Classical and Fuzzy Concepts in Mathematical Logic and Applications provides a broad, thorough coverage of the fundamentals of two-valued logic, multivalued logic, and fuzzy logic. Exploring the parallels between classical and fuzzy mathematical logic, the book examines the use of logic in computer science, addresses questions in automatic deduction, and describes efficient computer implementation of proof techniques. Specific issues discussed include: oPropositional and predicate logic oLogic networks oLogic programming oProof of correctness oSemantics oSyntax oCompletenesss oNon-contradiction oTheorems of Herbrand and Kalman The authors consider that the teaching of logic for computer science is biased by the absence of motivations, comments, relevant and convincing examples, graphic aids, and the use of color to distinguish language and metalanguage. Classical and Fuzzy Concepts in Mathematical Logic and Applications discusses how the presence of these facts trigger a stirring, decisive insight into the understanding process. This view shapes this work, reflecting the authors' subjective balance between the scientific and pedagogic components of the textbook. Usually, problems in logic lack relevance, creating a gap between classroom learning and applications to real-life problems. The book includes a variety of application-oriented problems at the end of almost every section, including programming problems in PROLOG III. With the possibility of carrying out proofs with PROLOG III and other software packages, readers will gain a first-hand experience and thus a deeper understanding of the idea of formal proof.

The fourth in the "Inside" series, this volume includes four theses completed under the editor's direction at the Institute for the Learning Sciences at Northwestern University. This series bridges the gap between Schank's books introducing (for a popular audience) the theories behind his work in artificial intelligence (AI) and the many articles and books written by Schank and other AI researchers for their colleagues and students. The series will be of interest to graduate students in AI and professionals in other academic fields who seek the retraining necessary to join the AI effort or to understand it at the professional level.
This volume elaborates the Case-Based Teaching Architecture. A central tenet of this architecture is the importance of acquiring cases, and being able to retrieve and use those cases to solve new problems. The theses address the problems of building case bases, indexing large amounts of data contained within those case bases, and retrieving information on a need-to-know basis. They also reflect the work of researchers at the Institute to design tools that enable software programs to be built more effectively and efficiently.

Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns. The aim is to facilitate the teaching of parallel programming by surveying some key algorithmic structures and programming models, together with an abstract representation of the underlying hardware. The presentation is friendly and informal. The content of the book is language neutral, using pseudocode that represents common programming language models. The first five chapters' present core concepts in parallel computing. SIMD, shared memory, and distributed memory machine models are covered, along with a brief discussion of what their execution models look like. The book also discusses decomposition as a fundamental activity in parallel algorithmic design, starting with a naive example, and continuing with a discussion of some key algorithmic structures. Important programming models are presented in depth, as well as important concepts of performance analysis, including work-depth analysis of task graphs, communication analysis of distributed memory algorithms, key performance metrics, and a discussion of barriers to obtaining good performance. The second part of the book presents three case studies that reinforce the concepts of the earlier chapters. One feature of these chapters is to contrast different solutions to the same problem, using select problems that aren't discussed frequently in parallel computing textbooks. They include the Single Source Shortest Path Problem, the Eikonal equation, and a classical computational geometry problem: computation of the two-dimensional convex hull. After presenting the problem and sequential algorithms, each chapter first discusses the sources of parallelism then

Addresses the major issues involved in computer design and architectures. Dealing primarily with theory, tools, and techniques as related to advanced computer systems, it provides tutorials and surveys and relates new important research results. Each chapter provides background information, describes and analyzes important work done in the field, and provides important direction to the reader on future work and further readings. The topics covered include hierarchical design schemes, parallel and distributed modeling and simulation, parallel simulation tools and techniques, theoretical models for formal and performance modeling, and performance evaluation techniques.

Contents:
Evolution of the endocrine system and mechanisms of hormone action; control of the endocrine system and the anterior pituitary gland; the posterior pituitary gland; the thyroid gland; the parathyroid gland and calcium homeostasis; the hormonal control of the gastrointestinal tract; the endocrine pancreas and the hormonal control of carbohydrate metabolism; the adrenal medulla; the adrenal cortex; the testes and the male reproductive system; the ovaries and the female reproductive system; the hormonal control of growth and development; answers to revision questions.

Digital Signal Processing Algorithms describes computational number theory and its applications to deriving fast algorithms for digital signal processing. It demonstrates the importance of computational number theory in the design of digital signal processing algorithms and clearly describes the nature and structure of the algorithms themselves. The book has two primary focuses: first, it establishes the properties of discrete-time sequence indices and their corresponding fast algorithms; and second, it investigates the properties of the discrete-time sequences and the corresponding fast algorithms for processing these sequences.
Digital Signal Processing Algorithms examines three of the most common computational tasks that occur in digital signal processing; namely, cyclic convolution, acyclic convolution, and discrete Fourier transformation. The application of number theory to deriving fast and efficient algorithms for these three and related computationally intensive tasks is clearly discussed and illustrated with examples.
Its comprehensive coverage of digital signal processing, computer arithmetic, and coding theory makes Digital Signal Processing Algorithms an excellent reference for practicing engineers. The authors' intent to demystify the abstract nature of number theory and the related algebra is evident throughout the text, providing clear and precise coverage of the quickly evolving field of digital signal processing.

Provides a readily accessible introduction to the analysis and design of digital circuits at a logic instead of electronics level. Second Edition features a new and improved arrangement of chapters, a balance of theoretical and practical implementation aspects and in-text examples in each chapter, 21 experiments using standard TTL type of ICs, updated end-of-chapter problems with answers to selected problems (answers provided in a Solutions Manual for Instructors only), and more.

This textbook serves as an introduction to fault-tolerance, intended for upper-division undergraduate students, graduate-level students and practicing engineers in need of an overview of the field. Readers will develop skills in modeling and evaluating fault-tolerant architectures in terms of reliability, availability and safety. They will gain a thorough understanding of fault tolerant computers, including both the theory of how to design and evaluate them and the practical knowledge of achieving fault-tolerance in electronic, communication and software systems. Coverage includes fault-tolerance techniques through hardware, software, information and time redundancy. The content is designed to be highly accessible, including numerous examples and exercises. Solutions and powerpoint slides are available for instructors.

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter covering the latest information from different perspectives. Divided into three parts, the book first lays the groundwork for understanding and simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and multiversion neural computing. The book concludes by examining various neural network applications, such as neuron-fuzzy control systems and image compression. This final part of the book also provides a case study involving oil spill detection. This book is invaluable for students and practitioners who have a basic understanding of neural computing yet want to broaden and deepen their knowledge of the field.

Based on a symposium honoring the extensive work of Allen Newell -- one of the founders of artificial intelligence, cognitive science, human-computer interaction, and the systematic study of computational architectures -- this volume demonstrates how unifying themes may be found in the diversity that characterizes current research on computers and cognition. The subject matter includes:
* an overview of cognitive and computer science by leading researchers in the field;
* a comprehensive description of Allen Newell's "Soar" -- a computational architecture he developed as a unified theory of cognition;
* commentary on how the Soar theory of cognition relates to important issues in cognitive and computer science;
* rigorous treatments of controversial issues in cognition -- methodology of cognitive science, hybrid approaches to machine learning, word-sense disambiguation in understanding material language, and the role of capability processing constraints in architectural theory;
* comprehensive and systematic methods for studying architectural evolution in both hardware and software;
* a thorough discussion of the use of analytic models in human computer interaction;
* extensive reviews of important experiments in the study of scientific discovery and deduction; and
* an updated analysis of the role of symbols in information processing by Herbert Simon.
Incorporating the research of top scientists inspired by Newell's work, this volume will be of strong interest to a large variety of scientific communities including psychologists, computational linguists, computer scientists and engineers, and interface designers. It will also be valuable to those who study the scientific process itself, as it chronicles the impact of Newell's approach to research, simultaneously delving into each scientific discipline and producing results that transcend the boundaries of those disciplines.

Microprocessors and Microcomputer-Based System Design, Second Edition, builds on the concepts of the first edition. It discusses the basics of microprocessors, various 32-bit microprocessors, the 8085 microprocessor, the fundamentals of peripheral interfacing, and Intel and Motorola microprocessors. This edition includes new topics such as floating-point arithmetic, Program Array Logic, and flash memories. It covers the popular Intel 80486/80960 and Motorola 68040 as well as the Pentium and PowerPC microprocessors. The final chapter presents system design concepts, applying the design principles covered in previous chapters to sample problems.

Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.

Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.

"The Encyclopedia of Microcomputers serves as the ideal companion reference to the popular Encyclopedia of Computer Science and Technology. Now in its 10th year of publication, this timely reference work details the broad spectrum of microcomputer technology, including microcomputer history; explains and illustrates the use of microcomputers throughout academe, business, government, and society in general; and assesses the future impact of this rapidly changing technology."

This book is the most comprehensive book you will find Autodesk Revit 2018 Architecture. Covering all of the 2D concepts, it uses both metric and imperial units to illustrate the myriad drawing and editing tools for this popular application. Use the companion files to set up drawing exercises and projects and see all of the book's figures in colour. Revit Architecture 2018 includes over 50 exercises or "mini-workshops," that complete small projects from concept through actual plotting. Solving all of the workshops will simulate the creation of three projects (architectural and mechanical) from beginning to end, without overlooking any of the basic commands and functions in Revit Architecture 2018.

This unique reference presents in-depth coverage of the latest methods and applications of digital image processing describing various computer architectures ideal for satisfying specific image processing demands.

This book gives a solution to the problem of constructing lightwave paths in free spaces by proposing the concept of a Self-Organized Lightwave Network (SOLNET). This concept enables us to form self-aligned coupling optical waveguides automatically. SOLNETs are fabricated by self-focusing of lightwaves in photosensitive media, in which the refractive index increases upon light beam exposure, to realize the following functions: 1) Optical solder: Self-aligned optical couplings between misaligned devices with different core sizes 2) Three-dimensional optical wiring 3) Targeting lightwaves onto specific objects SOLNETs are expected to reduce the efforts to implement lightwaves into electronic systems and allow us to create new architectures, thus reducing costs and energy dissipation and improving overall system performance. SOLNETs are also expected to be applied to a wide range of fields where lightwaves are utilized, for example, solar energy conversion systems and biomedical technologies, especially photo-assisted cancer therapies. Readers will systematically learn concepts and features of SOLNETs, SOLNET performance predicted by computer simulations, experimental demonstrations for the proof of concepts, and expected applications. They will also be prepared for future challenges of the applications. This book is intended to be read by scientists, engineers, and graduate students who study advanced optoelectronic systems such as optical interconnects within computers and optical networking systems, and those who produce new ideas or strategies on lightwave-related subjects.

"The Encyclopedia of Microcomputers serves as the ideal companion reference to the popular Encyclopedia of Computer Science and Technology. Now in its 10th year of publication, this timely reference work details the broad spectrum of microcomputer technology, including microcomputer history; explains and illustrates the use of microcomputers throughout academe, business, government, and society in general; and assesses the future impact of this rapidly changing technology."

Microprogrammed State Machine Design is a digital computer architecture text that builds systematically from basic concepts to complex state-machine design. It provides practical techniques and alternatives for designing solutions to data processing problems both in commerce and in research purposes. It offers an excellent introduction to the tools and elements of design used in microprogrammed state machines, and incoporates the necessary background in number systems, hardware building blocks, assemblers for use in preparing control programs, and tools and components for assemblers . The author conducts an in-depth examination of first- and second-level microprogrammed state machines. He promotes a top-down approach that examines algorithms mathematically to exploit the simplifications resulting from choosing the proper representation and application of algebraic manipulation. The steps involved in the cycle of design and simulation steps are demonstrated through an example of running a computer through a simulation. Other topics covered in Microprogrammed State Machine Design include a discussion of simulation methods, the development and use of assembler language processors, and comparisons among various hardware implementations, such as the Reduced Instruction Set Computer (RISC) and the Digital Signal Processor (DSP). As a text and guide, Microprogrammed State Machine Design will interest students in the computer sciences, computer architectects and engineers, systems programmers and analysts, and electrical engineers.

The book "Parallel Computing" deals with the topics of current interest in high performance computing, viz. pipeline and parallel processing architectures, and the whole book is based on treatment of these ideas. The present revised edition is updated with the addition of topics like processor performance and technology developments in chapter 1 and advanced pipeline processing on today's high performance processors in chapter 2. A new chapter on neurocomputing and two new sections on Branch prediction and scoreboard are the other major changes done to make the book more viable.

Modern Digital Design and Switching Theory is an important text that focuses on promoting an understanding of digital logic and the computer programs used in the minimization of logic expressions. Several computer approaches are explained at an elementary level, including the Quine-McCluskey method as applied to single and multiple output functions, the Shannon expansion approach to multilevel logic, the Directed Search Algorithm, and the method of Consensus. Chapters 9 and 10 offer an introduction to current research in field programmable devices and multilevel logic synthesis. Chapter 9 covers more advanced topics in programmed logic devices, including techniques for input decoding and Field-Programmable Gate Arrays (FPGAs). Chapter 10 includes a discussion of boolean division, kernels and factoring, boolean tree structures, rectangle covering, binary decision diagrams, and if-then-else operators. Computer algorithms covered in these two chapters include weak division, iterative weak division, and kernel extraction by tabular methods and by rectangle covering theory. Modern Digital Design and Switching Theory is an excellent textbook for electrical and computer engineering students, in addition to a worthwhile reference for professionals working with integrated circuits.

This volume reports new developments on work in the quantum flux parametron (QFP) project. It makes complete a series on Josephson supercomputers, which includes four earlier volumes, also published by World Scientific. QFP technology has great potential especially in the design of computer architecture. It is regarded as being able to go beyond the horizon of current technology, and is a leading direction for the advancement of computer technology in the next decade.

Hybrid architecture for intelligent systems is a new field of artificial intelligence concerned with the development of the next generation of intelligent systems. This volume is the first book to delineate current research interests in hybrid architectures for intelligent systems.
The book is divided into two parts. The first part is devoted to the theory, methodologies, and algorithms of intelligent hybrid systems. The second part examines current applications of intelligent hybrid systems in areas such as data analysis, pattern classification and recognition, intelligent robot control, medical diagnosis, architecture, wastewater treatment, and flexible manufacturing systems.
Hybrid Architectures for Intelligent Systems is an important reference for computer scientists and electrical engineers involved with artificial intelligence, neural networks, parallel processing, robotics, and systems architecture.

Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a solid introduction to current mainstream computer architecture, dominant parallel programming models, and useful optimization strategies for scientific HPC. From working in a scientific computing center, the authors gained a unique perspective on the requirements and attitudes of users as well as manufacturers of parallel computers. The text first introduces the architecture of modern cache-based microprocessors and discusses their inherent performance limitations, before describing general optimization strategies for serial code on cache-based architectures. It next covers shared- and distributed-memory parallel computer architectures and the most relevant network topologies. After discussing parallel computing on a theoretical level, the authors show how to avoid or ameliorate typical performance problems connected with OpenMP. They then present cache-coherent non-uniform memory access (ccNUMA) optimization techniques, examine distributed-memory parallel programming with message passing interface (MPI), and explain how to write efficient MPI code. The final chapter focuses on hybrid programming with MPI and OpenMP. Users of high performance computers often have no idea what factors limit time to solution and whether it makes sense to think about optimization at all. This book facilitates an intuitive understanding of performance limitations without relying on heavy computer science knowledge. It also prepares readers for studying more advanced literature. Read about the authors' recent honor: Informatics Europe Curriculum Best Practices Award for Parallelism and Concurrency.

BTEC National for IT Practitioners: Systems Units has been written specifically to cover the systems pathway of the BTEC National specifications. This book caters for one of the most popular pathways in the BTEC National specifications, bringing together all the key specialist units for students who have chosen the systems route, including the core units specific to this pathway that aren't covered in the core unit book. When used alongside its companions for the core units and business pathways, this series delivers the most accessible and usable student textbooks available for the BTEC National. Units covered: Unit 11 - Data Analysis and Design Unit 22 - Network Management Unit 13 - Human Computer Interaction Unit 28 - IT Technical Support Unit 16 - Maintaining Computer Systems Unit 29 - IT Systems Troubleshooting and Repair Written by an experienced tutor, each unit is illustrated with assessment activities, end-of-chapter questions, case studies and practical exercises. The result is a clear, straightforward textbook that encourages independent study and acts as a reference to various topics within the qualification.