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RISS 인기검색어
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- 저자 : Lv Hai-xia,Yu Guang,Wu Gang (검색결과 4 건)
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Celebrity Endorsement Problem on Social Media : Formulation, Analysis and Recommendation Algorithm
Lv Hai-xia,Yu Guang,Wu Gang 보안공학연구지원센터(IJUNESST) 2015 International Journal of u- and e- Service, Scienc Vol.8 No.1
In this paper, a new matching recommendation algorithm is proposed to help enterprises find one or more proper celebrities from social media for their product endorsement. The fans group of a celebrity, his impaction value in the social media, as well as the matching degree between the celebrity and the product are selected to measure a celebrity. The attribute similarities between target customers of the product and fans of the celebrity are calculated via the Pearson similarity formula. Then, considering the impaction value of the celebrity and the matching degree of the celebrity and the product which can be accessed on the website or usually available from the enterprise, an evaluation index is proposed. We use some data from Sina Micro-blog, which is the most popular social media platform in China, to show the effectiveness of our proposed matching recommendation algorithm. Moreover, the analysis shows that a particular celebrity may suitable to endorse different product on-line and off-line.
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Xiu Lei,Lv Gang,Xu Yan,Qiao Yang,Jiang Hai,Wang Xianwei,Ye Xia 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.7
Ultra-precision polishing is an important processing method for monocrystalline silicon, in order to improve the machining efficiency and obtain good machining quality, it is necessary to investigate the material removal process and process parameters of ultra-precision polishing. Smoothed particle hydrodynamics (SPH) is a meshless method with good self-adaptability, it can be used in the simulation of ultra-precision polishing which has high speed deformation characteristics. The calculation model and SPH analysis model of ultraprecision polishing are established according to the principle of ultra-precision polishing, SPH method is used to simulate and analyze ultra-precision polishing of the monocrystalline silicon. The material removal process of ultra-precision polishing is investigated, the effects of abrasive size and indentation depth on the equivalent plastic strain (PEEQ), Mises stress and the force of abrasive is investigated. The result is that, at the different time of ultra-precision polishing, the maximum PEEQ is different, but the difference is not obvious; the X direction force of the abrasive increases with the indentation depth; the size of abrasive has a great influence on the soft coefficient of stress state in ultra-precision polishing. According to the simulation results, it is possible to optimize the technological parameters of ultra-precision polishing, and provide the theoretical guidance for practical production.
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Wang, Jing-Jing,Wu, Hai-Feng,Sun, Tao,Li, Xia,Wang, Wei,Tao, Li-Xin,Huo, Da,Lv, Ping-Xin,He, Wen,Guo, Xiu-Hua Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.10
Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.
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Yang Tao,Xiao-mei Bie,Feng-xia Lv,Hai-zhen Zhao,Zhao-xin Lu 한국미생물학회 2011 The journal of microbiology Vol.49 No.1
The antifungal activity and mechanism of fengycin in the presence and absence of commercial surfactin against Rhizopus stolonifer were investigated. The MIC (minimal inhibitory concentration) of fengycin without commercial surfactin added was 0.4 mg/ml while the MIC of fengycin with commercial surfactin added was 2.0 mg/ml. Fengycin acted on cell membrane and cellular organs and inhibited DNA synthesis. The antifungal effect of fengycin was reduced after commercial surfactin was added. All these results suggest that the fungal cell membrane may be the primary target of fengycin action and commercial surfactin may reduce the antifungal activity of fengycin.
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