909 resultados para Data-Driven Behavior Modeling
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National Highway Traffic Safety Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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Mode of access: Internet.
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Decreasing vehicle understeer was strongly associated with the likelihood of control loss following both the unexpected and expected tire failures. Knowledge of the imminent tread separation reduced the overall probability of control loss from 55% to 20% and had a significant effect on how quickly drivers responded as well as on the nature of their initial responses (i.e., steering orbraking). Driver age was marginally associated with increased likelihood of vehicle control loss, but only on unexpected trials. Vehicle speed at the time of first steering input also contributed to the probability of control loss. Neither the location of the tire that failed (left rear vs. right rear) nor the specific instructions about how best to respond to the tread separation influenced the probability of control loss. Differences associated with vehicle understeer conditions observed in the present study were large and consistent, independent of driver expectations and across driver age groups. It is thus fair to conclude that in the event of a complete rear-tire detread, the increased difficulty in vehicle handling and the associated increased likelihood of loss of vehicle control with decreasing vehicle understeer generalize to real-world driving.
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National Highway Traffic Safety Administration, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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Pursuant to Public Act 93-1036, the Illinois State Board of Education has developed a five year comprehensive strategic plan for elementary and secondary education in Illinois. The plan focuses on three primary goal areas: enhancing literacy; improving educator quality for all children; and expanding data-driven management and school support practices.
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Pursuant to Public Act 93-1036, the Illinois State Board of Education has developed a five year comprehensive strategic plan for elementary and secondary education in Illinois. The plan focuses on three primary goal areas: enhancing literacy; improving educator quality for all children; and expanding data-driven management and school support practices.
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Thesis (Master's)--University of Washington, 2016-06
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Thesis (Master's)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Background: The OARSI Standing Committee for Clinical Trials Response Criteria Initiative had developed two sets of responder criteria to present the results of changes after treatment in three symptomatic domains (pain, function, and patient's global assessment) as a single variable for clinical trials (1). For each domain, a response was defined by both a relative and an absolute change, with different cut-offs with regard to the drug, the route of administration and the OA localization. Objective: To propose a simplified set of responder criteria with a similar cut-off, whatever the drug, the route or the OA localization. Methods: Data driven approach: (1) Two databases were considered The 'elaboration' database with which the formal OARSI sets of responder criteria were elaborated and The 'revisit' database. (2) Six different scenarios were evaluated: The two formal OARSI sets of criteria Four proposed scenarios of simplified sets of criteria Data from clinical randomized blinded placebo controlled trials were used to evaluate the performances of the two formal scenarios with two different databases ('elaboration' versus 'revisit') and those of the four proposed simplified scenarios within the 'revisit' database. The placebo effect, active effect, treatment effect, and the required sample arm size to obtain the placebo effect and the active treatment effect observed were the performances evaluated for each of the six scenarios. Experts' opinion approach: Results were discussed among the participants of the OMERACT VI meeting, who voted to select the definite OMERACT-OARSI set of criteria (one of the six evaluated scenarios). Results: Data driven approach: Fourteen trials totaling 1886 CA patients and fifteen studies involving 8164 CA patients were evaluated in the 'elaboration' and the 'revisit' databases respectively. The variability of the performances observed in the 'revisit' database when using the different simplified scenarios was similar to that observed between the two databases ('elaboration' versus 'revisit') when using the formal scenarios. The treatment effect and the required sample arm size were similar for each set of criteria. Experts' opinion approach: According to the experts, these two previous performances were the most important of an optimal set of responder criteria. They chose the set of criteria considering both pain and function as evaluation domain and requiring an absolute change and a relative change from baseline to define a response, with similar cut-offs whatever the drug, the route of administration or the CA localization. Conclusion: This data driven and experts' opinion approach is the basis for proposing an optimal simplified set of responder criteria for CA clinical trials. Other studies, using other sets of CA patients, are required in order to further validate this proposed OMERACT - OARSI set of criteria. (C) 2004 OsteoArthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
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In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg.
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Financial prediction has attracted a lot of interest due to the financial implications that the accurate prediction of financial markets can have. A variety of data driven modellingapproaches have been applied but their performance has produced mixed results. In this study we apply both parametric (neural networks with active neurons) and nonparametric (analog complexing) self-organisingmodelling methods for the daily prediction of the exchangerate market. We also propose acombinedapproach where the parametric and nonparametricself-organising methods are combined sequentially, exploiting the advantages of the individual methods with the aim of improving their performance. The combined method is found to produce promising results and to outperform the individual methods when tested with two exchangerates: the American Dollar and the Deutche Mark against the British Pound.