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In this study, methods for data acquisition, analysis, modelling, and simulation of performance parameters in road cycling on real tracks were developed and evaluated. A simulator was designed to facilitate the measurement in a laboratory environment. The simulation included real height profiles and a video playback that was synchronised with the cyclist’s current virtual position on the track, and online visualisation of course and performance parameters. Field data obtained on mountain tracks in this study were compared with the state-of-the-art mathematical model for road cycling power, established by Martin et al. (J Appl Biomech 14: 276–291, 1998), which accounts for the gradient force, air resistance, rolling resistance, frictional losses in wheel bearings and inertia. The model described the performance parameters accurately with correlation coefficients of 0.96–0.99 and signal-to-noise ratios of 19.7–23.9 dB. It was shown that the mathematical model could be implemented on an ergometer for simulating rides on real courses, providing similar quality measures when comparing field and simulator measurements.  相似文献   
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A procedure for smoothing the proportions of a double-entry expectancy table is described. The product of the procedure is a nomograph from which can be read expectancies from combinations of values of two predictor variables. The nomograph might be used in admissions advising or in establishing standards for the admission of freshman students. The procedure is used to construct nomographs for predicting proportions of freshman-year grade point averages greater than or equal to 2.0 and for proportions greater than or equal to 3.0 from high school class percentile ranks and ACT composite scores for a sample of first-time freshmen. Effects of sample size and of the minimum size of groups of students used in estimating nomograph curves on the stability of the curves are examined. Suggestions for additional work on deriving expectancy nomographs are given.Presented at the Thirty-First Annual Forum of the Association for Institutional Research, San Francisco, May 26–29, 1991.  相似文献   
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This research evaluated the usefulness of 3 approaches for predicting college grades: (a) traditional regression models, (b) high-school-effects models, and (c) hierarchical linear models. Results of an analysis of the records of 8,764 freshmen at a major research university revealed that both the high-school-effects model and the hierarchical linear model were more accurate predictors of freshman GPA than was the traditional model, particularly for lower ability students. Counter to expectations, the hierarchical linear model was not more accurate than the high school effects model.  相似文献   
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