845 resultados para 280400 Computation Theory and Mathematics


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Aquifers are a vital water resource whose quality characteristics must be safeguarded or, if damaged, restored. The extent and complexity of aquifer contamination is related to characteristics of the porous medium, the influence of boundary conditions, and the biological, chemical and physical processes. After the nineties, the efforts of the scientists have been increased exponentially in order to find an efficient way for estimating the hydraulic parameters of the aquifers, and thus, recover the contaminant source position and its release history. To simplify and understand the influence of these various factors on aquifer phenomena, it is common for researchers to use numerical and controlled experiments. This work presents some of these methods, applying and comparing them on data collected during laboratory, field and numerical tests. The work is structured in four parts which present the results and the conclusions of the specific objectives.

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A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

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For anyone involved in developing a research project, this textbook provides an integrated, accessible and humorous account that explains why research methods are the way they are and how they do what they do. Unrivalled in its nature Doing Business Research addresses the research project as a whole and provides: - essential detail of philosophical and theoretical matters that are crucial to conceptualising the nature of methodology - a pragmatic guide to why things are important and how they are important - a huge range of things to consider that the reader can use to develop their research project further - a resource book, providing extensive suggested reading to help the researcher do their research.

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It has been suggested that, in order to maintain its relevance, critical research must develop a strong emphasis on empirical work rather than the conceptual emphasis that has typically characterized critical scholarship in management. A critical project of this nature is applicable in the information systems (IS) arena, which has a growing tradition of qualitative inquiry. Despite its relativist ontology, actor–network theory places a strong emphasis on empirical inquiry and this paper argues that actor–network theory, with its careful tracing and recording of heterogeneous networks, is well suited to the generation of detailed and contextual empirical knowledge about IS. The intention in this paper is to explore the relevance of IS research informed by actor–network theory in the pursuit of a broader critical research project as de? ned in earlier work.

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We study the role of political accountability as a determinant of corruption and economic growth. Our model identifies two governance regimes defined by the quality of political institutions and shows that the relationship between corruption and growth is regime specific. We use a threshold model to estimate the impact of corruption on growth where corruption is treated as an endogenous variable. We find two governance regimes, conditional on the quality of political institutions. In the regime with high quality political institutions, corruption has a substantial negative impact on growth. In the regime with low quality institutions, corruption has no impact on growth.