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  • Open Access

    REVIEW

    A Survey of Spark Scheduling Strategy Optimization Techniques and Development Trends

    Chuan Li, Xuanlin Wen*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3843-3875, 2025, DOI:10.32604/cmc.2025.063047 - 19 May 2025

    Abstract Spark performs excellently in large-scale data-parallel computing and iterative processing. However, with the increase in data size and program complexity, the default scheduling strategy has difficulty meeting the demands of resource utilization and performance optimization. Scheduling strategy optimization, as a key direction for improving Spark’s execution efficiency, has attracted widespread attention. This paper first introduces the basic theories of Spark, compares several default scheduling strategies, and discusses common scheduling performance evaluation indicators and factors affecting scheduling efficiency. Subsequently, existing scheduling optimization schemes are summarized based on three scheduling modes: load characteristics, cluster characteristics, and matching More >

  • Open Access

    REVIEW

    Survey on AI-Enabled Resource Management for 6G Heterogeneous Networks: Recent Research, Challenges, and Future Trends

    Hayder Faeq Alhashimi1, Mhd Nour Hindia1, Kaharudin Dimyati1,*, Effariza Binti Hanafi1, Feras Zen Alden2, Faizan Qamar3, Quang Ngoc Nguyen4,5,*

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3585-3622, 2025, DOI:10.32604/cmc.2025.062867 - 19 May 2025

    Abstract The forthcoming 6G wireless networks have great potential for establishing AI-based networks that can enhance end-to-end connection and manage massive data of real-time networks. Artificial Intelligence (AI) advancements have contributed to the development of several innovative technologies by providing sophisticated specific AI mathematical models such as machine learning models, deep learning models, and hybrid models. Furthermore, intelligent resource management allows for self-configuration and autonomous decision-making capabilities of AI methods, which in turn improves the performance of 6G networks. Hence, 6G networks rely substantially on AI methods to manage resources. This paper comprehensively surveys the recent… More >

  • Open Access

    REVIEW

    MediGuard: A Survey on Security Attacks in Blockchain-IoT Ecosystems for e-Healthcare Applications

    Shrabani Sutradhar1,2, Rajesh Bose3, Sudipta Majumder1, Arfat Ahmad Khan4,*, Sandip Roy3, Fasee Ullah5, Deepak Prashar6,7

    CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3975-4029, 2025, DOI:10.32604/cmc.2025.061965 - 19 May 2025

    Abstract Cloud-based setups are intertwined with the Internet of Things and advanced, and technologies such as blockchain revolutionize conventional healthcare infrastructure. This digitization has major advantages, mainly enhancing the security barriers of the green tree infrastructure. In this study, we conducted a systematic review of over 150 articles that focused exclusively on blockchain-based healthcare systems, security vulnerabilities, cyberattacks, and system limitations. In addition, we considered several solutions proposed by thousands of researchers worldwide. Our results mostly delineate sustained threats and security concerns in blockchain-based medical health infrastructures for data management, transmission, and processing. Here, we describe… More >

  • Open Access

    ARTICLE

    How Work Affects the Mental Health of Postdocs?—An Analysis Based on Nature’s 2020 Global Postdoc Survey Data

    Li Yang1, Wanlin Cai2, Wenke Wang3, Chuanyi Wang1,*

    International Journal of Mental Health Promotion, Vol.27, No.4, pp. 421-449, 2025, DOI:10.32604/ijmhp.2025.060930 - 30 April 2025

    Abstract Background: The postdoctoral workforce has been expanding worldwide, playing a vital role in scientific progress, innovation, and knowledge dissemination. Nevertheless, their mental health is also increasingly a global concern, exacerbated by challenges such as intense competition, growing responsibilities, and pressure to publish. Purpose: Research on work characteristics is essential for guiding policy and interventions, offering valuable insights into the factors that affect postdoctoral researchers’ mental health. Hence, this study aims to examine the impact of work characteristics on postdocs’ mental health and explore the underlying mechanisms drawing on the Job Demands-Resources (JD-R) model. Methods: Using data… More >

  • Open Access

    ARTICLE

    Energy-Efficient Air Conditioning System with Combined a Ceiling Fan for Thermal Comfort in an Office

    Linlan Chang1, Win-Jet Luo1,2, Indra Permana2, Bowo Yuli Prasetyo3, Alya Penta Agharid1, Fujen Wang2,*

    Energy Engineering, Vol.122, No.5, pp. 1771-1787, 2025, DOI:10.32604/ee.2025.062209 - 25 April 2025

    Abstract Heating, Ventilation, and Air Conditioning (HVAC) systems are critical for maintaining thermal comfort in office environments which also crucial for occupant well-being and productivity. This study investigates the impact of integrating ceiling fans with higher air conditioning setpoints on thermal comfort and energy efficiency in office environments. Field measurements and questionnaire surveys were conducted to evaluate thermal comfort and energy-saving potential under varying conditions. Results show that increasing the AC setpoint from 25°C to 27°C, combined with ceiling fan operation, reduced power consumption by 10%, achieving significant energy savings. Survey data confirmed that 85% of… More >

  • Open Access

    REVIEW

    A Survey on Enhancing Image Captioning with Advanced Strategies and Techniques

    Alaa Thobhani1,*, Beiji Zou1, Xiaoyan Kui1,*, Amr Abdussalam2, Muhammad Asim3, Sajid Shah3, Mohammed ELAffendi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2247-2280, 2025, DOI:10.32604/cmes.2025.059192 - 03 March 2025

    Abstract Image captioning has seen significant research efforts over the last decade. The goal is to generate meaningful semantic sentences that describe visual content depicted in photographs and are syntactically accurate. Many real-world applications rely on image captioning, such as helping people with visual impairments to see their surroundings. To formulate a coherent and relevant textual description, computer vision techniques are utilized to comprehend the visual content within an image, followed by natural language processing methods. Numerous approaches and models have been developed to deal with this multifaceted problem. Several models prove to be state-of-the-art solutions… More >

  • Open Access

    REVIEW

    A Survey of Link Failure Detection and Recovery in Software-Defined Networks

    Suheib Alhiyari, Siti Hafizah AB Hamid*, Nur Nasuha Daud

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 103-137, 2025, DOI:10.32604/cmc.2024.059050 - 03 January 2025

    Abstract Software-defined networking (SDN) is an innovative paradigm that separates the control and data planes, introducing centralized network control. SDN is increasingly being adopted by Carrier Grade networks, offering enhanced network management capabilities than those of traditional networks. However, because SDN is designed to ensure high-level service availability, it faces additional challenges. One of the most critical challenges is ensuring efficient detection and recovery from link failures in the data plane. Such failures can significantly impact network performance and lead to service outages, making resiliency a key concern for the effective adoption of SDN. Since the More >

  • Open Access

    REVIEW

    A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

    Vajratiya Vajrobol1, Geetika Jain Saxena2, Amit Pundir2, Sanjeev Singh1, Akshat Gaurav3, Savi Bansal4,5, Razaz Waheeb Attar6, Mosiur Rahman7, Brij B. Gupta7,8,9,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 49-90, 2025, DOI:10.32604/cmes.2024.056500 - 17 December 2024

    Abstract Mental health is a significant issue worldwide, and the utilization of technology to assist mental health has seen a growing trend. This aims to alleviate the workload on healthcare professionals and aid individuals. Numerous applications have been developed to support the challenges in intelligent healthcare systems. However, because mental health data is sensitive, privacy concerns have emerged. Federated learning has gotten some attention. This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems. It explores various dimensions of federated learning in mental health, such as More >

  • Open Access

    REVIEW

    A Survey on Supervised, Unsupervised, and Semi-Supervised Approaches in Crowd Counting

    Jianyong Wang1, Mingliang Gao1, Qilei Li2, Hyunbum Kim3, Gwanggil Jeon3,*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3561-3582, 2024, DOI:10.32604/cmc.2024.058637 - 19 December 2024

    Abstract Quantifying the number of individuals in images or videos to estimate crowd density is a challenging yet crucial task with significant implications for fields such as urban planning and public safety. Crowd counting has attracted considerable attention in the field of computer vision, leading to the development of numerous advanced models and methodologies. These approaches vary in terms of supervision techniques, network architectures, and model complexity. Currently, most crowd counting methods rely on fully supervised learning, which has proven to be effective. However, this approach presents challenges in real-world scenarios, where labeled data and ground-truth… More >

  • Open Access

    REVIEW

    A Survey of Lung Nodules Detection and Classification from CT Scan Images

    Salman Ahmed1, Fazli Subhan2,3, Mazliham Mohd Su’ud3,*, Muhammad Mansoor Alam3,4, Adil Waheed5

    Computer Systems Science and Engineering, Vol.48, No.6, pp. 1483-1511, 2024, DOI:10.32604/csse.2024.053997 - 22 November 2024

    Abstract In the contemporary era, the death rate is increasing due to lung cancer. However, technology is continuously enhancing the quality of well-being. To improve the survival rate, radiologists rely on Computed Tomography (CT) scans for early detection and diagnosis of lung nodules. This paper presented a detailed, systematic review of several identification and categorization techniques for lung nodules. The analysis of the report explored the challenges, advancements, and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning (DL) algorithm. The findings also highlighted the usefulness of DL… More >

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