Computer science Books

Book SynopsisIntroduce your students to the important new features that the latest version of Microsoft Office has to offer with the focused approach found in MICROSOFT Office 365 & WINDOWS 2019: COMPREHENSIVE. Part of the acclaimed Shelly Cashman Series, this edition continues the series' strong history of innovation with an enhanced learning approach designed to engage students, improve retention and prepare learners for success with Microsoft Windows. A trademark step-by-step, screen-by-screen approach encourages students to expand their understanding of the software through experimentation, critical thought and personalization while also engaging them in real-world scenarios to reinforce critical skills to make them successful in their educational and professional careers. In addition, MindTap and updated SAM (Skills Assessment Manager) online resources are available to guide additional study and ensure successful results.Table of Contents1. Introduction to Windows 10. 2. Working with the Windows 10 Desktop. 3. File and Folder Management. 4. Personalizing Your Work Environment. 5. Advanced Personalization and Customization. 6. Advanced Searching Techniques. 7. Microsoft Edge. 8. Mastering Digital Media. 9. Understanding Security, Networking and Utilities. Index.

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Book SynopsisTable of ContentsWord 8: Using Collaboration, Integration, and Charts. Word 9: Creating a Reference Document. Word 10: Creating an Online Form. Word 11: Enhancing an Online Form and Using Macros. PPT 8: Creating Photo Albums and Delivering Presentations. Excel 8: Working with Trendlines, Pivot Table Reports, PivotChart Reports, and Slicers. Excel 9: Formula Auditing, Data Validation, and Complex Problem Solving. Excel 10: Data Analysis with Power Tools and Creating Macros. Excel 11: User Interfaces, Visual Basic for Applications (VBA), and Collaboration Features in Excel. Access 8: Macros, Navigation Forms, and Control Layouts. Access 9: Administering a Database System. Access 10: Using SQL. Access 11: Database Design. Index.

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Book SynopsisIntroduce your students to the important new features that the latest version of Microsoft Office has to offer with the focused approach found in MICROSOFT Office 365 & WINDOWS 2019: COMPREHENSIVE. Part of the acclaimed Shelly Cashman Series, this edition continues the series' strong history of innovation with an enhanced learning approach designed to engage students, improve retention and prepare learners for success with Microsoft Windows. A trademark step-by-step, screen-by-screen approach encourages students to expand their understanding of the software through experimentation, critical thought and personalization while also engaging them in real-world scenarios to reinforce critical skills to make them successful in their educational and professional careers. In addition, MindTap and updated SAM (Skills Assessment Manager) online resources are available to guide additional study and ensure successful results.Table of Contents1. Managing Email Messages with Outlook. 2. Managing Calendars with Outlook. 3. Managing Contacts and Personal Contact Information with Outlook 4. Creating and Managing Tasks with Outlook. 5. Customizing Outlook. Index.

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Book SynopsisLearn the principles of MIS as you explore the latest developments and industry trends with MIS 10. This practically focused approach helps you master foundational MIS concepts that will guide your career. You examine the latest topics, such as cloud computing, AR/VR, quantum computing and blockchain, with the most current MIS title on the market. Have you ever wondered what you would have done as a company leader in a critical moment? With this edition's MindTap digital experience, you can strengthen your decision-making skills with "YouDecide" -- new interactive case studies that bridge technology and business strategy and position you as the decision maker. You can also examine possible career paths with new career connection videos. Delve deeper into key course concepts with new concept videos and foundational case studies. In addition, MindTap's RSS feeds alert you to the latest advancements and trends for a stronger focus on today's real business world.Table of Contents1. Information Systems in Business. 2. Computers and Their Business Applications. 3. Data and Business Intelligence. 4. Personal, Legal, Ethical, and Organizational Issues. 5. Protecting Information Resources. 6. Data Communication: Delivering Information Anywhere and Anytime. 7. A Connected World. 8. E-Commerce. 9. Global Information Systems. 10. Building Successful Information Systems. 11. Enterprise Systems. 12. Supporting Decisions and Processes. 13. Artificial Intelligence and Automation. 14. Emerging Trends, Technologies, and Applications.

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Book SynopsisGain a clear understanding of even the most complex, highly theoretical computational theory topics in the approachable presentation found only in the market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today's computational theory course, this revision continues the book's well-know, approachable style with timely revisions, additional practice, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. You gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E's comprehensive coverage makes this a valuable reference for your continued studies in theoretical computing.Table of ContentsIntroduction. PART 1: AUTOMATA AND LANGUAGES. 1. Regular Languages. 2. Context-Free Languages. PART 2: COMPUTABILITY THEORY. 3. The Church-Turing Thesis. 4. Decidability. 5. Reducibility. 6. Advanced Topics in Computability Theory. PART 3: COMPLEXITY THEORY. 7. Time Complexity. 8. Space Complexity. 9. Intractability. 10. Advanced Topics in Complexity Theory. Selected Bibliography.

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Book SynopsisTable of ContentsPart I: DATABASE CONCEPTS 1. Database Systems 2. Data Models Part II: DESIGN CONCEPTS 3. The Relational Database Model 4. Entity Relationship (ER) Modeling 5. Advanced Data Modeling 6. Normalization of Database Tables Part III: ADVANCED DESIGN AND IMPLEMENTATION 7. Introduction to Structured Query Language (SQL) 8. Advanced SQL 9. Database Design Part IV: ADVANCED DATABASE CONCEPTS 10. Transaction Management and Concurrency Control 11. Database Performance Tuning and Query Optimization 12. Distributed Database Management Systems 13. Business Intelligence and Data Warehouses 14. Big Data Analytics and NoSQL Part V: DATABASES AND THE INTERNET 15. Database Connectivity and Web Technologies Part VI: DATABASE ADMINISTRATION 16. Database Administration and Security ONLINE APPENDICES Appendix Aa: Designing Databases with Lucicharts: A Tutorial Appendix Ab: Designing Databases with Visio: A Tutorial Appendix B: The University Lab: Conceptual Design Appendix C: The University Lab: Conceptual Design Verification, Logical Design, and Implementation Appendix D: Converting the ER Model into a Database Structure Appendix E: Comparison of ER Model Notations Appendix F: Client/Server Systems Appendix G: Object-Oriented Databases Appendix H: Unified Modeling Language (UML) Appendix I: Databases in Electronic Commerce Appendix J: Web Database Development with ColdFusion Appendix K: The Hierarchical Database Model Appendix L: The Network Database Model Appendix M: Microsoft Access Tutorial Appendix N: Creating a New Database Using Oracle 12c Appendix O: Data Warehouse Implementation Factors Appendix P: Working with MongoDB Appendix Q: Working with Neo4j

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Book SynopsisDiscover the power of Java for developing applications today with the engaging, hands-on approach in Farrell's JAVA PROGRAMMING, 10th edition. Even if you're a first-time programmer, JAVA PROGRAMMING can show you step-by-step how to quickly start developing useful programs, all while mastering the basic principles of structured and object-oriented programming. Up-to-date, reader-friendly explanations and meaningful programming and collaboration exercises emphasize business applications, while useful debugging exercises and contemporary case problems further expand your understanding. Offering anywhere, anytime learning, MindTap equips you with an additional online learning platform, interactive learning tools and auto-graded coding labs for practicing and expanding your skills.Table of Contents1. Creating Java Programs. 2. Using Data. 3. Using Methods. 4. Using Classes and Objects. 5. Making Decisions. 6. Looping. 7. Characters, Strings, and the StringBuilder. 8. Arrays. 9. Inheritance and Interfaces. 10. Exception Handling. 11. File Input and Output. 12. Recursion. 13. Collections and Generics. 14. Introduction to Swing Components. Appendix A. Working with the Java Platform. Appendix B. Data Representation. Appendix C. Formatting Output. Appendix D. Generating Random Numbers. Appendix E. Javadoc. Appendix F. Java FX. Glossary. Index.

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Book SynopsisHelping you understand the technological foundations for a wide range of digital devices, New Perspectives Computer Concepts Comprehensive, 21st edition, presents what every learner should know about using technology to complete your education, launch a successful career and engage in issues that shape today's world. The book's proven learning path is structured with today's busy reader in mind. Leading tech author June Parsons combines the latest on emerging technology with detailed illustrations and interactive activities that help you quickly understand technical topics. This edition provides updated information on current operating systems, digital rights management, the deep web and dark web, videoconferencing, the pandemic's impact on tech jobs, work-at-home and more. A unique module provides a hands-on introduction to programming, while MindTap offers anywhere, anytime learning solutions.Table of ContentsModule 1: Digital Content Module 2: Digital Devices Module 3: Networks Module 4: The Web Module 5: Social Media Module 6: Software Module 7: Digital Security Module 8: The ICT Industry Module 9: Information Systems Module 10: Databases Module 11: Programming Module PY: Coding With Python

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Book SynopsisTable of Contents1. Being a Digital Citizen: At Home, School, and Work. 2. The Internet: Connecting and Communicating Online. 3. Hardware: Evaluating Options. 4. Programs and Apps: Productivity, Graphics, Security. 5. Digital Security: Ethics, Privacy, and Protection. 6. Input and Output: Extending Capabilities. 7. Digital Storage: Preserving Content. 8. Operating System: Managing and Coordinating Resources. 9. Networks: Communicating Across Devices. 10. Databases: Organizing and Accessing Data. 11. System and Application Development: Tools and Strategies. 12. Web Development: Publishing Online Content. 13. Technology Careers: Entering the Workforce. Appendix A: Technology Acronyms. Appendix B: Troubleshooting Computer and Mobile Device Problems.

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Book SynopsisTable of ContentsCOVER BRIEF CONTENTS CONTENTS GETTING TO KNOW MICROSOFT OFFICE VERSIONS USING SAM PROJECTS AND TEXTBOOK PROJECTS MICROSOFT WORD Module 4: Creating a Multipage Document Module 5: Creating a Resume and Sharing Documents Module 6: Using Mail Merge Module 7: Creating a Newsletter MICROSOFT POWERPOINT Module 4: Customizing Slide Masters and Presentations Module 5: Collaborating and Adding Animation Module 6: Formatting Tables and Charts Module 7: Adding Media and Enhancing SmartArt MICROSOFT EXCEL Module 4: Financial Functions, Data Tables, and Amortization Schedules Module 5: Working with Multiple Worksheets and Workbooks Module 6: Creating, Sorting, and Querying a Table Module 7: Creating Templates, Importing Data, and Working with SmartArt, Images, and Screenshots MICROSOFT ACCESS Module 4: Creating Reports and Forms Module 5: Multiple-Table Forms Module 6: Advanced Report Techniques Module 7: Advanced Form Techniques INDEX

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Book SynopsisHelping you quickly get up to speed, Hoisington's THE SHELLY CASHMAN SERIES MICROSOFT OFFICE 365 & OUTLOOK 2021 COMPREHENSIVE, 1st edition, includes the latest on Microsoft 365 and Office 2021 features along with enhanced support for Mac users. Its trademark step-by-step, screen-by-screen, project-based approach enables you to expand your understanding of Office applications through hands-on experimentation and critical thinking. Module Learning Objectives are mapped to Microsoft Office Specialist (MOS) certification objectives, reinforcing the critical skills needed for college and career success. Other Ways boxes reveal alternate click paths to achieve a step, while BTW call-outs offer helpful hints as you work through your projects so you can make the most of Microsoft Office tools. In addition, MindTap and SAM (Skills Assessment Manager) online resources help maximize your study time -- and results.Table of Contents1. Managing Email Messages with Outlook. 2. Managing Calendars with Outlook. 3. Managing Contacts and Personal Contact Information with Outlook 4. Creating and Managing Tasks with Outlook. 5. Customizing Outlook. Index.

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Book SynopsisTable of Contents1. An Overview of Computers and Programming. 2. Elements of High-Quality Programs. 3. Understanding Structure. 4. Making Decisions. 5. Looping. 6. Arrays. 7. File Handling and Applications. 8. Advanced Data Handling Concepts. 9. Advanced Modularization Techniques. 10. Object-Oriented Programming. 11. More Object-Oriented Programming Concepts. 12. Event-Driven GUI Programming, Multithreading, and Animation. Appendix A: Understanding Numbering Systems and Computer Codes. Appendix B: Solving Difficult Structuring Problems .

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Book SynopsisTable of Contents1. Information Systems in Business. 2. Computers and Their Business Applications. 3. Data and Business Intelligence. 4. Personal, Legal, Ethical, and Organizational Issues. 5. Protecting Information Resources. 6. Data Communication: Delivering Information Anywhere and Anytime. 7. A Connected World. 8. E-Commerce. 9. Global Information Systems. 10. Building Successful Information Systems. 11. Enterprise Systems. 12. Supporting Decisions and Processes. 13. Artificial Intelligence and Automation. 14. Emerging Trends, Technologies, and Applications.

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Book SynopsisToday, there are few in senior management positions who can afford to ignore modern information technology, and few individuals who would prefer to be without it. Modern IT is key to organizational performance; yet we often assume the benefits will occur without forethought or effort. As managerial tasks become more complex, so the nature of the required information systems changes â from structured, routine support to ad hoc, unstructured, complex enquiries at the highest levels of management. If taken for granted, serious implications can arise for organizations.This fifth edition of Strategic Information Management has been brought fully up to date with recent developments in the management of information systems, including digital transformation strategy, the issues surrounding big data and algorithmic decision-making. The book provides a rich source of material reflecting recent thinking on the key issues facing executives, drawing from a wide range of contemporarTrade Review"This fifth edition of Strategic Information Management updates and extends a unique selection of theories and valuable practice insights, established in the previous editions, and offers a roadmap for executives navigating in the digital landscape and coping with the digitization challenges associated with organizational transformation. The book has the right balance of theoretical frameworks and practical insights. Taken together, the book reflects recent thinking regarding many of the key issues facing executives in getting the most out of their investments in information technology and digitalization initiatives, highlighting the complex strategy, organizational and governance issues involved." — IOANNA CONSTANTIOU, Copenhagen Business School, Denmark"I'm pleased the editors of Strategic Information Management have produced this 5th edition, which represents a major overhaul, including online supporting materials not available with prior editions. Particularly valuable is the amplification of theory in this edition – not theory for theory's sake, but rather practice-guiding theory; the implication being that we are all researchers and that complex matters demand research and unique approaches and solutions. I strongly encourage students and practitioners to assume an evidence-based practice perspective when reading and reflecting on these writings which, combined, provide a much-needed stimulus for critical thinking on these complex matters in what are challenging times." — GUY GABLE, Queensland University of Technology, Australia"The fifth edition of Strategic Information Management has great value in providing directions for practitioners and scholars towards an understanding of the strategic importance and managerial challenges of digital transformation in today’s organizations. With inputs from international scholars, the book offers really useful management frameworks and principles to help in understanding how organizations and industries are transformed by disruptive digital technologies." — CAROL HSU, Tongji University, China"This fifth edition of Strategic Information Management updates and strengthens what has long served as a vehicle through which current and future executives obtain a foundational understanding as well as pragmatic insights regarding a host of strategic and managerial issues associated with the digital transformation of organizations. As with the earlier editions, the authors refuse to fall into the too-often-taken route of providing readers with a handbook offering ‘one-size-fits-all’ practices and procedures – solutions which ultimately fail to align with the situations faced by readers. Instead, the editors successfully provide readers with exposures to critical themes and frameworks and to illustrations of how some of our brightest executives are applying these in addressing digitalization initiatives and challenges – providing readers with the capability to formulate workable solutions to many, if not most, of the situations they face in their digital transformation efforts." — ROBERT W. ZMUD, University of Oklahoma, USA"This fifth edition of Strategic Information Management updates and extends a unique selection of theories and valuable practice insights, established in the previous editions, and offers a roadmap for executives navigating in the digital landscape and coping with the digitization challenges associated with organizational transformation. The book has the right balance of theoretical frameworks and practical insights. Taken together, the book reflects recent thinking regarding many of the key issues facing executives in getting the most out of their investments in information technology and digitalization initiatives, highlighting the complex strategy, organizational and governance issues involved." – IOANNA CONSTANTIOU, Copenhagen Business School, Denmark"I'm pleased the editors of Strategic Information Management have produced this 5th edition, which represents a major overhaul, including online supporting materials not available with prior editions. Particularly valuable is the amplification of theory in this edition – not theory for theory's sake, but rather practice-guiding theory; the implication being that we are all researchers and that complex matters demand research and unique approaches and solutions. I strongly encourage students and practitioners to assume an evidence-based practice perspective when reading and reflecting on these writings which, combined, provide a much-needed stimulus for critical thinking on these complex matters in what are challenging times." – GUY GABLE, Queensland University of Technology, Australia"The fifth edition of Strategic Information Management has great value in providing directions for practitioners and scholars towards an understanding of the strategic importance and managerial challenges of digital transformation in today’s organizations. With inputs from international scholars, the book offers really useful management frameworks and principles to help in understanding how organizations and industries are transformed by disruptive digital technologies." – CAROL HSU, Tongji University, China"This fifth edition of Strategic Information Management updates and strengthens what has long served as a vehicle through which current and future executives obtain a foundational understanding as well as pragmatic insights regarding a host of strategic and managerial issues associated with the digital transformation of organizations. As with the earlier editions, the authors refuse to fall into the too-often-taken route of providing readers with a handbook offering ‘one-size-fits-all’ practices and procedures – solutions which ultimately fail to align with the situations faced by readers. Instead, the editors successfully provide readers with exposures to critical themes and frameworks and to illustrations of how some of our brightest executives are applying these in addressing digitalization initiatives and challenges – providing readers with the capability to formulate workable solutions to many, if not most, of the situations they face in their digital transformation efforts." – ROBERT W. ZMUD, University of Oklahoma, USATable of ContentsPart 1: Foundations to IS Strategy and Strategizing 1. Historical Approaches: Experiences in Information Systems Planning 2. Further Reflections: Reflections on Information Systems Strategizing 3. A Critique: On Confronting Some of the Common Myths of IS Strategy 4. Conceptual Developments: Further Developments in Information Systems Strategizing: Unpacking the Concept 5. Aligning Practices: Aligning in Practice: From Current Cases to a New Agenda Part 2: Digital Transformation and Organizational Transformation 6. Navigating digital transformation: How Big Old Companies Navigate Digital Transformation 7. Formulating a digital strategy: Options for Formulating a Digital Transformation Strategy 8. Building Digital Capabilities: How Lego Built the Foundations and Entreprise Capabilities for Digital Leadership 9. Chief Digital Officers: How Chief Digital Officers Promote the Digital Transformation of their Companies 10. Power Dynamics: Strategic Information Systems and Organizational Power Dynamics Part 3: Organizing and Governing the IS Function 11. Principles and models: Principles and Models for Organizing the IT Function 12. Managing in economic decline: How CIOs Manage IT during Economic Decline: Surviving and Thriving Amid Uncertainty 13. CIO profiles: CIO Leadership Profiles: Implications of Matching CIO Authority and Leadership Capability on IT Impact 14. Alternative roles for Chief Digital Officers: Three Types of Chief Digital Officers and the Reasons Organizations Adopt the Role 15. The IS organization: Rethinking the concept: Rethinking the Concept of the IS Organization Part 4: Some Current and Emerging Challenges 16. Opening strategy through social media: Social Media and the Emergence of Reflexiveness as a New Capability for Open Strategy 17. Organizational socialization and social media: An Affordance Perspective of Social Media and Organizational Socialization 18. Decision support systems failures: When Decision Support Systems Fail: Insights for Strategic Information Systems from Formula 1 19. Opportunities and challenges of datification: Strategic Opportunities (and Challenges) of Algorithmic Decision-Making: A Call for Action on the Long-Term Societal Effects of 'Datification' 20. Ethical issues: Ethical Issues in the Big Data Industry

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Book SynopsisThe book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts like object classification, object tracking, image-based rendering, and image registration. Intended to be a companion to a typical teaching course on computer vision, the book takes a problem-solving approach.Table of ContentsPart I Image Formation and Image Processing. 1 Introduction to Computer Vision and Basic Concepts of Image Formation. 2 Image Processing Concepts. Part II Image Features. 3 Image Descriptors and Features. Part III Recognition. 4 Fundamental Pattern Recognition Concepts. Part IV Applications. 5 Applications of Computer Vision.

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Book SynopsisThis is a book about the development of dependable, embedded software. It is for systems designers, implementers, and verifiers who are experienced in general embedded software development, but who are now facing the prospect of delivering a software-based system for a safety-critical application. It is aimed at those creating a product that must satisfy one or more of the international standards relating to safety-critical applications, including IEC 61508, ISO 26262, EN 50128, EN 50657, IEC 62304, or related standards.Of the first edition, Stephen Thomas, PE, Founder and Editor of FunctionalSafetyEngineer.com said, I highly recommend Mr. Hobbs' book. Table of ContentsPart 1: Background. 1. Introduction. 2. Terminology of Safety. 3. Safety Standards and Certification. 4. Representative Companies. Part 2: The Project. 5. Foundational Analyses. 6. Certified and Uncertified Components. Part 3: Design Patterns. 7. Architectural Balancing. 8. Error Detection and Handling. 9. Expecting the Unexpected. 10 Replication and Diversification. Part 4: Design Validation. 11. Markov Models. 12. The Fault Tree. 13. Software Failure Rates. 14. Semi-Formal Design Verification. 15. Formal Design Verification. Part 5: Coding. 16. Coding Guidelines. 17. Code Coverage Metrics. 18. Static Analysis. Part 6: Verification. 19. Integration Testing. 20. The Tool Chain. 21. Conclusion. Part 7: Appendices. A. Goal Structuring Notation. B. Bayesian Belief Networks. C .Calculating (2+3)+4. D. Notations.

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Book SynopsisIt takes 17 years on average to bring new medical treatments ideas into evidence-based clinical practice. The growing replicability crisis in science further delays these new miracles. Blockchain can improve science and accelerate medical research while bringing a new layer of trust to healthcare.This book is about science, its value to medicine, and how we can use blockchain to improve the quality and impact of both. The book looks at science and medicine from an insiderâs perspective and describes the processes, successes, shortcomings and opportunities in an accessible way for a broad audience. It weaves this a non-technical look at the emerging world of blockchain technology; what it is, where it is useful, and how it can improve science and medicine. It lays out a roadmap for this application to transform how we develop knowledge about health and medicine to improve our lives.In the first part, Blockchain isnât Tech, the authors look at blockchain/distributed ledgTable of ContentsList of Tables and Figures. Preface. Acknowledgements. About the Authors. Introduction. Part I - Blockchain isn’t Tech. Chapter 1 - Distributed Ledgers. Chapter 2 - Blockchain Basics. Chapter 3 - From Finance to Health: Way Beyond Bitcoin. Chapter 4 - Data Complexity. Chapter 5 - Blockchain is People. Part II - Science is Easy. Chapter 6 - Good Science. Chapter 7 - Evidence Based Medicine. Chapter 8 - Science Crisis. Chapter 9 - Open Science. Part III - DAO of Science. Chapter 10 - Distributing Science. Chapter 11 - Better Quality Science. Chapter 12 - Value-Based Research. Chapter 13 - Faster Medical Miracles. Chapter 14 - DAO of Science. Chapter 15 - The Roadmap. Notes. Index.

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Book SynopsisThe first edition of Exercises in Programming Style was honored as an ACM Notable Book and praised as The best programming book of the decade. This new edition retains the same presentation but has been upgraded to Python 3, and there is a new section on neural network styles.Using a simple computational task (term frequency) to illustrate different programming styles, Exercises in Programming Style helps readers understand the various ways of writing programs and designing systems. It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs.The book contains 40 different styles for writing the term frequency task. The styles are grouped into ten categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, interactivity, and neural networks. The author states the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.Table of ContentsPart 1 HistoricalPart 2 Basic StylesPart 3 Function CompositionPart 4 Objects and Object InteractionPart 5 Reflection and MetaprogrammingPart 6 AdversityPart 7 Data-CentricPart 8 ConcurrencyPart 9 InteractivityPart 10 Neural Networks

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Book SynopsisChris Barneyâs Pattern Language for Game Design builds on the revolutionary work of architect Christopher Alexander to show students, teachers, and game development professionals how to derive best practices in all aspects of game design. Using a series of practical, rigorous exercises, designers can observe and analyze the failures and successes of the games they know and love to find the deep patterns that underlie good design. From an in-depth look at Alexanderâs work, to a critique of pattern theory in various fields, to a new approach that will challenge your knowledge and put it to work, this book seeks to transform how we look at building the interactive experiences that shape us.Key Features: Background on the architectural concepts of patterns and a Pattern Language as defined in the work of Christopher Alexander, including his later work on the Fifteen Properties of Wholeness and Generative Codes. Analysis of other uses of Alexanderâs work in computer science and game design, and the limitations of those efforts. A comprehensive set of example exercises to help the reader develop their own patterns that can be used in practical day-to-day game design tasks. Exercises that are useful to designers at all levels of experience and can be completed in any order, allowing students to select exercises that match their coursework and allowing professionals to select exercises that address their real-world challenges. Discussion of common pitfalls and difficulties with the pattern derivation process. A guide for game design teachers, studio leaders, and university departments for curating and maintaining institutional Pattern Languages. An Interactive Pattern Language website where you can share patterns with developers throughout the world (patternlanguageforgamedesign.com). Comprehensive games reference for all games discussed in this book. AuthorChris Barney is an industry veteran with more than a decade of experience designing and engineering games such as Poptropica and teaching at Northeastern University. He has spoken at conferences, including GDC, DevCom, and PAX, on topics from core game design to social justice. Seeking degrees in game design before formal game design programs existed, Barney built his own undergraduate and graduate curricula out of offerings in sociology, computer science, and independent study. In pursuit of a broad understanding of games, he has worked on projects spanning interactive theater, live-action role-playing game (LARP) design, board games, and tabletop role-playing games (RPGs). An extensive collection of his essays of game design topics can be found on his development blog at perspectivesingamedesign.com.Table of ContentsSection I IntroductionChapter 1 ◾ Introduction 3Section II BackgroundChapter 2 ◾ Background on A Pattern Language by Christopher Alexander 21Chapter 3 ◾ Background on the Use of Pattern Languages in Other Fields 29Chapter 4 ◾ Background on the Use of Patterns in Game Design 35Section III An Introduction to Patterns in Game DesignChapter 5 ◾ An Introduction to Patterns in Game Design 53Chapter 6 ◾ Common Problems in Proposed Patterns 69Section IV Pattern ExercisesChapter 7 ◾ Pattern Exercises 77Chapter 8 ◾ Basic Pattern Exercise 79Chapter 9 ◾ Structural Pattern Exercises 89Chapter 10 ◾ Focused Patterns 147Chapter 11 ◾ Patterns That Break the Mold 185Section V The Fifteen PropertiesChapter 12 ◾ Taking a Step Back: What We Have Learned So Far 217Chapter 13 ◾ The “Fifteen Fundamental Properties of Wholeness” in Game Design 219Section VI Advanced Pattern-Generation ExercisesChapter 14 ◾ Advanced Pattern-Generation Exercises 241Section VII Building a LanguageChapter 15 ◾ Connecting Patterns into a Language 313Chapter 16 ◾ Organizing and Maintaining a Pattern Language 333Chapter 17 ◾ Creating New Pattern Exercises 375Chapter 18 ◾ Designing with a Pattern Language 379Chapter 19 ◾ Teaching Yourself or Students with Pattern Languages 385

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Book SynopsisThe design, construction, and upkeep of infrastructure is comprised of a multitude of dimensions spanning a highly complex paradigm of interconnected opportunities and challenges. While traditional methods fall short of adequately accounting for such complexity, artificial intelligence (AI) presents novel and out-of-the-box solutions that effectively tackle the growing demands of our infrastructure. The convergence between AI and civil engineering is an emerging frontier with tremendous potential.The book is likely to provide a boost to the state of infrastructure engineering by fostering a new look at civil engineering that capitalizes on AI as its main driver. It highlights the ongoing push to adopt and leverage AI to realize contemporary, intelligent, safe, and resilient infrastructure. The book comprises interdisciplinary and novel works from across the globe. It presents findings from innovative efforts supplemented with physical tests, numerical simulations, and case stTable of Contents1. Convolutional Neural Networks and Applications on Civil Infrastructure 2. Identifying Non-linearity in Construction Workers' Personality: Safety Behaviour Predictive Relationship Using Neural Network and Linear Regression Modelling 3. Machine Learning Framework for Predicting Failure Mode and Flexural Capacity of FRP-Reinforced Beams 4. A Novel Formulation for Estimating Compressive Strength of High Performance Concrete Using Gene Expression Programming 5. Implementation of Data-Driven Approaches for Condition Assessment of Structures and Analyzing Complex Data 6. Automatic Detection of Surface Thermal Cracks in Structural Concrete with Numerical Correlation Analysis 7. State-of-the-Art Research in the Area of Artificial Intelligence with Specific Consideration to Civil Infrastructure, Construction Engineering and Management, and Safety 8. Artificial Intelligence in Concrete Materials: A Scientometric View 9. Active Learning Kriging-Based Reliability for Assessing the Safety of Structures: Theory and Application 10. A Bayesian Estimation Technique for Multilevel Damage Classification in DBHM 11. Machine learning and IoT Data for Concrete Performance Testing and Analysis 12. Knowledge-enhanced Deep Learning for Efficient Response Estimation of Nonlinear Structures 13. Damage Detection in Reinforced Concrete Girders by Finite Element and Artificial Intelligence Synergy 14. Deep Learning in Transportation Cyber-Physical Systems 15. Artificial Intelligence in the Construction Industry: Theory and Emerging Applications for the Future of Work 16. The Use of Machine Learning in Heat Transfer Analysis for Structural Fire Engineering Applications 17. Using Artificial Intelligence to Derive Temperature Dependent Mechanical Properties of Ultra-High Performance Concrete 18. Smart Tunnel Fire Safety Management by Sensor Network and Artificial Intelligence

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Book SynopsisConservation of Time-based Media Art is the first book to take stock of the current practices and conceptual frameworks that define the emerging field of time-based media conservation, which focuses on contemporary artworks that contain video, audio, film, slides or software components.Written and compiled by a diverse group of time-based media practitioners around the world, including conservators, curators, registrars and technicians among others, this volume offers a comprehensive survey of specialized practices that have developed around the collection, preservation and display of time-based media art. Divided into 23 chapters with contributions from 36 authors and 85 additional voices, the narrative of this book provides both an overview and detailed guidance on critical topics, including the acquisition, examination, documentation and installation of time-based media art; cross-medium and medium-specific treatment approaches and methods; the registration, storaTable of ContentsPart 1: Caring for Time-based Media Art; 1. Implementing Time-based Media Art Conservation in Museum Practice - Joanna Phillips; 2. Theories of Time-based Media Art Conservation: From Ontologies to Ecologies - Renée van de Vall; 3. A Roundtable: Curatorial Perspectives on Collecting Time-based Media Art - Annet Dekker in conversation with Karen Archey, Ulanda Blair, Sarah Cook, Ana Gonçalves Magalhães, Sabine Himmelsbach, Kelani Nichole, Christiane Paul and Henna Paunu; 4. Institutional Assessments and Collection Surveys for Time-based Media Conservation - Lia Kramer, Alexandra Nichols, Mollie Anderson, Nora Kennedy, Lorena Ramírez López, and Glenn Wharton; 5. Outside the Institution: Crossing the Boundaries of Communities and Disciplines to Preserve Time-based Media - Mona Jimenez, Kristin MacDonough and Martha Singer; 6. The Role of Advocacy in Media Conservation - Jim Coddington; Part 2: Building a Workplace; 7. Building a Time-based Media Conservation Lab: A Survey and Practical Guide, from Minimum Requirements to Dream Lab - Kate Lewis; 8. Digital Storage for Artworks: Theory and Practice - Amy Brost; 9. Staffing and Training in Time-based Media Conservation - Louise Lawson; 10. A Roundtable: Implementing Cross-Departmental Workflows at SFMOMA - Martina Haidvogl in conversation with Michelle Barger, Joshua Churchill, Steve Dye, Rudolf Frieling, Mark Hellar, Jill Sterrett, Grace T. Weiss, Layna White, and Tanya Zimbardo; Part 3: Cross-medium Practices in Time-based Media Conservation; 11. Documentation as an Acquisition and Collection Tool for Time-based Media Artworks - Patricia Falcão, Ana Ribeiro, and Francesca Colussi; 12. Inventory and Database Registration of Time-based Media Art - Martina Haidvogl and Linda Leckart; 13. Digital Preservation and the Information Package - Nicole Martin; 14. Disk imaging as a back-up tool for digital objects - Eddy Colloton, Jonathan Farbowitz, and Caroline Gil Rodríquez; 15. Managing and Storing Artwork Equipment in Time-based Media Art - Duncan Harvey; 16. The Installation of Time-based Media Artworks - Tom Cullen; 17. A Roundtable: Collaborating with Media Artists to Preserve their Art - Joanna Phillips and Deena Engel in conversation with Lauren Cornell, Mark Hellar, Diego Mellado, Steven Sacks, Lena Stringari, Siebren Versteeg and Gaby Wijers; Part 4: Medium-specific Practices in Time-based Media Conservation; 18. Caring for Analog and Digital Video Art - Agathe Jarczyk and Peter Oleksik; 19. Sound in Time-based Media Art - Chris McDonald; 20. Caring for Analog and Digital Film-based Art - John Klacsmann with a contribution by Julian Antos; 21. Caring for Slide-based Artworks - Jeffrey Warda; 22. Caring for Software- and Computer-based Art - Deena Engel, Tom Ensom, Patricia Falcão , and Joanna Phillips; 23. A Word about Performance Art - Hélia Marçal.

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Book SynopsisThe book is based on the best papers of IEEE IRI 2018 and IEEE FMI 2018, Salt Lake City, July, 2018. They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought to be able to manage, integrate, and utilize large amounts of data despite hardware, software, and/or bandwidth constraints; to construct models yielding important data insights, and to create visualizations to aid in presenting and understanding the data. Furthermore, it addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically-sound and cost-effective advancement of all kinds of intelligent systems including all software and hardware aspects. The book addresses problems such as, how to optimally select the information/data sets for reuse and Table of ContentsExperimental Studies on the Impact of Data Sampling with Severely Imbalanced big data. How to Optimally Combine Univariate and Multivariate Feature Selection with Data Sampling for Classifying Noisy, High Dimensional and Class Imbalanced DNA Microarray Data. Big Data and Class Imbalance in Medicare Fraud Detection. Movie Recommendations Based on a Recurrent Neural Network Model. A Recommendation System Enhanced by Topic Modeling for Knowledge Reuse in MOOCs Ecosystems. Toward a Computer Vision Based Approach for Developing Algorithms for Soccer Playing Robots. Context-dependent Reachability Analysis for Hybrid Systems. Netflow Feature Evaluation for the Detection of Slow Read HTTP Attacks. Predictive Analysis of Server Log Data for Forecasting Events.

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Book SynopsisProgramming Media Art Using Processing: A Beginner''s Guide provides an entry-level exploration into visual design through computer programming using the open source and artist-friendly language, Processing. Used by hundreds of students, this learning system breaks lessons down into strategic steps towards fun and creative media art projects.This book provides a linear series of lessons with step-by-step examples that lead to beginning media art projects, including abstract designs, pixel landscapes, rollover animations, and simple video games. Computer programming can be overwhelming for the first-time learner, but this book makes the learning of code more digestible and fun through a full color, well-diagrammed, and deeply explained text presentation. Lessons are rhythmically broken down into digestible parts with code annotations and illustrations that help learners focus on the details one step at a time. The content is legible, flexible, and fun to work witTable of ContentsAcknowledgements and Contributor ListAuthor BioIntroduction and Best PracticesChapter 1: Designing Graphically with the Language of CodeGetting Started & Basic OverviewLesson 1.1: Pixel Grid SystemLesson 1.2: Code and Canvas WindowsLesson 1.3: More ShapesLesson 1.4: GrayscaleLesson 1.5: Syntax, Comments, and Order of CodeLesson 1.6: Line Commands (Stroke and No Stroke)Lesson 1.7: Coloring PixelsLesson 1.8: Adding Transparency ValuesLesson 1.9: The Processing Reference – Important Resource!Project: Geometric DesignChapter 2: Creating Responsive EnvironmentsLesson 2.1: Dynamic Computer ProgramsLesson 2.2: First AnimationsLesson 2.3: Animation Trails Lesson 2.4: Finding Exact CoordinatesLesson 2.5: Complex ShapesLesson 2.6: Linking Shapes for Synched MovementLesson 2.7: Adding TextLesson 2.8: Rotating ShapesProject: Interactive EnvironmentChapter 3: Automated AnimationsLesson 3.1: Counting VariablesLesson 3.2: Moving Objects in Multiple DirectionsLesson 3.3: Growing Shapes with the MouseLesson 3.4: Println() for DebuggingLesson 3.5: Constrain() for Stopping AnimationsLesson 3.6: Random() OpportunitiesLesson 3.7: Automated RotationsProject: Automated EnvironmentChapter 4: Animated CollagesLesson 4.1: Preparing and Importing ImageryLesson 4.2: Moving ImagesLesson 4.3: Fading and Coloring Images using Tint()Lesson 4.4: Resizing Images & MultiplesLesson 4.5: Constraining Mouse MovementsLesson 4.6: Void Key Pressed() and Image RotationsLesson 4.7: Create FontsLesson 4.8: Project Optimization and noSmooth()Project: Animated and Interactive CollageChapter 5: Conditional Interactions and Rollovers Lesson 5.1: Conditional Statements and Relational Operators Lesson 5.2: Conditional Statements with Custom Variables Lesson 5.3: And vs. Or Lesson 5.4: Logical Operators Defining Spaces Lesson 5.5: Variations with Mouse and Keyboard ActionsLesson 5.6: Two Variables: Alternating MovementsLesson 5.7: Color Detection Using the Get() FunctionProject: Rollover AnimationChapter 6: Events and Interactions for Simple Games: Part 1 Lesson 6.1: Turning Things on with Boolean Variables Lesson 6.2: Toggling Between Two States Using Boolean Variables Lesson 6.3: Multiple Buttons Alternating Lesson 6.4: Booleans Working with Counting Variables Lesson 6.5: Specific Keyboard Interactions Lesson 6.6: Creating a Walking CharacterLesson 6.7: BoundariesChapter 7: Events and Interactions for Simple Games: Part 2 Lesson 7.1: TimersLesson 7.2: Continuous Motion Key ControlsLesson 7.3: For Loops are EfficientLesson 7.4: Color Detection with For LoopsLesson 7.5: Game Creation from Keys, Loops, and Color DetectionLesson 7.6: Image Collisions with the Distance() FunctionLesson 7.7: Two Players, Directional Movement, and Jumping!Chapter 8: Multilevel Architectures and Arrays Lesson 8.1: Basic Levels ArchitectureLesson 8.2: States within LevelsLesson 8.3: ArraysLesson 8.4: Image ArraysLesson 8.5: Player OptionsLesson 8.6: Choice Based ProjectsConclusionFinal Project: Multilevel Interactive Experience

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Book SynopsisArtificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the iTable of Contents1. What accountants need to know. 2. Applications of AI in accounting. 3. Robotic process automation. 4. Text mining. 5. Contemporary case studies. 6. Challenges and ethical considerations of AI. 7. Future outlook.

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Book SynopsisHow did we end up here, masters of scientific insight, purveyors of ever more powerful technologies, astride the burning planet that created us, and now responsible for cleaning up the mess and determining the future direction of all of life? And what do we do about it?Technology is Dead is a book that attempts to answer both of those questions. It is a book of both challenge and hope, written for those who are able or willing to lead us out of our global predicament. It is a book for everybody: the politicians, CEOs, community leaders, everyday parents, and young people who understand that we must change our ways to ensure a sustainable future for all living things and the planet we rely on.

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Book SynopsisAn Introduction to Cyberpsychology provides a comprehensive introduction to this rapidly growing discipline. Fully updated in its second edition, the book encourages students to critically evaluate the psychology of online interactions and to develop appropriate research methodologies to complete their own work in this field.The book examines cyberpsychology and online research methodologies, social psychology in an online context, practical applications of cyberpsychology, and the psychological aspects of other technologies. This new edition has been carefully updated to include additional coverage of: Expanded content relating to major developments in the field and new content on gaming and screentime A new chapter examining the relationship between older adults and technology Cyberpsychology in focus feature boxes in each chapter that examine topics in depth Interviews with professionals working in fields relating to cyberpsychology Each chapter includes key terms and a glossary, content summaries, discussion questions, and recommended reading to guide further study.Supported by extensive online resources for students and instructors, this authoritative book is an essential core text for undergraduate modules in cyberpsychology, and an ideal primer for students of postgraduate programs in cyberpsychology.To view the additional student and instructor resources for this book, please visit https://routledgelearning.com/bpscoretextbooksTrade Review‘The editorial team and contributors’ knowledge and understanding of the broad intersections of cyberpsychology research is second-to-none, given their years of experience teaching and writing about the impact of technology on human behaviour. This is a must have book for those starting to learn about, or wanting to keep pace with, the multi-disciplinary field of cyberpsychology.’ Dr. Andrew J. Campbell, Associate Professor of Cyberpsychology, The University of Sydney, Australia‘The 2nd Edition of An Introduction to Cyberpsychology offers a comprehensive and thought-provoking critical analysis of a range of contemporary topics in this ever-evolving field. With supporting online resources, this is an essential read for interested scholars and students across a range of disciplinary areas, not least in psychology. Highly recommend.’ Neil Coulson, Professor of Health Psychology, University of Nottingham, UK‘The second edition of An Introduction to Cyberpsychology shares the most-up-to-date research on contemporary issues in cyberpsychology in accessible, easy-to-understand language. It is thorough and considers the multiple ways in which human behaviour shapes and is shaped by digital technology across all facets of life from developmental ages (youth and older age), work, education, sport, and interpersonal and romantic relationships. Chapters are written by leaders in the field and the online learning activities would enhance any cyberpsychology curriculum. I'm looking forward to using this in my own classrooms!’Dr Melanie Keep, Director of Academic Education, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney‘This book provides a comprehensive overview of cyberpsychology. It applies evidence-based literature from psychology and related disciplines to explore the impact of online technologies to a diverse range of topics including but not limited to health, education, social identity, consumer behaviour, and the workplace. In doing so it provides an invaluable resource for students, instructors, policymakers, and any other stakeholders with an interest in the increasingly important discipline of cyberpsychology. The supplementary online resources provided that can be accessed by students are engaging and will provide a deeper understanding of the issues that the book discusses.’Prof. John McAlaney, University of Bournemouth, UK‘As technology progresses, the importance of cyberpsychology as an essential part of the wider psychology curriculum becomes more apparent. This book acts as an excellent introduction to the field, providing an in-depth overview of all the subject has to offer. Through interactive discussion questions and additional reading lists, the book provides a valuable and accessible resource for students and anyone intrigued to find out more about our digital behaviours. An essential addition to the existing literature, with contributions from leading experts in the field. A great read!’ Dr Lisa Orchard, Senior Lecturer in Psychology, University of Wolverhampton, UK‘The new edition of An Introduction to Cyberpsychology by Irene Connolly, Marion Palmer, Hannah Barton, and Gráinne Kirwan demystifies the relatively new field of cyberpsychology. Moreover, it communicates the nuts and bolts of strategies from several up-to-date approaches for studying digital technologies. The companion website provides informative supplementary materials that are easy to follow. This is an important addition to the cyberpsychology literature.’ Thomas D. Parsons, PhD, Grace Center Professor for Innovation in Clinical Education, Simulation Science, & Immersive Technology, Director: Computational Neuropsychology & Simulation (CNS) Lab, Arizona State University, USA‘The second edition of An Introduction to Cyberpsychology is a valuable and much needed addition to the field. A must-read for those who are new to cyberpsychology as well as those who are looking to update their understandings. An Introduction to Cyberpsychology covers diverse topics at the forefront of cyberpsychology, which are highly applicable to life in the digital age. Importantly, An Introduction to Cyberpsychology provides readers with the building blocks to develop a nuanced and critical understanding of key issues in cyberpsychology.’Dr Catherine Talbot, Senior Lecturer in Psychology, Bournemouth University, UK‘An Introduction to Cyberpsychology does an amazing job of covering the current state of cyberpsychology and how its basic premises extend interdisciplinarily in both positive and potentially destructive ways. In addition to including many opportunities for the reader to think critically about this growing applied discipline within psychology, the editors and chapter authors have included many resources and relevant references that allow for extending the utility of the textbook outside of the very pages they appear on. As a cyberpsychological researcher and an academic teaching cyberpsychology at the graduate level, I found the focus on conducting online research particularly well-suited to my student’s needs, with several of the other chapters uniquely capturing the essence of what I want all of my first-year students to be aware of.’ Dr. Scott Debb, Associate Professor, CyberPsychology Research & Program Coordinator, Norfolk State University, USATable of ContentsPart 1: IntroductionInterview 1: Cyberpsychology in Professional PracticeItayi Viriri1. Introduction to CyberpsychologyGráinne Kirwan2. Conducting Online ResearchBrendan RooneyPart 2: Human interaction onlineInterview 2: Cyberpsychology in Professional PracticeLee Kelly3. Computer-Mediated Communication and Online MediaGráinne Kirwan4. Self and Identity in CyberspaceIrene Connolly5. The dark Side of the InternetHannah Barton and Derek Laffan6. Love and Relationships OnlineNicola Fox Hamilton7. Attention and Distraction OnlineJohn Greaney and Emma Mathias8. The Dynamics of Groups OnlineOlivia Hurley 9. Persuasion and Compliance in CyberspaceHannah Barton10. Privacy and Trust OnlineGrainne KirwanPart 3: Applied CyberpsychologyInterview 3: Cyberpsychology in Professional PracticeFardus Sultan11. Forensic CyberpsychologyGrainne Kirwan12. Cyberpsychology and PsychopathologyCliona Flood and Audrey Stenson13. Sport & Health CyberpsychologyOlivia Hurley 14. The Online WorkplaceCliona Flood and Audrey Stenson15. The Internet as an Educational SpaceMarion Palmer16. Consumer Cyberpsychology and Online marketingNicola Fox Hamilton 17. Young People and the InternetIrene Connolly 18. Older adults in the Digital AgeLiam ChallenorPart 4: Psychology and TechnologyInterview 4: Cyberpsychology in Professional PracticePhelim May19. Human-Computer InteractionAndrew Errity20. GamingDavid Hayes, Andrew Errity, Brendan Rooney, and Conall Tunney21. Psychological Applications of Virtual and Augmented/Mixed RealityGrainne Kirwan22. The Psychology of Artificial IntelligenceGrainne Kirwan

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Book SynopsisWhat is artificial intelligence (AI)? How does AI affect death matters and the digital beyond? How are death and dying handled in our digital age?AI for Dying and Death covers a broad range of literature, research and challenges around this topic. It explores ethical memorisation, digital legacies and bereavement, post death avatars and AI and the digital beyond. It also analyzes religious perspectives on AI for death and dying, and planning for death in a digital age. Table of ContentsChapter 1 What is Artificial Intelligence?Chapter 2 Death and Dying in the Digital AgeChapter 3 Ethical MemorialisationChapter 4 Digital Legacy ManagementChapter 5 Religious PerspectivesChapter 6 Digital BereavementChapter 7 Digital Afterlife, Digital Immortal Creation and Artificial IntelligenceChapter 8 Artificial Intelligence and the Digital BeyondReferences

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Book SynopsisAssisting organizations in improving their project management processes, the Project Management Maturity Model defines the industry standard for measuring project management maturity and agile and adaptive capabilities.Project Management Maturity Model, Fourth Edition provides a roadmap showing organizations how to move to higher levels of organizational behavior, improving project success and organizational performance. It''s a comprehensive tool for enhancing project management practices, covering areas critical to organizational improvement, such as the project management office, management oversight, and professional development. It also provides methods for optimizing project management processes and suggestions for deploying the model as a strategic tool in improving business outcomes. New material in each chapter also outlines good practices for implementing adaptive an agile processes. The book also includes the Project Portfolio Management Maturity ModeTable of Contents1. Describing Project Management Maturity. 2. Definitions of Maturity Levels. 3. Project Integration Management. 4. Project Scope Management. 5. Schedule Management. 6. Cost Management. 7. Quality Management. 8. Resource Management. 9. Communications Management. 10. Risk Management. 11. Procurement and Vendor Management. 12. Project Stakeholder Management. 13. Now What? Using Your Maturity Assessment to Achieve Business Goals. Epilogue. Appendix A: Self-Assessment Survey. Appendix B: PPM Maturity Model. Appendix C: A Glossary of Terms for Adaptive/Agile Project Management. References. Index.

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Book SynopsisVirtual Humans provides a much-needed definition of what constitutes a âvirtual humanâ and places virtual humans within the wider context of Artificial Intelligence development. It explores the technical approaches to creating a virtual human, as well as emergent issues such as embodiment, identity, agency and digital immortality, and the resulting ethical challenges. The book presents an overview of current research and practice in this area, and outlines the major challenges faced by todayâs developers and researchers. The book examines the possibility for using virtual humans in a variety of roles, from personal assistants to teaching, coaching and knowledge management, and the book situates these discussions around familiar applications (e.g. Siri, Cortana, Alexa) and the portrayal of virtual humans within Science Fiction.Features Presents a comprehensive overview of this rapidly developing field Trade Review"This book presents an overview of the present state of play with virtual humans. Appearance, attributes, communication and intelligence are all investigated, and the architectures involved are covered in detail. If you have little knowledge of what a virtual human is, but want to find out, then this is the book for you. For researchers in the virtual human field this is a definite must." -Professor Kevin Warwick, Coventry University "David Burden and Maggi Savin-Baden’s Virtual Humans offers a thorough, research-based treatment of how digital entities with human-like features and capabilities have left the domain of science fiction and are rapidly becoming a major aspect of human culture. In their clearly-written and well-organized work, they describe the current forms and abilities of virtual humans (including smart speakers and virtual assistant systems like Siri, Alexa, and Cortana and various types of Internet-based chatbots); examine how the creation of virtual bodies, senses, and minds can be combined to create virtual humans; and consider potential developments in the nature and functionality of virtual agents across a range of timeframes from the end of the next decade to the end of the century. Significantly, the authors recognize and discuss the great ethical, moral and social implications of these technological developments which makes their work relevant and important for the social sciences and humanities as well as the domains of computing and information sciences. I certainly intend to use Virtual Humans as an assigned reading in the interdisciplinary courses I teach on the personal and social impact of leading-edge digital technologies." -Richard Gilbert, Professor of Psychology and Director of the Psychology and New Technology Research Lab, Loyola Marymount University, Los Angeles, California "Intelligent, pragmatic and insightful, Virtual Humans is an essential guide for those who want to understand the complex landscape of today’s technology when thinking about designing and building a virtual human. Helpfully, it clearly deploys a wealth of supporting analysis, case studies, research, ethical questions, and moral dilemmas and adds a refreshing dose of healthy common sense along the way." -Nicola Strong, Strong Enterprises Table of ContentsIntroduction Part I The Landscape Chapter 1 What are Virtual Humans? Chapter 2 Virtual Humans and Artificial Intelligence Part II Technology Chapter 3 Body and Senses Chapter 4 Mind Chapter 5 Communication Chapter 6 Architecture Chapter 7 Embodiment Chapter 8 Assembling and Assemblages Part III Identity Chapter 9 Digital Ethics Chapter 10 Identity and Agency Chapter 11 Virtual Humans for Education Chapter 12 Digital Immortality Chapter 13 Futures and Possibilities Glossary

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Book SynopsisReflecting the immense progress in the development and use of software metrics in the past decades, this third edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. This edition contains new material relevant to object-oriented design, design patterns, model-driven development, and agile development procTrade Review"The wait for a new edition of this book is over. Long considered the go-to text for its thorough coverage of software measurement and experimentation, the new edition succeeds splendidly in bringing the field up to date while including new and important topics. … updated with the latest results from recent advances in software measurement research and practice. … The authors do an outstanding job of balancing formal analysis topics with examples that ground the reader in practical application. … Both researchers and practitioners alike will gain a valuable understanding of why measurement is critical for quality improvements in software development processes and software products. … With this updated edition, this book solidifies its standing as the most complete reference text for software measurement."—Computing Review, April 2015"I have been using this book as my primary reference on software metrics for over 20 years now. It still remains the best book by far on the science and practice of software metrics. This latest edition has some important updates, especially with the inclusion of material on Bayesian networks for prediction and risk assessment."—Paul Krause, University of Surrey, Guildford, UK"Great introduction to software metrics, measurement, and experimentation. This will be a must-read for my software engineering students."—Lukasz Radlinski, PhD, West Pomeranian University of Technology, Szczecin, Poland"I have loved this book from the first edition and with each new edition it just keeps getting better and better. I use this book constantly in my software engineering research and always recommend it to students. It is so much more than a software metrics book; to me it is an essential companion to rigorous empirical software engineering."—Dr. Tracy Hall, Department of Computer Science, Brunel University, Uxbridge, UK"This new edition of Software Metrics succeeds admirably in bringing the field of software measurement up to date and in delivering a wider range of topics to its readers as compared to its previous edition. I have both reviewed and used the book in my software measurement courses and find it to be one of the most advanced and well structured on the market today, tailored for training software engineers in both theoretical and practical aspects of software measurement. I look forward to continuing the use of the book for teaching purposes and am very comfortable offering my recommendation for this book as a primary textbook for graduate or undergraduate courses on software measurement. Thank you again for providing such a quality book to our software engineering education programs."—Olga Ormandjieva, Associate Professor, Department of Computer Science and Software Engineering, Concordia University, Canada"This book lucidly and diligently covers the nuts and bolts of software measurement. It is an excellent reference on software metric fundamentals, suitable as a comprehensive textbook for software engineering students and as a definitive manual for industry practitioners."—Mohammad Alshayeb, Associate Professor of Software Engineering, King Fahd University of Petroleum and MineralsTable of ContentsFundamentals of Measurement and Experimentation: Measurement: What Is It and Why Do It? The Basics of Measurement. A Goal-Based Framework for Software Measurement. Empirical Investigation. Software Metrics Data Collection. Analyzing Software Measurement Data. Metrics for Decision Support: The Need for Causal Models. Software Engineering Measurement: Measuring Internal Product Attributes: Size. Measuring Internal Product Attributes: Structure. Measuring External Product Attributes. Software Reliability: Measurement and Prediction. Appendix. Bibliography. Index.

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Book SynopsisThe ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning for a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or to any new personnel working in scientific computing or data analysis.Key Features: Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and Verilog Provides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web cloud computing Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamics A video of the author discussing the book can be accessed here: https://www.youtube.com/watch?v=KYn8aDKXlcs

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Book SynopsisThis handbook provides a hands-on experience based on the underlying topics, and assists students and faculty members in developing their algorithmic thought process and programs for given computational problems. It can also be used by professionals who possess the necessary theoretical and computational thinking background but are presently making their transition to Python.Key Features: Discusses concepts such as basic programming principles, OOP principles, database programming, GUI programming, application development, data analytics and visualization, statistical analysis, virtual reality, data structures and algorithms, machine learning, and deep learning Provides the code and the output for all the concepts discussed Includes a case study at the end of each chapter This handbook will benefit students of computer science, information systems, and information technology, or anyone who is involved in computer programming (entry-to-intermediate level), data analytics, HCI-GUI, and related disciplines.

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Book SynopsisExplanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model''s performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.Trade Review"The structure is well-conceived, with chapters consisting in five sections: intuition, method, example, pros and cons, and code snippets. I sense a teacher’s long experience behind these choices.The chapters contain good mathematical detail on the techniques discussed, but the theory is well balanced with examples and code.The visualizations are great. Often, the gist of a particular technique, and it’s practical, interpretive value, can be gleaned from the visualizations threading through the chapter, along with captions. The authors did a really nice job with this.The rationale for the book is well-described.The discussion of techniques seems both comprehensive (given my sense of the field) and helpfully specific, both at the instance and the dataset levels."-Jeff Webb, University of Utah"The authors are doing a very good job in addressing the potential readers, by providing a clean presentation and practical guidance on diagnostic graphical tools…Having an ‘intuition section’ at the beginning of each chapter is very useful."-Riccardo De Bin, University of Oslo"The book provides a unified presentation of model exploration, visualization, comparison and diagnostics of different machine learning algorithms…This book would be found useful by both students as well as practitioners who analyze their own data. Books including real data examples in R and in Python are needed in this area. (It) will serve as a reference, especially for analyses done with dalex or archivist R package (and )can serve as a textbook of data science courses in many fields including computer science, social sciences, economics and other."-Patricia Martinkova, Institute of Computer Science of the Czech Academy of Sciences"There are books that focus on prediction models, for example the element of statistical learning and an introduction to statistical learning but these are not focused on the evaluation of predictive models which is the main focus on the proposed book and its main advantage. As predictive models become very popular in the last years, such a book that focus on the evaluation of the models and model diagnostics can be very popular."-Ziv Shkedy, Data Science Institute, Hasselt University, Belgium'The book is clearly and consistently structured and well–written. The graphics are explained conceptually and mathematically. There are chapter sections on the pros and cons of what is proposed, where the authors are generally properly cautious and recommend a mixture of approaches.'- Antony Unwin, International Statistical Review, 2021 Volume 89, Issue 3"The structure is well-conceived, with chapters consisting in five sections: intuition, method, example, pros and cons, and code snippets. I sense a teacher’s long experience behind these choices. The chapters contain good mathematical detail on the techniques discussed, but the theory is well balanced with examples and code. The visualizations are great. Often, the gist of a particular technique, and it’s practical, interpretive value, can be gleaned from the visualizations threading through the chapter, along with captions. The authors did a really nice job with this. The rationale for the book is well-described. The discussion of techniques seems both comprehensive (given my sense of the field) and helpfully specific, both at the instance and the dataset levels." -Jeff Webb, University of Utah"The authors are doing a very good job in addressing the potential readers, by providing a clean presentation and practical guidance on diagnostic graphical tools…Having an ‘intuition section’ at the beginning of each chapter is very useful." -Riccardo De Bin, University of Oslo"The book provides a unified presentation of model exploration, visualization, comparison and diagnostics of different machine learning algorithms…This book would be found useful by both students as well as practitioners who analyze their own data. Books including real data examples in R and in Python are needed in this area. (It) will serve as a reference, especially for analyses done with dalex or archivist R package (and )can serve as a textbook of data science courses in many fields including computer science, social sciences, economics and other." -Patricia Martinkova, Institute of Computer Science of the Czech Academy of Sciences"There are books that focus on prediction models, for example the element of statistical learning and an introduction to statistical learning but these are not focused on the evaluation of predictive models which is the main focus on the proposed book and its main advantage. As predictive models become very popular in the last years, such a book that focus on the evaluation of the models and model diagnostics can be very popular." -Ziv Shkedy, Data Science Institute, Hasselt University, Belgium"We need to explore the models and learn about their behaviour. This book presents, explains, and summarises the techniques for doing so. Moreover, it provides code in R and Python for doing so. The methods have many similarities with those of sensitivity analysis developed within the Sensitivity Analysis of Model Output (SAMO) community. ... [M]any doctoral students, professional statisticians and researchers should ensure that they have access to it and know how to use its methods when dealing with highly complex functions in their data and model analysis." -Simon French, in the Journal of the Royal Statistics Society, Series A, June 2022"The book presents a valuable collection of methods for models’ exploration and diagnostics for various machine learning algorithms. It can be useful in the data and computer science courses for students and instructors, as well as for researchers and practitioners who need to analyze and interpret their statistical and machine learning models both of glass-box and blackbox kind. The book also serves as a great primary for applications of the R and Python software and their packages/libraries, so it is valuable in solving various problems of statistical prediction in various fields."-Stan Lipovetsky, in Technometrics, July 2022Table of ContentsI. Introduction 1. Introduction. 2. Model Development. 3. Do-it-yourself. 4. Datasets and models. II. Instance Level. 5. Introduction to Instance-level Exploration. 6. Break-down Plots for Additive Attributions. 7. Break-down Plots for Interactions. 8. Shapley Additive Explanations (SHAP) for Average Attributions. 9. Local Interpretable Model-agnostic Explanations (LIME). 10. Ceteris-paribus Profiles. 11. Ceteris-paribus Oscillations. 12. Local-diagnostics Plots. 13. Summary of Instance-level Exploration. III. Dataset Level. 14. Introduction to Dataset-level Exploration. 15. Model-performance Measures. 16. Variable-importance Measures. 17. Partial-dependence Profiles. 18. Local-dependence and Accumulated-dependence Profiles. 19. Residual Diagnostics Plots. 20. Summary of Model-level Exploration. IV. Use-cases. 21. FIFA 19.

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Book SynopsisThe Internetâs importance for freedom of expression and other rights comes in part from the ability it bestows on users to create and share information, rather than just receive it. Within the context of existing freedom of expression guarantees, this book critically evaluates the goal of bridging the 'digital divide' â the gap between those who have access to the Internet and those who do not. Central to this analysis is the examination of two questions: first, is there a right to access the Internet, and if so, what does that right look like and how far does it extend? Second, if there is a right to access the Internet, is there a legal obligation on States to overcome the digital divide?Through examination of this debateâs history, analysis of case law in the European Court of Human Rights and Inter-American Court of Human Rights, and a case study of one digital inclusion programme in Jalisco, Mexico, this book concludes that there is indeed currently a legal right to IntTable of Contents1. General Introduction 2. Historical Context of International Debates on a Right to Access to Information Technology and Digital Divide Guarantees3. Negative Obligations 4. Positive Obligations to Facilitate Access to the Internet5. Looking Outside Freedom of Expression to Strengthen Digital Inclusion Guarantees6. Case Study in Digital Inclusion7. Conclusions

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Book SynopsisThe emerging field of Data Science has had a large impact on science and society. This book explores how one distinguishing feature of Data Science its focus on data collected from social and environmental contexts within which learners often find themselves deeply embedded suggests serious implications for learning and education.Drawing from theories of learning and identity development in the learning sciences, this volume investigates the impacts of these complex relationships on how learners think about, use, and share data, including their understandings of data in light of history, race, geography, and politics. More than just using real world examples' to motivate students to work with data, this book demonstrates how learners' relationships to data shape how they approach those data with agency, as part of their social and cultural lives. Together, the contributions offer a vision of how the learning sciences can contribute to a more expansive, socially awareTable of Contents1. Introduction: Situating Data Science—Exploring How Relationships to Data Shape Learning 2. At Home with Data: Family Engagements with Data Involved in Type 1 Diabetes Management 3. Examining Spontaneous Perspective Taking and Fluid Self-to-Data Relationships in Informal Open-Ended Data Exploration 4. Learning at the Intersection of Self and Society: The Family Geobiography as a Context for Data Science Education 5. Authoring Data Stories in a Media Makerspace: Adolescents Developing Critical Data Literacies 6. From Data Collectors to Data Producers: Shifting Students’ Relationship to Data, Lisa Hardy 7. Scripts and Counterscripts in Community-Based Data Science: Participatory Digital Mapping and the Pursuit of a Third Space 8. Learning to Reason with Data: How Did We Get Here and What Do We Know? 9. Educating Data Scientists and Data Literate Citizens for a New Generation of Data

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Book SynopsisTransformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers.Key Features: A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in GoogTable of ContentsList of Figures List of Tables Author Bios Foreword Preface Contributors Deep Learning and Transformers: An Introduction 1.1 DEEP LEARNING: A HISTORIC PERSPECTIVE1.2 TRANSFORMERS AND TAXONOMY 1.2.1 Modified Transformer Architecture 1.2.1.1 Transformer block changes 1.2.1.2 Transformer sublayer changes 1.2.2 Pretraining Methods and Applications 1.3 RESOURCES 1.3.1 Libraries and Implementations 1.3.2 Books 1.3.3 Courses, Tutorials, and Lectures 1.3.4 Case Studies and Details Transformers: Basics and Introduction 2.1 ENCODER-DECODER ARCHITECTURE 2.2 SEQUENCE TO SEQUENCE 2.2.1 Encoder 2.2.2 Decoder 2.2.3 Training 2.2.4 Issues with RNN-based Encoder Decoder 2.3 ATTENTION MECHANISM 2.3.1 Background 2.3.2 Types of Score-Based Attention 2.3.2.1 Dot Product (multiplicative) 2.3.2.2 Scaled Dot Product or multiplicative 2.3.2.3 Linear, MLP, or additive 2.3.3 Attention-based Sequence to Sequence 2.4 TRANSFORMER 2.4.1 Source and Target Representation 2.4.1.1 Word Embedding 2.4.1.2 Positional Encoding 2.4.2 Attention Layers 2.4.2.1 Self-Attention 2.4.2.2 Multi-Head Attention 2.4.2.3 Masked Multi-Head Attention 2.4.2.4 Encoder-Decoder Multi-Head Attention 2.4.3 Residuals and Layer Normalization 2.4.4 Position-wise Feed-Forward Networks 2.4.5 Encoder 2.4.6 Decoder 2.5 CASE STUDY: MACHINE TRANSLATION 2.5.1 Goal 2.5.2 Data, Tools and Libraries 2.5.3 Experiments, Results and Analysis 2.5.3.1 Exploratory Data Analysis 2.5.3.2 Attention 2.5.3.3 Transformer2.5.3.4 Results and Analysis 2.5.3.5 Explainability Bidirectional Encoder Representations from Transformers (BERT) 3.1 BERT 3.1.1 Architecture 3.1.2 Pre-training 3.1.3 Fine-tuning 3.2 BERT VARIANTS 3.2.1 RoBERTa 3.3 APPLICATIONS 3.3.1 TaBERT 3.3.2 BERTopic 3.4 BERT INSIGHTS 3.4.1 BERT Sentence Representation 3.4.2 BERTology 3.5 CASE STUDY: TOPIC MODELING WITH TRANSFORMERS 3.5.1 Goal 3.5.2 Data, Tools, and Libraries 3.5.2.1 Data 3.5.2.2 Compute embeddings 3.5.3 Experiments, Results, and Analysis 3.5.3.1 Building Topics 3.5.3.2 Topic size distribution 3.5.3.3 Visualization of topics 3.5.3.4 Content of topics 3.6 CASE STUDY: FINE-TUNING BERT 3.6.1 Goal 3.6.2 Data, Tools and Libraries 3.6.3 Experiments, Results and Analysis Multilingual Transformer Architectures 4.1 MULTILINGUAL TRANSFORMER ARCHITECTURES 4.1.1 Basic Multilingual Transformer 4.1.2 Single-Encoder Multilingual NLU 4.1.2.1 mBERT 4.1.2.2 XLM 4.1.2.3 XLM-RoBERTa 4.1.2.4 ALM 4.1.2.5 Unicoder 4.1.2.6 INFOXL4.1.2.7 AMBER 4.1.2.8 ERNIE-M 4.1.2.9 HITCL 4.1.3 Dual-Encoder Multilingual NLU 4.1.3.1 LaBSE 4.1.3.2 mUSE 4.1.4 Multilingual NLG 4.2 MULTILINGUAL DATA 4.2.1 Pre-training Data 4.2.2 Multilingual Benchmarks 4.2.2.1 Classification 4.2.2.2 Structure Prediction 4.2.2.3 Question Answering 4.2.2.4 Semantic Retrieval 4.3 MULTILINGUAL TRANSFER LEARNING INSIGHTS 4.3.1 Zero-shot Cross-lingual Learning 4.3.1.1 Data Factors 4.3.1.2 Model Architecture Factors 4.3.1.3 Model Tasks Factors 4.3.2 Language-agnostic Cross-lingual Representations4.4 CASE STUDY 4.4.1 Goal 4.4.2 Data, Tools, and Libraries 4.4.3 Experiments, Results, and Analysis 4.4.3.1 Data Preprocessing 4.4.3.2 Experiments Transformer Modifications5.1 TRANSFORMER BLOCK MODIFICATIONS 5.1.1 Lightweight Transformers 5.1.1.1 Funnel-Transformer 5.1.1.2 DeLighT 5.1.2 Connections between Transformer Blocks 5.1.2.1 RealFormer 5.1.3 Adaptive Computation Time 5.1.3.1 Universal Transformers (UT) 5.1.4 Recurrence Relations between Transformer Blocks 5.1.4.1 Transformer-XL 5.1.5 Hierarchical Transformers 5.2 TRANSFORMERS WITH MODIFIED MULTI-HEAD SELF-ATTENTION5.2.1 Structure of Multi-head Self-Attention 5.2.1.1 Multi-head self-attention 5.2.1.2 Space and time complexity 5.2.2 Reducing Complexity of Self-attention 5.2.2.1 Longformer 5.2.2.2 Reformer 5.2.2.3 Performer 5.2.2.4 Big Bird 5.2.3 Improving Multi-head-attention 5.2.3.1 Talking-Heads Attention 5.2.4 Biasing Attention with Priors 5.2.5 Prototype Queries5.2.5.1 Clustered Attention 5.2.6 Compressed Key-Value Memory 5.2.6.1 Luna: Linear Unified Nested Attention 5.2.7 Low-rank Approximations5.2.7.1 Linformer 5.3 MODIFICATIONS FOR TRAINING TASK EFFICIENCY 5.3.1 ELECTRA5.3.1.1 Replaced token detection 5.3.2 T5 5.4 TRANSFORMER SUBMODULE CHANGES 5.4.1 Switch Transformer 5.5 CASE STUDY: SENTIMENT ANALYSIS5.5.1 Goal 5.5.2 Data, Tools, and Libraries 5.5.3 Experiments, Results, and Analysis 5.5.3.1 Visualizing attention head weights 5.5.3.2 Analysis Pretrained and Application-Specific Transformers 6.1 TEXT PROCESSING 6.1.1 Domain-Specific Transformers 6.1.1.1 BioBERT 6.1.1.2 SciBERT 6.1.1.3 FinBERT 6.1.2 Text-to-text Transformers 6.1.2.1 ByT5 6.1.3 Text generation 6.1.3.1 GPT: Generative Pre-training 6.1.3.2 GPT-2 6.1.3.3 GPT-3 6.2 COMPUTER VISION 6.2.1 Vision Transformer 6.3 AUTOMATIC SPEECH RECOGNITION 6.3.1 Wav2vec 2.0 6.3.2 Speech2Text2 6.3.3 HuBERT: Hidden Units BERT 6.4 MULTIMODAL AND MULTITASKING TRANSFORMER 6.4.1 Vision-and-Language BERT (VilBERT) 6.4.2 Unified Transformer (UniT) 6.5 VIDEO PROCESSING WITH TIMESFORMER 6.5.1 Patch embeddings 6.5.2 Self-attention 6.5.2.1 Spatiotemporal self-attention 6.5.2.2 Spatiotemporal attention blocks 6.6 GRAPH TRANSFORMERS 6.6.1 Positional encodings in a graph 6.6.1.1 Laplacian positional encodings 6.6.2 Graph transformer input 6.6.2.1 Graphs without edge attributes 6.6.2.2 Graphs with edge attributes 6.7 REINFORCEMENT LEARNING 6.7.1 Decision Transformer 6.8 CASE STUDY: AUTOMATIC SPEECH RECOGNITION 6.8.1 Goal 6.8.2 Data, Tools, and Libraries 6.8.3 Experiments, Results, and Analysis 6.8.3.1 Preprocessing speech data 6.8.3.2 Evaluation Interpretability and Explainability Techniques for Transformers7.1 TRAITS OF EXPLAINABLE SYSTEMS 7.2 RELATED AREAS THAT IMPACT EXPLAINABILITY 7.3 EXPLAINABLE METHODS TAXONOMY 7.3.1 Visualization Methods 7.3.1.1 Backpropagation-based 7.3.1.2 Perturbation-based 7.3.2 Model Distillation 7.3.2.1 Local Approximation 7.3.2.2 Model Translation 7.3.3 Intrinsic Methods 7.3.3.1 Probing Mechanism 7.3.3.2 Joint Training 7.4 ATTENTION AND EXPLANATION 7.4.1 Attention is not Explanation 7.4.1.1 Attention Weights and Feature Importance 7.4.1.2 Counterfactual Experiments 7.4.2 Attention is not not Explanation 7.4.2.1 Is attention necessary for all tasks? 7.4.2.2 Searching for Adversarial Models 7.4.2.3 Attention Probing 7.5 QUANTIFYING ATTENTION FLOW 7.5.1 Information flow as DAG 7.5.2 Attention Rollout 7.5.3 Attention Flow 7.6 CASE STUDY: TEXT CLASSIFICATION WITH EXPLAINABILITY 7.6.1 Goal 7.6.2 Data, Tools, and Libraries 7.6.3 Experiments, Results and Analysis 7.6.3.1 Exploratory Data Analysis 7.6.3.2 Experiments 7.6.3.3 Error Analysis and Explainability Bibliography Alphabetical Index

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Book SynopsisThis third edition of Paul Murrellâs classic book on using R for graphics represents a major update, with a complete overhaul in focus and scope. It focuses primarily on the two core graphics packages in R - graphics and grid - and has a new section on integrating graphics. This section includes three new chapters: importing external images in to R; integrating the graphics and grid systems; and advanced SVG graphics.The emphasis in this third edition is on having the ability to produce detailed and customised graphics in a wide variety of formats, on being able to share and reuse those graphics, and on being able to integrate graphics from multiple systems.This book is aimed at all levels of R users. For people who are new to R, this book provides an overview of the graphics facilities, which is useful for understanding what to expect from R's graphics functions and how to modify or add to the output they produce. For intermediate-level R users, this booTrade Review"...In transit from the first to the third edition, in addition to including new material, Dr. Murrell has introduced key changes and some rearrangements that have made the whole book more understandable, especially the concepts related to viewports and coordinate systems...With an emphasis on producing graphics from code (which promotes automation, sharing and reuse), R Graphics focuses on (i) offering tools and tricks for drawing detailed and customized graphics in a variety of formats and (ii) explaining how to integrate graphics from multiple systems. This distinguishes this book from other books centered on producing plots in R...After reading the book, the R practitioner will understand how to integrate the two distinct graphics systems of R (the base graphics system and the grid graphics system) and how to customize plots, including lattice and ggplot2 graphics. This book also explains how to import images from external files into R and how to integrate them as part of R graphics output. And, furthermore, it shows how to enrich plots created by R with graphical effects and features not supported by the core R graphics system...For R beginners, this book presents an outline of the base graphics facilities and shows how to modify or add to the output they produce. For slightly more skilled R users, the book provides a comprehensive introduction to the grid high-level plotting functions available in the lattice package and in the (probably now more popular) ggplot2 package. For intermediate level R users, the book teaches how to perform sophisticated customizations of R graphical outputs. And, for advanced users and R developers, R Graphics shows how to develop coherent, reusable, and extensible graphics functions...In short, this is a valuable book that the full range of R users will find of interest."- Jose M. Pavía, Journal of Statistical Software, February 2020Table of Contents1. An Introduction to R Graphics 2. Simple Usage of Base Graphics 3. Customizing Base Graphics 4. Trellis Graphics: The lattice Package 5. The Grammar of Graphics: The ggplot2 Package 6. The grid Graphics Model 7. The grid Graphics Object Model 8. Developing New Graphical Functions and Objects 9. Graphics Formats 10. Graphical Parameters 11. Importing Graphics 12. Combining Graphics Systems 13.Advanced Graphics

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Book SynopsisThis book is based on a successful curriculum designed to elevate technical artists with no programming experience up to essential programming competency as quickly as possible. Instead of abstract, theoretical problems, the curriculum employs familiar applications encountered in real production environments to demonstrate each lesson.Written with artists in mind, this book introduces novice programmers to the advantageous world of Python programming with relevant and familiar examples. Any digital artists (not just technical artists) will find this book helpful in assisting with day-to-day production activities.Concentrating upon subjects relevant to the creation of computer graphic assets, this book introduces Python basics, functions, data types, object-oriented programming, exception handling, file processing, graphical user interface creation, PEP 8 standards, and regular expressions. Programming within the SideFX Houdini 3D animation software provides a familiar environment for artists to create and experiment with the covered Python topics.

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