A Rapid Design Method for Centrifugal Pump Impellers Based on Machine Learning by Y. Chen, W. Li, Y. Luo, L. Ji, S. Li, Y. Long

“…Variations in the cross-sectional area of the flow passage influence the internal flow state of the centrifugal pump, ultimately impacting its hydraulic efficiency. A genetic algorithm, guided by variations in the cross-sectional area of the flow passage, optimizes the blade profile, achieving an improved impeller flow path and completing the rapid design of the centrifuge. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…However, the existing CS ISAR imaging methods based on deep learning (DL) mainly focus on improving the performance of the reconstruction algorithm while ignoring the potential room for improvement given by the design of the measurement matrix. …”
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Simulation and Test of a Fuel Cell Hybrid Golf Cart by Jingming Liang, Qifei Jian

“…This paper establishes the simulation model of fuel cell hybrid golf cart (FCHGC), which applies the non-GUI mode of the Advanced Vehicle Simulator (ADVISOR) and the genetic algorithm (GA) to optimize it. …”
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A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry by Yadong Guo, Wenxue Xu, Yanxiong Liu, Fanlin Yang, Xue Ji, Yikai Feng, Qiuhua Tang

“…Finally, a back propagation neural network (BPNN) model is constructed using the points generated from surface–seafloor shots, and the seafloor points in seafloor-undefined shots are obtained by optimizing the BPNN results. …”
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Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…Future research should focus on refining AI models to improve predictive accuracy and assessing long-term outcomes to further optimize disease management. …”
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Deformable cylinder extraction from LiDAR point cloud using candidate selection by Meng Du, Di Cao, Cheng Wang, Sheng Nie, Jingru Wang

“…Cylinder extraction is a fundamental task in point cloud-based environmental mapping such as tree modeling and reverse engineering. However, current methods are hindered by data missing, and their performance on deformable cylinders remains to be improved. …”
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Human Action Recognition Method Based on Multi-channel Fusion by Zhiyong TAO, Xijun GUO, Xiaokui REN, Ying LIU, Zemin WANG

“…Balancing the characteristics of each channel further improves the accuracy of action recognition.Results and Discussion Comprehensive experiments are conducted on public datasets and in real-world environments to evaluate the effectiveness of the proposed model. …”
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Surface Soil Organic Carbon Estimation Based on Habitat Patches in Southwest China by Jieyun Xiao, Wei Zhou, Ting Wang, Yao Peng, Zhan Shi, Saibo Li, Yang Li, Tianxiang Yue

“…Using the RF feature selection (FS) method to select optimal factors as model input variables improved simulation accuracy compared with using all factors or selecting based on Pearson correlation analysis (R² increased by 1.75%–64.71%). …”
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Application of collaborative innovation between the logical brain and the associative brain in oil and gas gathering and transportation systems by Jing GONG, Siheng SHEN, Daqian LIU, Qi KANG, Shangfei SONG, Haihao WU, Bohui SHI

“…There is an urgent need to overcome bottlenecks in areas such as algorithmic fusion, dynamic data sharing, and deep AI integration to enable a leap from localized optimization to system-wide intelligent decision-making. …”
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Enhanced Real-Time Simulation of ROV Attitude and Trajectory Under Ocean Current and Wake Disturbances by Yujing Zhao, Shipeng Xu, Xiaoben Zheng, Lisha Luo, Boyan Xu, Chunru Xiong

“…Experimental results demonstrate high consistency between the optimized model’s simulation outcomes and theoretical expectations. …”
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Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation by Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi

“…Conclusion The study displayed the effectiveness of psychophysiology-based AI models in predicting rehabilitation engagement, thus promoting their practical application for personalized care and improved clinical health outcomes.…”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…We also evaluated the performance of various algorithms (e.g., Random Forest (RF), Convolutional Neural Networks (CNN), Graph Neural Networks (GNN), and Multi-Layer Perceptron (MLP)) across these models. …”
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An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks by Deyu Lin, Quan Wang, Deqin Lin, Yong Deng

“…The issues which exist in WSNs are proposed and the primary reason why cluster head election is hard to control is then presented. A mathematical model aiming to ease the hot spots problem via optimizing the cluster size is proposed and an optimal cluster size (OCS) algorithm is given firstly. …”
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Research on adaptive motion methods of flexible knee joints based on the artificial potential field by LUO Tianhong, LI Chaoyang, MA Xiangyu, FU Qiang, FANG Shangchen

“…ObjectiveConsidering the tracking error of the motion trajectory of the flexible knee joint and the influence of the flexibility on the joint motion, an adaptive impedance control method based on the artificial potential field (APF) was proposed.MethodsThe method took the pneumatic artificial muscle as the power source, and by establishing a kinetic model between the human-machine interaction moment and the knee joint motion angular velocity, the size of the impedance control parameter could be adjusted in real time, so as to realize the following of the motion of the exoskeleton knee joint and the human leg; the control parameter was optimized using the APF concept to enhance the effect of the motion following, and the effectiveness of the algorithm was verified by simulation and test.ResultsThe results show that the proposed APF-based adaptive impedance control method enables the exoskeleton to adaptively track the human motion trajectory and can reduce the error of trajectory tracking, thus improving the suppleness of the flexible knee joint control and enhancing the human-machine synergy of the system.…”
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Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…To improve decision making, robots need a dependable framework to facilitate communication between different modules and the optimal action for real-world applications. …”
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KOALA: A Modular Dual-Arm Robot for Automated Precision Pruning Equipped with Cross-Functionality Sensor Fusion by Charan Vikram, Sidharth Jeyabal, Prithvi Krishna Chittoor, Sathian Pookkuttath, Mohan Rajesh Elara, Wang You

“…The You Only Look Once v8 (YOLOv8) object detection model powers the plant detection algorithm, achieving a 98.5% pruning plant detection rate and a 95% pruning accuracy using camera, depth sensor, and LiDAR data. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…The purpose of the work is the development of basic data structures, speed-efficient and memoryefficient algorithms for tracking changes in predefined decisions about sets of shortest paths on transport networks, notifications about which are received by autonomous coordinated transport agents with centralized or collective control. …”
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Reliability and Quality of Complex Systems by D.N. Novomeisky, M.N. Piganov, E.T. Eskibaev

“…Purpose – Analysis and evaluation of methodological errors in the process of electrophysical processing of film resistors by high-frequency flare discharge, implemented according to a given algorithm. Materials and methods. Computer modeling, programming, full-scale experiment, expert assessments were used. …”

Multi-dimensional feature extraction of EEG signal and its application in stroke classification by Teng Wang, Wenhui Jia, Fenglian Li, Xirui Liu, Xueying Zhang, Fengyun Hu

“…This study proposes a multi-dimensional feature extraction method based on autocorrelation and complexity theory. It introduces an improved multifractal detrended fluctuation analysis (MFDFA) algorithm based on optimized empirical mode decomposition to extract high-quality autocorrelation features. …”
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Research on Recognition of Green Sichuan Pepper Clusters and Cutting-Point Localization in Complex Environments by Qi Niu, Wenjun Ma, Rongxiang Diao, Wei Yu, Chunlei Wang, Hui Li, Lihong Wang, Chengsong Li, Pei Wang

“…This study compared the performance of multiple You Only Look Once (YOLO) algorithms for recognition and proposed a cluster segmentation method based on K-means++ and a cutting-point localization strategy using geometry-based iterative optimization. …”
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