Mahmudul Hasan¹, Shuji Doman¹, A. S. M. Bakibillah², Md Abdus Samad Kamal^1,*, Kou Yamada¹

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-17, 2026, DOI:10.32604/cmc.2025.070222 - 10 November 2025

Abstract Traffic at urban intersections frequently encounters unexpected obstructions, resulting in congestion due to uncooperative and priority-based driving behavior. This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles (CAVs) at single-lane intersections, particularly in the context of left-hand side driving on roads. The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks. We consider that all approaching vehicles share relevant information through vehicular communications. The Intersection Coordination Unit (ICU) processes this information and communicates the optimal crossing or turning times to the vehicles. The primary objective of this… More >

Qingtao Meng, Sang-Hyun Lee^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-15, 2026, DOI:10.32604/cmc.2025.069970 - 10 November 2025

Abstract This study proposes a lightweight rice disease detection model optimized for edge computing environments. The goal is to enhance the You Only Look Once (YOLO) v5 architecture to achieve a balance between real-time diagnostic performance and computational efficiency. To this end, a total of 3234 high-resolution images (2400 × 1080) were collected from three major rice diseases Rice Blast, Bacterial Blight, and Brown Spot—frequently found in actual rice cultivation fields. These images served as the training dataset. The proposed YOLOv5-V2 model removes the Focus layer from the original YOLOv5s and integrates ShuffleNet V2 into the… More >

Haotian Wu¹, Jiaming Pei², Jinhai Li^3,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069873 - 10 November 2025

Abstract With the increasing complexity of vehicular networks and the proliferation of connected vehicles, Federated Learning (FL) has emerged as a critical framework for decentralized model training while preserving data privacy. However, efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging. To address these issues, we propose Federated Learning with Client Selection and Adaptive Weighting (FedCW), a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks. FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts More >

Zhongliang Wei^1,*, Jianlong An¹, Chang Su²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.069335 - 10 November 2025

Abstract Images taken in dim environments frequently exhibit issues like insufficient brightness, noise, color shifts, and loss of detail. These problems pose significant challenges to dark image enhancement tasks. Current approaches, while effective in global illumination modeling, often struggle to simultaneously suppress noise and preserve structural details, especially under heterogeneous lighting. Furthermore, misalignment between luminance and color channels introduces additional challenges to accurate enhancement. In response to the aforementioned difficulties, we introduce a single-stage framework, M2ATNet, using the multi-scale multi-attention and Transformer architecture. First, to address the problems of texture blurring and residual noise, we design… More >

Fatima Al-Quayed^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069102 - 10 November 2025

Abstract Due to the growth of smart cities, many real-time systems have been developed to support smart cities using Internet of Things (IoT) and emerging technologies. They are formulated to collect the data for environment monitoring and automate the communication process. In recent decades, researchers have made many efforts to propose autonomous systems for manipulating network data and providing on-time responses in critical operations. However, the widespread use of IoT devices in resource-constrained applications and mobile sensor networks introduces significant research challenges for cybersecurity. These systems are vulnerable to a variety of cyberattacks, including unauthorized access,… More >

Lijuan Huang¹, Xianyi Liu², Jinping Liu^2,*, Pengfei Xu^2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-20, 2026, DOI:10.32604/cmc.2025.068818 - 10 November 2025

Abstract The ubiquity of mobile devices has driven advancements in mobile object detection. However, challenges in multi-scale object detection in open, complex environments persist due to limited computational resources. Traditional approaches like network compression, quantization, and lightweight design often sacrifice accuracy or feature representation robustness. This article introduces the Fast Multi-scale Channel Shuffling Network (FMCSNet), a novel lightweight detection model optimized for mobile devices. FMCSNet integrates a fully convolutional Multilayer Perceptron (MLP) module, offering global perception without significantly increasing parameters, effectively bridging the gap between CNNs and Vision Transformers. FMCSNet achieves a delicate balance between computation… More >

Jianhua Yang^*, Zhiwei Lv, Changling Huo

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.068442 - 10 November 2025

Abstract Aiming at the scale adaptation of automatic driving target detection algorithms in low illumination environments and the shortcomings in target occlusion processing, this paper proposes a YOLO-LKSDS automatic driving detection model. Firstly, the Contrast-Limited Adaptive Histogram Equalisation (CLAHE) image enhancement algorithm is improved to increase the image contrast and enhance the detailed features of the target; then, on the basis of the YOLOv5 model, the Kmeans++ clustering algorithm is introduced to obtain a suitable anchor frame, and SPPELAN spatial pyramid pooling is improved to enhance the accuracy and robustness of the model for multi-scale target… More >

Shengran Zhao, Zhensong Li^*, Xiaotan Wei, Yutong Wang, Kai Zhao

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-14, 2026, DOI:10.32604/cmc.2025.068138 - 10 November 2025

Abstract In printed circuit board (PCB) manufacturing, surface defects can significantly affect product quality. To address the performance degradation, high false detection rates, and missed detections caused by complex backgrounds in current intelligent inspection algorithms, this paper proposes CG-YOLOv8, a lightweight and improved model based on YOLOv8n for PCB surface defect detection. The proposed method optimizes the network architecture and compresses parameters to reduce model complexity while maintaining high detection accuracy, thereby enhancing the capability of identifying diverse defects under complex conditions. Specifically, a cascaded multi-receptive field (CMRF) module is adopted to replace the SPPF module… More >

Mingwei Yue¹, Shen Rao^1,*, Xiaomeng Liu¹, Wei Yang², Yuan Yuan¹, Feng Xu², Shuiyuan Cheng^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3319-3348, 2025, DOI:10.32604/phyton.2025.073602 - 01 December 2025

Abstract Cadmium (Cd), a highly toxic heavy metal, represents a major global environmental threat due to its widespread dispersion through anthropogenic activities. Environmental Cd contamination poses significant risks to living organisms, including humans, animals, and plants. Certain plant species have evolved Cd hyperaccumulating capabilities to adapt to high-Cd habitats, playing critical roles in phytoremediation strategies. Here we review the biodiversity and biogeography of Cd hyperaccumulators, the underlying mechanisms of Cd uptake and accumulation, and the ecological impacts of hyperaccumulation. The major points are the following: twenty-four Cd hyperaccumulator species have been documented, with shoot Cd concentrations More >

Nadia Lamsaadi¹, Oumaima Maarouf², Soukaina Lahmaoui², Hamid Msaad², Omar Farssi², Chaima Hamim², Mohamed Tamoudjout², Hafsa Hirt², Habiba Kamal², Majida El Hassni², Cherki Ghoulam^3,4, Ahmed El Moukhtari^5,*, Mohamed Farissi²

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3585-3610, 2025, DOI:10.32604/phyton.2025.072311 - 01 December 2025

Abstract Abiotic stresses, such as drought, heavy metals, salinity, and extreme temperatures, are among the most common adverse threats that restrict the use of land for agriculture and limit crop growth and productivity. As sessile organisms, plants defend themselves from abiotic stresses by developing various tolerance mechanisms. These mechanisms are governed by several biochemical traits. The biochemical mechanisms are the products of key genes that express under specific conditions. Interestingly, the expression of these genes is regulated by specialized proteins known as transcription factors (TFs). Several TFs, including those from the bZIP, bHLH, MYB, HSF, WRKY,… More >