High-performance computing for data analytics

One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.

Transdisciplinary approaches to urban computing

The research field of urban computing – defined as “the integration of computing, sensing, and actuation technologies into everyday urban settings and lifestyles” – considers the design and use of ubiquitous computing technology in public and shared urban environments. Its impact on cities, buildings, and spaces evokes innumerable kinds of change. Embedded into our everyday lived environments, urban computing technologies have the potential to alter the meaning of physical space, and affect the activities performed in those spaces. This paper starts a multi-themed discussion of various aspects that make up the, at times, messy and certainly transdisciplinary field of urban computing and urban informatics.

Meta-regulation approach to raise social accountability In global supply firms

This Article proposes a meta-regulation approach to address the gap between the objectives, commitment, practice and outcome in the accountability practice of the global supply chain in the developing countries. The literatures on the accountability practice in the global supply chains typically focuses on the strategies for raising corporate social accountability standards in multinational buying firms and seldom focuses on this strategies in the outsourced firms in the developing countries. This article tries to fill this void by examining the situation in Bangladesh, the third largest RMG supply country in the world. It conceptualizes a meta-regulation approach with the aim of raising social accountability practice in this industry. It shows that this regulation approach is suitable to effectively raise this practice standard in a perspective where the non-legal drivers are meagrely low, global buying firms are highly profit driven and the governmental agencies are either inadequate or highly corrupt.

Stakeholder pressures on corporate climate change-related accountability and disclosures: Australian evidence

This study investigates stakeholder pressures on corporate climate change-related accountability and disclosure practices in Australia. While existing scholarship investigates stakeholder pressures on companies to discharge their broader accountability through general social and environmental disclosures, there is a lack of research investigating whether and how stakeholder pressures emerge to influence accountability and disclosure practices related to climate change. We surveyed various stakeholder groups to understand their concerns about climate change-related corporate accountability and disclosure practices. We present three primary findings: first, while NGOs and the media have some influence, institutional investors and government bodies (regulators) are perceived to be the most powerful stakeholders in generating climate change-related concern and coercive pressure on corporations to be accountable. Second, corporate climate change-related disclosures, as documented through the Carbon Disclosure Project (CDP), are positively associated with such perceived coercive pressures. Lastly, we find a positive correlation between the level of media attention to climate change and Australian corporate responses to the CDP. Our results indicate that corporations will not disclose climate change information until pressured by non-financial stakeholders. This suggests a larger role for non-financial actors than previously theorized, with several policy implications.

Reliable, cloud-based communication for multi-robot systems

In contrast to single robotic agent, multi-robot systems are highly dependent on reliable communication. Robots have to synchronize tasks or to share poses and sensor readings with other agents, especially for co-operative mapping task where local sensor readings are incorporated into a global map. The drawback of existing communication frameworks is that most are based on a central component which has to be constantly within reach. Additionally, they do not prevent data loss between robots if a failure occurs in the communication link. During a distributed mapping task, loss of data is critical because it will corrupt the global map. In this work, we propose a cloud-based publish/subscribe mechanism which enables reliable communication between agents during a cooperative mission using the Data Distribution Service (DDS) as a transport layer. The usability of our approach is verified by several experiments taking into account complete temporary communication loss.

Information Accountability Framework (IAF)

POSTER: Information Accountability Framework (IAF) to mitigate and manage the risk of data breaches and unauthorised used of medical information (e.g., Electronic Health Records)

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

Nurses' accountability for stroke quality of care: part one: Review of the literature on nursing-sensitive patient outcomes

Over the past decade, an exciting area of research has emerged that demonstrates strong links between specific nursing care activities and patient outcomes. This body of research has resulted in the identification of a set of "nursing-sensitive outcomes"(NSOs). These NSOs may be interpreted with more meaning when they are linked to evidence-based best practice guidelines, which provide a structured means of ensuring care is consistent among all health care team members, across geographic locations, and across care settings. Uptake of evidence-based best practices at the point of care has been shown to have a measurable positive impact on processes of care and patient outcomes. The purpose of this paper is to present a systematic, narrative review of the literature regarding the clinical effectiveness of nursing management strategies on stroke patient outcomes sensitive to nursing interventions. Subsequent investigation will explore current applications of nursing-sensitive outcomes to patients with stroke, and identify and validate measurable NSOs within stroke care delivery.

Contributing to computing services to benchmarking asset management knowledge management

Asset management has broadened from a focus on maintenance management to whole of life cycle asset management requiring a suite of new competencies from asset procurement to management and disposal. Well developed skills and competencies as well as practical experience are a prerequisite to maintain capability, to manage demand as well to plan and set priorities and ensure on-going asset sustainability. This paper has as its focus to establish critical understandings of data, information and knowledge for asset management along with the way in which benchmarking these attributes through computer-aided design may aid a strategic approach to asset management. The paper provides suggestions to improve sharing, integration and creation of asset-related knowledge through the application of codification and personalization approaches.

NAPLAN, MySchool and accountability: Teacher perceptions of the effects of testing

This paper explores Rizvi and Lingard’s (2010) idea of the “local vernacular” of the global education policy trend of using high-stakes testing to increase accountability and transparency, and by extension quality, within schools and education systems in Australia. In the first part of the paper a brief context of the policy trajectory of National Assessment Program – Literacy and Numeracy (NAPLAN) is given in Australia. In the second part, empirical evidence drawn from a survey of teachers in Western Australia (WA) and South Australia (SA) is used to explore teacher perceptions of the impacts a high-stakes testing regime is having on student learning, relationships with parents and pedagogy in specific sites. After the 2007 Australian Federal election, one of Labor’s policy objectives was to deliver an “Education Revolution” designed to improve both the equity and excellence in the Australian school system1 (Rudd & Gillard, 2008). This reform agenda aims to “deliver real changes” through: “raising the quality of teaching in our schools” and “improving transparency and accountability of schools and school systems” (Rudd & Gillard, 2008, p. 5). Central to this linking of accountability, the transparency of schools and school systems and raising teaching quality was the creation of a regime of testing (NAPLAN) that would generate data about the attainment of basic literacy and numeracy skills by students in Australian schools.

Towards sustainable poverty alleviation: Building NGO accountability to beneficiaries in microenterprise development programs

This thesis investigates the operations of non-government organisations (NGOs) engaging in microenterprise development programs in Bangladesh and Indonesia, to understand the nature and mechanisms of NGO accountability to the poor. Findings reveal both barriers and mechanisms contributing to success within these programs. A range of mechanisms enhance both accountability of NGOs and the poor, facilitating more effective programs and sustainable poverty alleviation.

An ethical approach to sharing school successes in times of high-stakes accountability

High-stakes testing has become an important element of the Australian educational landscape. As one part of the neo-liberal paradigm where beliefs in the individual and the free market are paramount, it is of concern how school leaders can respond to this phenomenon in an ethical manner. Ethics and ethical leadership have increased in prominence both in the educational administration literature and in the media (Cranston, Ehrich, & Kimber, 2006). In this paper we consider ethical theories on which school principals can draw, not only in the leadership of their own schools but in their relationships with other schools. We provide an example of a school leader sharing a successful intervention with other schools, illustrating that school leaders can create spaces for promoting the public good within the context of high-stakes testing.

Distributed computing of all-to-all comparison problems in heterogeneous systems

The requirement of distributed computing of all-to-all comparison (ATAC) problems in heterogeneous systems is increasingly important in various domains. Though Hadoop-based solutions are widely used, they are inefficient for the ATAC pattern, which is fundamentally different from the MapReduce pattern for which Hadoop is designed. They exhibit poor data locality and unbalanced allocation of comparison tasks, particularly in heterogeneous systems. The results in massive data movement at runtime and ineffective utilization of computing resources, affecting the overall computing performance significantly. To address these problems, a scalable and efficient data and task distribution strategy is presented in this paper for processing large-scale ATAC problems in heterogeneous systems. It not only saves storage space but also achieves load balancing and good data locality for all comparison tasks. Experiments of bioinformatics examples show that about 89\% of the ideal performance capacity of the multiple machines have be achieved through using the approach presented in this paper.