Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

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Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

“…Subsequently, the computed indicator and operating speed are used as input features to train, test, and validate an RF model. …”
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Fluid volume status detection model for patients with heart failure based on machine learning methods by Haozhe Huang, Jing Guan, Chao Feng, Jinping Feng, Ying Ao, Chen Lu

“…Data from 186 heart failure patients collected between January 2022 and July 2022 were employed as an external validation set to investigate the effects of model training. SHapley Additive exPlanations (SHAP) were used to interpret the ML models Results: Thirty features were selected for model development, and the area under the ROC curve AUC (95 % CI) for the four machine learning models in the testing set was 0.75 (0.73–0.77), 0.77 (0.74–0.79), 0.70 (0.67–0.73), and 0.76 (0.73–0.78), and the AUC (95 % CI) in the external validation set was 0.74 (0.71–0.76), 0.70 (0.67–0.73), 0.64 (0.59–0.68), and 0.67 (0.63–0.71). …”
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Extended Analysis of Simulation Paradigms and Development of a Mesoscopic Model Based on the Discrete Time Paradigm by Tolujevs Jurijs, Zhumanov Azat, Kegenbekov Zhandos

“…The practical part of the work describes a simulation model of container train movement processes across the territory of the Republic of Kazakhstan. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…The first is a new sample selection method which combines block-based sampling with spatial features extracted by single or multiple windows. …”
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Two‐stage video anomaly detection based on dual‐stream networks and multi‐instance learning by Dejun Zhang, Wenbo Fang, Yuhang Liu, Zirong Lyu, Chen Xiong, Zhan Wang

“…First, the I3D network is used as a feature extractor to capture spatiotemporal features from the input video. …”
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MUF-Net: A Novel Self-Attention Based Dual-Task Learning Approach for Automatic Left Ventricle Segmentation in Echocardiography by Juan Lyu, Jinpeng Meng, Yu Zhang, Sai Ho Ling

“…These two tasks are then jointly trained using a temporal consistency mechanism to extract spatio-temporal features across frames. …”
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Fingerprint Matching for Noisy and Distorted Patterns Using a Siamese Network With ResNet50 and Multihead Attention by Tinny Sawhney, Ashu Sharma, Pawanesh Abrol, Parveen Kumar Lehana, Chaahat, Vaishali Yadav, Rafal scherer, Oleksii Kulakov, Ahmad Ali Alzubi

“…The proposed system was trained on the Sokoto coventry fingerprint dataset (SOCOFing) and a custom dataset. …”
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A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study by Lingfeng Zhang, Gang Xie, Yue Zhang, Yue Zhang, Junlin Li, Junlin Li, Wuli Tang, Wuli Tang, Ling Yang, Ling Yang, Kang Li

“…The radiomics features linked to MCE were pinpointed through a consistency test, Student’s t test and the least absolute shrinkage and selection operator (LASSO) method for selecting features. …”
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Feature-Driven EnsembleX: An Advanced Ensemble Framework for Enhanced MRI Abdomen Image Classification Using Feature Refinement and Boosting Techniques by Snehal V. Laddha, Rohini S. Ochawar

“…To refine the extracted features, Principal Component Analysis (PCA) was used to reduce dimensionality, followed by Recursive Feature Elimination (RFE) to select the most relevant attributes for classification. …”
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An End-to-End General Language Model (GLM)-4-Based Milling Cutter Fault Diagnosis Framework for Intelligent Manufacturing by Jigang He, Xuan Liu, Yuncong Lei, Ao Cao, Jie Xiong

“…Further robustness and noise-resistance analyses confirm its stability under varying SNR levels (10 dB to −10 dB) and limited training samples. This work highlights the potential of integrating domain-specific feature engineering with LLMs to advance intelligent manufacturing diagnostics.…”
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Retrieval of Passive Seismic Virtual Source Data Under Non-Ideal Illumination Conditions Based on Enhanced U-Net by Wensha Huang, Pan Zhang, Binghui Zhao, Donghao Zhang, Liguo Han

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AttenFlow: Context-Aware Architecture with Consensus-Based Retrieval and Graph Attention for Automated Document Processing by Xianfeng Zhang, Bin Hu, Shukan Liu, Qiao Sun, Lin Chen

“…Second, we develop adversarial mutual-attention hybrid-dimensional graph attention network (AM-HDGAT) for text, which transforms document classification by modeling inter-document relationships through graph structures while integrating high-dimensional semantic features and low-dimensional statistical features through mutual-attention mechanisms. …”
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A Driver Behavior Detection Model for Human-Machine Co-Driving Systems Based on an Improved Swin Transformer by Junhua Cui, Yunxing Chen, Zhao Wu, Huawei Wu, Wanghao Wu

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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

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Research on Vehicle Lane Change Intent Recognition Based on Transformers and Bidirectional Gated Recurrent Units by Dan Zhou, Yujie Chen, Kexing Fan, Qi Bai, Yong Luo, Guodong Xie

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MCT-CNN-LSTM: A Driver Behavior Wireless Perception Method Based on an Improved Multi-Scale Domain-Adversarial Neural Network by Kaiyu Chen, Yue Diao, Yucheng Wang, Xiafeng Zhang, Yannian Zhou, Minming Gu, Bo Zhang, Bin Hu, Meng Li, Wei Li, Shaoxi Wang

“…In the final step, domain-adversarial training is applied to extract common features from both the source and target domains, which helps reduce the domain shift. …”
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CLIP-Llama: A New Approach for Scene Text Recognition with a Pre-Trained Vision-Language Model and a Pre-Trained Language Model by Xiaoqing Zhao, Miaomiao Xu, Wushour Silamu, Yanbing Li

“…The visual branch provides initial predictions based on image features, while the cross-modal branch refines these predictions by addressing the differences between image features and textual semantics. …”
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Physical and psychological optimization of tele-exercise programs by establishing guidelines by Manuela Cantoia, Giovanna Zimatore, Barbara Matteo, Martina Sausa, Antonio Fabbrizio, Andrea De Giorgio, Angilletta Sonia, Nuno Domingos Garrido, Victor Machado Reis, José Manuel Vilaça-Alves, Gabriela Chaves Lucas, Rafael Peixoto, Filippo Macaluso, Carlo Baldari, Alberto Fucarino, Enzo Iuliano

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A deep biometric hash learning framework for three advanced hand‐based biometrics by Huikai Shao, Dexing Zhong, Xuefeng Du

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