A Majorization-Minimization Approach to Design of Power Transmission Networks

We propose an optimization approach to design cost-effective electrical power transmission networks. That is, we aim to select both the network structure and the line conductances (line sizes) so as to optimize the trade-off between network efficiency (low power dissipation within the transmission network) and the cost to build the network. We begin with a convex optimization method based on the paper ``Minimizing Effective Resistance of a Graph'' [Ghosh, Boyd \& Saberi]. We show that this (DC) resistive network method can be adapted to the context of AC power flow. However, that does not address the combinatorial aspect of selecting network structure. We approach this problem as selecting a subgraph within an over-complete network, posed as minimizing the (convex) network power dissipation plus a non-convex cost on line conductances that encourages sparse networks where many line conductances are set to zero. We develop a heuristic approach to solve this non-convex optimization problem using: (1) a continuation method to interpolate from the smooth, convex problem to the (non-smooth, non-convex) combinatorial problem, (2) the majorization-minimization algorithm to perform the necessary intermediate smooth but non-convex optimization steps. Ultimately, this involves solving a sequence of convex optimization problems in which we iteratively reweight a linear cost on line conductances to fit the actual non-convex cost. Several examples are presented which suggest that the overall method is a good heuristic for network design. We also consider how to obtain sparse networks that are still robust against failures of lines and/or generators.Comment: 8 pages, 3 figures. To appear in Proc. 49th IEEE Conference on Decision and Control (CDC '10

End-of-life care for non-cancer patients

[Extract]: The origins and early development of palliative care focussed on patients with cancer, apart from sporadic developments in a few non-malignant diseases such as MND and HIV. In the UK, this has been compounded by the setting of palliative care outside the National Health Service, principally funded by cancer-related charities who, at the time were instituted to relieve the suffering associated with cancer. When the modern hospice movement began, the course of malignant disease was seen as more predictable, with a defined palliative phase when anti-cancer treatments were no longer indicated. In the UK and many areas of the world where it was first adopted such as the Canada, USA, mainland Europe and Australia, this led to the traditional model of palliative care services, involved only in people with a prognosis of a few weeks or months. As a result, services have focused primarily on cancer leading to service and symptom management inequalities for equally needy patients with non-malignant diseases

Understanding consumer responses to special event entertainment (SEE) in shopping centres

This paper reviews the literature on the use of entertainment in shopping centres and outlines the constructs believed to impact upon consumer’s responses to special event entertainment. Special event entertainment (SEE) refers to entertainment events or activities that are offered on an occasional, temporary or discontinued basis in shopping centres. Examples of SEE include school holiday entertainment and fashion shows (Parsons, 2003; Sit, Merrilees, & Birch, 2003). Using SEE, shopping centre management seeks to entice consumer patronage, increase patron traffic or promote the shopping centre brand. Despite the popularity of SEE in shopping centres, very little academic research (e.g. Parsons, 2003; Sit, Merrilees, & Birch, 2003) has either conceptually or empirically examined how consumers perceive or respond to SEE. This research presents a conceptual model that examines the determinants and outcomes of consumer responses to SEE, In particular, consumer responses to SEE are represented by SEE proneness and overall appreciation of SEE. These SEE responses are proposed to be determined by sensation-seeking tendencies and perceived value of SEE. Eight propositions are presented to explain the relationships of SEE responses with their determinants and outcomes. These relationships will be empirically tested in future research. Research implications of the conceptual model are also presented

The Diversity of Terrestrial Mammals Surrounding Waterfall at Billy Barquedier National Park

Billy Barquedier is a National Park located in the Stann Creek district of Belize that contains Neotropical vegetation and wildlife. This study was performed to provide a baseline inventory and appearance frequency patterns of the terrestrial mammals located within Zone 1 of the park near a waterfall and to gain a greater understanding of the biodiversity and activity patterns of terrestrial mammals within the park. The methods included camera traps, small Sherman live traps, large live traps, and tracking methods. A non-random sampling method of placing camera traps and live traps on or near human-made or animal-made trails was used to identify the maximum amount of species possible within the eight-week study period. Bait including the local fruit Mamey Apple (Pouteria sapota) was used to attract wildlife to the study area. The hypothesis was at least eight species would be identified during the eight-week study period. The results indicated eleven species were identified, therefore the null hypothesis less than eight species would be identified was rejected and the alternative hypothesis that at least eight species would be identified was accepted. The non- random sampling method introduced bias into the data. Consequently, definite conclusions about relative density and abundance of animals in the area cannot be drawn by this study alone. However, chi-squared tests revealed statistically significant evidence animals appeared more frequently in the central region of the study site, during the first three days the cameras were set out, and during the nighttime hours (2000 to 0459)

Using Predictive Analysis for Meals on Wheels

We are living in the age of data. With the vast multitude of information flowing around us, we have an urgency to keep it, analyze it, and pull what we can from it. For our project, we are helping Meals on Wheels of Northwest Indiana do just that with the information they have. In our project, we will be helping the Meals on Wheels team sift through their data to find the characteristics of their clients, especially those that have signed up to pay for their food, so that they may better market to those individuals. We will be doing this be using Python scripts to clean the data, explore that data with manual review, and then create visualizations and statistics using Bokeh graphing tool, Excel, and other various tools

Lagrangian Relaxation for MAP Estimation in Graphical Models

We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an intractable estimation problem as one defined on a more tractable graph, but subject to additional constraints. Relaxing these constraints gives a tractable dual problem, one defined by a thin graph, which is then optimized by an iterative procedure. When this iterative optimization leads to a consistent estimate, one which also satisfies the constraints, then it corresponds to an optimal MAP estimate of the original model. Otherwise there is a ``duality gap'', and we obtain a bound on the optimal solution. Thus, our approach combines convex optimization with dynamic programming techniques applicable for thin graphs. The popular tree-reweighted max-product (TRMP) method may be seen as solving a particular class of such relaxations, where the intractable graph is relaxed to a set of spanning trees. We also consider relaxations to a set of small induced subgraphs, thin subgraphs (e.g. loops), and a connected tree obtained by ``unwinding'' cycles. In addition, we propose a new class of multiscale relaxations that introduce ``summary'' variables. The potential benefits of such generalizations include: reducing or eliminating the ``duality gap'' in hard problems, reducing the number or Lagrange multipliers in the dual problem, and accelerating convergence of the iterative optimization procedure.Comment: 10 pages, presented at 45th Allerton conference on communication, control and computing, to appear in proceeding