Creativity in Computing and DataFlow Supercomputing, the latest release in the Advances in Computers series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore topics in greater depth and breadth than journal articles typically allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

The demand is exploding for complete, integrated systems that sense, process, manipulate, and control complex entities such as sound, images, text, motion, and environmental conditions. These systems, from hand-held devices to automotive sub-systems to aerospace vehicles, employ electronics to manage and adapt to a world that is, predominantly, neither digital nor electronic.

To respond to this design challenge, the industry has developed and standardized VHDL-AMS, a unified design language for modeling digital, analog, mixed-signal, and mixed-technology systems. VHDL-AMS extends VHDL to bring the successful HDL modeling methodology of digital electronic systems design to these new design disciplines.

Gregory Peterson and Darrell Teegarden join best-selling author Peter Ashenden in teaching designers how to use VHDL-AMS to model these complex systems. This comprehensive tutorial and reference provides detailed descriptions of both the syntax and semantics of the language and of successful modeling techniques. It assumes no previous knowledge of VHDL, but instead teaches VHDL and VHDL-AMS in an integrated fashion, just as it would be used by designers of these complex, integrated systems.
* Explores the design of an electric-powered, unmanned aerial vehicle system (UAV) in five separate case studies to illustrate mixed-signal, mixed-technology, power systems, communication systems, and full system modeling.
* Includes a CD-ROM with code for all the examples and case studies in the book, an educational model library, a quick reference guide for VHDL-AMS, a syntax reference from Appendix E in the book, links to VHDL-AMS resources and Mentor Graphics SystemVision software, which provides a simulation and modeling environment with a schematic entry tool, a VHDL-AMS simulator, and a waveform viewing facility.

Building upon the success of best-sellers The Clean Coder and Clean Code, legendary software craftsman Robert C. "Uncle Bob" Martin shows how to bring greater professionalism and discipline to application architecture and design. As with his other books, Martin's Clean Architecture doesn't merely present multiple choices and options, and say "use your best judgment": it tells you what choices to make, and why those choices are critical to your success. Martin offers direct, no-nonsense answers to key architecture and design questions like: What are the best high level structures for different kinds of applications, including web, database, thick-client, console, and embedded apps? What are the core principles of software architecture? What is the role of the architect, and what is he/she really trying to achieve? What are the core principles of software design? How do designs and architectures go wrong, and what can you do about it? What are the disciplines and practices of professional architects and designers? Clean Architecture is essential reading for every software architect, systems analyst, system designer, and software manager -- and for any programmer who aspires to these roles or is impacted by their work.

A step-by-step guide to working with programs that exploit quantum computing principles with the help of IBM Quantum, Qiskit, and Python Key Features * Understand the difference between classical computers and quantum computers * Work with key quantum computational principles such as superposition and entanglement and see how they are leveraged on IBM Quantum systems * Run your own quantum experiments and applications by integrating with Qiskit and Python Book Description IBM Quantum Lab is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and on several real quantum computers. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum dashboard and Quantum Information Science Kit (Qiskit) SDK. You will get well versed with the IBM Quantum Composer interface as well as the IBM Quantum Lab. You will learn the differences between the various available quantum computers and simulators. Along the way, you'll learn some of the fundamental principles of quantum mechanics, quantum circuits, qubits, and the gates that are used to perform operations on each qubit. As you build on your knowledge, you'll understand the functionality of IBM Quantum and the developer-focused resources it offers to address key concerns like noise, decoherence, and affinity within a quantum system. You'll learn how to monitor and optimize your quantum circuits. Lastly, you'll look at the fundamental quantum algorithms and understand how they can be applied effectively. By the end of this quantum computing book, you'll know how to build quantum programs on your own and will have gained practical understanding of quantum computation skills that you can apply to your business. What you will learn * Get familiar with the contents and layout of IBM Quantum Lab * Create and visualize quantum circuits * Understand quantum gates and visualize how they operate on qubits using the IBM Quantum Composer * Save, import, and leverage existing circuits with the IBM Quantum Lab * Discover Qiskit and its latest modules for model, algorithm, and kernel developers * Get to grips with fundamental quantum algorithms such as Deutsch-Jozsa, Grover's algorithm, and Shor's algorithm Who This Book Is For This book is for Python developers who are looking to learn quantum computing from the ground up and put their knowledge to use in practical situations with the help of the IBM Quantum platform and Qiskit. Some background in computer science and high-school-level physics and math is required.

A complete and authoritative discussion of systems engineering and neural networks In Systems Engineering Neural Networks, a team of distinguished researchers deliver a thorough exploration of the fundamental concepts underpinning the creation and improvement of neural networks with a systems engineering mindset. In the book, you'll find a general theoretical discussion of both systems engineering and neural networks accompanied by coverage of relevant and specific topics, from deep learning fundamentals to sport business applications. Readers will discover in-depth examples derived from many years of engineering experience, a comprehensive glossary with links to further reading, and supplementary online content. The authors have also included a variety of applications programmed in both Python 3 and Microsoft Excel. The book provides: A thorough introduction to neural networks, introduced as key element of complex systems Practical discussions of systems engineering and forecasting, complexity theory and optimization and how these techniques can be used to support applications outside of the traditional AI domains Comprehensive explorations of input and output, hidden layers, and bias in neural networks, as well as activation functions, cost functions, and back-propagation Guidelines for software development incorporating neural networks with a systems engineering methodology Perfect for students and professionals eager to incorporate machine learning techniques into their products and processes, Systems Engineering Neural Networks will also earn a place in the libraries of managers and researchers working in areas involving neural networks.

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning.

Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection.

Shape grammar and space syntax have been separately developed but rarely combined in any significant way. The first of these is typically used to investigate or generate the formal or geometric properties of architecture, while the second is used to analyze the spatial, topological, or social properties of architecture. Despite the reciprocal relationship between form and space in architecture-it is difficult to conceptualize a completed building without a sense of both of these properties-the two major computational theories have been largely developed and applied in isolation from each another. Grammatical and Syntactical Approaches in Architecture: Emerging Research and Opportunities is a critical scholarly resource that explores the relationship between shape grammar and space syntax for urban planning and architecture and enables the creative discovery of both the formal and spatial features of an architectural style or type. This book, furthermore, presents a new method to selectively capture aspects of both the grammar and syntax of architecture. Featuring a range of topics such as mathematical analysis, spatial configuration, and domestic architecture, this book is essential for architects, policymakers, urban planners, researchers, academicians, and students.

Edsger Wybe Dijkstra (1930-2002) was one of the most influential researchers in the history of computer science, making fundamental contributions to both the theory and practice of computing. Early in his career, he proposed the single-source shortest path algorithm, now commonly referred to as Dijkstra's algorithm. He wrote (with Jaap Zonneveld) the first ALGOL 60 compiler, and designed and implemented with his colleagues the influential THE operating system. Dijkstra invented the field of concurrent algorithms, with concepts such as mutual exclusion, deadlock detection, and synchronization. A prolific writer and forceful proponent of the concept of structured programming, he convincingly argued against the use of the Go To statement. In 1972 he was awarded the ACM Turing Award for "fundamental contributions to programming as a high, intellectual challenge; for eloquent insistence and practical demonstration that programs should be composed correctly, not just debugged into correctness; for illuminating perception of problems at the foundations of program design." Subsequently he invented the concept of self-stabilization relevant to fault-tolerant computing. He also devised an elegant language for nondeterministic programming and its weakest precondition semantics, featured in his influential 1976 book A Discipline of Programming in which he advocated the development of programs in concert with their correctness proofs. In the later stages of his life, he devoted much attention to the development and presentation of mathematical proofs, providing further support to his long-held view that the programming process should be viewed as a mathematical activity. In this unique new book, 31 computer scientists, including five recipients of the Turing Award, present and discuss Dijkstra's numerous contributions to computing science and assess their impact. Several authors knew Dijkstra as a friend, teacher, lecturer, or colleague. Their biographical essays and tributes provide a fascinating multi-author picture of Dijkstra, from the early days of his career up to the end of his life.

Distributed systems intertwine with our everyday lives. The benefits and current shortcomings of the underpinning technologies are experienced by a wide range of people and their smart devices. With the rise of large-scale IoT and similar distributed systems, cloud bursting technologies, and partial outsourcing solutions, private entities are encouraged to increase their efficiency and offer unparalleled availability and reliability to their users. Applying Integration Techniques and Methods in Distributed Systems is a critical scholarly publication that defines the current state of distributed systems, determines further goals, and presents architectures and service frameworks to achieve highly integrated distributed systems and presents solutions to integration and efficient management challenges faced by current and future distributed systems. Highlighting topics such as multimedia, programming languages, and smart environments, this book is ideal for system administrators, integrators, designers, developers, researchers, and academicians.

If you look around you will find that all computer systems, from your portable devices to the strongest supercomputers, are heterogeneous in nature. The most obvious heterogeneity is the existence of computing nodes of different capabilities (e.g. multicore, GPUs, FPGAs, ...). But there are also other heterogeneity factors that exist in computing systems, like the memory system components, interconnection, etc. The main reason for these different types of heterogeneity is to have good performance with power efficiency. Heterogeneous computing results in both challenges and opportunities. This book discusses both. It shows that we need to deal with these challenges at all levels of the computing stack: from algorithms all the way to process technology. We discuss the topic of heterogeneous computing from different angles: hardware challenges, current hardware state-of-the-art, software issues, how to make the best use of the current heterogeneous systems, and what lies ahead. The aim of this book is to introduce the big picture of heterogeneous computing. Whether you are a hardware designer or a software developer, you need to know how the pieces of the puzzle fit together. The main goal is to bring researchers and engineers to the forefront of the research frontier in the new era that started a few years ago and is expected to continue for decades. We believe that academics, researchers, practitioners, and students will benefit from this book and will be prepared to tackle the big wave of heterogeneous computing that is here to stay.

Within global commerce, services and management play a vital role in the economy. Service systems are necessary for organisations, and a multi-disciplinary approach is ideal to establish full understanding of these systems. Best Practices and New Perspectives in Service Science and Management provides original research on all aspects of service science, service management, service engineering, and its supporting technology in order to administer cutting-edge knowledge to encourage the improvement of services. This book is essential for researchers and practitioners in the fields of computer science, software management, and engineering.

As technology continues to advance in today's global market, practitioners are targeting systems with significant levels of applicability and variance. Instrumentation is a multidisciplinary subject that provides a wide range of usage in several professional fields, specifically engineering. Instrumentation plays a key role in numerous daily processes and has seen substantial advancement in recent years. It is of utmost importance for engineering professionals to understand the modern developments of instruments and how they affect everyday life. Advancements in Instrumentation and Control in Applied System Applications is a collection of innovative research on the methods and implementations of instrumentation in real-world practices including communication, transportation, and biomedical systems. While highlighting topics including smart sensor design, medical image processing, and atrial fibrillation, this book is ideally designed for researchers, software engineers, technologists, developers, scientists, designers, IT professionals, academicians, and post-graduate students seeking current research on recent developments within instrumentation systems and their applicability in daily life.

Recent years have witnessed the rise of analysis of real-world massive and complex phenomena in graphs; to efficiently solve these large-scale graph problems, it is necessary to exploit high performance computing (HPC), which accelerates the innovation process for discovery and invention of new products and procedures in network science. Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities is a critical scholarly resource that examines trends, challenges, and collaborative processes in emerging fields within complex network analysis. Featuring coverage on a broad range of topics such as high-performance computing, big data, network science, and accelerated network traversal, this book is geared towards data analysts, researchers, students in information communication technology (ICT), program developers, and academics.

Though traditionally information systems have been centralized, these systems are now distributed over the web. This requires a re-investigation into the way information systems are modeled and designed. Because of this new function, critical problems, including security, never-fail systems, and quality of service have begun to emerge. Novel Approaches to Information Systems Design is an essential publication that explores the most recent, cutting-edge research in information systems and exposes the reader to emerging but relatively mature models and techniques in the area. Highlighting a wide range of topics such as big data, business intelligence, and energy efficiency, this publication is ideally designed for managers, administrators, system developers, information system engineers, researchers, academicians, and graduate-level students seeking coverage on critical components of information systems.

The Physics of Computing gives a foundational view of the physical principles underlying computers. Performance, power, thermal behavior, and reliability are all harder and harder to achieve as transistors shrink to nanometer scales. This book describes the physics of computing at all levels of abstraction from single gates to complete computer systems. It can be used as a course for juniors or seniors in computer engineering and electrical engineering, and can also be used to teach students in other scientific disciplines important concepts in computing. For electrical engineering, the book provides the fundamentals of computing that link core concepts to computing. For computer science, it provides foundations of key challenges such as power consumption, performance, and thermal. The book can also be used as a technical reference by professionals.

With the continual development of professional industries in today's modernized world, certain technologies have become increasingly applicable. Cyber-physical systems, specifically, are a mechanism that has seen rapid implementation across numerous fields. This is a technology that is constantly evolving, so specialists need a handbook of research that keeps pace with the advancements and methodologies of these devices. Tools and Technologies for the Development of Cyber-Physical Systems is an essential reference source that discusses recent advancements of cyber-physical systems and its application within the health, information, and computer science industries. Featuring research on topics such as autonomous agents, power supply methods, and software assessment, this book is ideally designed for data scientists, technology developers, medical practitioners, computer engineers, researchers, academicians, and students seeking coverage on the development and various applications of cyber-physical systems.

Present day sophisticated, adaptive, and autonomous (to a certain degree) robotic technology is a radically new stimulus for the cognitive system of the human learner from the earliest to the oldest age. It deserves extensive, thorough, and systematic research based on novel frameworks for analysis, modelling, synthesis, and implementation of CPSs for social applications. Cyber-Physical Systems for Social Applications is a critical scholarly book that examines the latest empirical findings for designing cyber-physical systems for social applications and aims at forwarding the symbolic human-robot perspective in areas that include education, social communication, entertainment, and artistic performance. Highlighting topics such as evolinguistics, human-robot interaction, and neuroinformatics, this book is ideally designed for social network developers, cognitive scientists, education science experts, evolutionary linguists, researchers, and academicians.

In recent years, most applications deal with constraint decision-making systems as problems are based on imprecise information and parameters. It is difficult to understand the nature of data based on applications and it requires a specific model for understanding the nature of the system. Further research on constraint decision-making systems in engineering is required. Constraint Decision-Making Systems in Engineering derives and explores several types of constraint decisions in engineering and focuses on new and innovative conclusions based on problems, robust and efficient systems, and linear and non-linear applications. Covering topics such as fault detection, data mining techniques, and knowledge-based management, this premier reference source is an essential resource for engineers, managers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.