833 resultados para Programming pedagogy
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Thesis (D.M.A.)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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This paper focuses on measuring the extent to which market power has been exercised in a recently deregulated electricity generation sector. Our study emphasises the need to consider the concept of market power in a long-run dynamic context. A market power index is constructed focusing on differences between actual market returns and long-run competitive returns, estimated using a programming model devised by the authors. The market power implications of hedge contracts are briefly considered. The state of Queensland Australia is used as a context for the analysis. The results suggest that generators have exercised significant market power since deregulation.
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There has been a great deal of discussion about the need for interdisciplinary, applied research to service the needs of the knowledge economy and to solve the broader complex theoretical problems of the twenty-first century. This is known as 'Mode 2' knowledge production. Yet, university research higher degree programs continue to be largely disciplinary-based. While there has been a rise in the number of research students working on industry-related, applied projects, very few research students gain exposure to interdisciplinary research processes. This paper explores several examples of interdisciplinary doctoral programs based in North America and Australia and seeks to draw upon examples of undergraduate interdisciplinary learning and epistemology. In reviewing this theoretical work and a number of strategies implemented at an Australian university, the paper begins to imagine an interdisciplinary doctoral pedagogy.
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In this paper, we consider dynamic programming for the election timing in the majoritarian parliamentary system such as in Australia, where the government has a constitutional right to call an early election. This right can give the government an advantage to remain in power for as long as possible by calling an election, when its popularity is high. On the other hand, the opposition's natural objective is to gain power, and it will apply controls termed as "boosts" to reduce the chance of the government being re-elected by introducing policy and economic responses. In this paper, we explore equilibrium solutions to the government, and the opposition strategies in a political game using stochastic dynamic programming. Results are given in terms of the expected remaining life in power, call and boost probabilities at each time at any level of popularity.
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Defeasible reasoning is a simple but efficient approach to nonmonotonic reasoning that has recently attracted considerable interest and that has found various applications. Defeasible logic and its variants are an important family of defeasible reasoning methods. So far no relationship has been established between defeasible logic and mainstream nonmonotonic reasoning approaches. In this paper we establish close links to known semantics of logic programs. In particular, we give a translation of a defeasible theory D into a meta-program P(D). We show that under a condition of decisiveness, the defeasible consequences of D correspond exactly to the sceptical conclusions of P(D) under the stable model semantics. Without decisiveness, the result holds only in one direction (all defeasible consequences of D are included in all stable models of P(D)). If we wish a complete embedding for the general case, we need to use the Kunen semantics of P(D), instead.
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The application of energy minimisation methods for stereo matching has been demonstrated to produce high quality disparity maps. However the majority of these methods are known to be computationally expensive, requiring minutes or even hours of computation. We propose a fast minimisation scheme that produces strongly competitive results for significantly reduced computation, requiring only a few seconds of computation. In this paper, we present our iterated dynamic programming algorithm along with a quadtree subregioning process for fast stereo matching.
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"Totally functional programming" (TFP) advocates the complete replacement of symbolic representations for data by functions. TFP is motivated by observations from practice in language extensibility and functional programming. Its technical essence extends the role of "fold" functions in structuring functional programs to include methods that make comparisons on elements of data structures. The obstacles that currently prevent the immediate uptake of TFP as a style within functional programming equally indicate future research directions in the areas of theoretical foundations, supporting technical infrastructure, demonstrated practical applicability, and relationship to OOP.