Moomba - A collaborative environment for supporting distributed extreme programming in global software development

Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.

Scalable Visualization of Galaxies, Oceans, and Brains

One of the challenges in scientific visualization is to generate software libraries suitable for the large-scale data emerging from tera-scale simulations and instruments. We describe the efforts currently under way at SDSC and NPACI to address these challenges. The scope of the SDSC project spans data handling, graphics, visualization, and scientific application domains. Components of the research focus on the following areas: intelligent data storage, layout and handling, using an associated “Floor-Plan” (meta data); performance optimization on parallel architectures; extension of SDSC’s scalable, parallel, direct volume renderer to allow perspective viewing; and interactive rendering of fractional images (“imagelets”), which facilitates the examination of large datasets. These concepts are coordinated within a data-visualization pipeline, which operates on component data blocks sized to fit within the available computing resources. A key feature of the scheme is that the meta data, which tag the data blocks, can be propagated and applied consistently. This is possible at the disk level, in distributing the computations across parallel processors; in “imagelet” composition; and in feature tagging. The work reflects the emerging challenges and opportunities presented by the ongoing progress in high-performance computing (HPC) and the deployment of the data, computational, and visualization Grids.

Caring for someone with dementia in a rural town .2. Services

Dementia care in rural areas is in need of attention from researchers, planners and policy makers. Family carers in these areas face some significant challenges, in terms of managing the care where support services are often unavailable or inaccessible. This paper reports on a qualitative study in which a group of rural based carers participated in a focus group and interviews. Through this process, the carers' perceptions of support services were explored. Content analysis of the data revealed that, despite a number of supportive aspects of rural life, these carers felt in need of more services, a finding supported by current literature.

Recent advances in the preparation and utilization of carbon nanotubes for hydrogen storage

Recent progress in the production, purification, and experimental and theoretical investigations of carbon nanotubes for hydrogen storage are reviewed. From the industrial point of view, the chemical vapor deposition process has shown advantages over laser ablation and electric-arc-discharge methods. The ultimate goal in nanotube synthesis should be to gain control over geometrical aspects of nanotubes, such as location and orientation, and the atomic structure of nanotubes, including helicity and diameter. There is currently no effective and simple purification procedure that fulfills all requirements for processing carbon nanotubes. Purification is still the bottleneck for technical applications, especially where large amounts of material are required. Although the alkali-metal-doped carbon nanotubes showed high H-2 Weight uptake, further investigations indicated that some of this uptake was due to water rather than hydrogen. This discovery indicates a potential source of error in evaluation of the storage capacity of doped carbon nanotubes. Nevertheless, currently available single-wall nanotubes yield a hydrogen uptake value near 4 wt% under moderate pressure and room temperature. A further 50% increase is needed to meet U.S. Department of Energy targets for commercial exploitation. Meeting this target will require combining experimental and theoretical efforts to achieve a full understanding of the adsorption process, so that the uptake can be rationally optimized to commercially attractive levels. Large-scale production and purification of carbon nanotubes and remarkable improvement of H-2 storage capacity in carbon nanotubes represent significant technological and theoretical challenges in the years to come.

Innovation in Queensland firms: implications for the smart State

The challenges in the business environment are forcing Australian firms to be innovative in all their efforts to serve customers. Reflecting this need there have been several innovation policy statements both at Federal and State government level aimed at encouraging innovation in Australian industry. In particular, the innovation policy statement launched by the Queensland government in the year 2000 primarily intends building a Sman State through innovation. During the last few decades the Australian government policy on innovation has emphasized support for industry R&D. However industry stakeholders demand a more firm-focused policy of innovation. Government efforts in this direction have been hindered by a lack of a consistent body of knowledge on innovation at the firm level. In particular the Australian literature focusing on firm level antecedents of innovation is limited and fragmented. This study examines the role of learning capabilities in innovation and competitive advantage. Based on a survey of manufacturing firms in Queensland the study finds that both technological and non·technological innovations lead to competitive advantage. The findings contribute to the theory competitive advantage and firm level antecedents of innovation. Implications for firm level innovation strategies and behaviour are discussed. In addition, the findings have important implications for Queensland government's current initiatives to build a Smart State through innovation.

Australia's Security and the threat of Islamic Extremism in Southeast Asia

Australian foreign and security policy confronts a series of difficult challenges in coping with the emergence of an Islamic extremist threat in Southeast Asia. Australian policy makers are being drawn into unfamiliar linkages with moderate Islam, and into closer cooperation with Indonesia, the most populous Islamic nation in the world, in an attempt to offset Islamic extremists. Further, they must achieve those objectives at a time when important interests are at stake beyond Southeast Asia, when bipartisan agreement about the direction of foreign policy is waning, and when divisions over the appropriate trajectory of Australian security policy are intense. A delicacy almost unprecedented in Australian foreign policy will be required.

On systems thinking, systems biology and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

Accounting for uncertainty in marine reserve design

Ecosystems and the species and communities within them are highly complex systems that defy predictions with any degree of certainty. Managing and conserving these systems in the face of uncertainty remains a daunting challenge, particularly with respect to developing networks of marine reserves. Here we review several modelling frameworks that explicitly acknowledge and incorporate uncertainty, and then use these methods to evaluate reserve spacing rules given increasing levels of uncertainty about larval dispersal distances. Our approach finds similar spacing rules as have been proposed elsewhere - roughly 20-200 km - but highlights several advantages provided by uncertainty modelling over more traditional approaches to developing these estimates. In particular, we argue that uncertainty modelling can allow for (1) an evaluation of the risk associated with any decision based on the assumed uncertainty; (2) a method for quantifying the costs and benefits of reducing uncertainty; and (3) a useful tool for communicating to stakeholders the challenges in managing highly uncertain systems. We also argue that incorporating rather than avoiding uncertainty will increase the chances of successfully achieving conservation and management goals.

Rethinking the labour movement in the "new South Africa"

The socio-economic system underpinning apartheid in South Africa was based on the exploitation of black workers in the mines, the factories, the fields and the shops. It is widely recognized that the struggles of the South African black working class contributed decisively to the overthrow of the racist regime. In recognition of the power of organised labour, the democratic government elected in 1994 granted South Africa's unions unprecedented legal and constitutional rights. However, despite these gains, the country's labour movement has been facing a fresh set of challenges, from macroeconomic policy to the factory floor, many of them emanating from labour’s political allies in Government. The purpose of this book is to examine how the South African labour movement is responding to these challenges in the new millennium. A variety of experts on South African labour, both within the country and outside deal with crucial issues: How has South Africa's labour movement reacted to the ANC Government's neoliberal economic agenda? How do the unions relate to an increasingly diversifying, “flexible” and vulnerable workforce? What are labour’s prospects of contributing to a left project in democratic South Africa? What are the challenges facing the unions in relation to new forms of militancy and social movements?

Machine learning for matching astronomy catalogues

An emerging issue in the field of astronomy is the integration, management and utilization of databases from around the world to facilitate scientific discovery. In this paper, we investigate application of the machine learning techniques of support vector machines and neural networks to the problem of amalgamating catalogues of galaxies as objects from two disparate data sources: radio and optical. Formulating this as a classification problem presents several challenges, including dealing with a highly unbalanced data set. Unlike the conventional approach to the problem (which is based on a likelihood ratio) machine learning does not require density estimation and is shown here to provide a significant improvement in performance. We also report some experiments that explore the importance of the radio and optical data features for the matching problem.

The protective effect of healthy ageing on the risk of injury in older people

Proceedings of ERA 2002 – 1st National Conference for Emerging Researchers in Ageing

Queensland's music outcomes: building pedagogical bridges

This paper discusses the challenges surrounding the implementation of the Music strand of the new syllabus for secondary teachers within the context of emerging trends in pedagogical reform in Queensland, and identifies several areas where research is needed to inform classroom music teaching practice and to guide teacher training programs. Secondary music teachers (Years 8-10) have not had the same systemic, school-based curriculum guidance that was given to teachers in years 1-7. This has resulted in a plethora of teaching and learning practices in lower secondary classrooms, many of which may be more experiential than developmental in approach and which may have little reference to the types of music programs common in primary classrooms.