The papers in this volume deal with academic research topics as well as practical applications in AI. Special emphasis is given to computer vision, machine learning, neural networks mixed with theory of logic and reasoning, and practical applications of expert systems in industry and decision support.

This volume reflects the state of the art in artificial intelligence in the Australasian region. It covers machine learning, knowledge acguisition, cognitive modelling, robots and vision, natural language, automated reasoning, knowledge-based systems, neural networks and genetic algorithms, distributed AI, etc.

In the last few years rapid advances have been made in reproductive medicine, making it necessary for those involved to regularly update their knowledge. The purpose of this book is to describe the state of the art in this field, making it possible for the reader to gain an orientation among all the diagnostic and therapeutic potentials of modern reproductive medicine in order to advise patients fully. Chapters from the fields of gynecology, and reproductive medicine in a specific sense provide knowledge about these subjects. Authors of international standing have contributed chapters on their specialties. These chapters together form a book describing the state of the art in the diagnosis and therapy of sterility in gynecology and andrology.

Machine learning algorithms hold extraordinary promise, but the reality is that their success depends entirely on the suitability of the data available. This book is about Ripple-Down Rules (RDR), an alternative manual technique for rapidly building AI systems. With a human in the loop, RDR is much better able to deal with the limitations of data. Ripple-Down Rules: The Alternative to Machine Learning starts by reviewing the problems with data quality and the problems with conventional approaches to incorporating expert human knowledge into AI systems. It suggests that problems with knowledge acquisition arise because of mistaken philosophical assumptions about knowledge. It argues people never really explain how they reach a conclusion, rather they justify their conclusion by differentiating between cases in a context. RDR is based on this more situated understanding of knowledge. The central features of a RDR approach are explained, and detailed worked examples are presented for different types of RDR, based on freely available software developed for this book. The examples ensure developers have a clear idea of the simple yet counter-intuitive RDR algorithms to easily build their own RDR systems. It has been proven in industrial applications that it takes only a minute or two per rule to build RDR systems with perhaps thousands of rules. The industrial uses of RDR have ranged from medical diagnosis through data cleansing to chatbots in cars. RDR can be used on its own or to improve the performance of machine learning or other methods.

Intelligent Support Systems for Marketing Decisions examines new product development, market penetration strategies, and other marketing decisions utilizing a confluence of methods, including Decision Support Systems (DSS), Artificial Intelligence in Marketing and Multicriteria Analysis. The authors systematically examine the use and implementation of these methodologies in making strategic marketing decisions. Part I discusses the basic concepts of multicriteria analysis vis-à-vis marketing decisions and in new product development situations. Part II presents basic concepts from the fields of Information Systems, Decision Support Systems, and Intelligent Decision Support Methods. In addition, specialized categories of DSS (multicriteria DSS, web-based DSS, group DSS, spatial DSS) are discussed in terms of their key features and current use in marketing applications. Part III presents IDSS and a multicriteria methodology for new product development. Further chapters present a developmental strategy for analyzing, designing, and implementing an Intelligent Marketing Decision Support System. The implementation discussion is illustrated with a real-world example of the methods and system in use.

Hydroinformatics addresses cross-disciplinary issues ranging from technological and sociological to more general environmental concerns, including an ethical perspective. It covers the application of information technology in the widest sense to problems of the aquatic environment.This two-volume publication contains about 250 high quality papers contributed by authors from over 50 countries. The proceedings present many exciting new findings in the emerging subjects, as well as their applications, such as: data mining, data assimilation, artificial neural networks, fuzzy logic, genetic algorithms and genetic programming, chaos theory and support vector machines, geographic information systems and virtual imaging, decision support and management systems, Internet-based technologies.This book provides an excellent reference to researchers, graduate students, practitioners, and all those interested in the field of hydroinformatics.

This book is a printed edition of the Special Issue " Development and Application of Nonlinear Dissipative Device in Structural Vibration Control" that was published in Applied Sciences

Hybrid Nanofluids: Preparation, Characterization and Applications presents the history of hybrid nanofluids, preparation techniques, thermoelectrical properties, rheological behaviors, optical properties, theoretical modeling and correlations, and the effect of all these factors on potential applications, such as solar energy, electronics cooling, heat exchangers, machining, and refrigeration. Future challenges and future work scope have also been included. The information from this book enables readers to discover novel techniques, resolve existing research limitations, and create novel hybrid nanofluids which can be implemented for heat transfer applications. - Describes the characterization, thermophysical and electrical properties of nanofluids - Assesses parameter selection and property measurement techniques for the calibration of thermal performance - Provides information on theoretical models and correlations for predicting hybrid nanofluids properties from experimental properties

The Mekong Basin in Southeast Asia is one of the largest international river basins in the world. Its abundant natural resources are shared by six riparian countries and provide the basis for the livelihoods of more than 75 million people. However, ongoing socio-economic growth and related anthropogenic interventions impact the region’s ecosystems, and there is an urgent need for the monitoring of the basin's land surface dynamics. Remote sensing has evolved as a key tool for this task, allowing for up-to-date analyses and regular monitoring of environmental dynamics beyond physical or political boundaries and at various temporal and spatial scales. This book serves as a forum for remote-sensing scientists with an interest in the Mekong River Basin to present their recent basin-related works as well as applied case studies of the region. A broad range of sensors from high to medium resolution, and from multispectral to SAR systems, are applied, covering topics such as land cover/land use classification and comparison, time series analyses of climate variables, vegetation structure and vegetation productivity, as well as studies on flood mapping or water turbidity monitoring. This book was originally published as a special issue of the International Journal of Remote Sensing.

This book constitutes the refereed proceedings of the 15th Australian Joint Conference on Artificial Intelligence, AI 2002, held in Canberra, Australia in December 2002. The 62 revised full papers and 12 posters presented were carefully reviewed and selected from 117 submissions. The papers are organized in topical sections on natural language and information retrieval, knowledge representation and reasoning, deduction, learning theory, agents, intelligent systems. Bayesian reasoning and classification, evolutionary algorithms, neural networks, reinforcement learning, constraints and scheduling, neural network applications, satisfiability reasoning, machine learning applications, fuzzy reasoning, and case-based reasoning.