Yu-Sheng Su^1,2,3,*, Yi-Wen Wang¹, Yun-Chin Wu³, Zheng-Yun Xiao¹, Ting-Jou Ding⁴

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1095-1111, 2025, DOI:10.32604/cmc.2025.067129 - 29 August 2025

Abstract In the context of global change, understanding changes in water resources requires close monitoring of groundwater levels. A mismatch between water supply and demand could lead to severe consequences such as land subsidence. To ensure a sustainable water supply and to minimize the environmental effects of land subsidence, groundwater must be effectively monitored and managed. Despite significant global progress in groundwater management, the swift advancements in technology and artificial intelligence (AI) have spurred extensive studies aimed at enhancing the accuracy of groundwater predictions. This study proposes an AI-based method that combines deep learning with a… More >

Qamar H. Naith^1,*, H. Mancy^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 387-405, 2025, DOI:10.32604/cmes.2025.066917 - 31 July 2025

Abstract Effective water distribution and transparency are threatened with being outrightly undermined unless the good name of urban infrastructure is maintained. With improved control systems in place to check leakage, variability of pressure, and conscientiousness of energy, issues that previously went unnoticed are now becoming recognized. This paper presents a grandiose hybrid framework that combines Multi-Agent Deep Reinforcement Learning (MADRL) with Shapley Additive Explanations (SHAP)-based Explainable AI (XAI) for adaptive and interpretable water resource management. In the methodology, the agents perform decentralized learning of the control policies for the pumps and valves based on the real-time… More >

KL Vasudev¹, Manish Pandey², Jaan H. Pu^3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1545-1569, 2025, DOI:10.32604/fdmp.2025.065289 - 31 July 2025

Abstract This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles (AUVs), paying special attention to drag, lift-to-drag ratio, and delivered power. A fully integrated optimisation framework is developed accordingly, combining a single-objective Genetic Algorithm (GA) for design parameter generation, Computer-Aided Geometric Design (CAGD) for the creation of hull geometries and associated fluid domains, and a Reynolds-Averaged Navier–Stokes (RANS) solver for evaluating hydrodynamic performance metrics. This unified approach eliminates manual intervention, enabling automated determination of optimal hull configurations. Three distinct optimisation problems are addressed using the proposed methodology. First,… More >

Yu-Shan Cheng¹, Bo-Zheng Luo¹, Guan-Hao Su¹, Yi-Hua Liu^2,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5791-5809, 2025, DOI:10.32604/cmc.2025.066125 - 30 July 2025

Abstract Underwater charging stations allow Autonomous Underwater Vehicles (AUVs) to recharge batteries, extending missions and reducing surface support. However, efficient wireless power transfer requires overcoming alignment challenges and environmental variations in conductive seawater. This paper employs Particle Swarm Optimization (PSO) to design coupling coils specifically applied for underwater wireless charging station systems. The establishment of underwater charging stations enables Autonomous Underwater Vehicles (AUVs) to recharge batteries underwater, extending mission duration and reducing reliance on surface-based resupply operations. The proposed charging system is designed to address the unique challenges of the underwater environment, such as alignment disruptions… More >

Yu-Hsien Lin^*, Po-Cheng Chuang, Joyce Yi-Tzu Huang

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4907-4948, 2025, DOI:10.32604/cmc.2025.065995 - 30 July 2025

Abstract This study proposes an automatic control system for Autonomous Underwater Vehicle (AUV) docking, utilizing a digital twin (DT) environment based on the HoloOcean platform, which integrates six-degree-of-freedom (6-DOF) motion equations and hydrodynamic coefficients to create a realistic simulation. Although conventional model-based and visual servoing approaches often struggle in dynamic underwater environments due to limited adaptability and extensive parameter tuning requirements, deep reinforcement learning (DRL) offers a promising alternative. In the positioning stage, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is employed for synchronized depth and heading control, which offers stable training, reduced overestimation… More >

Fatima Abu Siryeh^*, Hussein Alrammahi, Abdullahi Abdu İbrahim

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5021-5046, 2025, DOI:10.32604/cmc.2025.065206 - 30 July 2025

Abstract Biometric template protection is essential for finger-based authentication systems, as template tampering and adversarial attacks threaten the security. This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication. The system was tested against NIST SD4 and Anguli fingerprint datasets, wherein 10,000 watermarked fingerprints were employed for training. The designed approach recorded a tamper detection rate of 98.3%, performing 3–6% better than current DCT, SVD, and DWT-based watermarking approaches. The false positive rate (≤1.2%) and false negative rate (≤1.5%) were much lower compared to previous… More >

Qizhi Chen^1,2, Wensheng Cheng^1,2, Baoping Zou^1,2,*, Bowen Kong^1,2, Yansheng Deng^1,2, Xu Long^3,*

Journal of Polymer Materials, Vol.42, No.2, pp. 463-475, 2025, DOI:10.32604/jpm.2025.064257 - 14 July 2025

Abstract The rapid development of urban rail transit has posed increasing construction and operational challenges for metro tunnels, often leading to structural damage. Grouting technology using cement-based materials is widely applied to address issues such as seepage, leakage, and alignment correction in shield tunnels. This study investigates the additional stress induced by grouting in silty soil layers, using cement-based grouts with different water-to-cement ratios and polyurethane-modified cement-based materials. Results show that additional stress decreases with depth and is more influenced by horizontal distance from the grouting point. In staged grouting, the first injection phase contributes about More >

Hanyi Zou^1,2,#, Xinye Xu^1,3,#, Mutian Yao¹, Baoyang Lu^1,*

Journal of Polymer Materials, Vol.42, No.2, pp. 339-358, 2025, DOI:10.32604/jpm.2024.057955 - 14 July 2025

Abstract The global scarcity of clean water is an escalating issue due to climate change, population growth, and pollution. Traditional water purification technologies, while effective, often require significant energy input and complex infrastructure, limiting their accessibility. This review explores the use of conjugated polymer hydrogels as a promising solution for solar water purification. Conjugated polymer hydrogels offer unique advantages, including high photothermal conversion efficiency, effective heat management, and rapid water transport, which are crucial for efficient solar-driven water evaporation. By leveraging the properties of these hydrogels, it is possible to significantly reduce the energy required for More >

Yu-Shiuan Tsai^*, Zhen-Rong Wu, Jian-Zhi Liu

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3431-3457, 2025, DOI:10.32604/cmc.2025.066509 - 03 July 2025

Abstract Few-shot learning has emerged as a crucial technique for coral species classification, addressing the challenge of limited labeled data in underwater environments. This study introduces an optimized few-shot learning model that enhances classification accuracy while minimizing reliance on extensive data collection. The proposed model integrates a hybrid similarity measure combining Euclidean distance and cosine similarity, effectively capturing both feature magnitude and directional relationships. This approach achieves a notable accuracy of 71.8% under a 5-way 5-shot evaluation, outperforming state-of-the-art models such as Prototypical Networks, FEAT, and ESPT by up to 10%. Notably, the model demonstrates high… More >

Jiahao Liu^1,#, Yuanyuan Kang^2,#, Kun Cai^2,*, Haiyan Duan¹, Jiao Shi^3,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2573-2586, 2025, DOI:10.32604/cmc.2025.066249 - 03 July 2025

Abstract The directional explosion behavior of finite volume water confined within nanochannels holds considerable potential for applications in precision nanofabrication and bioengineering. However, precise control of nanoscale mass transfer remains challenging in nanofluidics. This study examined the dynamic evolution of water clusters confined within a single-end-opened carbon nanotube (CNT) under pulsed electric field (EF) excitation, with a particular focus on the structural reorganization of hydrogen bond (H-bond) networks and dipole orientation realignment. Molecular dynamics simulations reveal that under the influence of pulsed EF, the confined water molecules undergo cooperative restructuring to maximize hydrogen bond formation through… More > Graphic Abstract