Research Progress on Vehicle Status Information Perception Based on Distributed Acoustic Sensing by Wenqiang Dong, Xin Cheng, Jingmei Zhou, Wei Liu, Jianjin Gao, Chuan Hu, Xiangmo Zhao

“…Distributed Acoustic Sensing (DAS) demonstrates considerable potential in vehicle status perception due to its characteristics such as high spatial resolution and robustness in complex sensing environments. …”
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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

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Sap flow simulation of Cunninghamia lanceolata in degraded red soil region based on back propagation neural network by Tu Jie, Liu Qijing, Wei Jun, Hu Liang

“…Four main factors including air temperature, relative air humidity, average net radiation and vapor pressure deficit were chosen as the input variables, and the sap flow velocity was selected as the output variable, to train and examine the neural network model with Bayesian regularization algorithm and Levenberg-Marquardt algorithm. …”
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Sequence analysis of local indicators of spatio-temporal association for evolutionary pattern discovery by Jianing Yu, Hengcai Zhang, Peixiao Wang, Jinzi Wang, Feng Lu

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Research on Grouting Dynamic Monitoring Based on Borehole–Tunnel Joint Resistivity Method by Cheng Wang, Lei Zhou, Liangjun Yan, Bofan Li

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A COMPREHENSIVE MODEL FOR THE POWER TRANSFORMER DIGITAL DIFFERENTIAL PROTECTION FUNCTIONING RESEARCH by Yu. V. Rumiantsev

“…Digital differential protection blocking algorithms based on the harmonic content were considered. …”
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Research of theoretical basis of implementation of intelligent control systems for locomotive traction transmission by Oleksandr Gorobchenko, Denys Zaika, Sergiy Maliuk, Oleksandr Arkhypov, Oleksandr Nevedrov

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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…This paper systematically reviews the research progress in WEDM process optimization from two main perspectives: traditional optimization methods and artificial intelligence (AI) techniques. …”
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Multi-Scale Feature Fusion and Context-Enhanced Spatial Sparse Convolution Single-Shot Detector for Unmanned Aerial Vehicle Image Object Detection by Guimei Qi, Zhihong Yu, Jian Song

“…Experiments on two datasets (i.e., VisDrone and ARH2000; the latter dataset was created by the researchers) demonstrate that the MFFCESSC-SSD remarkably outperforms the performance of the SSD and numerous conventional object detection algorithms in terms of accuracy and efficiency.…”
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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

“…Next, the main techniques in sequential recommendation are summarized in detail, including: traditional methods based on Markov chains, which model user behavior sequences by relying on state transition probabilities; deep learning-driven methods, which utilize neural network models to capture long-term dependencies and complex patterns; hybrid models, which combine multiple algorithms to enhance the accuracy and robustness of recommendation systems; and emerging methods based on large language models, which improve the understanding of user behavior and recommendation content through the integration of pre-trained large language models. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

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Estimation of overlapped Eye Fixation Related Potentials: The General Linear Model, a more flexible framework than the ADJAR algorithm by Emmanuelle Kristensen, Bertrand Rivet, Anne Guérin-Dugué

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The GRAZ Method—Determination of Urban Surface Temperatures from Aerial Thermography Based on a Three-Dimensional Sampling Algorithm by Daniel Rüdisser, Thomas Posch, Wolfgang Sulzer

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Estimation of Canopy Water Content by Integrating Hyperspectral and Thermal Imagery in Winter Wheat Fields by Chenkai Gao, Shuimiao Liu, Pengnian Wu, Yanli Wang, Ke Wu, Lingyun Li, Jinghui Wang, Shilong Liu, Peimeng Gao, Zhiheng Zhao, Jing Shao, Haolin Yu, Xiaokang Guan, Tongchao Wang, Pengfei Wen

“…Multi-sensor data fusion is one of the solutions to this problem, but suitable spectral preprocessing methods and data fusion methods still need further research. The objectives of this study were to characterize the performance of two varieties at different growth stages under five water stress conditions and screen hyperspectral sensitive spectral bands by using continuous wavelet transform (CWT) and a <b>successive projection algorithm (SPA).…”
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Airway management algorithm during circular tracheal resection in adult patients with cicatricial stenosis (a single-center study) by A. V. Kozhanova, Т. N. Khlan, О. V. Strunin, А. А. Pechetov, К. V. Lukich, A. S. Ibragimov, Yu. G. Starkov

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Research on the Aided Diagnosis Method of Diseases Based on Domain Semantic Knowledge Bases by Deyan Chen, Hong Zhao, Xia Zhang

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A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

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Land surface temperature retrieval from SDGSAT-1: assessment of different retrieval algorithms with different atmospheric reanalysis data by Meng Zhou, Huadong Guo, Xiaoying Ouyang, Dinoo Gunasekera, Zhongchang Sun

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Computational methods for automatic traffic signs recognition in autonomous driving on road: A systematic review by Hui Chen, Mohammed A.H. Ali, Yusoff Nukman, Bushroa Abd Razak, Sherzod Turaev, YiHan Chen, Shikai Zhang, Zhiwei Huang, Zhenya Wang, Rawad Abdulghafor

“…The Traffic sign recognition has been developed to identify various shapes, sizes, orientations, and appearances of signs in diverse conditions. Researchers have proposed numerous algorithms to address these challenges. …”
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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT by Sefri Imanuel Fallo, Lidia Paskalia Nipu

“…This research is primarily dedicated to providing a comprehensive exposition of the methodology applied in the deployment of a cartographic-based machine learning algorithm designed for the precise identification of areas susceptible to landslides within the geographical confines of the Takari District.This research delves into the application of mapping-based machine learning algorithms in the domain of non-structural disaster mitigation, with a specific emphasis on the detection of landslide susceptibility within the Takari District. …”
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