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Although the Crowd-Sensing perception system brings great data value to people through the release and analysis of high-dimensional perception data, it causes great hidden danger to the privacy of participants in the meantime. Currently, various privacy protection methods based on differential privacy have been proposed, but most of them cannot simultaneously solve the complex attribute association problem between high-dimensional perception data and the privacy threat problems from untrustworthy servers. To address this problem, we put forward a local privacy protection based on Bayes network for high-dimensional perceptual data in this paper. This mechanism realizes the local data protection of the users at the very beginning, eliminates the possibility of other parties directly accessing the user’s original data, and fundamentally protects the user’s data privacy. During this process, after receiving the data of the user’s local privacy protection, the perception server recognizes the dimensional correlation of the high-dimensional data based on the Bayes network, divides the high-dimensional data attribute set into multiple relatively independent low-dimensional attribute sets, and then sequentially synthesizes the new dataset. It can effectively retain the attribute dimension correlation of the original perception data, and ensure that the synthetic dataset and the original dataset have as similar statistical characteristics as possible. To verify its effectiveness, we conduct a multitude of simulation experiments. Results have shown that the synthetic data of this mechanism under the effective local privacy protection has relatively high data utility.
Chunhua Ju; Qiuyang Gu; Gongxing Wu; Shuangzhu Zhang. Local Differential Privacy Protection of High-Dimensional Perceptual Data by the Refined Bayes Network. Sensors 2020, 20, 2516 .
AMA StyleChunhua Ju, Qiuyang Gu, Gongxing Wu, Shuangzhu Zhang. Local Differential Privacy Protection of High-Dimensional Perceptual Data by the Refined Bayes Network. Sensors. 2020; 20 (9):2516.
Chicago/Turabian StyleChunhua Ju; Qiuyang Gu; Gongxing Wu; Shuangzhu Zhang. 2020. "Local Differential Privacy Protection of High-Dimensional Perceptual Data by the Refined Bayes Network." Sensors 20, no. 9: 2516.
Existing literature tends to treat enterprises as a whole when measuring government intervention. However, in Chinese region-specific institutional development, ultimate control (i.e., local government) tends to control multiple enterprises. This paper considers the enterprises controlled by the same ultimate controller as a portfolio, which is used to measure government intervention by comparing the differences of the enterprises in the portfolio. This paper uses the data of Chinese listed local state-owned enterprises (LSOEs). and we assess whether local state ownership benefits or offsets LSOEs’ cross-border mergers and acquisitions (CBM & A) activities. We propose a new measurement of government intervention to explain the mechanisms through which government influences the cross-border mergers and acquisitions of local SOEs. The experimental results show that government intervention and region-specific marketization institutional development negatively moderate the effect of government internationalization subsidies and government intervention on CBM & A separately. However, government internationalization subsidies, government intervention, and region-specific marketization enhance the CBM & A effect of state ownership separately. This study explores the benefits of government involvement in local SOEs. The value of this paper is to provide a novel perspective, including the intermediary effect of government intervention and the market environment.
Qiuyang Gu; Chunhua Ju; Fuguang Bao. The Cross-Border Mergers and Acquisitions of Local State-Owned Enterprises: The Role of Home Country Government Involvement. Sustainability 2020, 12, 3020 .
AMA StyleQiuyang Gu, Chunhua Ju, Fuguang Bao. The Cross-Border Mergers and Acquisitions of Local State-Owned Enterprises: The Role of Home Country Government Involvement. Sustainability. 2020; 12 (7):3020.
Chicago/Turabian StyleQiuyang Gu; Chunhua Ju; Fuguang Bao. 2020. "The Cross-Border Mergers and Acquisitions of Local State-Owned Enterprises: The Role of Home Country Government Involvement." Sustainability 12, no. 7: 3020.
User influence has always been a major topic in the field of social networking. At present, most of the research focuses on three aspects: topological structure, social-behavioral dimension, and topic dimension and most of them ignore the difference between the audience. These models do not consider the impact of personality differences on user influences. To meet this need, this paper introduces the personality traits factor and proposes a user influence model which integrates personality traits (IPUIM) under a strong connection. The user influence measurement is constructed through the information dimension, structural dimension, and user behavioral dimension. The personality report of the user group is obtained by means of NEO-PI-R (The big five personality inventory, Chinese edition) and machine learning method, and it is integrated into the user influence model. The experiment proves that the model proposed in this paper has good accuracy and applicability in measuring user influence, and can effectively identify the key opinion leaders of different personality trait clusters.
Chunhua Ju; Qiuyang Gu; Yi Fang; Fuguang Bao. Research on User Influence Model Integrating Personality Traits under Strong Connection. Sustainability 2020, 12, 2217 .
AMA StyleChunhua Ju, Qiuyang Gu, Yi Fang, Fuguang Bao. Research on User Influence Model Integrating Personality Traits under Strong Connection. Sustainability. 2020; 12 (6):2217.
Chicago/Turabian StyleChunhua Ju; Qiuyang Gu; Yi Fang; Fuguang Bao. 2020. "Research on User Influence Model Integrating Personality Traits under Strong Connection." Sustainability 12, no. 6: 2217.
Qiuyang Gu; Yechen Huang; Yonglong Wang. Spatial Pattern and the New Growth Points Cultivation of Service Trade of qMaritime Silk Roadq in Zhejiang Province. 2017 3rd International Conference on Humanities and Social Science Research (ICHSSR 2017) 2017, 1 .
AMA StyleQiuyang Gu, Yechen Huang, Yonglong Wang. Spatial Pattern and the New Growth Points Cultivation of Service Trade of qMaritime Silk Roadq in Zhejiang Province. 2017 3rd International Conference on Humanities and Social Science Research (ICHSSR 2017). 2017; ():1.
Chicago/Turabian StyleQiuyang Gu; Yechen Huang; Yonglong Wang. 2017. "Spatial Pattern and the New Growth Points Cultivation of Service Trade of qMaritime Silk Roadq in Zhejiang Province." 2017 3rd International Conference on Humanities and Social Science Research (ICHSSR 2017) , no. : 1.
Qiuyang Gu; Yitao Xu; Zhenghai Li; Liyang Zhu; Haowei Xia. A Study on the Positioning of Warehouse Logistics Industry in Yangtze River Region--Based on the Agglomeration Efficiency of Service Industry. Proceedings of 2016 2nd International Conference on Humanities and Social Science Research (ICHSSR 2016) 2016, 1 .
AMA StyleQiuyang Gu, Yitao Xu, Zhenghai Li, Liyang Zhu, Haowei Xia. A Study on the Positioning of Warehouse Logistics Industry in Yangtze River Region--Based on the Agglomeration Efficiency of Service Industry. Proceedings of 2016 2nd International Conference on Humanities and Social Science Research (ICHSSR 2016). 2016; ():1.
Chicago/Turabian StyleQiuyang Gu; Yitao Xu; Zhenghai Li; Liyang Zhu; Haowei Xia. 2016. "A Study on the Positioning of Warehouse Logistics Industry in Yangtze River Region--Based on the Agglomeration Efficiency of Service Industry." Proceedings of 2016 2nd International Conference on Humanities and Social Science Research (ICHSSR 2016) , no. : 1.