951 resultados para improvements
Resumo:
There have been many improvements in Australian engineering education since the 1990s. However, given the recent drive for assuring the achievement of identified academic standards, more progress needs to be made, particularly in the area of evidence-based assessment. This paper reports on initiatives gathered from the literature and engineering academics in the USA, through an Australian National Teaching Fellowship program. The program aims to establish a process to help academics in designing and implementing evidence-based assessments that meet the needs of not only students and the staff that teach them, but also industry as well as accreditation bodies. The paper also examines the kinds and levels of support necessary for engineering academics, especially early career ones, to help meet the expectations of the current drive for assured quality and standards of both research and teaching. Academics are experiencing competing demands on their time and energy with very high expectations in research performance and increased teaching responsibilities, although many are researchers who have not had much pedagogic training. Based on the literature and investigation of relevant initiatives in the USA, we conducted interviews with several identified experts and change agents who have wrought effective academic cultural change within their institutions and beyond. These reveal that assuring the standards and quality of student learning outcomes through evidence-based assessments cannot be appropriately addressed without also addressing the issue of pedagogic training for academic staff. To be sustainable, such training needs to be complemented by a culture of on-going mentoring support from senior academics, formalised through the university administration, so that mentors are afforded resources, time, and appropriate recognition.
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We conducted a randomized controlled trial to test whether a Brief Mobile Treatment (BMT) intervention could improve outcomes relative to usual care among suicide attempters. The intervention included training in problem solving therapy, meditation, a brief intervention to increase social support as well as advice on alcohol and other drugs, and mobile phone follow-up. The effect of the intervention was measured in terms of a reduction in suicidal ideation, depression and self-harm at Baseline, six and 12 months. A wait-list control group received usual care. A total of 68 participants was recruited from a Sri Lankan hospital following a suicide attempt. Participants who received the intervention were found to achieve significant improvements in reducing suicidal ideation and depression than those receiving usual care. The BMT group also experienced a significant improvement of social support when compared to the control group. However, the BMT group did not demonstrate a significant effect in reducing actual self-harm and most substance use, and differential effects on alcohol use were restricted to men. Although the present study was limited in revealing which component of the intervention was more effective in preventing suicide, it showed its efficacy in reducing suicide as a whole.
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The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.
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This paper illustrates a field research performed with a team of experts involved in the evaluation of Trippple, a system aimed at supporting the different phases of a tourist trip, in order to provide feedback and insights, both on the functionalities already implemented (that at the time of evaluation were available only as early and very unstable prototypes), and on the functionalities still to be implemented. We show how the involvement of professionals helped to focus on challenging aspects, instead of less important, cosmetic, issues and resulted profitable in terms of early feedback, issues spotted, and improvements suggested
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Purpose The aim was to assess the effects of a Tai Chi based program on health related quality of life (HR-QOL) in people with elevated blood glucose or diabetes who were not on medication for glucose control. Method 41 participants were randomly allocated to either a Tai Chi intervention group (N = 20) or a usual medical care control group (N = 21). The Tai Chi group involved 3 x 1.5 hour supervised and group-based training sessions per week for 12 weeks. Indicators of HR-QOL were assessed by self-report survey immediately prior to and after the intervention. Results There were significant improvements in favour of the Tai Chi group for the SF36 subscales of physical functioning (mean difference = 5.46, 95% CI = 1.35-9.57, P < 0.05), role physical (mean difference = 18.60, 95% CI = 2.16-35.05, P < 0.05), bodily pain (mean difference = 9.88, 95%CI = 2.06-17.69, P < 0.05) and vitality (mean difference = 9.96, 95% CI = 0.77-19.15, P < 0.05). Conclusions The findings show that this Tai Chi program improved indicators of HR-QOL including physical functioning, role physical, bodily pain and vitality in people with elevated blood glucose or diabetes who were not on diabetes medication.
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We investigate the evolving quality of entrepreneurship in the Gold Coast Marine Precinct, a purpose-built industrial district in Southeast Queensland, Australia. Our findings are that the environment in the Precinct can be conducive to a better quality of entrepreneurship than may be feasible for firms in other settings; that a successful industrial district can be created artificially, with appropriate social relationships evolving afterwards; and that improvements in information and communications technology have undermined some aspects of traditional behaviour in the Precinct, but the essential nature of internal relationships remains intact.
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Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.
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A comparison was made of accelerated professional development (APD) for nurses (n=64), involving peer consultation and reflective practice, and peer consultation alone (n=30). Although APD participants had a higher completion rate, improvements in caregiver behaviors and work environment were not significantly different.
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Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.
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Background subtraction is a fundamental low-level processing task in numerous computer vision applications. The vast majority of algorithms process images on a pixel-by-pixel basis, where an independent decision is made for each pixel. A general limitation of such processing is that rich contextual information is not taken into account. We propose a block-based method capable of dealing with noise, illumination variations, and dynamic backgrounds, while still obtaining smooth contours of foreground objects. Specifically, image sequences are analyzed on an overlapping block-by-block basis. A low-dimensional texture descriptor obtained from each block is passed through an adaptive classifier cascade, where each stage handles a distinct problem. A probabilistic foreground mask generation approach then exploits block overlaps to integrate interim block-level decisions into final pixel-level foreground segmentation. Unlike many pixel-based methods, ad-hoc postprocessing of foreground masks is not required. Experiments on the difficult Wallflower and I2R datasets show that the proposed approach obtains on average better results (both qualitatively and quantitatively) than several prominent methods. We furthermore propose the use of tracking performance as an unbiased approach for assessing the practical usefulness of foreground segmentation methods, and show that the proposed approach leads to considerable improvements in tracking accuracy on the CAVIAR dataset.
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The effort to make schools more inclusive, together with the pressure to retain students until the end of secondary school, has greatly increased both the number and educational requirements of students enrolling in their local school. Of critical concern, despite years of research and improvements in policy, pedagogy and educational knowledge, is the enduring categorisation and marginalization of students with diverse abilities. Research has shown that it can be difficult for schools to negotiate away from the pressure to categorise or diagnose such students, particularly those with challenging behaviour. In this paper, we highlight instances where some schools have responded to increasing diversity by developing new cultural practices to engage both staff and students; in some cases, decreasing suspension while improving retention, behaviour and performance.
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Recent advances in the planning and delivery of radiotherapy treatments have resulted in improvements in the accuracy and precision with which therapeutic radiation can be administered. As the complexity of the treatments increases it becomes more difficult to predict the dose distribution in the patient accurately. Monte Carlo methods have the potential to improve the accuracy of the dose calculations and are increasingly being recognised as the “gold standard” for predicting dose deposition in the patient. In this study, software has been developed that enables the transfer of treatment plan information from the treatment planning system to a Monte Carlo dose calculation engine. A database of commissioned linear accelerator models (Elekta Precise and Varian 2100CD at various energies) has been developed using the EGSnrc/BEAMnrc Monte Carlo suite. Planned beam descriptions and CT images can be exported from the treatment planning system using the DICOM framework. The information in these files is combined with an appropriate linear accelerator model to allow the accurate calculation of the radiation field incident on a modelled patient geometry. The Monte Carlo dose calculation results are combined according to the monitor units specified in the exported plan. The result is a 3D dose distribution that could be used to verify treatment planning system calculations. The software, MCDTK (Monte Carlo Dicom ToolKit), has been developed in the Java programming language and produces BEAMnrc and DOSXYZnrc input files, ready for submission on a high-performance computing cluster. The code has been tested with the Eclipse (Varian Medical Systems), Oncentra MasterPlan (Nucletron B.V.) and Pinnacle3 (Philips Medical Systems) planning systems. In this study the software was validated against measurements in homogenous and heterogeneous phantoms. Monte Carlo models are commissioned through comparison with quality assurance measurements made using a large square field incident on a homogenous volume of water. This study aims to provide a valuable confirmation that Monte Carlo calculations match experimental measurements for complex fields and heterogeneous media.
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BACKGROUND: Although many studies have shown that high temperatures are associated with an increased risk of mortality and morbidity, there has been little research on managing the process of planned adaptation to alleviate the health effects of heat events and climate change. In particular, economic evaluation of public health adaptation strategies has been largely absent from both the scientific literature and public policy discussion. OBJECTIVES: his paper aims to discuss how public health organizations should implement adaptation strategies, and how to improve the evidence base for policies to protect health from heat events and climate change. DISCUSSION: Public health adaptation strategies to cope with heat events and climate change fall into two categories: reducing the heat exposure and managing the health risks. Strategies require a range of actions, including timely public health and medical advice, improvements to housing and urban planning, early warning systems, and the assurance that health care and social systems are ready to act. Some of these actions are costly, and the implementation should be based on the cost-effectiveness analysis given scarce financial resources. Therefore, research is required not only on the temperature-related health costs, but also on the costs and benefits of adaptation options. The scientific community must ensure that the health co-benefits of climate change policies are recognized, understood and quantified. CONCLUSIONS: The integration of climate change adaptation into current public health practice is needed to ensure they increase future resilience. The economic evaluation of temperature-related health costs and public health adaptation strategies are particularly important for policy decisions.
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Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency.
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Living with substance users negatively impacts upon family members in many ways, and distress is common. Despite these deep and wide-ranging impacts, supportive interventions for family members in their own right are rarely available. Thailand has substantial and growing problems with substance use, and there is very little support or family members of drug users, especially in community setting. The Thai Family Support (TFS) program was designed for implementation in primary health care units (PCUs) in Thailand. TFS was based on two approaches with existing empirical support in Western contexts—the 5-step method and CRAFT—with adaptations to a Thai setting that included integration with Buddhist practices. Its aims were to increase well-being of family members, reduce mental distress, improve family relationships between family members, and engage substance users in behaviour change. A small-scale randomised controlled trial on TFS with a Delayed Treatment control was conducted, with assessments at 8 weeks (Post 1) and 20-24 weeks (Post 2). Structured interviews with participants and PCU staff and an examination of five case studies augmented the quantitative results. Mixed Model Analyses were applied to quantitative outcomes, and thematic analysis was used for qualitative data. Thirty-six participants (18 in each of Immediate and Delayed Conditions) were recruited. A significant difference at Baseline between the two conditions was observed on the Thai GHQ-28 and Gender, but it was not possible to statistically control for these effects. There was a significant Time by Condition interaction on the Thai GHQ-28, WHOQOL-BREF-THAI and FAS, reflecting greater improvements in the Immediate condition by Post 1, but with the Delayed condition meeting or exceeding that effect by Post 2. On FES Cohesion and Conflict, there were falls across conditions at Post 2, but only Cohesion also showed a Time by Condition interaction, and that effect was consistent with a delayed impact of treatment. Overall, TFS by PCU staff in the Delayed Condition gave similar results to TFS conducted by the researcher, supporting the viability of its dissemination to standard health services. Qualitative data also confirmed the quantitative results. Most participants reported physiological and psychological improvements even though their substance-using relative did not change their drug use behaviour. After completing TFS, participants reported increased knowledge, group support and sharing feeling, having positive patient-professional relationship, having greater knowledge of substance abuse and social support. In particular, they changed their behaviour towards the substance user, resulting in improvements to family relationships. PCU staff gave similar responses on the efficacy of TFS, and saw it as feasible for routine use, although some implementation challenges were identified. The cultural adaptation and in particular the religious activities, were recognised by participants and PCU staff as an important component of TFS to support psychological health and well-being. Findings from this study showed the impact of substance use on family members and difficulties that they experienced when living with the substance users, resulting distresses and burden that may develop severe mental health disease. Drug use policies should be modified to support family members and response to their needs effectively for early prevention. This study also gave preliminary support for application of the TFS program in rural primary care settings and identified some policies that will be required for it to be disseminated more broadly.