Investigating the process of teaching and learning principles through practice : a case study on collegiate action by media practitioners and teachers, designing a skills-based learning program

This paper in the journalism education field reports on the construction of a new subject as part of a postgraduate coursework degree. The subject, or unit1 will offer both Journalism students and other students an introductory experience of creating media, using common ‘new media’ tools, with exercises that will model the learning of communication principles through practice. It has been named ‘Fundamental Media Skills for the Workplace’. The conceptualisation and teaching of it will be characteristic of the Journalism academic discipline that uses the ‘inside perspective’—understanding mass media by observing from within. Proposers for the unit within the Journalism discipline have sought to extend the common teaching approach, based on training to produce start-ready recruits for media jobs, backed by a study of contexts, e.g. journalistic ethics, or media audiences. In this proposal, students would then examine the process to elicit additional knowledge about their learning. The paper draws on literature of journalism and its pedagogy, and on communication generally. It also documents a ‘community of practice’ exercise conducted among practitioners as teachers for the subject, developing exercises and models of media work. A preliminary conclusion from that exercise is that it has taken a step towards enhancing skills-based learning for media work, as a portal to more generalised knowledge.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Australian Library and Information Studies (LIS) researchers' ranking of LIS journals

The paper describes the processes and the outcomes of the ranking of LIS journal titles by Australia’s LIS researchers during 2007-8, firstly through the Australian federal government’s Research Quality Framework (RQF) process and then its replacement, the Excellence in Research for Australia (ERA) initiative. The requirement to rank the journals titles used came from discussions held at the RQF panel meeting held in February 2007 in Canberra, Australia. While it was recognised that the Web of Science (formerly ISI) journal impact approach of journal acceptance for measures of research quality and impact might not work for LIS, it was apparent that this model would be the default if no other ranking of journal titles became apparent. Although an increasing number of LIS and related discipline journals were appearing in the Web of Science listed rankings, the number was few and it was thus decided by the Australian LIS research community to undertake the ranking exercise.

Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Adaptive Bayesian compound designs for dose finding studies

We consider the problem of how to efficiently and safely design dose finding studies. Both current and novel utility functions are explored using Bayesian adaptive design methodology for the estimation of a maximum tolerated dose (MTD). In particular, we explore widely adopted approaches such as the continual reassessment method and minimizing the variance of the estimate of an MTD. New utility functions are constructed in the Bayesian framework and are evaluated against current approaches. To reduce computing time, importance sampling is implemented to re-weight posterior samples thus avoiding the need to draw samples using Markov chain Monte Carlo techniques. Further, as such studies are generally first-in-man, the safety of patients is paramount. We therefore explore methods for the incorporation of safety considerations into utility functions to ensure that only safe and well-predicted doses are administered. The amalgamation of Bayesian methodology, adaptive design and compound utility functions is termed adaptive Bayesian compound design (ABCD). The performance of this amalgamation of methodology is investigated via the simulation of dose finding studies. The paper concludes with a discussion of results and extensions that could be included into our approach.

Business Process Management (BPM) education in Australia : a critical review based on content analysis

Business Process Management (BPM) is a top priority in organisations and is rapidly proliferating as an emerging discipline in practice. However, the current studies show lack of appropriate BPM skilled professionals in the field and a dearth of opportunities to develop BPM expertise. This paper analyses the gap between available BPM-related education in Australia and required BPM capabilities. BPM courses offered by Australian universities and training institutions have been critically analysed and mapped against leading BPM capability frameworks to determine how well current BPM education and training offerings in Australia actually address the core capabilities required for BPM professionals. The outcomes reported here can be used by Australian universities and training institutions to better align and position their training materials to the BPM required capabilities. It could also be beneficial to individuals looking for a systematic and in-depth understanding of BPM capabilities and trainings.

Application of an optimisation algorithm to configure an internal fixation device

Fractures of long bones are sometimes treated using various types of fracture fixation devices including internal plate fixators. These are specialised plates which are used to bridge the fracture gap(s) whilst anatomically aligning the bone fragments. The plate is secured in position by screws. The aim of such a device is to support and promote the natural healing of the bone. When using an internal fixation device, it is necessary for the clinician to decide upon many parameters, for example, the type of plate and where to position it; how many and where to position the screws. While there have been a number of experimental and computational studies conducted regarding the configuration of screws in the literature, there is still inadequate information available concerning the influence of screw configuration on fracture healing. Because screw configuration influences the amount of flexibility at the area of fracture, it has a direct influence on the fracture healing process. Therefore, it is important that the chosen screw configuration does not inhibit the healing process. In addition to the impact on the fracture healing process, screw configuration plays an important role in the distribution of stresses in the plate due to the applied loads. A plate that experiences high stresses is prone to early failure. Hence, the screw configuration used should not encourage the occurrence of high stresses. This project develops a computational program in Fortran programming language to perform mathematical optimisation to determine the screw configuration of an internal fixation device within constraints of interfragmentary movement by minimising the corresponding stress in the plate. Thus, the optimal solution suggests the positioning and number of screws which satisfies the predefined constraints of interfragmentary movements. For a set of screw configurations the interfragmentary displacement and the stress occurring in the plate were calculated by the Finite Element Method. The screw configurations were iteratively changed and each time the corresponding interfragmentary displacements were compared with predefined constraints. Additionally, the corresponding stress was compared with the previously calculated stress value to determine if there was a reduction. These processes were continued until an optimal solution was achieved. The optimisation program has been shown to successfully predict the optimal screw configuration in two cases. The first case was a simplified bone construct whereby the screw configuration solution was comparable with those recommended in biomechanical literature. The second case was a femoral construct, of which the resultant screw configuration was shown to be similar to those used in clinical cases. The optimisation method and programming developed in this study has shown that it has potential to be used for further investigations with the improvement of optimisation criteria and the efficiency of the program.

An examination of the relationships between lifestyle factors and mental health among Australian midlife and older women

Background It is well known that lifestyle factors including overweight/obesity, physical inactivity, smoking and alcohol use are largely related with morbidity and mortality of chronic diseases including diabetes and cardiovascular diseases. The effect of lifestyle factors on people’s mental health who have a chronic disease is less defined in the research. The World Health Organisation has defined health as “a state of complete physical, mental and social well-being”. It is important, therefore to develop an understanding of the relationships between lifestyle and mental health as this may have implications for maximising the efficacy of health promotion in people with chronic diseases. Objectives The overall aim of the research was to examine the relationships between lifestyle factors and mental health among Australian midlife and older women. Methodology The current research measured four lifestyle factors including weight status, physical activity, smoking and alcohol use. Three interconnecting studies were undertaken to develop a comprehensive understanding of the relationships between lifestyle factors and mental health. Study 1 investigated the longitudinal effect of lifestyle factors on mental health by using midlife and older women randomly selected from the community. Study 2 adopted a cross-sectional design, and compared the effect of lifestyle factors on mental health between midlife and older women with and without diabetes. Study 3 examined the mediating effect of self-efficacy in the relationships between lifestyle factors and mental health among midlife and older women with diabetes. A questionnaire survey was chosen as the means to gather information, and multiple linear regression analysis was conducted as the primary statistical approach. Results The research showed that the four lifestyle factors including weight status, physical activity, smoking and alcohol use did impact on mental health among Australian midlife and older women. First, women with a higher BMI had lower levels of mental health than women with normal weight, but as women age, the mental health of women who were overweight and obese becomes better than that of women with normal weight. Second, women who were physically active had higher levels of mental health than those who were not. Third, smoking adversely impacted on women’s mental health. Finally, those who were past-drinkers had less anxiety symptoms than women who were non-drinkers as they age. Women with diabetes appeared to have lower levels of mental health compared to women without. However, the disparities of mental health between two groups were confounded by low levels of physical activity and co-morbidities. This finding underlines the effect of physical activity on women’s mental health, and highlights the potential of reducing the gap of mental health by promoting physical activity. In addition, self-efficacy was shown to be the mediator of the relationships between BMI, physical activity and depression, suggesting that enhancing people’s self-efficacy may be useful for mental health improvement. Conclusions In conclusion, Australian midlife and older women who live with a healthier lifestyle have higher levels of mental health. It is suggested that strategies aiming to improve people’s mental health may be more effective if they focus on enhancing people’s self-efficacy levels. This study has implications to both health education and policy development. It indicates that health professionals may need to consider clients’ mental health as an integrated part of lifestyle changing process. Furthermore, given that lifestyle factors impact on both physical and mental health, lifestyle modification should continue to be the focus of policy development.

Car following model improvement for traffic safety metrics reproduction

Car Following models have a critical role in all microscopic traffic simulation models. Current microscopic simulation models are unable to mimic the unsafe behaviour of drivers as most are based on presumptions about the safe behaviour of drivers. Gipps model is a widely used car following model embedded in different micro-simulation models. This paper examines the Gipps car following model to investigate ways of improving the model for safety studies application. The paper puts forward some suggestions to modify the Gipps model to improve its capabilities to simulate unsafe vehicle movements (vehicles with safety indicators below critical thresholds). The result of the paper is one step forward to facilitate assessing and predicting safety at motorways using microscopic simulation. NGSIM as a rich source of vehicle trajectory data for a motorway is used to extract its relatively risky events. Short following headways and Time To Collision are used to assess critical safety event within traffic flow. The result shows that the modified proposed car following to a certain extent predicts the unsafe trajectories with smaller error values than the generic Gipps model.

Constructability improvement in sea water intake structure

Purpose The purpose of this paper is to explore the process, and analyse the implementation of constructability improvement and innovation result during the planning and design for sea water intake structure of fertilizer plant project. Design/methodology/approach The research methodology approach is case study method at project level. This constructability improvement process was investigated by using constructability implementation check lists, direct observation, documented lesson learned analysis and key personnel interviews. Findings The case study shows that the implementation of constructability during planning and design stage for this sea water intake structure has increased the project performance as well as improved the schedule by 5 months (14.21%) and reduced the project cost by 15.35%. Research limitations/implications This case study was limited to three (3) previous sea water intake projects as references and one (1) of new method sea water intake structure at fertilizer plant project. Practical implications A constructability improvement check list using theory and lesson learned for the specific construction project was documented. Originality/value The findings support the relevant study of constructability and provide specific lesson learned for three (3) previous project and one (1) of the new innovation method of the construction project and documented by the company.

Anion induced displacement studies in naphthalene diimide containing interpenetrated and interlocked structures

This article describes investigations into the development of supramolecular systems capable of sensing anions through either displacement type assays or molecular motion. An electron deficient naphthalene diimide thread and electron rich isophthalamide naphthohydroquinone macrocycle was shown to form a coloured pseudorotaxane assembly. Investigations into the ability of such interpenetrated systems to sense anions colorimetrically were undertaken. Anion complexation to the isophthalamide group of the macrocycle causes displacement of the naphthodiimide thread resulting in the loss of colour. The enhanced mechanically bonded binding strength between the naphthodiimide axle and the naphthohydroquinone groups of the macrocycle wheel in the corresponding rotaxane structure however, was found to negate the anion induced displacement process.

Why adopt now? Multiple case studies and survey studies comparing small, medium and large firms

While a number of factors have been highlighted in the innovation adoption literature, little is known about whether different factors are related to innovation adoption in differently-sized firms. We used preliminary case studies of small, medium and large firms to ground our hypotheses, which were then tested using a survey of 94 firms. We found that external stakeholder pressure and non-financial readiness were related to innovation adoption in SMEs; but that for large firms, adoption was related to the opportunity to innovate. It may be that the difficulties of adopting innovations, including both the financial cost and the effort involved, are too great for SMEs to overcome unless there is either a compelling need (external pressure) or enough in-house capability (non-financial readiness). This suggests that SMEs are more likely to have innovation “pushed” onto them while large firms are more likely to “pull” innovations when they have the opportunity.

Exploring the process of implementing a smoking cessation intervention in pregnancy training program for midwives

The question of how to implement evidence effectively reveals a deficiency in our knowledge and understanding of the compound factors involved in such a process (Kitson, Rycroft-Malone et al. 2008). Although there is some awareness of the complexities of the process, there has been little exploration of the effectiveness of implementing evidence-based programs in health care. Despite public awareness of the dangers of smoking in pregnancy, and widespread public health measures to prevent smoking-related disease, women still continue to smoke in pregnancy (Ananth, Savitz et al. 1997; Laws and Hilder 2008). Evaluation of public health measures concludes that smoking cessation interventions during pregnancy increase quit rates among pregnant women (Melvin, Dolan-Mullen et al. 2000; Albrecht, Maloni et al. 2004; Lumley, Oliver et al. 2007). Notwithstanding the potential for improvement in health outcomes for pregnant women and their unborn babies, smoking interventions are often conducted poorly or not at all. Although midwives understand why women smoke in pregnancy and parenthood and are aware of the risks of smoking to both the pregnancy and the unborn child, they require specific knowledge and skills in the provision of support and advice on smoking for pregnant women (Bull and Whitehead 2006) . Organisational-change research demonstrates the complexity of the process of planned change in professionalised institutions such as health care (Greenhalgh, Robert et al. 2005). Some innovations and interventions are never accepted, and others are poorly supported (Greenhalgh, Robert et al. 2004). Comprehension of the change process around health promotion is crucial to the implementation of new health promotion interventions within health care (Riley, Taylor et al. 2003). This study utilised a case study approach to explore the process of implementing a smoking cessation training program for midwives in Queensland metropolitan and regional clinical areas, who attended a ‘Train-the-Trainer program’. The study draws on the organisational change work of Greenhalgh et al (2004) as the theoretical framework through which situational and structural factors are explored and examined as they inform the implementation of smoking cessation programs. The research data constituted staged interviews with midwives who instituted training programs for midwives, as well as organisational and policy documentation. Analysis of the data identified some areas that were not fully addressed in the theoretical model; these formed the basis of the Discussion and Implications for Future Research.

Issues and concerns of microscopic calibration process at different network levels : case study of Pacific Motorway

Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such microcalibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, lane distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.