents of this book will help the readers understand the modern concepts and applications of the subject.

Summary: This book provides the connection between the growing body of literature on sustainability and the topics of energy and ICT. It aims to show how stakeholders active in this area need to play their part ensuring that the ICT-sector evolves towards a sector that can lead through “greening by IT” and also shows that it can “green its own IT” as well. This is the first book that integrates two seemingly incompatible approaches to sustainability: efficiency and effectiveness. The book builds on the efficiency initiatives already taken by industry, but it is not a “how-to-do-it manual”. It offers insight in state of the art approaches to green IT and greening by IT. Attention to important stakeholders outside the sector, e.g. policy makers and the field of education, makes this book comprehensive. A more encompassing view on ICT and sustainability is offered to the reader and, as such, managers in higher education, educators, CIO’s, policymakers and regulators are inspired to integrate their efforts and to contribute to a transition of one of the most important and prominent sectors in our global economy.

Summary: An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily p

Summary: Written with the aim of becoming the primary resource for students of business analytics, this book provides a holistic perspective of analytics with theoretical foundations and applications of the theory using examples across several industries.

Summary: Optimization plays an invaluable role in the exciting and rapidly developing field of computer vision, yet this importance is often overlooked in the literature. This practical and authoritative text/reference presents a broad introduction to the optimization methods used specifically in computer vision. In order to facilitate understanding, the presentation of the methods is supplemented by simple flow charts, followed by pseudocode implementations that reveal deeper insights into their mode of operation. These discussions are further supported by examples taken from important applications in computer vision. Topics and features: Provides a comprehensive overview of computer vision-related optimization Covers a range of techniques from classical iterative multidimensional optimization to cutting-edge topics of graph cuts and GPU-suited total variation-based optimization Describes in detail the optimization methods employed in computer vision applications Illuminates key concepts with clearly written and step-by-step explanations Presents detailed information on implementation, including pseudocode for most methods This easy-to-follow and applications-focused book is an essential resource for researchers and practitioners seeking guidance on implementing specific methods in computer vision. Marco Alexander Treiber is a software developer at ASM Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly. Among his other publications is the successful Springer title An Introduction to Object Recognition.

Summary: This textbook provides a progressive approach to the teaching of software engineering. First, readers are introduced to the core concepts of the object-oriented methodology, which is used throughout the book to act as the foundation for software engineering and programming practices, and partly for the software engineering process itself. Then, the processes involved in software engineering are explained in more detail, especially methods and their applications in design, implementation, testing, and measurement, as they relate to software engineering projects. At last, readers are given the chance to practice these concepts by applying commonly used skills and tasks to a hands-on project. The impact of such a format is the potential for quicker and deeper understanding. Readers will master concepts and skills at the most basic levels before continuing to expand on and apply these lessons in later chapters.

Summary: Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers, and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? John MacCormick answers this question in language anyone can understand, using vivid examples to explain the fundamental tricks behind nine computer algorithms that power our PCs, tablets, and smartphones.

Summary: You email your report, check the position of your stocks, play your favourite Rahman, and upload new patches for your favourite simulation game all using the same three-inch-by-five device that fits into your palm. You chat, share, play and blog, even check for directions to the new Italian restaurant in town online. Everyday life is now digital. Digital Cool examines life in the age of New Media. From Facebook to Internet dating, tablets to Twitter, cyber avatars to Wikis it tells the story of how human lives today are heavily mediated by cool technologies, and how the technologies themselves are mediated by our ways of living, playing, working. Digital Cool is simultaneously about individualisation, with its make-believe detachment ( Cool ), and the fierce collectivism facilitated by New Media. There s the young woman waiting for the tube while swishing through the bestseller she s just bought on her iPad, indifferent to her surroundings; there is also the fury of the mainly online Pink Chaddis campaign of 2009, the collaborative radical political critique of kafila.org, or the arrival of Spring in Tahrir, with its unforgettable images of Google executive Wael Ghonim coordinating revolution on Facebook, accessed on his smartphone. US Congressmen tweeted President Obama s first State of the Union address as he spoke, the world was alerted to Andres Iniesta s World Cup-winning goal on Twitter, and the incredible landing of US Airways Flight 1549 on the Hudson was first reported on the microblogging site. Twitter is today the cool way to update followers ; YouTube is the platform on which a participatory culture and the sense of belonging to a community play out. Digital technology empowers, enthuses, informs and mediates new forms of community, activism and identity. Culture jamming, participatory journalism and commons knowledge are all components of the activist new media, but also of popular culture. Wide-ranging, accessible and incisive---welcome readers, to the world of Digital Cool! Click here to enter.

Summary: "This book reviews and surveys new forward-thinking research and development in face image analysis technologies"--Provided by publisher.

Summary: Reconfigurable systems have pervaded nearly all fields of computation and will continue to do so for the foreseeable future. Reconfigurable System Design and Verification provides a compendium of design and verification techniques for reconfigurable systems, allowing you to quickly search for a technique and determine if it is appropriate to the task at hand. It bridges the gap between the need for reconfigurable computing education and the burgeoning development of numerous different techniques in the design and verification of reconfigurable systems in various application domains. The text explains topics in such a way that they can be immediately grasped and put into practice. It starts with an overview of reconfigurable computing architectures and platforms and demonstrates how to develop reconfigurable systems. This sets up the discussion of the hardware, software, and system techniques that form the core of the text. The authors classify design and verification techniques into primary and secondary categories, allowing the appropriate ones to be easily located and compared. The techniques discussed range from system modeling and system-level design to co-simulation and formal verification. Case studies illustrating real-world applications, detailed explanations of complex algorithms, and self-explaining illustrations add depth to the presentation. Comprehensively covering all techniques related to the hardware-software design and verification of reconfigurable systems, this book provides a single source for information that otherwise would have been dispersed among the literature, making it very difficult to search, compare, and select the technique most suitable. The authors do it all for you, making it easy to find the techniques that fit your system requirements, without having to surf the net or digital libraries to find the candidate techniques and compare them yourself.

Summary: The evolution of the mobile communication market is causing a major increase in data traffic demands. This could lead to disrupted mobility and intermittent degraded channel conditions that contribute to poor transmission control protocol (TCP) performance. TCP Performance over UMTS-HSDPA Systems presents a comprehensive study of the effect of TCP on achieved application bit rate performance and system capacity, and shows how to reduce the interaction of wireless networks on TCP with minimal cost. With self-contained chapters, the book consists of two main sections. The first several chapters provide background and describe the state of the art for wireless networks, emphasizing one of the third-generation (3G) wireless technologies: the universal mobile telecommunications system (UMTS). These chapters also include an analysis of the overall cell capacity for UMTS Release 99 and high-speed downlink packet access (HSDPA) systems. The second section focuses on the interaction of TCP with wireless systems, presenting an exhaustive list of TCP versions and link layer solutions that adapt TCP (often modifying the original TCP) to a wireless network. This section also displays mathematical modeling of the interaction of hybrid automatic repeat request (HARQ) and TCP in UMTS networks. While offering information for advanced undergraduate students who are unfamiliar with code division multiple access (CDMA) wireless systems as well as UMTS and HSDPA cellular systems, the book also provides extensive coverage of "TCP over wireless systems" problems and solutions for researchers, developers, and graduate students.

Summary: "This book investigates the integration of security concerns into software engineering practices, drawing expertise from the security and the software engineering community; and discusses future visions and directions for the field of secure software engineering"--Provided by publisher.

Summary: This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.

Summary: Current IT developments like component-based development and Web services have emerged as effective ways of building complex enterprise-scale information systems and providing enterprise application integration. To aid this process, platforms such as .NET and WebSphere have become standards in web-based systems development. However, there are still a lot of issues that need to be addressed before service-oriented software engineering (SOSE) becomes a prominent and widely accepted paradigm for enterprise information systems development and integration. This book provides a comprehensive view of SOSE through a number of different perspectives. Some of those perspectives include: service-based concepts, modeling and documentation, service discovery and composition, service-oriented architecture, model-driven development of service-oriented applications, service security and service-orientation in mobile settings. The book provides readers with an in-depth knowledge of the main challenges and practices in the exciting, new world of service-oriented software engineering. Addressing both technical and organizational aspects of this new field, it offers a balance making it valuable to a variety of readers, including IT architects, developers, managers, and analysts.

Summary: A state-of-the-art survey of recent advances in data mining or knowledge discovery. Data mining, or knowledge discovery, has become an indispensable technology for businesses and researchers in many fields. Drawing on work in such areas as statistics, machine learning, pattern recognition, databases, and high performance computing, data mining extracts useful information from the large data sets now available to industry and science. This collection surveys the most recent advances in the field and charts directions for future research. The first part looks at pervasive, distributed, and stream data mining, discussing topics that include distributed data mining algorithms for new application areas, several aspects of next-generation data mining systems and applications, and detection of recurrent patterns in digital media. The second part considers data mining, counter-terrorism, and privacy concerns, examining such topics as biosurveillance, marshalling evidence through data mining, and link discovery. The third part looks at scientific data mining; Topics include mining temporally-varying phenomena, data sets using graphs, and spatial data mining. The last part considers web, semantics, and data mining, examining advances in text mining algorithms and software, semantic webs, and other subjects.

Summary: Human-computer interaction (HCI) is the study of human-computer interaction through interfaces. Such an interaction is analogous to human-to-human interaction. Graphical user interfaces and multi-modal interfaces enable humans to engage with embodied character agents. The techniques of operating systems, computer graphics, programming languages and developing environments are vital to this field. Human-machine interfaces, if poorly designed can lead to systems failure and accidents. Research in HCI is focused on the improvement in the usability of human-computer interfaces for improved interaction. Further, emphasis is placed on the development of design methodologies, prototyping of software and hardware systems, experimentation with devices, exploration of interaction paradigms, etc. The three areas of personal information management (PIM), computer-supported cooperative work (CSCW) and human interaction management (HIM) have significant overlap with HCI. While PIM studies the way people use and acquire personal information to complete tasks, CSCW focuses on the use of computing systems for collaborative work. HIM extends the scope of CSCW to the level of organizations. Human-computer interaction is an upcoming field of technology that has undergone rapid development over the past few decades. This book will help the readers in keeping pace with the rapid changes in this field.