Based on the energy transfer model(ETM) proposed by Bao et al.and the Monte Carlo(MC) model proposed by Hutcherson and Ye, this paper proposes an efficient molecular model(MC-S) for squeeze-film damping(SQFD) in raref...Based on the energy transfer model(ETM) proposed by Bao et al.and the Monte Carlo(MC) model proposed by Hutcherson and Ye, this paper proposes an efficient molecular model(MC-S) for squeeze-film damping(SQFD) in rarefied air by releasing the assumption of constant molecular velocity in the gap.Compared with the experiment data, the MC-S model is more efficient than the MC model and more accurate than ETM.Besides, by using the MC-S model, the feasibility of the empirical model proposed by Sumali for SQFD of different plate sizes is discussed.It is proved that, for various plate sizes, the accuracy of the empirical model is relatively high.At last, the SQFD of various vibration frequencies is discussed, and it shows that, for low vibration frequency, the MC-S model is reduced to ETM.展开更多
A variety of existing image quality assessment (IQA) metrics share a similar two-stage framework: at the first stage, a quality map is constructed by comparison between local regions of reference and distorted imag...A variety of existing image quality assessment (IQA) metrics share a similar two-stage framework: at the first stage, a quality map is constructed by comparison between local regions of reference and distorted images; at the second stage, the spatial pooling is adopted to obtain overall quality score. In this work, we propose a novel spatial pooling strategy for image quality assessment through statistical analysis of the quality map. Our in-depth analysis indicates that the overall image quality is sensitive to the quality distribution. Based on the analysis, the quality histogram and statistical descriptors extracted from the quality map are used as input to the support vector regression to obtain the final objective quality score. Experimental results on three large public IQA databases have demonstrated that the proposed spatial pooling strategy can greatly improve the quality prediction performance of the original IQA metrics in terms of correlation with human subjective ratings.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.51375091)
文摘Based on the energy transfer model(ETM) proposed by Bao et al.and the Monte Carlo(MC) model proposed by Hutcherson and Ye, this paper proposes an efficient molecular model(MC-S) for squeeze-film damping(SQFD) in rarefied air by releasing the assumption of constant molecular velocity in the gap.Compared with the experiment data, the MC-S model is more efficient than the MC model and more accurate than ETM.Besides, by using the MC-S model, the feasibility of the empirical model proposed by Sumali for SQFD of different plate sizes is discussed.It is proved that, for various plate sizes, the accuracy of the empirical model is relatively high.At last, the SQFD of various vibration frequencies is discussed, and it shows that, for low vibration frequency, the MC-S model is reduced to ETM.
基金This work was supported by the National Natural Science Foundation of China under Grant No. 61571212 and the Natural Science Foundation of Jiangxi Province of China under Grant No. 20151BDH80003.
文摘A variety of existing image quality assessment (IQA) metrics share a similar two-stage framework: at the first stage, a quality map is constructed by comparison between local regions of reference and distorted images; at the second stage, the spatial pooling is adopted to obtain overall quality score. In this work, we propose a novel spatial pooling strategy for image quality assessment through statistical analysis of the quality map. Our in-depth analysis indicates that the overall image quality is sensitive to the quality distribution. Based on the analysis, the quality histogram and statistical descriptors extracted from the quality map are used as input to the support vector regression to obtain the final objective quality score. Experimental results on three large public IQA databases have demonstrated that the proposed spatial pooling strategy can greatly improve the quality prediction performance of the original IQA metrics in terms of correlation with human subjective ratings.