Computer architecture and logic design Books

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Book SynopsisThis book highlights the importance of data-driven techniques to solve wireless communication problems. It presents a number of problems (e.g., related to performance, security, and social networking), and provides solutions using various data-driven techniques, including machine learning, deep learning, federated learning, and artificial intelligence.This book details wireless communication problems that can be solved by data-driven solutions. It presents a generalized approach toward solving problems using specific data-driven techniques. The book also develops a taxonomy of problems according to the type of solution presented and includes several case studies that examine data-driven solutions for issues such as quality of service (QoS) in heterogeneous wireless networks, 5G/6G networks, and security in wireless networks. The target audience of this book includes professionals, researchers, professors, and students working in the field of networking, communicationTable of ContentsPart 1: Data-Driven Wireless Networks: Design and ApplicationsChapter 1: Data-Driven Wireless Networks: A PerspectiveChapter 2: A Collaborative Data-Driven Intelligence for Future Wireless NetworksChapter 3: Federated learning Technique in Enabling Data-driven Design for Wireless CommunicationChapter 4: Application of Wireless Network Data Driver using Edge Computing and Deep Learning in Intelligent TransportationChapter 5: Data-Driven Agriculture and the Role of AI in Smart FarmingPart II: Data-Driven Techniques and Security Issues in Wireless NetworksChapter 6: Data-Driven Techniques and Security Issues in Wireless NetworkChapter 7: Data-Driven Techniques for Intrusion Detection in Wireless NetworksPart III: Advanced Topics in Data-Driven Intelligence for Wireless NetworksChapter 8: Policy-based Data Analytic for Software-Defined WirelessChapter 9: Data-Driven Coexistence in Next-Generation Heterogeneous Cellular NetworksChapter 10: Programming Languages, Tools, and Technique

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Book SynopsisThis book describes how to establish data science and analytics capabilities in organisations using Emergent Design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment. Based on their experiences and those of a number of data leaders, the authors provide actionable advice on data technologies, processes, and governance structures so that readers can make choices that are appropriate to their organisational contexts and requirements.The book blends academic research on organisational change and data science processes with real-world stories from experienced data analytics leaders, focusing on the practical aspects of setting up a data capability. In addition to a detailed coverage of capability, culture, and technology choices, a unique feature of the book is its treatment of emerging issues such as data ethics and algorithmic fairness.Data Science and Analytics Strategy: An Emergent DesTrade Review"Not only does the discipline of data science need this book, it holds critical insights and lessons for other facets of enterprise IT too. For the first time, the critically important ideas of Emergent Design practice have been weaved into the hyper-rational world of data science in an accessible and practical way. Kailash Awati and Alex Scriven have written the first Data Science book of its kind – a must read for anyone interested in the governance of data and the complex problems that data and analytics seeks to help solve." -Paul Culmsee, Managing Partner, Seven Sigma Business Solutions"If you are passionate about the successful implementation of Data Science and Analytics strategies, then put this book on your required reading list. You will learn why and how to define a direction by finding and framing problems that matter to people across the organisation." -Zanne Van Wyk, Worldwide Education Industry Architect at Microsoft"Data Science and Analytics Strategy covers a wide range of topics like building analytics and data science capability, building data driven culture in the organization and ethical aspects of practicing data science. It includes advice which are easy and very practical to use in real world scenarios. All in all, a great read for all those who want to setup analytics and data science practises within their organization. " - Duhita Khadepau Director (Analytics and Data Science), Assignar"A refreshingly practical approach to success in data science and machine learning. The value of Awati and Scriven's contribution to this field is that emergent design lends to data science a coherence that previously was missed in the chasm between the promise of new tech and the organisational change required to harness it. They've bridged that gap with a highly accessible read, weaving the wealth of their collective experience with the rigour of leading researchers, intellectuals and practitioners into a lively jaunt covering the full vocabulary of concepts for leaders (from deep learning to tech stack to GDPR) that will hold 'aha' moments for even the most seasoned data and analytics professionals and (hopefully!) spawn a new generation of strategic leadership and emergent practice in this space." -Passiona Cottee, Associate Director, NSW Government."Succeeding with Data Science and Analytics is no easy ride, however this book gives the reader a range of ideas and actions to combat the challenges faced by professionals in this field. Finding a path to success requires new approaches and this book provides a refreshing perspective for practitioners to consider as they strive for success." -Sandra Hogan, Co-founder Amperfii. Table of ContentsForeword. Preface. Acknowledgements. Contributors. 1. Introduction. 2. What Is Data Science? 3. The Principles of Emergent Design. 4. Charting a Course. 5. Capability and Culture. 6. Technical Choices. 7. Doing Data Science: From Planning to Production. 8. Doing the Right Thing. 9. Coda. Index.

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Book SynopsisThis book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment. Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extractingTable of Contents1. Artificial Intelligence Challenges, Principles, and Applications in Smart Healthcare Systems. 2. Systematic View and Impact of Artificial Intelligence in Smart Healthcare Systems, principles, challenges and Applications. 3. Application of Machine Learning Techniques in COVID-19 Epidemiology: A Glimpse. 4. Automated Seven-Level Skin Cancer Staging Diagnosis in Dermoscopic images using Deep Learning. 5. Ensemble Classifier Based Predictive Model for Type-2 Diabetes Mellitus Prediction. 6. Machine Learning Approaches for Analysis in Smart Healthcare Informatics. 7. Smart Approaches for Diagnosis of Brain Disorders using Artificial Intelligence. 8. Bridging the Gap Between Technology and Medicine: Approaches of Artificial Intelligence in Healthcare. 9. Brain Tumor Classification using Transfer Learning. 10. Advanced Bayesian Estimation Of Weibull In Early Stage Eye Loss Prediction In Diabetic Retinopathy. 11. Automated Sleep Staging Using Single-Channel EEG SIgnal based on Machine Learning Approaches. 12. Machine Learning Based Intelligent Assistant for Smart Healthcare. 13. AI-Enabled Sentiment Analysis on COVID-19 Vaccination: A Twitter based study. 14. An Early Diagnosis of Lung Nodule Using CT Images based on Hybrid Machine Learning techniques. 15. Early Detection of Alzheimer’s Disease Assisted by AI-Powered Human-Robot Communication.

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Network Evolution and Applications provides a comprehensive, integrative, and easy approach to understanding the technologies, concepts, and milestones in the history of networking. It provides an overview of different aspects involved in the networking arena that includes the core technologies that are essential for communication and important in our day-to-day life. It throws some light on certain past networking concepts and technologies that have been revolutionary in the history of science and technology and have been highly impactful. It expands on various concepts like Artificial Intelligence, Software Defined Networking, Cloud Computing, and Internet of Things, which are very popular at present. This book focuses on the evolutions made in the world of networking. One can't imagine the world without the Internet today; with the Internet and the present- day networking, distance doesn't matter at all. The COVID-19 pandemic has resulted in a tough time worldwide

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Book SynopsisoneAPI is a unified programming model and software development kit (SDK) from Intel that empowers software developers to generate high-performance applications that can run on different devices, comprising CPUs, GPUs, FPGAs, and other accelerators. It lets developers write code once and deploy it on multiple architectures, decreasing the complexity as well as the cost and time of software development. One of the significant strengths of oneAPI is in its capability to support an eclectic range of devices and architectures, including artificial intelligence, high-performance computing, and data analytics. Along with libraries, tools, and compilers, oneAPI makes it cool for developers to create optimized code for an extensive variety of applications, making it an indispensable tool for any developer who wants to create high-performance software and reap the benefit of the latest hardware technologies. The versatility of oneAPI, by means of appropriate theory and practical implementatioTable of ContentsChapter 1 Intel oneAPI: An Introductory DiscussionChapter 2 The Intel oneAPI Toolkits: An Exploration Chapter 3 The Intel DevCloud and Jupyter Notebooks Chapter 4 What Is Machine Learning?: An Introduction! Chapter 5 Tools and Pre-requisites Chapter 6 Supervised Learning Chapter 7 Support Vector Machines (SVM): An Exploration Chapter 8 Decision Trees Chapter 9 Bagging Chapter 10 Boosting and Stacking Chapter 11 Clustering Techniques and Principial Component Analysis Chapter 12 More Intel Tools for Enhanced Developm ent Experience

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Book SynopsisDiscover the hidden depths of the digital underworld in this comprehensive, interdisciplinary exploration of the dark web.Ideal for security agencies, professionals, counter-terrorism experts, and policymakers alike, this work offers invaluable insights that will enhance understanding and fortify strategies. By shedding particular light on the nuances of the dark market,' this book provides readers with a detailed understanding of the dark web, encompassing both its sinister underbelly and unexpected potential.This book also uncovers the latest trends and cutting-edge mitigation techniques. From illicit transactions to thriving business ventures, it examines the key domains and sectors that thrive within this clandestine environment. This book consolidates myriad perspectives on security and threats on the dark web.Table of Contents1. Cybersecurity and The Dark Web. 2. A Guide to The Dark and Deep Web. 3. Dark Web Access with TOR Browser. 4. The Dark Web's Perils. 5. Cybercrime on The Dark Web. 6. Red Room Deep Web. 7. Terrorist Acts on The Surface and Dark Web. 8. Dark Web Markets. 9. We Are Anonymous. 10. Hitman for Hire. 11. The Positive and Evil Side of The Dark Web. 12. Techniques for Analyzing Dark Web Content. 13. Information Extraction from Dark Web Contents and Logs. 14. Dark Web Forensics. 15. OSINT Opensource Intelligence. 16. Emerging Dark Web Trends and Mitigation Techniques. 17. The Dark Web's Future. 18. Your Business on The Dark Web. Glossary. Bibliography.

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Book SynopsisFrom the Foreword:The authors of the chapters in this book are the pioneers who will explore the exascale frontier. The path forward will not be easy... These authors, along with their colleagues who will produce these powerful computer systems will, with dedication and determination, overcome the scalability problem, discover the new algorithms needed to achieve exascale performance for the broad range of applications that they represent, and create the new tools needed to support the development of scalable and portable science and engineering applications. Although the focus is on exascale computers, the benefits will permeate all of science and engineering because the technologies developed for the exascale computers of tomorrow will also power the petascale servers and terascale workstations of tomorrow. These affordable computing capabilities will empower scientists and engineers everywhere. Thom H. Dunning, Jr., Pacific Northwest National Laboratory and University Trade Review"Numerical simulation is now a need in many fields of science, technology, and industry. The complexity of the simulated systems coupled with the massive use of data makes the HPC essential to move towards predictive simulations. Advances in computer architecture have so far permitted scientific advances, but at the cost of continually adapting algorithms and applications. The next technological breaks force us to rethink the applications by taking energy consumption into account. These profound modifications require not only anticipation and sharing but also a paradigm shift in application design to ensure the sustainability of developments by guaranteeing a certain independence of the applications to the profound modifications of the architectures: it is the passage from optimal performance to the portability of performance. It is the challenge of this book to demonstrate by example the approach that one can adopt for the development of applications offering a portability of the performances in spite of the profound changes of the computing architectures."— Christophe Calvin, CEA, Fundamental Research Division, Scalay, France"This comprehensive summary of applications targeting Exascale at the three DoE labs is a must read."— Rio Yokota, Tokyo Institute of Technology, Tokyo, Japan"Three editors, one from each of the High Performance Computer Centers at Lawrence Berkeley, Argonne, and Oak Ridge National Laboratories, have complied a very useful set of chapters aimed at describing software developments for the next generation exa-scale computers. Such a book is needed for scientists and engineers to see where the field is going and how they will be able to exploit such architectures for their own work. The book will also benefit students as it provides insights into how to develop software for such computer architectures. Overall, this book fills an important need in showing how to design and implement algorithms for exa-scale architectures which are heterogeneous and have unique memory systems. The book discusses issues with developing user codes for these architectures and how to address these issues including actual coding examples.’ — Dr. David A. Dixon, Robert Ramsay Chair, The University of Alabama, USA"Numerical simulation is now a need in many fields of science, technology, and industry. The complexity of the simulated systems coupled with the massive use of data makes the HPC essential to move towards predictive simulations. Advances in computer architecture have so far permitted scientific advances, but at the cost of continually adapting algorithms and applications. The next technological breaks force us to rethink the applications by taking energy consumption into account. These profound modifications require not only anticipation and sharing but also a paradigm shift in application design to ensure the sustainability of developments by guaranteeing a certain independence of the applications to the profound modifications of the architectures: it is the passage from optimal performance to the portability of performance. It is the challenge of this book to demonstrate by example the approach that one can adopt for the development of applications offering a portability of the performances in spite of the profound changes of the computing architectures."— Christophe Calvin, CEA, Fundamental Research Division, Scalay, France"This comprehensive summary of applications targeting Exascale at the three DoE labs is a must read."— Rio Yokota, Tokyo Institute of Technology, Tokyo, Japan"Three editors, one from each of the High Performance Computer Centers at Lawrence Berkeley, Argonne, and Oak Ridge National Laboratories, have complied a very useful set of chapters aimed at describing software developments for the next generation exa-scale computers. Such a book is needed for scientists and engineers to see where the field is going and how they will be able to exploit such architectures for their own work. The book will also benefit students as it provides insights into how to develop software for such computer architectures. Overall, this book fills an important need in showing how to design and implement algorithms for exa-scale architectures which are heterogeneous and have unique memory systems. The book discusses issues with developing user codes for these architectures and how to address these issues including actual coding examples.’ — Dr. David A. Dixon, Robert Ramsay Chair, The University of Alabama, USATable of Contents1. Portable Methodologies for Energy Optimization on Large-Scale Power-Constrained Systems 2. Performance Analysis and Debugging Tools at Scale 3. Exascale Challenges in Numerical Linear and Multilinear Algebras 4. Exposing Hierarchical Parallelism in the FLASH Code for Supernova Simulation on Summit and Other Architectures 5. NAMD: Scalable Molecular Dynamics Based on the Charm++ Parallel Runtime System 6. Developments in Computer Architecture and the Birth and Growth of Computational Chemistry 7. On Preparing the Super Instruction Architecture and Aces4 for Future Computer Systems 8. Transitioning NWChem to the Next Generation of Manycore Machines 9. Exascale Programming Approaches for Accelerated Climate Modeling for Energy 10. Preparing the Community Earth System Model for Exascale Computing 11. Large Eddy Simulation of Reacting Flow Physics and Combustion 12. S3D-Legion: An Exascale Software for Direct Numerical Simulation of Turbulent Combustion with Complex Multicomponent Chemistry 13. Data and Work_ow Management for Exascale Global Adjoint Tomography 14. Scalable Structured Adaptive Mesh Refinement with Complex Geometry 15. Extreme Scale Unstructured Adaptive CFD for Aerodynamic Flow Control 16. Lattice Quantum Chromodynamics and Chroma 17. PIC Codes on the Road to Exascale Architectures 18. Extreme-Scale De Novo Genome Assembly 19. Exascale Scientific Applications: Programming Approaches for Scalability, Performance, and Portability: KKRnano 20. Real-Space Multiple-Scattering Theory and Its Applications at Exascale 21 Development of QMCPACK for Exascale Scientific Computing 22. Preparing an Excited-State Materials Application for Exascale 23. Global Gyrokinetic Particle-in-Cell Simulation 24. The Fusion Code XGC: Enabling Kinetic Study of Multiscale Edge Turbulent Transport in ITER

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Book SynopsisThis introductory user's guide to systems analysis and systems design focuses on building sustainable information systems to meet tomorrow's needs. It shows how practitioners can apply multiple participatory perspectives in development, so as to avoid future problems. As a practical guide, it is presented to be readily comprehensible and is organized to enable users to concentrate on their goals efficiently, and with minimum theoretical elaboration. The chapters follow the sequence involved in planning an information system, explaining key words, the time involved in each step, ending with a tutorial or exercises.Trade Review[An] excellent book.' Guy Fitzgerald, , Professor of Information Systems, Brunel University 'The book stands out in its field through the intelligent and constructive use of the soft systems methodology to develop the themes' Peter Roberts, former Visiting Professor, Open University and City University 'A useful text for teachers and practitioners of a Multiview approach to information analysis and design. It has matured and gained focus in this new edition' Gilbert Mansell, Head of Department of Multimedia and Information Systems, University of Huddersfield 'A textbook for people intending to practice information systems analysis and design.' SciTech Book NewsTable of ContentsInformation Systems and Organization * What is Systems Analysis and Systems Design? * The Role of the Systems Planner or Systems Analyst * Selecting Planning and Development Tools * The Human Activity System: Making a Model * Information Modelling: Making a Workable System * Technical and Social Needs: The Balance * The Human-Computer Interface * Technical Aspects: What is Needed? * Total Design, Training, Hardware, Software and Implementation * Glossary, Appendices, Further Reading, Index

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Book SynopsisThis introductory user's guide to systems analysis and systems design focuses on building sustainable information systems to meet tomorrow's needs. It shows how practitioners can apply multiple participatory perspectives in development, so as to avoid future problems. As a practical guide, it is presented to be readily comprehensible and is organized to enable users to concentrate on their goals efficiently, and with minimum theoretical elaboration. The chapters follow the sequence involved in planning an information system, explaining key words, the time involved in each step, ending with a tutorial or exercises.Trade Review[An] excellent book.' Guy Fitzgerald, , Professor of Information Systems, Brunel University 'The book stands out in its field through the intelligent and constructive use of the soft systems methodology to develop the themes' Peter Roberts, former Visiting Professor, Open University and City University 'A useful text for teachers and practitioners of a Multiview approach to information analysis and design. It has matured and gained focus in this new edition' Gilbert Mansell, Head of Department of Multimedia and Information Systems, University of Huddersfield 'A textbook for people intending to practice information systems analysis and design.' SciTech Book NewsTable of ContentsInformation Systems and Organization * What is Systems Analysis and Systems Design? * The Role of the Systems Planner or Systems Analyst * Selecting Planning and Development Tools * The Human Activity System: Making a Model * Information Modelling: Making a Workable System * Technical and Social Needs: The Balance * The Human-Computer Interface * Technical Aspects: What is Needed? * Total Design, Training, Hardware, Software and Implementation * Glossary, Appendices, Further Reading, Index

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Book SynopsisThis introductory textbook provides students with a system-level perspective and the tools they need to understand, analyze and design digital systems. Going beyond the design of simple combinational and sequential modules, it shows how such modules are used to build complete systems, reflecting real-world digital design. All the essential topics are covered, including design and analysis of combinational and sequential modules, as well as system timing and synchronization. It also teaches how to write Verilog HDL in a productive and maintainable style that enables CAD tools to do much of the tedious work. A complete introduction to digital design is given through clear explanations, extensive examples and online Verilog files. The teaching package is completed with lecture slides, labs and a solutions manual for instructors. Assuming no previous digital knowledge, this textbook is ideal for undergraduate digital design courses that will prepare students for modern digital practice.Trade Review'Dally and Harting blend circuit and architecture design in a clear and constructive manner on the basis of their exceptional experience in digital design. Students will discover a modern and effective way to understand the fundamental underpinning of digital design, by being exposed to the different abstraction levels and views of computing systems.' Giovanni De Micheli, École Polytechnique Fédérale de Lausanne'Bill and Curt have combined decades of academic and industry experience to produce a textbook that teaches digital system design from a very practical perspective without sacrificing the theoretical understanding needed to train tomorrow's engineers. Their approach pushes students to understand not just what they are designing but also what they are building. By presenting key advanced topics, such as synthesis, delay and logical effort, and synchronization, at the introductory level, this book is in the rare position of providing both practical advice and deep understanding. In doing so, this book will prepare students well even as technology, tools, and techniques change in the future.' David Black-Schaffer, Uppsala University'Everything you would expect from a book on digital design from [Professor] Dally. Decades of practical experience are distilled to provide the tools necessary to design and compose complete digital systems. A clear and well written text that covers the basics and system-level issues equally well. An ideal starting point for the microprocessor and SoC designers of the future!' Robert Mullins, University of Cambridge and the Raspberry Pi Foundation'This textbook sets a new standard for how digital system design is taught to undergraduates. The practical approach and concrete examples [provide] a solid foundation for anyone who wants to understand or design modern complex digital systems.' Steve Keckler, University of Texas, Austin'This book not only teaches how to do digital design, but more importantly shows how to do good design. It stresses the importance of modularization with clean interfaces, and the importance of producing digital artifacts that not only meet their specifications, but which can also be easily understood by others. It uses an aptly chosen set of examples and the Verilog code used to implement them … It includes a section on the design of asynchronous logic, a topic that is likely to become increasingly important as energy consumption becomes a primary concern in digital systems … The final appendix on Verilog coding style is particularly useful. This book will be valuable not only to students, but to practitioners in the area. I recommend it highly.' Chuck Thacker, Microsoft'A terrific book with a terrific point of view of systems. Everything interesting - and awful - that happens in digital design happens because engineers must integrate ideas from bits to blocks, from signals to CPUs. The book does a great job of focusing on the important stuff, moving from foundations to systems, with the right amount of HDL (Verilog) focus to make everything practical and relevant.' Rob A. Rutenbar, University of Illinois, Urbana-ChampaignTable of ContentsPart I. Introduction: 1. The digital abstraction; 2. The practice of digital system design; Part II. Combinational Logic: 3. Boolean algebra; 4. CMOS logic circuits; 5. Delay and power of CMOS circuits; 6. Combinational logic design; 7. Verilog descriptions of combinational logic; 8. Combinational building blocks; 9. Combinational examples; Part III. Arithmetic Circuits: 10. Arithmetic circuits; 11. Fixed- and floating-point numbers; 12. Fast arithmetic circuits; 13. Arithmetic examples; Part IV. Synchronous Sequential Logic: 14. Sequential logic; 15. Timing constraints; 16. Datapath sequential logic; 17. Factoring finite-state machines; 18. Microcode; 19. Sequential examples; Part V. Practical Design: 20. Verification and test; Part VI. System Design: 21. System-level design; 22. Interface and system-level timing; 23. Pipelines; 24. Interconnect; 25. Memory systems; Part VII. Asynchronous Logic: 26. Asynchronous sequential circuits; 27. Flip-flops; 28. Metastability and synchronization failure; 29. Synchronizer design; Appendix A. Verilog coding style; References; Index of Verilog modules; Subject index.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisSome of our earliest experiences of the conclusive force of an argument come from school mathematics: faced with a mathematical proof, we cannot deny the conclusion once the premises have been accepted. Behind such arguments lies a more general pattern of 'demonstrative arguments' that is studied in the science of logic. Logical reasoning is applied at all levels, from everyday life to advanced sciences, and a remarkable level of complexity is achieved in everyday logical reasoning, even if the principles behind it remain intuitive. Jan von Plato provides an accessible but rigorous introduction to an important aspect of contemporary logic: its deductive machinery. He shows that when the forms of logical reasoning are analysed, it turns out that a limited set of first principles can represent any logical argument. His book will be valuable for students of logic, mathematics and computer science.Trade Review'Elements of Logical Reasoning fills a gap by providing some much needed explanation and motivation to an otherwise dry literature.' Henry Towsner, The Mathematical IntelligencerTable of ContentsPart I. First Steps in Logical Reasoning: 1. Starting points; 2. Rules of proof; 3. Natural deduction; 4. Proof search; 5. Classical natural deduction; 6. Proof search in classical logic; 7. The semantics of propositional logic; Part II. Logical Reasoning with the Quantifiers: 8. The quantifiers; 9. Derivations in predicate logic; 10. The semantics of predicate logic; Part III. Beyond Pure Logic: 11. Equality and axiomatic theories; 12. Elements of the proof theory of arithmetic; Part IV. Complementary Topics: 13. Normalization and cut elimination; 14. Deductive machinery from Aristotle to Heyting.

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Book SynopsisThis book presents mathematical logic from the syntactic point of view, with an emphasis on aspects that are fundamental to computer science. It is an excellent introduction for graduate students and advanced undergraduates interested in logic in mathematics, computer science, and philosophy, and an invaluable reference for professional logicians.Trade Review'Avigad provides a much needed introduction to mathematical logic that foregrounds the role of syntax and computability in our understanding of consistency and inconsistency. The result provides a jumping off point to any of the fields of modern logic, not only teaching the technical groundwork, but also providing a window into how to think like a logician.' Henry Towsner, University of Pennsylvania'This book by one of the most knowledgeable researchers in the field covers a remarkably broad selection of material without sacrificing depth. Its clear organization and unified approach - focused on a syntactic approach and on the role of computation - make it suitable for a wide range of introductory logic sequences at the upper-level undergraduate and graduate level, as well as a valuable resource for background material in more advanced logic courses.' Denis Hirschfeldt, University of Chicago'… an excellent addition to the literature, with plenty more than enough divergences and side-steps from the more well-trodden paths through the material to be consistently interesting … this is most certainly a book to make sure your library gets.' Peter Smith, Logic MattersTable of ContentsPreface; 1. Fundamentals; 2. Propositional Logic; 3. Semantics of Propositional Logic; 4. First-Order Logic; 5. Semantics of First-Order Logic; 6. Cut Elimination; 7. Properties of First-Order Logic; 8. Primitive Recursion; 9. Primitive Recursive Arithmetic; 10. First-Order Arithmetic; 11. Computability 12. Undecidability and Incompleteness; 13. Finite Types; 14. Arithmetic and Computation; 15. Second-Order Logic and Arithmetic; 16. Subsystems of Second-Order Arithmetic; 17. Foundations; Appendix; References; Notation; Index.

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How can we provide guarantees of behaviours for autonomous systems such as driverless cars? This tutorial text, for professionals, researchers and graduate students, explains how autonomous systems, from intelligent robots to driverless cars, can be programmed in ways that make them amenable to formal verification. The authors review specific definitions, applications and the unique future potential of autonomous systems, along with their impact on safer decisions and ethical behaviour. Topics discussed include the use of rational cognitive agent programming from the Beliefs-Desires-Intentions paradigm to control autonomous systems and the role model-checking in verifying the properties of this decision-making component. Several case studies concerning both the verification of autonomous systems and extensions to the framework beyond the model-checking of agent decision-makers are included, along with complete tutorials for the use of the freely-available verifiable cognitive agent too

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Book SynopsisThe dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure.Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast how size scaling drives performance; Implicit parallelism how a sequential program can be executed faster with parallelism; Dynamic locality skirting physical limits, by arranging data in a smaller space; Parallelism increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators tTrade Review'Andrew Chien's Computer Architecture for Scientists: Principles and Practice is a timely and much-needed treatment of how computer architecture impacts the scalability and performance of the computing systems and the data-driven processes that operate at the upper levels of the software stack. Aimed at software engineers and data scientists, this book provides a holistic and principled coverage of technology-agnostic concepts that govern the interplay between hardware capabilities and software performance. Understanding this interplay is crucial as it allows practitioners not only to reason about the performance of the systems they develop, but in fact to design these systems in a way that leverages the architectural features of the hardware systems on which they are built.' Azer Bestavros, Associate Provost for Computing and Data Sciences, Boston University'This is a very timely book on computer architecture aimed at the new generation of computational scientists and data scientists. The end of Dennard Scaling, coupled with the breakthrough of Deep Neural Networks in Machine Learning, has led to the need for a radical re-think in the teaching of computer architecture. Andrew Chien's book addresses this need and gives scientific software developers a high-level understanding of the emerging computer architectures and the design principles they require to obtain maximum computer performance from their programs.' Tony Hey, Chief Data Scientist, Rutherford Appleton Lab, U.K.'Hurray for Computer Architecture for Scientists! Finally, a book aimed squarely at the rising complexities at the intersection of Moore's Law scaling of technology and the dizzying array of diverse computer architectures that have resulted. General versus special-purpose, programmable versus configurable, and a growing basket of colors and flavors of parallelism. While these make sense to working computer architects and chip designers – what of scientists and engineers just trying to get stuff done? Chien does a splendid job of translating and demystifying why and how computer architectures matter, how users can understand them, and use these insights to wrestle them into submission to do good science.' Rob A. Rutenbar, Distinguished Professor of Computer Science and Electrical and Computer Engineering, University of Pittsburgh'Andrew Chien's book connects the dots from interdependent architectural choices to underlying calculus of performance and in the process strikes a balance between high-level view of the machine and its realizations. It is essential that users of these tools have an intimate understanding of the principles and mechanisms that make computing machines deliver efficient and high performance without becoming hardware designers themselves. The book provides such insights through its succinctly stated principles that both educate and enlighten about fundamental abstractions in computing.' Rajesh Gupta, Professor of Computer Science and Engineering, University of California, San DiegoTable of ContentsPreface; 1. Computing and the transformation of society; 2. Instruction sets, software, and instruction execution; 3. Processors: small is fast and scaling; 4. Sequential abstraction, but parallel implementation; 5. Memories: exploiting dynamic locality; 6. The general-purpose computer; 7. Beyond sequential: parallelism in multi-core and the Cloud; 8. Accelerators: customized architectures for performance; 9. Computing performance: past, present, and future; References, Index.

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Book SynopsisModel-based development methods, and supporting technologies, can provide the techniques and tools needed to address the dilemma between reducing system development costs and time, and developing increasingly complex systems. This book provides the information needed to understand and apply model-drive engineering (MDE) and model-drive architecture (MDA) approaches to the development of embedded systems. Chapters, written by experts from academia and industry, cover topics relating to MDE practices and methods, as well as emerging MDE technologies. Much of the writing is based on the presentations given at the Summer School “MDE for Embedded Systems” held at Brest, France, in September 2004.Table of ContentsChapter Summary xi Chapter 1. Model Transformation: A Survey of the State of the Art 1 Tom MENS 1.1. Model-driven engineering 1 1.2. Model transformation 2 1.3. Model transformation languages 5 1.4. Model transformation activities 8 1.5. Conclusion 14 1.6. Acknowledgements 14 1.7. Bibliography 15 Chapter 2. Model-Based Code Generation 21 Chris RAISTRICK 2.1. Introduction 21 2.2. The model-driven architecture (MDA) process 22 2.3. The automated approach to code generation 23 2.4. Domain modeling 25 2.5. The executable UML (xUML) formalism 29 2.6. System generation 31 2.7. Executable UML to code mappings 34 2.8. Conclusions 41 2.9. Bibliography 42 Chapter 3. Testing Model Transformations: A Case for Test Generation from Input Domain Models 43 Benoit BAUDRY 3.1. Introduction 43 3.2. Challenges for testing systems with large input domains 46 3.3. Selecting test data in large domains 52 3.4. Metamodel-based test input generation 58 3.5. Conclusion 67 3.6. Acknowledgements 68 3.7. Bibliography 68 Chapter 4. Symbolic Execution-Based Techniques for Conformance Testing 73 Christophe GASTON, Pascale LE GALL, Nicolas RAPIN and Assia TOUIL 4.1. Context 73 4.2. Input output symbolic transition systems 79 4.3. Symbolic execution 84 4.4. Conformance testing for IOSTS 87 4.5. Concluding remarks 96 4.6. Bibliography 101 Chapter 5. Using MARTE and SysML for Modeling Real-Time Embedded Systems 105 Huascar ESPINOZA, Daniela CANCILA, Sébastien GÉRARD and Bran SELIC 5.1. Introduction 105 5.2. Background 108 5.3. Scenarios of combined usage 113 5.4. Combination Strategies 125 5.5. Related work 130 5.6. Conclusion 133 5.7. Acknowledgements 134 5.8. Bibliography 134 Chapter 6. Software Model-based Performance Analysis 139 Dorina C. PETRIU 6.1. Introduction 139 6.2. Performance models 142 6.3. Software model with performance annotations 148 6.4. Mapping from software to performance model 155 6.5. Using a pivot language: Core Scenario Model (CSM) 158 6.6. Case study performance model 160 6.7. Conclusions 162 6.8. Acknowledgements 163 6.9. Bibliography 163 Chapter 7. Model Integration for Formal Qualification of Timing-Aware Software Data Acquisition Components 167 Jean-Philippe BABAU, Philippe DHAUSSY and Pierre-Yves PILLAIN 7.1. Introduction 167 7.2. System modeling 170 7.3. Variation points modeling 182 7.4. Experiments and results 189 7.5. Conclusion 194 7.6. Bibliography 195 Chapter 8. SoC/SoPC Development using MDD and MARTE Profile 201 Denis AULAGNIER, Ali KOUDRI, Stéphane LECOMTE, Philippe SOULARD, Joël CHAMPEAU, Jorgiano VIDAL, Gilles PERROUIN and Pierre LERAY 8.1. Introduction 201 8.2. Related works 203 8.3. MOPCOM process and models 206 8.4. Application 210 8.5. System analysis 211 8.6. Abstract modeling level 214 8.7. Execution modeling level 216 8.8. Detailed modeling level 220 8.9. Tooling Support 223 8.10. HDL Code Generation 225 8.11. Conclusion 228 8.12. Acknowledgements 229 8.13. Bibliography 229 List of Authors 233 Index 237

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Book SynopsisIt is currently quite easy for students or designers/engineers to find very general books on the various aspects of safety, reliability and dependability of computer system architectures, and partial treatments of the elements that comprise an effective system architecture. It is not so easy to find a single source reference for all these aspects of system design. However, the purpose of this book is to present, in a single volume, a full description of all the constraints (including legal contexts around performance, reliability norms, etc.) and examples of architectures from various fields of application, including: railways, aeronautics, space, automobile and industrial automation. The content of the book is drawn from the experience of numerous people who are deeply immersed in the design and delivery (from conception to test and validation), safety (analysis of safety: FMEA, HA, etc.) and evaluation of critical systems. The involvement of real world industrial applications is handled in such as a way as to avoid problems of confidentiality, and thus allows for the inclusion of new, useful information (photos, architecture plans/schematics, real examples).Trade Review"The text is clearly written, well-illustrated, and includes a helpful glossary." (Booknews, 1 February 2011)Table of ContentsIntroduction xiii Chapter 1. Principles 1 Jean-Louis BOULANGER 1.1. Introduction 1 1.2. Presentation of the basic concepts: faults, errors and failures 1 1.3. Safe and/or available architecture 7 1.4. Resetting a processing unit 7 1.5. Overview of safety techniques 8 1.6. Conclusion 45 1.7. Bibliography 45 Chapter 2. Railway Safety Architecture 47 Jean-Louis BOULANGER 2.1. Introduction 47 2.2. Coded secure processor 47 2.3. Other applications 53 2.4. Regulatory and normative context 60 2.5. Conclusion 66 2.6. Bibliography 66 Chapter 3. From the Coded Uniprocessor to 2oo3 69 Gilles LEGOFF and Christophe GIRARD 3.1. Introduction 69 3.2. From the uniprocessor to the dual processor with voter 71 3.3. CSD: available safety computer 80 3.4. DIVA evolutions 93 3.5. New needs and possible solutions 99 3.6. Conclusion 101 3.7. Assessment of installations 102 3.8. Bibliography 103 Chapter 4. Designing a Computerized Interlocking Module: a Key Component of Computer-Based Signal Boxes Designed by the SNCF 105 Marc ANTONI 4.1. Introduction 105 4.2. Issues 107 4.3. Railway safety: fundamental notions 116 4.4. Development of the computerized interlocking module 124 4.5. Conclusion 145 4.6. Bibliography 147 Chapter 5. Command Control of Railway Signaling Safety: Safety at Lower Cost 149 Daniel DRAGO 5.1. Introduction 149 5.2. A safety coffee machine 149 5.3. History of the PIPC 150 5.4. The concept basis 155 5.5. Postulates for safety requirements 157 5.6. Description of the PIPC architecture7 159 5.7. Description of availability principles 173 5.8. Software architecture 176 5.9. Protection against causes of common failure 186 5.10. Probabilistic modeling 188 5.11. Summary of safety concepts 194 5.12. Conclusion 197 5.13. Bibliography 198 Chapter 6. Dependable Avionics Architectures: Example of a Fly-by-Wire system 199 Pascal TRAVERSE, Christine BEZARD, Jean-Michel CAMUS, Isabelle LACAZE, Hervé LEBERRE, Patrick RINGEARD and Jean SOUYRIS 6.1. Introduction 199 6.2. System breakdowns due to physical failures 205 6.3. Manufacturing and design errors 215 6.4. Specific risks 223 6.5. Human factors in the development of flight controls 225 6.6. Conclusion 229 6.7. Bibliography 229 Chapter 7. Space Applications 233 Jean-Paul BLANQUART and Philippe MIRAMONT 7.1. Introduction 233 7.2. Space system 233 7.3. Context and statutory obligation 237 7.4. Specific needs 243 7.5. Launchers: the Ariane 5 example 252 7.6. Satellite architecture 281 7.7. Orbital transport: ATV example 292 7.8. Summary and conclusions 302 7.9. Bibliography 304 Chapter 8. Methods and Calculations Relative to “Safety Instrumented Systems” at TOTAL 307 Yassine CHAABI and Jean-Pierre SIGNORET 8.1. Introduction 307 8.2. Specific problems to be taken into account 308 8.3. Example 1: system in 2/3 modeled by fault trees 322 8.4. Example 2: 2/3 system modeled by the stochastic Petri net 328 8.5. Other considerations regarding HIPS 333 8.6. Conclusion 342 8.7. Bibliography 343 Chapter 9. Securing Automobile Architectures 345 David LIAIGRE 9.1. Context 345 9.2. More environmentally-friendly vehicles involving more embedded electronics 347 9.3. Mastering the complexity of electronic systems 348 9.4. Security concepts in the automotive field 350 9.5. Which security concepts for which security levels of the ISO 26262 standard? 364 9.6. Conclusion 376 9.7. Bibliography 377 Chapter 10. SIS in Industry 379 Grégory BUCHHEIT and Olaf MALASSE 10.1. Introduction 379 10.2. Safety loop structure 384 10.3. Constraints and requirements of the application 407 10.4. Analysis of a safety loop 413 10.5. Conclusion 423 10.6. Bibliography 424 Chapter 11. A High-Availability Safety Computer 425 Sylvain BARO 11.1. Introduction 425 11.2. Safety computer 426 11.3. Applicative redundancy 433 11.4. Integrated redundancy 433 11.5. Conclusion 443 11.6. Bibliography 446 Chapter 12. Safety System for the Protection of Personnel in the CERN Large Hadron Collider 447 Pierre NININ, Silvia GRAU, Tomasz LADZINSKI and Francesco VALENTINI 12.1. Introduction 447 12.2. LACS 450 12.3. LASS 452 12.4. Functional safety methodology 459 12.5. Test strategy 466 12.6. Feedback 472 12.7. Conclusions 473 12.8. Bibliography 474 Glossary 477 List of Authors 485 Index 487

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