High impact training : achieving synergies between program management education and workplace practice

This paper addresses the challenges of transfer of training back to the workplace for programme and project managers who are being groomed for the leadership of large and complex projects. The paper draws on the experience of the development and delivery of Queensland University of Technology (QUT) education programs: an Executive Masters of Complex Project Management and a series of Continuing Professional Development (CPD) events for an Australian government agency, Defence Materiel Organisation (DMO). Drawing on notions of ‘far transfer’ (Laker 1990; Noe, 1986) and ‘transfer climate’ (Kozlowski & Salas, 1993; Yamnill & McLean, 2001), the paper describes the steps undertaken to achieve a design that ensures that programme and project leadership skills developed through these corporate education programs become successfully embedded back in the organisation. Further, the paper reports on a small qualitative study where the programme success was evaluated by the organisational sponsor, senior leaders and program participants. Nine interviews were conducted and analysed to identify the success of far transfer and transfer climate four months after the return of program participants from cohort 1 2008 to the workplace.

Open content creation : the issues of voice and the challenges of listening

This paper examines the proposition that increased ability to have a voice and be listened to, through ‘open ICT4D’ and ‘open content creation’ can be an effective mechanism for development. The paper discusses empirical work that strongly indicates that this only happens when voice is appropriately valued in the development process. Having a voice in development processes are less effective when participation is limited. Open ICT allows for more and more voices to be heard, but it is open ICT4D that has the obligation to ensure voices are listened to. In the paper I first explore participatory development and the idea of open ICT4D before elaborating on issues of voice and thinking about voice as process, and voice as value. Research findings are presented from research that experimented with participatory (or open) content creation, discussed in relation to notions of openness and voice. I then consider the challenges of listening, before drawing some conclusions about opening up ICT4D research.

Creating and sustaining a basis for life-long learning in tertiary dancer training

This paper acknowledges the influences that a generation Y population brings to dance training methodologies and examines this impact in a tertiary context. Over the last 4 years, Queensland University of Technology has been modifying their curriculum for new students transitioning from the private dance studio into the prevocational university environment. An intensive training program was designed to empower the student creating effective entry points for common understandings in the learning and teaching of dance techniques with improved and accelerated learning outcomes. This paper shares these philosophies and practices in training for life-long learning that prepare the young dancer for longevity in the industry.

Two voices : the marginalised body as a voice & Imperfect Offerings a novel

This thesis investigates the phenomenon of self-harm as a form of political protest using two different, but complementary, methods of inquiry: a theoretical research project and a novel. Through these two approaches, to the same research problem, I examine how we can re-position the body that self-harms in political protest from weapon to voice; and in doing so find a path towards ethical and equitable dialogue between marginalised and mainstream communities. The theoretical, or academic, portion of the thesis examines self-harm as protest, positing these acts as a form of tactical selfharm, and acknowledge its emergence as a voice for the otherwise silenced in the public sphere. Through the use of phenomenology and feminist theory I examine the body as site for political agency, the circumstances which surround the use of the body for protest, and the reaction to tactical self-harm by the individual and the state. Using Bakhtin’s concept of dialogism, and the dialogic space I propose that by ‘hearing’ the body engaged in tactical selfharm we come closer to entering into an ethical dialogue with the otherwise silenced in our communities (locally, nationally and globally). The novel, Imperfect Offerings, explores these ideas in a fictional world, and allows me to put faces, names and lives to those who are compelled to harm their bodies to be heard. Also using Bakhtin’s framework I encourage a dialogue between the critical and creative parts of the thesis, challenging the traditional paradigm of creative PhD projects as creative work and exegesis.

Improving automatic speaker verification using SVM techniques

Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

Rephrasing voice : art, practice-led research and the limits and sites of articulacy

While my PhD is practice-led research, it is my contention that such an inquiry cannot develop as long as it tries to emulate other models of research. I assert that practice-led research needs to account for an epistemological unknown or uncertainty central to the practice of art. By focusing on what I call the artist's 'voice,' I will show how this 'voice' is comprised of a dual motivation—'articulate' representation and 'inarticulate' affect—which do not even necessarily derive from the artist. Through an analysis of art-historical precedents, critical literature (the work of Jean-François Lyotard and Andrew Benjamin, the critical methods of philosophy, phenomenology and psychoanalysis) as well as of my own painting and digital arts practice, I aim to demonstrate how this unknown or uncertain aspect of artistic inquiry can be mapped. It is my contention that practice-led research needs to address and account for this dualistic 'voice' in order to more comprehensively articulate its unique contribution to research culture.

Research training and national innovation systems in Australia, Finland and the United States : a policy and systems study supported by 30 case studies of research students in the fields of geospatial science, wireless communication, biosciences, and materials science and engineering

Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.

Training and development for transitional employment in mature-aged manual workers

The purpose of the current article was to explore perceptions of transitional employment and training and development amongst blue collar workers employed in technical, trade, operations or physical and labour-intensive occupations within the local government system.

Do research thesis examiners need training? : practitioner stories

We are thesis examiners within the Australian academic system who formed a “community of practice” to try to resolve some of the issues we were facing. Stories of examiners reflecting on and examining their own practice are a notable silence in the higher degree research literature. In this study we have adopted a storytelling inquiry method that involved telling our practitioner stories, firstly to each other and then to a wider audience through this paper. We then identified issues that we believe are relevant to other thesis examiners. We have also found that engaging in a “community of practice” is itself a valuable form of examiner professional development. Key Words: Thesis Examiner Training, Storytelling, and Practitioner Research

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

Cascading appearance-based features for visual voice activity detection

The detection of voice activity is a challenging problem, especially when the level of acoustic noise is high. Most current approaches only utilise the audio signal, making them susceptible to acoustic noise. An obvious approach to overcome this is to use the visual modality. The current state-of-the-art visual feature extraction technique is one that uses a cascade of visual features (i.e. 2D-DCT, feature mean normalisation, interstep LDA). In this paper, we investigate the effectiveness of this technique for the task of visual voice activity detection (VAD), and analyse each stage of the cascade and quantify the relative improvement in performance gained by each successive stage. The experiments were conducted on the CUAVE database and our results highlight that the dynamics of the visual modality can be used to good effect to improve visual voice activity detection performance.