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Australia's Uranium Trade

RRP $59.99

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Australia's Uranium Trade explores why the export of uranium remains a highly controversial issue in Australia and how this affects Australia's engagement with the strategic, regime and market realms of international nuclear affairs. The book focuses on the key challenges facing Australian policy makers in a twenty-first century context where civilian nuclear energy consumption is expanding significantly while at the same time the international nuclear nonproliferation regime is subject to increasing, and unprecedented, pressures. By focusing on Australia as a prominent case study, the book is concerned with how a traditionally strong supporter of the international nuclear nonproliferation regime is attempting to recalibrate its interest in maximizing the economic and diplomatic benefits of increased uranium exports during a period of flux in the strategic, regime and market realms of nuclear affairs. Australia's Uranium Trade provides broader lessons for how â" indeed whether â" nuclear suppliers worldwide are adapting to the changing nuclear environment internationally.


Mining Very Large Databases With Parallel Processing

RRP $931.99

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Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms.
The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers.
It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science.
The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.



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