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  • Open Access

    ARTICLE

    Novel Decision Making Methodology under Pythagorean Probabilistic Hesitant Fuzzy Einstein Aggregation Information

    Shahzaib Ashraf1, Bushra Batool2, Muhammad Naeem3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1785-1811, 2023, DOI:10.32604/cmes.2023.024851 - 06 February 2023

    Abstract This research proposes multicriteria decision-making (MCDM)-based real-time Mesenchymal stem cells (MSC) transfusion framework. The testing phase of the methodology denotes the ability to stick to plastic surfaces, the upregulation and downregulation of certain surface protein markers, and lastly, the ability to differentiate into various cell types. First, two scenarios of an enhanced dataset based on a medical perspective were created in the development phase to produce varying levels of emergency. Second, for real-time monitoring of COVID-19 patients with different emergency levels (i.e., mild, moderate, severe, and critical), an automated triage algorithm based on a formal… More >

  • Open Access

    ARTICLE

    A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

    Runze Liu, Liguo Fei*, Jianing Mi

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 2039-2067, 2023, DOI:10.32604/cmes.2023.024927 - 06 February 2023

    Abstract Probabilistic linguistic term sets (PLTSs) are an effective tool for expressing subjective human cognition that offer advantages in the field of multi-attribute decision-making (MADM). However, studies have found that PLTSs have lost their ability to accurately capture the views of decision-makers (DMs) in certain circumstances, such as when the DM hesitates between multiple linguistic terms or the decision information is incomplete, thus affecting their role in the decision-making process. Belief function theory is a leading stream of thought in uncertainty processing that is suitable for dealing with the limitations of PLTS. Therefore, the purpose of… More > Graphic Abstract

    A Multi-Attribute Decision-Making Method Using Belief-Based Probabilistic Linguistic Term Sets and Its Application in Emergency Decision-Making

  • Open Access

    ARTICLE

    The Correlation Coefficient of Hesitancy Fuzzy Graphs in Decision Making

    N. Rajagopal Reddy, S. Sharief Basha*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 579-596, 2023, DOI:10.32604/csse.2023.034527 - 20 January 2023

    Abstract The hesitancy fuzzy graphs (HFGs), an extension of fuzzy graphs, are useful tools for dealing with ambiguity and uncertainty in issues involving decision-making (DM). This research implements a correlation coefficient measure (CCM) to assess the strength of the association between HFGs in this article since CCMs have a high capacity to process and interpret data. The CCM that is proposed between the HFGs has better qualities than the existing ones. It lowers restrictions on the hesitant fuzzy elements’ length and may be used to establish whether the HFGs are connected negatively or favorably. Additionally, a… More >

  • Open Access

    ARTICLE

    Non-Cooperative Behavior Management in Large-Scale Group Decision-Making Considering the Altruistic Behaviors of Experts and Its Application in Emergency Alternative Selection

    Mingjun Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 487-515, 2023, DOI:10.32604/cmes.2023.024014 - 05 January 2023

    Abstract Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns, leading to non-cooperative behaviors during the consensus-reaching process. Many studies on non-cooperative behavior management assumed that the maximum degree of cooperation of experts is to totally accept the revisions suggested by the moderator, which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process. In addition, when grouping a large group into subgroups by clustering methods, existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously. In… More >

  • Open Access

    ARTICLE

    Women Entrepreneurship Index Prediction Model with Automated Statistical Analysis

    V. Saikumari*, V. Sunitha

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1797-1810, 2023, DOI:10.32604/iasc.2023.034038 - 05 January 2023

    Abstract Recently, gender equality and women’s entrepreneurship have gained considerable attention in global economic development. Prior to the design of any policy interventions to increase women’s entrepreneurship, it is significant to comprehend the factors motivating women to become entrepreneurs. The non-understanding of the factors can result in the endurance of low living standards and the design of expensive and ineffectual policies. But female involvement in entrepreneurship becomes higher in developing economies compared to developed economies. Women Entrepreneurship Index (WEI) plays a vital role in determining the factors that enable the flourishment of high potential female entrepreneurs… More >

  • Open Access

    ARTICLE

    Classification of Nonlinear Confusion Component Using Hybrid Multi-Criteria Decision Making

    Nabilah Abughazalah1, Iqra Ishaque2, Majid Khan2,*, Ammar S. Alanazi3, Iqtadar Hussain4,5

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1451-1463, 2023, DOI:10.32604/iasc.2023.031855 - 05 January 2023

    Abstract In today’s digital world, the most inevitable challenge is the protection of digital information. Due to the weak confidentiality preserving techniques, the existing world is facing several digital information breaches. To make our digital data indecipherable to the unauthorized person, a technique for finding a cryptographically strong Substitution box (S-box) have presented. An S-box with sound cryptographic assets such as nonlinearity (NL), strict avalanche criterion (SAC), bit independence criteria (BIC), bit independence criteria of nonlinearity (BIC-NL), Bit independence criteria of Strict avalanche criteria (BIC-SAC), and Input/output XOR is considered as the robust S-box. The Decision-Making… More >

  • Open Access

    ARTICLE

    Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

    Nabilah Abughazalah1, Mohsin Iqbal2, Majid Khan3,*, Iqtadar Hussain4,5

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6523-6534, 2023, DOI:10.32604/cmc.2022.031859 - 28 December 2022

    Abstract The substitution box, often known as an S-box, is a nonlinear component that is a part of several block ciphers. Its purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults. A MultiCriteria Decision Making (MCDM) problem has a complex selection procedure because of having many options and criteria to choose from. Because of this, statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this score. Using the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal… More >

  • Open Access

    ARTICLE

    Impediments of Cognitive System Engineering in Machine-Human Modeling

    Fayaz Ahmad Fayaz1,2, Arun Malik2, Isha Batra2, Akber Abid Gardezi3, Syed Immamul Ansarullah4, Shafiq Ahmad5, Mejdal Alqahtani5, Muhammad Shafiq6,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6689-6701, 2023, DOI:10.32604/cmc.2023.032998 - 28 December 2022

    Abstract A comprehensive understanding of human intelligence is still an ongoing process, i.e., human and information security are not yet perfectly matched. By understanding cognitive processes, designers can design humanized cognitive information systems (CIS). The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information systems. The researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency More >

  • Open Access

    ARTICLE

    A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

    Abdulaziz Alhubaishy1,*, Abdulmajeed Aljuhani2

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2461-2481, 2023, DOI:10.32604/csse.2023.032217 - 21 December 2022

    Abstract In a cloud environment, consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost. On the other hand, Cloud Service Providers (CSPs) seek to maximize their profits by attracting and serving more consumers based on their resource capabilities. The literature has discussed the problem by considering either consumers’ needs or CSPs’ capabilities. A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task… More >

  • Open Access

    ARTICLE

    Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

    Mahmoud Ragab1,2,3,*, Mohammed W. Al-Rabia4,5, Sami Saeed Binyamin6, Ahmed A. Aldarmahi7,8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2889-2903, 2023, DOI:10.32604/cmc.2023.032192 - 31 October 2022

    Abstract With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition… More >

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