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Your search keyword '"Sun, Jia-Guang"' showing total 20 results
Start Over Author "Sun, Jia-Guang" Publication Type Books
20 results on '"Sun, Jia-Guang"'

16. Alternate Pattern Fill

Author

Zhang, Xiao-Xin, primary, Yong, Jun-Hai, additional, Gong, Lie-Hang, additional, Zheng, Guo-Qin, additional, and Sun, Jia-Guang, additional

Published
2004
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19. Surface Fitting to Curves with Energy Control.

Author

Bebis, George, Boyle, Richard, Parvin, Bahram, Koracin, Darko, Remagnino, Paolo, Nefian, Ara, Meenakshisundaram, Gopi, Pascucci, Valerio, Zara, Jiri, Molineros, Jose, Theisel, Holger, Malzbender, Thomas, Wang, Wen-Ke, Zhang, Hui, Yong, Jun-Hai, and Sun, Jia-Guang

Abstract

An algorithm for surface fitting to curves with energy control is proposed in this paper. Given four boundary curves and a set of unorganized curves, we impose the constrained energy on the desired surface, and covert the minimum energy problem into a linear equation system of the control points of the surface. We prove that there is one unique solution of this equation system. The proposed algorithm is independent of the coordinate system, and experience shows that the resultant surface is fair. [ABSTRACT FROM AUTHOR]

Published
2006
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20. An Efficient Anomaly Detection Algorithm for Vector-Based Intrusion Detection Systems.

Author

Lu, Xicheng, Zhao, Wei, Sun, Hong-Wei, Lam, Kwok-Yan, Chung, Siu-Leung, Gu, Ming, and Sun, Jia-Guang

Abstract

This paper proposes a new algorithm that improves the efficiency of the anomaly detection stage of a vector-based intrusion detection scheme. In general, intrusion detection schemes are based on the hypothesis that normal system/user behaviors are consistent and can be characterized by some behavior profiles such that deviations from the profiles are considered abnormal. In complicated computing environments, users may exhibit complicated usage patterns that the user profiles have to be established using sophisticated classification methods such as vector quantization (VQ) technique. However, anomaly detection based on the data set in a high dimension space is inefficient. In this paper we focus on the design of an algorithm that uses principal component analysis (PCA) to improve the anomaly detection efficiency. The main contribution of this research is to demonstrate how the efficiency of the anomaly detection can be raised while the effectiveness of the detection in terms of low false alarm rate and high detection rate can be maintained. Keywords: Intrusion Detection; Multivariate Data Analysis; Vector Quantization; Principal Component Analysis. [ABSTRACT FROM AUTHOR]

Published
2005
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