Computer science Books

Book SynopsisThe past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.Table of Contents Preface 1. Introduction 2. Resilient Distributed Datasets 3. Models Built over RDDs 4. Discretized Streams 5. Generality of RDDs 6. Conclusion References Author's Biography

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Book SynopsisThe past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too.This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing.We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective.This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.Table of Contents Preface 1. Introduction 2. Resilient Distributed Datasets 3. Models Built over RDDs 4. Discretized Streams 5. Generality of RDDs 6. Conclusion References Author's Biography

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.Table of Contents Introduction Theory and Neuroscience Foundations Theoretical Foundations of Multimodal Interfaces and Systems The Impact of Multimodal-Multisensory Learning on Human Performance and Brain Activation Patterns Approaches to Design and User Modeling Multisensory Haptic Interactions: Understanding the Sense and Designing for It A Background Perspective on Touch as a Multimodal Understanding and Supporting Modality Choices Using Cognitive Models to Understand Multimodal Processes: The Case for Speech and Gesture Production Multimodal Feedback in HCI: Haptics, Non-Speech Audio, and Their Applications Multimodal Technologies for Seniors: Challenges and Opportunities Common Modality Combinations Gaze Informed Multimodal Interaction Multimodal Speech and Pen Interfaces Multimodal Gesture Recognition Audio and Visual Modality Combination in Speech Processing Applications Multidisciplinary Challenge Topic: Perspectives on Learning with Multimodal Technology Contributors’ Brief Biographies: Editors, Authors and Challenge Discussants Index

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces— user input involving new media (speech, multi-touch, gestures, writing) embedded in multimodal-multisensor interfaces. These interfaces support smart phones, wearables, in-vehicle and robotic applications, and many other areas that are now highly competitive commercially. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This first volume of the handbook presents relevant theory and neuroscience foundations for guiding the development of high-performance systems. Additional chapters discuss approaches to user modeling and interface designs that support user choice, that synergistically combine modalities with sensors, and that blend multimodal input and output. This volume also highlights an in-depth look at the most common multimodal-multisensor combinations—for example, touch and pen input, haptic and non-speech audio output, and speech-centric systems that co-process either gestures, pen input, gaze, or visible lip movements. A common theme throughout these chapters is supporting mobility and individual differences among users. These handbook chapters provide walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces should be designed in the future to most effectively advance human performance.Table of Contents Introduction Theory and Neuroscience Foundations Theoretical Foundations of Multimodal Interfaces and Systems The Impact of Multimodal-Multisensory Learning on Human Performance and Brain Activation Patterns Approaches to Design and User Modeling Multisensory Haptic Interactions: Understanding the Sense and Designing for It A Background Perspective on Touch as a Multimodal Understanding and Supporting Modality Choices Using Cognitive Models to Understand Multimodal Processes: The Case for Speech and Gesture Production Multimodal Feedback in HCI: Haptics, Non-Speech Audio, and Their Applications Multimodal Technologies for Seniors: Challenges and Opportunities Common Modality Combinations Gaze Informed Multimodal Interaction Multimodal Speech and Pen Interfaces Multimodal Gesture Recognition Audio and Visual Modality Combination in Speech Processing Applications Multidisciplinary Challenge Topic: Perspectives on Learning with Multimodal Technology Contributors’ Brief Biographies: Editors, Authors and Challenge Discussants Index

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.Table of Contents 1. Multimodal Machine Learning 2. Classifying Multimodal Data 3. Learning for Multimodal and Context-sensitive Interfaces 4. Deep Learning for Multisensorial and Multimodal Interaction 5. Multimodal User State and Trait Recognition 6. Multimodal-Multisensor Affect Detection 7. Multimodal Analysis of Social Signals 8. Real-time Sensing of Affect and Social Signals in a Multimodal Framwork 9. How do Users Perceive Multimodal Expressions of Affects? 10. Multimodal Behavior and Physiological Signals as Indicators of Cognitive Load 11. Multimodal Learning Analytics 12. Multimodal Assessment of Depression and Related Disorders Based on Behavioral Signals 13. Multimodal Deception Detection 14. Perspectives on Strategic Fusion 15. Perspectives on Predictive Power of Multimodal Deep Learning

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.Table of Contents 1. Multimodal Machine Learning 2. Classifying Multimodal Data 3. Learning for Multimodal and Context-sensitive Interfaces 4. Deep Learning for Multisensorial and Multimodal Interaction 5. Multimodal User State and Trait Recognition 6. Multimodal-Multisensor Affect Detection 7. Multimodal Analysis of Social Signals 8. Real-time Sensing of Affect and Social Signals in a Multimodal Framwork 9. How do Users Perceive Multimodal Expressions of Affects? 10. Multimodal Behavior and Physiological Signals as Indicators of Cognitive Load 11. Multimodal Learning Analytics 12. Multimodal Assessment of Depression and Related Disorders Based on Behavioral Signals 13. Multimodal Deception Detection 14. Perspectives on Strategic Fusion 15. Perspectives on Predictive Power of Multimodal Deep Learning

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces-user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces.This three-volume handbook is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas.This third volume focuses on state-of-the-art multimodal language and dialogue processing, including semantic integration of modalities. The development of increasingly expressive embodied agents and robots has become an active test bed for coordinating multimodal dialogue input and output, including processing of language and nonverbal communication. In addition, major application areas are featured for commercializing multimodal-multisensor systems, including automotive, robotic, manufacturing, machine translation, banking, communications, and others. These systems rely heavily on software tools, data resources, and international standards to facilitate their development. For insights into the future, emerging multimodal-multisensor technology trends are highlighted in medicine, robotics, interaction with smart spaces, and similar areas. Finally, this volume discusses the societal impact of more widespread adoption of these systems, such as privacy risks and how to mitigate them. The handbook chapters provide a number of walk-through examples of system design and processing, information on practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces need to be equipped to most effectively advance human performance during the next decade.Table of Contents Preface Figure Credits Introduction: Toward the Design, Construction, and Deployment of Multimodal-Multisensor Interfaces MULTIMODAL LANGUAGE AND DIALOGUE PROCESSING Multimodal Integration for Interactive Conversational Systems Multimodal Conversational Interaction with Robots Situated Interaction Software Platforms and Toolkits for Building Multimodal Systems and Applications Challenge Discussion: Advancing Multimodal Dialogue Nonverbal Behavior in Multimodal Performances MULTIMODAL BEHAVIOR Ergonomics for the Design of Multimodal Interfaces Early Integration for Movement Modeling in Latent Spaces Standardized Representations and Markup Languages for Multimodal Interaction Multimodal Databases EMERGING TRENDS AND APPLICATIONS Medical and Health Systems Automotive Multimodal Human-Machine Interface Embedded Multimodal Interfaces in Robotics: Applications, Future Trends, and Societal Implications Multimodal Dialogue Processing for Machine Translation Commercialization of Multimodal Systems Privacy Concerns of Multimodal Sensor Systems Index Biographies Volume 3 Glossary

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Book SynopsisThe Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces-user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces.This three-volume handbook is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas.This third volume focuses on state-of-the-art multimodal language and dialogue processing, including semantic integration of modalities. The development of increasingly expressive embodied agents and robots has become an active test bed for coordinating multimodal dialogue input and output, including processing of language and nonverbal communication. In addition, major application areas are featured for commercializing multimodal-multisensor systems, including automotive, robotic, manufacturing, machine translation, banking, communications, and others. These systems rely heavily on software tools, data resources, and international standards to facilitate their development. For insights into the future, emerging multimodal-multisensor technology trends are highlighted in medicine, robotics, interaction with smart spaces, and similar areas. Finally, this volume discusses the societal impact of more widespread adoption of these systems, such as privacy risks and how to mitigate them. The handbook chapters provide a number of walk-through examples of system design and processing, information on practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this emerging field. In the final section of this volume, experts exchange views on a timely and controversial challenge topic, and how they believe multimodal-multisensor interfaces need to be equipped to most effectively advance human performance during the next decade.Table of Contents Preface Figure Credits Introduction: Toward the Design, Construction, and Deployment of Multimodal-Multisensor Interfaces MULTIMODAL LANGUAGE AND DIALOGUE PROCESSING Multimodal Integration for Interactive Conversational Systems Multimodal Conversational Interaction with Robots Situated Interaction Software Platforms and Toolkits for Building Multimodal Systems and Applications Challenge Discussion: Advancing Multimodal Dialogue Nonverbal Behavior in Multimodal Performances MULTIMODAL BEHAVIOR Ergonomics for the Design of Multimodal Interfaces Early Integration for Movement Modeling in Latent Spaces Standardized Representations and Markup Languages for Multimodal Interaction Multimodal Databases EMERGING TRENDS AND APPLICATIONS Medical and Health Systems Automotive Multimodal Human-Machine Interface Embedded Multimodal Interfaces in Robotics: Applications, Future Trends, and Societal Implications Multimodal Dialogue Processing for Machine Translation Commercialization of Multimodal Systems Privacy Concerns of Multimodal Sensor Systems Index Biographies Volume 3 Glossary

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Book SynopsisCommunities of Computing is the first book-length history of the Association for Computing Machinery (ACM), founded in 1947 and with a membership today of 100,000 worldwide. It profiles ACM's notable SIGs, active chapters, and individual members, setting ACM's history into a rich social and political context. The book's 12 core chapters are organized into three thematic sections. ""Defining the Discipline"" examines the 1960s and 1970s when the field of computer science was taking form at the National Science Foundation, Stanford University, and through ACM's notable efforts in education and curriculum standards. "Broadening the Profession" looks outward into the wider society as ACM engaged with social and political issues - and as members struggled with balancing a focus on scientific issues and awareness of the wider world.Chapters examine the social turbulence surrounding the Vietnam War, debates about the women's movement, efforts for computing and community education, and international issues including professionalization and the Cold War. "Expanding Research Frontiers" profiles three areas of research activity where ACM members and ACM itself shaped notable advances in computing, including computer graphics, computer security, and hypertext.Featuring insightful profiles of notable ACM leaders, such as Edmund Berkeley, George Forsythe, Jean Sammet, Peter Denning, and Kelly Gotlieb, and honest assessments of controversial episodes, the volume deals with compelling and complex issues involving ACM and computing. It is not a narrow organizational history of ACM committees and SIGS, although much information about them is given. All chapters are original works of research. Many chapters draw on archival records of ACM's headquarters, ACM SIGs, and ACM leaders. This volume makes a permanent contribution to documenting the history of ACM and understanding its central role in the history of computing.Table of Contents 1. ACM and the Computing Revolution (Thomas J. Misa) Theme 1: Defining the Discipline 2. From Handmaiden to 'Proper Intellectual Discipline': Creating a Scientific Identity for Computer Science in 1960s America (Janet Abbate) 3. George Forsythe, the ACM, and the Creation of Computer Science As We Know It (Joseph November) 4. Solving a Career Equation: The First Doctoral Women in Computer Science (Irina Nikivincze) 5. The History and Purpose of Computing Curricula (1960s to 2000s) (Sebastian Dziallas) Theme 2: Broadening the Profession 6. 'Deeply Political and Social Issues': Debates within ACM 1965-1985 (Janet Toland) 7. Organized Advocacy for Professional Women in Computing: Comparing Histories of the AWC and the ACM-W (Amy Sue Bix) 8. The Development of Computer Professionalization in Canada (Scott Campbell) 9. The Anatomy of an Encounter: Transnational Mediation and Discipline Building in Cold War Computer Science (Ksenia Tatarchenko) 10. Concern for the 'Disadvantaged': ACM's Role in Training and Education for Communities of Color 1958-1975 (R. Arvid Nelsen) Theme 3: Expanding Research Frontiers 11. Other Places of Invention: Computer Graphics at the University of Utah (Jacob Gaboury) 12. Framing Computer Security and Privacy, 1967-1992 (Rebecca Slayton) 13. Hypertext, Digital Libraries, and Beyond: A History of SIGWEB (Inna Kouper) Bibliography

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Book SynopsisCommunities of Computing is the first book-length history of the Association for Computing Machinery (ACM), founded in 1947 and with a membership today of 100,000 worldwide. It profiles ACM's notable SIGs, active chapters, and individual members, setting ACM's history into a rich social and political context. The book's 12 core chapters are organized into three thematic sections. "Defining the Discipline" examines the 1960s and 1970s when the field of computer science was taking form at the National Science Foundation, Stanford University, and through ACM's notable efforts in education and curriculum standards. "Broadening the Profession" looks outward into the wider society as ACM engaged with social and political issues - and as members struggled with balancing a focus on scientific issues and awareness of the wider world.Chapters examine the social turbulence surrounding the Vietnam War, debates about the women's movement, efforts for computing and community education, and international issues including professionalization and the Cold War. "Expanding Research Frontiers" profiles three areas of research activity where ACM members and ACM itself shaped notable advances in computing, including computer graphics, computer security, and hypertext.Featuring insightful profiles of notable ACM leaders, such as Edmund Berkeley, George Forsythe, Jean Sammet, Peter Denning, and Kelly Gotlieb, and honest assessments of controversial episodes, the volume deals with compelling and complex issues involving ACM and computing. It is not a narrow organizational history of ACM committees and SIGS, although much information about them is given. All chapters are original works of research. Many chapters draw on archival records of ACM's headquarters, ACM SIGs, and ACM leaders. This volume makes a permanent contribution to documenting the history of ACM and understanding its central role in the history of computing.Table of Contents 1. ACM and the Computing Revolution (Thomas J. Misa) Theme 1: Defining the Discipline 2. From Handmaiden to 'Proper Intellectual Discipline': Creating a Scientific Identity for Computer Science in 1960s America (Janet Abbate) 3. George Forsythe, the ACM, and the Creation of Computer Science As We Know It (Joseph November) 4. Solving a Career Equation: The First Doctoral Women in Computer Science (Irina Nikivincze) 5. The History and Purpose of Computing Curricula (1960s to 2000s) (Sebastian Dziallas) Theme 2: Broadening the Profession 6. 'Deeply Political and Social Issues': Debates within ACM 1965-1985 (Janet Toland) 7. Organized Advocacy for Professional Women in Computing: Comparing Histories of the AWC and the ACM-W (Amy Sue Bix) 8. The Development of Computer Professionalization in Canada (Scott Campbell) 9. The Anatomy of an Encounter: Transnational Mediation and Discipline Building in Cold War Computer Science (Ksenia Tatarchenko) 10. Concern for the 'Disadvantaged': ACM's Role in Training and Education for Communities of Color 1958-1975 (R. Arvid Nelsen) Theme 3: Expanding Research Frontiers 11. Other Places of Invention: Computer Graphics at the University of Utah (Jacob Gaboury) 12. Framing Computer Security and Privacy, 1967-1992 (Rebecca Slayton) 13. Hypertext, Digital Libraries, and Beyond: A History of SIGWEB (Inna Kouper) Bibliography

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Book SynopsisThe idea of this book grew out of a symposium that was held at Stony Brook in September 2012 in celebration of David S.Warren's fundamental contributions to Computer Science and the area of Logic Programming in particular.Logic Programming (LP) is at the nexus of Knowledge Representation, Artificial Intelligence, Mathematical Logic, Databases, and Programming Languages. It is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Logic programs are more declarative in the sense that they strive to be logical specifications of ""what"" to do rather than ""how"" to do it, and thus they are high-level and easier to understand and maintain. Yet, without being given an actual algorithm, LP systems implement the logical specifications automatically.Several books cover the basics of LP but focus mostly on the Prolog language with its incomplete control strategy and non-logical features. At the same time, there is generally a lack of accessible yet comprehensive collections of articles covering the key aspects in declarative LP. These aspects include, among others, well-founded vs. stable model semantics for negation, constraints, object-oriented LP, updates, probabilistic LP, and evaluation methods, including top-down vs. bottom-up, and tabling.For systems, the situation is even less satisfactory, lacking accessible literature that can help train the new crop of developers, practitioners, and researchers. There are a few guides onWarren’s Abstract Machine (WAM), which underlies most implementations of Prolog, but very little exists on what is needed for constructing a state-of-the-art declarative LP inference engine. Contrast this with the literature on, say, Compilers, where one can first study a book on the general principles and algorithms and then dive in the particulars of a specific compiler. Such resources greatly facilitate the ability to start making meaningful contributions quickly. There is also a dearth of articles about systems that support truly declarative languages, especially those that tie into first-order logic, mathematical programming, and constraint solving.LP helps solve challenging problems in a wide range of application areas, but in-depth analysis of their connection with LP language abstractions and LP implementation methods is lacking. Also, rare are surveys of challenging application areas of LP, such as Bioinformatics, Natural Language Processing, Verification, and Planning.The goal of this book is to help fill in the previously mentioned void in the LP literature. It offers a number of overviews on key aspects of LP that are suitable for researchers and practitioners as well as graduate students. The following chapters in theory, systems, and applications of LP are included.Table of Contents Preface PART I THEORY 1. Datalog: Concepts, History, and Outlook 2. An Introduction to the Stable and Well-Founded Semantics of Logic Programs 3. A Survey of Probabilistic Logic Programming PART II SYSTEMS 4. WAM for Everyone: A Virtual Machine for Logic Programming 5. Predicate Logic as a Modeling Language: The IDP System 6. SolverBlox: Algebraic Modeling in Dialog PART III APPLICATIONS 7. Exploring Life: Answer Set Programming in Bioinformatics 8. State-Space Search with Tabled Logic Programs 9. Natural Language Processing with (Tabled and Constraint) Logic Programming 10. Logic Programming Applications: What Are the Abstractions and Implementations? Index Biographies

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Book SynopsisThe idea of this book grew out of a symposium that was held at Stony Brook in September 2012 in celebration of David S.Warren's fundamental contributions to Computer Science and the area of Logic Programming in particular.Logic Programming (LP) is at the nexus of Knowledge Representation, Artificial Intelligence, Mathematical Logic, Databases, and Programming Languages. It is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Logic programs are more declarative in the sense that they strive to be logical specifications of "what" to do rather than "how" to do it, and thus they are high-level and easier to understand and maintain. Yet, without being given an actual algorithm, LP systems implement the logical specifications automatically.Several books cover the basics of LP but focus mostly on the Prolog language with its incomplete control strategy and non-logical features. At the same time, there is generally a lack of accessible yet comprehensive collections of articles covering the key aspects in declarative LP. These aspects include, among others, well-founded vs. stable model semantics for negation, constraints, object-oriented LP, updates, probabilistic LP, and evaluation methods, including top-down vs. bottom-up, and tabling.For systems, the situation is even less satisfactory, lacking accessible literature that can help train the new crop of developers, practitioners, and researchers. There are a few guides onWarren’s Abstract Machine (WAM), which underlies most implementations of Prolog, but very little exists on what is needed for constructing a state-of-the-art declarative LP inference engine. Contrast this with the literature on, say, Compilers, where one can first study a book on the general principles and algorithms and then dive in the particulars of a specific compiler. Such resources greatly facilitate the ability to start making meaningful contributions quickly. There is also a dearth of articles about systems that support truly declarative languages, especially those that tie into first-order logic, mathematical programming, and constraint solving.LP helps solve challenging problems in a wide range of application areas, but in-depth analysis of their connection with LP language abstractions and LP implementation methods is lacking. Also, rare are surveys of challenging application areas of LP, such as Bioinformatics, Natural Language Processing, Verification, and Planning.The goal of this book is to help fill in the previously mentioned void in the LP literature. It offers a number of overviews on key aspects of LP that are suitable for researchers and practitioners as well as graduate students. The following chapters in theory, systems, and applications of LP are included.Table of Contents Preface PART I THEORY 1. Datalog: Concepts, History, and Outlook 2. An Introduction to the Stable and Well-Founded Semantics of Logic Programs 3. A Survey of Probabilistic Logic Programming PART II SYSTEMS 4. WAM for Everyone: A Virtual Machine for Logic Programming 5. Predicate Logic as a Modeling Language: The IDP System 6. SolverBlox: Algebraic Modeling in Dialog PART III APPLICATIONS 7. Exploring Life: Answer Set Programming in Bioinformatics 8. State-Space Search with Tabled Logic Programs 9. Natural Language Processing with (Tabled and Constraint) Logic Programming 10. Logic Programming Applications: What Are the Abstractions and Implementations? Index Biographies

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Book SynopsisDans le contexte préscolaire francophone, rares sont les études qui considèrent les jeunes enfants comme de véritables interlocuteurs des chercheurs. Grâce à la traduction de chercheures, anglaise, islandaise, néo-zélandaise et suédoise, l'objectif de cet ouvrage est de diffuser des recherches réalisées avec les enfants et visant à rendre compte de leurs points de vue. Il montre des pratiques mises en œuvre concrètement avec les enfants pour faire entendre leur voix et comment s'en réapproprier les perspectives dans la recherche et les politiques de la petite enfance.À travers la diversité des investigations réalisées dans les établissements d'accueil et d'éducation des jeunes enfants, les contributions insistent sur une éthique et une déontologie des chercheurs. Elles ouvrent de nouvelles démarches, proposent de nouveaux outils, en soulignant notamment l'importance des méthodologies visuelles pour permettre aux jeunes enfants d'exprimer, de différentes manières, leurs points de vue. À l'heure où la qualité de leur accueil et de leur éducation est réinterrogée, il est essentiel de se saisir de ces nouvelles perspectives qui permettent aux jeunes enfants d'être considérés comme experts de leur propre vie et parties prenantes d'une nouvelle vision du préscolaire.

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Book SynopsisCet ouvrage explore les conditions dans lesquelles s'élabore l'adressage aux enfants dans différentes industries culturelles. Il questionne en particulier la façon dont les professionnels impliqués dans la fabrique des produits pour enfants (auteurs, dessinateurs, éditeurs, scénaristes, game designers, etc.) abordent le travail de conception avec un certain nombre de connaissances, d'expériences ou même d'intuitions au sujet des enfants, qui interviennent pour guider ou justifier leurs décisions. De quelle façon tous ces savoirs ou représentations sur l'enfance qui demeurent hétérogènes, plus ou bien informés, tout en se révélant parfois en contradiction au sein d'une même entreprise se construisent-ils et affectent-ils la conception des produits pour enfants ? Quelles logiques (ludiques, éducatives, scolaires, etc.) et quelles images de l'enfant (joueur, membre de famille, élève, etc.) sont ainsi activées par les industries culturelles ? Et qu'en est-il lorsque des enfants, bien réels, sont sollicités et impliqués dans le développement des produits ?À partir d'enquêtes menées sur des terrains variés (littérature, bande dessinée, presse, applications mobiles, dessin animé) et suivant une démarche qui confronte le produit fini à ses différentes étapes de développement, aux chaînes de coopération qui permettent d'y aboutir et aux marchés dans lesquels il s'insère, ce livre offre un regard inédit et documenté sur la fabrication contemporaine des cultures matérielles et médiatiques des enfants et alimente les réflexions sur la figure de l'enfant-consommateur.

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Book SynopsisEt si on tentait d'ouvrir la boite noire du raisonnement grammatical des élèves ? que trouve-t-on dans les tiroirs des élèves, derrière les étiquettes noms , verbe ou encore déterminant ? ces termes sont-ils aussi intuitifs que la grammaire scolaire semble le croire ?S'inscrivant dans le champ des recherches concernant les représentations des élèves sur la langue, cette étude exploratoire utilise un dispositif didactique particulier, le tri de mots à visée grammaticale, afin de recueillir des données lors du suivi longitudinal d'une classe située en zone d'éducation prioritaire, sur une durée de deux années, en CE2 et CM1 (élèves âgés de 8 à 10 ans). Le corpus constitué par les traces écrites produites par les élèves a fait l'objet d'un traitement statistique afin d'en permettre la lisibilité. Les outils d'analyse linguistiques et didactiques utilisés ont permis de conforter des hypothèses déjà émises, mais aussi de dégager des tendances nouvelles concernant l'acquisition des classes grammaticales par les élèves de l'école élémentaire.Les résultats exposés portent sur les savoirs et savoir-faire des élèves, mais aussi sur l'éclairage que ces conceptions apportent sur les systèmes d'explication de la langue. Entre grammaire scolaire et linguistique, il s'agit de mieux comprendre le point de vue des élèves sur la langue afin d'ouvrir des pistes de réflexions didactiques.

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Book SynopsisThis book is about describing the meaning of programming languages. The author teaches the skill of writing semantic descriptions as an efficient way to understand the features of a language. While a compiler or an interpreter offers a form of formal description of a language, it is not something that can be used as a basis for reasoning about that language nor can it serve as a definition of a programming language itself since this must allow a range of implementations. By writing a formal semantics of a language a designer can yield a far shorter description and tease out, analyse and record design choices. Early in the book the author introduces a simple notation, a meta-language, used to record descriptions of the semantics of languages. In a practical approach, he considers dozens of issues that arise in current programming languages and the key techniques that must be mastered in order to write the required formal semantic descriptions. The book concludes with a discussion of the eight key challenges: delimiting a language (concrete representation), delimiting the abstract content of a language, recording semantics (deterministic languages), operational semantics (non-determinism), context dependency, modelling sharing, modelling concurrency, and modelling exits. The content is class-tested and suitable for final-year undergraduate and postgraduate courses. It is also suitable for any designer who wants to understand languages at a deep level. Most chapters offer projects, some of these quite advanced exercises that ask for complete descriptions of languages, and the book is supported throughout with pointers to further reading and resources. As a prerequisite the reader should know at least one imperative high-level language and have some knowledge of discrete mathematics notation for logic and set theory. Trade Review“This book is much more than a textbook … . Overall, the book is very well written and organised. … this book is a very good tour of the history and development of mainstream programming languages from a formal methods perspective. It is both technically sound and a well-structured narrative. I would consider this a must-read for anyone in the discipline of formal methods.” (Andrew Butterfield, Formal Aspects of Computing, Vol. 34 (3-4), November, 2022)“One of the great strengths of this book … is the continual reference to the research culture, both contemporary and historical. There are voluminous references, copious footnotes and a light-touch set of asides on the history of ideas in this field which I think will strongly motivate the best students to read and fully engage with the topic, and to understand that there are open questions and opportunities to make their own future contributions.” (Adrian Johnstone, bcs.org, July, 2021)“This well-written textbook focuses on a precise description of programming language semantics in a relatively easily understood manner, utilizing a notation derived from a subset of the Vienna development method (VDM). … The author developed both the formalism and textbook over an extended period, using ten years of classes to refine the content. The resultant book is easy to read, well organized, and appropriate for an upper-level undergraduate or graduate class.” (Michael Oudshoorn, Computing Reviews, June 29, 2021)Table of Contents

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Book SynopsisMobile agent computing is being used in fields as diverse as artificial intelligence, computational economics and robotics. Agents' ability to adapt dynamically and execute asynchronously and autonomously brings potential advantages in terms of fault-tolerance, flexibility and simplicity. This monograph focuses on studying mobile agents as modelled in distributed systems research and in particular within the framework of research performed in the distributed algorithms community. It studies the fundamental question of how to achieve rendezvous, the gathering of two or more agents at the same node of a network. Like leader election, such an operation is a useful subroutine in more general computations that may require the agents to synchronize, share information, divide up chores, etc. The work provides an introduction to the algorithmic issues raised by the rendezvous problem in the distributed computing setting. For the most part our investigation concentrates on the simplest case of two agents attempting to rendezvous on a ring network. Other situations including multiple agents, faulty nodes and other topologies are also examined. An extensive bibliography provides many pointers to related work not covered in the text. The presentation has a distinctly algorithmic, rigorous, distributed computing flavor and most results should be easily accessible to advanced undergraduate and graduate students in computer science and mathematics departments. Table of Contents: Models for Mobile Agent Computing / Deterministic Rendezvous in a Ring / Multiple Agent Rendezvous in a Ring / Randomized Rendezvous in a Ring / Other Models / Other TopologiesTable of ContentsModels for Mobile Agent Computing.- Deterministic Rendezvous in a Ring.- Multiple Agent Rendezvous in a Ring.- Randomized Rendezvous in a Ring.- Other Models.- Other Topologies.

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Book SynopsisUnderstanding distributed computing is not an easy task. This is due to the many facets of uncertainty one has to cope with and master in order to produce correct distributed software. Considering the uncertainty created by asynchrony and process crash failures in the context of message-passing systems, the book focuses on the main abstractions that one has to understand and master in order to be able to produce software with guaranteed properties. These fundamental abstractions are communication abstractions that allow the processes to communicate consistently (namely the register abstraction and the reliable broadcast abstraction), and the consensus agreement abstractions that allows them to cooperate despite failures. As they give a precise meaning to the words "communicate" and "agree" despite asynchrony and failures, these abstractions allow distributed programs to be designed with properties that can be stated and proved. Impossibility results are associated with these abstractions. Hence, in order to circumvent these impossibilities, the book relies on the failure detector approach, and, consequently, that approach to fault-tolerance is central to the book. Table of Contents: List of Figures / The Atomic Register Abstraction / Implementing an Atomic Register in a Crash-Prone Asynchronous System / The Uniform Reliable Broadcast Abstraction / Uniform Reliable Broadcast Abstraction Despite Unreliable Channels / The Consensus Abstraction / Consensus Algorithms for Asynchronous Systems Enriched with Various Failure Detectors / Constructing Failure DetectorsTable of ContentsList of Figures.- The Atomic Register Abstraction.- Implementing an Atomic Register in a Crash-Prone Asynchronous System.- The Uniform Reliable Broadcast Abstraction.- Uniform Reliable Broadcast Abstraction Despite Unreliable Channels.- The Consensus Abstraction.- Consensus Algorithms for Asynchronous Systems Enriched with Various Failure Detectors.- Constructing Failure Detectors.

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Book SynopsisUnderstanding distributed computing is not an easy task. This is due to the many facets of uncertainty one has to cope with and master in order to produce correct distributed software. A previous book Communication and Agreement Abstraction for Fault-tolerant Asynchronous Distributed Systems (published by Morgan & Claypool, 2010) was devoted to the problems created by crash failures in asynchronous message-passing systems. The present book focuses on the way to cope with the uncertainty created by process failures (crash, omission failures and Byzantine behavior) in synchronous message-passing systems (i.e., systems whose progress is governed by the passage of time). To that end, the book considers fundamental problems that distributed synchronous processes have to solve. These fundamental problems concern agreement among processes (if processes are unable to agree in one way or another in presence of failures, no non-trivial problem can be solved). They are consensus, interactive consistency, k-set agreement and non-blocking atomic commit. Being able to solve these basic problems efficiently with provable guarantees allows applications designers to give a precise meaning to the words ""cooperate"" and ""agree"" despite failures, and write distributed synchronous programs with properties that can be stated and proved. Hence, the aim of the book is to present a comprehensive view of agreement problems, algorithms that solve them and associated computability bounds in synchronous message-passing distributed systems. Table of Contents: List of Figures / Synchronous Model, Failure Models, and Agreement Problems / Consensus and Interactive Consistency in the Crash Failure Model / Expedite Decision in the Crash Failure Model / Simultaneous Consensus Despite Crash Failures / From Consensus to k-Set Agreement / Non-Blocking Atomic Commit in Presence of Crash Failures / k-Set Agreement Despite Omission Failures / Consensus Despite Byzantine Failures / Byzantine Consensus in Enriched ModelsTable of ContentsList of Figures.- Synchronous Model, Failure Models, and Agreement Problems.- Consensus and Interactive Consistency in the Crash Failure Model.- Expedite Decision in the Crash Failure Model.- Simultaneous Consensus Despite Crash Failures.- From Consensus to k-Set Agreement.- Non-Blocking Atomic Commit in Presence of Crash Failures.- k-Set Agreement Despite Omission Failures.- Consensus Despite Byzantine Failures.- Byzantine Consensus in Enriched Models.

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Book SynopsisThis monograph presents the Timed Input/Output Automaton (TIOA) modeling framework, a basic mathematical framework to support description and analysis of timed (computing) systems. Timed systems are systems in which desirable correctness or performance properties of the system depend on the timing of events, not just on the order of their occurrence. Timed systems are employed in a wide range of domains including communications, embedded systems, real-time operating systems, and automated control. Many applications involving timed systems have strong safety, reliability, and predictability requirements, which make it important to have methods for systematic design of systems and rigorous analysis of timing-dependent behavior. The TIOA framework also supports description and analysis of timed distributed algorithms -- distributed algorithms whose correctness and performance depend on the relative speeds of processors, accuracy of local clocks, or communication delay bounds. Such algorithms arise, for example, in traditional and wireless communications, networks of mobile devices, and shared-memory multiprocessors. The need to prove rigorous theoretical results about timed distributed algorithms makes it important to have a suitable mathematical foundation. An important feature of the TIOA framework is its support for decomposing timed system descriptions. In particular, the framework includes a notion of external behavior for a timed I/O automaton, which captures its discrete interactions with its environment. The framework also defines what it means for one TIOA to implement another, based on an inclusion relationship between their external behavior sets, and defines notions of simulations, which provide sufficient conditions for demonstrating implementation relationships. The framework includes a composition operation for TIOAs, which respects external behavior, and a notion of receptiveness, which implies that a TIOA does not block the passage of time. The TIOA framework also defines the notion of a property and what it means for a property to be a safety or a liveness property. It includes results that capture common proof methods for showing that automata satisfy properties. Table of Contents: Introduction / Mathematical Preliminaries / Describing Timed System Behavior / Timed Automata / Operations on Timed Automata / Properties for Timed Automata / Timed I/O Automata / Operations on Timed I/O Automata / Conclusions and Future WorkTable of ContentsIntroduction.- Mathematical Preliminaries.- Describing Timed System Behavior.- Timed Automata.- Operations on Timed Automata.- Properties for Timed Automata.- Timed I/O Automata.- Operations on Timed I/O Automata.- Conclusions and Future Work.

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Book SynopsisWireless sensor networks are about to be part of everyday life. Homes and workplaces capable of self-controlling and adapting air-conditioning for different temperature and humidity levels, sleepless forests ready to detect and react in case of a fire, vehicles able to avoid sudden obstacles or possibly able to self-organize routes to avoid congestion, and so on, will probably be commonplace in the very near future. Mobility plays a central role in such systems and so does passive mobility, that is, mobility of the network stemming from the environment itself. The population protocol model was an intellectual invention aiming to describe such systems in a minimalistic and analysis-friendly way. Having as a starting-point the inherent limitations but also the fundamental establishments of the population protocol model, we try in this monograph to present some realistic and practical enhancements that give birth to some new and surprisingly powerful (for these kind of systems) computational models. Table of Contents: Population Protocols / The Computational Power of Population Protocols / Enhancing the model / Mediated Population Protocols and Symmetry / Passively Mobile Machines that Use Restricted Space / Conclusions and Open Research Directions / Acronyms / Authors' BiographiesTable of ContentsPopulation Protocols.- The Computational Power of Population Protocols.- Enhancing the model.- Mediated Population Protocols and Symmetry.- Passively Mobile Machines that Use Restricted Space.- Conclusions and Open Research Directions.- Acronyms.- Authors' Biographies.

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Book SynopsisCooperative network supercomputing is becoming increasingly popular for harnessing the power of the global Internet computing platform. A typical Internet supercomputer consists of a master computer or server and a large number of computers called workers, performing computation on behalf of the master. Despite the simplicity and benefits of a single master approach, as the scale of such computing environments grows, it becomes unrealistic to assume the existence of the infallible master that is able to coordinate the activities of multitudes of workers. Large-scale distributed systems are inherently dynamic and are subject to perturbations, such as failures of computers and network links, thus it is also necessary to consider fully distributed peer-to-peer solutions. We present a study of cooperative computing with the focus on modeling distributed computing settings, algorithmic techniques enabling one to combine efficiency and fault-tolerance in distributed systems, and the exposition of trade-offs between efficiency and fault-tolerance for robust cooperative computing. The focus of the exposition is on the abstract problem, called Do-All, and formulated in terms of a system of cooperating processors that together need to perform a collection of tasks in the presence of adversity. Our presentation deals with models, algorithmic techniques, and analysis. Our goal is to present the most interesting approaches to algorithm design and analysis leading to many fundamental results in cooperative distributed computing. The algorithms selected for inclusion are among the most efficient that additionally serve as good pedagogical examples. Each chapter concludes with exercises and bibliographic notes that include a wealth of references to related work and relevant advanced results. Table of Contents: Introduction / Distributed Cooperation and Adversity / Paradigms and Techniques / Shared-Memory Algorithms / Message-Passing Algorithms / The Do-All Problem in Other Settings / Bibliography / Authors' BiographiesTable of ContentsIntroduction.- Distributed Cooperation and Adversity.- Paradigms and Techniques.- Shared-Memory Algorithms.- Message-Passing Algorithms.- The Do-All Problem in Other Settings.- Bibliography.- Authors' Biographies.

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Book SynopsisLink reversal is a versatile algorithm design technique that has been used in numerous distributed algorithms for a variety of problems. The common thread in these algorithms is that the distributed system is viewed as a graph, with vertices representing the computing nodes and edges representing some other feature of the system (for instance, point-to-point communication channels or a conflict relationship). Each algorithm assigns a virtual direction to the edges of the graph, producing a directed version of the original graph. As the algorithm proceeds, the virtual directions of some of the links in the graph change in order to accomplish some algorithm-specific goal. The criterion for changing link directions is based on information that is local to a node (such as the node having no outgoing links) and thus this approach scales well, a feature that is desirable for distributed algorithms. This monograph presents, in a tutorial way, a representative sampling of the work on link-reversal-based distributed algorithms. The algorithms considered solve routing, leader election, mutual exclusion, distributed queueing, scheduling, and resource allocation. The algorithms can be roughly divided into two types, those that assume a more abstract graph model of the networks, and those that take into account more realistic details of the system. In particular, these more realistic details include the communication between nodes, which may be through asynchronous message passing, and possible changes in the graph, for instance, due to movement of the nodes. We have not attempted to provide a comprehensive survey of all the literature on these topics. Instead, we have focused in depth on a smaller number of fundamental papers, whose common thread is that link reversal provides a way for nodes in the system to observe their local neighborhoods, take only local actions, and yet cause global problems to be solved. We conjecture that future interesting uses of link reversal are yet to be discovered. Table of Contents: Introduction / Routing in a Graph: Correctness / Routing in a Graph: Complexity / Routing and Leader Election in a Distributed System / Mutual Exclusion in a Distributed System / Distributed Queueing / Scheduling in a Graph / Resource Allocation in a Distributed System / ConclusionTable of ContentsIntroduction.- Routing in a Graph: Correctness.- Routing in a Graph: Complexity.- Routing and Leader Election in a Distributed System.- Mutual Exclusion in a Distributed System.- Distributed Queueing.- Scheduling in a Graph.- Resource Allocation in a Distributed System.- Conclusion.

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Book SynopsisThe study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the robots are capable of performing complex tasks, and form a system with desirable fault-tolerant and self-stabilizing properties. The research has been concerned with the computational aspects of such systems. In particular, the focus has been on the minimal capabilities that the robots should have in order to solve a problem. This book focuses on the recent algorithmic results in the field of distributed computing by oblivious mobile robots (unable to remember the past). After introducing the computational model with its nuances, we focus on basic coordination problems: pattern formation, gathering, scattering, leader election, as well as on dynamic tasks such as flocking. For each of these problems, we provide a snapshot of the state of the art, reviewing the existing algorithmic results. In doing so, we outline solution techniques, and we analyze the impact of the different assumptions on the robots' computability power. Table of Contents: Introduction / Computational Models / Gathering and Convergence / Pattern Formation / Scatterings and Coverings / Flocking / Other DirectionsTable of ContentsIntroduction.- Computational Models.- Gathering and Convergence.- Pattern Formation.- Scatterings and Coverings.- Flocking.- Other Directions.

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Book SynopsisThe focus of this monograph is on symmetry breaking problems in the message-passing model of distributed computing. In this model a communication network is represented by a n-vertex graph G = (V,E), whose vertices host autonomous processors. The processors communicate over the edges of G in discrete rounds. The goal is to devise algorithms that use as few rounds as possible. A typical symmetry-breaking problem is the problem of graph coloring. Denote by ? the maximum degree of G. While coloring G with ? + 1 colors is trivial in the centralized setting, the problem becomes much more challenging in the distributed one. One can also compromise on the number of colors, if this allows for more efficient algorithms. Other typical symmetry-breaking problems are the problems of computing a maximal independent set (MIS) and a maximal matching (MM). The study of these problems dates back to the very early days of distributed computing. The founding fathers of distributed computing laid firm foundations for the area of distributed symmetry breaking already in the eighties. In particular, they showed that all these problems can be solved in randomized logarithmic time. Also, Linial showed that an O(?2)-coloring can be solved very efficiently deterministically. However, fundamental questions were left open for decades. In particular, it is not known if the MIS or the (? + 1)-coloring can be solved in deterministic polylogarithmic time. Moreover, until recently it was not known if in deterministic polylogarithmic time one can color a graph with significantly fewer than ?2 colors. Additionally, it was open (and still open to some extent) if one can have sublogarithmic randomized algorithms for the symmetry breaking problems. Recently, significant progress was achieved in the study of these questions. More efficient deterministic and randomized (? + 1)-coloring algorithms were achieved. Deterministic ?1 + o(1)-coloring algorithms with polylogarithmic running time were devised. Improved (and often sublogarithmic-time) randomized algorithms were devised. Drastically improved lower bounds were given. Wide families of graphs in which these problems are solvable much faster than on general graphs were identified. The objective of our monograph is to cover most of these developments, and as a result to provide a treatise on theoretical foundations of distributed symmetry breaking in the message-passing model. We hope that our monograph will stimulate further progress in this exciting area.Table of ContentsAcknowledgments.- Introduction.- Basics of Graph Theory.- Basic Distributed Graph Coloring Algorithns.- Lower Bounds.- Forest-Decomposition Algorithms and Applications.- Defective Coloring.- Arbdefective Coloring.- Edge-Coloring and Maximal Matching.- Network Decompositions.- Introduction to Distributed Randomized Algorithms.- Conclusion and Open Questions.- Bibliography.- Authors' Biographies.

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Book SynopsisThis book aims at being a comprehensive and pedagogical introduction to the concept of self-stabilization, introduced by Edsger Wybe Dijkstra in 1973. Self-stabilization characterizes the ability of a distributed algorithm to converge within finite time to a configuration from which its behavior is correct (i.e., satisfies a given specification), regardless the arbitrary initial configuration of the system. This arbitrary initial configuration may be the result of the occurrence of a finite number of transient faults. Hence, self-stabilization is actually considered as a versatile non-masking fault tolerance approach, since it recovers from the effect of any finite number of such faults in an unified manner. Another major interest of such an automatic recovery method comes from the difficulty of resetting malfunctioning devices in a large-scale (and so, geographically spread) distributed system (the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweight property to achieve fault tolerance as compared to other classical fault tolerance approaches. Indeed, the overhead, both in terms of time and space, of state-of-the-art self-stabilizing algorithms is commonly small. This makes self-stabilization very attractive for distributed systems equipped of processes with low computational and memory capabilities, such as wireless sensor networks. After more than 40 years of existence, self-stabilization is now sufficiently established as an important field of research in theoretical distributed computing to justify its teaching in advanced research-oriented graduate courses. This book is an initiation course, which consists of the formal definition of self-stabilization and its related concepts, followed by a deep review and study of classical (simple) algorithms, commonly used proof schemes and design patterns, as well as premium results issued from the self-stabilizing community. As often happens in the self-stabilizing area, in this book we focus on the proof of correctness and the analytical complexity of the studied distributed self-stabilizing algorithms. Finally, we underline that most of the algorithms studied in this book are actually dedicated to the high-level atomic-state model, which is the most commonly used computational model in the self-stabilizing area. However, in the last chapter, we present general techniques to achieve self-stabilization in the low-level message passing model, as well as example algorithms.Table of ContentsPreface.- Acknowledgments.- Introduction.- Preliminaries.- Coloring under a Locally Central Unfair Daemon.- Synchronous Unison.- BFS Spanning Tree Under a Distributed Unfair Daemon.- Dijkstra's Token Ring.- Hierarchical Collateral Composition.- Self-Stabilization in Message Passing Systems.- Bibliography.- Authors' Biographies.- Index.

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Book SynopsisAutomatic Control with Interactive Tools is a textbook for undergraduate study of automatic control. Providing a clear course structure, and covering concepts taught in engineering degrees, this book is an ideal companion to those studying or teaching automatic control. The authors have used this text successfully to teach their students.By providing unique interactive tools, which have been designed to illustrate the most important automatic control concepts, Automatic Control with Interactive Tools helps students overcome the potential barriers presented by the significant mathematical content of automatic control courses. Even when they have previously had only the benefit of an introductory control course, the software tools presented will help readers to get to grips with the use of such techniques as differential equations, linear algebra, and differential geometry. This textbook covers the breadth of automatic control topics, including time responses of dynamic systems, the Nyquist criterion and PID control. It switches smoothly between analytical and practical approaches. Automatic Control with Interactive Tools offers a clear introduction to automatic control, ideal for undergraduate students, instructors and anyone wishing to familiarize themselves with the fundamentals of the subjectTable of Contents1. Introduction.- 2. From Nonlinear Physical Models to Linear Models.- 3. Time Response.- 4. Frequency Response.- 5. Relationship Between Model Parameters with Physical Models.- 6. Closed-Loop Systems and Stability.- 7. Control Systems Design.- 8. Control of Physical Systems.- 9. Introduction to Control Systems Design in State Space.

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Book SynopsisThis is open access book provides plenty of pleasant mathematical surprises. There are many fascinating results that do not appear in textbooks although they are accessible with a good knowledge of secondary-school mathematics. This book presents a selection of these topics including the mathematical formalization of origami, construction with straightedge and compass (and other instruments), the five- and six-color theorems, a taste of Ramsey theory and little-known theorems proved by induction. Among the most surprising theorems are the Mohr-Mascheroni theorem that a compass alone can perform all the classical constructions with straightedge and compass, and Steiner's theorem that a straightedge alone is sufficient provided that a single circle is given. The highlight of the book is a detailed presentation of Gauss's purely algebraic proof that a regular heptadecagon (a regular polygon with seventeen sides) can be constructed with straightedge and compass. Although the mathematics used in the book is elementary (Euclidean and analytic geometry, algebra, trigonometry), students in secondary schools and colleges, teachers, and other interested readers will relish the opportunity to confront the challenge of understanding these surprising theorems.Supplementary material to the book can be found at https://github.com/motib/suprises.Table of Contents- 1. The Collapsing Compass. - 2. Trisection of an Angle. - 3. Squaring the Circle. - 4. The Five-Color Theorem. - 5. How to Guard a Museum. - 6. Induction. - 7. Solving Quadratic Equations. - 8. Ramsey Theory. - 9. Langford’s Problem. - 10. The Axioms of Origami. - 11. Lill’s Method and the Beloch Fold. - 12. Geometric Constructions Using Origami. - 13. A Compass Is Sufficient. - 14. A Straightedge and One Circle is Sufficient. - 15. Are Triangles with Equal Areas and Perimeters Congruent?. - 16. Construction of a Regular Heptadecagon.

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Book SynopsisThis book draws on almost five decades of entrepreneurial experience and innovation and offers a broad perspective on ethical tech startups. It approaches the subject on two fronts by considering both the business of ethical technology as well as the challenges of tech startups with an imperative to behave ethically. The book provides readers with the tools to ethically frame and construct their startup ventures whether or not their core business is rooted in a technology meant to serve a social good. Incorporating ethical business practices both in knowledge and action, this book leads readers through the process of shaping an incipient startup idea all the way through the long-term operating stages. Using real-world case studies, the book explores key factors in successfully planning, framing, launching, leading, managing, and financing startups. This book is essential reading for researchers, academics, and students as well as industry professionals who have an idea or technology they want to get out into the world. Whether readers are seasoned in the field, employees of existing startups looking for better approaches, or new idealistic innovators who want to learn where to start, this guidebook explains and explores the road to launching the next great ethical tech startup.Table of ContentsPrologue.Problems, Solutions, and Value.Underlying Magic and Competitive Advantage.Validation and User Experience,- Identity: Defining It and Communicating It.Business Models and Go-to-Market Plans.Finances and Financing.Leadership, Management, and Team.Ethical Entrepreneurship.Principles for Success.Epilogue.

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Book SynopsisThis book constitutes proceedings of the 7th International Conference on Information, Communication and Computing Technology, ICICCT 2022, held in New Delhi, India, in July 2022.The 11 papers presented in this volume were carefully reviewed and selected from 65 submissions. The papers cover a great variety of topics, such as wireless networks, deep learning, machine learning, neural networks, natural language processing, sentiment analysis, network security, image processing, image augmentation and others. The contributions are divided into the following thematic blocks: Networking and Communication; Evolutionary Computing through Machine Learning.Table of ContentsNetworking and Communication.- Energy Efficient Communication using Constrained Application Protocol for IoT Devices.- A Systematic Study on LoRa Communication in IoT: Implementation Challenges and Research Solutions.- A Low Complexity CFO Reduction Technique for LFDMA Systems.- DICCh-D: Detecting IPv6-based Covert Channels using DNN.- Evolutionary Computing through Machine Learning.- Image Caption Generation for Low Light Images.- A Study On Feature Selection For Gender Detection In Speech Processing For Assamese Language.- Bengali Fake News Detection: Transfer Learning Based Technique with Masked LM Process by BERT.- Crowd Counting Using Federated Learning And Domain Adaptation.- News Headline Generation using Abstractive Text Summarization.- Facial Based Age Estimation Among Dark Skinned Hominid Species.- Multi-class Classification of Leaves using Transfer Learning.

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Book SynopsisThis nine-volume set LNCS 14104 – 14112 constitutes the refereed workshop proceedings of the 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, held at Athens, Greece, during July 3–6, 2023. The 350 full papers and 29 short papers and 2 PHD showcase papers included in this volume were carefully reviewed and selected from a total of 876 submissions. These nine-volumes includes the proceedings of the following workshops: Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2023); Advanced Processes of Mathematics and Computing Models in Complex Computational Systems (ACMC 2023); Artificial Intelligence supported Medical data examination (AIM 2023); Advanced and Innovative web Apps (AIWA 2023); Assessing Urban Sustainability (ASUS 2023); Advanced Data Science Techniques with applications in Industry and Environmental Sustainability (ATELIERS 2023); Advances in Web Based Learning (AWBL 2023); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2023); Bio and Neuro inspired Computing and Applications (BIONCA 2023); Choices and Actions for Human Scale Cities: Decision Support Systems (CAHSC-DSS 2023); and Computational and Applied Mathematics (CAM 2023).Table of Contents​MOdels and indicators for assessing and measuring the urban settlement deVElopment in the view of ZERO net land take by 2050 (MOVEto0 2023).- Energy transition and spatial transformation: looking for a suitable trade-off.- Machine learning techniques for the semiautomated recognition of urban and peri-urban configurations.- Modelling Post-Covid cities (MPCC 2023).- Eco-Fashion Luxury Brand: an empirical survey on the attitudes of Millennials and Centennials.- Metropolitan City Lab (Metro_City_Lab 2023).- Minimum environmental criteria and climate issue in the metropolitan urban ecosystem.- A conceptual framework to correlate the electric transition and well-being and equity. The Italy case.- 3rd Workshop on Privacy in the Cloud/Edge/IoT World (PCEIoT 2023).- FPGA-enabled Efficient Framework for High-Performance Intrusion Prevention Systems.- Improving Drone Security in Smart Cities via Lightweight Cryptography.- "SHeMed": An application on Secure computation of Medical cloud data based on Homomorphic encryption.- Evaluating the effectiveness of privacy and security promotion strategies.- A decentralized Smart City using Solid and Self-Sovereign Identity.- Prevention of cyber-attacks and privacy breaches in healthcare sector.- TokenFuse: A Versatile NFT Marketplace.- PORt ciTy interface: land Use, logistic aNd rear pOrt area planning (PORTUNO 2023).- Sustainable maritime passenger transport: a network analysis approach on a national basis.- Sustainable maritime passenger transport: a network analysis approach on a national basis.- Ports in the port: the case of Messina.- The stable Strait crossing system. What developments and opportunities?.- Scientific Computing Infrastructure (SCI 2023).- Polynomial neural layers for numerical modeling of dynamical processes.- Deploying Deep Learning models using serverless computing for Diabetic Retinopathy detection.- The survey of self-driving car challenges in smart city infrastructures.- New Security Challenges of Internet of Things.- K-anonymity Versus PSI3 for Depersonalization and Security Assessment of Large Data Structures.- Continuous Authentication Methods for Zero-Trust Cybersecurity Architecture.- Spatial COgnition in urban and regional Planning Under Risk (SCOPUR23).- Mapping citizens' knowledge and perception. What support for flood risk planning? Some tips from Brindisi case study.- Advancing Urban Science with Multi-Agent Systems: Prospects for Innovation and Sustainability in Spatial Planning and Urban Governance.- Socio-Economic and Environmental Models for Land Use Management (SEMLUM 2023).- The student housing as a catalyst for virtuous processes of "win-win" revitalization of property assets in disuse.- The student housing as a catalyst for virtuous processes of "win-win" revitalization of property assets in disuse.- The real estate risk assessment: an innovative methodology for supporting public and private subjects involved into sustainable urban interventions.- (Con)temporary housing: the AirBnb phenomenon and its impact on the Naples historic center's rental market.- Endogenous vs. Exogenous Leadership in Teamwork: An Socio-Economic Experimental Study.- A GIS referenced methodological approach for the brownfield redevelopment.- A methodological approach for the assessment of parametric costs of sustainable urban roads: an application to the city of Rome (Italy).- The usufruct right as an effective strategy for the enhancement of properties in disuse.- Specifics of smart cities development in Europe (SPEED 2023).- Engagement and inclusion experiences for energy communities. An ongoing case study in Cagliari, Italy.- Citizens participation in the transition of Greek cities to smart cities: Does size matter?.- Impacts of Smart Governance on Urban Development.- Multi-Level Perspective within the regulatory framework of shared mobility: a case studies analysis of Italian Demand Responsive Shared Transport services (DRSTs).- Website as a Tool of Local E-Governance in Czechia: which CMS Is the Most Popular in the Moravian-Silesian Region?.

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