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 >

Hayder Faeq Alhashimi¹, Mhd Nour Hindia¹, Kaharudin Dimyati^1,*, Effariza Binti Hanafi¹, Feras Zen Alden², Faizan Qamar³, Quang Ngoc Nguyen^4,5,*

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 >

Shrabani Sutradhar^1,2, Rajesh Bose³, Sudipta Majumder¹, Arfat Ahmad Khan^4,*, Sandip Roy³, Fasee Ullah⁵, Deepak Prashar^6,7

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 >

Li Yang¹, Wanlin Cai², Wenke Wang³, Chuanyi Wang^1,*

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 >

Linlan Chang¹, Win-Jet Luo^1,2, Indra Permana², Bowo Yuli Prasetyo³, Alya Penta Agharid¹, Fujen Wang^2,*

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 >

Alaa Thobhani^1,*, Beiji Zou¹, Xiaoyan Kui^1,*, 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 >

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 >

Vajratiya Vajrobol¹, Geetika Jain Saxena², Amit Pundir², Sanjeev Singh¹, Akshat Gaurav³, Savi Bansal^4,5, Razaz Waheeb Attar⁶, Mosiur Rahman⁷, Brij B. Gupta^7,8,9,*

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 >

Jianyong Wang¹, Mingliang Gao¹, Qilei Li², Hyunbum Kim³, Gwanggil Jeon^3,*

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 >

Salman Ahmed¹, Fazli Subhan^2,3, Mazliham Mohd Su’ud^3,*, Muhammad Mansoor Alam^3,4, 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 >