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In this study the supposed difference between political nationalism and what is termed 'cultural nationalism' is interrogated. It is through literary tropes and images, after all, that the imaginary reflections and misrecognitions of land and religion have been instantiated. This study also contends that there is a definite symphysis between literary language and the political embodiment of nationalist ideology.
Water provides benefits as a commodity for agriculture, industry, and households, and as a public good such as fisheries habitat, water quality and recreational use. To aid in cost-benefit analysis under conditions where market determined price signals are usually unavailable, economists have developed a range of alternative valuation methods for measuring economic benefits.
This volume provides the most comprehensive exposition to-date of the application of economic valuation methods to proposed water resources investments and policies. It provides a conceptual framework for valuation of both commodity and public good uses of water, addressing non-market valuation techniques appropriate to measuring public benefits - including water quality improvement, recreation, and fish habitat enhancement. The book describes the various measurement methods, illustrates how they are applied in practice, and discusses their strengths, limitations, and appropriate roles.
In this second edition, all chapters have been thoroughly updated, and in particular the coverage of water markets and valuation of ecosystem services from water has been expanded. Robert Young, author of the 2005 edition, has been joined for this new edition by John Loomis, who brings additional expertise on ecosystem services and the environmental economics of water for recreational and other public good uses of water.
This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increas ingly popular in the last few years, and their integration is currently an area of active research. In essence, data mining consists of extracting valid, comprehensible, and in teresting knowledge from data. Data mining is actually an interdisciplinary field, since there are many kinds of methods that can be used to extract knowledge from data. Arguably, data mining mainly uses methods from machine learning (a branch of artificial intelligence) and statistics (including statistical pattern recog nition). Our discussion of data mining and evolutionary algorithms is primarily based on machine learning concepts and principles. In particular, in this book we emphasize the importance of discovering comprehensible, interesting knowledge, which the user can potentially use to make intelligent decisions. In a nutshell, the motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions (rules or another form of knowl edge representation). In contrast, most rule induction methods perform a local, greedy search in the space of candidate rules. Intuitively, the global search of evolutionary algorithms can discover interesting rules and patterns that would be missed by the greedy search."
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