Occasional paper : Towards the development of an online learning environment (OLE) quality management framework

The project is committed to understanding, recognising and developing various forms of institutionally relevant distributed leadership in developing and trialling various components of a quality management framework for online learning environments in Australian higher education. This paper provides an overview of issues related to the management and improvement of quality, including in the context of higher education. In response to the complex and multi-dimensional nature of both quality and online learning environments (OLEs), the concept of a framework for organising policies, procedures and actions relating to the good governance of OLEs can be found in the literature. Such frameworks vary in scope, format and title, and a (non-exhaustive) sample is presented in summary here. Key learnings that can be drawn from the exemplars frameworks and the related literature include:
- the processes for the design of such frameworks;
- the components of such frameworks;
- the measurement mechanisms and metrics employed in such frameworks; and
- the validation of such frameworks.

An intelligent content discovery technique for health portal content management

Background: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics.Objective: This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new contentMethods: A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper.Results: The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management.Conclusions: The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current.

An overview of recent advances in intrusion detection

The intrusion detection system is one of the security defense tools for computer networks. In recent years this research has lacked in direction and focus. In this paper we present a survey on the recent progression of multiagent intrusion detection systems. We survey the existing types, techniques and architectures of Intrusion Detection Systems in the literature. Finally we outline the present research challenges and issues

Ubiquitous multicore (UM) methodology for multimedia

For more than a decade now, multimedia developers have usually "ride the waves", so to speak, with the coming of each generation of microprocessors, which allows their applications, designs and programs to usually running more proficiently, efficiently and effectively. This so-called "free" ride seems to be coming to an end, with results of increases clock speeds, the widening of the gap in processor and memory performance, and the tradeoffs that are needed to meet the former two points, with the new multi-core systems. In this paper, we build upon our previous work within multi-core systems, by proposing a ubiquitous multi-core (UM) design. The goal of such a framework is help researchers to plan and implement their multimedia applications so they can take advantage of speed up computations of multi-core systems and allow real-time multimedia. As our experiments show, our UM system increases performance speeds at an average of 100%, with the average execution cost of 1.4ms, showing that multimedia can use multi-core resources efficiently and effectively.

The OPtimising HEalth LIterAcy (Ophelia) process: study protocol for using health literacy profiling and community engagement to create and implement health reform

Health literacy is a multi-dimensional concept comprising a range of cognitive, affective, social, and personal skills and attributes. This paper describes the research and development protocol for a large communities-based collaborative project in Victoria, Australia that aims to identify and respond to health literacy issues for people with chronic conditions. The project, called Ophelia (OPtimising HEalth LIterAcy) Victoria, is a partnership between two universities, eight service organisations and the Victorian Government. Based on the identified issues, it will develop and pilot health literacy interventions across eight disparate health services to inform the creation of a health literacy response framework to improve health outcomes and reduce health inequalities.

Implementation of an audit with feedback knowledge translation intervention to promote medication error reporting in health care: a protocol.

BACKGROUND: Health professionals strive to deliver high-quality care in an inherently complex and error-prone environment. Underreporting of medical errors challenges attempts to understand causative factors and impedes efforts to implement preventive strategies. Audit with feedback is a knowledge translation strategy that has potential to modify health professionals' medical error reporting behaviour. However, evidence regarding which aspects of this complex, multi-dimensional intervention work best is lacking. The aims of the Safe Medication Audit Reporting Translation (SMART) study are to: 1. Implement and refine a reporting mechanism to feed audit data on medication errors back to nurses 2. Test the feedback reporting mechanism to determine its utility and effect 3. Identify characteristics of organisational context associated with error reporting in response to feedback METHODS/DESIGN: A quasi-experimental design, incorporating two pairs of matched wards at an acute care hospital, is used. Randomisation occurs at the ward level; one ward from each pair is randomised to receive the intervention. A key stakeholder reference group informs the design and delivery of the feedback intervention. Nurses on the intervention wards receive the feedback intervention (feedback of analysed audit data) on a quarterly basis for 12 months. Data for the feedback intervention come from medication documentation point-prevalence audits and weekly reports on routinely collected medication error data. Weekly reports on these data are obtained for the control wards. A controlled interrupted time series analysis is used to evaluate the effect of the feedback intervention. Self-report data are also collected from nurses on all four wards at baseline and at completion of the intervention to elicit their perceptions of the work context. Additionally, following each feedback cycle, nurses on the intervention wards are invited to complete a survey to evaluate the feedback and to establish their intentions to change their reporting behaviour. To assess sustainability of the intervention, at 6 months following completion of the intervention a point-prevalence chart audit is undertaken and a report of routinely collected medication errors for the previous 6 months is obtained. This intervention will have wider application for delivery of feedback to promote behaviour change for other areas of preventable error and adverse events.

Explaining the environmentally sustainable consumer behavior: a social capital perspective

Purpose - The purpose of this study is to examine the effects of social capital within a community on the adoption of consumer eco-behaviour or environmentally sustainable behaviour of consumers. The authors draw on the behavioural perspective model (BPM) of consumer behaviour and social capital theory in arguing that social capital shapes a consumer's knowledge of environmental issues and pro-environmental attitudes, which in turn influence a consumer's perceived capability to engage in eco-behaviour. Design/methodology/approach - This study uses partial least squares approach to structural equation modelling of survey data involving 1,044 consumers in the Philippines. It involves testing of a measurement model to examine the validity and reliability of the constructs used in the study. This is followed by testing of the structural models to test the hypothesised relationships of the constructs. Findings - The results suggest the substantive influence of social capital on environmental knowledge, pro-environmental attitudes and eco-capability. Both knowledge and attitudes have positive effects on eco-capability, which in turn positively shapes eco-behaviour. Research limitations/implications - Future studies can examine how social capital as a multi-dimensional construct impacts context-specific consumer behaviour. Practical implications - Social and environmental marketing may focus on social network activation to encourage eco-behaviours of consumers. Social implications - Findings highlight the role of social capital within one's community as a resource channel to encourage environmentally responsible consumer behaviour. Originality/value - The study extends the BPM by offering a social capital view as a more nuanced explanation of consumer eco-behaviour.

Aplicação de filtros de Gabor no processo de classificação de imagens digitais com base em atributos de textura

No processo de classificação de uma imagem digital, o atributo textura pode ser uma fonte importante de informações. Embora o processo de caracterização da textura em uma imagem seja mais difícil, se comparado ao processo de caracterização de atributos espectrais, sabe-se que o emprego daquele atributo pode aumentar significativamente a exatidão na classificação da imagem. O objetivo deste trabalho de pesquisa consiste em desenvolver e testar um método de classificação supervisionado em imagens digitais com base em atributos de textura. O método proposto implementa um processo de filtragem baseado nos filtros de Gabor. Inicialmente, é gerado um conjunto de filtros de Gabor adequados às freqüências espaciais associadas às diferentes classes presentes na imagem a ser classificada. Em cada caso, os parâmetros utilizados por cada filtro são estimados a partir das amostras disponíveis, empregando-se a transformada de Fourier. Cada filtro gera, então, uma imagem filtrada que quantifica a freqüência espacial definida no filtro. Este processo resulta em um certo número de imagens filtradas as quais são denominadas de "bandas texturais". Desta forma, o problema que era originalmente unidimensional passa a ser multi-dimensional, em que cada pixel passa a ser definido por um vetor cuja dimensionalidade é idêntica ao número de filtros utilizados. A imagem em várias "bandas texturais" pode ser classificada utilizando-se um método de classificação supervisionada. No presente trabalho foi utilizada a Máxima Verossimilhança Gaussiana. A metodologia proposta é então testada, utilizandose imagens sintéticas e real. Os resultados obtidos são apresentados e analisados.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.