UAS Classification: Key to effective airworthiness and operational regulations

This presentation discusses some of the general issues relating to the classification of UAS for the purposes of defining and promulgating safety regulations. One possible approach for the definition of a classification scheme for UAS Type Certification Categories reviewed.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Indigenous knowledge and effective parent / school partnerships : insights and issues from 4 school case studies

Towards the last decade of the last millennium, Indigenous knowledge has been central to scholarly debates relating to decolonising knowledge on a global level. Much of these debates were advanced by Indigenous scholars in colonised countries particularly Australia, New Zealand, Canada and the United States. Indigenous scholars argue for the location of Indigenous knowledge as the epistemological standpoint (Battiste, Bell and Findlay, 2002; Kai’a, 2005; Nakata 2002, 2007) for intellectual engagements and methodology for resisting colonial constructions of the colonised other (Rigney, 1997; Smith, 1999, 2005). However, the challenge to engage Indigenous knowledge to inform research and educational processes, in many respects, is still a contested debate in western-oriented universities and institutions of higher education. The place of Indigenous knowledge in Australian secondary and primary schools remains vague, while efforts to embed Indigenous perspectives in the curriculum continue to be made by both government and private educational providers. Educational funding for Indigenous education continues to operate from a ‘deficiency’ model, whereby educational outcomes are often measured against set criteria, reflecting a pass/fail structure, than a more comprehensive investigation of educational outcomes and quality of learning experiences. Teacher knowledge, effective parental and community engagement into students’ learning and students’ experiences of schooling continue to be secondary to students’ final results. This paper presents preliminary findings of Parent School Partnership Initiative (PSPI) project conducted by the Oodgeroo Unit at the Queensland University of Technology in partnerships with the Aboriginal and Torres Strait Islander Education Focus Group for the Caboolture Shire, in South East Queensland. The state government sponsored initiative was to examine factors that promote and enhance parent/school engagement with their students’ schooling, and to contribute to Aboriginal and Torres Strait Islander students’ learning and completion of secondary schooling within the participating schools in a more holistic way. We present four school case studies and discuss some of the early findings. We conclude by arguing the importance of the recognition of Indigenous knowledge and its place in enhancing parent – schools partnerships.

The role of legislative, executive and judicial mechanisms in ensuring a fair and effective asylum process

A good faith reading of core international protection obligations requires that states employ appropriate legislative, administrative and judicial mechanisms to ensure the enjoyment of a fair and effective asylum process. Restrictive asylum policies instead seek to ‘denationalize’ the asylum process by eroding access to national statutory, judicial and executive safeguards that ensure a full and fair hearing of an asylum claim. From a broader perspective, the argument in this thesis recognizes hat international human rights depend on domestic institutions for their effective implementation, and that a rights-based international legal order requires that power is limited, whether that power is expressed as an instance of the sovereign right of states in international law or as the authority of governments under domestic constitutions.

Post-disaster housing reconstruction : challenges for effective community participation

The extant literature suggests that community participation is an important ingredient for the successful delivery of post-disaster housing reconstruction projects. Even though policy-makers, international funding bodies and non-governmental organisations broadly appreciate the value of community participation, post-disaster reconstruction practices systematically fail to follow, or align with, existing policy statements. Research into past experiences has led many authors to argue that post-disaster reconstruction is the least successful physically visible arena of international cooperation. Why is the principle of community participation not evident in the veracity of reconstructions already carried out on the ground? This paper discusses and develops the concepts of, and challenges to, community participation and the subsequent negative and positive effects on post-disaster reconstruction projects outcomes.

Knowledge translation for effective consumers

With the emergence of patient-centered care, consumers are becoming more effective managers of their care—in other words, “effective consumers.” To support patients to become effective consumers, a number of strategies to translate knowledge to action (KTA) have been used with varying success. The use of a KTA framework can be helpful to researchers and implementers when framing, planning, and evaluating knowledge translation activities and can potentially lead to more successful activities. This article briefly describes the KTA framework and its use by a team based out of the University of Ottawa to translate evidence-based knowledge to consumers. Using the framework, tailored consumer summaries, decision aids, and a scale to measure consumer effectiveness were created in collaboration with consumers. Strategies to translate the products into action then were selected and implemented. Evaluation of the knowledge tools and products indicates that the products are useful to consumers. Current research is in place to monitor the use of these products, and future research is planned to evaluate the effect of using the knowledge on health outcomes. The KTA framework provides a useful and valuable approach to knowledge translation.

Automatic generation of effective video summaries

As the popularity of video as an information medium rises, the amount of video content that we produce and archive keeps growing. This creates a demand for shorter representations of videos in order to assist the task of video retrieval. The traditional solution is to let humans watch these videos and write textual summaries based on what they saw. This summarisation process, however, is time-consuming. Moreover, a lot of useful audio-visual information contained in the original video can be lost. Video summarisation aims to turn a full-length video into a more concise version that preserves as much information as possible. The problem of video summarisation is to minimise the trade-off between how concise and how representative a summary is. There are also usability concerns that need to be addressed in a video summarisation scheme. To solve these problems, this research aims to create an automatic video summarisation framework that combines and improves on existing video summarisation techniques, with the focus on practicality and user satisfaction. We also investigate the need for different summarisation strategies in different kinds of videos, for example news, sports, or TV series. Finally, we develop a video summarisation system based on the framework, which is validated by subjective and objective evaluation. The evaluation results shows that the proposed framework is effective for creating video skims, producing high user satisfaction rate and having reasonably low computing requirement. We also demonstrate that the techniques presented in this research can be used for visualising video summaries in the form web pages showing various useful information, both from the video itself and from external sources.

Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.