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Date: 2017/6/8             Browse: 251
Speaker:  Yunghsiang S. Han
Time:       June 08, 10:00am-11:00am.
Location: Room 1A-200, SIST Building
Inviter:    Prof. Ning Cai
In this talk, we showed how coding theory based techniques can be used to ensure reliable signal processing. We presented our coding theory based technique (DCFECC) which can be used in various signal processing applications to handle erroneous data from agents. Humans can also be modeled as sensors through social media data and in doing so, we can consider a system consisting of agents who would have some elements of human
computation models and some elements of WSN models. In this way, we can consider a generalized framework which covers various applications. By considering the examples of distributed classication, target localization and crowdsourcing, we presented schemes that use DCFECC technique to handle faults by sensors, falsied data due to malicious sensors (Byzantines), and unreliable data from anonymous crowd workers. Note that many other applications  the framework described in this talk where reliable processing could be ensured by our coding theory based approach.
Yunghsiang S. Han received B.Sc. and M.Sc. degrees in electrical engineering from the National Tsing Hua University, Taiwan, in 1984 and 1986, respectively, and a Ph.D. degree from the School of Computer and Information Science, Syracuse University, NY, in 1993. He was with Hua Fan College of Humanities and Technology, National Chi Nan University, and
National Taipei University, Taiwan. From August 2010 to January 2017, he was with the Department of Electrical Engineering at National Taiwan University of Science and Technology. Now he is with School of Electrical Engineering & Intelligentization at Dongguan University of Technology. Dr. Han's research interests are in error-control coding, wireless networks, and security. Dr. Han has conducting state-of-the-art research in
the area of decoding error-correcting codes for more than sixteen years. He first developed a sequential-type algorithm based on Algorithm A* from artificial intelligence. At the time, this algorithm drew a lot of attention since it was the most efficient maximum-likelihood decoding algorithm for binary linear block codes. Dr. Han has also successfully applied coding theory in the area of wireless sensor networks. He has published several highly cited works on wireless sensor networks such as random key pre-distribution schemes. He also serves as the editors of several international journals.
                                                                                         SIST-Seminar 17020