l Riad Taha Al-Kasasbeh

l Chuanlei Zhang

	Riad Taha Al-Kasasbeh PhD & Professor Postdoctoral Fellow of Konstanz University (Germany) Mechatronics engineering-School of Engineering, the University of Jordan
	Chuanlei Zhang Prof. & Ph.D Professor, School of Artificial Intelligence, Tianjin University of Science and Technology, China

Bioimpedance Spectroscopy for Disease Assessment Using Intelligent Classifiers and Voigt Model Optimization

Riad Taha Al-Kasasbeh PhD. Professor

Postdoctoral Fellow of Konstanz University (Germany)

Mechatronics engineering-School of Engineering, the University of Jordan

Email: r.al-kasasbeh@ju.edu.jo

Abstract: A novel bioimpedance spectroscopy method is introduced; the proposed method can help in the development of objective and accessible criteria for disease assessment, in addition to evaluating the effectiveness of treatment methods. The proposed method can be utilized to develop criteria for conservative therapy options and surgical interventions in severe cases. The method employs a recurrent Voigt model to represent biomaterial segment impedance. For each biomaterial segment model, a Cole plot is drawn in a given frequency range. The model parameters allow the formation of descriptors for multimodal classifiers of the functional state of living systems and parameters of the model links. To confirm the validity of the classifier, a group of patients diagnosed with pneumonia have been tested. To obtain bioimpedance analysis data, an electrode belt was placed on the chest of each patient, and impedance diagrams corresponding to a certain combination of electrodes were determined. The quality indicators of various classifier models reached 78% and were above 62%.

Bio-Sketch: Riad Taha Al-Kasasbeh earned his MS in Engineering Science and Ph.D. in Controlling Biological and Electronic Equipment from Saint-Petersburg Electrotechnical University ETU “LETI”. He furthered his academic pursuits as a postdoctoral fellow at Konstanz University (Germany). Currently, he holds the position of Professor at the University of Jordan. He is a prolific researcher and has co-authored over 120 papers published in reputable journals and conferences including Springer, IEEE, Taylor & Francis, IASTED, Inderscience, and Elsevier. Professor Al-Kasasbeh has held Visiting Professorships at several esteemed universities, including Philadelphia University, Konstanz University (Germany) (HTWG), Karaganda State Industrial University (Kazakhstan), and "Moscow Power Engineering Institute" (MPEI). He has also served as a Research Fellow of DFG at the HTWG. His research interests encompass a wide array of topics, including Artificial Intelligence, Biomedical Instrumentation, Biophysics, Acupuncture, Fuzzy Logic Decision-Making, Medical and Ecology Information Systems, and Ergonomics. He is a sought-after keynote speaker at international conferences, where he presents his groundbreaking work.

Professor Al-Kasasbeh's contributions to the field include the development of novel clinical methods for predicting and diagnosing heart and stomach diseases. He has also devised features for determining the level of psycho-emotional tension in man-machine system operators using bio-active points based on fuzzy logic rules. Furthermore, he has successfully managed research and development projects that conduct scientific research for both local and international industry and medical departments and organizations.

Three-way Decision in Artificial Intelligence

Chuanlei Zhang Prof. & Ph.D

School of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin, China
Email: 97313114@tust.edu.bn

Abstract: A theory of three-way decision concerns thinking, problem solving, and computing in threes or through triads. The triad of Symbols-Meaning-Value spaces combines three powerful ideas, namely, a trilevel categorization of communications problems in terms of the symbols-meaning-effectiveness of a message, the data-knowledge-wisdom (DKW) hierarchy in information science, and the triad of perception-cognition-action in cognitive science and psychology. In this presentation, Professor Zhang will explain artificial intelligence (AI) from the perspective of cognitive computing based three-way decision (3WD) theory. Professor Zhang also propose a Machine-People-Government triangular model for smart agriculture (MPGSA), emphasizing the roles of machines, human contributors, and government. Additionally, Professor Zhang introduce a conceptual three-level framework based on the Symbol-Meaning-Value (SMV) space (SMV4SA) for smart agriculture. This framework delineates the nine critical roles of machine, people, and government across three layers: agricultural data acquisition, knowledge discovery, and decision-making.

Brief Bio-data: Chuanlei Zhang (M’07) from Yiyuan, China, born on Oct. 09, 1973, received the B.S. from Taiyuan University of Technology and M.S. & Ph.D. degrees from China University of Mining and Technology (Beijing), China, in 1995, 1998, and 2006, respectively, all in electrical engineering. Since Oct. 2013, he has been with the College of Artificial Intelligence at Tianjin University of Science and Technology, China, where he is now a full professor. Since Sept. 2010, he had been with the Department of Electrical and Computer Engineering, Ryerson University, Canada, as Post-doc of Communication and Signal Processing Applications Laboratory (CASPAL). From 2000 to 2010, he was a Software Manager, Senior Software Engineer at Motorola (China). His research interests include Pattern Recognition, Data Mining, Computational Intelligence and applications in Bioinformatics.

Professor Chuanlei Zhang ’s current research interests are theory of three-way decision, pattern recognition and understanding, image recognition, Internet of Things (IoT), deep learning. Chuanlei has published over 80 technical papers in these areas in international conferences, journals and jointly holds three Chinese national patents.