An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

Learning object dynamics for smooth tracking of moving lip contours

A new technique is proposed for learning the dynamic characteristics of a deformable object, applied in particular to the problem of lip-tracking. Experimental results are given which demonstrate that the use of dynamic models allows the system to track more robustly under adverse conditions and to correct spurious, poorly tracked frames

Reflections on music therapy with Indigenous families : cultural learning put into practice

This paper will describe the process of learning and development that occurred when the Sing & Grow prevention and early intervention project began to provide services to Indigenous families, a relatively new area or music therapy, particularly in Brisbane. The first attempt at establishing a weekly group music therapy program for Indigenous families was not as successful as anticipated; however through analysis of the contributing factors, guidelines were developed and implemented in the following program, which resulted in a positive learning experience for the families and therapists involved.

Scaffolding techniques : a teacher training for cooperative learning in Thailand primary education

In general, the benefits of using cooperative learning include academic achievement, communication skills, problem-solving, social skills and student motivation. Yet cooperative learning as a Western educational concept may be ineffective in a different learning system. The study aims to investigate scaffolding techniques for cooperative learning in Thailand primary education. The program was designed to foster Thai primary school teachers’ cooperative learning implementation that includes the basic tenets of cooperative learning and socio-cognitive based learning. Two teachers were invited to participate in this experimental teacher training program for one and a half weeks. Then the teachers implemented a cooperative learning in their mathematics class for six weeks. The data from teacher interview and classroom observation indicated that the both teachers are able to utilise questions to scaffold their students’ engagement in cooperative learning. This initiative study showed that difficulty or failure of implementing cooperative learning in Thailand education may not be derived from cultural difference. The paper discussed the techniques the participant teachers applied with proactive scaffolding, reactive scaffolding and scaffolding questions that can be used to facilitate the implementation of cooperative learning in Thai school.

Theorising a model for teaching and assessing reflective learning in higher education

The importance of reflection in higher education, and across disciplinary fields is widely recognised; it is generally included in university graduate attributes, professional standards and program objectives. Furthermore, reflection is commonly embedded into assessment requirements in higher education subjects, often without necessary scaffolding or clear expectations for students. Despite the rhetoric around the importance of reflection for ongoing learning, there is scant literature on any systematic, developmental approach to teaching reflective learning across higher education programs/courses. Given that professional or academic reflection is not intuitive, and requires specific pedagogic intervention to do well, a program/course-wide approach is essential. This paper draws on current literature to theorise a new, transferable and customisable model for teaching and assessing reflective learning across higher education, which foregrounds and explains the pedagogic field of higher education as a multi-dimensional space. We argue that explicit and strategic pedagogic intervention, supported by dynamic resources, is necessary for successful, broad-scale approaches to reflection in higher education.

Ontology learning from user tagging for recommendation making

Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging into some form of ontology, but the application of the resulted ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

Application of machine learning in fault diagnostics of mechanical systems

A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.

REGAL : a regularization based algorithm for reinforcement learning in weakly communicating MDPs

We provide an algorithm that achieves the optimal regret rate in an unknown weakly communicating Markov Decision Process (MDP). The algorithm proceeds in episodes where, in each episode, it picks a policy using regularization based on the span of the optimal bias vector. For an MDP with S states and A actions whose optimal bias vector has span bounded by H, we show a regret bound of ~ O(HS p AT ). We also relate the span to various diameter-like quantities associated with the MDP, demonstrating how our results improve on previous regret bounds.

An ecological footprint for an early learning centre : identifying opportunities for early childhood sustainability education through interdisciplinary research

In this study, engineers and educators worked together to adapt and apply the ecological footprint (EF) methodology to an early learning centre in Brisbane, Australia. Results were analysed to determine how environmental impact can be reduced at the study site and more generally across early childhood settings. It was found that food, transport and energy consumption had the largest impact on the centre’s overall footprint. In transport and energy, early childhood centres can reduce their impact through infrastructure and cultural change, in association with changed curriculum strategies. Building design, the type of energy purchased and appliance usage can all be modified to reduce the energy footprint. The transport footprint can be reduced through more families using active and public transport, which can be encouraged by providing information, support and facilities and appropriate siting of new centres. Introducing the concept of ecological footprint in early childhood education may be an effective way to educate children, staff and parents on the links between the food they eat, land usage and environmental impact. This study responds directly to the call in this journal for research focused on early childhood education and for more to be made of interdisciplinary research opportunities.

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.

Assessment policy change in relation to English language teaching and learning in China : a study of perspectives from two universities

In response to concerns about the quality of English Language Learning (ELL) education at tertiary level, the Chinese Ministry of Education (CMoE) launched the College English Reform Program (CERP) in 2004. By means of a press release (CMoE, 2005) and a guideline document titled College English Curriculum Requirements (CECR) (CMoE, 2007), the CERP proposed two major changes to the College English assessment policy, which were: (1) the shift to optional status for the compulsory external test, the College English Test Band 4 (CET4); and (2) the incorporation of formative assessment into the existing summative assessment framework. This study investigated the interactions between the College English assessment policy change, the theoretical underpinnings, and the assessment practices within two Chinese universities (one Key University and one Non-Key University). It adopted a sociocultural theoretical perspective to examine the implementation process as experienced by local actors of institutional and classroom levels. Systematic data analysis using a constant comparative method (Merriam, 1998) revealed that contextual factors and implementation issues did not lead to significant differences in the two cases. Lack of training in assessment and the sociocultural factors such as the traditional emphasis on the product of learning and hierarchical teacher/students relationship are decisive and responsible for the limited effect of the reform.

Support teachers, learning difficulties and secondary school culture

This thesis will report on mixed method research which examined secondary Support Teachers Learning Difficulties (STLDs) and their modes of operation in New South Wales (NSW) government schools, Australia. Four modes of operation were identified in the literature as consultancy, team teaching, in-class support and withdrawal. An additional area of other duties was also included to examine the time when STLDs were not functioning in the four identified modes of operation. NSW government policy is in keeping with the literature as it recommends that STLDs should spend the majority of their time in consultancy and team teaching while in class with a minimum of withdrawal of students from their main classrooms for individual or small group instruction. STLDs, however, did not appear to be functioning in the recommended way. A number of factors identified in the literature, which may influence the modes of operation, can be grouped under the heading of school culture thus this research involved the examination of the effects of school culture on the modes of operation with the aim of expanding our understanding of the functioning of STLDs and providing suggestions for improvement. The theoretical base of social constructionism has informed this research which included survey and case study methods. Case studies of the STLDs in three secondary schools led to the conclusion that, in conjunction with factors such as flexibility and commitment, the involvement of the STLD in a sub-culture of learning support may lead to functioning in the recommended modes of operation.

Towards a global carbon integrity system : learning from the GFC and avoiding a GCC

This paper examines some of the central global ethical and governance challenges of climate change and carbon emis-sions reduction in relation to globalization, the “global financial crisis” (GFC), and unsustainable conceptions of the “good life”, and argues in favour of the development of a global carbon “integrity system”. It is argued that a funda-mental driver of our climate problems is the incipient spread of an unsustainable Western version of the “good life”, where resource-intensive, high-carbon western lifestyles, although frequently criticized as unsustainable and deeply unsatisfying, appear to have established an unearned ethical legitimacy. While the ultimate solution to climate change is the development of low carbon lifestyles, the paper argues that it is also important that economic incentives support and stimulate that search: the sustainable versions of the good life provide an ethical pull, whilst the incentives provide an economic push. Yet, if we are going to secure sustainable low carbon lifestyles, it is argued, we need more than the ethical pull and the economic push. Each needs to be institutionalized—built into the governance of global, regional, national, sub-regional, corporate and professional institutions. Where currently weakness in each exacerbates the weaknesses in others, it is argued that governance reform is required in all areas supporting sustainable, low carbon versions of the good life.

Early years teachers’ epistemic beliefs and beliefs about children’s moral learning

There is strong political and social interest in values education both internationally and across Australia. Investment in young children is recognised as important for the development of moral values for a cohesive society; however, little is known about early years teachers’ beliefs about moral values teaching and learning. The aim of the current study was to investigate the relationships between Australian early years teachers’ epistemic beliefs and their beliefs about children’s moral learning. Three hundred and seventy-nine teachers completed a survey about their personal epistemic beliefs and their beliefs about children’s moral learning. Results indicated that teachers with more sophisticated epistemic beliefs viewed children as capable of taking responsibility for their own moral learning. Conversely, teachers who held more naive or simplistic personal epistemic beliefs agreed that children need to learn morals through learning the rules for behaviour. Results are discussed in terms of the implications for moral pedagogy in the classroom and teacher professional development. It is suggested that in conjunction with explicitly reflecting on epistemic beliefs, professional development may need to assist teachers to ascertain how their beliefs might relate to their moral pedagogies in order to make any adjustments.