Despite the ample number of articles on parallel-vector computational algorithms published over the last 20 years, there is a lack of texts in the field customized for senior undergraduate and graduate engineering research. Parallel-Vector Equation Solvers for Finite Element Engineering Applications aims to fill this gap, detailing both the theoretical development and important implementations of equation-solution algorithms. The mathematical background necessary to understand their inception balances well with descriptions of their practical uses. Illustrated with a number of state-of-the-art FORTRAN codes developed as examples for the book, Dr. Nguyen's text is a perfect choice for instructors and researchers alike.

Deals with the most basic notion of linear algebra, to bring emphasis on approaches to the topic serving at the elementary level and more broadly.

This is a book about computation, something which is ubiquitous in the modern world. More precisely, it examines computability theory and computational complexity theory. Computability theory is the part of mathematics and computer science which seeks to clarify what we mean by computation or algorithm. When is there a computational solution possible to some question? How can we show that none is possible? How computationally hard is the question we are concerned with? Arguably, this area lead to the development of digital computers. (Computational) complexity theory is an intellectual heir of computability theory. Complexity theory is concerned with understanding what resources are needed for computation, where typically we would measure the resources in terms of time and space. Can we perform some task in a feasible number of steps? Can we perform some algorithm with only a limited memory? Does randomness help? Are there standard approaches to overcoming computational difficulty?

This Festschrift volume contains the proceedings of the conference Mathematical Methods in Computer Science, MMICS 2008, which was held during December 17-19, 2008, in Karlsruhe, Germany, in memory of Thomas Beth. The themes of the conference reflected the many interests of Thomas Beth. Although, these interests might seem diverse, mathematical methods and especially algebra as a language constituted the common denominator of all of his scientific achievements.

This book is an evolution from my book A First Course in Information Theory published in 2002 when network coding was still at its infancy. The last few years have witnessed the rapid development of network coding into a research ?eld of its own in information science. With its root in infor- tion theory, network coding has not only brought about a paradigm shift in network communications at large, but also had signi?cant in?uence on such speci?c research ?elds as coding theory, networking, switching, wireless c- munications,distributeddatastorage,cryptography,andoptimizationtheory. While new applications of network coding keep emerging, the fundamental - sults that lay the foundation of the subject are more or less mature. One of the main goals of this book therefore is to present these results in a unifying and coherent manner. While the previous book focused only on information theory for discrete random variables, the current book contains two new chapters on information theory for continuous random variables, namely the chapter on di?erential entropy and the chapter on continuous-valued channels. With these topics included, the book becomes more comprehensive and is more suitable to be used as a textbook for a course in an electrical engineering department.

The first edition of the monograph Information and Randomness: An Algorithmic Perspective by Crist ian Calude was published in 1994. In my Foreword I said: "The research in algorithmic information theory is already some 30 years old. However, only the recent years have witnessed a really vigorous growth in this area. . . . The present book by Calude fits very well in our series. Much original research is presented. . . making the approach richer in consequences than the classical one. Remarkably, however, the text is so self-contained and coherent that the book may also serve as a textbook. All proofs are given in the book and, thus, it is not necessary to consult other sources for classroom instruction. " The vigorous growth in the study of algorithmic information theory has continued during the past few years, which is clearly visible in the present second edition. Many new results, examples, exercises and open prob­ lems have been added. The additions include two entirely new chapters: "Computably Enumerable Random Reals" and "Randomness and Incom­ pleteness".

Informational Macrodynamics (IMD) presents the unified information systemic approach with common information language for modeling, analysis and optimization of a variety of interactive processes, such as physical, biological, economical, social, and informational, including human activities.

This book contains a selection of papers presented at the International Workshop Machine Learning, Meta-Reasoning and Logics held in Hotel de Mar in Sesimbra, Portugal, 15-17 February 1988. All the papers were edited afterwards. The Workshop encompassed several fields of Artificial Intelligence: Machine Learning, Belief Revision, Meta-Reasoning and Logics. The objective of this Workshop was not only to address the common issues in these areas, but also to examine how to elaborate cognitive architectures for systems capable of learning from experience, revising their beliefs and reasoning about what they know. Acknowledgements The editing of this book has been supported by COST-13 Project Machine Learning and Knowledge Acquisition funded by the Commission o/the European Communities which has covered a substantial part of the costs. Other sponsors who have supported this work were Junta Nacional de lnvestiga~ao Cientlfica (JNICT), lnstituto Nacional de lnvestiga~ao Cientlfica (INIC), Funda~ao Calouste Gulbenkian. I wish to express my gratitude to all these institutions. Finally my special thanks to Paula Pereira and AnaN ogueira for their help in preparing this volume. This work included retyping all the texts and preparing the camera-ready copy. Introduction 1 1. Meta-Reasoning and Machine Learning The first chapter is concerned with the role meta-reasoning plays in intelligent systems capable of learning. As we can see from the papers that appear in this chapter, there are basically two different schools of thought.

I am glad to see this new book on the e language and on verification. I am especially glad to see a description of the e Reuse Methodology (eRM). The main goal of verification is, after all, finding more bugs quicker using given resources, and verification reuse (module-to-system, old-system-to-new-system etc. ) is a key enabling component. This book offers a fresh approach in teaching the e hardware verification language within the context of coverage driven verification methodology. I hope it will help the reader und- stand the many important and interesting topics surrounding hardware verification. Yoav Hollander Founder and CTO, Verisity Inc. Preface This book provides a detailed coverage of the e hardware verification language (HVL), state of the art verification methodologies, and the use of e HVL as a facilitating verification tool in implementing a state of the art verification environment. It includes comprehensive descriptions of the new concepts introduced by the e language, e language syntax, and its as- ciated semantics. This book also describes the architectural views and requirements of verifi- tion environments (randomly generated environments, coverage driven verification environments, etc. ), verification blocks in the architectural views (i. e. generators, initiators, c- lectors, checkers, monitors, coverage definitions, etc. ) and their implementations using the e HVL. Moreover, the e Reuse Methodology (eRM), the motivation for defining such a gui- line, and step-by-step instructions for building an eRM compliant e Verification Component (eVC) are also discussed.

An invited collection of peer-reviewed papers surveying key areas of Roger Needham's distinguished research career at Cambridge University and Microsoft Research. From operating systems to distributed computing, many of the world's leading researchers provide insight into the latest concepts and theoretical insights–many of which are based upon Needham's pioneering research work. A critical collection of edited-survey research papers spanning the entire range of Roger Needham's distinguished scientific career, from operating systems to distributed computing and security. Many of the world's leading researchers survey their topics' latest developments and acknowledge the theoretical foundations of Needham's work. Introduction to book written by Rick Rashid, Director of Microsoft Research Worldwide.

Automatic Quantum Computer Programming provides an introduction to quantum computing for non-physicists, as well as an introduction to genetic programming for non-computer-scientists. The book explores several ways in which genetic programming can support automatic quantum computer programming and presents detailed descriptions of specific techniques, along with several examples of their human-competitive performance on specific problems. Source code for the author’s QGAME quantum computer simulator is included as an appendix, and pointers to additional online resources furnish the reader with an array of tools for automatic quantum computer programming.

Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math­ ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air­ line crew scheduling, corporate planning, computer-aided design and man­ ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory.

The aim of this text is to treat selected topics of the subject of contemporary cryptology, structured in five quite independent but related themes:

Cryptography in Chinese consists of two characters meaning "secret coded". Thanks to Ch'in Chiu-Shao and his successors, the Chinese Remainder Theorem became a cornerstone of public key cryptography. Today, as we observe the constant usage of high-speed computers interconnected via the Internet, we realize that cryptography and its related applications have developed far beyond "secret coding". China, which is rapidly developing in all areas of technology, is also writing a new page of history in cryptography. As more and more Chinese become recognized as leading researchers in a variety of topics in cryptography, it is not surprising that many of them are Professor Xiao's former students.

Konrad Zuse is one of the great pioneers of the computerage. He created thefirst fully automated, programcontrolled, freely programmable computer using binaryfloating-point calculation. It was operational in 1941. Hebuilt his first machines in Berlin during the Second WorldWar, with bombs falling all around, and after the war hebuilt up a company that was taken over by Siemens in 1967.Zuse was an inventor in the traditional style, full ofphantastic ideas, but also gifted with a powerful analyticalmind. Single-handedly, he developed one of the firstprogramming languages, the Plan Calculus, including featurescopied only decades later in other languages. He wrotenumerousbooks and articles and won many honors and awards.This is his autobiography, written in an engagingly livelyand pleasant style, full of anecdotes, reminiscences, andphilosophical asides. It traces his life from his childhoodin East Prussia, through tense wartime experiences and hardtimes building up his business after the war, to a ripe oldage andwell-earned celebrity.