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Description Logics are a family of knowledge representation languages that have been studied extensively in Artificial Intelligence over the last two decades. They are embodied in several knowledge-based systems and are used to develop various real-life applications. The Description Logic Handbook provides a thorough account of the subject, covering all aspects of research in this field, namely: theory, implementation, and applications. Its appeal will be broad, ranging from more theoretically-oriented readers, to those with more practically-oriented interests who need a sound and modern understanding of knowledge representation systems based on Description Logics. The chapters are written by some of the most prominent researchers in the field, introducing the basic technical material before taking the reader to the current state of the subject, and including comprehensive guides to the literature. In sum, the book will serve as a unique reference for the subject, and can also be used for self-study or in conjunction with Knowledge Representation and Artificial Intelligence courses.
Design and Use of Assistive Technology assesses major hurdles in the design and use of assistive technologies, while also providing guidelines and recommendations to improve these technologies. This volume takes an interdisciplinary approach to solving the major issues surrounding designing and using assistive technologies for the physically impaired by blending engineering, computer science and medicine. The most difficult problems in assistive technologies, such as privacy concerns in data gathering and analysis, inherent heterogeneity of the user population, knowledge transfer of novel technologies and incorporation of the user perspective into the design process are all addressed. The bo...
What Is Autonomic Computing Autonomic computing (AC) refers to the utilization of distributed computing resources that have self-management qualities. These resources can adjust to changes that are unpredictable while masking the fundamental complexity from users and operators. This endeavor, which was started by IBM in 2001, has as its ultimate goal the creation of computer systems that are capable of managing themselves, the overcoming of the constantly increasing complexity of managing computing systems, and the reduction of the barrier that complexity poses to further expansion. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Autonomic computing ...
Zusammenfassung: This book offers a comprehensive survey of shared-memory synchronization, with an emphasis on "systems-level" issues. It includes sufficient coverage of architectural details to understand correctness and performance on modern multicore machines, and sufficient coverage of higher-level issues to understand how synchronization is embedded in modern programming languages. The primary intended audience for this book is "systems programmers"--the authors of operating systems, library packages, language run-time systems, concurrent data structures, and server and utility programs. Much of the discussion should also be of interest to application programmers who want to make good use of the synchronization mechanisms available to them, and to computer architects who want to understand the ramifications of their design decisions on systems-level code
Constraint Satisfaction Problems (CSPs) are natural computational problems that appear in many areas of theoretical computer science. Exploring which CSPs are solvable in polynomial time and which are NP-hard reveals a surprising link with central questions in universal algebra. This monograph presents a self-contained introduction to the universal-algebraic approach to complexity classification, treating both finite and infinite-domain CSPs. It includes the required background from logic and combinatorics, particularly model theory and Ramsey theory, and explains the recently discovered link between Ramsey theory and topological dynamics and its implications for CSPs. The book will be of interest to graduate students and researchers in theoretical computer science and to mathematicians in logic, combinatorics, and dynamics who wish to learn about the applications of their work in complexity theory.
This innovative textbook presents the key foundational concepts for a one-semester undergraduate course in the theory of computation. It offers the most accessible and motivational course material available for undergraduate computer theory classes. Directed at undergraduates who may have difficulty understanding the relevance of the course to their future careers, the text helps make them more comfortable with the techniques required for the deeper study of computer science. The text motivates students by clarifying complex theory with many examples, exercises and detailed proofs.* This book is shorter and more accessible than the books now being used in core computer theory courses. * Theory of computing is a standard, required course in all computer science departments.
Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. Chapter 1 addresses compression architecture, and reviews and compares compression methods. Chapters 2 through 4 focus on lossless compression (where the decompressed image must be bit for bit identical to the original). Chapter 5, contributed by the editors, describes a lossless algorithm based on vector quantization with extensions to near lossless and possibly lossy compression for efficient browning and pure pixel classification. Chapter 6 deals with near lossless compression while. Chapter 7 considers lossy techniques constrained by almost perfect classification. Chapters 8 through 12 address lossy compression of hyperspectral imagery, where there is a tradeoff between compression achieved and the quality of the decompressed image. Chapter 13 examines artifacts that can arise from lossy compression.
This volume presents the proceedings of the 6th Portuguese Conference on Artificial Intelligence, EPIA '93, organized by the Portuguese Artificial Intelligence Association. Like the last two conferences in this series, it was run as an international event with strict requirements as to the quality of accepted submissions. Fifty-one submissions were receivedfrom 9 countries, the largest numbers coming from Portugal (18), Germany (10), and France (8). The volume contains 25 selected papers, together with 7 poster abstracts and one invited lecture: "Organizations as complex, dynamic design problems" by L. Gasser, I. Hulthage, B. Leverich, J. Lieb, and A. Majchrzak, all from the University of Southern California. The papersare grouped into parts on: distributed artificial intelligence, natural language processing, knowledge representation, logic programming, non-standard logics, automated reasoning, constraints, planning, and learning.
A global examination of what influences women's participation in computing and what can be done to fix the gender gap.
Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.