The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Measuring market power in electricity generation: A long-term perspective using a programming model

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.

Effectiveness and safety of repeat courses of hylan G-F 20 in patients with knee osteoarthritis

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.

Undergraduate performance in accounting and business-based information technology

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.

Improving learning in undergraduate control engineering courses using context-based learning models

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.

Stochastic dynamic programming for election timing: A game theory approach

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.

Embedding defeasible logic into logic programming

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.

Fast stereo matching by iterated dynamic programming and quadtree subregioning

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.

Obstacles to a totally functional programming style

"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.