Optimal control of distributed generators and capacitors by hybrid DPSO

In this paper, a comprehensive planning methodology is proposed that can minimize the line loss, maximize the reliability and improve the voltage profile in a distribution network. The injected active and reactive power of Distributed Generators (DG) and the installed capacitor sizes at different buses and for different load levels are optimally controlled. The tap setting of HV/MV transformer along with the line and transformer upgrading is also included in the objective function. A hybrid optimization method, called Hybrid Discrete Particle Swarm Optimization (HDPSO), is introduced to solve this nonlinear and discrete optimization problem. The proposed HDPSO approach is a developed version of DPSO in which the diversity of the optimizing variables is increased using the genetic algorithm operators to avoid trapping in local minima. The objective function is composed of the investment cost of DGs, capacitors, distribution lines and HV/MV transformer, the line loss, and the reliability. All of these elements are converted into genuine dollars. Given this, a single-objective optimization method is sufficient. The bus voltage and the line current as constraints are satisfied during the optimization procedure. The IEEE 18-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate the unavoidable need for optimal control on the DG active and reactive power and capacitors in distribution networks.

Redefining excellence : a strategic policy framework for community engagement and higher education

This report provides a current overview and analysis of the role of universities in local community development in the State of Victoria. Drawing on successful programs of community engagement in Victoria, Australia, Europe, Africa, and North America, the report proposes policy strategies for fostering community development for Victorian Higher Education through effective community engagement programs.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Optimal-stopping control for airborne collision avoidance and return-to-course flight

This paper considers an aircraft collision avoidance design problem that also incorporates design of the aircraft’s return-to-course flight. This control design problem is formulated as a non-linear optimal-stopping control problem; a formulation that does not require a prior knowledge of time taken to perform the avoidance and return-to-course manoeuvre. A dynamic programming solution to the avoidance and return-to-course problem is presented, before a Markov chain numerical approximation technique is described. Simulation results are presented that illustrate the proposed collision avoidance and return-to-course flight approach.

Optimal online prediction in adversarial environments

In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

Optimal online prediction in adversarial environments

In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

Optimal strategies and minimax lower bounds for online convex games

A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal.

An analysis of the nature and effectiveness of corporate governance in smaller listed Australian companies

The objective of this thesis is to investigate the corporate governance attributes of smaller listed Australian firms. This study is motivated by evidence that these firms are associated with more regulatory concerns, the introduction of ASX Corporate Governance Recommendations in 2004, and a paucity of research to guide regulators and stakeholders of smaller firms. While there is an extensive body of literature examining the effectiveness of corporate governance, the literature principally focuses on larger companies, resulting in a deficiency in the understanding of the nature and effectiveness of corporate governance in smaller firms. Based on a review of agency theory literature, a theoretical model is developed that posits that agency costs are mitigated by internal governance mechanisms and transparency. The model includes external governance factors but in many smaller firms these factors are potentially absent, increasing the reliance on the internal governance mechanisms of the firm. Based on the model, the observed greater regulatory intervention in smaller companies may be due to sub-optimal internal governance practices. Accordingly, this study addresses four broad research questions (RQs). First, what is the extent and nature of the ASX Recommendations that have been adopted by smaller firms (RQ1)? Second, what firm characteristics explain differences in the recommendations adopted by smaller listed firms (RQ2), and third, what firm characteristics explain changes in the governance of smaller firms over time (RQ3)? Fourth, how effective are the corporate governance attributes of smaller firms (RQ4)? Six hypotheses are developed to address the RQs. The first two hypotheses explore the extent and nature of corporate governance, while the remaining hypotheses evaluate its effectiveness. A time-series, cross-sectional approach is used to evaluate the effectiveness of governance. Three models, based on individual governance attributes, an index of six items derived from the literature, and an index based on the full list of ASX Recommendations, are developed and tested using a sample of 298 smaller firms with annual observations over a five-year period (2002-2006) before and after the introduction of the ASX Recommendations in 2004. With respect to (RQ1) the results reveal that the overall adoption of the recommendations increased from 66 per cent in 2004 to 74 per cent in 2006. Interestingly, the adoption rate for recommendations regarding the structure of the board and formation of committees is significantly lower than the rates for other categories of recommendations. With respect to (RQ2) the results reveal that variations in rates of adoption are explained by key firm differences including, firm size, profitability, board size, audit quality, and ownership dispersion, while the results for (RQ3) were inconclusive. With respect to (RQ4), the results provide support for the association between better governance and superior accounting-based performance. In particular, the results highlight the importance of the independence of both the board and audit committee chairs, and of greater accounting-based expertise on the audit committee. In contrast, while there is little evidence that a majority independent board is associated with superior outcomes, there is evidence linking board independence with adverse audit opinion outcomes. These results suggest that board and chair independence are substitutes; in the presence of an independent chair a majority independent board may be an unnecessary and costly investment for smaller firms. The findings make several important contributions. First, the findings contribute to the literature by providing evidence on the extent, nature and effectiveness of governance in smaller firms. The findings also contribute to the policy debate regarding future development of Australia’s corporate governance code. The findings regarding board and chair independence, and audit committee characteristics, suggest that policy-makers could consider providing additional guidance for smaller companies. In general, the findings offer support for the “if not, why not?” approach of the ASX, rather than a prescriptive rules-based approach.

Inequitable Provision of Optimal Services for Patients with Chronic Heart failure: A National Geo-Mapping Study

Objective: To compare the location and accessibility of current Australian chronic heart failure (CHF) management programs and general practice services with the probable distribution of the population with CHF. Design and setting: Data on the prevalence and distribution of the CHF population throughout Australia, and the locations of CHF management programs and general practice services from 1 January 2004 to 31 December 2005 were analysed using geographic information systems (GIS) technology. Outcome measures: Distance of populations with CHF to CHF management programs and general practice services. Results: The highest prevalence of CHF (20.3–79.8 per 1000 population) occurred in areas with high concentrations of people over 65 years of age and in areas with higher proportions of Indigenous people. Five thousand CHF patients (8%) discharged from hospital in 2004–2005 were managed in one of the 62 identified CHF management programs. There were no CHF management programs in the Northern Territory or Tasmania. Only four CHF management programs were located outside major cities, with a total case load of 80 patients (0.7%). The mean distance from any Australian population centre to the nearest CHF management program was 332 km (median, 163 km; range, 0.15–3246 km). In rural areas, where the burden of CHF management falls upon general practitioners, the mean distance to general practice services was 37 km (median, 20 km; range, 0–656 km). Conclusion: There is an inequity in the provision of CHF management programs to rural Australians.

The Maori social science academy and evidence-based policy

This paper focuses on recent moves to forge stronger linkages between the Māori social science academy and the policy industry. A critical appraisal of this development is offered, with particular attention given to the desirability of enhancing the academy’s role in the policy process, given the policy industry’s continued privileging of Eurocentric theory and research methodologies within the developing evidence-based environment. The paper ends with a discussion of the possibilities and problems associated with engagement with the policy industry, particularly as these relate to the various roles members can (or are forced to) take; either as ‘insiders’ (such as policy workers and contract researchers), or independent, critical ‘outsiders’. The author concludes that the best that insiders can hope for are incremental, largely ineffective changes to Māori policy, while independent members of the academy are best placed to speak on behalf of Māori, Māori communities, hapu and iwi.