A Lightweight Framework for Rapid Response to Short-Term Forecasting of Wind Farms Using Dual Scale Modeling and Normalized Feature Learning by Yan Chen, Miaolin Yu, Haochong Wei, Huanxing Qi, Yiming Qin, Xiaochun Hu, Rongxing Jiang

“…The model captures both short-term and long-term sequence variations through continuous and interval sampling. To mitigate the interference of dynamic features, we propose a normalization feature learning block (NFLBlock) as the core component of NFLM for processing sequences. …”
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RainHCNet: Hybrid High-Low Frequency and Cross-Scale Network for Precipitation Nowcasting by Lei Wang, Zheng Wang, Wenjun Hu, Cong Bai

“…In addition, a cross-scale supervision module integrates multiscale features from both deep and shallow layers to mitigate information loss. …”
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MCDiff: A Multilevel Conditional Diffusion Model for PolSAR Image Classification by Qingyi Zhang, Xiaoxiao Fang, Tao Liu, Ronghua Wu, Liguo Liu, Chu He

“…Finally, a multilevel high-order statistical feature learning module is introduced to aid in the additive Gaussian noise prediction of noisy labels while mitigating the impact of PolSAR images' multiplicative speckle noise on the prediction. …”
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IEAM: Integrating Edge Enhancement and Attention Mechanism with Multi-Path Complementary Features for Salient Object Detection in Remote Sensing Images by Fubin Zhang, Zichi Zhang

“…The Spatially Adaptive Edge Embedded Module (SAEM) refines object boundary perception, the SCAAP module dynamically selects relevant spatial and channel features while balancing adaptive and maximal pooling, and the Spatial Adaptive Guidance (SAG) module enhances feature localization in cluttered environments to mitigate semantic dilution in U-shaped networks. …”
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A Joint Network of 3D-2D CNN Feature Hierarchy and Pyramidal Residual Model for Hyperspectral Image Classification by Hongwei Wei, Yufan Wang, Yu Sun, Jianfeng Zheng, Xiaodong Yu

“…Since convolutional neural networks (CNN) can extract deeper features from hyperspectral images, they show good classification performance in the hyperspectral image (HSI) classification task. …”
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EBDet: Ellipse Feature Encode and Balanced Decoupling Label Assignment for Arbitrary-Oriented Ship Detection in Optical Remote Sensing Images by Tianqi Zhao, Yunhan Sun, Jin Qian, Zheng Li, Yunxiao Gao, Zhikang Zhao, Yongcheng Wang

“…The dynamic decoupling label assignment (DDLA) strategy adaptively evaluates the sample space sensitivity, and mitigates the feature misalignment problem by decoupling positive samples in classification and regression. …”
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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

“…Additionally, incorporating a feature weighting parameter in the objective function highlights the importance of significant features in creating optimal clusters. …”
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Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired Key Generation and Encryption by Israel Edem Agbehadji, Richard C. Millham, Emmanuel Freeman, Wanqing Wu, Xianbin Zhang

“…In this research, fusing multiple domains ECG feature and adaptive Variational Mode Decomposition approaches are utilized to mitigate the challenge of losing the intra-leading correlations of mode decompositions, which might reduce the robustness of encryption algorithms. …”
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Dynamic process of hydrogen flow and spontaneous combustion in tubes featuring different configurations after leakage from 35 and 70 MPa by Qin Huang, Zuo-Yu Sun, Ya-Long Du, Jia-Ying Li

“…This suggested that measures to mitigate shockwave effects (thus reducing the likelihood of spontaneous combustion) should be implemented in the upstream section of the tubes, regardless of the configuration. …”
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Predicting Tropical Cyclone Extreme Rainfall in Guangxi, China: An Interpretable Machine Learning Framework Addressing Class Imbalance and Feature Optimization by Yuexing Cai, Cuiyin Huang, Fengqin Zheng, Guangtao Li, Sheng Lai, Liyun Zhu, Qiuyu Zhu

“…The framework integrated three supervised learning algorithms, namely XGBoost, Random Forest, and AdaBoost, along with feature selection techniques and an explainable method. …”
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Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China by Yanan Zuo, Min Ji, Jiutao Yang, Zhenjin Li, Jing Wang

“…Finally, integrating natural disaster risk theory, this paper achieved an assessment and zoning of corn borer risk in the study area based on hazard, sensitivity, disaster prevention and mitigation capacity, and comprehensive states. The results indicated that compared with the original RF model, the improved feature optimization model achieves increases of 18.64%, 11.12%, and 11.21% in OOB_score, Accuracy, and F1_score, respectively, and outperforms eight other benchmark models. …”
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SARFA-Net: Shape-Aware Label Assignment and Refined Feature Alignment for Arbitrary-Oriented Object Detection in Remote Sensing Images by Yan Dong, Minghong Wei, Guangshuai Gao, Chunlei Li, Zhoufeng Liu

“…On the other hand, fixed convolution kernels and coarse sampling positions are not well suited for adapting to rotating objects in complex remote sensing scenes, resulting in Feature Misalignment. To alleviate the above issues, in this article, a novel SARFA-Net is proposed, incorporating a Shape-Aware Label Assignment (SALA) strategy and Refined Feature Alignment module (RFAM). …”
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CFNet: Optimizing Remote Sensing Change Detection Through Content-Aware Enhancement by Fan Wu, Sijun Dong, Xiaoliang Meng

“…CFNet employs EfficientNet-B5 as the backbone for feature extraction. To enhance the model’s focus on the content features of images while mitigating the misleading effects of style features, we develop a constraint strategy that prioritizes the content features of bitemporal images, termed Content-Aware. …”
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Neuro-Cells Mitigate Amyloid Plaque Formation and Behavioral Deficits in the APPswe/PS1dE9 Model of Alzheimer Disease While Also Reducing IL-6 Production in Human Monocytes by Johannes de Munter, Kirill Chaprov, Ekkehard Lang, Kseniia Sitdikova, Erik Ch. Wolters, Evgeniy Svirin, Aliya Kassenova, Andrey Tsoy, Boris W. Kramer, Sholpan Askarova, Careen A. Schroeter, Daniel C. Anthony, Tatyana Strekalova

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Change-Guided Difference Interaction Attention Network for Remote Sensing Change Detection by Canbin Hu, Sida Du, Hongyun Chen, Xiaokun Sun, Kailun Liu

“…However, many existing methods struggle to extract change-relevant features when faced with dual-temporal remote sensing images characterized by inconsistent and complex feature distributions, leading to false alarms. …”
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Dense-ShuffleGCANet: An Attention-Driven Deep Learning Approach for Diabetic Foot Ulcer Classification Using Refined Spatio-Dimensional Features by Armaano Ajay, Akshaj Singh Bisht, R. Karthik

“…Timely intervention and treatment are crucial in mitigating the impact of DFU on patients’ well-being. …”
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Leverage Gaussian Interpolation Features Extraction and Advanced Encode–Decode Models for 2D Steady State Flows Estimation by Thi-Thu-Huong Le, Changwoo Choi, Junyoung Son, Howon Kim

“…This paper introduces a novel approach that combines Gaussian interpolation-based feature extraction with advanced encode-decode models, including AutoEncoder, UNet, and DeepLabV3+. …”
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Phytobacter sp. RSE02 is a rice seed endophytic plant probiotic bacterium with human probiotic features and cholesterol-lowering ability by Santosh Kumar Jana, Rajarshi Bhattacharya, Sunanda Mukherjee, Samudra Gupta, Subhra Prakash Hui, Ansuman Chattopadhyay, Swadesh Ranjan Biswas, Sukhendu Mandal

“…RSE02, which demonstrates distinctive beneficial probiotic features in animal models. We examine the safety and probiotic potential of RSE02 in human cell lines, zebrafish, and mice. …”
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The protective effect of Chlorella vulgaris against diclofenac toxicity in Clarias gariepinus: haemato-immunological parameters and spleen histological features as outcome markers by Ahmed Gabr, Amr M. Mohamed, Amr M. Mohamed, Nasser S. Abou Khalil, Nasser S. Abou Khalil, Alaa El-Din H. Sayed, Alaa El-Din H. Sayed

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Digital Twin Simulation and Implementation in Safety Risk Management Process by Gravito Eko Virando, Bogyeong Lee, Seong-Hoon Kee, Jurng-Jae Yee

“…This study showcases the latest DT technology trends by listing DTs’ expected features and practical twinning processes while underscoring the constraints and unresolved problems in adopting DTs for safety risk management.…”
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