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- 저자 : Xianming Sun (검색결과 3 건)
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A Solution to Privacy Preservation in Publishing Human Trajectories
( Xianming Li ),( Guangzhong Sun ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.8
With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users’ privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users’ behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users’ privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary’s background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users’ privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.
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Xin Chen,Zhiqiang Zhang,Aiqun Li,Hu, Liang,Liu, Xianming,Fan, Zhong,Sun, Peng 한국풍공학회 2021 Wind and Structures, An International Journal (WAS Vol.32 No.2
The 246.8-m-tall Beijing Olympic Tower (BOT) is a new landmark in Beijing City, China. Its unique architectural style with five sub-towers and a large tower crown gives rise to complex dynamic characteristics. Thus, it is wind-sensitive, and a double-stage pendulum tuned mass damper (DPTMD) has been installed for vibration mitigation. In this study, a finite-element analysis of the wind-induced responses of the tower based on full-scale measurement results was performed. First, the structure of the BOT and the full-scale measurement are introduced. According to the measured dynamic characteristics of the BOT, such as the natural frequencies, modal shapes, and damping ratios, an accurate finite-element model (FEM) was established and updated. On the basis of wind measurements, as well as wind-tunnel test results, the wind load on the model was calculated. Then, the wind-induced responses of the BOT with the DPTMD were obtained and compared with the measured responses to assess the numerical wind-induced response analysis method. Finally, the wind-induced serviceability of the BOT was evaluated according to the field measurement results for the wind-induced response and was found to be satisfactory for human comfort.
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Bearing fault diagnosis of wind turbines based on dynamic multi-adversarial adaptive network
Miao Tian,Xiaoming Su,Changzheng Chen,Yuanqing Luo,Xianming Sun 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.4
Owing to the shortage of available labeled data on wind turbine bearings, a new wind turbine bearing fault diagnosis method based on a dynamic multi-adversarial adaptive network (DMAAN) was proposed. In this new method, a laboratory data were used to obtain fault diagnosis models for wind turbine bearings. The first step was evaluating the interdomain distribution difference and intraclass distribution differences between domains. The second step was setting a dynamic adversarial factor to dynamically measure the relative contribution of the two different distributions. The last step was, reducing the distribution difference through multiple adversarial training, to obtain the diagnosis results. The validity of DMAAN was verified via the transfer experiments of laboratory datasets and wind turbine generator measured datasets. The results showed that DMAAN has a higher diagnostic accuracy and better transmission capability in cross-machine transfer fault diagnosis in compare with the existing methods.
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