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Shen, W., Liu, Y., Wu, Q., Tian, Y., Liu, Y., Peng, H..  2018.  Application of Dynamic Security Technology Architecture for Advanced Directional Attacks in Power System Information Security. 2018 International Conference on Power System Technology (POWERCON). :3042–3047.

In view of the increasingly severe network security situation of power information system, this paper draws on the experience of construction of security technology system at home and abroad, with the continuous monitoring and analysis as the core, covering the closed-loop management of defense, detection, response and prediction security as the starting point, Based on the existing defense-based static security protection architecture, a dynamic security technology architecture based on detection and response is established. Compared with the traditional PDR architecture, the architecture adds security threat prediction, strengthens behavior-based detection, and further explains the concept of dynamic defense, so that it can adapt to changes in the grid IT infrastructure and business application systems. A unified security strategy can be formed to deal with more secretive and professional advanced attacks in the future. The architecture emphasizes that network security is a cyclical confrontation process. Enterprise network security thinking should change from the past “emergency response” to “continuous response”, real-time dynamic analysis of security threats, and automatically adapt to changing networks and threat environments, and Constantly optimize its own security defense mechanism, thus effectively solving the problem of the comprehensive technology transformation and upgrading of the security technology system from the traditional passive defense to the active sensing, from the simple defense to the active confrontation, and from the independent protection to the intelligence-driven. At the same time, the paper also gives the technical evolution route of the architecture, which provides a planning basis and a landing method for the continuous fulfillment of the new requirements of the security of the power information system during the 13th Five-Year Plan period.

Pan, G., He, J., Wu, Q., Fang, R., Cao, J., Liao, D..  2018.  Automatic stabilization of Zigbee network. 2018 International Conference on Artificial Intelligence and Big Data (ICAIBD). :224–227.

We present an intelligent system that focus on how to ensure the stability of ZigBee network automatically. First, we discussed on the character of ZigBee compared with WIFI. Pointed out advantage of ZigBee resides in security, stability, low power consumption and better expandability. Second, figuring out the shortcomings of ZigBee on application is that physical limitation of the frequency band and weak ability on diffraction, especially coming across a wall or a door in the actual environment of home. The third, to put forward a method which can be used to ensure the strength of ZigBee signal. The method is to detect the strength of ZigBee relay in advance. And then, to compare it with the threshold value which had been defined in previous. The threshold value of strength of ZigBee is the minimal and tolerable value which can ensure stable transmission of ZigBee. If the detected value is out of the range of threshold, system will prompt up warning message which can be used to hint user to add ZigBee reply between the original ZigBee node and ZigBee gateway.

Peng, Y., Yue, M., Li, H., Li, Y., Li, C., Xu, H., Wu, Q., Xi, W..  2018.  The Effect of Easy Axis Deviations on the Magnetization Reversal of Co Nanowire. IEEE Transactions on Magnetics. 54:1–5.
Macroscopic hysteresis loops and microscopic magnetic moment distributions have been determined by 3-D model for Co nanowire with various easy axis deviations from applied field. It is found that both the coercivity and the remanence decrease monotonously with the increase of easy axis deviation as well as the maximum magnetic product, indicating the large impact of the easy axis orientation on the magnetic performance. Moreover, the calculated angular distributions and the evolution of magnetic moments have been shown to explain the magnetic reversal process. It is demonstrated that the large demagnetization field in the two ends of the nanowire makes the occurrence of reversal domain nucleation easier, hence the magnetic reversal. In addition, the magnetic reversal was illustrated in terms of the analysis of the energy evolution.
Peng, M., Wu, Q..  2019.  Enhanced Style Transfer in Real-Time with Histogram-Matched Instance Normalization. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :2001—2006.

Since the neural networks are utilized to extract information from an image, Gatys et al. found that they could separate the content and style of images and reconstruct them to another image which called Style Transfer. Moreover, there are many feed-forward neural networks have been suggested to speeding up the original method to make Style Transfer become practical application. However, this takes a price: these feed-forward networks are unchangeable because of their fixed parameters which mean we cannot transfer arbitrary styles but only single one in real-time. Some coordinated approaches have been offered to relieve this dilemma. Such as a style-swap layer and an adaptive normalization layer (AdaIN) and soon. Its worth mentioning that we observed that the AdaIN layer only aligns the means and variance of the content feature maps with those of the style feature maps. Our method is aimed at presenting an operational approach that enables arbitrary style transfer in real-time, reserving more statistical information by histogram matching, providing more reliable texture clarity and more humane user control. We achieve performance more cheerful than existing approaches without adding calculation, complexity. And the speed comparable to the fastest Style Transfer method. Our method provides more flexible user control and trustworthy quality and stability.

Wu, Q., Zhao, W..  2018.  Machine Learning Based Human Activity Detection in a Privacy-Aware Compliance Tracking System. 2018 IEEE International Conference on Electro/Information Technology (EIT). :0673–0676.

In this paper, we report our work on using machine learning techniques to predict back bending activity based on field data acquired in a local nursing home. The data are recorded by a privacy-aware compliance tracking system (PACTS). The objective of PACTS is to detect back-bending activities and issue real-time alerts to the participant when she bends her back excessively, which we hope could help the participant form good habits of using proper body mechanics when performing lifting/pulling tasks. We show that our algorithms can differentiate nursing staffs baseline and high-level bending activities by using human skeleton data without any expert rules.

Cao, L., Kang, Y., Wu, Q., Wu, R., Guo, X., Feng, T..  2020.  Searchable encryption cloud storage with dynamic data update to support efficient policy hiding. China Communications. 17:153–163.
Ciphertext policy attribute based encryption (CP-ABE) can provide high finegrained access control for cloud storage. However, it needs to solve problems such as property privacy protection, ciphertext search and data update in the application process. Therefore, based on CP-ABE scheme, this paper proposes a dynamically updatable searchable encryption cloud storage (DUSECS) scheme. Using the characteristics of homomorphic encryption, the encrypted data is compared to achieve efficient hiding policy. Meanwhile, adopting linked list structure, the DUSECS scheme realizes the dynamic data update and integrity detection, and the search encryption against keyword guessing attacks is achieved by combining homomorphic encryption with aggregation algorithm. The analysis of security and performance shows that the scheme is secure and efficient.