9 resultados para CMConv Special Issue

em University of Queensland eSpace - Australia


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Bourdieu … makes it possible to explain how the actions of principals are always contextual, since their interests vary with issue, location, time, school mix, composition of staff and so on. This 'identity' perspective points at a different kind of research about principal practice: to understand the game and its logic requires an analysis of the situated everyday rather than abstractions that claim truth in all instances and places. (Thomson 2001a: 14)

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Papers in this issue of Natural Resources Research are from the “Symposium on the Application of Neural Networks to the Earth Sciences,” held 20–21 August 2002 at NASA Moffet Field, Mountain View, California. The Symposium represents the Seventh International Symposium on Mineral Exploration (ISME-02). It was sponsored by the Mining and Materials Processing Institute of Japan (MMIJ), the US Geological Survey, the Circum-Pacific Council, and NASA. The ISME symposia have been held every two years in order to bring together scientists actively working on diverse quantitative methods applied to the earth sciences. Although the title, International Symposium on Mineral Exploration, suggests exclusive focus on mineral exploration, interests and presentations always have been wide-ranging—talks presented at this symposium are no exception.

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There have been a number of developments in the need, design and use of passive air samplers (PAS) for persistent organic pollutants (POPs). This article is the first in a Special Issue of the journal to review these developments and some of the data arising from them. We explain the need and benefit of developing PAS for POPs, the different approaches that can be used, and highlight future developments and needs. (c) 2006 Elsevier Ltd. All rights reserved.

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This special issue is a collection of the selected papers published on the proceedings of the First International Conference on Advanced Data Mining and Applications (ADMA) held in Wuhan, China in 2005. The articles focus on the innovative applications of data mining approaches to the problems that involve large data sets, incomplete and noise data, or demand optimal solutions.