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  • Open Access

    ARTICLE

    Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

    Wenxiang Dong, H. Vicky Zhao*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 139-170, 2024, DOI:10.32604/cmes.2024.047156 - 16 April 2024

    Abstract Understanding and modeling individuals’ behaviors during epidemics is crucial for effective epidemic control. However, existing research ignores the impact of users’ irrationality on decision-making in the epidemic. Meanwhile, existing disease control methods often assume users’ full compliance with measures like mandatory isolation, which does not align with the actual situation. To address these issues, this paper proposes a prospect theory-based framework to model users’ decision-making process in epidemics and analyzes how irrationality affects individuals’ behaviors and epidemic dynamics. According to the analysis results, irrationality tends to prompt conservative behaviors when the infection risk is low More >

  • Open Access

    ARTICLE

    Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

    Heesup Han1, Hong Ngoc Nguyen2, Hyerin Lee3, Sanghyeop Lee4,*

    International Journal of Mental Health Promotion, Vol.25, No.4, pp. 449-469, 2023, DOI:10.32604/ijmhp.2023.025379 - 01 March 2023

    Abstract Since the outbreak of COVID-19, tourists have been increasingly concerned over various risks of international travel, while knowledge of the pandemic appears to vary significantly. In addition, as travel restrictions continue to impact adversely on international tourism, tourism efforts should be placed more on the domestic markets. Via structural equation modeling, this study unearthed different risk factors impacting Korean travelers’ choices of alternative local destinations in the post-pandemic era. In addition, this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19, which was proven to hold a significantly More >

  • Open Access

    ARTICLE

    Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

    K. Abhirami1,*, M. K. Kavitha Devi2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1127-1144, 2022, DOI:10.32604/csse.2022.020013 - 24 September 2021

    Abstract With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The… More >

  • Open Access

    ARTICLE

    A Novel Cardholder Behavior Model for Detecting Credit Card Fraud

    Yiğit Kültür, Mehmet Ufuk Çağlayan

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 807-817, 2018, DOI:10.1080/10798587.2017.1342415

    Abstract Because credit card fraud costs the banking sector billions of dollars every year, decreasing the losses incurred from credit card fraud is an important driver for the sector and end-users. In this paper, we focus on analyzing cardholder spending behavior and propose a novel cardholder behavior model for detecting credit card fraud. The model is called the Cardholder Behavior Model (CBM). Two focus points are proposed and evaluated for CBMs. The first focus point is building the behavior model using single-card transactions versus multi-card transactions. As the second focus point, we introduce holiday seasons as More >

  • Open Access

    ARTICLE

    Multi-agent Based Traffic Simulation at Merging Section Using Coordinative Behavior Model

    Hideki Fujii1, Shinobu Yoshimura1, Kazuya Seki1

    CMES-Computer Modeling in Engineering & Sciences, Vol.63, No.3, pp. 265-282, 2010, DOI:10.3970/cmes.2010.063.265

    Abstract Traffic system is a typical complex system emerged through interactions among a large number of traffic actors such as car drivers, pedestrians and others. We model each actor as an intelligent agent that can judge and act by itself autonomously, and develop a traffic simulator named MATES, which is based on an intelligent multi-agent model. In this simulator, microscopic behaviors of the traffic actors cause macroscopic traffic phenomena through their interaction. In this research, we newly develop a coordinative behavior model among multiple cars, and implement it to MATES to enhance the reproducibility of traffic More >

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