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A fast numerical method for solving a regularized problem associated with obstacle problems
DaMing Yuan,Xi Li,ChengFeng Lei 대한수학회 2012 대한수학회지 Vol.49 No.5
Kirsi Majava and Xue-Cheng Tai [12] proposed a modified level set method for solving a free boundary problem associated with unilateral obstacle problems. The proximal bundle method and gradient method were applied to solve the nonsmooth minimization problems and the regularized problem, respectively. In this paper, we extend this approach to solve the bilateral obstacle problems and employ Rung-Kutta method to solve the initial value problem derived from the regularized problem. Numerical experiments are presented to verify the efficiency of the methods.
Research on Hadoop Identity Authentication Based on Improved Kerberos Protocol
Daming Hu, Deyun Chen,Yuanxu Zhang,Shujun Pei 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.11
This paper researches the authentication mechanism of Kerberos protocol under HDFS, and points out the problems that identity authentication mechanism of Kerberos protocol faced in HDFS cluster environment: time synchronization, KDC security, dictionary attacks and denial mechanism. Aiming at these security problems, firstly, this paper provides an overview of the authentication process of the current Kerberos protocol under HDFS cluster environment; secondly, it modifies Kerberos protocol by using public key encryption and data signature mechanism; lastly, it provides the authentication process of improved Kerberos protocol in HDFS environment. Comprehensive analysis shows that both safety and time efficiency of the improved Kerberos protocol are improved compared with the existing identity authentication mechanism. It provides a more reliable and efficient identity authentication solution for HDFS cluster.
Li, Daming,Deng, Lianbing,Bhooshan Gupta, Brij,Wang, Haoxiang,Choi, Chang Elsevier science 2019 Information sciences Vol.479 No.-
<P><B>Abstract</B></P> <P>The rise of machine learning increases the current computing capabilities and paves the way to novel disruptive applications. In the current era of big data, the application of image retrieval technology for large-scale data is a popular research area. To ensure the robustness and security of digital image watermarking, we propose a novel algorithm using synergetic neural networks. The algorithm first processes a meaningful gray watermark image, then embeds it as a watermark signal into the block Discrete Cosine Transform (DCT) component. The companion algorithm for detection and extraction of the watermark uses a cooperative neural network, where the suspected watermark signal is used as the input while the output consists in the result of the recognition process. The simulation experiments show that the algorithm can complete certain image processing operations with improved performance, not only simultaneously completing watermark detection and extraction, but also efficiently determining the watermark attribution. Compared with other state-of-the-art models, the proposed model obtains an optimal Peak Signal-to-noise ratio (PSNR).</P>
A FAST NUMERICAL METHOD FOR SOLVING A REGULARIZED PROBLEM ASSOCIATED WITH OBSTACLE PROBLEMS
Yuan, Daming,Li, Xi,Lei, Chengfeng Korean Mathematical Society 2012 대한수학회지 Vol.49 No.5
Kirsi Majava and Xue-Cheng Tai [12] proposed a modified level set method for solving a free boundary problem associated with unilateral obstacle problems. The proximal bundle method and gradient method were applied to solve the nonsmooth minimization problems and the regularized problem, respectively. In this paper, we extend this approach to solve the bilateral obstacle problems and employ Rung-Kutta method to solve the initial value problem derived from the regularized problem. Numerical experiments are presented to verify the efficiency of the methods.