982 resultados para Simon, HeinrichSimon, HeinrichHeinrichSimon


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The Australian National Data Service (ANDS) was established in 2008 and aims to: influence national policy in the area of data management in the Australian research community; inform best practice for the curation of data, and, transform the disparate collections of research data around Australia into a cohesive collection of research resources One high profile ANDS activity is to establish the population of Research Data Australia, a set of web pages describing data collections produced by or relevant to Australian researchers. It is designed to promote visibility of research data collections in search engines, in order to encourage their re-use. As part of activities associated with the Australian National Data Service, an increasing number of Australian Universities are choosing to implement VIVO, not as a platform to profile information about researchers, but as a 'metadata store' platform to profile information about institutional research data sets, both locally and as part of a national data commons. To date, the University of Melbourne, Griffith University, the Queensland University of Technology, and the University of Western Australia have all chosen to implement VIVO, with interest from other Universities growing.

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Aims--Telemonitoring (TM) and structured telephone support (STS) have the potential to deliver specialised management to more patients with chronic heart failure (CHF), but their efficacy is still to be proven. Objectives To review randomised controlled trials (RCTs) of TM or STS on all- cause mortality and all-cause and CHF-related hospitalisations in patients with CHF, as a non-invasive remote model of specialised disease-management intervention.--Methods and Results--Data sources:We searched 15 electronic databases and hand-searched bibliographies of relevant studies, systematic reviews, and meeting abstracts. Two reviewers independently extracted all data. Study eligibility and participants: We included any randomised controlled trials (RCT) comparing TM or STS to usual care of patients with CHF. Studies that included intensified management with additional home or clinic visits were excluded. Synthesis: Primary outcomes (mortality and hospitalisations) were analysed; secondary outcomes (cost, length of stay, quality of life) were tabulated.--Results: Thirty RCTs of STS and TM were identified (25 peer-reviewed publications (n=8,323) and five abstracts (n=1,482)). Of the 25 peer-reviewed studies, 11 evaluated TM (2,710 participants), 16 evaluated STS (5,613 participants) and two tested both interventions. TM reduced all-cause mortality (risk ratio (RR 0•66 [95% CI 0•54-0•81], p<0•0001) and STS showed similar trends (RR 0•88 [95% CI 0•76-1•01], p=0•08). Both TM (RR 0•79 [95% CI 0•67-0•94], p=0•008) and STS (RR 0•77 [95% CI 0•68-0•87], p<0•0001) reduced CHF-related hospitalisations. Both interventions improved quality of life, reduced costs, and were acceptable to patients. Improvements in prescribing, patient-knowledge and self-care, and functional class were observed.--Conclusion: TM and STS both appear effective interventions to improve outcomes in patients with CHF.

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The term ‘driving self-restriction’ is used in the road safety literature to describe the behaviour of some older drivers. It includes the notion that older drivers will avoid driving in specific, usually self-identified situations, such as those in which safety is compromised. We sought to identify the situations that older drivers report avoiding; and, to determine the adequacy of a key measure of such behaviour. A sample of 75 drivers aged 65 years and older completed Baldock et al.’s modification of the Driving Habits Questionnaire avoidance items (Baldock et al., 2006), the Driving Behaviour Questionnaire, and open-ended items that elicited written descriptions of the most and least safe driving situation. Consistent with previous results, we found a relatively low level of driving self-restriction and infrequent episodes of aggressive violations. However, when combined with the situation descriptions, these data suggest that Driving Habits Questionnaire did not cover all of the situations that older drivers might choose avoid. We suggest that a new avoidance scale is needed and we present a new item pool that may be used for this purpose.

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Post license advanced driver training programs in the US and early programs in Europe have often failed to accomplish their stated objectives because, it is suspected, that drivers gain self perceived driving skills that exceed their true skills—leading to increased post training crashes. The consensus from the evaluation of countless advanced driver training programs is that these programs are a detriment to safety, especially for novice, young, male drivers. Some European countries including Sweden, Finland, Austria, Luxembourg, and Norway, have continued to refine these programs, with an entirely new training philosophy emerging around 1990. These ‘post-renewal’ programs have shown considerable promise, despite various data quality and availability concerns. These programs share in common a focus on teaching drivers about self assessment and anticipation of risk, as opposed to teaching drivers how to master driving at the limits of tire adhesion. The programs focus on factors such as self actualization and driving discipline, rather than low level mastery of skills. Drivers are meant to depart these renewed programs with a more realistic assessment of their driving abilities. These renewed programs require considerable specialized and costly infrastructure including dedicated driver training facilities with driving modules engineered specifically for advanced driver training and highly structured curricula. They are conspicuously missing from both the US road safety toolbox and academic literature. Given the considerable road safety concerns associated with US novice male drivers in particular, these programs warrant further attention. This paper reviews the predominant features and empirical evidence surrounding post licensing advanced driver training programs focused on novice drivers. A clear articulation of differences between the renewed and current US advanced driver training programs is provided. While the individual quantitative evaluations range from marginally to significantly effective in reducing novice driver crash risk, they have been criticized for evaluation deficiencies ranging from small sample sizes to confounding variables to lack of exposure metrics. Collectively, however, the programs sited in the paper suggest at least a marginally positive effect that needs to be validated with further studies. If additional well controlled studies can validate these programs, a pilot program in the US should be considered.

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We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

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In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP datasets.

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In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

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The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes and as such remains a focus of considerable safety research. The Georgia Department of Transportation spearheaded a regional fatal crash analysis to identify various safety performances of two-lane rural highways and to offer guidance for identifying suitable countermeasures with which to mitigate fatal crashes. The fatal crash data used in this study were compiled from Alabama, Georgia, Mississippi, and South Carolina. The database, developed for an earlier study, included 557 randomly selected fatal crashes from 1997 or 1998 or both (this varied by state). Each participating state identified the candidate crashes and performed physical or video site visits to construct crash databases with enhance site-specific information. Motivated by the hypothesis that single- and multiple-vehicle crashes arise from fundamentally different circumstances, the research team applied binary logit models to predict the probability that a fatal crash is a single-vehicle run-off-road fatal crash given roadway design characteristics, roadside environment features, and traffic conditions proximal to the crash site. A wide variety of factors appears to influence or be associated with single-vehicle fatal crashes. In a model transferability assessment, the authors determined that lane width, horizontal curvature, and ambient lighting are the only three significant variables that are consistent for single-vehicle run-off-road crashes for all study locations.

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The city of Scottsdale Arizona implemented the first fixed photo Speed Enforcement camera demonstration Program (SEP) on a US freeway in 2006. A comprehensive before-and-after analysis of the impact of the SEP on safety revealed significant reductions in crash frequency and severity, which indicates that the SEP is a promising countermeasure for improving safety. However, there is often a trade off between safety and mobility when safety investments are considered. As a result, identifying safety countermeasures that both improve safety and reduce Travel Time Variability (TTV) is a desirable goal for traffic safety engineers. This paper reports on the analysis of the mobility impacts of the SEP by simulating the traffic network with and without the SEP, calibrated to real world conditions. The simulation results show that the SEP decreased the TTV: the risk of unreliable travel was at least 23% higher in the ‘without SEP’ scenario than in the ‘with SEP’ scenario. In addition, the total Travel Time Savings (TTS) from the SEP was estimated to be at least ‘569 vehicle-hours/year.’ Consequently, the SEP is an efficient countermeasure not only for reducing crashes but also for improving mobility through TTS and reduced TTV.

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Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

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Antipsychotic medications act as either antagonists or partial agonists of the dopamine D2 receptor (DRD2) and antipsychotic drugs vary widely in their binding affinity for the D2 receptor (Kapur and Seeman, 2000). The DRD2 957CNT (rs6277) polymorphism has previously been associated with schizophrenia (Lawford et al., 2005) and the T-allele of the 957CNT polymorphism is associated with reduced mRNA stability and synthesis of the dopamine D2 receptor (Duan et al., 2003). The aim of the study was to determine if the rs6277 polymorphism predicts some of the variability of positive and negative symptoms observed in schizophrenia patients being treated with antipsychotic medication.

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In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

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Intrinsically photosensitive retinal ganglion cells (ipRGC) signal environmental light level to the central circadian clock and contribute to the pupil light reflex. It is unknown if ipRGC activity is subject to extrinsic (central) or intrinsic (retinal) network-mediated circadian modulation during light entrainment and phase shifting. Eleven younger persons (18–30 years) with no ophthalmological, medical or sleep disorders participated. The activity of the inner (ipRGC) and outer retina (cone photoreceptors) was assessed hourly using the pupil light reflex during a 24 h period of constant environmental illumination (10 lux). Exogenous circadian cues of activity, sleep, posture, caffeine, ambient temperature, caloric intake and ambient illumination were controlled. Dim-light melatonin onset (DLMO) was determined from salivary melatonin assay at hourly intervals, and participant melatonin onset values were set to 14 h to adjust clock time to circadian time. Here we demonstrate in humans that the ipRGC controlled post-illumination pupil response has a circadian rhythm independent of external light cues. This circadian variation precedes melatonin onset and the minimum ipRGC driven pupil response occurs post melatonin onset. Outer retinal photoreceptor contributions to the inner retinal ipRGC driven post-illumination pupil response also show circadian variation whereas direct outer retinal cone inputs to the pupil light reflex do not, indicating that intrinsically photosensitive (melanopsin) retinal ganglion cells mediate this circadian variation.

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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

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Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.