Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall benefits of operation and maintenance while meeting the required standards.…”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…Global FFT processing extracts real-time Doppler-SNR parameter pairs, while a KNN-based arbiter dynamically selects the optimal estimator by: (1) Projecting parameter pairs into historical performance space, (2) Identifying the accuracy-optimal algorithm for current beam conditions, and (3) Executing real-time switching to balance accuracy and robustness. …”
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Development and application of a generalized fatigue driving monitoring system for open-pit mining vehicles: A case study in a myanmar copper mine by Tao Li, Baomeng Chang, Yan Sun, Yaodong Zhou, Bin Zhou, Lubin Zhang

“…Engineering practices yielding the following outcomes: (1) The Beidou positioning antenna demonstrated superior performance in the S&K mine, ensuring accurate vehicle tracking and minimal signal blind spots in challenging open-pit mining environments. (2) The GFDMS effectively identifies unsafe driving behaviors, including speeding, fatigue driving and irregular operations, providing real-time alerts to enhance safety. (3) A comprehensive analysis of system performance demonstrated its effectiveness, reducing traffic incident rates by over 70 % for mining dump trucks and auxiliary vehicles within a year while improving vehicle utilization and operational reliability. (4) Challenges in improving the GFDMS persist in areas such as environmental adaptability, algorithm generalization, and scalability. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…Statistical <i>t</i>-tests confirm the superiority of DRL-NSABC over other algorithms, while achieving a variance of 0.00014. Moreover, DRL-NSABC demonstrates the fastest convergence, reaching near-optimal accuracy within the first 100 epochs. …”
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Investigation of Load Sharing and Dynamic Load Characteristics of a Split Torque Transmission System with Double-Helical Gear Modification by Xuan Liu, Zongde Fang, Haitao Jia, Ning Zhao, Yunbo Shen, Hui Guo, Xijin Zhang

“…Following the modification of a double-helical gear, the dynamic load characteristics of the split torque transmission system are significantly improved, while its load sharing characteristics are improved to a certain extent.…”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…To address this, we propose the IASL-YOLO algorithm, which optimizes the YOLOv8s model to enhance detection accuracy and lightweight efficiency. …”
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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…In seismic data processing, interpolation, super-resolution, and denoising are three key issues to improve data quality. While deep learning methods have successfully addressed one or two of these tasks, simultaneously resolving all three within a single network faces difficulties. …”
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Analysis of injured-skin SS-OCT images based on combined attention UNet. by Xiyu Zheng, Jingyuan Wu, Qiong Ma, Diantao Luo, Qingyu Cai, Haiyang Sun, Hongxing Kang

“…These models were used to segment the damaged skin regions, followed by a 3D reconstruction method to quantitatively evaluate the volume of skin damage while analyzing changes about laser dose and recovery time.The BM3D algorithm effectively suppressed high-noise components, significantly improving image clarity. …”
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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…[Conclusions]The pruned YOLOv8s model successfully maintained high detection accuracy while reducing computational costs and improving inference speed. …”
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AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…We outline criteria for selecting algorithms to improve speed and resource efficiency in HLS design. …”
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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Feature selection and optimization of input scenarios were achieved using a combination of particle swarm optimization (PSO) and manual methods. …”
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Neural network compression for reinforcement learning tasks by Dmitry A. Ivanov, Denis A. Larionov, Oleg V. Maslennikov, Vladimir V. Voevodin

“…The use of sparsity and pruning for optimizing Neural Network inference, and particularly to improve energy efficiency, latency and throughput, is a standard technique. …”
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MUFFNet: lightweight dynamic underwater image enhancement network based on multi-scale frequency by Dechuan Kong, Dechuan Kong, Yandi Zhang, Xiaohu Zhao, Yanqiang Wang, Lei Cai

“…A Multi-Scale Joint Loss framework facilitates dynamic network optimization.ResultsExperimental results demonstrate that MUFFNet outperforms existing state-of-the-art models while consuming fewer computational resources and aligning enhanced images more closely with human visual perception.DiscussionThe enhanced images generated by MUFFNet exhibit better alignment with human visual perception, making it a promising solution for improving underwater robotic vision systems.…”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5&#x002F;7&#x002F;8&#x002F;9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
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A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…Through illumination adjustment while suppressing noise, images with uniform illumination and clear textures were obtained. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The proposed ECE-VDT system encompasses an optimized SimYOLO-V5s algorithm and its five variants for vehicle detection, while the optimized deep-SORT algorithm is proposed for vehicle tracking. …”
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Intelligent Counterforce Allocation Method Using Multi-Agent Reinforcement Learning for Ground Operations by Kiwoong Park, Sangheun Shim

“…Modern military operations require commanders to make complex tactical decisions involving the effective allocation of multiple friendly forces to counter enemy threats while managing diverse streams of battlefield information. …”
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A Robust Hybrid MRAPID Controller Design for an Underactuated Nonlinear System With Parametric Uncertainty by Ahmed Abduljabbar Mahmood, Mohamed Abderrahim

“…The hybrid controller design is developed by combining the MRAPIDC design with controller gains applied to each output and incorporating the system adaptation error in a specific configuration. Optimal performance is achieved through parameter tuning via the social spider optimization (SSO) algorithm, and MIT (Massachusetts Institute of Technology) rule criteria are employed to ensure system stability. …”
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