Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (302)
  • Open Access

    ARTICLE

    Testing the internal factor reliability of an Organisational Citizenship Behaviour (OCB) measure for a South African higher education setting

    Mariette Coetzee*, Linda Naidoo

    Journal of Psychology in Africa, Vol.35, No.5, pp. 627-634, 2025, DOI:10.32604/jpa.2025.065791 - 24 October 2025

    Abstract This study developed and tested the internal reliability of a 27-item Organisational Citizenship Behaviour (OCB) scale for higher education institutions. Participants were a probability sample of 452 (N = 452) university staff of a South African open-distance higher education institution (academics 46%, administrative staff 33%, professional and managerial staff 21%). The participants completed the Organisational Citizenship Behaviour questionnaire. Exploratory factor analysis identified a four-construct measurement model for organisational citizenship behaviour: altruism, civic virtue, sportsmanship, and sense of duty and consideration. The sense of duty and consideration is the only factor not previously identified as a factor More >

  • Open Access

    ARTICLE

    miR-122-5p Regulates Ferroptosis through Targeting the Glutamine Transporter SLC1A5 in Hepatocellular Carcinoma

    Mingxuan Lei1, Jiayin Xu2, Xiaoying Hu2, Lin Feng3, Baoping Luo4,5,6,*

    BIOCELL, Vol.49, No.10, pp. 1947-1965, 2025, DOI:10.32604/biocell.2025.068926 - 22 October 2025

    Abstract Background: Hepatocellular carcinoma (HCC) typically begins inconspicuously and progresses swiftly, leading to most patients being diagnosed at an advanced stage. Accordingly, a pressing priority is to clarify the development mechanisms of HCC and devise efficient intervention and treatment protocols. Methods: An upstream miRNA of solute carrier transporter family 1 member 5 (SLC1A5) was predicted to be miR-122-5p by various databases, and a dual-luciferase reporter gene assay was used to verify the SLC1A5- and miR-122-5p-targeting relationship. SLC1A5 and miR-122-5p expression in HCC cells was quantitatively assessed using quantitative reverse transcription polymerase chain reaction (qRT–PCR). Western blotting… More >

  • Open Access

    ARTICLE

    Protecting the Mental Health of Esports Players: A Qualitative Case Study on Their Stress, Coping Strategies, and Social Support Systems

    Young-Vin Kim1, Hyunkyun Ahn2,*

    International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1301-1334, 2025, DOI:10.32604/ijmhp.2025.068251 - 30 September 2025

    Abstract Objectives: Recently, the global esports industry has experienced remarkable growth, leading to an expansion in the scale and influence of professional player communities. However, despite this outward growth, systems to protect players’ mental health remain inadequate. Comprehensive analysis of structural risk factors, including performance pressure, public evaluation, and career instability, remains insufficient. This study, aimed to explore stressors encountered by esports athletes, coping strategies, and the role of social support systems in safeguarding mental health. Using the transactional model of stress and coping, the job demands–resources model, and social support theory, the study adopts an… More >

  • Open Access

    ARTICLE

    Urban Transportation Strategy Selection for Multi-Criteria Group Decision-Making Using Pythagorean Fuzzy N-Bipolar Soft Expert Sets

    Sagvan Y. Musa1,2, Zanyar A. Ameen3,*, Wafa Alagal4, Baravan A. Asaad5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3493-3529, 2025, DOI:10.32604/cmes.2025.070019 - 30 September 2025

    Abstract Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility, cost-effectiveness, and environmental impact, often under uncertainty and incomplete information. These complex decisions require input from various stakeholders, including planners, policymakers, engineers, and community representatives, whose opinions may differ or contradict. Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations. To address these challenges, we propose a novel decision-making framework based on Pythagorean fuzzy N-bipolar soft expert sets. This model allows experts to express both positive and negative opinions on a multinary scale, capturing nuanced judgments with higher accuracy. It… More >

  • Open Access

    PROCEEDINGS

    Techno-Economic Analysis of Offshore Hydrogen Energy Storage and Transportation Based on Levelized Cost

    Ziming Hu1, Jingfa Li1,*, Chaoyang Fan1, Jiale Xiao1, Huijie Huang2, Bo Yu1, Baocheng Shi1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010823

    Abstract Hydrogen production from offshore wind power is an effective means to address the challenges of wind power grid integration and has emerged as a focal point in the development and research of offshore wind energy in recent years. However, the current state of hydrogen storage and transportation technologies for offshore applications lacks comprehensive economic analysis. This study aims to provide a thorough economic evaluation of these technologies by considering both fixed investment costs and operational and maintenance costs. A levelized cost model is employed to analyze four offshore hydrogen storage and transportation schemes: gas hydrogen… More >

  • Open Access

    REVIEW

    A Review of Artificial Intelligence-Enhanced Fuzzy Multi-Criteria Decision-Making Approaches for Sustainable Transportation Planning

    Nezir Aydin1,2,*, Melike Cari3, Betul Kara3, Ertugrul Ayyildiz1,3

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2625-2650, 2025, DOI:10.32604/cmc.2025.067290 - 23 September 2025

    Abstract Transportation systems are rapidly transforming in response to urbanization, sustainability challenges, and advances in digital technologies. This review synthesizes the intersection of artificial intelligence (AI), fuzzy logic, and multi-criteria decision-making (MCDM) in transportation research. A comprehensive literature search was conducted in the Scopus database, utilizing carefully selected AI, fuzzy, and MCDM keywords. Studies were rigorously screened according to explicit inclusion and exclusion criteria, resulting in 73 eligible publications spanning 2006–2025. The review protocol included transparent data extraction on methodological approaches, application domains, and geographic distribution. Key findings highlight the prevalence of hybrid fuzzy AHP and… More >

  • Open Access

    ARTICLE

    Identification of Visibility Level for Enhanced Road Safety under Different Visibility Conditions: A Hierarchical Clustering-Based Learning Model

    Asmat Ullah1, Yar Muhammad1,*, Bakht Zada1, Korhan Cengiz2, Nikola Ivković3,*, Mario Konecki3, Abid Yahya4

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3767-3786, 2025, DOI:10.32604/cmc.2025.067145 - 23 September 2025

    Abstract Low visibility conditions, particularly those caused by fog, significantly affect road safety and reduce drivers’ ability to see ahead clearly. The conventional approaches used to address this problem primarily rely on instrument-based and fixed-threshold-based theoretical frameworks, which face challenges in adaptability and demonstrate lower performance under varying environmental conditions. To overcome these challenges, we propose a real-time visibility estimation model that leverages roadside CCTV cameras to monitor and identify visibility levels under different weather conditions. The proposed method begins by identifying specific regions of interest (ROI) in the CCTV images and focuses on extracting specific… More >

  • Open Access

    ARTICLE

    An Adaptive Hybrid Metaheuristic for Solving the Vehicle Routing Problem with Time Windows under Uncertainty

    Manuel J. C. S. Reis*

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3023-3039, 2025, DOI:10.32604/cmc.2025.066390 - 23 September 2025

    Abstract The Vehicle Routing Problem with Time Windows (VRPTW) presents a significant challenge in combinatorial optimization, especially under real-world uncertainties such as variable travel times, service durations, and dynamic customer demands. These uncertainties make traditional deterministic models inadequate, often leading to suboptimal or infeasible solutions. To address these challenges, this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms (GA) with Local Search (LS), while incorporating stochastic uncertainty modeling through probabilistic travel times. The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance. This adaptivity enhances the algorithm’s… More >

  • Open Access

    ARTICLE

    SDN-Enabled IoT Based Transport Layer DDoS Attacks Detection Using RNNs

    Mohammad Nowsin Amin Sheikh1,2,*, Muhammad Saibtain Raza1, I-Shyan Hwang1,*, Md. Alamgir Hossain3, Ihsan Ullah1, Tahmid Hasan4, Mohammad Syuhaimi Ab-Rahman5

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 4043-4066, 2025, DOI:10.32604/cmc.2025.065850 - 23 September 2025

    Abstract The rapid advancement of the Internet of Things (IoT) has heightened the importance of security, with a notable increase in Distributed Denial-of-Service (DDoS) attacks targeting IoT devices. Network security specialists face the challenge of producing systems to identify and offset these attacks. This research manages IoT security through the emerging Software-Defined Networking (SDN) standard by developing a unified framework (RNN-RYU). We thoroughly assess multiple deep learning frameworks, including Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Feed-Forward Convolutional Neural Network (FFCNN), and Recurrent Neural Network (RNN), and present the novel usage of Synthetic Minority Over-Sampling More >

  • Open Access

    ARTICLE

    A Novel Reduced Error Pruning Tree Forest with Time-Based Missing Data Imputation (REPTF-TMDI) for Traffic Flow Prediction

    Yunus Dogan1, Goksu Tuysuzoglu1, Elife Ozturk Kiyak2, Bita Ghasemkhani3, Kokten Ulas Birant1,4, Semih Utku1, Derya Birant1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1677-1715, 2025, DOI:10.32604/cmes.2025.069255 - 31 August 2025

    Abstract Accurate traffic flow prediction (TFP) is vital for efficient and sustainable transportation management and the development of intelligent traffic systems. However, missing data in real-world traffic datasets poses a significant challenge to maintaining prediction precision. This study introduces REPTF-TMDI, a novel method that combines a Reduced Error Pruning Tree Forest (REPTree Forest) with a newly proposed Time-based Missing Data Imputation (TMDI) approach. The REPTree Forest, an ensemble learning approach, is tailored for time-related traffic data to enhance predictive accuracy and support the evolution of sustainable urban mobility solutions. Meanwhile, the TMDI approach exploits temporal patterns… More >

Displaying 21-30 on page 3 of 302. Per Page