Manh-Tuan Ha¹, Nhu-Nghia Bui², Dinh-Quy Vu^1,*, Thai-Viet Dang^2,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077237 - 09 April 2026

Abstract In the realm of unmanned surface vehicle (USV) operations, leveraging environmental factors to enhance situational awareness has garnered significant academic attention. Developing vision systems for USVs presents considerable challenges, mainly due to variable observational conditions and angular vibrations caused by hydrodynamic forces. The paper proposed a novel MDGAN-DIFI network for end-to-end multi-object tracking (MOT), specifically designed for camera systems mounted on USVs. Beyond enhancing traditional MOT models, the proposed MDGAN-DIFI includes preprocessing modules designed to enhance the efficiency of processing input signal quality. Initially, a Deep Iterative Frame Interpolation (DIFI) module is used to stabilize… More >

Yihao Kuang^1,2, Hong Zhang^1,2, Jiaqi Wang^1,2, Lingyu Jin^1,2, Bo Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076652 - 09 April 2026

Abstract 3D single object tracking (SOT) based on point clouds is a fundamental task for environmental perception in autonomous driving and dynamic scene understanding in robotics. Recent technological advancements in this field have significantly bolstered the environmental interaction capabilities of intelligent systems. This field faces persistent challenges, including feature degradation induced by point cloud sparsity, representation drift caused by non-rigid deformation, and occlusion in complex scenarios. Traditional appearance matching methods, particularly those relying on Siamese networks, are severely constrained by point cloud characteristics, often failing under rapid motions or structural ambiguities among similar objects. In response,… More >

Wulfran Fendzi Mbasso^1,2, Idriss Dagal³, Manish Kumar Singla^4,5,*, Muhammad Suhail Shaikh⁶, Aseel Smerat⁷, Abdullah Mohammed Al Fatais^8,9, Ali Saeed Almufih^8,9, Rabia Emhamed Al Mamlookol^10,11

Energy Engineering, Vol.123, No.4, 2026, DOI:10.32604/ee.2026.072751 - 27 March 2026

Abstract Photovoltaic (PV) systems in the field operate under complex, uncertain conditions rapid irradiance ramps, partial shading, temperature swings, surface soiling, and weak-grid disturbances including off-nominal frequency and voltage distortion that degrade energy yield and power quality. We propose a drift-aware, power-quality-constrained MPPT framework that co-optimizes MPPT, PLL, and current-loop gains under stochastic frequency drift, while enforcing IEEE-519 limits (per-order I_h/I_L and TDD) during optimization. Unlike energy-only or THD-only methods, the design target integrates PQ constraints into the objective and is validated across calibrated drift scenarios with explicit per-order and TDD reporting. Operating scenarios are calibrated to… More > Graphic Abstract

Shih-Ming Cho¹, Sung-Wen Wang¹, Min-Chie Chiu^2,*, Shao-Chun Chen¹

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.074911 - 12 March 2026

Abstract To address crop depredation by intelligent species (e.t, macaques) and the habituation from traditional methods, this study proposes an intelligent, closed-loop, adaptive laser deterrence system. A core contribution is an efficient multi-stage Semi-Supervised Learning (SSL) and incremental fine-tuning (IFT) framework, which reduced manual annotation by ~60% and training time by ~68%. This framework was benchmarked against YOLOv8n, v10n, and v11n. Our analysis revealed that YOLOv12n’s high Signal-to-Noise Ratio (SNR) (47.1% retention) pseudo-labels made it the only model to gain performance (+0.010 mAP) from SSL, allowing it to overtake competitors. Subsequently, in the IFT stress test,… More >

Wulfran Fendzi Mbasso^1,2, Idriss Dagal³, Manish Kumar Singla^4,5,*, Muhammad Suhail Shaikh⁶, Aseel Smerat⁷

Energy Engineering, Vol.123, No.3, 2026, DOI:10.32604/ee.2026.072899 - 27 February 2026

Abstract Utility-scale PV plants increasingly operate under partial shading, soiling, temperature swings, and rapid irradiance ramps that depress yield and challenge stability on weak grids. This critical review addresses those conditions by (i) unifying a stressor-to-method taxonomy that links field stressors to global intelligent MPPT (metaheuristics and learning-based trackers) and to advanced inverter controls (adaptive/MPC and grid-forming), (ii) standardizing metrics and reporting aligned with IEC 61724-1 and IEEE 1547/1547.1 to enable fair, reproducible comparisons, and (iii) framing MPPT and grid support as a co-design problem with a DT→HIL→Field validation pathway and seedable scenarios. We identify persistent… More > Graphic Abstract

Nien-Tsu Hu^1,*, Hsiang-Tung Kao¹, Chin-Sheng Chen¹, Shih-Hao Chang²

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074993 - 10 February 2026

Abstract Trajectory tracking for nonlinear robotic systems remains a fundamental yet challenging problem in control engineering, particularly when both precision and efficiency must be ensured. Conventional control methods are often effective for stabilization but may not directly optimize long-term performance. To address this limitation, this study develops an integrated framework that combines optimal control principles with reinforcement learning for a single-link robotic manipulator. The proposed scheme adopts an actor–critic structure, where the critic network approximates the value function associated with the Hamilton–Jacobi–Bellman equation, and the actor network generates near-optimal control signals in real time. This dual… More >

Langyue Zhao^1,2, Yubin Yuan^3,*, Yiquan Wu^2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.070563 - 10 February 2026

Abstract Regular detection of pavement cracks is essential for infrastructure maintenance. However, existing methods often ignore the challenges such as the continuous evolution of crack features between video frames and the difficulty of defect quantification. To this end, this paper proposes an integrated framework for pavement crack detection, segmentation, tracking and counting based on Transformer. Firstly, we design the VitSeg-Det network, which is an integrated detection and segmentation network that can accurately locate and segment tiny cracks in complex scenes. Second, the TransTra-Count system is developed to automatically count the number of defects by combining defect More >

Guangyu Xu^1,2, Yuxin Liu¹, Bo Yang¹, Siyu Lu^3,*, Chao Liu⁴, Junmin Lyu⁵, Wenfeng Zheng^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074938 - 29 January 2026

Abstract Soft-tissue motion introduces significant challenges in robotic teleoperation, especially in medical scenarios where precise target tracking is critical. Latency across sensing, computation, and actuation chains leads to degraded tracking performance, particularly around high-acceleration segments and trajectory inflection points. This study investigates machine learning-based predictive compensation for latency mitigation in soft-tissue tracking. Three models—autoregressive (AR), long short-term memory (LSTM), and temporal convolutional network (TCN)—were implemented and evaluated on both synthetic and real datasets. By aligning the prediction horizon with the end-to-end system delay, we demonstrate that prediction-based compensation significantly reduces tracking errors. Among the models, TCN More >

Huda Talib Najm^1,2, Ahmed Sabah Al-Araji³, Nur Syazreen Ahmad^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.071837 - 29 January 2026

Abstract Mobile service robots (MSRs) in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions, including model uncertainties and external disturbances. This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller (NFIDC) with a Feedback Radial Basis Function Neural Network (FRBFNN). The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1. The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.… More >

Ahsan Habib Siam¹, Md. Ehsanul Haque¹, Fahmid Al Farid², Anindita Sutradhar³, Jia Uddin^4,*, Sarina Mansor^2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.069718 - 12 January 2026

Abstract As healthcare systems increasingly embrace digitalization, effective management of electronic health records (EHRs) has emerged as a critical priority, particularly in inpatient settings where data sensitivity and real-time access are paramount. Traditional EHR systems face significant challenges, including unauthorized access, data breaches, and inefficiencies in tracking follow-up appointments, which heighten the risk of misdiagnosis and medication errors. To address these issues, this research proposes a hybrid blockchain-based solution for securely managing EHRs, specifically designed as a framework for tracking inpatient follow-ups. By integrating QR code-enabled data access with a blockchain architecture, this innovative approach enhances… More >