An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…The IGTO algorithm is used to optimize the parameters of VMD and LSTM, enhancing signal decomposition and feature extraction. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Addressing the longitudinal nature of aircraft flight parameter time series, a long temporal correlation attention (LTCA) mechanism is designed for feature extraction, enhancing spatiotemporal correlation representation. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…In this paper, we propose a multimodality image registration network based on multistage transformation enhancement features (MTEF) to maintain the continuity of the deformation field. …”
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CosPoint Transformer: Enhancing 3-D Semantic Segmentation With Cosine Similarity Attention and Cross-Attention by Thien Huynh-The, Minh-Thanh Le, Won Jae Ryu, Anh-Kiet Vo

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HP-YOLO: A Lightweight Real-Time Human Pose Estimation Method by Haiyan Tu, Zhengkun Qiu, Kang Yang, Xiaoyue Tan, Xiujuan Zheng

“…We designed an Enhanced Large Separated Kernel Attention (ELSKA) mechanism and integrated it into the backbone network, thereby improving the model’s effective receptive field and feature separation capabilities, which enhances keypoint detection accuracy in challenging environments. …”
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Machine Learning in the Design and Performance Prediction of Organic Framework Membranes: Methodologies, Applications, and Industrial Prospects by Tong Wu, Jiawei Zhang, Qinghao Yan, Jingxiang Wang, Hao Yang

“…Methodologically, ML workflows—spanning data construction, feature engineering, and model optimization—accelerate candidate screening, inverse design, and mechanistic interpretation, as demonstrated in gas separations and nascent liquid-phase applications. …”
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Synthesis of Pyrazolone Derivatives and Their Nanometer Ag(I) Complexes and Physicochemical, DNA Binding, Antitumor, and Theoretical Implementations by Ismail Althagafi, Nashwa M. El-Metwaly, Marwa G. Elghalban, Thoraya A. Farghaly, Abdalla M. Khedr

“…Kinetic studies yield essential parameters to assert on the rule of metal atom on thermal feature of organic compounds. …”
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Lightweight RT-DETR with Attentional Up-Downsampling Pyramid Network by Nan Li, Xiao Han, Xingguo Song, Xu Fang, Mengming Wu, Qiulin Yu

“…This lightweight, efficient design integrates YOLOv9’s ADown module, the RepNCSPELAN4 module, and custom attention-based AdaptiveGateUpsample and AdaptiveGateDownsample modules for enhanced multi-scale feature fusion, reducing weight and complexity while optimizing real-time detection. …”
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A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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A Dual-channel Progressive Graph Convolutional Network via subgraph sampling by Wenrui Guan, Xun Wang

“…To enhance the representation power, we construct a dual channel fusion module by using both the geometric information of the node feature and the original topology. Specifically, we evaluate the complementary information of the dual channels based on the joint entropy between the feature information and the adjacency matrix, and effectively reduce the information redundancy by reasonably selecting the feature information. …”
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Chest CT in Pulmonary Fibrosis: A Narrative Review of Imaging Patterns and Their Prognostic Significance by Mehrshad Dabbagh, Mohammad Amin Shajareh Pour Salavati, Yas Zeinaly Parizi

“…We conducted a literature review of studies published between 2010 and 2025 using PubMed, Scopus, and Web of Science, focusing on CT features, subtype differentiation, prognostic imaging biomarkers, and recent innovations in radiomics and artificial intelligence (AI). …”
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Enhancing Undrained Shear Strength Prediction through Innovative Hybridization Techniques by Chisom Samuel, Damilare Adewunmi

“…The issue is addressed by employing cutting-edge data-driven Decision Tree (DT) techniques to analyze the intricate connections between USS and fundamental soil parameters. An innovative approach for predicting USS in soft clays using machine learning methods is pioneered in this study, with a specific focus on a set of five crucial feature variables, such as pre-consolidation stress (PS), vertical effective stress (VES), liquid limit (LL), plastic limit (PL), and natural water content (W), which serve as inputs for the data-driven models. …”
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Human Activity Recognition Based on Point Clouds from Millimeter-Wave Radar by Seungchan Lim, Chaewoon Park, Seongjoo Lee, Yunho Jung

“…The proposed HAR system uses a pillar feature encoder that converts 3D point-cloud data into a 2D image and a classification network based on depth-wise separable convolution for lightweighting. …”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. …”
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Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis by Mostafa Alizade-Harakiyan, Amin Khodaei, Ali Yousefi, Hamed Zamani, Asghar Mesbahi

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Machine learning-based approach for bandwidth and frequency prediction of circular SIW antenna by Md Mahabub Alam, Nurhafizah Abu Talip Yusof, Ahmad Afif Mohd Faudzi, Md Raihanul Islam Tomal, Md Ershadul Haque, Md. Suaibur Rahman

“…Abstract Machine Learning (ML) has significantly transformed antenna design by enabling efficient optimization of geometrical parameters, modeling complex electromagnetic behavior, and accelerating performance prediction with reduced computational cost. …”
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Construction of a model of subsoil moisture movement in cultivated slope lands by Andrey A. Mikhaylin

“…Insufficient study of the dynamics of moisture movement both in the soil loosened by the tillage tool and in the zone of uncultivated subsoil wall in the conditions of moisture deficient south of Russia necessitated for development of a mathematical model of subsoil moisture transfer. A distinctive feature of this model is the study of moisture transfer in the zone of the upper soil layer of 0.60 m by the developed universal tillage tool for cultivating of sloping and plain lands. …”
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SBCS-Net: Sparse Bayesian and Deep Learning Framework for Compressed Sensing in Sensor Networks by Xianwei Gao, Xiang Yao, Bi Chen, Honghao Zhang

“…The core of SBCS-Net is to optimize key SBL parameters through end-to-end learning. This can adaptively improve signal sparsity and probabilistically process measurement noise, while fully leveraging the powerful feature extraction and global context modeling capabilities of deep learning modules. …”
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Progressive Conditional Diffusion Model for Multistage Spectral Restoration of Remote Sensing Image by Jinfeng Gao, Gangqiang Li, Ruxian Yao, Qiang Liu, Junming Zhang

“…The spectral-up-sampled multispectral features, combined with the output from the previous diffusion model, serve as a conditional matrix, which is input into the next diffusion model to obtain the final result. …”
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PS-YOLO: A Lighter and Faster Network for UAV Object Detection by Han Zhong, Yan Zhang, Zhiguang Shi, Yu Zhang, Liang Zhao

“…This detection head effectively increases inference speed without significantly increasing parameter counts. The proposed PS-YOLO is validated on the Visdrone2019 dataset, and the results demonstrate that PS-YOLO provides a 2% improvement in precision, 0.5% improvement in recall, 1.3% improvement in mean average precision (mAP), 41.3% reduction in parameter counts, 6.1% reduction in computational cost, and 26.73 FPS improvement in inference speed compared to the benchmark model YOLOv11-s.…”
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