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Operational research: Methods and Applications

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arXiv 2023年

作者： Petropoulos, Fotios Laporte, Gilbert Aktas, Emel Alumur, Sibel A. Archetti, Claudia Ayhan, Hayriye Battarra, Maria Bennell, Julia A. Bourjolly, Jean-Marie Boylan, John E. Breton, Michèle Canca, David Charlin, Laurent Chen, Bo Cicek, Cihan Tugrul Cox, Louis Anthony Currie, Christine S.M. Demeulemeester, Erik Ding, Li Disney, Stephen M. Ehrgott, Matthias Eppler, Martin J. Erdogan, Güneş Fortz, Bernard Franco, L. Alberto Frische, Jens Greco, Salvatore Gregory, Amanda J. Hämäläinen, Raimo P. Herroelen, Willy Hewitt, Mike Holmström, Jan Hooker, John N. Işık, Tugçe Johnes, Jill Kara, Bahar Y. Karsu, Özlem Kent, Katherine Köhler, Charlotte Kunc, Martin Kuo, Yong-Hong Letchford, Adam N. Leung, Janny Li, Dong Li, Haitao Lienert, Judit Ljubić, Ivana Lodi, Andrea Lozano, Sebastián Lurkin, Virginie Martello, Silvano McHale, Ian G. Midgley, Gerald Morecroft, John D.W. Mutha, Akshay Oguz, Ceyda Petrovic, Sanja Pferschy, Ulrich Psaraftis, Harilaos N. Rose, Sam Saarinen, Lauri Salhi, Said Song, Jing-Sheng Sotiros, Dimitrios Stecke, Kathryn E. Strauss, Arne K. Tarhan, Istenç Thielen, Clemens Toth, Paolo Van Woensel, Tom Vanden Berghe, Greet Vasilakis, Christos Vaze, Vikrant Vigo, Daniele Virtanen, Kai Wang, Xun Weron, Rafal White, Leroy Yearworth, Mike Yıldırım, E. Alper Zaccour, Georges Zhao, Xuying School of Management University of Bath Bath United Kingdom Makridakis Open Forecasting Center University of Nicosia Nicosia Cyprus Department of Decision Sciences HEC Montréal Montreal Canada Molde University College Molde Norway Cranfield School of Management Cranfield University Cranfield United Kingdom Department of Management Sciences University of Waterloo Waterloo Canada ESSEC Business School in Paris Department of Information Systems Decision Sciences and Statistics Cergy France H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta United States Centre for Decision Research Leeds University Business School University of Leeds Leeds United Kingdom Université du Québec à Montréal Montreal Canada Centre for Marketing Analytics and Forecasting Lancaster University Management School Lancaster University Lancaster United Kingdom School of Engineering Department of Industrial Engineering and Management Science I University of Seville Seville Spain Mila-Quebec AI Institute Montreal Canada Warwick Business School University of Warwick Coventry United Kingdom Department of Industrial Engineering Atilim University Ankara Turkey Department of Business Analytics University of Colorado School of Business Denver United States Cox Associates Denver United States Mathematical Sciences University of Southampton Southampton United Kingdom Faculty of Economics and Business Research Center for Operations Management KU Leuven Leuven Belgium Durham University Business School Durham University Durham United Kingdom Center for Simulation Analytics and Modelling University of Exeter Business School Exeter United Kingdom Department of Management Science Lancaster University Management School Lancaster University Lancaster United Kingdom University of St. Gallen St. Gallen Switzerland HEC - Management School of the University of Liège Liège Belgium Département d'Informatique Université Libre de Bruxelles Bruss

Throughout its history, Operational research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes. © 2023, CC BY.

关键词： Decision making

Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching

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arXiv 2020年

作者： Khan, Wasiq Hussain, Abir Khan, Sohail Ahmed Al-Jumailey, Mohammed Nawaz, Raheel Liatsis, Panos Department of Computing and Mathematics Liverpool John Moores University LiverpoolL33AF United Kingdom Department of Computer Science DeepCamera Research Lab Interactive Media Smart System Emerging Technologies Center Nicosia Cyprus The Regenerative Clinic Queen Anne Medical Centre Harley Street Medical Area London United Kingdom Department of Computing and Mathematics Manchester Metropolitan University ManchesterM156BH United Kingdom Department of Electrical Engineering and Computer Science Khalifa University PO Box 127788 Abu Dhabi United Arab Emirates

Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools. However, limited work has been performed towards the modelling of complex associations between the combined demographic attributes and varying nature of the COVID-19 infections across the globe. This study presents an intelligent approach to investigate the multi-dimensional associations between demographic attributes and COVID-19 global variations. We gather multiple demographic attributes and COVID-19 infection data (by 8 January 2021) from reliable sources, which are then processed by intelligent algorithms to identify the significant associations and patterns within the data. Statistical results and experts’ reports indicate strong associations between COVID-19 severity levels across the globe and certain demographic attributes, e.g. female smokers, when combined together with other attributes. The outcomes will aid the understanding of the dynamics of disease spread and its progression, which in turn may support policy makers, medical specialists and society, in better understanding and effective management of the disease. © 2020, CC BY.

关键词： Population statistics

Retraction notice to "An efficient and magnetically recoverable g-C3N4/ZnS/CoFe2O4 nanocomposite for sustainable photodegradation of organic dye under UV-visible light illumination" [Environ. Res. 201 (2021) 111429]

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Environmental research 2025年 279卷 121909页

作者： G Palanisamy Nora Hamad Al-Shaalan K Bhuvaneswari G Bharathi G Bharath T Pazhanivel Sathishkumar V E Madan Kumar Arumugam S K Khadeer Pasha Mohamed A Habila Adel El-Marghany Department of Physics Periyar University Salem 636 011 Tamil Nadu India. Department of Chemistry College of Science Princess Nourah bint Abdulrahman University Riyadh 11671 Saudi Arabia. Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province College of Optoelectronic Engineering Shenzhen University Shenzhen Guangdong Province 518060 PR China. Department of Chemical Engineering Khalifa University P.O. Box 127788 Abu Dhabi United Arab Emirates. Department of Computer Science and Engineering Kongu Engineering College Perundurai Erode 638101 Tamil Nadu India. Cancer Biology Lab Centre for Molecular and Nanomedical Sciences Sathyabama Institute of Science and Technology Chennai 600119 India. Department of Physics VIT-AP University Amaravati Guntur 522501 Andhra Pradesh India. Advanced Materials Research Chair Chemistry Department College of Science King Saud University Riyadh 11451 Saudi Arabia.

A new multilevel voltage source inverter configuration with minimum number of circuit elements

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Journal of Central South University 2017年第4期24卷 912-920页

作者： Mohammad Reza Jannati Oskuee Masoumeh Karimi Yahya Naderi Sajad Najafi Ravadanegh Seyyed Hossein Hosseini Smart Distribution Grid Research Lab. Electrical Engineering Department Azarbaijan Shahid Madani University Tabriz Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

An advanced configuration for multilevel voltage source converters is proposed. The proposed converter is able to apply asymmetrical DC sources. The configuration of the proposed inverter is well designed in order to provide the maximum number of voltage levels in output terminals using lower number of circuit devices. The authority of the proposed inverter versus the conventional H-bridge cascaded inverter and the most recently introduced ones, is verified with a provided comparison study. The proposed inverter is able to generate the desired voltage levels using a lower number of circuit devices including power semi-conductor switches, IGBTs, diodes, related gate driver circuits of switches and DC voltage sources. As a result, the total cost and installation area are considerably reduced and the control scheme gets simpler. To confirm the feasibility of the proposed multilevel structure, both the simulation and experimental results are provided and compared which shows good agreements.

关键词： multilevel voltage source inverter reduction of circuit components symmetric inverter asymmetric inverter

用于糖尿病培训的大型语言模型:一项前瞻性研究（英文）

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Science Bulletin 2025年第6期 934-942页

作者：李灏萱江泽铧管洲榆包玉倩刘月星胡婷婷李佳佳刘茹涵吴量程棣纪宏伟王勇王亚星 Carol Y.Cheung 郑颖丰王继红李震吴卫兵 Cynthia Ciwei Lim Yong Mong Bee Hong Chang Tan Elif I.Ekinci David C.Klonoff Justin B.Echouffo-Tcheugui Nestoras Mathioudakis Leonor Corsino Rafael Simó Charumathi Sabanayagam Gavin Siew Wei Tan 程景煜黄天荫李华婷蔡淳毛丽娟 Lee-Ling Lim 覃宇宗盛斌贾伟平 Shanghai University of Sport School of Clinical Medicine Beijing Tsinghua Changgung Hospital Tsinghua Medicine Tsinghua University Beijing Visual Science and Translational Eye Research Institute(BERI) Tsinghua Medicine Tsinghua University Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Center for Diabetes MoE Key Lab of Artificial Intelligence Artificial Intelligence Institute Shanghai Jiao Tong University Department of Cardiology the Affiliated Hospital of Qingdao University CEMS NCMIS HCMS MADIS Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematics University of Chinese Academy of Sciences Chinese Academy of Sciences Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Beijing Institute of Ophthalmology Beijing Tongren Hospital Capital Medical University Beijing Ophthalmology and Visual Sciences Key Laboratory Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangdong Provincial Clinical Research Center for Ocular Diseases Department of Renal Medicine Singapore General Hospital Sing Health-Duke Academic Medical Centre Department of Endocrinology Singapore General Hospital Department of Endocrinology Austin Health Department of Medicine The University of Melbourne(Austin Health) Australian Centre for Accelerating Diabetes Innovations(ACADI) The Univ

Diabetes poses a considerable global health challenge, with varying levels of diabetes knowledge among healthcare professionals, highlighting the importance of diabetes training. Large Language Models(LLMs)provide new insights into diabetes training, but their performance in diabetes-related queries remains uncertain, especially outside the English language like Chinese. We first evaluated the performance of ten LLMs: Chat GPT-3.5, Chat GPT-4.0, Google Bard, Lla MA-7B, Lla MA2-7B, Baidu ERNIE Bot, Ali Tongyi Qianwen, Med GPT, Huatuo GPT, and Chinese Lla MA2-7B on diabetes-related queries, based on the Chinese National Certificate Examination for Primary Diabetes Care in China(NCE-CPDC) and the English Specialty Certificate Examination in Endocrinology and Diabetes of Membership of the Royal College of Physicians of the United Kingdom. Second, we assessed the training of primary care physicians(PCPs) without and with the assistance of Chat GPT-4.0 in the NCE-CPDC examination to ascertain the reliability of LLMs as medical assistants. We found that Chat GPT-4.0 outperformed other LLMs in the English examination, achieving a passing accuracy of 62.50%, which was significantly higher than that of Google Bard, Lla MA-7B, and Lla MA2-7B. For the NCE-CPFC examination, Chat GPT-4.0, Ali Tongyi Qianwen, Baidu ERNIE Bot, Google Bard, Med GPT, and Chat GPT-3.5 successfully passed, whereas Lla MA2-7B, Huatuo GPT,Chinese LLa MA2-7B, and Lla MA-7B failed. Chat GPT-4.0(84.82%) surpassed all PCPs and assisted most PCPs in the NCE-CPDC examination(improving by 1%–6.13%). In summary, LLMs demonstrated outstanding competence for diabetes-related questions in both the Chinese and English language, and hold great potential to assist future diabetes training for physicians globally.

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A split-and-recombine approach for follow-up query analysis

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arXiv 2019年

作者： Liu, Qian Chen, Bei Liu, Haoyan Lou, Jian-Guang Fang, Lei Zhou, Bin Zhang, Dongmei State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China State Key Lab of Software Development Environment Beihang University China Microsoft Research Beijing China

Context-dependent semantic parsing has proven to be an important yet challenging task. To leverage the advances in context-independent semantic parsing, we propose to perform follow-up query analysis, aiming to restate context-dependent natural language queries with contextual information. To accomplish the task, we propose STAR, a novel approach with a well-designed two-phase process. It is parser-independent and able to handle multifarious follow-up scenarios in different domains. Experiments on the FollowUp dataset show that STAR outperforms the state-of-the-art baseline by a large margin of nearly 8%. The superiority on parsing results verifies the feasibility of follow-up query analysis. We also explore the extensibility of STAR on the SQA dataset, which is very promising. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

Multimodal, Multiuser Immersive Brainstorming and Scenario Planning for Intelligence Analysis

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Multimodal, Multiuser Immersive Brainstorming and Scenario P...

2019 IEEE International Symposium on Technologies for Homeland Security, HST 2019

作者： Briggs, Shannon Perrone, Michael Peveler, Matthew Drozdal, Jaimie Balagyozyan, Lilit Su, Hui Communications and Rhetoric Rensselaer Polytechnic Institute TroyNY United States IBM Thomas J. Watson Research Laboratory IBM Yorktown HeightsNY United States Computer Science Rensselaer Polytechnic Institute TroyNY United States Cognitive Immersive Systems Lab Rensselaer Polytechnic Institute TroyNY United States Mechanical Engineering Rensselaer Polytechnic Institute TroyNY United States

ISBN: (纸本)9781728150925

This paper discusses two pieces of software designed for intelligence analysis, the brainstorming tool and the Scenario Planning Advisor. These tools were developed in the Cognitive Immersive systems lab (CISL) in conjunction with IBM. We discuss the immersive environment the tools are situated in, and the proposed benefit for intelligence analysis. © 2019 IEEE.

关键词： Risk assessment

Democratising Knowledge Representation with BioCypher

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arXiv 2022年

作者： Lobentanzer, Sebastian Aloy, Patrick Baumbach, Jan Bohar, Balazs Charoentong, Pornpimol Danhauser, Katharina Doğan, Tunca Dreo, Johann Dunham, Ian Fernandez-Torras, Adrià Gyori, Benjamin M. Hartung, Michael Hoyt, Charles Tapley Klein, Christoph Korcsmaros, Tamas Maier, Andreas Mann, Matthias Ochoa, David Pareja-Lorente, Elena Popp, Ferdinand Preusse, Martin Probul, Niklas Schwikowski, Benno Sen, Bünyamin Strauss, Maximilian T. Turei, Denes Ulusoy, Erva Heidrun Wodke, Judith Andrea Saez-Rodriguez, Julio Heidelberg University Faculty of Medicine Heidelberg University Hospital Institute for Computational Biomedicine Bioquant Heidelberg Germany The Barcelona Institute of Science and Technology Catalonia Barcelona Spain Catalonia Barcelona Spain Institute for Computational Systems Biology University of Hamburg Germany Earlham Institute Norwich United Kingdom Biological Research Centre Szeged Hungary Heidelberg University Im Neuenheimer Feld 267 Heidelberg69120 Germany Im Neuenheimer Feld 460 Heidelberg69120 Germany Department of Pediatrics Dr. von Hauner Children’s Hospital University Hospital LMU Munich Germany Biological Data Science Lab Department of Computer Engineering Hacettepe University Ankara Turkey Department of Bioinformatics Graduate School of Health Sciences Hacettepe University Ankara Turkey Computational Systems Biomedicine Lab Department of Computational Biology Institut Pasteur Université Paris Cité Paris France Bioinformatics and Biostatistics Hub Institut Pasteur Université Paris Cité Paris France Wellcome Genome Campus Cambridgeshire HinxtonCB10 1SD United Kingdom Open Targets Wellcome Genome Campus Cambridgeshire HinxtonCB10 1SD United Kingdom Laboratory of Systems Pharmacology Harvard Medical School Boston United States Imperial College London London United Kingdom Quadram Institute Bioscience Norwich United Kingdom Proteomics Program Novo Nordisk Foundation Centre for Protein Research University of Copenhagen Copenhagen Denmark Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany Im Neuenheimer Feld 460 Heidelberg69120 Germany Neuherberg Germany Medical Informatics Laboratory University Medicine Greifswald Germany

Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate harmonisation and interoperability despite this fundamental challenge, we propose to standardise the framework of knowledge graph creation instead. We implement this standardisation in BioCypher, a FAIR (findable, accessible, interoperable, reusable) framework to transparently build biomedical knowledge graphs while preserving provenances of the source data. Mapping the knowledge onto biomedical ontologies helps to balance the needs for harmonisation, human and machine readability, and ease of use and accessibility to nonspecialist researchers. We demonstrate the usefulness of this framework on a variety of use cases, from maintenance of task-specific knowledge stores, to interoperability between biomedical domains, to on-demand building of task-specific knowledge graphs for federated learning. BioCypher (https://***) frees up valuable developer time;we encourage further development and usage by the community. © 2022, CC BY-NC-ND.

关键词： Ontology

Priority-Based Optimization of I/O Isolation for Hybrid Deployed Services 15th

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Priority-Based Optimization of I/O Isolation for Hybrid Depl...

15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Zhang, Jiancheng Li, Youhuizi Zhou, Li Ren, Zujie Wan, Jian Wang, Yuan Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Zhejiang Lab Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Key Enterprise Research Institute of NetEase Big Data of Zhejiang Province Netease Hangzhou Network Co.Ltd Hangzhou China

ISBN: (纸本)9783030301453

With the increasing of software complexity and user demands, collaborative service is becoming more and more popular. Each service focuses on its own specialty, their cooperation can support complicated task with high efficiency. To improve the resources utilization, virtualization technology like container is used and it enables multiple services running in the same physical machine. However, since the host physical machine is shared by several services, the resource competition is inevitable. Isolation is an effective solution, but the weak isolation mechanisms of container cannot handle such complicated scenarios. In the worst situation, the performance of services cannot meet the requirements and the system may crash. In order to solve this problem, we propose a priority-based optimization mechanism for I/O isolation after analyzing the characteristics of typical service workloads. Based on the real-time performance data, priority is automatically assigned to each service and corresponding optimization methods are applied. We evaluate the optimization effects of the priority-based mechanism in both static and dynamic workload cases, besides, the influence of different priority order is also analyzed. The experimental results show that our approach can indeed improve the system performance and guarantee the requirements of all the running services are satisfied. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Containers