Optimizing machine learning methods for groundwater quality prediction: Case study in District Bagh, Azad Kashmir, Pakistan by Usman Basharat, Wenjing Zhang, Cuihong Han, Shoukat Husain Khan, Arshad Abbasi, Sehrish Mahroof, Shuxin Li

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MAK-Net: A Multi-Scale Attentive Kolmogorov–Arnold Network with BiGRU for Imbalanced ECG Arrhythmia Classification by Cong Zhao, Bingwei Lai, Yongzheng Xu, Yiping Wang, Haorong Dong

“…We further mitigate imbalance by synergistically applying focal loss and the Synthetic Minority Oversampling Technique (SMOTE). …”
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Systematic Approach for Malware Detection in IoT Devices: Enhancing Security and Performance by Vasudeva Pai, B. H. Karthik Pai, G. S. Sudhiksha, Vandya Kamath, K. Varsha, S. Manjunatha

“…These include ensemble methods such as Bagging, Stacking, Voting, AdaBoost, and H2O AutoML, as well as advanced models such as sparse neural networks with pruning and feature selection and regularized classifiers L1. …”
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Machine learning for early detection of plant viruses: Analyzing post-infection electrical signal patterns by Elham Ghasemi, Esmaeil Ebrahimie, Ali Niazi

“…Through precise feature selection techniques, and using only three key features—Median, Autoregressive coefficients, and Autocorrelation—machine learning models, including Support Vector Machine, K-Nearest Neighbors, and Random Forest, achieved approximately 97% accuracy in detecting virus-infected plants even before the appearance of visual symptoms. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…This paper also introduces the Non_Local attention mechanism to integrate the position information of human key points in the image into the channel dimension, thereby enhancing the efficiency of feature extraction and mitigating the accuracy degradation issues that often occur after model lightweighting. …”
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Automated Generation of Geometric FE Models for Timber Structures Using 3D Point Cloud Data by Lin Chen, Liufang Jiang, Haibei Xiong

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A deep dive into artificial intelligence with enhanced optimization-based security breach detection in internet of health things enabled smart city environment by S Jayanthi, Sodagudi Suhasini, N. Sharmili, E. Laxmi Lydia, V. Shwetha, Bibhuti Bhusan Dash, Mrinal Bachute

“…For the selection of the feature process, the proposed SADDBN-AMOA model designs a slime mould optimization (SMO) model to select the most related features from the data. …”
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Using multisource satellite products to estimate forest aboveground biomass in Oita prefecture: a novel approach with improved accuracy and computational efficiency by Hantao Li, Tomomichi Kato, Masato Hayashi, Jianhong Liu

“…Together, this study provides a valuable strategy for feature selection to lessen multicollinearity and redundancy.…”
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PEYOLO a perception efficient network for multiscale surface defects detection by Xun Li, Yuzhen Zhao, Xiangke Jiao, Qingzhe Meng, Zhun Guo, Ruijuan Yao, Yaqiao Yang, Baoxi Yuan

“…First, we introduce the Defect Capture Path Aggregation Network, which enhances the feature fusion network’s ability to learn multi-scale representations. …”
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DIO-SLAM: A Dynamic RGB-D SLAM Method Combining Instance Segmentation and Optical Flow by Lang He, Shiyun Li, Junting Qiu, Chenhaomin Zhang

“…Feature points from moving objects can negatively impact the accuracy of Visual Simultaneous Localization and Mapping (VSLAM) algorithms, while detection or semantic segmentation-based VSLAM approaches often fail to accurately determine the true motion state of objects. …”
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An Accurate Altimetry Method for High-Altitude Airburst Fuze Based on Two-Dimensional Joint Extension Characteristics by Liwen Pan, Yao Zhang, Qianyu Wang, Shuhuan He, Xi Pan

“…Considering the challenge of precise altimetry for high-altitude airburst fuzes, this paper proposes a two-dimensional joint extension characteristic altimetry method based on an improved constant false alarm rate (CFAR) detection and an accurate feature region extraction approach. First, an improved CFAR detection method with secondary protection windows is introduced to effectively mitigate the masking effect caused by conventional CFAR algorithms. …”
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Dynamic cobble berm revetments: the state of the practice and a proposed design process by Hailey G. Bond, Meagan E. Wengrove, Chris E. Blenkinsopp, Paul M. Bayle, George M. Kaminsky, Jonathan C. Allan, David R. Michalsen, Kayla S. Ostrow, Hans Rod Moritz

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MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images by Huinan Guo, Congying Sun, Jing Zhang, Wuxia Zhang, Nengshuang Zhang

“…This network utilizes cosine similarity to divide the original features into common features and specific features, which are then refined and fused through specific modules. …”
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Multi-Scale Differentiated Network with Spatial–Spectral Co-Operative Attention for Hyperspectral Image Denoising by Xueli Chang, Xiaodong Wang, Xiaoyu Huang, Meng Yan, Luxiao Cheng

“…The DMF module adopts a multi-branch parallel structure with differentiated processing to dynamically fuse multi-scale spatial–spectral features and incorporates a cross-scale feature compensation strategy to improve feature representation and mitigate information loss. …”
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FTDZOA: An Efficient and Robust FS Method with Multi-Strategy Assistance by Fuqiang Chen, Shitong Ye, Lijuan Xu, Rongxiang Xie

“…Feature selection (FS) is a pivotal technique in big data analytics, aimed at mitigating redundant information within datasets and optimizing computational resource utilization. …”
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Unveiling the metabolic fate of drugs through metabolic reaction-based molecular networking by Haodong Zhu, Xupeng Tong, Qi Wang, Aijing Li, Zubao Wu, Qiqi Wang, Pei Lin, Xinsheng Yao, Liufang Hu, Liangliang He, Zhihong Yao

“…A minimum 75% correlation between structural similarity and MS2 similarity of neighboring metabolites was ensured, mitigating false negatives due to spectral feature degradation. …”
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Dual-Scale Complementary Spatial-Spectral Joint Model for Hyperspectral Image Classification by Huayue Chen, Yue Sun, Xiang Li, Bochuan Zheng, Tao Chen

“…In essence, the final classification result is obtained through decision fusion of two complementary feature extraction stages. In the preprocessing stage, a new dual-scale truncated filtering feature extraction method (DTFE) is proposed, which uses truncated filters with two different parameter settings to obtain two scales of smoothed patches, and then fuses them to obtain dual-scale structural features using Kernel principal component analysis. …”
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MC-ASFF-ShipYOLO: Improved Algorithm for Small-Target and Multi-Scale Ship Detection for Synthetic Aperture Radar (SAR) Images by Yubin Xu, Haiyan Pan, Lingqun Wang, Ran Zou

“…Two key innovations distinguish our approach: (1) We introduce a Monte Carlo Attention (MCAttn) module into the backbone network that employs random sampling pooling operations to generate attention maps for feature map weighting, enhancing focus on small targets and improving their detection performance. (2) We add Adaptively Spatial Feature Fusion (ASFF) modules to the detection head that adaptively learn spatial fusion weights across feature layers and perform dynamic feature fusion, ensuring consistent ship representations across scales and mitigating feature conflicts, thereby enhancing multi-scale detection capability. …”
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XAI-XGBoost: an innovative explainable intrusion detection approach for securing internet of medical things systems by Yousif Hosain, Muhammet Çakmak

“…The proposed approach integrates a hybrid random sampling technique to mitigate class imbalance, Recursive Feature Elimination (RFE) for feature selection, and an optimized XGBoost classifier for robust attack detection. …”
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Enhanced YOLOv5s Model for Improved Multi-Sized Object Detection in Road Scenes by Sangavi Sivanandham, Dharanibai Gunaseelan

“…To improve the feature fusion process, a Multi-scale BiFPN block is integrated into the neck of the model. …”
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