An evaluation framework for cross-lingual link discovery

Cross-Lingual Link Discovery (CLLD) is a new problem in Information Retrieval. The aim is to automatically identify meaningful and relevant hypertext links between documents in different languages. This is particularly helpful in knowledge discovery if a multi-lingual knowledge base is sparse in one language or another, or the topical coverage in each language is different; such is the case with Wikipedia. Techniques for identifying new and topically relevant cross-lingual links are a current topic of interest at NTCIR where the CrossLink task has been running since the 2011 NTCIR-9. This paper presents the evaluation framework for benchmarking algorithms for cross-lingual link discovery evaluated in the context of NTCIR-9. This framework includes topics, document collections, assessments, metrics, and a toolkit for pooling, assessment, and evaluation. The assessments are further divided into two separate sets: manual assessments performed by human assessors; and automatic assessments based on links extracted from Wikipedia itself. Using this framework we show that manual assessment is more robust than automatic assessment in the context of cross-lingual link discovery.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.

A bondgraph approach to formation control using relative state measurements

In this paper we apply port-Hamiltonian theory with the bondgraph modelling approach to the problem of formation control using partial measurements of relative positions. We present a control design that drives a group of vehicles to a desired formation without requiring inter-vehicle communications or global position and velocity measurements to be available. Our generic approach is applicable to any form of relative measurement between vehicles, but we specifically consider the important cases of relative bearings and relative distances. In the case of bearings, our theory closely relates to the field of image-based visual servo (IBVS) control. We present simulation results to support the developed theory.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Attitudinal, normative, and control beliefs underlying people’s curbside household waste recycling decisions

This study examined the beliefs underlying people’s decision-making, from a theory of planned behaviour (TPB) framework, in the prediction of curbside household waste recycling. Community members in Brisbane, Australia (N = 148) completed a questionnaire assessing the belief based TPB measures of attitudinal beliefs (costs and benefits), normative beliefs (important referents), and control beliefs (barriers) in relation to engaging in curbside household waste recycling for a 2-week period. Two weeks later, participants completed self report measures of recycling behaviour for the previous fortnight. The results revealed that the attitudinal, normative, and control beliefs for people who performed higher and lower levels of recycling differed significantly. A regression analysis identified both normative and control beliefs as the main determinants of recycling behaviour. For normative beliefs, high level recyclers perceived more approval from referents such as partners, friends, and neighbours to recycle all eligible materials. In addition, the strong results for control beliefs indicated that barriers such as forgetfulness, lack of time, and laziness were rated as more likely to hamper optimal recycling performance for low level recyclers. These findings provide important applied information about beliefs to target in the development of future community recycling campaigns.

Development and use of risk adjusted statistical process control tools for the monitoring and improvement of clinical outcomes in interventional cardiology

This thesis explored the development of statistical methods to support the monitoring and improvement in quality of treatment delivered to patients undergoing coronary angioplasty procedures. To achieve this goal, a suite of outcome measures was identified to characterise performance of the service, statistical tools were developed to monitor the various indicators and measures to strengthen governance processes were implemented and validated. Although this work focused on pursuit of these aims in the context of a an angioplasty service located at a single clinical site, development of the tools and techniques was undertaken mindful of the potential application to other clinical specialties and a wider, potentially national, scope.

Analysis of 3 common polymorphisms in the KCNK18 gene in an Australian migraine case-control cohort

Migraine is a common neurological disorder characterised by temporary disabling attacks of severe head pain and associated disturbances. There is significant evidence to suggest a genetic aetiology to the disease however few causal mutations have been conclusively linked to the migraine subtypes Migraine with (MA) or without Aura (MO). The Potassium Channel, Subfamily K, member 18 (KCNK18) gene, coding the potassium channel TRESK, is the first gene in which a rare mutation resulting in a non-functional truncated protein has been identified and causally linked to MA in a multigenerational family. In this study, three common polymorphisms in the KCNK18 gene were analysed for genetic variation in an Australian case-control migraine population consisting of 340 migraine cases and 345 controls. No association was observed for the polymorphisms examined with the migraine phenotype or with any haplotypes across the gene. Therefore even though the KCNK18 gene is the only gene to be causally linked to MA our studies indicate that common genetic variation in the gene is not a contributor to MA.