Labelled silhouettes for human pose estimation

This paper proposes a new method of using foreground silhouette images for human pose estimation. Labels are introduced to the silhouette images, providing an extra layer of information that can be used in the model fitting process. The pixels in the silhouettes are labelled according to the corresponding body part in the model of the current fit, with the labels propagated into the silhouette of the next frame to be used in the fitting for the next frame. Both single and multi-view implementations are detailed, with results showing performance improvements over only using standard unlabelled silhouettes.

The osteogenic properties of CaP/silk composite scaffolds

The rationale for the present study was to develop porous CaP/silk composite scaffolds with a CaP-phase distribution and pore architecture better suited to facilitate osteogenic properties of human bone mesenchymal stromal cells (BMSCs) and in vivo bone formation abilities. This was achieved by first preparing CaP/silk hybrid powders which were then incorporated into silk to obtain uniform CaP/silk composite scaffolds, by means of a freeze-drying method. The composition, microstructure and mechanical properties of the CaP/silk composite scaffolds were ascertained by X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), scanning electron microscope (SEM) and a universal mechanical testing machine. BMSCs were cultured in these scaffolds and cell proliferation analyzed by confocal microscopy and MTS assay. Alkaline phosphatase (ALP) activity and osteogenic gene expression were assayed to determine if osteogenic differentiation had taken place. A calvarial defect model in SCID mice was used to determine the in vivo bone forming ability of the hybrid CaP/silk scaffolds. Our results showed that incorporating the hybrid CaP/silk powders into silk scaffolds improved both pore structure architecture and distribution of CaP powders in the composite scaffolds. By incorporating the CaP phase into silk scaffolds in vitro osteogenic differentiation of BMSCs was enhanced and there was increased in vivo cancellous bone formation. Here we report a method with which to prepare Ca/P composite scaffolds with a pore structure and Ca/P distribution better suited to facilitate BMSC differentiation and bone formation.

Examining the role of human resource management in continuous improvement

The objective of this paper is to take a first step in developing a theoretical framework describing the role of HRM in successful CI, based on the current literature from both fields. To this end, elements from the CI Maturity Model and a framework depicting the role of HRM in innovation serve as a foundation for examining how specific bundles of HRM practices utilised during different phases of the CI implementation process may contribute to sustained organisational and enhanced operational performance. The primary contribution of this paper is theoretical; however, the framework has practical value in that it suggests important relationships between HRM practices and behaviours necessary for successful CI. A preliminary test of the framework in an empirical setting is summarised at the conclusion of this paper, where a number of possible research avenues are also suggested.

MiLK. Mobile Learning Kit

The Mobile Learning Kit is a new digital learning application that allows students and teachers to compose, publish, discuss and evaluate their own mobile learning games and events. The research field was interaction design in the context of mobile learning. The research methodology was primarily design-based supported by collaboration between participating disciplines of game design, education and information technology. As such, the resulting MiLK application is a synthesis of current pedagogical models and experimental interaction design techniques and technologies. MiLK is a dynamic learning resource for incorporating both formal and informal teaching and learning practices while exploiting mobile phones and contemporary digital social tools in innovative ways. MiLK explicitly addresses other predominant themes in educational scholarship that relate to current education innovation and reform such as personalised learning, life-long learning and new learning spaces. The success of this project is indicated through rigorous trials and actual uptake of MiLK by international participants in Australia, UK, US and South Africa. MiLK was awarded for excellence in the use of emerging technologies for improved learning and teaching as a finalist (top 3) in the Handheld Learning and Innovation Awards in the UK in 2008. MiLK was awarded funding from the Australasian CRC for Interaction Design in 2008 to prepare the MiLK application for development. MiLK has been awarded over $230,000 from ACID since 2006. The resulting application and research materials are now being commercialised by a new company, ‘ACID Services’.

The 10% rule. Maximising learning through collaborative game design

This paper presents a retrospective view of a game design practice that recently switched from the development of complex learning games to the development of simple authoring tools for students to design their own learning games for each other. We introduce how our ‘10% Rule’, a premise that only 10% of what is learnt during a game design process is ultimately appreciated by the player, became a major contributor to the evolving practice. We use this rule primarily as an analytical and illustrative tool to discuss the learning involved in designing and playing learning games rather than as a scientifically and empirically proven rule. The 10% rule was promoted by our experience as designers and allows us to explore the often overlooked and valuable learning processes involved in designing learning games and mobile games in particular. This discussion highlights that in designing mobile learning games, students are not only reflecting on their own learning processes through setting up structures for others to enquire and investigate, they are also engaging in high-levels of independent inquiry and critical analysis in authentic learning settings. We conclude the paper with a discussion of the importance of these types of learning processes and skills of enquiry in 21st Century learning.

Farm it right : the sustainable farming simulation

Farm It Right is an innovative creative work that simulates sustainable farming techniques using ecological models prepared by academics at Bradford University (School of Life Sciences). This interactive work simulates the farming conditions and options of our ancestors and demonstrates the direct impact their actions had on their environment and on the ’future of their cultures’ (Schmidt 2008). Specifically, the simulation allows users to explore and experiment with the complex relationships between environmental factors and human decision making within the harsh conditions of an early (9th century) Nordic farm. The simulation interface displays both statistical and graphical feedback in response to the users selections regarding animal reproduction rates, shelter provisions, food supplies etc. as well as demonstrating resulting impacts to soil erosion, water supply, animal population sizes etc.---------- 'Farm It Right' is now used at Bradford University (School of Life Sciences) as a dynamic e-Learning resource for incorporating environmental archaeology with sustainable development education, improving the engagement with complex data and the appreciation of human impacts on the environment and the future of their cultures. 'Farm It Right' is also demonstrated as an exemplar case study for interaction design students at Queensland University of Technology.

Designing spatial story-telling software

What does it mean when we design for accessibility, inclusivity and "dissolving boundaries" -- particularly those boundaries between the design philosophy, the software/interface actuality and the stated goals? This paper is about the principles underlying a research project called 'The Little Grey Cat engine' or greyCat. GreyCat has grown out of our experience in using commercial game engines as production environments for the transmission of culture and experience through the telling of individual stories. The key to this endeavour is the potential of the greyCat software to visualize worlds and the manner in which non-formal stories are intertwined with place. The apparently simple dictum of "show, don't tell" and the use of 3D game engines as a medium disguise an interesting nexus of problematic issues and questions, particularly in the ramifications for cultural dimensions and participatory interaction design. The engine is currently in alpha and the following paper is its background story. In this paper we discuss the problematic, thrown into sharp relief by a particular project, and we continue to unpack concepts and early designs behind the greyCat itself.

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.

ACE's role in developing Australia's human capital : a structural analysis

This project explored ways in which Adult and Community Education (ACE) could make a greater contribution to the human capital development outcome under the National Reform Agenda (NRA), and increase the number of skilled workers in Australia. Data on current vocational and non-vocational ACE programs was analysed. Strategies to improve ACE were collated for consideration by government authorities and ACE providers. There is much diversity in the perceived role and activities of ACE. Researchers have found it challenging to create a profile that depicts the whole sector, particularly in the absence of much reliable, valid and comparable data on ACE activities and outcomes. However, there is evidence indicative of ACE’s assistance in re-engaging with learning and training, and initiating pathways to further training or employment. The potential for ACE to make a bigger contribution to skilling Australia is recognised by governments across the nation (Senate Employment, Workplace Relations, Small Business and Education Committee, 1997). Yet policy changes to facilitate an increased role of ACE in the skilling process, and resourcing for ACE programs continue to receive less attention. This project explored three research questions: • What does the current profile of the ACE sector look like? • How is ACE contributing to reducing the skills deficit? • How can ACE enhance its contributions to reduce the skills deficit and achieve the human capital development outcome of the National Reform Agenda? The responsiveness

Work ethic, protestantism and human capital

Weber's contribution on Protestant work ethic has stimulated numerous social scientists. However, the question whether a Protestant specific work ethic exists at all is still rarely analysed. Our results indicate that work ethic is influenced by denomination-based religiosity and education.

The Federal circuit in Bilski : the machine-or-transformation test

In a much anticipated judgment, the Federal Circuit has sought to clarify the standards applicable in determining whether a claimed method constitutes patent-eligible subject matter. In Bilski, the Federal Circuit identified a test to determine whether a patentee has made claims that pre-empt the use of a fundamental principle or an abstract idea or whether those claims cover only a particular application of a fundamental principle or abstract idea. It held that the sole test for determining subject matter eligibility for a claimed process under § 101 is that: (1) it is tied to a particular machine or apparatus, or (2) it transforms a particular article into a different state or thing. The court termed this the “machine-or-transformation test.” In so doing it overruled its earlier State Street decision to the extent that it deemed its “useful, tangible and concrete result” test as inadequate to determine whether an alleged invention recites patent-eligible subject matter.

Automated control of a dragline using machine vision

The research described in this paper is directed toward increasing productivity of draglines through automation. In particular, it focuses on the swing-to-dump, dump, and return-to-dig phases of the dragline operational cycle by developing a swing automation system. In typical operation the dragline boom can be in motion for up to 80% of the total cycle time. This provides considerable scope for improving cycle time through automated or partially automated boom motion control. This paper describes machine vision based sensor technology and control algorithms under development to solve the problem of continuous real time bucket location and control. Incorporation of this capability into existing dragline control systems will then enable true automation of dragline swing and dump operations.

Vision-based detection and tracking of aerial targets for UAV collision avoidance

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.

Evidence-based practice : information professionals' experience of information literacy in the workplace

Evidence-based practice is increasingly being recognised as an important issue in a range of professional contexts including education, nursing, occupational therapy and librarianship. Many of these professions have observed a relationship or interface between evidence-based practice and information literacy. Using a phenomenographic approach this research explores variation in the how library and information professionals are experiencing evidence-based practice as part of their professional work. The findings of the research provide a basis for arguing that evidence-based practice represents the professional's enactment of information literacy in the workplace.

Airborne vision-based collision-detection system

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.