Keynotes

Volatile Multiple Smart Systems Network

Anne Håkansson

UiT The Arctic University of Norway

Abstract

Cyber-physical systems, CPS, like self-driving vehicles, e.g., cars, drones, and water vessels, are common in society, today. AI is used to enable the CPS to autonomously carry out tasks in society. But fully autonomous CPS can currently not be accepted in heavy traffic and dynamic environments. In this talk Professor Anne Håkansson describes Volatile Multiple Smart Systems Network and how this kind of network can be applied to deploy fully autonomous CPS in society.  

BIO

Anne Håkansson is a professor in computer science with a focus on Artificial Intelligence, UiT The Arctic University of Norway. She is a Docent in computer science at KTH Royal Institute of Technology Sweden.   
 
Professor Håkansson has more than 25 years of experience in the AI field, giving her broad knowledge in several AI areas. Her research interests lie in decision-making and reasoning strategies and visualizing and explanation, in particular, negotiation between systems and agents. She has worked with KBS, meta-agents in MAS, and is currently working with CPS in the transportation sector, Industry 4.0, and Smart Cities and Societies with automated smart products and services.    
 
Anne Håkansson is the chair of the Computational Analytics and Intelligence (CAI) research lab at UiT, Tromsø which includes several different groups as UiT, Norway. She is also the chair of Senseable Stockholm Lab, KTH, Kista. She is the author and co-author of several books, proceedings, and international publications and serves in technical program committees of international top conferences IJCAI and AAAI as well as general track chair for KES international conferences. She is the editor-in-chief of NORA Machine Intelligence Journal, Norway. She is a frequently engaged speaker for Artificial Intelligence and popular science and has been an ambassador for Uppsala municipality, Sweden. 

Complex systems and Epidemic modeling

Jacques Demongeot

Université Grenoble Alpes ( UGA)

Abstract

Epidemic modeling and more, pandemic modeling, involves a mathematical approach using complex systems architectures at two levels: i) for representing the contagion process between susceptible individuals and ii) for simulating the efficiency of mitigating and/or curative measures based on prevention, vaccination and therapy policies. For the first level, we will take as example the COVID-19 outbreak and for the second the obesity spread, both declared worldwide pandemic by the World Health Organization (WHO). 

References

1. J. Gaudart, J. Landier, L. Huiart, E. Legendre, L. Lehot, M.K. Bendiane, L. Chiche, A. Petitjean, E. Mosnier, F. Kirakoya-Samadoulougou, J. Demongeot, R. Piarroux & S. Rebaudet 
Factors associated with spatial heterogeneity of Covid-19 in France: a nationwide ecological study.  
The Lancet Public Health, 6, e222-e231 (2021). 

2. J. Demongeot, K. Oshinubi, M. Rachdi, H. Seligmann, F. Thuderoz & J. Waku 
Estimation of Daily Reproduction Rates in COVID-19 Outbreak. 
Computation, 9, 109 (2021).

3. K. Oshinubi, S. BuHamra, N. Alkandari, J. Waku, M. Rachdi & J. Demongeot 
Age Dependent Epidemic Modelling of COVID-19 Outbreak in Kuwait, France and Cameroon. 
Healthcare, 10, 482 (2022). 

4. Z. Xu, D. Yang, L. Wang & J. Demongeot 
Statistical Analysis Supports UTR (untranslated region) Deletion Theory in SARS-CoV-2. 
Virulence, 13, 1772-1789 (2022). 

5. J. Demongeot & C. Fougere 
mRNA vaccines – Facts and hypotheses on fragmentation and encapsulation. 
Vaccines, 11, 40 (2022). 

6. M. Jelassi, K. Oshinubi, M. Rachdi & J. Demongeot 
Epidemic Dynamics on Social Interaction Networks. 
AIMS Bioengineering, 9, 348-361 (2022). 

 7. J. Demongeot, Q. Griette, Y. Maday & P. Magal 
A Kermack-McKendrick model with age of infection starting from a single or multiple cohorts of infected patients. 
Proc. Royal Society A, 479, 2022.0381 (2023). 

8. B. Kammegne, K. Oshinubi, T. Babasola, O.J. Peter, O.B. Longe, R.B. Ogunrinde, E.O. Titiloye & J. Demongeot 
Mathematical modelling of spatial distribution of COVID-19 outbreak using diffusion equation. 
Pathogens, 12, 88 (2023). 

9. Z. Xu, D. Wei, Q. Zeng, H. Zhang, Y. Sun & J. Demongeot  
More or less deadly? A mathematical model that predicts 1 SARS-CoV-2 evolutionary direction. 
Computers in Biology & Medicine, 153, 106510 (2023). 

10. J. Demongeot & P. Magal 
Data Driven Modeling in Mathematical Biology.   
Frontiers in Applied Maths & Statistics, 9, 1129749 (2023). 

11. Z. Xu, D. Yang & J. Demongeot 
A Deterministic Agent-based Model with Antibody Dynamics Information in COVID-19 Epidemic Simulation. 
Frontiers in Public Health (submitted). 

BIO

Jacques Demongeot, MD and PhD in Mathematics, is Professor Emeritus at Université Grenoble Alpes (UGA), Honorary Member of the Institut Universitaire de France (IUF), Member of the International Academy of Medical and Biological Engineering (IAMBE) and of the I@nternational Organization called the Third Way of Evolution (https://www.thethirdwayofevolution.com/people/view/jacques-demongeot) and foreign member of the Chilean Academy of Sciences. He belongs since 2016 to the AGEIS UGA laboratory, dedicated to gerontechnology and e-health.  In 1980, he founded the team Treatment of Information and Modeling in Biomedicine (TIMB) and in 1987 the CNRS laboratory (Techniques of Imaging, Modeling and Complexity (TIMC), inside the institute Informatics, Mathematics and Applications of Grenoble (IMAG), which he directed until 2011. In 1985, he founded at the Grenoble University Hospital the Medical Informatics Service, enlarged in 2003 to the Public Health Pole, which he directed until 2012. In 1992, he founded the Doctoral School of Engineering for Health, Cognition and Environment (EDISCE), which he directed until 2003. He was responsible from 1997 to 2000 of the Bureau Technologies for Health at the Ministry of Research, then from 2002 to 2007 of the CNRS Complex Systems Program. He has published more than 500 papers (https://scholar.google.com/citations?hl=fr&user=iycL2TIAAAAJ&view_op=list_works&sortby=pubdate), which are  focused on biomathematics, bioinformatics and medical engineering. 

A diachronic epistemology of Complex System

Pierre Collet

University of Strasbourg

Biography

Pierre COLLET, 56, is a distinguished Professor in Computer Science at
Strasbourg University (France). President of the French Association for Articial Evolution
from 2003 to 2008 and head of the BFO research team from 2007 to 2011, Prof. Pierre
Collet was the head of the Department of Computer Science of Strasbourg University
from 2011 to 2015. He then created the new CSTB (Complex Systems and Translational
Bioinformatics) research team of the ICUBE UNISTRA laboratory. In 2014, co-created the
Complex Systems Digital Campus UNESCO UniTwin, a large network of 149 universities
around the world that are developing research and education on Complex Systems. In
2016, he co-created the new UFAZ Franco-Azerbaijani University. Pierre Collet has
published around 200 refereed research papers. He specializes on Complex Systems,
Articial Intelligence, massively parallel articial evolution, emergent e-education and
epistemology. His latest research is using articial evolution to help develop quantum
computers.

Abstract.

The science of Complex Systems is a « new » science born in the middle of the
XXth century, but is it really the case? This keynote will present how the understanding of
science has evolved in the Western World since Parmenides of Elea (6th century BCE) and
Leucippus (5th century BCE) to the beginning of the 20th century with Poincaré and the
advent of the 3rd meta-ethics in the 1970s, and the latest understanding of Loop
Quantum Gravity as an attempt for a Theory of Everything (TOE).

Method Based on Alpha-Level Fuzzy Model to Eciently Process Z-numbers in Business Applications

Babek Guirimov

SOCAR, ASOIU

Biography. Babek G. Guirimov graduated from St.-Petersburgh Technical University in
1996 as Systems Engineer and the same year joined the research team in Azerbaijan State
Industry University. He received his Ph.D. degree in robots and mechatronics from the
Baku State University in 2001. His research interests include soft computing, fuzzy and
extended fuzzy logic, neurocomputing, evolutionary optimization, Articial Intelligence.
He has implemented extensive software packages for many original methods he and his
colleagues developed in above-mentioned research elds. He has published one book
and about 50 articles in the eld of soft computing based intelligent and decision-making
systems in leading academic journals. Dr. Guirimov is a member of regular “International
Conferences on Applications of Fuzzy Systems and Soft Computing” and “International
Conferences on Soft Computing and Computing with Words”

Abstract. The research considers an approach to processing data described as
Z-numbers, which is ecient in business applications. Zadeh’s Extension principle is used
as a general framework for solution. Alpha-level based fuzzy number model is used for
both Value (A) and Reliability (B) parts of Z-number. The evolutionary DEC algorithm
developed by the authors is suggested for optimization tasks. The performance and
accuracy of the Approach is demonstrated on example problems. The software
implemented on the basis of the suggested method has demonstrated excellent
performance, which allows its potential use for complex processing problems involving
Z-numbers.

Method Based on Alpha-Level Fuzzy Model to Eciently Process Z-numbers in Business Applications

Latafat Gardashova

Azerbaijan State Oil and Industry University

Biography. Latafat A. Gardashova graduated from Baku State University from the faculty
of Applied Mathematics. Gardashova received the Ph.D. and Doctorate degrees from the
Institute of Control Problems, Baku, in 1999 and 2014, respectively. Her major elds of
study are decision making, fuzzy logic, soft computing and Big Data. She is a professor
and the Vice –rector of ASOIU for Scientic Aairs. Her current researches are focused
decision theory with uncertainty information, calculus with Z numbers, and application
Fuzzy and Z-number theories in Engineering, Chemistry, Economics, Medicine and
Education. She has over 200 scientic publications including 6 books, 5 editor books and
over 100 research papers. Dr. Gardashova is a member of regular “International
Conferences on Applications of Fuzzy Systems and Soft Computing” and “International
Conferences on Soft Computing and Computing with Words”. She was awarded “Scientist
of 2016” (2017) and Honored Scientist of Azerbaijan (2020). She was supervisor of more
than 5 PhD Students and over 3 Doctorate Dissertations.

Abstract. The research considers an approach to processing data described as
Z-numbers, which is ecient in business applications. Zadeh’s Extension principle is used
as a general framework for solution. Alpha-level based fuzzy number model is used for
both Value (A) and Reliability (B) parts of Z-number. The evolutionary DEC algorithm
developed by the authors is suggested for optimization tasks. The performance and
accuracy of the Approach is demonstrated on example problems. The software
implemented on the basis of the suggested method has demonstrated excellent
performance, which allows its potential use for complex processing problems involving
Z-numbers.

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