Portal-based support for mental health research

This paper describes experiences with the use of the Globus toolkit and related technologies for development of a secure portal that allows nationally-distributed Australian researchers to share data and application programs. The portal allows researchers to access infrastructure that will be used to enhance understanding of the causes of schizophrenia and advance its treatment, and aims to provide access to a resource that can expand into the world’s largest on-line collaborative mental health research facility. Since access to patient data is controlled by local ethics approvals, the portal must transparently both provide and deny access to patient data in accordance with the fine-grained access permissions afforded individual researchers. Interestingly, the access protocols are able to provide researchers with hints about currently inaccessible data that may be of interest to them, providing them the impetus to gain further access permissions.

Enhancing the auditor's report : to what extent is there support for the IAASB's proposed changes?

This article outlines proposed reforms to auditor reporting currently being considered by the International Auditing and Assurance Standards Board (IAASB), and other key national and transnational standard-setters and regulatory bodies. It adds to recent academic contributions on reforming the auditor’s report by analyzing the 165 stakeholder responses to the IAASB’s 2012 Invitation to Comment: Improving the Auditor’s Report to determine levels of support for the IAASB’s proposed reforms, and the differences, if any, between the views of various respondents based on stakeholder groups (e.g. audit and assurance firms, users, preparers, regulators, etc.) and regional classifications. Guided by insights from communication theory, our results show the levels of stakeholder support for the IAASB’s proposed reforms addressing auditors’ expectations, information and communication gaps are mixed. The strongest overall support was for enhanced auditor reporting on other information attached to, or intended to be read with, the financial statements, and the least supported initiative was including additional information in the auditor’s report about the auditor’s judgements and processes. Whilst overall there is generally consensus across both stakeholder groups and regions concerning the various questions investigated, we highlight where statistically significant differences between groups do exist. Notably, North American respondents were less likely to support a number of the IAASB’s proposed reforms than their counterparts from other regions.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Leadership to support quality improvement in Vietnamese higher education

The impetus for the study reported in this paper is the Higher Education (HE) reform agenda outlined by the Vietnamese Ministry of Education and Training (MOET). The paper reports on phase one of a mixed method research; a quantitative approach using the Multifactor Leadership Questionnaire (MLQ) to investigate the Vietnamese HE leaders’ leadership styles. The MLQ survey was administered to approximately 190 senior managers in State HE institutions in Mekong Delta region in Vietnam (nine of colleges). The psychometrics of the MLQ for the Vietnamese sample confirmed the reliability and validity of the instrument with a Cronbach’s alpha of 0.779. A CFA was conducted and all factor structures were stable and consistent. The demographic variables were used to analyse patterns of leadership behaviours by the different sub-groups. The findings suggest that leaders who have different educational background and different gender in Mekong Delta region, Vietnam do not differ significantly in their perceptions about leadership factors.

Refactoring Service Interface to Support Artefact-centric Service interaction

The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges for improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operations having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

When sex doesn't sell: Using sexualized images of women reduces support for ethical campaigns

Images of scantily clad women are used by advertisers to make products more attractive to men. This ‘‘sex sells’’ approach is increasingly employed to promote ethical causes, most prominently by the animal-rights organization PETA. Yet sexualized images can dehumanize women, leaving an unresolved paradox – is it effective to advertise an ethical cause using unethical means? In Study 1, a sample of Australian male undergraduates (N = 82) viewed PETA advertisements containing either sexualized or non-sexualized images of women. Intentions to support the ethical organization were reduced for those exposed to the sexualized advertising, and this was explained by their dehumanization of the sexualized women, and not by increased arousal. Study 2 used a mixed-gender community sample from the United States (N = 280), replicating this finding and extending it by showing that behaviors helpful to the ethical cause diminished after viewing the sexualized advertisements, which was again mediated by the dehumanization of the women depicted. Alternative explanations relating to the reduced credibility of the sexualized women and their objectification were not supported. When promoting ethical causes, organizations may benefit from using advertising strategies that do not dehumanize women.

Emotional effort and perceived support in renal nursing: A comparative interview study

Background: Social support is an important moderator of poor well-being outcomes for nurses engaged in emotional labour with patients; however, the most effective support for renal nurses is not well understood compared with other specialties. Objectives: To identify patterns and themes in how renal nurses and two other specialties engage with patients’ emotional expressions, express their own emotion and access and provide support for emotional expenditure. Method: Renal, emergency and palliative care nurses from Perth, Western Australia, were interviewed. Results: Renal nurses engage in significant amounts of emotional labour with patients, and identify co-workers as the most important source of support due to their availability and a sense of shared experience. However, comparative analysis showed that renal nurses do not recognise their emotional expenditure as readily and have less certainty of co-worker support. Conclusions: Because their high levels of emotional engagement with patients are mostly positive, renal nurses are less prepared than other nurses to manage difficult emotional situations. As co-worker support is highly valued, organisations should train renal nurses specifically to support one another.

Developing and evaluating approaches for utilising injury data to support product safety initiatives

With increasing concern about consumer product-related injuries in Australia, product safety regulators need evidence-based research to understand risks and patterns to inform their decision making. This study analysed paediatric injury data to identify and quantify product-related injuries in children to inform product safety prioritisation. This study provides information on novel techniques for interrogating health data to identify trends and patterns in product-related injuries to inform strategic directions in this growing area of concern.

Multi-parametric hydrogels support 3D in vitro bioengineered microenvironment models of tumour angiogenesis

Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.

Fibroin-based materials support co-cultivation of limbal epithelial and stromal cells

The silk protein fibroin (Bombyx mori) provides a potential substrate for use in ocular tissue reconstruction. We have previously demonstrated that transparent membranes produced from fibroin support cultivation of human limbal epithelial (HLE) cells (Tissue Eng A. 14(2008)1203-11). We extend this body of work to studies of human limbal stromal cell (HLS) growth on fibroin in the presence and absence of serum. Also, we investigate the ability to produce a bi-layered composite scaffold of fibroin with an upper HLE layer and lower HLS layer.

Self-regulation support through music

A critical dimension of early learning competence in the year prior to school is self-regulation. Self-regulation enables children to manage their emotions and direct their attention, thinking, and actions to meet adaptive goals. These skills enhance young children's readiness to learn.

Evaluation of ANPR trials for traffic policing in Queensland. Report to the Queensland Police Service, State Traffic Support Branch

In response to the Travelsafe Committee Report No. 51 – report on the inquiry into Automatic Plate Recognition Technology – it was recommended that the Queensland Police Service continue to trial the deployment of ANPR technology for traffic enforcement work and to evaluate the road safety impacts and operational effectiveness of the technology. As such, the purpose of this report is to provide an independent evaluation of a trial of ANPR that was conducted by a project team within the State Traffic Support Branch of the Queensland Police Service (QPS) and provide recommendations as to the applicability and usability of the technology for use throughout Queensland...

A neurofuzzy approach to future intelligent driver support systems

This paper reviews a variety of advanced signal processing algorithms that have been developed at the University of Southampton as part of the Prometheus (PROgraMme for European Traffic flow with Highest Efficiency and Unprecedented Safety) research programme to achieve an intelligent driver warning system (IDWS). The IDWS includes: visual detection of both generic obstacles and other vehicles, together with their tracking and identification, estimates of time to collision and behavioural modelling of drivers for a variety of scenarios. These application areas are used to show the applicability of neurofuzzy techniques to the wide range of problems required to support an IDWS, and for future fully autonomous vehicles.

Decision support system for infrastructure sustainability in operations

There is an increasing awareness of sustainability and climate change and its impact on infrastructure and engineering asset management in design, construction, and operations. Sustainability rating tools have been proposed and/or developed that provide ratings of infrastructure projects in differing phases of their life cycle on sustainability. This paper provides an overview of decision support systems using sustainability rating framework that can be used to prioritize or select tasks and activities within projects to enhance levels of sustainability outcomes. These systems can also be used to prioritize projects within an organization to optimize sustainability outcomes within an allocated budget.