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频率对热声制冷机影响的研究 被引量:4
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作者 张晓青 F.J.Jerbi +1 位作者 郭方中 M.X.FRANCOIS 《低温与超导》 CAS CSCD 北大核心 2001年第2期66-67,57,共3页
分析和研究了频率对热声制冷机声压、温差和声功的影响 ;使用网络模型计算的结果与实验结果相吻合 ;该研究也是对网络模拟和声功测量方法的验证。
关键词 热声制冷机 声功 网络模拟 声压 温差 频率
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Predicting a Failure of Public Speaking Performance Using Multidimensional Assessment
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作者 Jiewen Hua Edith Filaire +5 位作者 Tom Giraud David Antonio Gomez Jauregui Mariette Soury Jean-Claude Martin Laurence Devillers Christine Le Scanff 《Journal of Sports Science》 2016年第4期197-209,共13页
The present study aimed to examine multidimensional factors that contribute to a poor performance in a public speaking task. An adapted version of the Trier Social Stress Test (TSST) as used to elicit psychosocial s... The present study aimed to examine multidimensional factors that contribute to a poor performance in a public speaking task. An adapted version of the Trier Social Stress Test (TSST) as used to elicit psychosocial stress among 43 university students and multidimensional assessments were involved to investigate acute stress responses by psychological measures (i.e. personality, affect, appraisal, coping), physiological measures (i.e. cortisol; Dehydroepiandrosterone: DHEA; ratio of cortisol/DHEA) and behavioural measures (voice, postural control). Our results showed that psychological factors seemed to be the most sensitive to stress performance. A mediation effect was detected between psychological factors and objective performance. Cortisol to DHEA ratio also showed to be associated with speaking performance. This study added evidence to the literature with regards to a multidimensional way to study human stress response and may help individuals use functional coping to improve their performance and better adapt to stressful situations. 展开更多
关键词 Public speaking performance trait anxiety COPING APPRAISAL the ratio of cortisol/DHEA.
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A Compressed Sensing Approach for Partial Differential Equations with Random Input Data
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作者 L.Mathelin K.A.Gallivan 《Communications in Computational Physics》 SCIE 2012年第9期919-954,共36页
In this paper,a novel approach for quantifying the parametric uncertainty associated with a stochastic problem output is presented.As with Monte-Carlo and stochastic collocation methods,only point-wise evaluations of ... In this paper,a novel approach for quantifying the parametric uncertainty associated with a stochastic problem output is presented.As with Monte-Carlo and stochastic collocation methods,only point-wise evaluations of the stochastic output response surface are required allowing the use of legacy deterministic codes and precluding the need for any dedicated stochastic code to solve the uncertain problem of interest.The new approach differs from these standard methods in that it is based on ideas directly linked to the recently developed compressed sensing theory.The technique allows the retrieval of the modes that contribute most significantly to the approximation of the solution using a minimal amount of information.The generation of this information,via many solver calls,is almost always the bottle-neck of an uncertainty quantification procedure.If the stochastic model output has a reasonably compressible representation in the retained approximation basis,the proposedmethod makes the best use of the available information and retrieves the dominantmodes.Uncertainty quantification of the solution of both a 2-D and 8-D stochastic Shallow Water problem is used to demonstrate the significant performance improvement of the new method,requiring up to several orders of magnitude fewer solver calls than the usual sparse grid-based Polynomial Chaos(Smolyak scheme)to achieve comparable approximation accuracy. 展开更多
关键词 Uncertainty quantification compressed sensing collocation technique stochastic spectral decomposition Smolyak sparse approximation stochastic collocation
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