242 resultados para vehicle-driver model

em University of Queensland eSpace - Australia


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Community-based models for injury prevention have become an accepted part of the overall injury control strategy. This systematic review of the scientific literature examines the evidence for their effectiveness in reducing pedestrian injury in children 0-14 years of age. A comprehensive search of the literature was performed using the following study selection criteria: community-based intervention study; target population was children under 14 years; outcome measure is either pedestrian injury rates or observed child pedestrian or vehicle driver behaviour; and use of a community control or an historical control in the study design. Quality assessment and data abstraction was guided by a standardized procedure and performed independently by two authors. Data synthesis was in tabular and text form with meta-analysis not being possible due to the discrepancy in methods and measures between the studies.

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The current study was designed to confirm that female drivers sit closer to the steering wheel than do male drivers and to investigate whether this expected difference in sitting position is attributable to differences in the physical dimensions of men and women. Driver body dimensions and multiple measures of sitting distance from the steering wheel were collected from a sample of 150 men and 150 women. The results confirmed that on average, women sit closer to the steering wheel than men do and that this difference is accounted for by variations in body dimensions, especially height. This result suggests that driver height may provide a good surrogate for sitting distance from the steering wheel when investigating the role of driver position in real-world crash outcomes. The potential applications of this research include change to vehicle design that allows independent adjustment of the relative distance among the driver's seat, the steering wheel, and the floor pedals.

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This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

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Some motor tasks can be completed, quite literally, with our eyes shut. Most people can touch their nose without looking or reach for an object after only a brief glance at its location. This distinction leads to one of the defining questions of movement control: is information gleaned prior to starting the movement sufficient to complete the task (open loop), or is feedback about the progress of the movement required (closed loop)? One task that has commanded considerable interest in the literature over the years is that of steering a vehicle, in particular lane-correction and lane-changing tasks. Recent work has suggested that this type of task can proceed in a fundamentally open loop manner [1 and 2], with feedback mainly serving to correct minor, accumulating errors. This paper reevaluates the conclusions of these studies by conducting a new set of experiments in a driving simulator. We demonstrate that, in fact, drivers rely on regular visual feedback, even during the well-practiced steering task of lane changing. Without feedback, drivers fail to initiate the return phase of the maneuver, resulting in systematic errors in final heading. The results provide new insight into the control of vehicle heading, suggesting that drivers employ a simple policy of “turn and see,” with only limited understanding of the relationship between steering angle and vehicle heading.

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HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

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The diffusion model for percutaneous absorption is developed for the specific case of delivery to the skin being limited by the application of a finite amount of solute. Two cases are considered; in the first, there is an application of a finite donor (vehicle) volume, and in the second, there are solvent-deposited solids and a thin vehicle with a high partition coefficient. In both cases, the potential effect of an interfacial resistance at the stratum corneum surface is also considered. As in the previous paper, which was concerned with the application of a constant donor concentration, clearance limitations due to the viable eqidermis, the in vitro sampling rate, or perfusion rate in vivo are included. Numerical inversion of the Laplace domain solutions was used for simulations of solute flux and cumulative amount absorbed and to model specific examples of percutaneous absorption of solvent-deposited solids. It was concluded that numerical inversions of the Laplace domain solutions for a diffusion model of the percutaneous absorption, using standard scientific software (such as SCIENTIST, MicroMath Scientific software) on modern personal computers, is a practical alternative to computation of infinite series solutions. Limits of the Laplace domain solutions were used to define the moments of the flux-time profiles for finite donor volumes and the slope of the terminal log flux-time profile. The mean transit time could be related to the diffusion time through stratum corneum, viable epidermal, and donor diffusion layer resistances and clearance from the receptor phase. Approximate expressions for the time to reach maximum flux (peak time) and maximum flux were also derived. The model was then validated using reported amount-time and flux-time profiles for finite doses applied to the skin. It was concluded that for very small donor phase volume or for very large stratum corneum-vehicle partitioning coefficients (e.g., for solvent deposited solids), the flux and amount of solute absorbed are affected by receptor conditions to a lesser extent than is obvious for a constant donor constant donor concentrations. (C) 2001 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 90:504-520, 2001.

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Pasminco Century Mine has developed a geophysical logging system to provide new data for ore mining/grade control and the generation of Short Term Models for mine planning. Previous work indicated the applicability of petrophysical logging for lithology prediction, however, the automation of the method was not considered reliable enough for the development of a mining model. A test survey was undertaken using two diamond drilled control holes and eight percussion holes. All holes were logged with natural gamma, magnetic susceptibility and density. Calibration of the LogTrans auto-interpretation software using only natural gamma and magnetic susceptibility indicated that both lithology and stratigraphy could be predicted. Development of a capability to enforce stratigraphic order within LogTrans increased the reliability and accuracy of interpretations. After the completion of a feasibility program, Century Mine has invested in a dedicated logging vehicle to log blast holes as well as for use in in-fill drilling programs. Future refinement of the system may lead to the development of GPS controlled excavators for mining ore.

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Purpose : The purpose of this article is to critically review the literature to examine factors that are most consistently related to employment outcome following traumatic brain injury (TBI), with a particular focus on metacognitive skills. It also aims to develop a conceptual model of factors related to employment outcome. Method : The first stage of the review considered 85 studies published between 1980 and December 2003 which investigated factors associated with employment outcome following TBI. English-language studies were identified through searches of Medline and PsycINFO, as well as manual searches of journals and reference lists. The studies were evaluated and rated by two independent raters (Kappa = 0.835) according to the quality of their methodology based upon nine criteria. Fifty studies met the criteria for inclusion in the second stage of the review, which examined the relationship between a broad range of variables and employment outcome. Results : The factors most consistently associated with employment outcome included pre-injury occupational status, functional status at discharge, global cognitive functioning, perceptual ability, executive functioning, involvement in vocational rehabilitation services and emotional status. Conclusions : A conceptual model is presented which emphasises the importance of metacognitive, emotional and social environment factors for improving employment outcome.

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Tannerella forsythia has been implicated as a defined periodontal pathogen. In the present study a mouse model was used to determine the phenotype of leukocytes in the lesions induced by subcutaneous injections of either live (group A) or nonviable (group B) T. forsythia. Control mice (group C) received the vehicle only. Lesions were excised at days 1, 2, 4, and 7. An avidin-biotin immunoperoxidase method was used to stain infiltrating CD4(+) and CD8(+) T cells, CD14(+) macrophages, CD19(+) B cells, and neutrophils. Hematoxylin and eosin sections demonstrated lesions with central necrotic cores surrounded by neutrophils, macrophages and lymphocytes in both group A and group B mice. Lesions from control mice exhibited no or only occasional solitary leukocytes. In both groups A and B, neutrophils were the dominant leukocyte in the lesion 1 day after injection, the numbers decreasing over the 7-day experimental period. There was a relatively low mean percent of CD4(+) and CD8(+) T cells in the lesions and, whereas the percent of CD8(+) T cells remained constant, there was a significant increase in the percent of CD4(+) T cells at day 7. This increase was more evident in group A mice. The mean percent of CD14(+) macrophages and CD19(+) B cells remained low over the experimental period, although there was a significantly higher mean percent of CD19(+) B cells at day 1. In conclusion, the results showed that immunization of mice with live T. forsythia induced a stronger immune response than nonviable organisms. The inflammatory response presented as a nonspecific immune response with evidence of an adaptive (T-cell) response by day 7. Unlike Porphyromonas gingivalis, there was no inhibition of neutrophil migration.

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The University of Queensland, Australia has developed Fez, a world-leading user-interface and management system for Fedora-based institutional repositories, which bridges the gap between a repository and users. Christiaan Kortekaas, Andrew Bennett and Keith Webster will review this open source software that gives institutions the power to create a comprehensive repository solution without the hassle..

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We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.

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The classical model of surface layering followed by capillary condensation during adsorption in mesopores, is modified here by consideration of the adsorbate solid interaction potential. The new theory accurately predicts the capillary coexistence curve as well as pore criticality, matching that predicted by density functional theory. The model also satisfactorily predicts the isotherm for nitrogen adsorption at 77.4 K on MCM-41 material of various pore sizes, synthesized and characterized in our laboratory, including the multilayer region, using only data on the variation of condensation pressures with pore diameter. The results indicate a minimum mesopore diameter for the surface layering model to hold as 14.1 Å, below which size micropore filling must occur, and a minimum pore diameter for mechanical stability of the hemispherical meniscus during desorption as 34.2 Å. For pores in-between these two sizes reversible condensation is predicted to occur, in accord with the experimental data for nitrogen adsorption on MCM-41 at 77.4 K.

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The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

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View of model for competition entry.