Educating the world's railway engineers

An increasing loss of engineering expertise from the railway industry globally coincides with a rapid expansion of the industry. Continuing professional development is critical to this sector, but needs to be distance based to cater for the international demand for such development. A unique Master degree in railway infrastructure was created out of extensive materials prepared by expert engineers, which captured their detailed knowledge. A team at Queensland University of Technology in Australia prepared the detailed and high quality online resources needed for this degree; the team comprised an academic, a project manager, learning designers and a publisher, all with experience in distance education. The degree has been running for 12 months with students from many countries. A key aim of the degree is to create a collaborative community comprising learners, teachers and practicing engineers from around the world. The team has also worked hard to ensure the content of the study materials, the form of the assessment tasks and the interactive learning sessions relate closely to real-world problems and challenges faced by the students in their workplace, wherever that is. Widely differing time zones are a challenge but are usually obviated by the asynchronous nature of the online resources.

GPS fault detection with IMU and aircraft dynamics

Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.

Competency Standards and Educational Requirements for Specialist Breast Nurses in Australia

There is substantial evidence that Specialist Breast Nurses (SBNs) make an important contribution to improved outcomes for women with breast cancer, by providing information and support and promoting continuity of care. However, a recent study has identified significant variation in how the role functions across individual nurses and settings, which is likely to contribute to varied outcomes for women with breast cancer. The project reported in this paper illustrates how a set of competency standards for SBNs were developed by the National Breast Cancer Centre. The competency standards were developed through a review of published literature and consultation with key stakeholders. The resulting SBN Competency Standards reflect the core domains and elements of SBN practice seen as integral to achieving optimal outcomes for women with breast cancer. This project identifies the SBN as a registered nurse who applies advanced knowledge of the health needs, preferences and circumstances of women with breast cancer to optimise the individual's health and well-being at various phases across the continuum of care, including diagnosis, treatment, rehabilitation, follow-up and palliative care. The five core domains of practice identified are: Supportive care; Collaborative care; Coordinated care; Information provision and education; and Clinical leadership. A variety of education programs are currently available for nurses who wish to learn about breast cancer nursing. The majority of stakeholders consulted in this project agreed that a Graduate Diploma level of education is required at minimum in order for an SBN to develop the minimum level of competence required to perform the role. The evidence supports the view that as an advanced role, nurses practising as SBNs require high-quality programs of sufficient depth and scope to achieve the required level of competence

Fingerprint analysis using wavelet transform with application to compression and feature extraction

The main goal of this research is to design an efficient compression al~ gorithm for fingerprint images. The wavelet transform technique is the principal tool used to reduce interpixel redundancies and to obtain a parsimonious representation for these images. A specific fixed decomposition structure is designed to be used by the wavelet packet in order to save on the computation, transmission, and storage costs. This decomposition structure is based on analysis of information packing performance of several decompositions, two-dimensional power spectral density, effect of each frequency band on the reconstructed image, and the human visual sensitivities. This fixed structure is found to provide the "most" suitable representation for fingerprints, according to the chosen criteria. Different compression techniques are used for different subbands, based on their observed statistics. The decision is based on the effect of each subband on the reconstructed image according to the mean square criteria as well as the sensitivities in human vision. To design an efficient quantization algorithm, a precise model for distribution of the wavelet coefficients is developed. The model is based on the generalized Gaussian distribution. A least squares algorithm on a nonlinear function of the distribution model shape parameter is formulated to estimate the model parameters. A noise shaping bit allocation procedure is then used to assign the bit rate among subbands. To obtain high compression ratios, vector quantization is used. In this work, the lattice vector quantization (LVQ) is chosen because of its superior performance over other types of vector quantizers. The structure of a lattice quantizer is determined by its parameters known as truncation level and scaling factor. In lattice-based compression algorithms reported in the literature the lattice structure is commonly predetermined leading to a nonoptimized quantization approach. In this research, a new technique for determining the lattice parameters is proposed. In the lattice structure design, no assumption about the lattice parameters is made and no training and multi-quantizing is required. The design is based on minimizing the quantization distortion by adapting to the statistical characteristics of the source in each subimage. 11 Abstract Abstract Since LVQ is a multidimensional generalization of uniform quantizers, it produces minimum distortion for inputs with uniform distributions. In order to take advantage of the properties of LVQ and its fast implementation, while considering the i.i.d. nonuniform distribution of wavelet coefficients, the piecewise-uniform pyramid LVQ algorithm is proposed. The proposed algorithm quantizes almost all of source vectors without the need to project these on the lattice outermost shell, while it properly maintains a small codebook size. It also resolves the wedge region problem commonly encountered with sharply distributed random sources. These represent some of the drawbacks of the algorithm proposed by Barlaud [26). The proposed algorithm handles all types of lattices, not only the cubic lattices, as opposed to the algorithms developed by Fischer [29) and Jeong [42). Furthermore, no training and multiquantizing (to determine lattice parameters) is required, as opposed to Powell's algorithm [78). For coefficients with high-frequency content, the positive-negative mean algorithm is proposed to improve the resolution of reconstructed images. For coefficients with low-frequency content, a lossless predictive compression scheme is used to preserve the quality of reconstructed images. A method to reduce bit requirements of necessary side information is also introduced. Lossless entropy coding techniques are subsequently used to remove coding redundancy. The algorithms result in high quality reconstructed images with better compression ratios than other available algorithms. To evaluate the proposed algorithms their objective and subjective performance comparisons with other available techniques are presented. The quality of the reconstructed images is important for a reliable identification. Enhancement and feature extraction on the reconstructed images are also investigated in this research. A structural-based feature extraction algorithm is proposed in which the unique properties of fingerprint textures are used to enhance the images and improve the fidelity of their characteristic features. The ridges are extracted from enhanced grey-level foreground areas based on the local ridge dominant directions. The proposed ridge extraction algorithm, properly preserves the natural shape of grey-level ridges as well as precise locations of the features, as opposed to the ridge extraction algorithm in [81). Furthermore, it is fast and operates only on foreground regions, as opposed to the adaptive floating average thresholding process in [68). Spurious features are subsequently eliminated using the proposed post-processing scheme.

Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

Dynamic coast control of train movement with genetic algorithm

The railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. Train service usually varies with the population activities throughout a day and train coordination and service regulation are then expected to meet the daily passengers' demand. Dwell time control at stations and fixed coasting point in an inter-station run are the current practices to regulate train service in most metro railway systems. However, a flexible and efficient train control and operation is not always possible. To minimize energy consumption of train operation and make certain compromises on the train schedule, coast control is an economical approach to balance run-time and energy consumption in railway operation if time is not an important issue, particularly at off-peak hours. The capability to identify the starting point for coasting according to the current traffic conditions provides the necessary flexibility for train operation. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigates the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. Further, a hierarchical genetic algorithm (HGA) is introduced here to identify the number of coasting points required according to the traffic conditions, and Minimum-Allele-Reserve-Keeper (MARK) is adopted as a genetic operator to achieve fitter solutions.

A systematic review of the association between physical activity and colorectal cancer risk

This review evaluated the strength of the evidence for a causal relationship between physical activity (PA) and colorectal cancer (CRC). A systematic review of databases through February 2008 was conducted to identify studies that assessed the association between total or recreational PA and incidence or mortality of CRC (including CRC, rectal cancer, colon cancer, and proximal or distal colon cancer). Studies were evaluated for significant associations between PA and risk of CRC endpoints and for evidence of dose–response relationships in the highest quality studies. Twenty cohort studies were evaluated; 11 were high-quality. Fifty percent of all studies and 64%of highest quality studies reported at least one significant association between PA and risk of a CRC endpoint (Po0.05).However, only 28%of all analyses (31% of analyses of highest quality studies) were significant (Po0.05). Only 40% of analyses of highest quality studies resulted in a significant P for trend (Po0.05); however, a non-significant inverse linear association between PA and colon cancer riskwas apparent.Heterogeneity in the evidence from all studies and from the highest quality studies was evident. Evidence from cohort studies is not sufficient to claim a convincing relationship exists between PA and CRC risk.

Education-to-work transitions of aspiring creatives

Despite some segments of the creative industries in Australia performing better than other segments in terms of earnings and employment growth, they all rely on highly skilled workers and face similar workforce challenges. Workers typically experience multiple entry attempts, spells of unemployment, short-term contracts, high degrees of mobility, casual/part-time employment within and outside the creative industries, and pressure to ensure their skills remain relevant. Skills shortages and gaps, an insufficient supply of high quality industry-ready graduates, difficulties in predicting demand for skills, weak linkages between industry and education providers, reliance on overseas talent in some segments, limited opportunities for workers to engage in skill development, and pressure on workers to keep abreast of technological developments are ongoing issues in the creative industries workforce. In response to these concerns, the Australian Research Council, three State Governments, industry, and a large vocational education and training (VET) provider funded Queensland University of Technology (QUT) to conduct the 60Sox project. This three-year project investigated the education, training, and work experiences of aspiring creatives defined as new entrants, recent graduates, and students enrolled in creative industries courses. It involved the largest survey of aspiring creatives ever undertaken in Australia, attracting 507 respondents, and a survey of 50 employers. Using the framework proposed by Hannan, Raffe, and Smyth (1996), this article presents findings from an analysis of the macro and micro labour market outcomes of aspiring creatives using data from the two 60Sox project surveys and publicly available sources. The analysis confirmed that many graduates of creative industries courses who participated in the 60Sox survey and the national surveys for the National Centre for Vocational Education Research and Graduate Careers Australia were struggling to make a successful transition from education to work. This article also discusses the causes of this key finding and possible solutions to address transition issues.

Coast control of train movement with genetic algorithms

Railway service is now the major transportation means in most of the countries around the world. With the increasing population and expanding commercial and industrial activities, a high quality of railway service is the most desirable. We present an application of genetic algorithms (GA) to search for the appropriate coasting point(s) and investigate the possible improvement on fitness of genes. Single and multiple coasting point control with simple GA are developed to attain the solutions and their corresponding train movement is examined. The multiple coasting point control with hierarchical genetic algorithm (HGA) is then proposed to integrate the determination of the number of coasting points.

Paediatric spinal deformity research at the Mater Children's Hospital, Brisbane, Australia.

The Paediatric Spine Research group was formed in 2002 to perform high quality research into the prevention and management of spinal deformity, with an emphasis on scoliosis. The group has successfully built collaborative bridges between the scientific and research expertise at QUT, and the clinical skills and experience of the spinal orthopaedic surgeons at the Mater Children’s Hospital in Brisbane. Clinical and biomechanical research is now possible as a result of the development of detailed databases of patients who have innovative and unique surgical interventions for spinal deformity such as thoracoscopic scoliosis correction, thoracoscopic staple insertion for juvenile idiopathic scoliosis and minimally invasive growing rods. The Mater in Brisbane provides these unique datasets of spinal deformity surgery patients, whose procedures are not being performed anywhere else in the Southern Hemisphere. The most detailed is a database of thoracoscopic scoliosis correction surgery which now contains 180 patients with electronic collections of X-Rays, photographs and patient questionnaires. With ethics approval, a subset of these patients has had CT scans, and a further subset have had MRI scans with and without a compressive load to simulate the erect standing position. This database has to date contributed to 17 international refereed journal papers, a further 7 journal papers either under review or in final preparation, 53 national conference presentations and 35 international conference presentations. Major findings from selected journal publications will be presented. It is anticipated that as the surgical databases grow they will continue to provide invaluable clinical data which will feed into clinically relevant projects driven by both medical and engineering researchers whose findings will benefit spinal deformity patients and scientific knowledge worldwide.

Coasting control of train operation by genetic algorithm

Balancing between the provision of high quality of service and running within a tight budget is one of the biggest challenges for most metro railway operators around the world. Conventionally, one possible approach for the operator to adjust the time schedule is to alter the stop time at stations, if other system constraints, such as traction equipment characteristic, are not taken into account. Yet it is not an effective, flexible and economical method because the run-time of a train simply cannot be extended without limitation, and a balance between run-time and energy consumption has to be maintained. Modification or installation of a new signalling system not only increases the capital cost, but also affects the normal train service. Therefore, in order to procure a more effective, flexible and economical means to improve the quality of service, optimisation of train performance by coasting point identification has become more attractive and popular. However, identifying the necessary starting points for coasting under the constraints of current service conditions is no simple task because train movement is attributed by a large number of factors, most of which are non-linear and inter-dependent. This paper presents an application of genetic algorithms (GA) to search for the appropriate coasting points and investigates the possible improvement on computation time and fitness of genes.

A comprehensive condition monitoring of modern railway

The demand for high quality rail services in the twenty-first century has put an ever increasing demand on all rail operators. In order to meet the expectation of their patrons, the maintenance regime of railway systems has to be tightened up, the track conditions have to be well looked after, the rolling stock must be designed to withstand heavy duty. In short, in an ideal world where resources are unlimited, one needs to implement a very rigorous inspection regime in order to take care of the modem needs of a railway system [1]. If cost were not an issue, the maintenance engineers could inspect the train body by the most up-to-date techniques such as ultra-sound examination, x-ray inspection, magnetic particle inspection, etc. on a regular basis. However it is inconceivable to have such a perfect maintenance regime in any commercial railway. Likewise, it is impossible to have a perfect rolling stock which can weather all the heavy duties experienced in a modem railway. Hence it is essential that some condition monitoring schemes are devised to pick up potential defects which could manifest into safety hazards. This paper introduces an innovative condition monitoring system for track profile and, together with an instrumented car to carry out surveillance of the track, will provide a comprehensive railway condition monitoring system which is free from the usual difficulty of electromagnetic compatibility issues in a typical railway environment

Transitioning toward transdisciplinary learning in a multidisciplinary environment

Multidisciplinary learning, interdisciplinary learning and transdisciplinary learning are often used with a similar meaning, but the misunderstanding of these terms may cause a failure of defining learner needs and developing high quality learning design. In this article, the three terms are reviewed in line with learner engagement and are conceptualised according to different types and levels of interactivity. An undergraduate course, named Creative Industries: Making Connections, was designed to deliver various learning modules to over 1200 students from 11 different disciplines in a blended learning mode. A visual communication learning module in the course, in particular, challenges students as well as academic staff to experience transdisciplinary learning. A survey was conducted to evaluate students' learning experience in the visual communication learning module. The results of the survey bring up meaningful implications for the realisation of transdisciplinary learning.

Interventions for preventing and managing aggressive patients admitted to an acute hospital setting: A systematic review

Background: Violence in health care has been widely reported and health care workers, particularly nurses in acute care settings, are ill-equipped to manage patients who exhibit aggressive traits. Aim: The aim of this systematic review was to establish best practice in the prevention and management of aggressive behaviours in patients admitted to acute hospital settings. Data Sources: An extensive search of the major databases was conducted from 1990 to 2007. The search included published and unpublished studies and papers in English. Review Methods: This review considered any quantitative research study design that evaluated the effectiveness of interventions in the prevention and management of patients who exhibit aggressive behaviours in an acute hospital setting. Each included study was quality assessed by two independent reviewers and data were extracted using the relevant tools developed by the Joanna Briggs Institute. Results: Ten studies met the inclusion criteria and were included in the review. The evidence identified from the studies includes: the benefit of education and training of acute care nurses in aggression management techniques; use of “as required” medications is effective in minimising harm to patients and staff; and that specific interventions such as physical restraint may play a role in managing aggressive behaviours from patients in the acute care setting. Conclusions: This review makes several recommendations for the prevention and management of aggressive behaviours in acute hospital patients. However, due to the lack of high-quality studies conducted in the acute care setting there is huge scope for future research in this area.

Supervisory safety practices in the work-related driving context

Work-related driving crashes are the most common cause of work-related injury, death, and absence from work in Australia and overseas. Surprisingly however, limited attention has been given to initiatives designed to improve safety outcomes in the work-related driving setting. This research paper will present preliminary findings from a research project designed to examine the effects of increasing work-related driving safety discussions on the relationship between drivers and their supervisors and motivations to drive safely. The research project was conducted within a community nursing population, where 112 drivers were matched with 23 supervisors. To establish discussions between supervisors and drivers, safety sessions were conducted on a monthly basis with supervisors of the drivers. At these sessions, the researcher presented context specific, audio-based anti-speeding messages. Throughout the course of the intervention and following each of these safety sessions, supervisors were instructed to ensure that all drivers within their workgroup listened to each particular anti-speeding message at least once a fortnight. In addition to the message, supervisors were also encouraged to frequently promote the anti-speeding message through any contact they had with their drivers (i.e., face to face, email, SMS text, and/or paper based contact). Fortnightly discussions were subsequently held with drivers, whereby the researchers ascertained the number and type of discussions supervisors engaged in with their drivers. These discussions also assessed drivers’ perceptions of the group safety climate. In addition to the fortnightly discussion, drivers completed a daily speed reporting form which assessed the proportion of their driving day spent knowingly over the speed limit. As predicted, the results found that if supervisors reported a good safety climate prior to the intervention, increasing the number of safety discussions resulted in drivers reporting a high quality relationship (i.e., leader-member exchange) with their supervisor post intervention. In addition, if drivers reported a good safety climate, increasing the number of discussions resulted in increased motivation to drive safely post intervention. Motivations to drive safely prior to the intervention also predicted self-reported speeding over the subsequent three months of reporting. These results suggest safety discussions play an important role in improving the exchange between supervisors and their drivers and drivers’ subsequent motivation to drive safely and, in turn, self reported speeding.