SOFSEM 2004: Theory and Practice of Computer Science


Book Description

This book constitutes the refereed proceedings of the 30th Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2004, held in Merín, Czech Republic, in January 2004. The volume presents 10 invited lectures and 22 full papers selected from 136 submissions. Among the topics covered are computer science theory, programming theory, database systems, information systems, cognitive technologies and Web technologies.




SOFSEM 2004: Theory and Practice of Computer Science


Book Description

This book constitutes the refereed proceedings of the 30th Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2004, held in Mern, Czech Republic, in January 2004. The volume presents 10 invited lectures and 22 full papers selected from 136 submissions. Among the topics covered are computer science theory, programming theory, database systems, information systems, cognitive technologies and Web technologies.




The Wiley Handbook of Problem-Based Learning


Book Description

The first book to offer an in-depth exploration of the topic of problem-based learning with contributions from international experts The Wiley Handbook of Problem-Based Learning is the first book of its kind to present a collection of original essays that integrate the research and practice of problem-based learning in one comprehensive volume. With contributions from an international panel of leading scholars, researchers, practitioners and educational and training communities, the handbook is an authoritative, definitive, and contemporary volume that clearly demonstrates the impact and scope of research-based practice in problem-based learning (PBL). After many years of its successful implementation in medical education curricula, problem-based learning is now being emphasized and practiced more widely in K-12, higher education, and other professional fields. The handbook provides timely and stimulating advice and reflection on the theory, research, and practice of PBL. Throughout the book the contributors address the skills needed to implement PBL in the classroom and the need for creating learning environments that are active, collaborative, experiential, motivating and engaging. This important resource: Addresses the need for a comprehensive resource to problem-based learning research and implementation Contains contributions from an international panel of experts on the topic Offers a rich collection of scholarly writings that challenge readers to refresh their knowledge and rethink their assumptions Takes an inclusive approach that addresses the theory, design, and practice of problem-based learning Includes guidelines for instructional designers, and implementation and assessment strategies for practitioners Written for academics, students, and practitioners in education, The Wiley Handbook of Problem-Based Learning offers a key resource to the most recent information on the research and practice of problem-based learning.




Handbook of Knowledge Representation


Book Description

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily




Bayesian Networks


Book Description

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.




Research in Progress


Book Description




Probabilistic Similarity Networks


Book Description

In this remarkable blend of formal theory and practical application, David Heckerman develops methods for building normative expert systems—expert systems that encode knowledge in a decision-theoretic framework. Heckerman introduces the similarity network and partition, two extensions to the influence diagram representation. He uses the new representations to construct Pathfinder, a large, normative expert system for the diagnosis of lymph-node diseases. Heckerman shows that such expert systems can be built efficiently, and that the use of a normative theory as the framework for representing knowledge can dramatically improve the quality of expertise that is delivered to the user. He concludes with a formal evaluation of the power of his methods for building normative expert systems. David Heckerman is Assistant Professor of Computer Science at the University of Southern California. He received his doctoral degree in Medical Information Sciences from Stanford University. Contents: Introduction. Similarity Networks and Partitions: A Simple Example. Theory of Similarity Networks. Pathfinder: A Case Study. An Evaluation of Pathfinder. Conclusions and Future Work.




Probabilistic Modeling in Bioinformatics and Medical Informatics


Book Description

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.




Ai 2004: Advances In Artificial Intelligence


Book Description

This book constitutes the refereed proceedings of the 17th Australian Conference on Artificial Intelligence, AI 2004, held in Cairns, Australia, in December 2004. The 78 revised full papers and 62 revised short papers presented were carefully reviewed and selected from 340 submissions. The papers are organized in topical sections on agents; biomedical applications; computer vision, image processing, and pattern recognition; ontologies, knowledge discovery and data mining; natural language and speech processing; problem solving and reasoning; robotics; and soft computing.




Proceedings of the First Symposium on Aviation Maintenance and Management-Volume I


Book Description

Proceedings of the First Symposium on Aviation Maintenance and Management collects selected papers from the conference of ISAMM 2013 in China held in Xi’an on November 25-28, 2013. The book presents state-of-the-art studies on the aviation maintenance, test, fault diagnosis, and prognosis for the aircraft electronic and electrical systems. The selected works can help promote the development of the maintenance and test technology for the aircraft complex systems. Researchers and engineers in the fields of electrical engineering and aerospace engineering can benefit from the book. Jinsong Wang is a professor at School of Mechanical and Electronic Engineering of Northwestern Polytechnical University, China.