510 resultados para ELECTRICAL CHARACTERISTICS


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Objectives: The purpose of this study was to investigate the characteristics associated with fatal and non-fatal low-speed vehicle run-over (LSVRO) events in relation to person, incident and injury characteristics, in order to identify appropriate points for intervention and injury prevention. Methods: Data on all known LSVRO events in Queensland, Australia, over 11 calendar years (1999–2009) were extracted from five different databases representing the continuum of care ( prehospital to fatality) and manually linked. Descriptive and multivariate analyses were used to analyse the sample characteristics in relation to demographics, health service usage, outcomes, incident characteristics, and injury characteristics. Results: Of the 1641 LSVRO incidents, 98.4% (n=1615) were non-fatal, and 1.6% were fatal (n=26). Over half the children required admission to hospital (56%, n=921); mean length of stay was 3.4 days. Younger children aged 0–4 years were more frequently injured, and experienced more serious injuries with worse outcomes. Patterns of injury (injury type and severity), injury characteristics (eg, time of injury, vehicle type, driver of vehicle, incident location), and demographic characteristics (such as socioeconomic status, indigenous status, remoteness), varied according to age group. Almost half (45.6%; n=737) the events occurred outside major cities, and approximately 10% of events involved indigenous children. Parents were most commonly the vehicle drivers in fatal incidents. While larger vehicles such as four-wheel drives (4WD) were most frequently involved in LSVRO events resulting in fatalities, cars were most frequently involved in non-fatal events. Conclusions: This is the first study, to the authors’ knowledge, to analyse the characteristics of fatal and non-fatal LSVRO events in children aged 0–15 years on a state-wide basis. Characteristics of LSVRO events varied with age, thus age-specific interventions are required. Children living outside major cities, and indigenous children, were over-represented in these data. Further research is required to identify the burden of injury in these groups.

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Due to significant increase in vehicular accident and traffic congestions, vehicle to vehicle (V2V) communication based on the intelligent transport system (ITS) was introduced. However, to carry out efficient design and implementation of a reliable vehicular communication systems,a deep knowledge of the propagation channel characteristics in different environments is crucial, in particular the Doppler and pathloss parameters. Therefore, this paper presents an empirical V2V channel characterization and measurement performed under realistic urban, suburban and highway driving conditions in Brisbane, Australia. Based on Lin Cheng statistical Doppler Model (LCDM), values for the RMS Doppler spread and coherence time due to time selective nature of V2V channels were presented. Also, based on Log-distance power law model, values for the mean pathloss exponent and the standard deviation of shadowing were reported for urban, suburban and highway environments. The V2V channel parameters can be useful to system designers for the purpose of evaluating, simulating and developing new protocols and systems.

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This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

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This research was a step forward in investigating the characteristics of recycled concrete aggregates to use as an unbound pavement material. The results present the guidelines for successfully application of recycled concrete aggregates in high traffic volume roads. Outcomes of the research create more economical and environmental benefits through reducing the depletion of natural resources and effectively manage the generated concrete waste before disposal as land fill.

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This paper reports profiling information for speeding offenders and is part of a larger project that assessed the deterrent effects of increased speeding penalties in Queensland, Australia, using a total of 84,456 speeding offences. The speeding offenders were classified into three groups based on the extent and severity of an index offence: once-only low-rang offenders; repeat high-range offenders; and other offenders. The three groups were then compared in terms of personal characteristics, traffic offences, crash history and criminal history. Results revealed a number of significant differences between repeat high-range offenders and those in the other two offender groups. Repeat high-range speeding offenders were more likely to be male, younger, hold a provisional and a motorcycle licence, to have committed a range of previous traffic offences, to have a significantly greater likelihood of crash involvement, and to have been involved in multiple-vehicle crashes than drivers in the other two offender types. Additionally, when a subset of offenders’ criminal histories were examined, results revealed that repeat high-range speeding offenders were also more likely to have committed a previous criminal offence compared to once only low-range and other offenders and that 55.2% of the repeat high-range offenders had a criminal history. They were also significantly more likely to have committed drug offences and offences against order than the once only low-range speeding offenders, and significantly more likely to have committed regulation offences than those in the other offenders group. Overall, the results indicate that speeding offenders are not an homogeneous group and that, therefore, more tailored and innovative sanctions should be considered and evaluated for high-range recidivist speeders because they are a high-risk road user group.

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With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.

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Conventional voltage driven gate drive circuits utilise a resistor to control the switching speed of power MOS-FETs. The gate resistance is adjusted to provide controlled rate of change of load current and voltage. The cascode gate drive configuration has been proposed as an alternative to the conventional resistor-fed gate drive circuit. While cascode drive is broadly understood in the literature the switching characteristics of this topology are not well documented. This paper explores, through both simulation and experimentation, the gate drive parameter space of the cascode gate drive configuration and provides a comparison to the switching characteristics of conventional gate drive.

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A systematic literature review and a comprehensive meta-analysis that combines the findings from existing studies, was conducted in this thesis to analyse the impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to investigate the quality, publication bias and outlier bias of the various studies, and the time intervals used to measure traffic characteristics were considered. Based on this comprehensive and systematic review, and the results of the subsequent meta-analysis, major issues in study design, traffic and crash data, and model development and evaluation are discussed.

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There is a great deal of research that examines flexible working arrangements, but this work tends to be concentrated in large organisations. This research examines the approach taken to flexible working arrangements in five small community based, not for profit organisations. We present three propositions that aim to understand the constraints and the characteristics of flexible work in this rarely studied sector.

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Injection velocity has been recognized as a key variable in thermoplastic injection molding. Its closed-loop control is, however, difficult due to the complexity of the process dynamic characteristics. The basic requirements of the control system include tracking of a pre-determined injection velocity curve defined in a profile, load rejection and robustness. It is difficult for a conventional control scheme to meet all these requirements. Injection velocity dynamics are first analyzed in this paper. Then a novel double-controller scheme is adopted for the injection velocity control. This scheme allows an independent design of set-point tracking and load rejection and has good system robustness. The implementation of the double-controller scheme for injection velocity control is discussed. Special techniques such as profile transformation and shifting are also introduced to improve the velocity responses. The proposed velocity control has been experimentally demonstrated to be effective for a wide range of processing conditions.