904 resultados para Programming courses


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Objective: To compare the effectiveness and safety of repeat treatment with hylan G-F 20 based on data from a randomized, controlled trial [Raynauld JP, Torrance GW, Band PA, Goldsmith CH, Tugwell P, Walker V, et al. A prospective, randomized, pragmatic, health outcomes trial evaluating the incorporation of hylan G-F 20 into the treatment paradigm for patients with knee osteoarthritis (Part 1 of 2): clinical results. Osteoarthritis Cartilage 2002;10:506-17]. The hypotheses tested were whether the single-course and repeat-course subgroups would be superior to appropriate care and not different from each other. Method: A total of 255 patients with knee osteoarthritis were randomized to appropriate care with hylan G-F 20 or appropriate care without hylan G-F 20. The hylan G-F 20 group was partitioned into two subgroups: (1) patients who received a single course of hylan G-F 20; and (2) patients who received two or more courses of hylan G-F 20. Results: For the primary effectiveness measure, change in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score as a percent of baseline, the single-course subgroup improved by 41%, the repeat-course subgroup by 35%, and the appropriate care group by 14%. Both subgroups improved significantly more than the appropriate care group (P < 0.05), and were not statistically significantly different from each other (70% power to detect a 20% difference). Secondary effectiveness measures showed similar results. In the repeat-course subgroup, no statistically significant differences were found in the number of local adverse events, the number of patients with local adverse events, or arthrocentesis rates between the first and repeat courses of treatment. Conclusions: Although the study was neither designed nor powered to examine repeat treatment, this a posteriori analysis provides support for a favorable effectiveness and safety profile of hylan G-F 20 in repeat course patients. (C) 2004 OsteoArthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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The pervasiveness of information systems (IS) in organizations mandates the need for high levels of IS skills. In recognition, professional bodies impose IS course requirements for accreditation. For both students and employers, performance in IS courses has become important. The tertiary entrance overall performance score accounted for 19.7 per cent of the variance in students' passing grades. Thereafter, proficiency in office automation software and programming accounted for 1.5 and 0.8 per cent of the variance, respectively. Students living in a stable, family home-based environment performed better and it is likely that this environment underpinned other factors affecting performance.

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Control Engineering is an essential part of university electrical engineering education. Normally, a control course requires considerable mathematical as well as engineering knowledge and is consequently regarded as a difficult course by many undergraduate students. From the academic point of view, how to help the students to improve their learning of the control engineering knowledge is therefore an important task which requires careful planning and innovative teaching methods. Traditionally, the didactic teaching approach has been used to teach the students the concepts needed to solve control problems. This approach is commonly adopted in many mathematics intensive courses; however it generally lacks reflection from the students to improve their learning. This paper addresses the practice of action learning and context-based learning models in teaching university control courses. This context-based approach has been practised in teaching several control engineering courses in a university with promising results, particularly in view of student learning performances.

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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.

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Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.