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Corrigendum to “An improved multiplicative acceptability consistency-driven group decision making with triangular fuzzy reciprocal preference relations” [Comput. Ind. Eng. 176 (2023) 108981]

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Computers & Industrial Engineering 2023年 183卷

作者： Mengqi Li Jing Huang Xia Liu Yejun Xu Francisco Herrera Business School Hohai University Nanjing 211100 PR China Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Granada 18071 Spain School of Management Science and Engineering Nanjing University of Information Science and Technology Nanjing 210044 PR China College of Management and Economics Tianjin University Tianjin 300072 PR China

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Correction: Medical health resources allocation evaluation in public health emergencies by an improved ORESTE method with linguistic preference orderings

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Fuzzy Optimization and Decision Making 2023年第1期23卷 29-29页

作者： Gou, Xunjie Xu, Xinru Deng, Fumin Zhou, Wei Herrera-Viedma, Enrique Business School Sichuan University Chengdu China School of Finance Yunnan University of Finance and Economics Kunming China Andalusian Research Institute in Data Science and Computational Intelligence Granada Spain

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Success-Driven Opinion Formation Determines Social Tensions

SSRN

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SSRN 2023年

作者： Chica, Manuel Perc, Matjaž Santos, Francisco C. Andalusian Research Institute DaSCI "Data Science and Computational Intelligence" University of Granada Granada18071 Spain School of Electrical Engineering and Computing The University of Newcastle CallaghanNSW2308 Australia Instituto Superior Técnico Universidade de Lisboa Porto Salvo2744-016 Portugal Faculty of Natural Sciences and Mathematics University of Maribor Koroška cesta 160 Maribor2000 Slovenia Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Alma Mater Europaea Slovenska ulica 17 Maribor2000 Slovenia Complexity Science Hub Vienna Josefstädterstraße 39 Vienna1080 Austria Department of Physics Kyung Hee University 26 Kyungheedae-ro Dongdaemun-gu Seoul Korea Republic of

Polarization is common in politics and public opinion. It is believed to be shaped by the media as well as ideologies, and often incited by misinformation. However, little is known about the microscopic dynamics behind polarization and the resulting social tensions. By coupling together opinion formation with the strategy selection in different social dilemmas, we reveal how success at an individual level transforms to global consensus or lack thereof. When defection carries with it the fear of punishment in the absence of greed, as in the stag-hunt game, opinion fragmentation is smallest. Conversely, if defection promises a higher payoff and thus evokes also greed, like in the prisoner's dilemma and the snowdrift game, consensus is much more difficult to attain. Our research thus challenges the top-down narrative of social tensions, showing that they may well originate from fundamental principles at individual level, like the desire to prevail in pairwise evolutionary comparisons. © 2023, The Authors. All rights reserved.

关键词： Polarization

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Ed-Tgan: A Methodology on Temporal Generative Gan for Imbalanced data for Predicting Academic Performance of Students

SSRN

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SSRN 2022年

作者： Waheed, Hajra Zhou, Jia Aljohani, Naif R. Tuarob, Suppawong Nawaz, Raheel Herrera, Francisco Hassan, Saeed-Ul Information Technology University 346-B Ferozepur Road Lahore Pakistan Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University Zhejiang Jinhua321004 China Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia Faculty of Information and Communication Technology Mahidol University Thailand Staffordshire University Stoke-on-Trent United Kingdom Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Manchester Metropolitan University Manchester United Kingdom

With the increase in the self-paced learning phenomenon, class imbalance in the learning analytics community has become more prevalent, with lesser students dropping out than students who intend to pursue. Similarly, an imbalance in the behavioral performances of students is also observed. This imbalance problem becomes more complicated for temporal data, where each time sequence represents a particular student, and several sequences formulate the overall engagement of students throughout a course. The conventional methods for generating synthetic data do not account for this association of sequences, where each synthetically generated student is associated with its previous sequence. Generative Adversarial Networks (GANs) have been rapidly adopted in the machine learning discipline for synthetic data generation to reduce the class imbalance. In this study, we propose a deep learning-powered methodology called Educational Temporal Generative Adversarial Networks (Ed-TGANs) methodology comprising the following steps: a) Smart data Processing for Actionable data, b) GANs for Temporal data Generation, and c) Learning Approach. Furthermore, the Open University Learning Analytics dataset was deployed as a case study comprising 69% pass and 31% fail students to validate the effectiveness of our proposed methodology, encompassing discrete and continuous features. The results are compared with GAN-based and non-GAN upsampling approaches to demonstrate the proposed methodology's effectiveness, which shows an increase in accuracy of up to 5.33% compared to classic GANs, resulting in improved understating of student behavior. We believe that the presented methodology can be used as a starting point for various areas for upsampling jobs with temporal longitudinal data. © 2022, The Authors. All rights reserved.

关键词： Students

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EXPLAINABLE ARTIFICIAL intelligence (XAI) 2.0: A MANIFESTO OF OPEN CHALLENGES AND INTERDISCIPLINARY RESEARCH DIRECTIONS

arXiv

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arXiv 2023年

作者： Longo, Luca Brcic, Mario Cabitza, Federico Choi, Jaesik Confalonieri, Roberto Ser, Javier Del Guidotti, Riccardo Hayashi, Yoichi Herrera, Francisco Holzinger, Andreas Jiang, Richard Khosravi, Hassan Lecue, Freddy Malgieri, Gianclaudio Páez, Andrés Samek, Wojciech Schneider, Johannes Speith, Timo Stumpf, Simone The Artificial Intelligence and Cognitive Load Research Lab Technological University Dublin Ireland University of Zagreb Faculty of Electrical Engineering and Computing Croatia University of Milano-Bicocca Milan Italy IRCCS Ospedale Galeazzi Sant’Ambrogio Milan Italy Kim Jaechul Graduate School of AI Korea Advanced Institute of Science & Technology Korea Republic of INEEJI Corporation Korea Republic of Department of Mathematics University of Padua Italy Derio Spain Bilbao Spain University of Pisa Pisa Italy Department of Computer Science Meiji University Tokyo Japan Department of Computer Science and Artificial Intelligence DaSCI Andalusian Institute in Data Science & Computational Intelligence University of Granada Granada Spain Human-Centered AI Lab University of Natural Resources and Life Sciences Vienna Austria School of Computing and Communications Lancaster University United Kingdom The University of Queensland Brisbane Australia Sophia Antipolis France eLaw Center for Law and Digital Technologies Leiden University Netherlands Department of Philosophy Universidad de los Andes Bogotá Colombia Center for Research & Formation in Artificial Intelligence Universidad de los Andes Bogotá Colombia Technical University of Berlin Berlin Germany Fraunhofer Heinrich Hertz Institute Berlin Germany Berlin Germany Department of Information Systems and Computer Science University of Liechtenstein Liechtenstein Liechtenstein Department of Philosophy University of Bayreuth Bayreuth Germany Center for Perspicuous Computing Saarland University Saarbrücken Germany School of Computing Science University of Glasgow United Kingdom

As systems based on opaque Artificial intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. © 2023, CC BY-SA.

关键词： Ethical technology

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Corrigendum to “Reciprocal Recommender Systems: Analysis of state-of-art literature, challenges and opportunities towards social recommendation” Information Fusion Volume 69 (2020) 103-127

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Information Fusion 2021年 75卷 101-101页

作者： Iván Palomares James Neve Carlos Porcel Luiz Pizzato Ido Guy Enrique Herrera-Viedma Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI) University of Granada Spain Intelligent Systems Laboratory University of Bristol Bristol United Kingdom AI Labs Commonwealth Bank of Australia Sydney Australia eBay Research Netanya Israel Department of Electrical and Computer Engineering from the Faculty of Engineering of the King Abdulaziz University Jeddah 21589 Saudi Arabia

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Correction: An intelligent approach for estimating aeration efficiency in stepped cascades: optimized support vector regression models and mutual information theory

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Soft Computing 2022年第22期26卷 12865-12865页

作者： Haji Seyed Asadollah, Seyed Babak Sharafati, Ahmad Haghbin, Masoud Motta, Davide Hosseinian Moghadam Noghani, Mohamadreza Department of Environmental Resources Engineering State University of New York College of Environmental Science and Forestry Syracuse USA Department of Civil Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Structural Mechanics and Hydraulics Engineering Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada (UGR) Granada Spain Department of Mechanical and Construction Engineering Northumbria University Newcastle upon Tyne UK

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Corrigendum to “Some models to manage additive consistency and derive priority weights from hesitant fuzzy preference relations” [Inform. Sci. 586 (2022) 450–467]

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Information sciences 2023年 631卷 327-327页

作者： Yejun Xu Weijia Dai Jing Huang Mengqi Li Enrique Herrera-Viedma College of Management and Economics Tianjin University Tianjin 300072 PR China Research Center for Green Development of Agriculture South China Agriculture University Guang Zhou 510642 PR China Business School Hohai University Nanjing 210009 PR China Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada 18071 Spain

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Subgrouping of Burkitt lymphoma variants by DNA methylation is driven by an EBV-associated epigenotype

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Hematological Oncology 2023年第S2期41卷

作者： S. Glaser C. Del Val R. Wagener H. Kretzmer W. Klapper M. Hummel O. Ammerpohl P. Lichter B. Burkhardt L. Trümper S. Mbulaiteye Institute of Human Genetics Ulm University and Ulm University Medical Center Ulm Germany Department of Computer Science and Artifical Intelligence Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) Universtiy of Granada Granada Spain Transciptome Bioinformatics Group LIFE Research Center for Civilization Diseases University of Leipzig Leipzig Germany Department of Pathology University of Kiel/University Hospital Schleswig-Holstein Kiel Germany Institute of Pathology Charité – University Medicine Berlin Berlin Germany Division of Molecular Genetics German Cancer Research Center Heidelberg Germany Department of Pediatric Hematology and Oncology University Hospital Münster Münster Germany Hematology and Oncology University of Göttingen Göttingen Germany Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Bethesda MC USA

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The multichord stellar occultation by the centaur Bienor on

arXiv

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arXiv 2022年

作者： Fernández-Valenzuela, Estela Morales, N. Vara-Lubiano, M. Ortiz, J.L. Benedetti-Rossi, G. Sicardy, B. Kretlow, M. Santos-Sanz, P. Morgado, B. Souami, D. Organero, F. Ana, L. Fonseca, F. Román, A. Alonso, S. Gonçalves, R. Ferreira, M. Iglesias-Marzoa, R. Lamadrid, J.L. Alvarez-Candal, A. Assafin, M. Braga-Ribas, F. Camargo, J.I.B. Colas, F. Desmars, J. Duffard, R. Lecacheux, J. Gomes-Júnior, A.R. Rommel, F.L. Vieira-Martins, R. Pereira, C.L. Casanova, V. Selva, A. Perelló, C. Mottola, S. Hellmich, S. Maestre, J.L. Castro-Tirado, A.J. Pal, A. Trigo-Rodriguez, J.M. Beisker, W. Laporta, A. Garcés, M. Escaned, L. Bretton, M. Florida Space Institute UCF 12354 Research Parkway Partnership 1 building Room 211 Orlando United States Instituto de astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n Granada18008 Spain UNESP - São Paulo State University Grupo de Dinâmica Orbital e Planetologia SP Guaratinguetá12516-410 Brazil Laboratório Interinstitucional de e-Astronomia - LIneA INCT do e-Universo Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil LESIA Observatoire de Paris Université PSL Sorbonne Université Université de Paris CNRS Meudon92190 France naXys University of Namur 8 Rempart de la Vierge NamurB-5000 Belgium Rua Gal. José Cristino 77—Bairro Imperial de São Cristóvão Rio de Janeiro20921-400 Brazil Complejo Astronómico de La Hita Camino de Doña Sol s/n LaVilla de Don fadrique45850 Spain Sociedad Astronómica Granadina Apartado de Correos 195 Granada18080 Spain Software Engineering Department Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Spain Instituto Politécnico de Tomar CI2 e U.D. Matemática e Física Tomar2300-313 Portugal Centro Ciência Viva Alto de Santa Bárbara Via Galileu Galilei 817 Constância2250-100 Portugal Centro de Estudios de Física del Cosmos de Aragón Plaza San Juan 1 Teruel44001 Spain Instituto de Física Aplicada a las Ciencias y las Tecnologías Universidad de Alicante San Vicent del Raspeig AlicanteE03080 Spain Observatório do Valongo/UFRJ Ladeira Pedro Antonio 43 RJ Rio de Janeiro20.080-090 Brazil Av. Sete de Setembro 3165 CEP Curitiba80230-901 Brazil Institut Polytechnique des Sciences Avancées IPSA 63 boulevard de Brandebourg Ivry-sur-SeineF-94200 France Institut de Mécanique Céleste et de Calcul des Éphémérides IMCCE Observatoire de Paris PSL Research University CNRS Sorbonne Universités UPMC Univ Paris 06 Univ. Lille 77 Av. Denfert-Rochereau ParisF-75014 France Agrupación Astronómica de Sabadell Carrer Prat de la Riba 116 Sabadell08206 Spai

Within our program of physical characterization of trans-Neptunian objects and centaurs, we predicted a stellar occultation by the centaur (54598) Bienor to occur on January 11, 2019, with good observability potential. We obtained high accuracy astrometric data to refine the prediction, resulting in a shadow path favorable for the Iberian Peninsula. This encouraged us to carry out an occultation observation campaign that resulted in five positive detections from four observing sites. This is the fourth centaur for which a multichord (more than two chords) stellar occultation has been observed so far, the other three being (2060) Chiron, (10199) Chariklo, and (95626) 2002 GZ32. From the analysis of the occultation chords, combined with the rotational light curve obtained shortly after the occultation, we determined that Bienor has an area-equivalent diameter of 150 ± 20 km. This diameter is ∼ 30 km smaller than the one obtained from thermal measurements. The position angle of the short axis of the best fitting ellipse obtained through the analysis of the stellar occultation does not match that of the spin axis derived from long-term photometric models. We also detected a strong irregularity in one of the minima of the rotational light curve that is present no matter the aspect angle at which the observations were done. We present different scenarios to reconcile the results from the different techniques. We did not detect secondary drops related to potential rings or satellites. Nonetheless, similar rings in size to that of Chariklo’s cannot be discarded due to low data accuracy. © 2022, CC BY.

关键词： Photometry

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