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  • Open Access

    ARTICLE

    Enhancing IoT Security: Quantum-Level Resilience against Threats

    Hosam Alhakami*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 329-356, 2024, DOI:10.32604/cmc.2023.043439 - 30 January 2024

    Abstract The rapid growth of the Internet of Things (IoT) operations has necessitated the incorporation of quantum computing technologies to meet its expanding needs. This integration is motivated by the need to solve the specific issues provided by the expansion of IoT and the potential benefits that quantum computing can offer in this scenario. The combination of IoT and quantum computing creates new privacy and security problems. This study examines the critical need to prevent potential security concerns from quantum computing in IoT applications. We investigate the incorporation of quantum computing approaches within IoT security frameworks,… More >

  • Open Access

    ARTICLE

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

    Nadeem Salamat1, Muhammad Kamran1,2,*, Shahzaib Ashraf1, Manal Elzain Mohammed Abdulla3, Rashad Ismail3, Mohammed M. Al-Shamiri3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1893-1933, 2024, DOI:10.32604/cmes.2023.044697 - 29 January 2024

    Abstract The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy, accessibility, and cost-effectiveness. This paper investigates the potential applications of intuitionistic fuzzy sets (IFS) with rough sets in the context of sparse data. When it comes to capture uncertain information emanating from both upper and lower approximations, these intuitionistic fuzzy rough numbers (IFRNs) are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets, respectively. We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their… More > Graphic Abstract

    Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

  • Open Access

    ARTICLE

    Stroke Risk Assessment Decision-Making Using a Machine Learning Model: Logistic-AdaBoost

    Congjun Rao1, Mengxi Li1, Tingting Huang2,*, Feiyu Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898 - 30 December 2023

    Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline… More >

  • Open Access

    ARTICLE

    A Novel Method for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

    Salma Khan1, Muhammad Gulistan1, Nasreen Kausar2, Seifedine Kadry3,4,5, Jungeun Kim6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1951-1979, 2024, DOI:10.32604/cmes.2023.030896 - 17 November 2023

    Abstract Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons, including leisure, pleasure, or business. A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set (ROFHS) to enhance the formal representation of human thought processes and evaluate tourism carrying capacity. This approach can capture the imprecision and ambiguity often present in human perception. With the advanced mathematical tools in this field, the study has also incorporated the Einstein aggregation operator and score function into the ROFHS values to support multi-attribute More >

  • Open Access

    ARTICLE

    The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

    Huzaira Razzaque1, Shahzaib Ashraf1,*, Muhammad Naeem2, Yu-Ming Chu3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1925-1950, 2024, DOI:10.32604/cmes.2023.030030 - 17 November 2023

    Abstract Spherical q-linear Diophantine fuzzy sets (Sq-LDFSs) proved more effective for handling uncertainty and vagueness in multi-criteria decision-making (MADM). It does not only cover the data in two variable parameters but is also beneficial for three parametric data. By Pythagorean fuzzy sets, the difference is calculated only between two parameters (membership and non-membership). According to human thoughts, fuzzy data can be found in three parameters (membership uncertainty, and non-membership). So, to make a compromise decision, comparing Sq-LDFSs is essential. Existing measures of different fuzzy sets do, however, can have several flaws that can lead to counterintuitive… More >

  • Open Access

    ARTICLE

    An Adaptive Hybrid Optimization Strategy for Resource Allocation in Network Function Virtualization

    Chumei Wen1, Delu Zeng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1617-1636, 2024, DOI:10.32604/cmes.2023.029864 - 17 November 2023

    Abstract With the rapid development of Network Function Virtualization (NFV), the problem of low resource utilization in traditional data centers is gradually being addressed. However, existing research does not optimize both local and global allocation of resources in data centers. Hence, we propose an adaptive hybrid optimization strategy that combines dynamic programming and neural networks to improve resource utilization and service quality in data centers. Our approach encompasses a service function chain simulation generator, a parallel architecture service system, a dynamic programming strategy for maximizing the utilization of local server resources, a neural network for predicting More >

  • Open Access

    ARTICLE

    Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

    Cheng Wang1, Haoran Zhu2,*, Congjun Rao2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 691-718, 2024, DOI:10.32604/cmes.2023.029258 - 22 September 2023

    Abstract Cardiovascular disease (CVD) has gradually become one of the main causes of harm to the life and health of residents. Exploring the influencing factors and risk assessment methods of CVD has become a general trend. In this paper, a machine learning-based decision-making mechanism for risk assessment of CVD is designed. In this mechanism, the logistics regression analysis method and factor analysis model are used to select age, obesity degree, blood pressure, blood fat, blood sugar, smoking status, drinking status, and exercise status as the main pathogenic factors of CVD, and an index system of risk More >

  • Open Access

    ARTICLE

    Effects of Emotion on Decision-Making of Methamphetamine Users: Based on the Emotional Iowa Gambling Task

    Xiaoqing Zeng1,2,3,*, Song Tu1,2,3, Ting Liu4

    International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1229-1236, 2023, DOI:10.32604/ijmhp.2023.029903 - 08 December 2023

    Abstract The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate the impact of different emotions on the decision-making behavior of meth users. We used 2 (gender: male, female) × 3 (emotion: positive, negative, neutral) × 5 (block: 1, 2, 3, 4, 5) mixed experiment design. The study involved 168 meth users who were divided into three groups: positive emotion, negative emotion and neutral emotion group, and tested by the emotional Iowa Gambling Task (IGT). The IGT performance of male users exhibited a decreasing trend from Block 1 to Block More > Graphic Abstract

    Effects of Emotion on Decision-Making of Methamphetamine Users: Based on the Emotional Iowa Gambling Task

  • Open Access

    ARTICLE

    Evaluating the Derivative Value of Smart Grid Investment under Dual Carbon Target: A Hybrid Multi-Criteria Decision-Making Analysis

    Na Yu1, Changzheng Gao2, Xiuna Wang2, Dongwei Li2,*, Weiyang You2

    Energy Engineering, Vol.120, No.12, pp. 2879-2901, 2023, DOI:10.32604/ee.2023.029426 - 29 November 2023

    Abstract With the goal of “carbon peaking and carbon neutralization”, it is an inevitable trend for investing smart grid to promote the large-scale grid connection of renewable energy. Smart grid investment has a significant driving effect (derivative value), and evaluating this value can help to more accurately grasp the external effects of smart grid investment and support the realization of industrial linkage value with power grid investment as the core. Therefore, by analyzing the characterization of the derivative value of smart grid driven by investment, this paper constructs the evaluation index system of the derivative value… More >

  • Open Access

    ARTICLE

    Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

    Wenshu Xu, Mingwei Lin*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 199-222, 2023, DOI:10.32604/cmc.2023.041475 - 31 October 2023

    Abstract Industrial control systems (ICSs) are widely used in various fields, and the information security problems of ICSs are increasingly serious. The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts. Thus, this paper introduces the probabilistic linguistic term sets (PLTSs) to model the evaluation information of experts. Meanwhile, we propose a probabilistic linguistic multi-criteria decision-making (PL-MCDM) method to solve the information security assessment problem of ICSs. Firstly, we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods. Secondly, we use the Best Worst… More >

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