Two PhD students from the University of Macau (UM) Faculty of Science and Technology (FST) received best paper awards at international meetings. Zhou Jin received the Best Paper Award at the 2013 International Conference on Fuzzy Theory and Its Applications (iFuzzy2013), while Wen Guoxing received the Best Student Paper Award (Final List) at the 2013 International Automatic Control Conference.

More than 120 papers from around the world were presented at the iFuzzy2013, which was attended by four editor-in-chiefs of IEEE Transactions and other participants. Only six papers made it to the final list of best papers. The other five recipients of the Best Paper Award are from Chung Cheng University in Taiwan; the Universiti Teknologi MARA in Malaysia; as well as the Osaka Institute of Technology, the University of Electro-Communications, and Hokkai-Gakuen University in Japan.

Zhou’s paper, entitled “Multi-Attribute Decision Making for Data-centric Routing in Wireless Sensor Networks”, is co-authored with FST Dean Prof. Philip Chen and Dr. Chen Long, who is also from FST. The paper was selected for the Best Paper Award for providing a novel data-centric routing algorithm in wireless sensor networks, which not only can make various routing decisions according to the choice of different attributes to meet diverse routing requirements of users, but can also achieve a good balance in energy consumption of sensors and the delay time of data transmission. More importantly, as a fundamental data routing research, the proposed algorithm can also be widely applied in complex networking systems such as the Internet of Things, intelligent transportation systems, and public networks.

Another PhD student Wen Guoxing received the Best Student Paper Award (Final List) at the 2013 International Automatic Control Conference (CACS 2013). Wen’s paper, entitled “Adaptive Consensus Tracking Control for a Class of Nonlinear Multi-agent Systems,” is co-authored with FST Dean Prof. Philip Chen. The conference accepted more than 180 papers from around the world, and only six made it to the final list of best papers.

Wen’s paper proposes a novel consensus control method for a class of nonlinear multi-agent systems based on the universal approximation property of neural networks. According to the Lyapunov stability theorem, it is proven that the nonlinear multi-agent system is stable and the consensus tracking errors can converge to a small neighborhood of zero by applying the proposed control method. The effectiveness of the developed scheme is further verified by a simulation example.

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