Ivan Pliško, Mihael Cipek^*, Danijel Pavković

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078275 - 18 June 2026

Abstract Nowadays, battery electric vehicles are increasingly used, from passenger cars to heavy-duty commercial vehicles, trains, and ships, all in an effort to reduce greenhouse gas emissions. In electric vehicles, battery capacity significantly affects their range and performance, but a larger battery also increases the vehicle’s mass and cost. This paper proposes parametric optimization of battery capacity and peak electric motor power for electric vehicles under different load types and vehicle capacities. A computational model of an electric vehicle is developed, with parameters such as battery capacity, payload, and peak motor power being variable. Using parametric More >

Yunkeun Song¹, Samuel Woo², Suji Lee³, Yousik Lee^3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.083267 - 15 June 2026

Abstract Software-Defined Vehicles (SDVs) increase cybersecurity complexity through the combination of external connectivity, software-intensive functions, and distributed development across vehicle manufacturers and suppliers. Although United Nations (UN) Regulation No. 155 and ISO/SAE 21434 require Threat Analysis and Risk Assessment (TARA) throughout the vehicle lifecycle, conventional TARA methodologies remain largely system-focused and often provide limited procedural guidance for coordinating supplier-derived TARA results at the vehicle level. This paper proposes an orchestration model for TARA across vehicle manufacturers and suppliers that structures TARA activities into the concept phase and the product development phases. The model defines interactions between… More >

Sajid Ullah Khan^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082458 - 15 June 2026

Abstract Autonomous underwater vehicles (AUVs) play a crucial role in oceanographic research, monitoring the environment, and exploring resources in the ocean. Nevertheless, the operational efficiency of these devices is frequently constrained by the limited battery capacity and the requirement for charging while connected to a power source. Wireless power transfer (WPT) offers a non-contact alternative to conventional wet-mate electrical connectors, with inductive coupling receiving particular attention because of its relatively high efficiency, safety, and suitability for underwater charging over short transfer gaps. However, it is limited by the transfer distance, coil misalignment, coupler design constraints, and… More >

Kemeng Zhu¹, Dingju Zhu^1,2,*, Shihua Mao¹, Jinchen Wu³, Depeng Kong⁴, Kaileung Yung⁵, Andrew W. H. Ip⁶

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082431 - 15 June 2026

Abstract Unmanned aerial vehicles (UAVs) have become an increasingly important platform for agricultural remote sensing, yet the accurate recognition of pests and diseases is frequently compromised by drastic scale variability and complex environmental backgrounds. To address these challenges, this study introduces a novel attention-driven approach centered on a Multi-Scale Grouped Channel–Spatial Dual Attention (MS-GCDA) mechanism. The MS-GCDA module achieves robust feature calibration by decoupling and jointly modeling multi-scale spatial contexts and grouped channel dependencies, which significantly enhances the model’s sensitivity to fine-grained disease symptoms while suppressing background clutter. This core mechanism is integrated into Augmented EfficientNet… More >

Lei Wang¹, Hongji Luo², Yong Heng², Jingnan Tang², Xiaochuan Ju², Jianwei An^1,*, Haitao Xu¹, Xianwei Zhou¹

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082418 - 15 June 2026

Abstract In intelligent connected vehicles (ICVs) system, driving users connect to service providers (SPs) to obtain location-based services (LBS). Users transmit large volumes of encrypted sensitive information related to their itineraries to SPs to access value-added services. Attackers may launch chosen-ciphertext attacks (CCA) against SPs by exploiting the malleability of homomorphic encryption. This enables adversaries to infer or steal private key information, thereby threatening the long-term privacy of user data. Furthermore, existing key management technologies in ICVs system predominantly rely on passive defense strategies and suffer from limitations such as single protection mechanisms, delayed updates, and More >

Yao-Bo Long¹, Yu-Ke Ouyang², Bo Zhuang², Ao-Qi Liu^3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081203 - 15 June 2026

Abstract This study addresses the real-time visual tracking task in edge environments by proposing a robust visual servoing control system based on a higher-order sliding mode observer, enabling a quadrotor UAV to autonomously track a moving soccer ball during outdoor sports broadcasts while relying solely on a monocular camera and an inertial measurement unit, thereby eliminating any dependency on external positioning or velocity sensors such as GPS. The system adopts a hierarchical control architecture in which the observer plays a central role: operating on resource-constrained edge devices, it leverages only visual information to estimate unknown external… More >

Xuan-Thuc Nguyen¹, Le-Minh Nguyen¹, Ngoc-Quynh Nguyen¹, Nhu-Nghia Bui², Dinh-Quy Vu^3,*, Thai-Viet Dang^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080008 - 15 June 2026

Abstract The development of unmanned automated vehicles (UAVs) has become a key focus in aerial robotics, fueling the need for navigation systems capable of performing complex and delicate tasks with speed and precision. However, the end-to-end path tracking process often encounters challenges in learning efficiency, generalization, and varying environmental conditions. In this paper, we propose the novel IRL-TP framework for learning-based UAVs’ trajectory planning that employs a deep inverse reinforcement learning (IRL) approach. Firstly, the RL-based path planner must develop a reward function that effectively captures flight safety, collision avoidance, trajectory smoothness, and navigation efficiency within… More >

Rubina Castro^1,2, Bruno Silva^1,3, Luiz Guerreiro Lopes^1,4, Fábio Mendonça^1,2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.079979 - 15 June 2026

Abstract Path planning for autonomous underwater vehicles requires reliable and computationally efficient methods, particularly in cluttered environments. This work presents a comparative evaluation of representative approaches, including metaheuristic optimization methods (continuous genetic algorithm, particle swarm optimization, gray wolf optimizer, and Jaya), a sampling-based method (probabilistic roadmap with genetic refinement), a reactive strategy (artificial potential fields), and a control-based approach (model predictive control with control barrier functions). The algorithms are assessed in a controlled two-dimensional simulated workspace with randomly generated obstacles and systematically increasing obstacle density. Each configuration is evaluated across multiple independent trials using metrics such… More >

Oluwatosin Ahmed Amodu¹, Zurina Mohd Hanapi^1,*, Chedia Jarray², Huda Althumali³, Faten A. Saif ⁴, Raja Azlina Raja Mahmood¹, Mohammed Sani Adam⁵, Nor Fadzilah Abdullah⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077054 - 27 May 2026

Abstract Non-terrestrial networks (NTNs)—including UAVs, HAPs, and satellite systems—are rapidly becoming key enablers of wide-area, resilient connectivity for large-scale IoT applications. As these platforms integrate with terrestrial networks to form space–air–ground architectures, optimization challenges related to trajectory, resource management, energy efficiency, and security become increasingly complex. Machine learning (ML) has emerged as a central tool for addressing these challenges by enabling adaptive, data-driven decision-making under uncertainty. This survey presents an optimization-centric review of ML-based NTN-assisted IoT systems focusing on aspect-specific datasets. Using a structured methodology involving dataset curation, keyword filtering, metadata analysis, and citation-based paper selection,… More >

Zujun Ding, Zhi Liu, Peng Huang, Yuhan Qian, Chengyi Li, Zizhuo Yu, Hui Huang, Baolian Liu, Wan Chen, Jie Ji^*

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2025.074440 - 27 May 2026

Abstract Under extreme weather conditions (such as hurricanes and heatwaves causing sudden drops in renewable energy output and surges in load), microgrid operations face severe challenges due to the uncertainty of renewable energy and load fluctuations. Although existing research has focused on microgrid optimal scheduling or electric vehicle integration, there has not yet been a systematic approach to multi-timescale scheduling that combines electric vehicle fleets under extreme weather scenarios, and particularly, explicit modeling of weather events and their impact on component failure rates and transmission lines is lacking. This paper proposes, for the first time, a… More >