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A I I E Transactions 2023年第7期55卷 657-671页

作者： Yucheng Dong Siqi Wu Xiaoping Shi Yao Li Francisco Chiclana a Center for Network Big Data and Decision-Making Business School Sichuan University Chengdu China b Irving K. Barber School of Arts and Sciences University of British Columbia Kelowna Canada a Center for Network Big Data and Decision-Making Business School Sichuan University Chengdu Chinac Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain c Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada Spaind Institute of Artificial Intelligence School of Computer Science and Informatics De Montfort University Leicester UK

Failure Mode and Effect Analysis (FMEA) is a highly structured risk-prevention management process that improves the reliability and safety of a system. This article investigates one of the most critical issues in FMEA practice: Clustering failure modes based on their risks. In the failure mode clustering problem, all identified failure modes need to be assigned to several predefined and risk-ordered categories to manage their risks. We model the clustering of failure modes through multi-expert multiple criteria decision making with an additive value function, and call it the additiveN-clustering problem. We begin by proposing six axioms that describe an ideal clustering method in the additiveN-clustering problem, and find that the EXogenous Clustering Method (EXCM), where category thresholds can be exogenously provided, is ideal (Exogenous Possibility Theorem), whereas any endogenous clustering method, where the clustering is determined endogenously in the given method, cannot satisfy all six axioms simultaneously (Endogenous Impossibility Theorem). In practice, endogenous clustering methods are important, due to the difficulty in providing accurate and reasonable category thresholds of the EXCM. Therefore, we propose the Consensus-based ENdogenous Clustering Method (CENCM) and discuss its axiomatic properties. We also apply the CENCM to the SARS-CoV-2 prevention case and justify the CENCM through axiomatic comparisons and a detailed simulation experiment.

关键词： Reliability management failure mode and effect analysis clustering axioms consensus

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An efficient multi-attribute combinatorial auction for 4PL transportation service procurement

An efficient multi-attribute combinatorial auction for 4PL t...

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第35届中国控制与决策会议

作者： Na Yuan Haiming Liang Min Huang Yanfeng Zhang College of Information Science and Engineering Northeastern University Center for Network Big Data and Decision-Making Business School Sichuan University College of Computer Science and Engineering Northeastern University

In this paper,we study the mechanism design problem of combinatorial reverse auction for 4 PL transportation service procurement(TSP) considering price and multiple nonprice *** order to achieve efficient winner determination and transportation request allocation,we develop a 0-1 programing model to minimize social cost,where social cost includes real transportation cost of 3 PLs and the costs incurred by non-price attributes.A multi-attribute VCG(MA-VCG) reverse auction mechanism is proposed,which satisfies efficiency,incentive compatibility,individual rationality,and budget ***,a numerical example is designed to demonstrate the effectiveness and applicability of the proposed ***,sensitivity analysis is implemented to illustrate the influences of attribute preference,cost coefficient and other parameters on auction results.

关键词： Transportation service procurement Mechanism design Combinatorial reverse auction Multi-attribute auction

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An efficient multi-attribute combinatorial auction for 4PL transportation service procurement

An efficient multi-attribute combinatorial auction for 4PL t...

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Chinese Control and decision Conference, CCDC

作者： Na Yuan Haiming Liang Min Huang Yanfeng Zhang College of Information Science and Engineering Northeastern University Shenyang China Center for Network Big Data and Decision-Making Business School Sichuan University Chengdu China College of Computer Science and Engineering Northeastern University Shenyang China

In this paper, we study the mechanism design problem of combinatorial reverse auction for 4PL transportation service procurement (TSP) considering price and multiple non-price attributes. In order to achieve efficient winner determination and transportation request allocation, we develop a 0-1 programing model to minimize social cost, where social cost includes real transportation cost of 3PLs and the costs incurred by non-price attributes. A multi-attribute VCG (MA-VCG) reverse auction mechanism is proposed, which satisfies efficiency, incentive compatibility, individual rationality, and budget balance. Then, a numerical example is designed to demonstrate the effectiveness and applicability of the proposed mechanism. Finally, sensitivity analysis is implemented to illustrate the influences of attribute preference, cost coefficient and other parameters on auction results.

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Exploring the space-time pattern of log-transformed infectious count of COVID-19: A clustering-segmented autoregressive sigmoid model

arXiv

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arXiv 2021年

作者： Shi, Xiaoping Chen, Meiqian Dong, Yucheng Department of Mathematics and Statistics Thompson Rivers University Canada Center for Network Big Data and Decision-Making Business School Sichuan University China

At the end of April 20, 2020, there were only a few new COVID-19 cases remaining in China, whereas the rest of the world had shown increases in the number of new cases. It is of extreme importance to develop an efficient statistical model of COVID-19 spread, which could help in the global fight against the virus. We propose a clustering-segmented autoregressive sigmoid (CSAS) model to explore the space-time pattern of the log-transformed infectious count. Four key characteristics are included in this CSAS model, including unknown clusters, change points, stretched S-curves, and autoregressive terms, in order to understand how this outbreak is spreading in time and in space, to understand how the spread is affected by epidemic control strategies, and to apply the model to updated data from an extended period of time. We propose a nonparametric graph-based clustering method for discovering dissimilarity of the curve time series in space, which is justified with theoretical support to demonstrate how the model works under mild and easily verified conditions. We propose a very strict purity score that penalizes overestimation of clusters. Simulations show that our nonparametric graph-based clustering method is faster and more accurate than the parametric clustering method regardless of the size of data sets. We provide a bayesian information criterion (bIC) to identify multiple change points and calculate a confidence interval for a mean response. by applying the CSAS model to the collected data, we can explain the differences between prevention and control policies in China and selected *** Codes 62H30(Primary) 65D10 (Secondary) © 2021, CC bY-NC-ND.

关键词： Cluster analysis

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Countering terrorist propaganda: Competitive resource allocation to communities

A I I E Transactions

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A I I E Transactions 2025年第1期57卷

作者： Xia Chen Yucheng Dong Jun Zhuang a School of Public Administration University of Electronic Science and Technology of China Chengdu China b Center for Network Big Data and Decision-Making Business School Sichuan University Chengdu China c Department of Industrial and Systems Engineering University at Buffalo NY USA

Increased terrorist propaganda has caused greater violence worldwide. Communities are efficient channels through which terrorist organizations can access target audiences; thus, communities are playing larger roles in terrorist propaganda distribution. However, no previous studies have examined the interactions between terrorists and governments regarding terrorist propaganda in communities from a game-theoretic lens. This article aims to fill this research gap. We first classify the relationships between the communities as independent or interactive. For both cases, we describe the process of terrorist propaganda distribution in communities, highlighting the dependence of the degree of terrorist ideology within a community on the terrorist-organization and government resource allocations; based on this, we build novel sequential game models of the terrorist and the government and obtain the equilibrium solutions. Furthermore, we conduct a comparative study to elucidate the differences in the expected government losses for independent and interactive communities. The outcomes are as follows: (i) the higher the community propagation centrality, the greater the resource expenditure of the government and terrorist organization, and (ii) introducing an interaction network among communities decreases the expected government loss when the network directly destroys the distribution uniformity of the community propagation centralities. Finally, we present a case study to illustrate the usability of the proposed models. This study provides novel insights for governments targeting optimal allocation of intervention resources to communities so as to counter terrorist propaganda distributed by a strategic terrorist.

关键词： Homeland security terrorist propaganda opinion dynamics resource allocation communities game theory

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Opinion dynamics in finance and business: a literature review and research opportunities

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Financial Innovation 2020年第1期6卷 971-992页

作者： Quanbo Zha Gang Kou Hengjie Zhang Haiming Liang Xia Chen Cong‑Cong Li Yucheng Dong School of Management Science and Real Estate Chongqing UniversityChongqing 400045China School of Business Administration Southwestern University of Finance and EconomicsChengdu 611130China Business School Hohai UniversityNanjing 211100China Center for Network Big Data and Decision-Making Business SchoolSichuan UniversityChengdu 610065China School of Economics and Management Southwest Jiaotong UniversityChengdu 610031China

Opinion dynamics is an opinion evolution process of a group of agents,where the final opinion distribution tends to three stable states:consensus,polarization,and *** present,the opinion dynamics models have been extensively studied in differrent *** paper provides a review of opinion dynamics in finance and business,such as,finance,marketing,e-commerce,politics,and group decision ***,identified research challenges have been proposed to promote the future research of this topic.

关键词： Opinion dynamics Financial market business

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Redefining pandemic preparedness:Multidisciplinary insights from the CERP modelling workshop in infectious diseases,workshop report

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Infectious Disease Modelling 2024年第2期9卷 501-518页

作者： Marta C.Nunes Edward Thommes Holger Fröhlich Antoine Flahault Julien Arino Marc baguelin Matthew biggerstaff Gaston bizel-bizellot Rebecca borchering Giacomo Cacciapaglia Simon Cauchemez Alex barbier-Chebbah Carsten Claussen Christine Choirat Monica Cojocaru Catherine Commaille-Chapus Chitin Hon Jude Kong Nicolas Lambert Katharina b.Lauer Thorsten Lehr Cédric Mahe Vincent Marechal Adel Mebarki Seyed Moghadas Rene Niehus Lulla Opatowski Francesco Parino Gery Pruvost Andreas Schuppert Rodolphe Thiébaut Andrea Thomas-bachli Cecile Viboud Jianhong Wu Pascal Crépey Laurent Coudeville Center of Excellence in Respiratory Pathogens(CERP) Hospices Civils de Lyon(HCL)and Centre International de Recherche en Infectiologie(CIRI)Équipe SantéPubliqueÉpidémiologie etÉcologieÉvolutive des Maladies Infectieuses(PHE3ID)Inserm U1111CNRS UMR5308ENS de LyonUniversitéClaude Bernard Lyon 1LyonFrance South African Medical Research Council Vaccines&Infectious Diseases Analytics Research UnitFaculty of Health SciencesUniversity of the WitwatersrandJohannesburgSouth Africa New Products and Innovation(NPI) Sanofi Vaccines(Global)TorontoOntarioCanada Department of Mathematics and Statistics University of GuelphGuelphOntarioCanada Fraunhofer Institute for Algorithms and Scientific Computing(SCAI) Department of BioinformaticsSchloss BirlinghovenSankt AugustinGermany University of Bonn Bonn-Aachen International Center for IT(b-it)BonnGermany Institute of Global Health Faculty of MedicineUniversity of GenevaGenevaSwitzerland and Swiss School of Public HealthZürichSwitzerland Department of Mathematics University of ManitobaWinnipegManitobaCanada MRC Centre for Global Infectious Disease Analysis School of Public HealthImperial College LondonLondonUK Centre for Mathematical Modelling of Infectious Diseases Department of Infectious Disease EpidemiologyLondon School of Hygiene&Tropical MedicineLondonUK National Center for Immunization and Respiratory Diseases(NCIRD) US Centers for Disease Control and Prevention(CDC)AtlantaGAUSA Departement of Computational Biology Departement of Global HealthInstitut PasteurParisFrance Institut de Physique des Deux Infinis de Lyon(IP2I) UMR5822IN2P3/CNRSUniversitéClaude Bernard Lyon 1VilleurbanneFrance Mathematical Modelling of Infectious Diseases Unit Institut PasteurUniversitéParis CitéUMR2000 CNRSParisFrance Decision and Bayesian Computation Institut PasteurUniversitéParis CitéCNRS UMR 3571France Fraunhofer-Institute for Translational Medicine and Pharmacology HamburgGermany Institute of Global Health Faculty of MedicineUniversity of

In July 2023,the center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 *** report summarizes the rich discussions that occurred during the *** workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data,social media,and wastewater *** advancements were noted in the development of predictive models,with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease *** role of open collaboration between various stakeholders in modelling was stressed,advocating for the continuation of such partnerships beyond the pandemic.A major gap identified was the absence of a common international framework for data sharing,which is crucial for global pandemic ***,the workshop underscored the need for robust,adaptable modelling frameworks and the integration of different data sources and collaboration across sectors,as key elements in enhancing future pandemic response and preparedness.

关键词： Modelling Covid-19 Infectious diseases Pandemic preparedness Workshop

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Distributed linguistic representations in decision making: Taxonomy, key elements and applications, and challenges in data science and explainable artificial intelligence

arXiv

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arXiv 2020年

作者： Wu, Yuzhu Zhang, Zhen Kou, Gang Zhang, Hengjie Chao, Xiangrui Li, Cong-Cong Dong, Yucheng Herrera, Francisco School of Business Administration Southwestern University of Finance and Economics Chengdu611130 China Institute of Systems Engineering Dalian University of Technology Dalian116024 China Business School Hohai University Nanjing211100 China Center for Network Big Data and Decision-Making Business School Sichuan University Chengdu610065 China School of Economics and Management Southwest Jiaotong University Chengdu610031 China School of Information Management and Statistics Hubei University of Economics Wuhan430205 China University of Granada Granada18071 Spain Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia

Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence. Copyright © 2020, The Authors. All rights reserved.

关键词： decision making

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Correction to: Differences in factors influencing the use of eRehabilitation after stroke;a cross-sectional comparison between brazilian and Dutch healthcare professionals

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bMC health services research 2020年第1期20卷 607页

作者： berber brouns Leti van bodegom-Vos Arend J de Kloet Thea P M Vliet Vlieland Ingrid L C Gil Lígia M N Souza Lucia W braga Jorit J L Meesters Department of Orthopaedics Rehabilitation and Physical Therapy Leiden University Medical Center Albinusdreef 2 2333 ZA Leiden The Netherlands. b.brouns@basaltrevalidatie.nl. Faculty of Health Nutrition and Sports The Hague University for Applied Sciences The Hague The Netherlands. b.brouns@basaltrevalidatie.nl. Basalt Rehabilitation The Hague/ Leiden The Netherlands. b.brouns@basaltrevalidatie.nl. Department of Biomedical Data Sciences section Medical Decision Making Leiden University Medical Center Leiden The Netherlands. Faculty of Health Nutrition and Sports The Hague University for Applied Sciences The Hague The Netherlands. Basalt Rehabilitation The Hague/ Leiden The Netherlands. Department of Orthopaedics Rehabilitation and Physical Therapy Leiden University Medical Center Albinusdreef 2 2333 ZA Leiden The Netherlands. The SARAH Network of Rehabilitation Hospitals Brasilia Brazil.

An amendment to this paper has been published and can be accessed via the original article.

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A Fine Excision ATLS Manual No Longer Defines Trauma as a Surgical Disease

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ANNALS OF EMERGENCY MEDICINE 2010年第3期55卷 20A-24A页

作者： Millard, William b. The new 8th edition of the Advanced Trauma Life Support (ATLS) course manual contains a small but significant change. The phrase “trauma is a surgical disease” long a point of contention with other specialties caring for trauma patients has been removed. Now used in over 50 countries as the basis for training in the initial assessment and management of trauma this publication reflects the research and clinical experience of the American College of Surgeons (ACS) Committee on Trauma and expresses that organization's philosophy toward triage diagnosis and clinical care. Astute readers of the ATLS materials have noticed that a certain message is conspicuous by its absence. The preface to the 7th edition of the ATLS describes the ACS's role as follows: In accordance with that role and recognizing that trauma is a surgical disease the ACS Committee on Trauma (COT) has worked to establish guidelines for the care of the trauma patient. The 8th edition includes a substantially similar sentence minus the crucial phrase on trauma as a “surgical disease.” John B. Kortbeek MD FACS professor of surgery and critical care at the University of Alberta and a member of the COT who was instrumental in the revision process for the manual confirms that the deletion is intentional. Dr. Kortbeek explains the change in historical terms. “The intent of making that statement” he says “was to emphasize that to have a successful trauma system and a successful trauma hospital surgeons needed to be included in the management team and the care of the trauma patient. That remains true today. What changed over time is that that statement became a focal point and could be interpreted in varying ways including in a negative exclusive way suggesting that only surgeons should be managing trauma patients which is not correct and never was the intent of the statement.” The ATLS he says presents a “common language” for a safe and effective response to trauma not a mandatory formula. Harmonious relations among the various spe

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