July 2022 - SIPTA News - lists.sipta.org

ECONVN'23: deadline extended to August 31, 2022
by Kreinovich, Vladik Aug. 1, 2022

Aug. 1, 2022

FYI, economics-related applications of imprecise probabilities are always welcome at this series of conferences *********************************************************** CALL FOR PAPERS The Sixth International Econometric Conference of Vietnam - ECONVN2023 Ho Chi Minh City, Vietnam, January 9-11, 2023 https://hcm-hn.conference-econ-buh-bav-rist.vn/ Main theme: OPTIMAL TRANSPORT STATISTICS FOR ECONOMICS AND RELATED TOPICS The first Conference ECONVN2018 focused on the main theme "Econometrics for Financial Applications"; selected papers were published in the Springer Series in Computational Intelligence, # 760, 2018. The main theme of the second Conference ECONVN2019 was "Beyond Traditional Probabilistic Methods in Economics"; selected papers were published in the Springer series in Computational Intelligence, # 908, 2019. The main theme of the third Conference ECONVN2020 was "Data Science for Financial Econometrics"; selected papers were published in the Springer series in Computational Intelligence, # 898, 2020. The main theme of the fourth conference ECONVN2021 was "Prediction and Causality in Econometrics and Related Topics"; selected papers were published in the Springer series in Computational Intelligence, # 983, 2021 The main theme of the fifth conference ECONVN2022 was "Financial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics"; selected papers will also appear in the new Springer series "Studies in Systems, Decision, and Control", 2022. The main theme of the sixth conference ECONVN2023 is "Optimal Transport Statistics for Economics and Related Topics". Selected papers will be published in the Springer series "Studies in Systems, Decision, and Control" (Scopus, DBLP, WTI Frankfurt eG, zbMATH, SCImago) and will be submitted for consideration in Web of Science (ISI). Venue: Banking University of Ho Chi Minh City, 36 Ton That Dam Street, District 1, Ho Chi Minh City, Vietnam. Conference Date: January 9-11, 2023 Conference Website: hcm-hn.conference-econ-buh-bav-rist.vn Point of Contact: vietnam.buh.econvn(a)gmail.com<mailto:vietnam.buh.econvn@gmail.com> Tel: (84) 28.382.102.38 The Conference welcomes research contributions to all aspects of financial econometrics, with special emphasis on, but not limited to different techniques: * Optimal Transport Statistics * Bayesian Analysis; * Predictive Modeling; * Causal Inference; * Machine Learning; * Artificial Intelligence * Intelligent Data Analysis; * Big Data Techniques; and their applications to: * Economics and international economics; * Money market and capital market; * Public and corporate finance. Publications: Accepted papers must be presented at the Conference which will be published (few months after the conference dates) in the Springer Volume, Series: STUDIES IN SYSTEMS, DECISION AND CONTROL (Economics, Social and Life Science Classifications) Indexed by SCOPUS, SCImago (submitted for Web of Science) Important Dates: * Paper submission deadline: August 31, 2022. * Notification of acceptance: October 1, 2022. * Camera-Ready Manuscript: October 31, 2022. Instructions for Submissions: * Get your account on EasyChair (then click on Conferences, on ECONVN2023) and submit your PDF files to EasyChair. Link: https://easychair.org/conferences/?conf=econvn2023 * Make sure your PDF files have Authors' EMAILS on them for correspondence. Registration Fee 1. Presenters * Presenter + publication USD 200 (non-residents)/VND 9,600,000 (residents) * Student + publication USD 100 (non-residents)/VND 4,800,000 (residents) 2. Participants: * General USD 100 (non-residents)/VND 2,300,000 (residents) * Student USD 30 (non-residents)/VND 1,000,000 (residents) Authors from Banking University of Ho Chi Minh City and Co-organizers are discounted by 50%. Plenary Invited Speakers (Tentative) * Bernadette Bouchon-Meunier (France) * Vladik Kreinovich (USA) * Hung T. Nguyen (USA & Thailand) * Tonghui Wang (USA) * John Harding (USA) * William Briggs (USA) * Mark Schaffer (UK) * Polina Khrennikova (UK) * Woraphon Yamaka (Thailand) * Daniel S. Hain (Denmark) * Katsuhiro Sugita (Japan) * Vyacheslav Yukalov (Russia) General Chair Doan Thanh Ha (Chair) Nguyen Duc Trung (Co-chair) Nguyen Tran Phuc Ha Thi Thieu Dao Organizing Committee CHAIR: NGUYEN NGOC THACH Secretary: Pham Thi Thuy Diem Scientific Committee CHAIR: HUNG T. NGUYEN (USA & THAILAND) Members: Vladik Kreinovich (USA) Nguyen Duc Trung (Vietnam) Nguyen Thi Canh (Vietnam) Nguyen Trong Hoai (Vietnam) Tonghui Wang (USA) William Briggs (USA) Mark Schaffer (UK) Janusz Kacprzyk (Poland) Emmanuel Haven (Canada) Polina Khrennikova (UK) Woraphon Yamaka (Thailand) Nguyen Ngoc Thach (Vietnam) Duan Jin-Chuan (Singapore) Poom Kumam (Thailand) Bernadette Bouchon-Meunier (France) John Harding (USA) Cathy Chen (Taiwan) Boris Choy (Australia) Ying Chen (Singapore) Akira Namatame (Japan) Marc Paolella (Switzerland) Michael Wolf (Switzerland) Sa-At Nipong (Thailand) Radim Jirousek (Czech Republic) Vilem Novak (Czech Republic) Irina Perfilieva (Czech Republic) Galit Shmueli (Taiwan) Michio Sugeno (Japan) David Trafimov (USA) Boualem Dejhiche (Sweden) Vyacheslav Yukalov (Russia) Niels Haldrup (Denmark) Daniel Schmidt (Australia) Michael Eichter (Netherlands) Daniel Hain (Denmark) Rakesh Gupta (Australia) Paulo Fraga Martins Maio (Finland) Asian Journal of Economics and Banking (AJEB)

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First post in a series of interviews on the SIPTA blog
by Alexander Erreygers July 8, 2022

July 8, 2022

Dear IP aficionados Do you know who in the SIPTA community would describe themselves as "jack of all trades, gamer and conversationalist" and has, to their own surprise, encountered the sequence of Pell numbers <http://oeis.org/A000129> in their research? Find out in SIPTA's latest blog post <https://sipta.org/blog/interview-sebastien/>, which is the first instalment in a new blog series of interviews with members of the SIPTA community on their career so far, their thoughts on imprecise probabilities, and more. The series is curated by our blog editors Henna Bains and Diego Estrada. Interested in writing a post for the SIPTA blog? Get in touch with Henna and Diego at blog(a)sipta.org. Every good wish Alexander Erreygers SIPTA's Executive Editor

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PhD student opportunity - Prognostics and Health Management solutions for Reliable Autonomous Systems
by Joxe Inaxio Aizpurua July 6, 2022

July 6, 2022

*Prognostics and Health Management solutions for* *Reliable Autonomous Systems* *Description* The revolution in robotics and autonomous systems (RAS) is unstoppable. The advance of autonomous system applications, such as autonomous transport [1, 2] and autonomous inspections [3], generate multiple benefits for the industry and society, including the improved driving security in autonomous transport, and improved reliability of critical and remote infrastructure through specialized robots and drones. However, the reliability assurance of RAS is a complex challenge, as it requires incorporating advanced intelligence that should evolve according to run-time operation [4]. The challenging yet exciting, operation context of RAS, hampers the reliability assurance of RAS, which decelerates the acceptance and everyday use of RAS. Different technological solutions have emerged to improve the design and reliability of RAS [5]. Most of the technological configurations include a combination of mechanical and electrical components, along with onboard software intelligence to adopt decisions without direct human intervention. In this context, using the ever-increasing prognostics and health management solutions, it is possible to develop a prognostics modelling approach for RAS health monitoring using reliability, machine learning, uncertainty modelling and optimization methods [6]. The project’s objective is to develop novel prognostics methods for RAS, which can accurately inform about the model’s confidence in the decisions in real-time and the way to mitigate the existing problem via optimization methods, and always, provide a worst-case estimate on its predictions by using a proper modelling and update of the different sources of uncertainty. In particular, the work will focus on the integration of uncertainties to make prognostic predictions robust, using concepts such as adversarial learning, combined with statistical learning and artificial intelligence methods. The models developed in this project will be validated with the data collected from industry partners that work with autonomous robots focusing on (i) autonomous remote inspections for renewable energy and (ii) automotive industry. The project will be developed in <https://www.mondragon.edu/en/home>Mondragon Unibertsitatea within the Electronics and Computer Science Department, in collaboration between the Data Analytics and Signal Processing and Communications groups. Throughout the thesis, the student will engage continuously with industry and stays at different universities and/or research centers will be pursued. Interested applicants, send your CV and a short motivation letter to: jiaizpurua(a)mondragon.edu and ezugasti(a)mondragon.edu Application deadline. Review of applications will begin July 1st and continue until the position is filled. *Requirements* - M.Sc. degree in telecommunications, electronics, computer science, mathematics, embedded systems or a related area. - Programming skills: Matlab, Python, R, or C++ (samples from prior projects or a GitHub repository are preferred) - Statistics/mathematics, data science/AI/ML - Knowledge/experience with autonomous systems is a plus. - Knowledge/experience with reliability and/or diagnostics/health management methods is a plus. - Experience with artificial intelligence / optimization methods is a plus. *References* [1] Feng, S., Yan, X., Sun, H. et al. Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment. *Nature Communications* 12, 748 (2021). <https://doi.org/10.1038/s41467-021-21007-8> https://doi.org/10.1038/s41467-021-21007-8 [2] Ellefsen, A. L., Æsøy, V., Ushakov, S., & Zhang, H. (2019). A comprehensive survey of prognostics and health management based on deep learning for autonomous ships. IEEE Transactions on Reliability, 68(2), 720-740 [3] Floreano, D., & Wood, R. J. (2015). Science, technology and the future of small autonomous drones. *nature*, *521*(7553), 460-466. [4] Aslansefat, K., Kabir, S., Abdullatif, A., Vasudevan, V., & Papadopoulos, Y. (2021). Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems. *Computer*, *54*(8), 66-76. [5] Elghazel, W., Bahi, J., Guyeux, C., Hakem, M., Medjaher, K., & Zerhouni, N. (2015). Dependability of wireless sensor networks for industrial prognostics and health management. Computers in Industry, 68, 1-15. [6] Aizpurua, J. I., Catterson, V. M., Papadopoulos, Y., Chiacchio, F., & Manno, G. (2017). Improved dynamic dependability assessment through integration with prognostics. *IEEE Transactions on Reliability*, *66*(3), 893-913. -- *Joxe Aizpurua.*

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