Mingfang Li, Damin Zhang^*, Qing He, Chenglong Zhou, Mingrong Li, Xiaobo Zhou

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076433 - 09 April 2026

Abstract Traffic sign detection is a critical task in autonomous driving environmental perception. However, models often suffer from degraded detection performance in complex real-world scenarios due to variable target scales, blurred fine-grained features, and complex background interference. This paper proposes an improved YOLOv8n detection model, MSD-YOLO, to address these challenges. First, a Multi-scale Detail Enhancement Module (MDEM) is designed, which achieves targeted enhancement of edge features through high-frequency residual modulation and multi-scale cooperative attention. Second, an enhanced feature pyramid network termed SG-FPN is constructed. It introduces soft nearest neighbor interpolation (SNI) for semantic-spatial aligned feature fusion… More >

Zahra Farhadpour^1,*, Tan Fong Ang^1,*, Chee Sun Liew²

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076163 - 09 April 2026

Abstract The heterogeneity and dynamic behavior of fog computing environments introduce major challenges to achieving optimal application placement. Limited fog resources and varying workloads often necessitate offloading applications beyond their local clusters, making it difficult to maintain the required level of service quality under varying conditions. In this context, placement methods must ensure a balanced trade-off between multiple objectives, such as time and cost, while maintaining reliable adherence to constraints like application deadlines and limited fog-node memory. Existing solutions, including heuristic, metaheuristic, learning-based, and hybrid optimization approaches, have been proposed to address these challenges. However, many… More >

A. Sivasangari^1,*, V. J. K. Kishor Sonti¹, J. Cruz Antony¹, E. Murali¹, D. Deepa¹, A. Happonen²

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074429 - 09 April 2026

Abstract In the past two decades, Precision Agriculture has received research attention since the development of robotics. Agricultural robotic equipment and drones, which can be operated by farmers, are appearing more frequently and being used to make the process of farming easier and more productive. This paper attempts to develop a modified Q-learning algorithm. A reinforcement learning algorithm called Q-learning has Q-values that are updated in order to find the best routes for the robotic devices to follow while avoiding any obstacles. Different types of terrain and other factors that influence the development of good routes… More >

Fangxiang Hu¹, Qi Fu^1,2,*, Shiwen Zhang¹, Jing Huang¹

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.074154 - 09 April 2026

Abstract In the Internet of Vehicles (IoV) environment, the growing demand for computational resources from diverse vehicular applications often exceeds the capabilities of intelligent connected vehicles. Traditional approaches, which rely on one or more computational resources within the cloud-edge-device computing model, struggle to ensure overall service quality when handling high-density traffic flows and large-scale tasks. To address this issue, we propose a computational offloading scheme based on a cloud-edge-device collaborative 6G IoV edge computing model, namely, Multi-Agent Deep Reinforcement Learning-based and Server-weighted scoring Selection (MADRLSS), which aims to optimize dynamic offloading decisions and resource allocation. The… More >

Arifur Rahman¹, MD Azam Khan¹, Farhad Uddin Mahmud¹, Kanchon Kumar Bishnu², Ashifur Rahman³, M. F. Mridha^4,*, Md. Jakir Hossen^5,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.071029 - 09 April 2026

Abstract Generative Artificial Intelligence (AI) is reshaping digital marketing by creating automated content, personalizing campaigns, and offering new ways to engage consumers. This systematic review examines research on generative AI, highlighting both its technological progress and the ethical, technical, and organizational hurdles that could limit its use. We used a PRISMA-based method to search major databases (ACM Digital Library, IEEE Xplore, and Scopus) for peer-reviewed studies published from 2018 to 2025. Our findings reveal major gains in text creation, image generation, and multimodal campaigns, which can lower costs and spark creative thinking. Still, data privacy, bias More >

Kuok Ho Daniel Tang^*

Journal of Polymer Materials, Vol.43, No.1, 2026, DOI:10.32604/jpm.2025.074391 - 03 April 2026

Abstract Biobased biodegradable plastics have gained increasing attention as sustainable alternatives to petroleum-based materials in food packaging, offering biodegradability, renewability, and reduced environmental impact. This review adopts a narrative review approach, integrating studies published between 2015 and 2025 from major databases to critically evaluate the recent advances, feasibility, and limitations of biobased biodegradable plastics in food packaging. Literature was thematically analyzed by material type and functional enhancement to assess their feasibility and limitations for sustainable packaging applications. Recent advances have focused on enhancing their mechanical, barrier, and functional properties through polymer blending, nanoparticle reinforcement, and incorporation… More >

Lishuai Zhu¹, Guangcai Zhang^1,*, Qun Xie^1,*, Zhen Peng², Li Ai³, Ruijun Liang¹, Taochun Yang¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.074620 - 31 March 2026

Abstract Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and… More >

Xianghui Li^1,2, Xin Fu³, Libo Pan², Fancong Zeng^1,2,*, Zhijiang Zuo^1,2

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.073124 - 31 March 2026

Abstract The present study proposes an autonomous visual inspection system based on Wall-Climbing Robot (WCR), with a view to addressing the shortcomings of traditional building crack detection methods, namely their low measurement accuracy, high manual dependence and insufficient environmental adaptability. The system has been developed to construct a crack recognition model with robust illumination adaptation by fusing the improved YOLOv5s target detection algorithm with the Canny edge enhancement algorithm. The system has been realized as a lightweight deployment on an embedded device (MaixCAM). The robot platform employs a design scheme integrating a dual-chamber negative pressure adsorption… More >

Qi Feng^1,2, Dan Wang^3,*, Weijie Hu¹, Wenhao Zhao²

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072968 - 31 March 2026

Abstract Engineered Cementitious Composites (ECC) represent an advanced class of fiber-reinforced cement-based materials developed over the past three decades, characterized by remarkable tensile strain-hardening and multiple-cracking behavior. By incorporating hybrid fibers, Hybrid Fiber engineered cementitious composites (HFECC) can be tailored to meet specific engineering demands in terms of strength, deformation, dynamic mechanical performance, and cost-effectiveness. This paper provides a comprehensive review of the critical fiber volume theory, experimental investigations into quasi-static and dynamic mechanical properties, and the structural performance of HFECC. Furthermore, current research gaps and future directions for the development and application of HFECC are More >

Yi Wang^1,2,*, Yansong Li², Bingxu Cai², Yukai Zhu¹, Hairong Wu¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072553 - 31 March 2026

Abstract Prefabricated buildings have developed rapidly due to their advantages in energy efficiency, environmental protection, and high construction efficiency, which have greatly promoted the advancements of connection technology and the mechanical properties of prefabricated hollow panels. This study proposes a new optimization scheme for prefabricated wall structures using transversely arranged prefabricated hollow plates and develops a new joint connection. First, the constitutive relations are experimentally validated to establish an accurate finite element analysis model; Then the equal-size specimens are compared with the control specimens without node connections; Finally, the effects of axial compression ratio, aspect ratio, More >