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Identification of the football teams assessment model using the COMET method

Procedia computer science 2019年 159卷 2491-2501页

作者： Krzysztof Palczewski Wojciech Sałabun Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

Many people, organizations and managers try to assess the performance of the football teams and seek new improved approaches. Rankings are an unavoidable part of the football world, where high competitiveness and efficiency is a natural factor. One of the techniques to deal with such problems is the use of multi-criteria decision-analysis methods (MCDA), offering an effective approach to not only ranking but also assessing, selecting and sorting given alternatives. In this paper, the Characteristic Objects METhod (COMET) is used in order to create a performance ranking of the top-tier football clubs. The assessment model is identified and compared with the existing benchmark ranking by the Spearman’s rank correlation coefficient.

关键词： COMET Characteristic Objects Method football ranking MCDA multi-criteria decision-analysis

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Ccdh: Complexity Based Causal Discovery of Hidden Common Cause (and Other Beasts) in Time Series

SSRN

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SSRN 2022年

作者： Varga, Bálint Stippinger, Marcell Benkő, Zsigmond Fabó, Dániel Halász, Péter Erőss, Loránd Somogyvári, Zoltán Telcs, András Department of Computational Sciences Wigner Research Centre for Physics BudapestH-1121 Hungary János Szentágothai Doctoral School of Neurosciences Semmelweis University BudapestH-1085 Hungary Epilepsy Center Juhász Pál National Institute of Clinical Neurosciences BudapestH-1145 Hungary EPI-HELP BudapestH-1012 Hungary Department of Functional Neurosurgery National Institute of Clinical Neurosciences BudapestH-1145 Hungary Faculty of Information Technology and Bionics Péter Pázmány Catholic University BudapestH-1083 Hungary Neuromicrosystems ltd. BudapestH-1113 Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics BudapestH-1111 Hungary Department of Quantitative Methods University of Pannonia Faculty of Business and Economics VeszprémH-8200 Hungary

Non-interventional causal discovery is a challenging task. This is particularly true for causal relations of dynamic systems with chaotic attractors. The known solutions are data-intensive and cannot detect a hidden common driver (common cause or confounder). We propose a new method which eliminates both *** method is based on Takens' embedding theorem and complexity of the rank order patterns of the embedded series measured by the compressibility usingnon-sequential recursive pair substitution. The method works on shortsamples and is capable of detecting all kinds of causal connection (including hidden common cause). The newmethod is validated on synthetic data sets and applied to two types of humanelectrophysiological data from epileptic patients. In bothcases, the method revealed self-consistent, contradiction-free and biologically relevant causal connections between the investigatedareas. Thus the method may provide additional indication for the location ofintervention for the decision making medical panel. Given the method advantages and simplicity it might be applied in many other scientific and practical areas with success. © 2022, The Authors. All rights reserved.

关键词： Time series

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Influence of various normalization methods in PROMETHEE II: an empirical study on the selection of the airport location

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Procedia computer science 2019年 159卷 2051-2060页

Multi-criteria decision-analysis (MCDA) is a popular field of study with implementations in various areas, such as supply chain management, logistics, engineering, health, sustainable development, to name a few. The normalization of the data considered in such challenges (decision matrix) is an essential step of many MCDA methods. Different normalization techniques can influence the results obtained, and hence, generate different final rankings. In this paper, the investigation of normalization effects is conducted in the PROMETHEE II method. Five different normalization methods were used and additionally, the case without normalization was examined. In order to compare the influence of various normalization methods, an empirical study on the selection of the location of the airport was analyzed, with ten alternatives and seven criteria. The outcomes of investigation of normalization effects in regard to the PROMETHEE II method prove that they do have an impact on the final rankings.

关键词： PROMETHEE II normalization multi-criteria decision-analysis MCDA

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The fuzzy TOPSIS applications in the last decade

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Procedia computer science 2019年 159卷 2294-2303页

Multi-criteria decision-analysis (MCDA) methods have been widely applied by many researchers in various fields of study. One of the numerous MCDA methods, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under fuzzy environment, namely fuzzy TOPSIS, has been successfully applied in many practical, real-world challenges. This paper provides a short review of fuzzy TOPSIS applications. The research is based on 25 studies conducted in the years 2009 - 2018. Most relevant and most cited papers concerned with fuzzy TOPSIS technique were analyzed and categorized into application areas, such as supply chain, environment, energy sources, business, healthcare. Fuzzy TOPSIS implementations are examined and compared by approaches used, such as fuzzy sets, hesitant fuzzy sets or intuitionistic fuzzy sets, by other methods combined with fuzzy TOPSIS, such as fuzzy Analytic Hierarchic Process (AHP) or enhancements for group decision-making and by a number of alternatives and criteria used. Finally, insights into ongoing trends, most popular approaches, and directions of study concerning the fuzzy TOPSIS method are presented.

关键词： fuzzy TOPSIS review multi-criteria decision-analysis MCDA

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Design of an Infological Model for Prediction of Problems during Drilling Using Machine Learning and Systems Analysis

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IOP Conference Series: Earth and Environmental science 2022年第4期988卷

作者： A L Zolkin V D Munister R V Faizullin N N Smoktal Ph.D. in Engineering Science Senior Lecturer of Computer and Information Sciences Department of the Povolzhskiy State University of Telecommunications and Informatics Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Associate Professor of the Department of Information Technologies in Public Administration Institute of Management Technologies MIREA — Russian technological university Teacher at the Department of 'Renewable Energy Sources and Electrical Systems and Networks' Sevastopol State University

The article deals with the actual problem of identification of probabilistic processes as a result of the operation of drilling rigs in the oil industry. The world experience of finding ways to solve optimal forecasting tools using machine learning is summarized. Mnemonic rule for the implementation of classification and ranking systems in the detection of feedbacks as probable indicators of complications of ongoing technological processes is implemented through the description of the formal model of the drilling process in form of a hidden Markov model. The results of evaluation of the developed mathematical apparatus in the form of predictive analytics and a cut of basic complications in the drilling process are presented. An infological diagram of the developed architectural solution of the analysis project is proposed. The results of the control algorithms formalization are given in conclusion. These results allow to ensure the effective procees modes of equipment operation and make it possible to save electricity and water.

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Ecology and STEM

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IOP Conference Series: Materials science and Engineering 2021年第1期1089卷

作者： E V Esina M A Velichko Yu P Gladkikh O N Satler R A Nortsova Department of Foreign Languages and Professional Communication Belgorod State University 85 Pobeda St. Belgorod 308015 Russia Department of Computer Science Natural Sciences and Teaching Methods Belgorod State University 85 Pobeda St. Belgorod 308015 Russia Gymnasium #12 4 Khikhlushki St. Belgorod 308014 Russia

This paper is devoted to combining ecology challenges and STEM technologies. We consider ecology as an integral part of STEM process. The including of ecology in the STEM allows not only to develop mathematician calculations and engineering skills but also forms students' ecological consciousness. The attempt to combine ecology and STEM is aimed to make the knowledge in ecological sphere more practical. STEM education can help in solving the main ecological problems and challenges. STEM lessons, projects, conferences, exchanges could explain and give a living example of damages caused to our planet by irrational using of natural resources. It can improve public awareness and show the careful attitude to our planet.

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A Doubly-Masked-Ballot Multi-questions Voting Scheme with Distributed Trust

A Doubly-Masked-Ballot Multi-questions Voting Scheme with Di...

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Computing Conference, 2019

作者： Szabo, Robert Telcs, Andras Department of Telecommunications and Media Informatics Budapest University of Technology and Economics Budapest Hungary Department of Computational Sciences Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Quantitative Methods Faculty of Business and Economics University of Pannonia Veszprem Hungary

ISBN: (纸本)9783030228675

We propose an electronic voting scheme for multiple questions voting based on masked ballots, homomorph counting, publicly verifiable secret sharing based tallying and public communication channels. In our scheme all on-line authority functions (authentication, candidate slate check, counting and tallying) are distributed among the active voters. Off-line authorities only prepare and distribute election secrets. We analyze our scheme for different adversary attacks and show that the maximum that the strongest adversary can achieve is a random attack. © 2019, Springer Nature Switzerland AG.

关键词： Security of data

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A leadfield-free optimization framework for transcranially applied electric currents

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computers in Biology and Medicine 2025年 195卷

作者： Konstantin Weise Kristoffer H. Madsen Torge Worbs Thomas R. Knösche Anders Korshøj Axel Thielscher Department of Clinical Medicine Aarhus University Aarhus Denmark Methods and Development Group “Brain Networks” Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany Leipzig University of Applied Sciences (HTWK) Institute for Electrical Power Engineering Leipzig Germany Technical University of Denmark Section for Cognitive Systems Department of Applied Mathematics and Computer Science Kongens Lyngby Denmark Danish Research Centre for Magnetic Resonance Department of Radiology and Nuclear Medicine Copenhagen University Hospital Amager and Hvidovre Hvidovre Denmark Technical University of Denmark Section for Magnetic Resonance Department of Health Technology Kongens Lyngby Denmark Department of Neurosurgery Aarhus University Hospital Aarhus Denmark

Background Transcranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT) and Tumor Treating Fields (TTFields) are based on the application of electric current patterns to the brain. Objective The optimal electrode positions, shapes and alignments for generating a desired current pattern in the brain vary between persons due to anatomical variability. The aim is to develop a flexible and efficient computational approach to determine individually optimal montages based on electric field simulations. methods We propose a leadfield-free optimization framework that allows the electrodes to be placed freely on the head surface. It is designed for the optimization of montages with a low to moderate number of spatially extended electrodes or electrode arrays. Spatial overlaps are systematically prevented during optimization, enabling arbitrary electrode shapes and configurations. The approach supports maximizing the field intensity in target region-of-interests (ROI) and optimizing for a desired focality-intensity tradeoff. Results We demonstrate montage optimization for standard two-electrode TES, focal center-surround TES, TIS, ECT and TTFields. Comparisons against reference simulations are used to validate the performance of the algorithm. The system requirements are kept moderate, allowing the optimization to run on regular notebooks and promoting its use in basic and clinical research. Conclusion(s) The new framework complements existing optimization methods that require small electrodes, a predetermined discretization of the electrode positions on the scalp and work best for multi-channel systems. It strongly extends the possibilities to optimize electrode montages towards application-specific aims and supports researchers in discovering innovative stimulation schemes. The framework is available in SimNIBS.

关键词： Electroconvulsive therapy Montage optimization Temporal interference stimulation Transcranial electric stimulation Tumor treating fields

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The Use of Large Language Models and Their Association With Enhanced Impact in Biomedical Research and Beyond

MedComm - Future Medicine

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MedComm - Future Medicine 2025年第2期4卷

作者： Cheng, Huzi Shi, Wen Sheng, Bin Lee, Aaron Y. Car, Josip Chaudhary, Varun Atanasov, Atanas G. Liu, Nan Qiu, Yue Chen, Qingyu Wong, Tien Yin Tham, Yih-Chung Zheng, Ying-Feng Department of Psychological and Brain Sciences Indiana University Bloomington IN United States Department of Ophthalmology the First Affiliated Hospital of Guangzhou Medical University Guangzhou China Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology University of Washington School of Medicine Seattle WA United States Centre for Population Health Sciences Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore Department of Primary Care and Public Health School of Public Health Imperial College London London United Kingdom Department Health Research Methods Evidence and Impact McMaster University Hamilton ON Canada Department of Surgery McMaster University Hamilton ON Canada Ludwig Boltzmann Institute Digital Health and Patient Safety Medical University of Vienna Vienna Austria Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences Jastrzebiec Poland Centre for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Tsinghua Medicine Tsinghua University Beijing China Yale School of Medicine Yale University United States Singapore Eye Research Institute Singapore National Eye Centre Singapore School of Clinical Medicine Beijing Tsinghua Changgung Hospital Beijing China Ophthalmology and Visual Sciences Academic Clinical Program Duke-NUS Medical School Singapore Centre for Innovation and Precision Eye Health and Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China

The release of ChatGPT in 2022 has catalyzed the adoption of large language models (LLMs) across diverse writing domains, including academic writing. However, this technological shift has raised critical questions regarding the prevalence of LLM usage in academic writing and its potential influence on the quality and impact of research articles. Here, we address these questions by analyzing preprint articles from arXiv, bioRxiv, and medRxiv between 2022 and 2024, employing a novel LLM usage detection tool. Our study reveals that LLMs have been widely adopted in biomedical and other types of academic writing since late 2022. Notably, we noticed that LLM usage is linked to an enhanced impact of research articles after examining their correlation, as measured by citation numbers. Furthermore, we observe that LLMs influence specific content types in academic writing, including hypothesis formulation, conclusion summarization, description of phenomena, and suggestions for future work. Collectively, our findings underscore the potential benefits of LLMs in scientific communication, suggesting that they may not only streamline the writing process but also enhance the dissemination and impact of research findings across disciplines. © 2025 The Author(s). MedComm - Future Medicine published by John Wiley & Sons Australia, Ltd on behalf of Sichuan International Medical Exchange & Promotion Association (SCIMEA).

关键词： academic writing chatGPT large language models LLM

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Robust geometrical parametrization of the lower limb for the digital twin of patients under compression therapy

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computer methods and programs in biomedicine 2025年 269卷 108875页

作者： Aratz Garcia-LLona Miquel Aguirre Francesc Verdugo Stéphane Avril Mines Saint-Étienne University Lyon University Jean Monnet INSERM Saint-Étienne France. Electronic address: aratz.garciallona@emse.fr. Laboratori de Càlcul Numèric Universitat Politècnica de Catalunya Barcelona Spain International Centre for Numerical Methods in Engineering (CIMNE) Gran Capità Barcelona Spain. Department of Computer Science Vrije Universiteit Amsterdam Amsterdam The Netherlands. Mines Saint-Étienne University Lyon University Jean Monnet INSERM Saint-Étienne France.

BACKGROUND AND OBJECTIVE:Compression therapy is extensively used for the treatment of venous deficiency and edema in the lower limb. The applied compression improves fluid circulation, which reduces the interstitial fluid accumulation. However, the effect of compression garments on soft tissues is poorly understood due to the high variability among the patients. With the long-term goal of designing patient-specific compression therapy, this study aims to develop a real-time simulation tool, able to predict the mechanical response of soft tissues of the lower limb under compression. methods:For such purpose, the use of standard Finite Element Analysis (FEA) falls short, as typically large numerical models needed for such simulations imply high computational cost. For this purpose, a solution based on Reduced Order Modeling (ROM) is developed to compute, in real-time, the mechanical effects of compression therapy. More specifically, this work focuses on the geometrical parametrization of lower limbs and the definition of the ROM through an adaptive sampling, which reduces the computational cost of the offline stage. RESULTS:The implemented ROM reduces the dimensionality of the problem, which enables to carry out simulation in real time (online stage). Moreover, the proposed adaptive-sampling method offers an acceptable trade-off between computational cost and accuracy on the offline stage. Once the ROM is developed, it is used to perform a sensitivity analysis, which gives a detailed insight on the mechanical effects in the soft tissues of the lower limb. CONCLUSION:The proposed methodology to develop ROM of the lower limb serves as a valuable numerical tool to foresee the effects of the compression therapy on the lower limb.

关键词： Geometry parametrization Lower-limb edema Parallel-adaptive sampling Reduced order model

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