World Scientific Series In Computer Science – serie

Pictorial representations are very useful for humans to understand complicated relations or structures. This is the reason that the user interface of information systems is strongly required to visualize many kinds of information in a wide variety of graphical forms. At present, however, only some very specialized visualization techniques have been developed probably because the generality in the visualization has not been appreciated correctly. This book presents a visualization framework for translating abstract objects and relations, typically represented in textual forms, into pictorial representations, and describes a general visualization interface based on this framework. In the framework, abstract objects and relations are mapped to graphical objects and relations by user-defined mapping rules. The declarative nature of the mapping rules provides users with more global and more flexible layout capabilities. Also presented is an algorithm for drawing general undirected graphs which can be used to visualize network structures as network diagrams. The proposed visualization framework is shown to be general enough to be applied to various types of visualization problems, such as the visualization of semantics of natural language sentences, the generation of diagrams for data structures and program structures, and the drawing of database schema. Examples of all these problems are shown with actual mapping rules and pictorial results.

The research and development of multi-dimensional pattern recognition, scene analysis, computer vision and image processing have progressed very rapidly in recent years. Among various models employed for pattern representation and analysis, the array grammar has attracted more and more attention because it has several advantages over others.This special volume, perhaps the first time ever in the literature, is a collection of 14 papers by prominent professionals and experts, aimed at promoting array grammars, patterns and recognizers. They are grouped in the following categories: (1) Array grammars and pattern generation, (2) Array pattern recognizers, (3) Coordinate grammars and L-systems, and (4) Hexagonal grids, tilings and encryption.

This book contains a selection of 14 papers presented at the workshop organised by the International Association for Pattern Recognition (IAPR) Technical Committee on Syntactical and Structural Pattern Recognition, at Pont-à-Mousson, 1988. These papers which have been expanded, focus on both fundamental aspects and applications. They show that structural methods are a good framework for integrating both symbolic and numerical knowledge for modeling, recognition and also learning. The applications described are on document analysis, speech and image analysis.

This book focuses on object-oriented concurrent computing, which can be considered a model of concurrent programming, and proposes a new programming language, ConcurrentSmalltalk, which is based on object-oriented concurrent computing. The book also shows the efficiency of object-oriented concurrent computing through the design, implementation, and evaluation of ConcurrentSmalltalk. ConcurrentSmalltalk is designed to be upwardly compatible with Smalltalk-80. In the book, the ConcurrentSmalltalk object model is first proposed. Next, issues which arise from maintaining compatibility with Smalltalk-80 are discussed. Finally, the ConcurrentSmalltalk virtual machine which executes the ConcurrentSmalltalk programs is proposed.

This book describes a study on the question of what sort of innate knowledge it is that enables children to acquire a first language. The author, using a computational approach, builds a model, named BUD (Bring Up a Daughter), on the basis of the data linguists and psychologists have collected.BUD is based on the empirists, view of first language acquisition (as opposed to that of the nativists'), that children make a number of rules in acquiring a first language and that over generalizations can be found in the acquisition of every aspect of a language. Thus, BUD has no built-in procedure by which it computes the structures of a language. A detailed description of the BUD model and its workings answers the question on which the study is based.

This book contains in easily accessible form all the main ideas of the creator and principal architect of algorithmic information theory. This expanded second edition has added thirteen abstracts, a 1988 Scientific American Article, a transcript of a EUROPALIA 89 lecture, an essay on biology, and an extensive bibliography. Its new larger format makes it easier to read. Chaitin's ideas are a fundamental extension of those of Gödel and Turning and have exploded some basic assumptions of mathematics and thrown new light on the scientific method, epistemology, probability theory, and of course computer science and information theory.

This book contains in easily accessible form all the main ideas of the creator and principal architect of algorithmic information theory. This expanded second edition has added thirteen abstracts, a 1988 Scientific American Article, a transcript of a EUROPALIA 89 lecture, an essay on biology, and an extensive bibliography. Its new larger format makes it easier to read. Chaitin's ideas are a fundamental extension of those of Gödel and Turning and have exploded some basic assumptions of mathematics and thrown new light on the scientific method, epistemology, probability theory, and of course computer science and information theory.

The contents of this book are self-sufficient in the sense that no preliminary knowledge other than elementary set theory is needed and there are no complicated mathematical theorems in the book. A must for those entering the field.

This book considers computer vision to be an integral part of the artificial intelligence system. The core of the book is an analysis of possible approaches to the creation of artificial vision systems, which simulate human visual perception. Much attention is paid to the latest achievements in visual psychology and physiology, the description of the functional and structural organization of the human perception mechanism, the peculiarities of artistic perception and the expression of reality. Computer vision models based on these data are investigated. They include the processes of external data analysis, internal environmental model synthesis, and the generating of behavioristic responses based on external and internal models comparison. Computer vision system evolution resulting from environmental effects is also considered. A unique feature of this book is the authors' use of black and white, and colour prints of traditional and contemporary Russian art to illustrate their principal theses. In doing so, they introduce the reader to a particularly Russian view of the world.

This book considers computer vision to be an integral part of the artificial intelligence system. The core of the book is an analysis of possible approaches to the creation of artificial vision systems, which simulate human visual perception. Much attention is paid to the latest achievements in visual psychology and physiology, the description of the functional and structural organization of the human perception mechanism, the peculiarities of artistic perception and the expression of reality. Computer vision models based on these data are investigated. They include the processes of external data analysis, internal environmental model synthesis, and the generating of behavioristic responses based on external and internal models comparison. Computer vision system evolution resulting from environmental effects is also considered. A unique feature of this book is the authors' use of black and white, and colour prints of traditional and contemporary Russian art to illustrate their principal theses. In doing so, they introduce the reader to a particularly Russian view of the world.

This book describes how model selection and statistical inference can be founded on the shortest code length for the observed data, called the stochastic complexity. This generalization of the algorithmic complexity not only offers an objective view of statistics, where no prejudiced assumptions of "true" data generating distributions are needed, but it also in one stroke leads to calculable expressions in a range of situations of practical interest and links very closely with mainstream statistical theory. The search for the smallest stochastic complexity extends the classical maximum likelihood technique to a new global one, in which models can be compared regardless of their numbers of parameters. The result is a natural and far reaching extension of the traditional theory of estimation, where the Fisher information is replaced by the stochastic complexity and the Cramer-Rao inequality by an extension of the Shannon-Kullback inequality. Ideas are illustrated with applications from parametric and non-parametric regression, density and spectrum estimation, time series, hypothesis testing, contingency tables, and data compression.

The research detailed in this book has been motivated by the search for a simple parallel digital optical architecture for image processing. The development of a simple unified consistent theory of parallel binary image processing is described and its implementation on digital optical processors is considered. Both theoretical and experimental work are included, and both algorithmic and architectural designs are covered. Also presented are the experimental results of the implementation of a prototype Digital Optical Cellular Image Processor (DOCIP) system used to demonstrate the concept of the DOCIP architecture.

This book is an essay on relevant problems of epistemology (the theory of knowledge) related to computer science. It draws a continuous line between the earliest scientific approaches of epistemology, starting with the Greek Classics and the recent practical and theoretical problems of computer modelling, and by that the appropriate application of computers to our present problems. Uncertainty, logic and language are the key issues of this road leading to some new aspects of cognitive psychology and unification of the different results for a modelling procedure. The book is not a textbook but a critical survey of usual and advertised methods with an evaluation of them from the point of view of their applicability, reliability and limits. Probability, Bayesian, Dempster-Shafer, fuzzy and other approaches are treated in this way in uncertainty, different worlds' concepts, non-monotonic logic and other methods and views in logic. The emphasis in linguistics is put on the meta concept, and in cognitive applications of the pattern concept.Written mostly in an entertaining style, this book provides a more palatable reading of a profound subject.

This book is an essay on relevant problems of epistemology (the theory of knowledge) related to computer science. It draws a continuous line between the earliest scientific approaches of epistemology, starting with the Greek Classics and the recent practical and theoretical problems of computer modelling, and by that the appropriate application of computers to our present problems. Uncertainty, logic and language are the key issues of this road leading to some new aspects of cognitive psychology and unification of the different results for a modelling procedure. The book is not a textbook but a critical survey of usual and advertised methods with an evaluation of them from the point of view of their applicability, reliability and limits. Probability, Bayesian, Dempster-Shafer, fuzzy and other approaches are treated in this way in uncertainty, different worlds' concepts, non-monotonic logic and other methods and views in logic. The emphasis in linguistics is put on the meta concept, and in cognitive applications of the pattern concept.Written mostly in an entertaining style, this book provides a more palatable reading of a profound subject.

This volume contains a well-balanced set of applications and theory papers in artificial intelligence advances. The applications papers each discuss a system that is (or is close to being) a fielded system that solves real problems using one or more AI techniques. They cover areas such as education, physics, energy, control, medicine and mechanical engineering.The theory papers, representing recent advances in various theoretical aspects of AI technology, concern themselves with “building block” issues, i.e. theories, algorithms, architectures, and software tools that can or will be used for modules within future systems. The topics covered are: clustering, natural language, adaptive algorithms, distributed processing, knowledge acquisition, and systems programming.

Learning and planning are two important topics of artificial intelligence. Learning deals with the algorithmic processes that make a computing machine able to “learn” and improve its performance during the process of complex tasks. Planning on the other hand, deals with decision and construction processes that make a machine capable of constructing an intelligent plan for the solution of a particular complex problem.This book combines both learning and planning methodologies and their applications in different domains. It is divided into two parts. The first part contains seven chapters on the ongoing research work in symbolic and connectionist learning. The second part includes seven chapters which provide the current research efforts in planning methodologies and their application to robotics.

This book contains 15 reviewed papers selected from among those presented at the 4th Vision Interface Conference in Halifax, Canada 14 - 18 May 1990. The papers are grouped into three sections which deal with parallel architectures and neural networks, algorithms for analysis and processing, and systems and applications.

This book provides a comprehensive yet concise coverage of the concepts and technology of database systems and their evolution into knowledge-bases. The traditional material on database systems at senior undergraduate level is covered. An understanding of concepts is emphasized avoiding extremes in formalism or detail.Rather than be restricted to a single example used over an entire book, a variety of examples are used. These enable the reader to understand the basic abstractions which underlie description of many practical situations.A major portion of the book concerns database system technology with focus on the relational model. Various topics are discussed in detail, preparing the ground for more advanced work.

This book provides a comprehensive yet concise coverage of the concepts and technology of database systems and their evolution into knowledge-bases. The traditional material on database systems at senior undergraduate level is covered. An understanding of concepts is emphasized avoiding extremes in formalism or detail.Rather than be restricted to a single example used over an entire book, a variety of examples are used. These enable the reader to understand the basic abstractions which underlie description of many practical situations.A major portion of the book concerns database system technology with focus on the relational model. Various topics are discussed in detail, preparing the ground for more advanced work.

Character and handwriting recognition by computers is attracting much attention particularly because of its potential for application in many areas such as office automation, bank check processing, recognition of postal addresses and ZIP Codes, signature verification, and document and text recognition.Over the past four decades, many methods have been proposed, developed and tested for computers to recognize characters, and they have been reported in a variety of publications. The present volume is a coherent and integrated publication containing papers which give new research results in this increasingly active field. It is a boon to researchers, scientists and engineers who need to keep abreast of new developments in character and handwriting methodologies and applications.

Twelve outstanding papers have been carefully selected from those presented at a series of symposia held at Kyoto University and the Advanced Software Technology and Mechatronics Research Institute of Kyoto during the years 1986 through 1990. Sponsored by the Research Institute of Mathematical Sciences of Kyoto University and ASTEM RI/Kyoto, the symposia covers the theoretical and practical aspects of programming languages and systems, programming styles and methodologies, design and analysis of algorithms, database systems and machine architectures. This volume fulfils in part the goal of the symposia to promote research activities in software, to encourage publication of recent works by Japanese researchers and to circulate these results to the worldwide academic community.

Parallel implementation of algorithms involves many difficult problems. In particular among them are round-off analysis, the way to convert sequential programs and algorithms into the parallel mode, the choice of appropriate or optimal computer architect and so on. To solve these problems, it is necessary to know very well the structure of algorithms. This book deal with the mathematical mechanism that permits us to investigate structures of both sequential and parallel algorithms. This mechanism allows us to recognize and explain the relations between different methods of constructing parallel algorithms, the methods of analysing round-off errors, the methods of optimizing memory traffic, the methods of working out the fastest implementation for a given parallel computer and other methods attending the joint investigation of algorithms and computers.

This book describes recent strategies and applications for extracting useful information from sensor data. For example, the methods presented by Roth and Levine are becoming widely accepted as the ‘best’ way to segment range images, and the neural network methods for Alpha-numeric character recognition, presented by K Yamada, are believed to be the best yet presented. An applied system to analyze the images of dental imprints presented by J Côté, et al. is one of several examples of image processing systems that have already been proven to be practical, and can serve as a model for the image processing system designer. Important aspects of the automation of processes are presented in a practical way which can provide immediate new capabilities in fields as diverse as biomedical image processing, document processing, industrial automation, understanding human perception, and the defence industries. The book is organized into sections describing Model Driven Feature Extraction, Data Driven Feature Extraction, Neural Networks, Model Building, and Applications.

This book contains articles on advanced topics in language architectures and programming environments. The chapters are written by distinctive leaders in their respective research fields. The original articles and reprints are enhanced by the editors' descriptions which are intended to guide the reader. The book will be of immense use to computer science students, computer system architects and designers, and designers of programming environments, requiring a deep and broad knowledge of these fields.

This volume brings together papers by experts in different areas of computer science, who have a common interest in the design and management of visual interfaces. Since cognitive science and metaphor analysis prove useful for understanding the basic mechanisms which allow visual interfaces to be easy to learn and use, these topics are also featured. Other areas focused on are: visual languages, visual database systems, intelligent agents for system interaction, graphical and pictorial communication tools, multimedia environments and specific technological developments.

In this mathematical autobiography, Gregory Chaitin presents a technical survey of his work and a nontechnical discussion of its significance. The volume is an essential companion to the earlier collection of Chaitin's papers Information, Randomness and Incompleteness, also published by World Scientific.The technical survey contains many new results, including a detailed discussion of LISP program size and new versions of Chaitin's most fundamental information-theoretic incompleteness theorems. The nontechnical part includes the lecture given by Chaitin in Gšdel's classroom at the University of Vienna, a transcript of a BBC TV interview, and articles from New Scientist, La Recherche, and the Mathematical Intelligencer.

This monograph is the first comprehensive study of the design, application, and implementation of Pandora, a new parallel logic programming language. Pandora combines stream and-parallelism with don't-know non-determinism in a unified and efficient manner. As a result, it provides a programming paradigm of non-deterministic concurrent communicating processes, which opens up interesting application areas that cannot conveniently be expressed in existing logic programming languages. The author describes the use of Pandora for constraint programming, solving resource allocation problems, heuristic search, and distributed discrete event simulation. The final chapters describe in detail the implementation of Pandora on single- as well as multi-processor architectures.The volume is aimed at the community of logic programming students and professionals, as well as researchers and professionals in artificial intelligence. It will also be of great interest to researchers in programming language design and parallel processing.

It is well recognized that knowledge acquisition is the critical bottleneck of knowledge engineering. This book presents three major approaches of current research in this field, namely the psychological approach, the artificial intelligence approach and the software engineering approach. Special attention is paid to the most recent advances in knowledge acquisition research, especially those made by Chinese computer scientists. A special chapter is devoted to its applications in other fields, e.g. language analysis, software engineering, computer-aided instruction, etc., which were done in China.

This book contains a selection of papers which were presented at the Vision Interface '92 Conference. It also includes several invited articles from prominent researchers in the field, suggesting future directions in Computer Vision.