Sports Motion Recognition Using MCMR Features Based on Interclass Symbolic Distance by Yu Wei, Libin Jiao, Shenling Wang, Rongfang Bie, Yinfeng Chen, Dalian Liu

“…In this paper, we discuss motion recognition in sports training using features extracted from distance estimation of different kinds of sensors. …”
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Machine learning in CTEPH: predicting the efficacy of BPA based on clinical and echocardiographic features by Qiumeng Xi, Juanni Gong, Jianfeng Wang, Xiaojuan Guo, Yuanhua Yang, Xiuzhang lv, Suqiao Yang, Yidan Li

“…SHapley Additive exPlanations (SHAP) values were applied to interpret feature importance of the predictive model. Results A total of 135 patients were included to construct models. 6 features were selected from 49 variables for model training. …”
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A composite Feature Selection Method to improve Classifying Imbalanced Big Data by Shaymaa Razoqi, Ghayda Al-Talib

“…Therefore, this research proposed a composed feature selection method using the filter feature selection technique and permutation-based important features with the ensemble learning method. …”
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Standardized Extraction of Air Traffic Control Hazard Features Based on Expert Knowledge by Xianghua Tan, Zhipeng Cai, Zhibin Quan, Weili Zeng

“…We illustrate the model training process using communication navigation and surveillance (CNS) data, which includes candidate feature generation, feature vectorization, and cluster-based standardization. …”
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A Novel Temporal Footprints-Based Framework for Fake News Detection by Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Ashok Kumar Das, Shehzad Ashraf Chaudhry

“…This research study uses Random Forest (RF) and Bi-LSTM techniques to classify fake news based on temporal features and textual features. …”
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FEATURES OF THE EDUCATIONAL PROCESS IN THE CONTEXT OF THE CORONAVIRUS PANDEMIC (BY THE EXAMPLE OF TEACHING CIVIL LAW) by M. A. Bychko, I. A. Komarevceva

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Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

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Building consistency in explanations: Harmonizing CNN attributions for satellite-based land cover classification by Timo T. Stomberg, Lennart A. Reißner, Martin G. Schultz, Ribana Roscher

“…This is achieved by coherently linking feature representations to attributions derived from analyzing the training data, enabling direct attribution assignment to features in (unseen) images. …”
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Invariant Feature Matching in Spacecraft Rendezvous and Docking Optical Imaging Based on Deep Learning by Dongwen Guo, Shuang Wu, Desheng Weng, Chenzhong Gao, Wei Li

“…Focusing on exploring a new approach as assistance, this study marks the first application of deep learning-based image feature matching in spacecraft docking tasks, introducing the Class-Tuned Invariant Feature Transformer (CtIFT) algorithm. …”
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Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning by Zhangjian Guo, Tongling Wang, Shuxun Chi, Li Huang

“…Abstract This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existing methods in terms of data feature extraction, model complexity, and adaptability to practical applications. …”
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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…To address these gaps, this study proposes a novel framework that integrates bio-inspired feature selection and graph-based deep learning for enhanced sepsis risk prediction. …”
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An intrusion detection method based on system call sequence for train-mounted host devices by WANG Xue, WANG Lide, WANG Biao, XU Shuxian, WANG Chong

“…In case of a cyberattack, the malware will interact with the kernel via the system call and leave a trace. Therefore, the train-mounted host device intrusion can be detected based on system call sequence. …”
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A Lightweight Tri-Stream Feature Fusion Network for Speech Emotion Recognition by Ronghe Cao, Yunxing Wang, Xiaolong Wu, Shuang Jin, Huiling Niu

“…Existing approaches, focusing on prosodic features or deep representations from pre-trained models, often struggle to capture the full spectrum of emotional cues present in real-world speech. …”
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Improved Road Extraction Models through Semi-Supervised Learning with ACCT by Hao Yu, Shihong Du, Zhenshan Tan, Xiuyuan Zhang, Zhijiang Li

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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…Notably, the gradient flow mechanism enriches target feature extraction for moving vessels, thereby improving detection accuracy in wake-disturbed scenarios, while adversarial training further fortifies model resilience. …”
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Bearing fault diagnosis for high-speed train based on improved VMD and APSO-SVM by ZHANG Qingsong, ZHANG Bing, QIN Yi

“…Aiming at the problem that the fault information of high-speed train wheel bearing is weak and difficult to extract, a fault feature extraction and recognition model for vibration signal of high-speed train bearing based on variational mode decomposition and adaptive particle swarm optimization-support vector machine was proposed. …”
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Talent Supply and Demand Matching Based on Prompt Learning and the Pre-Trained Language Model by Kunping Li, Jianhua Liu, Cunbo Zhuang

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KICA-DPCA-Based Fault Detection of High-Speed Train Traction Motor Bearings by Yunkai Wu, Yu Tian, Yang Zhou

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The Research on Diagnosis Technology of High-speed Train Power Chain Based on Electrical Signal by Jianghua FENG

“…Then, based on the theory of multi-feature fusion and machine learning, a new electrical signal diagnosis method was proposed. …”
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Fatigue Load Prediction of Wind Turbine Drive Train Based on CNN-BiLSTM by Xiaodong WANG, Qing LI, Deyi FU, Yingming LIU, Ruojin WANG

“…First, we construct a fatigue load feature database using simulation data from OpenFAST under rated wind speed conditions and above, which is subsequently used for training and testing the model. …”
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