Xiaomin He

Work place: Faculty of Automation, Guang Dong University of Technology, GuangZhou, China

E-mail: teacher_smc@163.com


Research Interests: Computational Science and Engineering, Process Control System, Data Structures and Algorithms


Xiaomin He, was born in 1961, received the Master’s Degree from South China University of Technology (Guangzhou, China). She is an associate professor of Faculty of Automation, GuangDong University of Technology (Guangzhou, China), teaching Ensemble Language, Configuration Software, and Principles of Computer Organization. She is professional in research of Control Science and Control Engineering. Her current research interests include SCM, e-learning and operation system. She has published several papers in her research fields.

Author Articles
Construction of Cisco Virtual Lab Platform

By Gang Zhang Jiajian Yin Xiaomin He Qinling Zhong

DOI: https://doi.org/10.5815/ijeme.2011.03.07, Pub. Date: 29 Sep. 2011

In experiment of network engineering and network construction, students are required to configure Cisco network equipment. Due to limit of lab environment, amount of equipment is not enough and some experiments require much more expensive and higher level equipment that are not practical to purchase and maintain. It is meaningful to use network equipment simulator on PCs. The proposed platform utilizes Dynamips simulator to simulate routers and switches of Cisco product series. Dynamips supports directly loading Cisco IOS images and provides configuration interface as true equipment’s. It has very good teaching effect in experiment of network engineering. And success of the proposed platform shows it can be used in other network related courses.

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Data Mining based Software Development Communication Pattern Discovery

By Gang Zhang Caixian ye Chunru Wang Xiaomin He

DOI: https://doi.org/10.5815/ijmecs.2010.02.04, Pub. Date: 8 Dec. 2010

Smaller time loss and smoother communication pattern is the urgent pursuit in the software development enterprise. However, communication is difficult to control and manage and demands on technical support, due to the uncertainty and complex structure of data appeared in communication. Data mining is a well established framework aiming at intelligently discovering knowledge and principles hidden in massive amounts of original data. Data mining technology together with shared repositories results in an intelligent way to analyze data of communication in software development environment. We propose a data mining based algorithm to tackle the problem, adopting a co-training styled algorithm to discover pattern in software development environment. Decision tree is trained as based learners and a majority voting procedure is then launched to determine labels of unlabeled data. Based learners are then trained again with newly labeled data and such iteration stops when a consistent state is reached. Our method is naturally semi-supervised which can improve generalization ability by making use of unlabeled data. Experimental results on data set gathered from productive environment indicate that the proposed algorithm is effective and outperforms traditional supervised algorithms.

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