Tharam S. Dillon

Allan Kang Ying Wong

Wilfred Wan Kei Lin

Although the Internet and World Wide Web (WWW) are popular as tools for convenient exchange of information, it is not easy to utilise the Internet for time-critical applications such as on-line remote diagnosis in telemedicine. It is a wish of the United Nations to bring e-health to every corner of the world via the Internet. This is easier said than done because the sheer size of the Internet implies unpredictable faults of all kinds. These faults are physically translated into communication and computation delays. Since these faults and delays have many contributing factors that can change suddenly, it is impractical to monitor them all for the sake of fault tolerance. For this reason the new concept of interpreting the channel dynamics by gauging its end-to-end behaviour has emerged. The aim is to measure the changes of the average service roundtrip time (RTT) over time and interpret the possible signs of faults from these changes. If the length of the average service RTT is suddenly increased in an exponential manner, network congestion and widespread retransmission are indicated. Then, the Internet and/or the applications running on it should invoke fault tolerance measures to prevent system breakdown and partial failures. This concept of gauging the channel dynamics to prevent system failure is generally known as Internet End-to-End Performance Measurement (IEPM). The purpose of the book is to shed light on some of the novel practical fault tolerance techniques that can help shorten the end-to-end service roundtrip (RTT) time of a logical Internet channel. As a result the Internet can be harnessed for serious time-critical applications. Several practical cases are presented to demonstrate how the effective harnessing can be achieved.

Concept, Techniques and Cases

Harnessing the Service Roundtrip Time Over the Internet to Support Time-critical Applications

Matthew Bellgard

Amandeep S. Sidhu

Compared with data from general application domains, modern biological data has many unique characteristics. The goal of this book is to cover data and applications identifying new issues and directions for future research in biomedical domain.

Biomedical Data and Applications

Kit Yan Chan

C.K. Kwong

Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the computational intelligence based approaches to product design. This book covers the state-of-art of computational intelligence methods for product design, which provides a clear picture to post-graduate students in industrial engineering and computer science. It is particularly suitable for researchers and professionals working on computational intelligence for product design. It provides concepts, techniques and methodologies, for product designers in applying computational intelligence to deal with product design.

Computational Intelligence Techniques for New Product Design

Yuk Shan Wong

Robert Meersman

Elizabeth Chang

Katia Sycara

This book constitutes the first volume of a series of books focusing on the vital and ever-growing field of web semantics. The primary aim of the series is to investigate, present and promote core concepts, ideas and exemplary technologies for the next generation of semantic web research, stemming from both academia and industry. Topics covered will include process semantics, web services, ontologies, workflows, trust and reputation, and web applications. The 14 papers in this volume, written by key scientists in the field, are preceded by an introduction written by the volume editors. The papers have been divided into three sections on Ontologies and Knowledge Sharing, Applied Semantic Web, and Web Services.

Ontologies, Web Services and Applied Semantic Web

Advances in Web Semantics I

Henry Tan

Fedja Hadzic

Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Mining of Data with Complex Structures

Sankar Kumar Pal

Daniel S. Yeung

This text demonstrates how various soft computing tools can be applied to design and develop methodologies and systems with case based reasoning, that is, for real-life decision-making or recognition problems. Comprising contributions from experts, it introduces the basic concepts and theories, and includes many reports on real-life applications. This book is of interest to graduate students and researchers in computer science, electrical engineering and information technology, as well as researchers and practitioners from the fields of systems design, pattern recognition and data mining.

Tharam S. Dillon

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