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Privacy-Preserving One-Class Support Vector Machine with Vertically Partitioned Data
Qiang Lin,Huimin Pei,Kuaini Wang,Ping Zhong 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.5
We establish a new model of privacy-preserving one-class support vector machine (SVM) based on vertically partitioned data. Every participant holds all the data with a part of attributes. They apply different random matrices to establish their own kernel matrix. By sharing these partial kernel matrices, we construct a global kernel matrix and establish linear and nonlinear privacy-preserving models. Experimental results on benchmark data sets verify the validity of the proposed models.
Privacy-Preserving One-Class Support Vector Machine with Horizontally Partitioned Data
Qiang Lin,Huimin Pei,Kuaini Wang,Ping Zhong 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.9
We propose a new algorithm of privacy-preserving one-class support vector machine (SVM) with horizontally partitioned data. Every participant holds a part of data with all the data attributes. They apply the same random matrix to establish their own kernel matrix. By sharing these partial kernel matrices, we generate a global kernel matrix and establish two privacy-preserving one-class SVM models, which include the linear model and the nonlinear model. Partial kernel matrix can protect the privacy of the participants, and the global kernel matrix can ensure the classification accuracy. Experimental results on benchmark data sets indicate the effectiveness of the proposed algorithms.
Xiaoqi Yu,Xiaoyi Liu,Yuanli Li,Huimin He,Xinxin Pei,Tengfei Ma,Yuanyuan Chen,Yi Wang,Hongxia Li,Wenchu Lin,Changzhi Xu,Buchang Zhang 한국식품과학회 2024 Food Science and Biotechnology Vol.33 No.8
Heptadecanoic acid (C17:0), an odd-chain saturated fatty acid (OCSFA) in ruminant lipid, has been demonstrated to be potential for treating cancers. Our results also showed that sheep tail fat (STF) with higher level of C17:0-containing saturated fatty acids (SFAs) whereas lower level of oleic acid (C18:1), performed remarkable inhibition against non-small-cell lung cancer (NSCLC) cells. To enrich the content of C17:0, a C17:0-rich SFA concentrate (HRSC) was prepared from STF by solvent crystallization and urea complexation methods (hexane/STF = 3.5/1, 4 °C for 8 h, and 80% ethanol/urea/free fatty acids = 8/1/1, 4 °C for 6 h). The content of C17:0 was up from 3.02 to 6.34% and the recovery was 4.17%. Biological experiments showed that HRSC exerted better antiproliferative effect against NSCLC cells. Moreover, HRSC performed enhanced inhibitory effect in A549 cell xenograft mouse model. Therefore, HRSC has the potential to be applied in adjuvant therapy for NSCLC.