Ningbo Liu, received a Ph.D. degree in information and communication engineering from Naval Aviation University and worked as a post-doctoral in the second academy of ChinaAerospace Science and Industry Corporation. He now works in the InformationFusion Institute of the Naval Aviation University. His research interest is intelligent signal processing and radar target detection. 

Title 1 : Adaptive Network Convergence and Security Technology for Future Hybrid Adaptive Networks

Keywords : Heterogeneous, Adaptive Network, Security, Network Convergence

Summary:

With the development of the Internet of things technology and the Internet of things sensing node equipment, the perception node equipment is gradually changing to a variety of types and isomerization. How to manage network globally and allocate network resources as a whole has become a new research hotspot. At the same time, large-scale data transmission in the network also involves data security issues. For example, heterogeneous network convergence can guarantee the interconnection of various private networks and large-scale applications. In hybrid adaptive network, users can access multiple communication networks (commercial communication network, enterprise private network or comprehensive utilization of these two networks) at the same time, which will improve the performance, flexibility and affordability of the existing network. On the other hand, this multi network flexibility provides deterrent capability. It is easy for users to switch between communication networks, which increases the time, workload and cost of attacks. So, it has stronger security.

The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of hybrid adaptive network and understand how securitytechnology can influenceit. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case design.

Chair:

Title 1 : Edge Video Analysis and Compression

Keywords : edge computing, video analysis, video compression, hardware acceleration

Summary:

In recent years, enormous intelligent cameras have been utilized for various applications, including surveillance, autonomous vehicles, quality detection, etc. With more data being created by video content and analytics, machine vision comes up with new requirements and challenges, including data storage, network bandwidth, security, and instantaneity. To address the above-mentioned issues, the compression and storage of surveillance videos have become an increasingly hot research topic to reduce the requirements of data storage and network bandwidth. The video data analysis is also moved from the cloud to the edge to improve real-time performance. However, the computing capability is usually insufficient in edge or end devices. Therefore, light-weighted networks and dedicated hardware accelerators are under intensive development to reduce the computing energy while maintaining the quality of the data analysis and compression. 

This workshop will provide an interchange forum to show the latest research results including system optimization, AI algorithm, computer architecture, and circuit design for edge video analysis and compression. Moreover, it will offer an opportunity for academic and industrial attendees to interact and explore collaborations.

Chair: 

Keywords : Optical Network, Natural Disasters, Survivability, Satellite Neworks

Summary:

Optical network has been deployed in many scenes such as mobile backhaul, access network, metro network, core network, data center network, sensor network, etc. Since optical network covers a wide area and is composed of a large number of easily damaged optical components, it is highly susceptible to natural disasters or man-made destructions. Natural disasters such as earthquake, tsunami, hurricane, are most common and destructive failures due to those broad geographical coverage and very great destructiveness. To design a disaster-resilient optical network, various survivability technologies have been developed. However, most of proposed survivability technologies merely rely on optical network itself that it is difficult to deal with widespread link failures, network islanding, and even network paralysis, caused by severe natural disasters or man-made destructions. In 2008, the 7.8-magnitude Wenchuan earthquake in China leads to around 30,000 km of fiber optic cables cut and 4000 telecom offices becoming ineffective. Rescuers cannot contact the outside world merely using optical networks that brings great difficulty to rescue works. Besides using optical network to achieve uninterrupted traffic transmission, other mediums such as photonic millimeter-wave, satellite, long term evolution (LTE), etc., are also used to recover interrupted traffic in optical network. Satellites which are located at space area over 400 kilometers are disaster-independent with the TON. In other words, even if serious disasters occur on the earth, satellites can run properly. Moreover, it can provide homogeneous spatial light-paths for interrupted light-paths in optical network and avoids complex transformations of communication protocol, signal type, signal rate, etc. The satellite network provides a promising method to improve the survivability of TONs against disasters. Using heterogeneous media to achieve disaster-resilient survivability becomes an important research focus. 

The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of disaster-resilient survivability of large-scale optical networks based on heterogeneous media. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews. Please name the title of the submission email with "paper title_workshp title".

Chair:

Title 1：Recent Advances in Edge Computing, Networking and Storage for Smart Cities

Keywords：Smart Cities, Edge/Fog computing, Edge storage, Internet of Things

Summary：

A smart city is a framework, predominantly composed of the advanced information and communication technologies, which enables citizens to realize high quality of life via smart services. In the concrete, citizens engage with smart city ecosystems in various ways using smartphones, global positioning systems, smart sensors, and connected cars and homes. The abundant smart devices must reliably and availably transmit a diverse set of data obtained by capturing a physical aspect of the environment to deliver the cloud for processing. However, the cloud has bandwidth limitations when trying to deal with such a number of connections. Edge computing is a viable solution to address the limitations of cloud computing for enabling real-time smart cities environments. Edge computing, networking and storage are making the storage and computing closer to edge devices, enabling many citizen-oriented applications in smart cities. There are many important technical challenges, including reliable distributed storage for high-speed mobile devices, low-latency networking in complex and heterogeneous urban environments, information processing and computing with varied quality requirements, algorithms and protocols for better computing and communication service, the support for emerging applications including Internet of Things, intelligent traffic, smart home, and more.

The aim of this workshop is bring together the leading researchers and developers from both academia and industry to discuss and present their latest research and innovations on the theory, algorithms and system technologies that can substantially impact existing edge computing and networking or lead to novel future developments for smart cities. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.

Chair:

Title 1：Emerging Antennas and circuits for 5G Applications

Keywords：5G mobile communication, Antennas, Microwave, Millimeter wave, RF components

Summary：

With the blooming of wireless technologies for communications, fifth-generation (5G) mobile networks have become one of the hottest topics in recent years. For any 5G wireless devices and systems, antennas, filters, amplifiers, mixers, and so forth are crucial components for the RF frontend. However, most conventional designs have difficulty satisfying the stringent requirements of the 5G mobile communications on bandwidth, radiation pattern, size, and cost. For example, antennas and circuits for implantable systems and Internet of Things are desired to be with new frequency band, low profile, compact size, low cost, and easy integration. Thus, the demand for different types of novel and high-performance antennas and circuits is increasing exponentially.

This workshop is intended to propose and discuss the design of microwave and millimeter-wave antennas and circuits regarding the 5G mobile communications. The objective of this workshop is to establish the state of the art for the most relevant problems in RF components and to search for novel efficient concepts and designs in the related areas. It is expected to address and report recent attractive topics in antennas and circuits for the 5G techniques. The desired purpose of the workshop is to make a contribution to 5G mobile communications in both academic and industrial areas. We invite investigators to submit original research articles and reviews to this workshop.

Chair：

Jinxin Li received the B.S. degree in electronic information science and technology in 2008 and Ph.D degree in electromagnetic fieldand microwave technology in 2017 from the University of Electronic Science and Technology of China(UESTC), Chengdu, China. From 2015 to 2016, he was a Visiting Ph.D. Student at the Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA

Workshop 14： Intelligent Systems

Title 1：Vibration signal processing

Keywords: Signal Processing, Equipment fault diagnosis

Summary:

Prof. Fan Jiang, China University of Mining and Technology, China

Fan Jiang is associate professor, master tutor, director of the Rotor Dynamics Professional Committee of China Vibration Engineering Society with Ph.D., was selected as the vice president of science and technology of "Jiangsu Science and Technology Association Young Science and Technology Talents Lifting Project" in 2018 and "Double Innovation Plan" in Jiangsu Province in 2017.The main research interests are: big data processing and analysis, intelligent diagnosis and health assessment, intelligent monitoring and control.

As the project leader, he presided over the National Natural Science Foundation of China Youth Fund Project, Jiangsu Natural Science Foundation Youth Fund Project, the first-class support project for Chinese doctoral students, and the Youth Science and Technology Fund Project of China University of Mining and Technology.

Workshop 15：Image Processing & Internet of Things

Title 1：Heterogeneous Data Fusion and Deep Learning for Smart City

Keywords: Posture Recognition, Edge Computing, Heterogeneous Data Fusion, Indoor Positioning

Summary:

Smart City, established based on Digital City, Internet of things, and Cloud Computing, is the integration of the real world and the digital world. It has a wide prospect for economic transformation and development, smart urban management, and intelligent services for the public. The upsurge of intellectualization has brought about research hotspots of Smart City including intelligent perception and adaptive feature extraction and fusion of multi-source heterogeneous big data, real-time scheduling and optimization of cloud resources for the complex environment, multi-level integration and visualization of big data based on deep learning and open and fault-tolerant cloud platform architecture for flexible scheduling services, which are widely applied in areas of Intelligent Security, Intelligent Education, Intelligent Care, Intelligent Monitoring, etc.
One aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. And the other goal is to present the latest research results of multi-source heterogeneous big data fusion and its deep learning in the field of Smart City. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case review.

Prof. Hou Qing, College of computer science and technology, Guizhou University, China

Hou Qing, received a doctor’s degree from the Key Laboratory of Advanced Manufacturing Technology of the Ministry of Education, Guizhou University in 2017, works as a professor and master's supervisor of Guizhou University, and the general manager of Group Customer Department of China ComService Guizhou Company, as well as a professor-level senior engineer. His research interests include data mining and analysis, image processing and the Internet of Things. He has been engaged in planning consultation, R&D and implementation and software development in communication and information industry for years, and has taken the lead to accomplish more than 100 projects, published 20 papers and obtained over 10 invention patents. He obtained the Title of National Excellent Communication Designer and Labor Model of China Telecom.

Workshop 16：Artificial Intelligence

Title 1：Brain like Computing

Keywords: Natural Computing, Intelligent System, Artificial Intelligence, Intelligence Robot

Summary:

Brain like computing is a highly intersected and integrated life science, especially brain science and information technology. Its technical connotation includes a deep understanding of the principle of brain information processing. On this basis, a new processor, algorithm, and system integration architecture are developed and applied to a wide range of fields such as new generation artificial intelligence, big data processing, and human-computer interaction. A brain-like computer is a new computer model which simulates the operation of a brain neural network and has ultra-large-scale pulse real-time communication.
This workshop aims to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of Brain-like Computing and understand how some strategies can influence it. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews. Please name the title of the submission email with “paper title_workshop number”.

Prof. Hongwei Mo, Harbin Engineering University, China

Hongwei Mo, born in 1973. He is a professor at Automation College of Harbin Engineering University. He got Ph.D. degree from the same university in 2005. He is a visiting Scholar of UCDavis, CA, USA from 10, 2003-10, 2004.

He worked as a lecturer, associate professor, and professor in Automation College, Harbin Engineering University from 1996 till now.
His main research interests includes Natural Computing, Intelligent System, Artificial Intelligence, Intelligence Robot, and UAV. He has published 80 papers on nature inspired computing in international journals and conferences. He is the guest editor of Special issue on Nature inspired computing and applications of Journal of Information Technology Research. He is the author of 5 monographs and he is the editor of "Handbook of Artificial Immune Systems and Nature inspired computing: Applying Complex Adaptive Technologies".
And he is a member of the IEEE Computing Intelligence Society, IEEE Robotics and Automaton Society. He is also the program committee member over 30 international conferences. And he is the organization committees chair of the 2013 International Conference on Swarm Intelligence. He is the program committees chair of 2017 International Conference on Bio-inspired Computing Theories and Applications.
   He serves as the associate editor of the International Journal of Computing Intelligence and Pattern Recognition, member of editorial boards of the Journal of Information Technology Research and International Journal of Swarm Intelligence Research, International Journal of Robotics and Automation Technology.

Jin-Yuan Wang received his Ph.D. degree in Information and Communication Engineering from the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China, in 2015. From January 2016 to June 2019, he was a Lecturer with the Nanjing University of Posts and Telecommunications, Nanjing, China, where he has been an Associate Professor since July 2019. His current research interest is optical wireless communications.

Fumin Zou, received a Ph.D. degree in Traffic Information Engineering and Control from Central South University. He is currently Secretary-General of Fujian Automotive Networking Industry Alliance, Director of Fujian Key Laboratory of Automotive Electronics and Electric Drive Technology, Director of Digital Fujian Transportation Big Data Research Institute. His research interests include Traffic Information and Control Engineering, Big Data Technology and Artificial Intelligence.