1. Title：Embedded Computing and Information Security
Embedded computing systems are designed to a wide range of competing criteria that have given rise to several different fields. On the one hand, they must perform increasingly complex tasks. On the other hand, embedded systems must meet tight cost, power consumption, and performance constraints.
Information security is the practice of preventing unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of information. The information or data may take any form, e.g. electronic or physical. Information security’s primary focus is the balanced protection of the confidentiality, integrity and availability of data while maintaining a focus on efficient policy implementation, all without hampering organization productivity.
Machine Learning is an idea to learn from examples and experience, without being explicitly programmed. Instead of writing code, you feed data to the generic algorithm, and it builds logic based on the data given.
This special Workshop aims to present and highlight the latest developments and emerging research of Embedded Computing, CryptographyAlgorithms, Machine Learning with applications in developing all aspects of image, video, music, texture et.al..
Embedded Computing; Cryptography; Information Security; Machine Learning; Neural Network;
Dr.Hui-Huang Zhao, Hengyang Normal University, China
Dr.Hui-Huang Zhao received his Ph.D. degree in 2010 from XiDian University. He was a Sponsored Researcher in the School of Computer Science and Informatics, Cardiff University. Now he is an Associate Professor in the College of Computer Science and Technology, Hengyang Normal University. His main research interests include Image Processing, Compressive Sensing and Machine Learning.
Prof. Bin Fu, University of Texas Rio Grande Valley, USA.
Prof. Bin Fu received his Ph.D. degree in 1998 from Yale University. He is a Professor in the Department of Computer Science, University of Texas Rio Grande Valley. His main research interests include Algorithms in Networking and Bioinformatics, Computational Complexity Theory.
Energy Internet can be understood as a new power network composed of distributed energy acquisition devices, distributed energy storage devices and various types of loads, which integrates advanced power electronics technology, information technology and intelligent management technology to realize energy exchange and sharing network with bidirectional energy flow.
This special Workshop aims to introduce and highlight the latest developments and emerging research in energy Internet and smart grid technologies, and to apply them to electrical, power, information, control and other aspects.
Distributed Energy；Virtual Synchronizer Technology；DC Transmission Technology；Control Technology；Power Grid Information System
Prof. Xi-Zheng Zhang, Hunan Institute of Engineering, China
Xi-Zheng Zhang(M’09) received the B.S. degree in control engineering, the M.S. degree in circuits and systems, and the Ph.D. degree in control science and engineering from Hunan University, Changsha, China, in 2000, 2003, and 2010, respectively. He is a Professor in Hunan Institute of Engineering, Xiangtan, China. His research interests include hybrid electric vehicle control and industrial automation.
Prof. Yi-Ping Luo, Hunan Institute of Engineering
Yi-ping Luoreceived his Ph.D. degree from South China University of Technology, Guangzhou. He is Professor with the Hunan Institute of Engineering, Hunan, China. And he is also an academic leader of The Cooperative Innovation Center of Wind Power Equipment and Energy Conversion, Hunan, China. His main research interests include neural network, pattern recognition, complex network and Distributed parameter systems.
Prof. Yong-Qi Tang, Hunan Institute of Engineering
Yongqi Tang, born in 1964, professor, master supervisor. He received the B.S. degree in automatic, the M.S. degree in control engineering, from Hunan University, Changsha, China, in 1985 and 2004, respectively. He joined Hunan Institute of Engineering, Xiangtan, China, in April 1997. His research interests include Power conversion and grid-connected control technology, motor drive control technology. He participated in three National Natural Science Foundation of China and more than ten National Natural Science Foundation of Hunan Province of China, he authored and co-authored over 40 refereed papers and applied 6 patents.
3. Title：IoT-Driven Emerging Technologies
Evolving towards the Internet of everything, the Internet-of-things (IoT) is currently more than just networked things but a closed-loop ecosystem, where data is collected by sensing devices integrated into the daily objects and then fed into analyzers to process large volumes of data and gain various insights. Firstly, 5G, edge/fog computing, deterministic networking, etc. enable low-delay performance to expedites the response of real-time IoT applications and remarkably relieves traffic delivered through networks. Secondly, AI-driven networking can potentially lead to efficient, rapid, trustworthy management operations, which has been exemplified by recent initiatives to set-up IoT platforms, such as smart grid, smart cities and so on. Thirdly, the analysis and security of big data become more critical for handle the massive amounts of information that are produced by current Internet of things. However, the practical implementation and potential technologies are still in the very early stage, and the challenging issues are being identified under the joint efforts from academia and industry.
Internet of things; 5G; Security; Big Data; Artificial Intelligence
Lei Feng, Associated Professor, Beijing University of Posts and Telecommunications, China
Lei Feng received his B.Eng. and Ph.D. degrees in Communication and Information Systems from Beijing University of Posts and Telecommunications (BUPT) in 2009 and 2015. He is a associated professor at present in State Key Laboratory of Networking and Switching Technology, BUPT. His research interests are resources management in cellular IoT network and smart grid. He has published more than 30 SCI/EI index papers and 10 national patents, 2 monographs.
Wenjing Li, Professor, Beijing University of Posts and Telecommunications, China
Wenjing Li, received his Ph.D. degrees from Beijing University of Posts and Telecommunications (BUPT). she is now a professor at BUPT and serves as a director in the Key Laboratory of Network Management Research Center. Meanwhile, she is the leader of TC7/WG1 in the China Communications Standards Association (CCSA). Her research interests are wireless network management and automatic healing in SONs.
Cheng Zhang, Assistant Professor, School of Fundamental Science and Engineering, Waseda University, Japan
Cheng Zhang received the Ph.D. degree from the Waseda University in Japan. He is currently an Assistant Professor in School of Fundamental Science and Engineering, Waseda University. His research interests include automatic control, embedded software, human-machine cooperation, network optimization, etc. He has many years of work experience in the industrial and academic area.
Miao Ye, Professor, Guilin University of Electronic Technology, China
Miao Ye received his Ph.D. from in Computer Science and Technology from Xidian University. He is now a professor in Guilin University of Electronic Technology. His research interests include wireless sensor networks, distributed storage system, deep learning, the optimization methods and their application in engineering, He hosted one and participated in three National Natural Science Foundation, hosted three Natural Science Foundation of Guangxi Province of China, and publish over 30 SCI/EI indexed papers as first or corresponding author.
4.Title：Cloud computing and Data mining
Cloud computing and big data are the main research directions in the current Internet. Especially the research of scheduling algorithms under cloud computing tasks and data mining under big data are the focus of current research. (1) How to more effectively perform task resource scheduling It is the focus of research under cloud computing. In particular, the current task scheduling model needs to be improved to some extent. The traditional single bionic algorithm can not meet the needs of current research, hybrid algorithms or new ones. Bionics algorithm has become a new solution for task scheduling under cloud computing. (2) Data mining has always been the focus of research, especially in the context of big data. Traditional neural networks have many training times and training. The long time and the disadvantage of large training error, so the intelligent optimization of traditional neural network can be an effective supplement to the current neural network algorithm.
Internet of things; cloud computing; Big Data; Data mining
ShuFeng Ai，Professor, Communication University of ZheJiang, China.
ShuFeng Ai received his the M.S. degree in computer from YanShan Universtiy , His research interests include cloud computing and Algorithm Design
XiangJun Xin，Professor, ZhengZhou University of Light Industry, China.
XiangJun Xin received his the ph.D degree in computer from Xidian University, His research interests include Cryptography and Information security
To be continued
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