Keynote Speaker I

Prof. Yang Xiao
The University of Alabama, Tuscaloosa, USA

Speech Title: Monitoring Systems and the Internet

Dr. Yang Xiao currently is a Full Professor of Department of Computer Science at the University of Alabama, Tuscaloosa, AL, USA. His current research interests include communications/networks and computer/network security. He has published over 200 SCI-indexed journal papers (including over 50 IEEE/ACM transactions papers) and over 200 EI indexed refereed conference papers and book chapters related to these research areas. His research has been supported by the U.S. NSF, U.S. Army Research, GENI, Fleet Industrial Supply Center-San Diego, FIATECH, and The University of Alabama's Research Grants Committee. Dr. Xiao was a Voting Member of IEEE 802.11 Working Group from 2001 to 2004, involving IEEE 802.11 (WIFI) standardization work. He is a Fellow of IET (previously IEE) (FIET). He served/serves as a Panelist for the U.S. National Science Foundation (NSF), The Global Environment for Network Innovations (GENI), Canada Foundation for Innovation (CFI)'s Telecommunications expert committee, and the American Institute of Biological Sciences (AIBS), as well as a Referee/Reviewer for many national and international funding agencies. He currently serves as Editor-in-Chief for International Journal of Security and Networks (EI-index), International Journal of Sensor Networks (SCI-index), and Journal of Communications (EI-index). He had (s) been an Editorial Board or Associate Editor for 20 international journals, including IEEE Transactions on Systems, Man, and Cybernetics: Systems, during 2014 to 2015, IEEE Transactions on Vehicular Technology, during 2007 to 2009, and IEEE Communications Survey and Tutorials, during 2007 to 2014. He served (s) as a Guest Editor for over 20 times for different international journals, including IEEE Network, IEEE Wireless Communications , and ACM/Springer Mobile Networks and Applications (MONET). Dr. Xiao has delivered over 30 keynote speeches at international conferences around the world and gave more than 60 invited talks at different international institutes..

Abstract: Accountability implies that any entity should be held responsible for its own specific action or behavior so that the entity is part of larger chains of accountability. One of the goals of accountability is that once an event has transpired, the events that took place are traceable so that the causes can be determined afterward. The poor accountability provided by today's computers and networks wastes a great deal of money and effort. This is due to the simple fact that today's computing and network infrastructure was not built with accountability in mind. In this talk we introduce our previous work: accountable monitoring methodology called flow-net. We apply this methodology to many applications ranging from operating system design to computer networks.
 

Keynote Speaker II

Prof. Nobuo Funabiki,
Department of Electrical and Communication Engineering
Okayama University, Japan

Speech Title: Java Programming Learning Assistant System: JPLAS

Nobuo Funabiki received the B.S. and Ph.D. degrees in mathematical engineering and information physics from the University of Tokyo, Japan, in 1984 and 1993, respectively. He received the M.S. degree in electrical engineering from Case Western Reserve University, USA, in 1991. From 1984 to 1994, he was with the System Engineering Division, Sumitomo Metal Industries, Ltd., Japan. In 1994, he joined the Department of Information and Computer Sciences at Osaka University, Japan, as an assistant professor, and became an associate professor in 1995. He stayed at University of California, Santa Barbara, in 2000-2001, as a visiting researcher. In 2001, he moved to the Department of Communication Network Engineering (currently, Electrical and Communication Engineering) at Okayama University as a professor. He is the chairman at IEEE Hiroshima Section from 2015. His research interests include computer networks, optimization algorithms, educational technology, and Web technology.

Abstract: As a useful and practical object-oriented programming language, Java has been used in many practical systems including enterprise servers, smart phones, and embedded systems, due to its high safety and portability. Then, a lot of educational institutes such as universities and professional schools have offered Java programming courses to cultivate Java engineers. To assist Java programming educations, we have proposed and implemented a Web-based Java Programming Learning Assistant System called JPLAS. JPLAS offers four types of problems that have different difficulties to cover studies of students at different learning levels: 1) element fill-in-blank problem, 2) value trace problem, 3) statement fill-in-blank problem, and 4) code writing problem. For 1), we have proposed a graph-theory based algorithm to automatically generate element fill-in-blank problems that have unique correct answers. For 3) and 4), we have adopted the test-driven development (TDD) method so that the answer codes from students can be automatically verified using test codes for their self-studies. In this talk, we introduce the outline of JPLAS and its application results to the Java programming course in our department. Besides, we introduce some new features of JPLAS such as the offline answering function, the coding rule learning function, and the clone code deletion problem.

 

Keynote Speaker III

Prof. Feng Gang,
University of Electronic Science and Technology of China, China

Speech Title: Software Defined Protocol and Network Slicing for 5G

Dr. Gang Feng (M'01, SM'06) received his BEng. and MEng degrees in Electronic Engineering from the University of Electronic Science and Technology of China (UESTC), in 1986 and 1989, respectively, and the Ph.D. degrees in Information Engineering from The Chinese University of Hong Kong in 1998. He joined the School of Electric and Electronic Engineering, Nanyang Technological University in December 2000 as an assistant professor and was promoted as an associate professor in October 2005. At present he is a professor with the National Laboratory of Communications, UESTC. Dr. Feng has extensive research experience and has published widely in computer networking and wireless networking research. Three of his papers have been listed as ESI highly cited papers. His research interests include next generation mobile networks, mobile cloud computing, big data analytics for wireless networking, etc. Dr. Feng is a senor member of IEEE.

Abstract: In this talk, I will first review the notion of plastic architecture and end-to-end network slicing for next generation mobile networks (5G). Then my talk will be focused on Software Defined Protocol (SDP), as the key enabling technology for RAT slicing to facilitate a flexible service-oriented protocol stack deployment for 5G. SDP is designed to provide high-throughput, low-latency and elastic mobile services by making data-plane protocol programmable based on platform virtualization and functionality modularization. Next I will address one of the most important issues in SDP, namely SDP request mapping (SDPM). In SDPM, an SDP request (SDPR) is fulfilled by mapping the corresponding SDP function blocks and virtual links onto underlying SDP servers. We employ the LTE Layer-2 data-plane processing as a benchmark for validating the effectiveness of the SDP technique. Finally, I will elaborate a prototypye of 5G network slicing based on SDP and present experimental and simulation results for demonstrating the effectiveness and advantages of SDP technique in providing elastic low-latency mobile services.

 

Keynote Speaker IV

Assoc. Prof. Maode Ma
Nanyang Technological University, Singapore

Speech Title: Design of A Secured VANET-based Navigation Scheme for Autonomous Vehicles

Dr. Maode Ma received his Ph.D. degree in computer science from Hong Kong University of Science and Technology in 1999. Now, Dr. Ma is an Associate Professor in the School of Electrical and Electronic Engineering at Nanyang Technological University in Singapore. He has extensive research interests including network security and wireless networking. He has led and/or participated in over 20 research projects funded by government, industry, military and universities in various countries. Dr. Ma has more than 300 international academic publications including more than 140 journal papers and over 170 conference papers. He currently serves as the Editor-in-Chief of International Journal of Computer and Communication Engineering and International Journal of Electronic Transport. He also serves as a Senior Editor for IEEE Communications Surveys and Tutorials, and an Associate Editor for other 4 International Journals. Dr. Ma is the Fellow of IET and a senior member of IEEE Communication Society, IEEE Intelligent Transportation Systems Society, and IEEE Education Society. He is the Chair of the IEEE Education Society, Singapore Chapter. He has served as an IEEE Communication Society Distinguished Lecturer from 2013 to 2016. .

Abstract: Recently, the issue of autonomous vehicles (AV) has drawn much research attention. The AVs need effective automatic navigation service to guide them to reach their destinations securely in the situation that there is no human driver. It is possible and feasible to take use of the infrastructure of vehicle ad hoc networks (VANET) to implement this objective. Although there are a lot of security solutions proposed to prevent various malicious attacks in VANETs, the performance issue of the VANETs has been ignored. The security solutions with complex security functions may cost much computation resource and incur a high authentication delay for not only the on-board unit (OBU) on vehicles but also the roadside units (RSUs), especially when the navigation service is involved. In this talk, I will address the security issues of the VANETs with an introduction of a lightweight secure VANET-based navigation scheme (LSVN) that has a lower computation cost and a lower authentication delay. By the LSVN, a vehicle firstly initiates the navigation service with a RSU nearby to request a shared symmetric key for later communication with other RSUs in the VANET. Then, the best route will be selected. The pseudo identity of the vehicle and the shared keying materials are sent to the RSUs on the route of the vehicle to its destination. At last, the vehicle will be led to its destination by these RSUs in series. The LSVN scheme has been formally verified by BAN Logic to provide the guarantee of the integrity of messages and mutual authentication of the communication parties. Performance analysis shows that the LSVN can minimize the use of asymmetric cryptographic operations and reduce the authentication delay comparing with an existing security scheme.

 

Keynote Speaker V

Prof. Dr. Xu Huang,
University of Canberra, Australia

Speech Title: Signal Processing for Bilateral Brain Network in a Somatosensory Region Based on Near-Infrared Spectroscopy (NIRS) by Wavelet Time and Frequency Analysis

Professor (Dr) Xu Huang has received the B.E. and M.E. degrees and first Ph.D. in Electrical Engineering and Optical Engineering prior to 1989 and his second Ph.D. in Experimental Physics in the University of New South Wales, Australia in 1992. He has earned the Graduate Certificate in Higher Education in 2004 at the University of Canberra, Australia.  He has been working on the areas of cybersecurity, network security, the telecommunications, networking engineering, network security, Internet of Things (IoT), Clouding computing, software engineering, wireless communications, optical communications, digital signal processing, bio-signal processing, brain computer interface (BCI), intelligent system, smart networks, and nuclear physics more than 30 years. Currently he was the Head of the Engineering at the Faculty of Information Sciences and Engineering, University of Canberra, Australia. He was the Course Conveners including Engineering (106JA), Doctor of Philosophy (235AA), Masters of Information Sciences (by research) (862AA), Professional Doctor (861AA), Master of Engineering. He has been a senior member of IEEE in Electronics and in Computer Society since 1989 and a Fellow of Institution of Engineering Australian (FIEAust), Chartered Professional Engineering (CPEng), a Member of Australian Institute of Physics; He was a member of the Executive Committee of the Australian and New Zealand Association for Engineering Education, he has been a member of Committee of the Institution of Engineering Australia at Canberra Branch for last 10 years. Dr Xu Huang has been the Chair, Co-Chair, and TCM at various high quality International Conferences, and Editor for various high quality Journals. Professor Huang has edited seven books, nine Book Chapters, 41 Journal Articles, and about two hundred papers in high level of the IEEE and other international conferences (within ERA ranking); Professor has been awarded 17 patents in Australia between 2010 and 2013.

Abstract: Near-infrared spectroscopy (NIRS), as signal detecting and processing, has been used in medical imaging to obtain oxygenation and hemodynamic response in the cerebral cortex. As one of updated techniques, it has been evidenced useful, efficient, and effective in the medical examinations. It applied in cortical activation detection and functional connectivity in brain research. Despite some advances in functional lateralization, most of the studies have focused on the prefrontal cortex but little has been done to study the somatosensory region (S1). For this reason, the aim of our current study is to assess bilateral connectivity in the somatosensory region by using NIRS and noxious stimulation. A few healthy subjects were investigated using near-infrared spectroscopy during an acupuncture stimulation procedure to safely induce pain in subjects. A multiscale analysis based on wavelet transform coherence (WTC) was designed to assess the functional connectivity of corresponding channel pairs within the left and right S1 region. The distributions of the reactions based on WTC in the brain after the stimulations are presented by both time region and frequencies domain. The coherence in time-frequency domain between homologous signals generated by contralateral channel pairs increased during stimulation tasks but not during resting time. This study will contribute to the research field to investigate cerebral hemodynamic response of pain perception using NIRS.

 

Invited Speaker I

Dr. Li Ping, The Education University of Hong Kong, Hong Kong

Speech Title: Efficient Image/video Restyling Using GPU Parallelism

Dr. LI Ping is currently a Lecturer at The Education University of Hong Kong, who obtained his Ph.D. from The Chinese University of Hong Kong. His research interests include image/video stylization, learning analytics, big data visualization and creative media. He has one image/video processing national patent, and has excellent research project reported worldwide by ACM TechNews. Besides, he has won the first prize of the U.S. mathematical contest in modeling, the First Runner-Up Award in the Postgraduate Paper Contest of IEEE (HK) and guided the CUHK students to get the IBM Inter-University Programming Contest Champion and 2nd Runner-Up Awards (Twin Wins). Through research, he maintains good relations of cooperation with many universities, including Wuhan University, Shanghai Jiao Tong University and University of California, Davis. He has published many top-tier graphics and visualization papers refereed, including Medical Image Analysis, IEEE Transactions on Visualization and Computer Graphics (TVCG), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Computers & Graphics, Computer Animation and Virtual Worlds (CAVW), Multimedia Tools and Applications, ACM SIGGRAPH VRCAI

Abstract: Image/video restyling as an expressive way for producing user-customized appearances has received much attention in creative media researches. In interactive design, it would be powerful to re-render the stylized presentation of interested objects virtually using computer-aided design tools for retexturing, especially in the image space with a single image or video as input. The nowaday retexturing methods mostly process texture distortion by inter-pixel distance manipulation in image space, the underlying texture distortion is always destroyed due to limitations like improper distortion caused by human mesh stretching, or unavoidable texture splitting caused by texture synthesis. In this talk, we focused the image/video restyling work on efficient retexturing and stylization. We present the interactive retexturing that preserves similar texture distortion without knowing the underlying geometry and lighting environment. We utilized SIFT corner features to naturally discover the underlying texture distortion. The gradient depth recovery and wrinkle stress optimization are applied to accomplish the distortion process. We facilitate the interactive retexturing via real-time bilateral grids and feature-guided distortion optimization using GPU-CUDA parallelism. Video retexturing is achieved through a keyframe-based texture transferring strategy using accurate TV-L1 optical flow with patch motion tracking techniques in real-time. Further, we work on GPU-based abstract stylization that preserves the fine structure in the original images using gradient optimization. We propose the image structure map to naturally distill the fine structure of the original images. Gradient-based tangent generation and tangent-guided morphology are applied to build the structure map. We facilitate the final stylization via parallel bilateral grids and structure-aware stylizing in real-time on GPU-CUDA. In the experiments, our proposed approaches consistently demonstrate high quality performance of image/video restyling in real-time using GPU parallelism. In the future, we will further extend the interactive retexturing to more complicated general video applications with large motion and occluded scene avoiding textures flicking. We will also work on new approaches to make video retexturing more stable by inspiration from latest video processing techniques.

 

Invited Speaker II

Dr. Enji Sun, Virginia Tech, USA

The Intelligent Detection of Fatigue for Haul Truck Drivers based on the Features of Eyes

Dr. Enji Sun, research associate at Virginia Polytechnic Institute and State University (Virginia Tech, VT). His research centers on the seismic tomography of CO2 injection in the rock mechanics lab of VT. He focus on the TomoDD algorithm improvements and numerical simulation of CO2 plume. Before that, He was a senior engineer at China Academy of Safety Science and Technology (CASST), who was in charge of projects focusing on safety monitoring technologies applied to tailing dams, slope stability in surface mining and advanced water leakage detection and prediction in underground mines. He developed the tailing dams monitoring system that have been installed in 10 mines successfully. When pursuing a Ph.D. degree, he built up the assisted driving system for haul trucks in surface mining. Meanwhile, he was invited to teach in Beijing Union University due to his academic achievements.
Dr. Enji Sun has strong abilities of computer programming (C++, C#, Java), field work experience in mines and laboratory investigation. He has been working on double difference tomography, database design of digital mines, management information system (MIS), haul trucks proximity warning system, hazard prevention and controls, the FEM/DEM simulations (Abaqus, Comsol and Flac3D). He is researching on Android API, OpenCV and Arduino system development and their possible applications.
Dr. Enji Sun is the editor of IJEI and reviewer of safety science, International Journal of Mining, Reclamation and Environment, Earth Science, Journal of Safety Science and Technology etc. He reviewed more than 50 papers in the past one year.

Abstract: The aim of this paper here is to study the eyes’ movements’ regulation of the haul truck driver in surface mining. It developed a real-time, non-intrusive eyes’ features based driver fatigue monitoring technologies. The Sobel operator was adopted to detect on the eye edge area, which attracted the texture features of eyes and detected the status of eyes with Gabor wavelet filter. The driver fatigue degree was judged by PERCLOS algorithm. The research results show that this integrated methods can monitor the driver fatigue for haul truck drivers which results in reducing the transportations accidents in surface mining. The further research will concern on the multiple judge indicators including the body gestures and the facial changes of drivers.