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Titlebook: High Performance Computing and Applications; Third International Jiang Xie,Zhangxin Chen,Yan Chen Conference proceedings 2016 Springer Int

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Xianshun Ping,Junjie Peng,Shan Ouyang,Yunfu Shen,Yi Jinre more infectious while others were not. These variants may serve as candidates for identification of the signature sequences linked to infectivity and viral transgressions. Based on our previous hijacking and transgression hypothesis, we aimed to investigate whether SARS-CoV-2 sequences associated
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Sulan Zhang,Yuexing Han,Yunfu Shen,Yi Jinnts and vaccine strategies.Lays groundwork for how to use om.The COVID-19 pandemic caused by the SARS-CoV-2 virus has affected nearly every country and territory in the world. Although worldwide vaccination efforts have reduced the risk of serious disease outcomes, disparities in distribution have l
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Wenhao Zhu,Wenxin Yao,Song Dai,Zhiguo Lung the processing of these materials for chip fabrication, we have developed and tested three techniques, which can be used at any pressure, and at temperatures between 300 and 500°C..Implementing the “Interferometric Technique”, we have used HeNe laser interferometry to follow the etching of Si, Ga
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Evidences that Software Based on Non-overlapping Discretization Is Most Efficient for Applying High and engineering is to develop software capable of effectively solving in parallel partial differential equations or systems of such equations. For this purpose much work on domain decomposition methods has been done. Recently, I. Herrera introduced a new ‘non-overlapping discretization method’ that
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An Improved Differential Evolution Algorithm for Solving Absolute Value Equations,ute value equation problems so research on solving an absolute value problem has important practical and theoretical significance. An improved adaptive differential evolution algorithm was proposed to solve the absolute value equations in this paper. The algorithm combined global search ability and
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Tea Category Classification Based on Feed-Forward Neural Network and Two-Dimensional Wavelet Entropification of teas. (.) In our work, we present a computer assisted discrimination system on the basis of two steps: (i) two-dimensional wavelet-entropy for feature extraction; (ii) the feedforward Neural Network (FNN) for classification. Specifically, the wavelet entropy features were fed into a FNN
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