期刊：
Journal of Statistical Mechanics: Theory and Experiment,2008年2008(01):P01009- ISSN：1742-5468
通讯作者：
Xu, Xinping
作者机构：
[Xu, Xinping; Liu, Feng] Hua Zhong Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.;[Xu, Xinping] Chinese Acad Sci, Inst High Energy Phys, Beijing 100049, Peoples R China.
通讯机构：
[Xu, Xinping] H;Hua Zhong Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.
摘要：
The standard model of particle physics predicts a complex structure of decay modes for hadrons, which opens up an avenue for observing the internal forces governing the decay dynamics. In this paper, we present the decay modes of hadrons as a network in which the nodes are particles and directed links are pointing from the mother particles to daughter particles. Using the database of decay modes collected from the Particle Data Group, we try to unveil the topological structure and possible intrinsic nature of hadron decays in the light of recent investigations of complex networks. We study distributions of the numbers of daughter and mother particles, and explore scaling laws that may govern the underlying decay structure of the system. We find that it is a small-world network with symmetrical structure. We also study the influence of constraints arising from conservation laws on the network structure, and our analysis suggests that the constraints of conservations of momentum–energy, charge, lepton number and baryon number play important roles in the topology of the decay network. Finally, we classify the hadrons into communities according to their quark component, and uncover the relationship between the particle roles and connection patterns in the communities.
摘要：
公共服务是现代政府工作的一项重要职能,完善的公共服务建设将推动电子政务更好的发展。知识管理是确保公共服务质量的关键因素之一。通过对电子政务公共服务中的知识管理需求和 Wiki 的知识管理特性的分析,提出了政务级 Wiki 应用的工作流程及基于 Wiki 的政府知识管理平台模型,并对 Wiki 在政府知识管理中的具体应用作初步构想。
期刊：
2008 ISECS INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT, VOL 1, PROCEEDINGS,2008年:317-321
作者机构：
[Wu, Yan-Wen; Ai, Xue-Yi] Huazhong Normal Univ, Dept Informat Technol, Wuhan, Peoples R China.
摘要：
In this paper an improvement of the performance for detecting faces in color images is proposed. This improvement is achieved by integrating the AdaBoost learning algorithm with skin color information. Firstly, the system searches the entire image for face candidates by skin color segmentation and morphological operations, then a powerful feature selection algorithm, AdaBoost is performed to automatically select a small set of features in order to achieve robust detection results, the final face regions are obtained via scanning these face candidates using the cascaded classifier, which is constructed by AdaBoost algorithm.The complete system is tested on a variety of color images and compared with other relevant methods. Experimental results show the proposed system obtains competitive results and improves detection performance substantially.
