Using a knowledge-based approach : the way healthy communities make decisions

The planning for Knowledge Cities faces significant challenges due to the lack of effective information tools. These challenges are magnified while planning healthy communities. The Australian Health Information Council (AHIC) concluded in its last report that health information needs to be shared more effectively (AHIC, 2008). Some research justifies the use of Decision Support Systems (DSS) as an E-planning tool, particularly in the context of healthy communities. However, very limited research has been conducted in this area to date, especially in terms of evaluating the impact of these tools on decision-makers within the health planning practice. The paper presents the methodological instruments which were developed to measure the impact of the E-planning tool (i.e., Health Decision Support System [HDSS])) on a group of health planners, namely, the Logan Beaudesert Health Coalition (LBHC). The paper is focused on the culture in which decisions were made before and after the intervention of the HDSS. Subsequently, the paper presents the observed impact of the HDSS tool, to facilitate a knowledge-based decision-making approach. This study is an attempt to make some contribution to the Knowledge Cities literature in the context of planning healthy communities by adopting E-planning tools.

A sequential Monte Carlo approach to design for population pharmacokinetics studies

Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of phase III clinical trials where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalogue of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical phase III clinical trial.

Modelling contractor's and subcontractor's trust : a system dynamics approach

A general mistrust within the contactor and subcontractor companies has identified one of the significant barriers to derive benefits from true downstream supply chain integration. Using the general theory of trust in inter-organizational relations and conducting interviews, this research discusses factors that influence development of trust and cooperation in contractor– subcontractor relationships in construction projects. System dynamics is the simulation method is selected in this theory-building effort, based on qualitative data collected from two projects of a construction company in Thailand. Performance, permeability and system based trust are found to make significant contributions toward parties’ trust level. Three strategic policies such as best value contracting, management of subcontractors as internal team and semi project partnering approach are recommended to stimulate the trust factors as well as cooperative long term relationship.

One approach to finding evidence for the effectiveness of scientific visualisations in high school physics and chemistry education

Enormous amounts of money and energy are being devoted to the development, use and organisation of computer-based scientific visualisations (e.g. animations and simulations) in science education. It seems plausible that visualisations that enable students to gain visual access to scientific phenomena that are too large, too small or occur too quickly or too slowly to be seen by the naked eye, or to scientific concepts and models, would yield enhanced conceptual learning. When the literature is searched, however, it quickly becomes apparent that there is a dearth of quantitative evidence for the effectiveness of scientific visualisations in enhancing students’ learning of science concepts. This paper outlines an Australian project that is using innovative research methodology to gather evidence on this question in physics and chemistry classrooms.

Understanding the coping strategies of international students : a qualitative approach

International students encounter a range of additional challenges as a part of their tertiary study experience. A qualitative approach was used to understand the challenges faced by international students, coping strategies that promoted their personal resilience and advice they have for future international students. Twenty-two international students from an Australian university participated in four focus groups. The challenges identified by students included adjustment, social isolation, English language skills, academic difficulties, unmet expectations, employment, culture shock and psychological distress. Participants shared their own personal experiences and strategies used by them to cope and identified strategies that future students could use prior to leaving their home country and whilst in Australia to improve their adjustment. Uses of international student stories in prevention interventions are discussed.

Exploring intercultural competence : a service-learning approach

This study explored the developing intercultural competence of fourth-year Australian education pre-service teachers through a core unit of study on inclusive education, following a service-learning pathway. The Australian pre-service teachers volunteered to be 'of service' to a cohort of second-year Malaysian pre-service teachers studying in Australia in a transnational twinning program. Students participated in a Patches program which included writing 'patches' (reflections) and engaging in social exchanges. Data were gathered from focus group interviews, written reflection logs and Patches writing books and were analysed through Butin's (2005) four-lenses of service-learning: technical, cultural, political and post-modern lenses. Data revealed that initially the Australian pre-service teachers felt their presumptions but by the end of the semester embraced the basic tenants of inclusion and were able to project how they could take their new understandings into the classroom as inclusive teachers.

Developing a curriculum for the real world : a whole of institution approach

Keynote address at University of Surrey, Real World Education Symposium, 29 September 2010. Full-text in audio form only. Link to audio provided in Official URL field.

Content-based video indexing for sports applications using integrated multi-modal approach

To sustain an ongoing rapid growth of video information, there is an emerging demand for a sophisticated content-based video indexing system. However, current video indexing solutions are still immature and lack of any standard. This doctoral consists of a research work based on an integrated multi-modal approach for sports video indexing and retrieval. By combining specific features extractable from multiple audio-visual modalities, generic structure and specific events can be detected and classified. During browsing and retrieval, users will benefit from the integration of high-level semantic and some descriptive mid-level features such as whistle and close-up view of player(s).

An innovative approach to reducing risks associated with infant feeding : the use of technology

Infant feeding is a complex behavior enacted in a risk adverse society. Despite ongoing communication and education strategies, breastfeeding rates in countries like Australia, the US, and the UK remain static, thus increasing the risk of short and long-term health problems. Health professionals and non-profit organizations recognize social marketing as an appropriate strategy for increasing breastfeeding duration since it addresses the shortfalls of education-only campaigns. Technology as an innovative alternative to mass media and education has the potential to reduce the social price of breastfeeding by assisting women to manage the identity and health risks associated with infant feeding. This paper reports findings from six focus groups that explored the risks associated with breastfeeding and the potential role of technology in ameliorating these risks. A key finding of this research was that technology has the potential to negate the impact of perceived uncertainty and lack of control associated with breastfeeding. The results indicated that future breastfeeding campaigns that are innovative in their approach and use technology may be more effective in changing breastfeeding behavior.

Diversity in Knowledge Management : A Cultural Approach

This paper reviews diversity in knowledge management (KM) from a cultural perspective; it argues that culturally embedded theories and practices influence the practice of knowledge management. It further presents and analyses several case studies and in particular a case study of the Islamic culture focusing on its traditional approach to both Islamic knowledge and management. The analysis of this case reveals the cultural challenges that emerge in the process of applying essentially Western management theories within an Islamic culture with particular reference to knowledge management theories. The paper concludes that the concept of knowledge management must take into account the diversity of national culture in which the organization exists and that the concept of knowledge management will benefit from a diversity perspective rather than a universality perspective.

A rights management approach to protection of privacy in a cloud of electronic health records

A patient-centric DRM approach is proposed for protecting privacy of health records stored in a cloud storage based on the patient's preferences and without the need to trust the service provider. Contrary to the current server-side access control solutions, this approach protects the privacy of records from the service provider, and also controls the usage of data after it is released to an authorized user.

Performance control of distributed generation using digital estimation of signal parameters

The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

Adaptive and optimal under frequency load shedding

Power systems in many countries are stressed towards their stability limit. If these stable systems experience any unexpected serious contingencies, or disturbances, there is a significant risk of instability, which may lead to wide-spread blackout. Frequency is a reliable indicator for such instability condition exists on the power system; therefore under-frequency load shedding technique is used to stable the power system by curtail some load. In this paper, the SFR-UFLS model redeveloped to generate optimal load shedding method is that optimally shed load following one single particular contingency event. The proposed optimal load shedding scheme is then tested on the 39-bus New England test system to show the performance against random load shedding scheme.

An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata

Modelling an environmental process involves creating a model structure and parameterising the model with appropriate values to accurately represent the process. Determining accurate parameter values for environmental systems can be challenging. Existing methods for parameter estimation typically make assumptions regarding the form of the Likelihood, and will often ignore any uncertainty around estimated values. This can be problematic, however, particularly in complex problems where Likelihoods may be intractable. In this paper we demonstrate an Approximate Bayesian Computational method for the estimation of parameters of a stochastic CA. We use as an example a CA constructed to simulate a range expansion such as might occur after a biological invasion, making parameter estimates using only count data such as could be gathered from field observations. We demonstrate ABC is a highly useful method for parameter estimation, with accurate estimates of parameters that are important for the management of invasive species such as the intrinsic rate of increase and the point in a landscape where a species has invaded. We also show that the method is capable of estimating the probability of long distance dispersal, a characteristic of biological invasions that is very influential in determining spread rates but has until now proved difficult to estimate accurately.