Recent years have seen the development of two significant trends namely: the adoption of some Traditional Chinese Medicine Practices into mainstream Allopathic Western Medicine and the advent of the internet and broad band networks leading to an increased interest in the use of Telemedicine to deliver medical services. In this book, we see the convergence of these two trends leading to a semantically-based TCM Telemedicine system that utilizes an ontology to provide sharable knowledge in the TCM realm to achieve this. The underpinning research required the development of a three-layer architecture and an Ontology of the TCM knowledge. As TCM knowledge like all medical knowledge is not frozen in time it was important to develop an approach that would allow evolution of the Ontology when new evidence became available. In order for the system to be practically grounded it was important to work with an industry partner PuraPharm Group/HerbMiners Informatics Limited. This partnership was initiated through Professor Allan Wong and the Chairman of PuraPharm Group Mr. Abraham Chan. This led to the system being utilized in more than 20 Mobile Clinics in Hong Kong and 300 Hospitals in China. In order for these different deployments of the system to be coherent with the main core Ontology, it was necessary for us to develop an Ontology Driven Software System Generation approach.

Recent years have seen the development of two significant trends namely: the adoption of some Traditional Chinese Medicine Practices into mainstream Allopathic Western Medicine and the advent of the internet and broad band networks leading to an increased interest in the use of Telemedicine to deliver medical services. In this book, we see the convergence of these two trends leading to a semantically-based TCM Telemedicine system that utilizes an ontology to provide sharable knowledge in the TCM realm to achieve this. The underpinning research required the development of a three-layer architecture and an Ontology of the TCM knowledge. As TCM knowledge like all medical knowledge is not frozen in time it was important to develop an approach that would allow evolution of the Ontology when new evidence became available. In order for the system to be practically grounded it was important to work with an industry partner PuraPharm Group/HerbMiners Informatics Limited. This partnership was initiated through Professor Allan Wong and the Chairman of PuraPharm Group Mr. Abraham Chan. This led to the system being utilized in more than 20 Mobile Clinics in Hong Kong and 300 Hospitals in China. In order for these different deployments of the system to be coherent with the main core Ontology, it was necessary for us to develop an Ontology Driven Software System Generation approach.

Risk and reward are always foremost in the determination of investment decisions and business transactions. Advances in the area of Information Communication Technologies (ICT) have enabled the development of new business paradigms. Such paradigms involve transactions taking place between loosely connected parties, often totally or partially unknown to one another. One important concept required to ensure such transactions are successful is transactional risk. The importance of doing this has been demonstrated in recent financial crisis. This book is unique in simultaneously taking into account the likelihood of an event occurring and its financial impact and provides an integrated discussion of the process of transactional risk identification, assessment, evaluation, management and recording in these emerging domains. It provides a detailed and clear exposition of the importance of transactional risk before detailing for its assessment and evaluation. The scope of the book is theoretical and practical and as such it will have a broad market both within academia and industry. Specifically this book should be of primary interest to researchers, graduate students and practitioners in the area of developing business intelligence techniques and their application in various real world applications.

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.

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."

Risk and reward are always foremost in the determination of investment decisions and business transactions. Advances in the area of Information Communication Technologies (ICT) have enabled the development of new business paradigms. Such paradigms involve transactions taking place between loosely connected parties, often totally or partially unknown to one another. One important concept required to ensure such transactions are successful is transactional risk. The importance of doing this has been demonstrated in recent financial crisis. This book is unique in simultaneously taking into account the likelihood of an event occurring and its financial impact and provides an integrated discussion of the process of transactional risk identification, assessment, evaluation, management and recording in these emerging domains. It provides a detailed and clear exposition of the importance of transactional risk before detailing for its assessment and evaluation. The scope of the book is theoretical and practical and as such it will have a broad market both within academia and industry. Specifically this book should be of primary interest to researchers, graduate students and practitioners in the area of developing business intelligence techniques and their application in various real world applications.

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.

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."

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.

Soft Computing in Case Based Reasoning demonstrates how various soft computing tools can be applied to design and develop methodologies and systems with case based reasoning for real-life decision-making or recognition problems.Comprising contributions from experts from all over the world, it:- Provides an introduction to CBR and soft computing, and the relevance of their integration- Evaluates the strengths and weaknesses of CBR in its current form- Presents recent developments and significant applications in domains such as data-mining, medical diagnosis, knowledge-based expert systems, banking, and forensic investigation- Addresses new information on developing intelligent systemsThis book will be of particular interest to graduate students and researchers in computer science, electrical engineering and information technology but it will also be of interest to researchers and practitioners in the fields of systems design, pattern recognition and data mining.