995 resultados para crash data


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Purpose Intensity modulated radiotherapy (IMRT) treatments require more beam-on time and produce more linac head leakage to deliver similar doses to conventional, unmodulated, radiotherapy treatments. It is necessary to take this increased leakage into account when evaluating the results of radiation surveys around bunkers that are, or will be, used for IMRT. The recommended procedure of 15 applying a monitor-unit based workload correction factor to secondary barrier survey measurements, to account for this increased leakage when evaluating radiation survey measurements around IMRT bunkers, can lead to potentially-costly over estimation of the required barrier thickness. This study aims to provide initial guidance on the validity of reducing the value of the correction factor when applied to different radiation barriers (primary barriers, doors, maze walls and other walls) by 20 evaluating three different bunker designs. Methods Radiation survey measurements of primary, scattered and leakage radiation were obtained at each of five survey points around each of three different radiotherapy bunkers and the contribution of leakage to the total measured radiation dose at each point was evaluated. Measurements at each survey point were made with the linac gantry set to 12 equidistant positions from 0 to 330o, to 25 assess the effects of radiation beam direction on the results. Results For all three bunker designs, less than 0.5% of dose measured at and alongside the primary barriers, less than 25% of the dose measured outside the bunker doors and up to 100% of the dose measured outside other secondary barriers was found to be caused by linac head leakage. Conclusions Results of this study suggest that IMRT workload corrections are unnecessary, for 30 survey measurements made at and alongside primary barriers. Use of reduced IMRT workload correction factors is recommended when evaluating survey measurements around a bunker door, provided that a subset of the measurements used in this study are repeated for the bunker in question. Reduction of the correction factor for other secondary barrier survey measurements is not recommended unless the contribution from leakage is separetely evaluated.

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Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

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This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.

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Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.

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Macroscopic Fundamental Diagram (MFD) has been proved to exist in large urban road and freeway networks by theoretic method and real data in cities. However hysteresis and scatters have also been found existed both on motorway network and urban road. This paper investigates how the incident variables affect the scatter and shape of the MFD using both the simulated data and the real data collected from the Pacific Motorway M3 in Brisbane, Australia. Three key components of incident are investigated based on the simulated data: incident location, incident duration time and traffic demand. Results based on the simulated data indicate that MFD shape is a property not only of the network itself but also of the incident characteristics variables. MFDs for three types of real incidents (crash, hazard and breakdown) are explored separately. The results based on the empirical data are consistent with the simulated results. The hysteresis phenomenon occurs on both the upstream and the downstream of the incident location, but for opposite hysteresis loops. Gradient of the MFD for the upstream is more than that for the downstream on the incident site, when traffic demand is off peak.

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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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Numerous statements and declarations have been made over recent decades in support of open access to research data. The growing recognition of the importance of open access to research data has been accompanied by calls on public research funding agencies and universities to facilitate better access to publicly funded research data so that it can be re-used and redistributed as public goods. International and inter-governmental bodies such as the ICSU/CODATA, the OECD and the European Union are strong supporters of open access to and re-use of publicly funded research data. This thesis focuses on the research data created by university researchers in Malaysian public universities whose research activities are funded by the Federal Government of Malaysia. Malaysia, like many countries, has not yet formulated a policy on open access to and re-use of publicly funded research data. Therefore, the aim of this thesis is to develop a policy to support the objective of enabling open access to and re-use of publicly funded research data in Malaysian public universities. Policy development is very important if the objective of enabling open access to and re-use of publicly funded research data is to be successfully achieved. In developing the policy, this thesis identifies a myriad of legal impediments arising from intellectual property rights, confidentiality, privacy and national security laws, novelty requirements in patent law and lack of a legal duty to ensure data quality. Legal impediments such as these have the effect of restricting, obstructing, hindering or slowing down the objective of enabling open access to and re-use of publicly funded research data. A key focus in the formulation of the policy was the need to resolve the various legal impediments that have been identified. This thesis analyses the existing policies and guidelines of Malaysian public universities to ascertain to what extent the legal impediments have been resolved. An international perspective is adopted by making a comparative analysis of the policies of public research funding agencies and universities in the United Kingdom, the United States and Australia to understand how they have dealt with the identified legal impediments. These countries have led the way in introducing policies which support open access to and re-use of publicly funded research data. As well as proposing a policy supporting open access to and re-use of publicly funded research data in Malaysian public universities, this thesis provides procedures for the implementation of the policy and guidelines for addressing the legal impediments to open access and re-use.

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Collecting regular personal reflections from first year teachers in rural and remote schools is challenging as they are busily absorbed in their practice, and separated from each other and the researchers by thousands of kilometres. In response, an innovative web-based solution was designed to both collect data and be a responsive support system for early career teachers as they came to terms with their new professional identities within rural and remote school settings. Using an emailed link to a web-based application named goingok.com, the participants are charting their first year plotlines using a sliding scale from ‘distressed’, ‘ok’ to ‘soaring’ and describing their self-assessment in short descriptive posts. These reflections are visible to the participants as a developing online journal, while the collections of de-identified developing plotlines are visible to the research team, alongside numerical data. This paper explores important aspects of the design process, together with the challenges and opportunities encountered in its implementation. A number of the key considerations for choosing to develop a web application for data collection are initially identified, and the resultant application features and scope are then examined. Examples are then provided about how a responsive software development approach can be part of a supportive feedback loop for participants while being an effective data collection process. Opportunities for further development are also suggested with projected implications for future research.

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The need to address on-road motorcycle safety in Australia is important due to the disproportionately high percentage of riders and pillions killed and injured each year. One approach to preventing motorcycle-related injury is through training and education. However, motorcycle rider training lacks empirical support as an effective road safety countermeasure to reduce crash involvement. Previous reviews have highlighted that risk-taking is a contributing factor in many motorcycle crashes, rather than merely a lack of vehicle-control skills (Haworth & Mulvihill, 2005; Jonah, Dawson & Bragg, 1982; Watson et al, 1996). Hence, though the basic vehicle-handling skills and knowledge of road rules that are taught in most traditional motorcycle licence training programs may be seen as an essential condition of safe riding, they do not appear to be sufficient in terms of crash reduction. With this in mind there is considerable scope for the improvement of program focus and content for rider training and education. This program of research examined an existing traditional pre-licence motorcycle rider training program and formatively evaluated the addition of a new classroom-based module to address risky riding; the Three Steps to Safer Riding program. The pilot program was delivered in the real world context of the Q-Ride motorcycle licensing system in the state of Queensland, Australia. Three studies were conducted as part of the program of research: Study 1, a qualitative investigation of delivery practices and student learning needs in an existing rider training course; Study 2, an investigation of the extent to which an existing motorcycle rider training course addressed risky riding attitudes and motives; and Study 3, a formative evaluation of the new program. A literature review as well as the investigation of learning needs for motorcyclists in Study 1 aimed to inform the initial planning and development of the Three Steps to Safer Riding program. Findings from Study 1 suggested that the training delivery protocols used by the industry partner training organisation were consistent with a learner-centred approach and largely met the learning needs of trainee riders. However, it also found that information from the course needs to be reinforced by on-road experiences for some riders once licensed and that personal meaning for training information was not fully gained until some riding experience had been obtained. While this research informed the planning and development of the new program, a project team of academics and industry experts were responsible for the formulation of the final program. Study 2 and Study 3 were conducted for the purpose of formative evaluation and program refinement. Study 2 served primarily as a trial to test research protocols and data collection methods with the industry partner organisation and, importantly, also served to gather comparison data for the pilot program which was implemented with the same rider training organisation. Findings from Study 2 suggested that the existing training program of the partner organisation generally had a positive (albeit small) effect on safety in terms of influencing attitudes to risk taking, the propensity for thrill seeking, and intentions to engage in future risky riding. However, maintenance of these effects over time and the effects on riding behaviour remain unclear due to a low response rate upon follow-up 24 months after licensing. Study 3 was a formative evaluation of the new pilot program to establish program effects and possible areas for improvement. Study 3a examined the short term effects of the intervention pilot on psychosocial factors underpinning risky riding compared to the effects of the standard traditional training program (examined in Study 2). It showed that the course which included the Three Steps to Safer Riding program elicited significantly greater positive attitude change towards road safety than the existing standard licensing course. This effect was found immediately following training, and mean scores for attitudes towards safety were also maintained at the 12 month follow-up. The pilot program also had an immediate effect on other key variables such as risky riding intentions and the propensity for thrill seeking, although not significantly greater than the traditional standard training. A low response rate at the 12 month follow-up unfortunately prevented any firm conclusions being drawn regarding the impact of the pilot program on self-reported risky riding once licensed. Study 3a further showed that the use of intermediate outcomes such as self-reported attitudes and intentions for evaluation purposes provides insights into the mechanisms underpinning risky riding that can be changed by education and training. A multifaceted process evaluation conducted in Study 3b confirmed that the intervention pilot was largely delivered as designed, with course participants also rating most aspects of training delivery highly. The complete program of research contributed to the overall body of knowledge relating to motorcycle rider training, with some potential implications for policy in the area of motorcycle rider licensing. A key finding of the research was that psychosocial influences on risky riding can be shaped by structured education that focuses on awareness raising at a personal level and provides strategies to manage future riding situations. However, the formative evaluation was mainly designed to identify areas of improvement for the Three Steps to Safer Riding program and found several areas of potential refinement to improve future efficacy of the program. This included aspects of program content, program delivery, resource development, and measurement tools. The planned future follow-up of program participants' official crash and traffic offence records over time may lend further support for the application of the program within licensing systems. The findings reported in this thesis offer an initial indication that the Three Steps to Safer Riding is a useful resource to accompany skills-based training programs.

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In contemporary game development circles the ‘game making jam’ has become an important rite of passage and baptism event, an exploration space and a central indie lifestyle affirmation and community event. Game jams have recently become a focus for design researchers interested in the creative process. In this paper we tell the story of an established local game jam and our various documentation and data collection methods. We present the beginnings of the current project, which seeks to map the creative teams and their process in the space of the challenge, and which aims to enable participants to be more than the objects of the data collection. A perceived issue is that typical documentation approaches are ‘about’ the event as opposed to ‘made by’ the participants and are thus both at odds with the spirit of the jam as a phenomenon and do not really access the rich playful potential of participant experience. In the data collection and visualisation projects described here, we focus on using collected data to re-include the participants in telling stories about their experiences of the event as a place-based experience. Our goal is to find a means to encourage production of ‘anecdata’ - data based on individual story telling that is subjective, malleable, and resists collection via formal mechanisms - and to enable mimesis, or active narrating, on the part of the participants. We present a concept design for data as game based on the logic of early medieval maps and we reflect on how we could enable participation in the data collection itself.

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Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

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Scooter and moped sales have increased at a faster rate than motorcycle sales over the last decade in countries such as Australia, Canada and the United States. This may be particularly evident in jurisdictions where moped riding is permitted for car license holders and a motorcycle license is not required, such as in Queensland, Australia. Having historically comprised only a small proportion of powered two-wheelers (PTWs) outside of Europe and Asia, the safety of scooters and mopeds has received relatively little focused research attention. However, the recent trends in sales and crash involvement have stimulated greater interest in these PTW types. The current paper examines differences and similarities between scooters (over 50cc), mopeds (up to 50cc) and motorcycles in crash involvement and crash characteristics through analyses of crash and registration data from Queensland, Australia. The main findings include that moped and scooter riders are similar in terms of usage patterns, but the evidence suggests superior skills, greater experience and safer behaviour among scooter riders than moped riders. The requirement in Queensland for scooter riders but not moped riders to hold a motorcycle license, usually obtained through competency-based training and assessment, may help to explain some of this difference. Findings also suggest that scooter riders are safer than motorcycle riders in some respects, despite both being subject to the same licensing requirements which encourage participation in rider training. Safer attitudes and motivations rather than superior skills and knowledge may therefore underlie the differences between scooter and motorcycle riders. In summary, riders of larger scooters exhibit a combination of skills and behavior suggestive of safer riding than both their moped and motorcycle riding counterparts. It is reasonable to expect that mopeds and scooters will remain popular and that their usage may increase further, along with that of motorcycles. This research therefore has important practical implications regarding pathways to improved PTW safety. Future policy and planning should consider options for encouraging moped riders to acquire better riding skills and greater safety awareness, as apparent among scooter riders, including rider training, education and licensing. As is noted in recent literature and reflected in some contemporary rider training programs, motorcycle safety may be improved by addressing rider attitudes more comprehensively in addition to developing skills and knowledge.

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A 3-year longitudinal study Transforming Children’s Mathematical and Scientific Development integrates, through data modelling, a pedagogical approach focused on mathematical patterns and structural relationships with learning in science. As part of this study, a purposive sample of 21 highly able Grade 1 students was engaged in an innovative data modelling program. In the majority of students, representational development was observed. Their complex graphs depicting categorical and continuous data revealed a high level of structure and enabled identification of structural features critical to this development.

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The activities introduced here were used in association with a research project in four Year 4 classrooms and are suggested as a motivating way to address several criteria for Measurement and Data in the Australian Curriculum: Mathematics. The activities involve measuring the arm span of one student in a class many times and then of all students once.

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Trees are capable of portraying the semi-structured data which is common in web domain. Finding similarities between trees is mandatory for several applications that deal with semi-structured data. Existing similarity methods examine a pair of trees by comparing through nodes and paths of two trees, and find the similarity between them. However, these methods provide unfavorable results for unordered tree data and result in yielding NP-hard or MAX-SNP hard complexity. In this paper, we present a novel method that encodes a tree with an optimal traversing approach first, and then, utilizes it to model the tree with its equivalent matrix representation for finding similarity between unordered trees efficiently. Empirical analysis shows that the proposed method is able to achieve high accuracy even on the large data sets.