The book provides an overview of III-nitride-material-based light-emitting diode (LED) technology, from the basic material physics to the latest advances in the field, such as homoepitaxy and heteroepitaxy of the materials on different substrates. It also includes the latest advances in the field, such as approaches to improve quantum efficiency and reliability as well as novel structured LEDs. It explores the concept of material growth, chip structure, packaging, reliability and application of LEDs. With spectra coverage from ultraviolet (UV) to entire visible light wavelength, the III-nitride-material-based LEDs have a broad application potential, and are not just limited to illumination. These novel applications, such as health & medical, visible light communications, fishery and horticulture, are also discussed in the book.

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

This book takes a fresh look at the problem of unconstrained handwriting recognition and introduces the reader to new techniques for the recognition of written words and characters using statistical and soft computing approaches. The types of uncertainties and variations present in handwriting data are discussed in detail. The book presents several algorithms that use modified hidden Markov models and Markov random field models to simulate the handwriting data statistically and structurally in a single framework. The book explores methods that use fuzzy logic and fuzzy sets for handwriting recognition. The effectiveness of these techniques is demonstrated through extensive experimental results and real handwritten characters and words.

This authoritative and comprehensive collection contains the most important published papers and articles on the economics of crime. It presents a variety of different perspectives and will be an essential reference source for both researchers and policymakers.The book examines the theory and methodology of the economics of law enforcement and crime prevention as they affect both public authorities and private individuals. It explores the economics of organized crime from the point of view of the criminal, but also considers the costs to the community of criminal acts and their effects. It studies the causes of crime and the costs and effectiveness of deterrence and punishment. The editors have written a new authoritative introduction which gives a wide-ranging overview of the topics covered.

The book provides an overview of III-nitride-material-based light-emitting diode (LED) technology, from the basic material physics to the latest advances in the field, such as homoepitaxy and heteroepitaxy of the materials on different substrates. It also includes the latest advances in the field, such as approaches to improve quantum efficiency and reliability as well as novel structured LEDs. It explores the concept of material growth, chip structure, packaging, reliability and application of LEDs. With spectra coverage from ultraviolet (UV) to entire visible light wavelength, the III-nitride-material-based LEDs have a broad application potential, and are not just limited to illumination. These novel applications, such as health & medical, visible light communications, fishery and horticulture, are also discussed in the book.

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

Over the last few decades, research on handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the prices of scanners, com puters and handwriting-input devices are falling steadily, we have seen an increased demand for handwriting recognition systems and software pack ages. Some commercial handwriting recognition systems are now available in the market. Current commercial systems have an impressive performance in recognizing machine-printed characters and neatly written texts. For in stance, High-Tech Solutions in Israel has developed several products for container ID recognition, car license plate recognition and package label recognition. Xerox in the U. S. has developed TextBridge for converting hardcopy documents into electronic document files. In spite of the impressive progress, there is still a significant perfor mance gap between the human and the machine in recognizing off-line unconstrained handwritten characters and words. The difficulties encoun tered in recognizing unconstrained handwritings are mainly caused by huge variations in writing styles and the overlapping and the interconnection of neighboring characters. Furthermore, many applications demand very high recognition accuracy and reliability. For example, in the banking sector, although automated teller machines (ATMs) and networked banking sys tems are now widely available, many transactions are still carried out in the form of cheques."

This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Machine Learning and Cybernetics, ICMLC 2005, held in Guangzhou, China in August 2005.

The 114 revised full papers of this volume were carefully reviewed and selected from 2461 paper submissions and 1050 real conference presentations respectively during two rounds of reviewing and improvement. The papers are organized in topical sections on agents and distributed artificial intelligence, control, data mining and knowledge discovery, fuzzy information processing, learning and reasoning, machine learning applications, neural networks and statistical learning methods, pattern recognition, vision and image processing.