Problems and perspectives of family doctors training on the undergraduate stage by Yu. M. Kolesnik, V. D. Syvolap, N. S. Mikhaylovskaya, T.O. Kulinich

“…Under healthcare reform activities of all medical schools and post-graduate education institutions are directed to improvement of the effectiveness of high-qualified family doctors training. …”
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Brown Rice Germ Integrity Identification Based on Deep Learning Network by Shuofeng Li, Bing Li, Jin Li, Bin Liu

“…This paper improves the brown rice (BR) segmentation algorithm based on background skeleton. …”
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A long-term localization and mapping system for autonomous inspection robots in large-scale environments using 3D LiDAR sensors. by Wandeng Mao, Liang Jiang, Shanfeng Liu, Shengzhe Xi, Hua Bao

“…Then, to address drift errors, we formulate the global map as a graph of local submaps that undergo global optimization. Furthermore, we utilize marching cubes to generate a mesh model of the map. …”
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The artificial intelligence-based agricultural field irrigation warning system using GA-BP neural network under smart agriculture. by Xiying Wang

“…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …”
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Broad learning system based on attention mechanism and tracking differentiator by LIAO Lüchao, ZOU Weidong, YANG Jialong, LU Huihuang, XIA Yuanqing, GAO Jianlei

“…To alleviate these problems, broad learning system based on attention mechanism and tracking differentiator (TD), abbreviated as A-TD-BLS, was proposed. In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
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Enhancing Spreading Factor Assignment in LoRaWAN with a Geometric Distribution Approach for Practical Node Distributions by Phanupong Tempiem, Rardchawadee Silapunt

“…By leveraging the Probability Mass Function (PMF) of the GD model, the algorithm effectively addresses biased node distributions encountered in real-world scenarios. …”
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Research on a UAV-View Object-Detection Method Based on YOLOv7-Tiny by Yuyang Miao, Xihan Wang, Ning Zhang, Kai Wang, Lianhe Shao, Quanli Gao

“…Experiments conducted on the VisDrone2019 dataset show that the improved algorithm achieves a mAP@0.5 of 38.2%, with a model size of 29.01 MB and a computational complexity of 16.2 G. …”
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Real-time Detection of Imperfect Wheat Grains on Wheat Pile Surface Based on IDS-YOLO by FAN Jiawei, WU Lan, YAN Jingjing

“…To address the high missed detection rate of imperfect grains in target detection algorithms and to enhance the model detection speed, this study optimized the lightweight network model YOLOV4-Tiny. …”
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基于分层模糊优化的湿式多片离合器起步控制研究 by 闫光辉, 关志伟, 童敏勇

“…According to the control theory of wet multi-plate clutch and starting process,taking full account of starting impact and sliding friction works,the starting process is analyzed and the control parameters of each starting process are selected.And then the hierarchical fuzzy optimization control strategy of clutch engagement occupation-empty ratio is proposed,which means the first analysis of starting intention,followed by initial occupation-empty ratio control,and finally to optimize occupation-empty ratio.Based on the control strategy,the control model and algorithm of hierarchical fuzzy optimization is designed.After vehicle simulation and compare with other control strategies,the results show that the strategy can effectively identify the driver’s starting intention,improve the smoothness of the wet clutch and reduce the starting impact and sliding friction works.…”
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Comparative techno-economic analysis of grid-connected solar PV-battery and PV-fuel cell systems for educational institutions sustainable academic laboratories by Takele Ferede Agajie, Fuseini Seidu Ibrahim, Isaac Amoussou, Elsabet Ferede Agajie, Eriisa Yiga Paddy, Yayehyirad Ayalew Awoke, Wirnkar Basil Nsanyuy, Mohit Bajaj

“…Techno-economic decision criteria were implemented using MATLAB. Three algorithms were used: Teaching–Learning-Based Optimization (TLBO), Water Cycle Algorithm (WCA), and Improved Grey Wolf Optimization (I-GWO). …”
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Prediction of Bus Arrival Time Based on Gated Recurrent Unit Neural Networks by LU Juntian;SUN Ling;SHI Quan

“…Furthermore, combining more than 50 million pieces of raw data, the model uses Spark elastic distributed data set in distributed Hadoop cluster to clean data and site matching algorithm to match source data, Lasso algorithm to optimize feature options and remove interference. …”
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Development and evaluation of customized software to automatically align macula and optic disc centered scanning laser ophthalmoscope fundus images by M. Elena Martinez-Perez, Franziska G. Rauscher, Pingping Zhao, Tobias Elze

“…BloodVesselReg implements an image registration and mosaicing algorithm based on retinal blood vessels. OCTFundusReg optimizes a general-purpose image registration toolkit to operate on SLO images. …”
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Bike-Sharing Static Rebalancing by Considering the Collection of Bicycles in Need of Repair by Sheng Zhang, Guanhua Xiang, Zhongxiang Huang

“…A hybrid Discrete Particle Swarm Optimization (DPSO) algorithm was proposed to solve the model, which incorporates a reduced variable neighborhood search (RVNS) functionality together with DPSO to improve the global optimization performance. …”
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Cross-modal adaptive reconstruction of open education resources by Tang Shengju, Feng Li, Zhan Wang, Xie Zhaoyuan

“…DKG-CMR focuses on three key improvements: (1) Aligning meaning across different data types (e.g., text, video, user behavior logs). (2) Maintaining the knowledge graph’s real-time relevance. (3) Reducing the cognitive demand of recommendations (optimizing cognitive efficiency). …”
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Research status and prospect of UWB radar echo signal processing technology for mine rescue by Xuezhao ZHENG, Chaoyang SUN, Yuan HUANG, Wen DING, Yang MA, Qiang LI, Haowei MOU

“…In view of the existing problems, the future development trend of UWB radar life information detection echo signal processing technology is proposed: the mine clutter model is constructed and the real-time adaptive filtering algorithm is studied. …”
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Unstructured road semantic segmentation method based on 3D point cloud of open pit mine by Caiwu LU, Jianan XUE, Meng LI, Shengyu YAN, sai ZHANG, Song JIANG, Runfeng HE

“…Based on SFM and MVS algorithms for dense point cloud reconstruction of captured multi-viewpoint images, and optimization and improvement of PointNet++, MLP, channel attention mechanism, and self-attention mechanism based on point attention are introduced, and a point cloud semantic segmentation model for unstructured roads in open-pit mines is designed. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. …”
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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Digital Inspection Technology for Sheet Metal Parts Using 3D Point Clouds by Jian Guo, Dingzhong Tan, Shizhe Guo, Zheng Chen, Rang Liu

“…The improved iterative closest point (ICP) algorithm, used for fine registration, can enhance the registration accuracy and efficiency. …”
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