Keynote Speakers

Improving Biometric Iris Recognition System Technology with Optimum Feature Extraction

Prof. A Taha
Auckland, New Zealand
Chengdu University, China

Abstract:
Iris-based biometric recognition systems have become an area of great research interest and been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. Consequently, researchers are focused on finding suitable features can extract from iris images that can be used as indexes the stored templates in a manner that enables access to and retrieval of those data by efficient search processes. We propose a method that extracts the most relevant features of iris images to facilitate minimization of the indexing time and the search area of the biometric database, the expected results will be showing a significant performance improvement in terms of bin miss rate and penetration rate compared with conventional methods.

Short Bio:
Dr A Taha is an Honorary Professor and External Advisor from New Zealand and High-end Foreign Expert at Widad University College & CDU. His research interests include improving biometric system technology with optimum feature extraction and various topics related to IT and medical research. His research results have been published in more than 50 papers in international journals and conferences, including various SCI/SCIE/IEEE indexing. He received various awards such as Chosen for Who’s Who in Medicine and Healthcare 2010. He is currently an editor board member for several international journals.

Trends in Machine Intelligence and the Role of Nonlinear Science

Prof. Dr. Wenfeng Wang
The Editor- in -Chief
International Journal of Applied Nonlinear Science
Shanghai Institute of Technology, China

 

Abstract:
This speech aims to introduce the trends in machine intelligence, which is characterized as three intelligence levels - the system-level intelligence, the behavior-level intelligence and the thinking- level intelligence as an industry innovation. These intelligence layers can be further recognized as a nonlinear framework of machine intelligence. The role of nonlinear science in this framework is also introduced along with my journal - International Journal of Applied Nonlinear Science (https://www.inderscience.com/jhome.php?jcode=ijans) and my Springer books, including Brain-Inspired Intelligence and Visual Perception - The Brain and Machine Eyes (https://link.springer.com/book/10.1007/978-981-13-3549-5), Interdisciplinary Evolution of the Machine Brain-Vision, Touch & Mind (https://link.springer.com/book/10.1007/978-981-33-4244-6), Five Layer Intelligence of the Machine Brain - System Modelling and Simulation (https://link.springer.com/book/10.1007/978-981-19-0272-7).

Biography:
Prof. Wen-Feng Wang is an evaluation expert for National Natural Science Foundation of China, National Excellent Youth Fund (overseas projects), National Publishing Fund and Shanghai Government Procurement, and Shanghai Enterprise Technological Innovation Project. He is the Editor in Chief of International Journal of Applied Nonlinear Science, one editorial board member of Nature-scientific reports, the general chair of the 3DWCAI, the chief scientist of Shanghai Lingang Artificial Intelligence Lab, the chief scientist in the field of big data and intelligent computing of RealMax, and in 2021, he was selected as "100 people in the intelligent era" of China. He is now a professor of Shanghai Institute of Technology, a tenured professor of IMT Institute in India and the director of Sino-Indian Joint Research Center of Artificial Intelligence and Robotics. He has been invited as a reviewer for tens of SCI journals, including some top ones - Nature Computational Science, Expert System with Applications, Water Research, Science of the Total Environment, Environmental Pollution, IEEE Transactions on Automation Science and Engineering. He has been invited as keynote speakers of many influential Springer-Nature conferences and has been invited to give special reports to many famous institutes in China and U.S. He motivated the foundation of the International Academy of Visual Arts and Engineering in London in 2021 to promote the novel applications of artificial intelligence in visual arts and visual engineering. As a well-known scholar in artificial intelligence, he has participated in THE's Global Academic Reputation Survey at the invitation of THE to determine the World University Reputation Ranking in 2022 and the World University Ranking in 2023.

Corporate Knowledge Management Research: An Integrated Perspective

Lin Wang PhD, Associate Dean, Distinguished Professor
Chinese Academy of Science and Education Research, Hangzhou Dianzi University, China

Abstract:
Knowledge management is the explicit and systematic management of vital knowledge - and its associated processes of creation, organization, diffusion, use, and exploitation. It is a process to help organizations identify, select, organize, disseminate, transfer knowledge. In this speech, I illustrate that how an understanding of knowledge and the knowing process differ from information and information management. Based on the taxonomy of explicit and tacit knowledge, I put forward a corporate knowledge management model. I also discuss the management strategies dealing with different kinds of knowledge. Nonaka's SECI model of knowledge creation and knowledge spiral process of knowledge theory are analyzed in detail. The innovation cycle and knowledge management cycle are compared. Three knowledge management models and traditions, documentalist, technologist, and learner & communicator models are introduced in the speech. I also discuss the success factors of corporate knowledge management. The difference in knowledge management in eastern and western countries is elaborated. Some main issues of knowledge management systems are briefly reviewed.

Biography:
Lin Wang is a distinguished professor of information science at Hangzhou Dianzi University. He was a visiting professor in University of California Berkeley, Nanyang Technological University. Lin is a guest research fellow in the National Information Resource Management Institute at Beijing. He was awarded Young Information Scientist by China Society for Scientific and Technical Information. He is a trustee of Tianjin Society for Chinese Information Research and Tianjin Association of Public Administration. He is also a member of editorial board of American Journal of Information Management. He has been elected as an expert of Xinhua News Agency Outlook Think Tank. He is a reviewer of program committee for many international conferences, such as iConference and ASIS&T. Recently Lin became the Session Chair (Long Paper) ACM/IEEE Joint Conference of Digital Libraries 2020. He got his PhD degree of information science from Peking University. His research interest includes foundation of information science and information philosophy. He has hosted more than 20 academic projects. He has published more than eighty academic papers in the international LIS journals like Journal of Documentation and Information Research, and leading peer-reviewed information science journals in China. His several papers were awarded as the best paper in the national academic organizations such as Chinese National S&T Information Society, Chinese S&T Communication Society.