Obstacle-free range determination for rail track maintenance vehicles

Maintenance trains travel in convoy. In Australia, only the first train of the convoy pays attention to the track sig- nalization (the other convoy vehicles simply follow the preceding vehicle). Because of human errors, collisions can happen between the maintenance vehicles. Although an anti-collision system based on a laser distance meter is already in operation, the existing system has a limited range due to the curvature of the tracks. In this paper, we introduce an anti-collision system based on vision. The two main ideas are, (1) to warp the camera image into an image where the rails are parallel through a projective transform, and (2) to track the two rail curves simultaneously by evaluating small parallel segments. The performance of the system is demonstrated on an image dataset.

Implementing an emergency department patient admission predictive tool : insights from practice

Purpose: This paper aims to show that identification of expectations and software functional requirements via consultation with potential users is an integral component of the development of an emergency department patient admissions prediction tool. ---------- Design/methodology/approach: Thematic analysis of semi-structured interviews with 14 key health staff delivered rich data regarding existing practice and future needs. Participants included emergency department staff, bed managers, nurse unit managers, directors of nursing, and personnel from health administration. ---------- Findings: Participants contributed contextual insights on the current system of admissions, revealing a culture of crisis, imbued with misplayed communication. Their expectations and requirements of a potential predictive tool provided strategic data that moderated the development of the Emergency Department Patient Admissions Prediction Tool, based on their insistence that it feature availability, reliability and relevance. In order to deliver these stipulations, participants stressed that it should be incorporated, validated, defined and timely. ---------- Research limitations/implications: Participants were envisaging a concept and use of a tool that was somewhat hypothetical. However, further research will evaluate the tool in practice. ---------- Practical implications: Participants' unsolicited recommendations regarding implementation will not only inform a subsequent phase of the tool evaluation, but are eminently applicable to any process of implementation in a healthcare setting. ---------- Originality/value: The consultative process engaged clinicians and the paper delivers an insider view of an overburdened system, rather than an outsider's observations.

Application of reliability-centred maintenance technology on electric trains

This paper demonstrates the application of the reliability-centred maintenance (RCM) process to analyse and develop preventive maintenance tasks for electric multiple units (EMU) in the East Rail of the Kowloon-Canton Railway Corporation (KCRC). Two systems, the 25 kV electrical power supply and the air-conditioning system of the EMU, have been chosen for the study. RCM approach on the two systems is delineated step by step in the paper. This study confirms the feasibility and effectiveness of RCM applications on the maintenance of electric trains.

Beyond statistical procedures for predictive modelling: Data mining algorithms and support for university research at QUT

In a seminal data mining article, Leo Breiman [1] argued that to develop effective predictive classification and regression models, we need to move away from the sole dependency on statistical algorithms and embrace a wider toolkit of modeling algorithms that include data mining procedures. Nevertheless, many researchers still rely solely on statistical procedures when undertaking data modeling tasks; the sole reliance on these procedures has lead to the development of irrelevant theory and questionable research conclusions ([1], p.199). We will outline initiatives that the HPC & Research Support group is undertaking to engage researchers with data mining tools and techniques; including a new range of seminars, workshops, and one-on-one consultations covering data mining algorithms, the relationship between data mining and the research cycle, and limitations and problems with these new algorithms. Organisational limitations and restrictions to these initiatives are also discussed.

The role of nature-based experiences in the development and maintenance of wellness

Wellness is now seen as central to redefining the National Health agenda. There is growing evidence that contact with nature and physical activity in nature has considerable positive effects on human health. At the most basic level humanity is reliant on the natural world for resources such as air and water. However, a growing body of research is finding that beyond this fundamental relationship exposure to the non-human natural world can also positively enhance perceptions of physiological, emotional, psychological and spiritual health in ways that cannot be satisfied by alternate means. Theoretical explanations for this have posited that non-human nature might 1) restore mental fatigue, 2) trigger deep reflections, 3) provide an opportunity for nurturing and 4) rekindle innate connections. In this paper the authors show how human wellness is strongly connected to their relationship with the natural world. This paper points to how non-human nature could be better utilised for enhancing human health and wellness.

Maintenance person or architect? The role of academic advertising research in building better understanding

This paper suggests that, while advertising has changed, advertising research has not. Indeed, questions asked of advertising research more than 20 years ago have still not been answered. The enormity of change in advertising compounded by the lack of response from researchers suggests the traditional academic advertising research model requires more than routine maintenance. It seeks an architect with vision to redesign an academic research model that is probably broken or badly outdated. Five areas of the academic research approach are identified as needing rethinking: (1) the advertising problem, (2) sample frame and subjects, (3) assumptions regarding consumer behaviour, (4) research methodologies and (5) findings. Suggestions are made for improvement. But perhaps the biggest challenge is academic leadership. This paper proposes the establishment of a blue-ribbon panel to report back on recommended changes or improvements.

Autonomous underwater vehicle trajectory design coupled with predictive ocean models : a case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Construction safety in the repair and maintenance sector

Statistics indicate that the percentage of fatal industrial accidents arising from repair, maintenance, minor alteration and addition (RMAA) works in Hong Kong was disturbingly high and was over 56% in 2006. This paper provides an initial report of a research project funded by the Research Grants Council (RGC) of the HKSAR to address this safety issue. The aim of this study is to scrutinize the causal relationship between safety climate and safety performance in the RMAA sector. It aims to evaluate the safety climate in the RMAA sector; examine its impacts on safety performance, and recommend measures to improve safety performance in the RMAA sector. This paper firstly reports on the statistics of construction accidents arising from RMAA works. Qualitative and quantitative research methods applied in conducting the research are dis-cussed. The study will critically review these related problems and provide recommendations for improving safety performance in the RMAA sector.

Alcohol expectancy changes over a 12-week cognitive–behavioral therapy program are predictive of treatment success

This study examines if outcome expectancies (perceived consequences of engaging in certain behavior) and self- efficacy expectancies (confidence in personal capacity to regulate behavior) contribute to treatment outcome for alcohol dependence. Few clinical studies have examined these constructs. The Drinking Expectancy Profile (DEP), a psychometric measure of alcohol expectancy and drinking refusal selfefficacy, was administered to 298 alcohol-dependent patients (207 males) at assessment and on completion of a 12-week cognitive–behavioral therapy alcohol abstinence program. Baseline measures of expectancy and self-efficacy were not strong predictors of outcome. However, for the 164 patients who completed treatment, all alcohol expectancy and self-efficacy factors of the DEP showed change over time. The DEP scores approximated community norms at the end of treatment. Discriminant analysis indicated that change in social pressure drinking refusal self-efficacy, sexual enhancement expectancies, and assertion expectancies successfully discriminated those who successfully completed treatment from those who did not. Future research should examine the basis of expectancies related to social functioning as a possible mechanism of treatment response and a means to enhance treatment outcome.