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( Ning Sun Hang ),( Guo Jixin Liu ),( Guang Han ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.9
Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker l2-norm sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.
Multidisciplinary design optimization of external engagement cylindrical gear flowmeter
Lintao Wang,Fengzhang Zhu,Ning Hao,Hang Yin,Wei Sun 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.6
Many factors affect the performance of an engagement cylindrical gear flowmeter (EGF). Each factor can simultaneously affect multiple performance indicators (e.g., flow pulsation, internal leakage and the total power loss) in different ways, and each indicator affects each other, which increases the difficulty of optimization design and precision compensation. In this paper, an optimization design method is proposed. First, the accurate displacement calculation formula was obtained by integrating the tooth profile equation. Second, the important factors that affect each performance index and the influence trend between each performance index were obtained by the design of experiments (DOE) and sensitivity analysis (SA). Third, based on the SA results, the optimization equations were established and the optimal structural parameters were obtained by using MIGA and NLPQL combined optimization algorithm. The results show that this optimization strategy can be applied to the optimization design of EGF.