Rapid acquisition and surface defects recognition based on panoramic image of small-section hydraulic tunnel by Haoyu Wang, Jichen Xie, Jinyang Fu, Cong Zhang, Dingping Chen, Zhiheng Zhu, Xuesen Zhang

“…The algorithm introduces DenseNet to optimize the backbone feature extraction network and incorporates an efficient channel attention ECA module to make a better extraction of features of defects. …”
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A Precise Oxide Film Thickness Measurement Method Based on Swept Frequency and Transmission Cable Impedance Correction by Yifan Li, Qi Xiao, Lisha Peng, Songling Huang, Chaofeng Ye

“…A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. …”
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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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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…The optimized models exhibit comparable or improved accuracy compared to those using the whole EIS data and have reasonable performance on unseen test data. …”
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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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Research on Channel Modeling and Communication Coverage of Wireless Sensor Networks in Barrier Area of Nuclear Power Plants by Zhi-Guang Deng, Qian Wu, Xin Lv, Bi-Wei Zhu, Mei-Qiong Xiang, Xue-Mei Wang, Jia-Liang Zhu

“…The simulation results show that the improved teaching and learning algorithm can optimize the network coverage of the obstacle area well, and under the four obstacle modules, 14 nodes can cover the whole area by more than 99%. …”
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Consumer-Centered Collaborative Governance of Regional Business Environment by Tingting Xiang, Hongzhi Lin

“…Optimizing the regional business environment plays a crucial role in improving the market supply structure, enhancing market dynamism, and boosting consumer welfare. …”
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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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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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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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Breast cancer survival prediction using an automated mitosis detection pipeline by Nikolas Stathonikos, Marc Aubreville, Sjoerd deVries, Frauke Wilm, Christof A Bertram, Mitko Veta, Paul J vanDiest

“…Considering the potential of AI to improve reproducibility of MC between pathologists, we undertook the next validation step by evaluating the prognostic value of a fully automatic method to detect and count mitoses on whole slide images using a deep learning model. …”
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QoS Routing in Telecommunications Networks by N. I. Listopad, O. A. Lavshuk

“…The existing routing algorithms have been developed quite fully and, on the whole, function effectively if the optimization of the route selection is carried out according to one parameter. …”
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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…In this work we propose two methods that reduce the resources/state preparations required for QNG, while keeping the advantages and performance of the QNG-based optimization. …”
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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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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…The proposed method was tested on a small dataset within transplantology, focusing on binary classification. Optimal parameters for the method were identified using the Dual Annealing algorithm. …”
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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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Tent–PSO-Based Unmanned Aerial Vehicle Path Planning for Cooperative Relay Networks in Dynamic User Environments by Shuyue Liu, Wenmao Zhou, Mingwei Qin, Xin Peng

“…The proper planning of UAV paths can improve user coverage while maintaining communication quality. …”
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Hybrid Damping Mode MR Damper: Development and Experimental Validation with Semi-Active Control by Jeongwoo Lee, Kwangseok Oh

“…This configuration supports four damping modes—Soft/Soft, Hard/Soft, Soft/Hard, and Hard/Hard—allowing adaptability to varying driving conditions. Magnetic circuit optimization ensures rapid damping force adjustments (≈10 ms), while a semi-active control algorithm incorporating skyhook logic, roll, dive, and squat control strategies was implemented. …”
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