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Developing a comprehensive service quality model for online to offline e-commerce platforms using a hybrid model

Electronic Commerce Research 2024年 1-30页

作者： Shao, QiGan Liou, James J. H. Weng, SungShun Jiang, HongBo Shao, Ting Lin, ZhenWen School of Economics and Management Xiamen University of Technology Xiamen China Department of Industrial Engineering and Management National Taipei University of Technology Taipei Taiwan Department of Information and Finance Management National Taipei University of Technology Taipei Taiwan Department of Software Engineering Xiamen Institute of Software Technology Xiamen China

One of the impacts of the COVID pandemic has been to force people to find alternates sources for daily supplies, turning to online to offline (O2O) platforms. The service quality of the O2O platform naturally affects the satisfaction which in turn has an impact on customer retention. The aim of this study is to evaluate the service quality of O2O platform to find strategies to improve consumer satisfaction. This study proposed a hybrid RS-DANP-CoCoSo model, which applies the rough set (RS) method to obtain the factors which influence the service quality of O2O platforms. The Analytic Network Process based on the Decision-making Trial and Evaluation Laboratory method (DANP) is applied to obtain the relationships and weights of the factors. The results indicate that empathy, social interaction and recommendation quality are the three most important factors. The practicability of our evaluation model is verified using the combined compromise solution (CoCoSo) method to evaluate the service quality of four O2O platforms in China. The hybrid model proposed in this study is applied to evaluate and diagnose online consumer satisfaction levels, providing personalized solutions for merchants to improve services. Finally, management implications based on the findings are also discussed. © 2024, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Rough set theory

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Emotional Engagement with Haptic Feedback in Virtual Scenarios: A Literature Review

Emotional Engagement with Haptic Feedback in Virtual Scenari...

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2024 International Conference on engineering and Computing, ICECT 2024

作者： Qaisar, Taimoor Mumtaz, Mamoona Raza, Hamda Ali, Mir Mutabassim Khalid, Kainaat Bajwa, Ibrahim University of Management and Technology Department of Software Engineering Pakistan

ISBN: (纸本)9798350349719

Virtual reality (VR) is a simulated environment that computer technology generates. Haptic feedback uses touch sensations to enhance user interaction within a VR. Exploring emotional engagement in VR has witnessed a surge in interest, particularly concerning the integration of haptic feedback. This study systematically reviews 26 primary studies published from 2013 to 2023. We identify nineteen emotional engagement techniques and support leveraging the impact of emotional engagement in collaboration with haptics. Then, we develop a relationship based on emotional engagement and haptic feedback, emphasizing the significance of sensory integration and haptic elements in augmenting emotional connections in a VR environment. The investigation unveils various techniques, encompassing multi-sensory emotion recognition, immersive VR environments, interactive digital narratives, and haptic feedback strategies. Our findings suggest that the researchers need to explore emotional engagement in multiple virtual environments for synchronous user interaction to advance immersive technologies. © 2024 IEEE.

关键词： Virtual reality

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Evolution Analysis of Network Attack and Defense Situation Based on Game Theory

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Computers, Materials & Continua 2025年第4期83卷 1475-1494页

作者： Haiyan Sun Chenglong Shao Jianwei Zhang Kun Wang Wanwei Huang College of Software Engineering Zhengzhou University of Light IndustryZhengzhou450007China Intelligent Computing Power Research Department Zhengzhou Xinda Advanced Technology Research InstituteZhengzhou450007China

To address the problem that existing studies lack analysis of the relationship between attack-defense game behaviors and situation evolution from the game perspective after constructing an attack-defense model,this paper proposes a network attack-defense game model(ADGM).Firstly,based on the assumption of incomplete information between the two sides of the game,the ADGM model is established,and methods of payoff quantification,equilibrium solution,and determination of strategy confrontation results are ***,drawing on infectious disease dynamics,the network attack-defense situation is defined based on the density of nodes in various security states,and the transition paths of network node security states are ***,the network zero-day virus attack-defense behaviors are analyzed,and comparative experiments on the attack-defense evolution trends under the scenarios of different strategy combinations,interference methods,and initial numbers are conducted using the NetLogo simulation *** experimental results indicate that this model can effectively analyze the evolution of the macro-level network attack-defense situation from the micro-level attack-defense *** instance,in the strategy selection experiment,when the attack success rate decreases from 0.49 to 0.29,the network destruction rate drops by 11.3%,in the active defense experiment,when the interference coefficient is reduced from 1 to 0.7,the network destruction rate decreases by 7%,and in the initial node number experiment,when the number of initially infected nodes increases from 10 to 30,the network destruction rate rises by 3%.

关键词： Network attack-defense situation evolution zero-day virus NetLogo

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Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

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Computers, Materials & Continua 2023年第7期76卷 133-150页

作者： Ali Haider Khan Hassaan Malik Wajeeha Khalil Sayyid Kamran Hussain Tayyaba Anees Muzammil Hussain Department of Software Engineering Faculty of Computer SciencesLahore Garrison UniversityLahorePakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Computer Science&Information Technology University of Engineering and Technology(UET)PeshawarPakistan Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CFI)is a screening technology that is both effective and *** to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic *** traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of *** addition,they usually only target one or a few different kinds of eye diseases at the same *** this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs ***_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification *** DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right *** then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel *** the attributes have been analyzed,they are integrated to provide a representation at the patient *** the whole process of ODs categorization,the patient-level representation will be *** efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

关键词： Ocular disease multi-label spatial correlation CNN eye disease

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Overview of image segmentation methods based on deep learning 3

Overview of image segmentation methods based on deep learnin...

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3rd International Conference on Electronic Information engineering and Data Processing, EIEDP 2024

作者： Wang, Yiwen Department of Software Engineering and Intelligent Technology Tianjin University of Finance and Economics Tianjin300222 China

ISBN: (纸本)9781510680531

Image segmentation is an important branch of computer vision, which has been widely used in many research fields. In order to understand the research status in the field of image segmentation, this paper systematically analyses and compares the traditional image segmentation method and the image segmentation method based on deep learning. Firstly, the development, advantages, and disadvantages of traditional image segmentation methods are summarized according to the three types of segmentation methods based on threshold, edge, and region. Then, the segmentation network models of three commonly used image segmentation methods based on deep learning, namely, fully convolutional neural network, pyramid scene analysis network, and Mask R-CNN, are analyzed. Based on the previous experimental results and the current research progress based on deep learning models, the problems of contour edge optimization and multi-level pixel information fusion in the field of image segmentation are summarized. At the same time, improvement ideas are put forward for the existing problems. Finally, the improvement and development of future image segmentation methods are prospected, which provides a reference for the subsequent research of segmentation methods. © 2024 SPIE.

关键词： Image segmentation

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Secure Consumer-Centric Demand Response management in Resilient Smart Grid as Industry 5.0 Application with Blockchain-Based Authentication

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 1370-1379页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Saleem, Muhammad Asad Omar, Marwan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan Illinois Institute of Technology Information Technology and Management ChicagoIL60616 United States

The development of the industrial Internet of Things and smart grid networks has emphasized the importance of secure smart grid communication for the future of electric power transmission. However, the current deployment of smart meters and wireless communication methods presents several security concerns that must be addressed to ensure sustainable and resilient smart grid networks for Industry 5.0, with a focus on consumer-centric technologies. In this context, we propose a privacy-focused authentication solution for secure consumer-centric demand response management in smart grid networks, incorporating consumer electronics. Our proposed protocol utilizes blockchain-based authentication to enhance resistance against potential attacks and ensure the integrity of demand response data. Additionally, we have incorporated a PUF to prevent physical attacks. We have conducted informal and formal security analyses to verify the effectiveness of our proposed protocol against various threats and to confirm the session key security. Our comparison study has demonstrated that our protocol provides superior security and added functionalities, with lower computation and communication costs compared to similar protocols. Furthermore, we have measured the computational time for implementing the blockchain component of our protocol while considering the impact of varying numbers of block additions and transactions per block. © 1975-2011 IEEE.

关键词： Authentication

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Truck scheduling with fixed outbound departures in a closed-loop conveyor system with shortcuts

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Flexible Services and Manufacturing Journal 2024年第3期36卷 1107-1156页

作者： Chen, James C. Chen, Tzu-Li Wu, Ping-Hsuan Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu30013 Taiwan Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei City106335 Taiwan

With the global trend of e-commerce, companies pursue a higher quality of parcel delivery service since customers expect faster transportation in this fast-paced society. Several of them are committed to improving the efficiency of logistics and reducing operating costs and increasing their market competitiveness in the industry. The parcel distribution center thus plays a critical role in parcel delivery industries to sort and consolidate parcel flows to full truckloads. The benefit of the strategy is significant such as reducing transfer time and related costs. On the other hand, an automated sorting system (ASS) is also highly used in many supply chains with impressive characteristics like fast operation speed, large capacity, high reliability. The goal of this research is to apply the scheduling method to reduce the sorting time in an automated sorting system to improve distribution efficiency. This study focuses on the truck scheduling problem with fixed outbound schedules in a closed-loop conveyor system with shortcuts. The objective is to minimize the costs of extra trucks used to deliver delayed parcels and holding cost of parcels at each shipping dock door. If a parcel fails to be loaded onto the pre-determined outbound trucks, an extra outbound truck will be used to deliver the parcel. The problem is modeled with a mixed integer nonlinear programming model. This problem is proven to be NP-hard in the strong sense. As a result, an adaptive genetic algorithm with local search (LSAGA) is developed to solve the problem under twelve scenarios and compared with other algorithms, and a full factorial design of experiment was conducted. The computational experiments show that four factors, layout, inbound truck, outbound truck, and algorithm are significant to the objective value, and the proposed algorithm can obtain high-quality solutions with more stability. A sensitivity analysis is also conducted and bring some managerial insights. © The Author(s), under excl

关键词： Trucks

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Minimising makespan in distributed assembly hybrid flowshop scheduling problems

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International Journal of Production Research 2025年第5期63卷 1674-1691页

作者： Ying, Kuo-Ching Lin, Shih-Wei Chen, Kuan-Fu Department of Industrial Engineering and Management National Taipei University of Technology Taipei Taiwan Department of Information Management Chang Gung University Taoyuan Taiwan Department of Emergency Medicine Keelung Chang Gung Memorial Hospital Keelung Taiwan Department of Industrial Engineering and Management Ming Chi University of Technology Taipei Taiwan College of Intelligent Computing Chang Gung University Taoyuan Taiwan

To enhance the manufacturing flexibility, resilience, and production efficiency, the integration of scheduling for distributed manufacturing with assembly systems has become a pivotal driver of production planning evolution. In this research endeavour, we present a Mixed-Integer Linear Programming model and an innovative Iterated Epsilon-Greedy Reinforcement Learning algorithm to address the distributed assembly hybrid flowshop scheduling problem. Empirical validation, conducted through computational experiments on a benchmark problem set, is used to gain important managerial insights. The computational results demonstrate that the proposed algorithms significantly reduce the makespan for the addressed problem. This study has the potential to make valuable contributions to ongoing research endeavours within the realm of multi-stage shop scheduling, an area that continues to warrant progressive advancement. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Learning algorithms

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Multi-user reinforcement learning based task migration in mobile edge computing

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Frontiers of Computer Science 2024年第4期18卷 161-173页

作者： Yuya CUI Degan ZHANG Jie ZHANG Ting ZHANG Lixiang CAO Lu CHEN Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of TechnologyTianjin 300384China School of Internet of Things Engineering Jiangsu Vocational College of Information TechnologyWuxi 214153China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Sports Economics and Management Tianjin University of SportTianjin 301617China

Mobile Edge Computing(MEC)is a promising *** service migration is a key technology in *** order to maintain the continuity of services in a dynamic environment,mobile users need to migrate tasks between multiple servers in real *** to the uncertainty of movement,frequent migration will increase delays and costs and non-migration will lead to service ***,it is very challenging to design an optimal migration *** this paper,we investigate the multi-user task migration problem in a dynamic environment and minimizes the average service delay while meeting the migration *** order to optimize the service delay and migration cost,we propose an adaptive weight deep deterministic policy gradient(AWDDPG)*** distributed execution and centralized training are adopted to solve the high-dimensional *** show that the proposed algorithm can greatly reduce the migration cost and service delay compared with the other related algorithms.

关键词： mobile edge computing mobility service migration deep reinforcement learning deep deterministic policy gradient

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Current research and future challenges in parcel hub towards logistics 4.0: a systematic literature review from a decision-making perspective

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International Journal of Production Research 2024年第23期62卷 8562-8593页

作者： Chen, James C. Anggrahini, Dewanti Chen, Tzu-Li Department of Industrial Engineering and Engineering Management National Tsing Hua University Hsinchu Taiwan Department of Industrial and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Graduate Institute of Intelligent Manufacturing Technology National Taiwan University of Science and Technology Taipei Taiwan

Parcel hub (PH), as one of the logistic system entities, plays a significant role in delivering packages. PH operations are identical to a cross-docking system. Numerous studies were conducted to examine solutions in PH and cross-docking in general. This paper aims to investigate scientific references published within the last fifteen years through a systematic literature review (SLR). The objectives are to determine the critical decisions related to PH problems, classify the applied solution approach, and identify the future challenges regarding the transformation towards intelligent logistics. This study implements an SLR methodology that consists of five stages: planning, searching, screening, analysing, and reporting. This study utilises two publication databases and one reference management system. More than four thousand documents were collected in the searching stage. Then, five assessments are conducted to sort the most relevant papers. One hundred and forty-six articles are included in the further analysis. This study classifies four important decisions associated with PH problems: truck scheduling, internal process planning, facility planning, and technology selection. In addition, this study categorises ten solution approaches employed to find the best decision in the prior research. Moreover, this study explains the future research directions and managerial implications of managing parcel hub systems. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Decision making

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