Enhancing Heart Disease Diagnosis Using ECG Signal Reconstruction and Deep Transfer Learning Classification with Optional SVM Integration by Mostafa Ahmad, Ali Ahmed, Hasan Hashim, Mohammed Farsi, Nader Mahmoud

“…<b>Background/Objectives:</b> Accurate and efficient diagnosis of heart disease through electrocardiogram (ECG) analysis remains a critical challenge in clinical practice due to noise interference, morphological variability, and the complexity of overlapping cardiac signals. …”
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WDNET-YOLO: Enhanced Deep Learning for Structural Timber Defect Detection to Improve Building Safety and Reliability by Xiaoxia Lin, Weihao Gong, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Yingzhou Meng, Xinyue Xiao, Junyan Zhang

“…Second, the ECA attention mechanism dynamically suppresses complex wood grain interference and enhances the discriminative feature representation between high-risk defect classes (e.g., cracks vs. knots). …”
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HorGait: Advancing Gait Recognition With Efficient High-Order Spatial Interactions in LiDAR Point Clouds by Jiaxing Hao, Yanxi Wang, Zhigang Chang, Hongmin Gao, Zihao Cheng, Chen Wu, Xin Zhao, Peiye Fang, Rachmat Muwardi

“…Due to the limitation in spatial perception capability inherent in 2D gait representations, LiDAR can directly capture 3D gait features and represent them as point clouds, reducing environmental and lighting interference in recognition while significantly advancing privacy protection. …”
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Smart reconfigurable metadevices made of shape memory alloy metamaterials by Shiqiang Zhao, Yuancheng Fan, Ruisheng Yang, Zhehao Ye, Fuli Zhang, Chen Wang, Weijia Luo, Yongzheng Wen, Ji Zhou

“…Here, we propose and experimentally demonstrate that integrating metamaterial design principles with the intrinsic features of natural materials can engineer thermal smart metadevices. …”
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Noise Robust Underwater Fishing Net Recognition Based on Range Gated Imaging by Zhensong Xu, Xinwei Wang, Liang Sun, Bo Song, Yue Zhang, Pingshun Lei, Jianan Chen, Jun He, Yan Zhou, Yuliang Liu

“…Comprehensive experiments on the test data show that SFNR-Net can effectively solve noise interference and achieve the best recognition accuracy of 96.28% compared with existing methods. …”
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Verification of a Probabilistic Model and Optimization in Long-Range Networks by José Luis Romero Vázquez, Abel García-Barrientos, José Alberto Del-Puerto-Flores, Francisco R. Castillo Soria, Roilhi F. Ibarra-Hernández, Ulises Pineda Rico, Ernesto Zambrano-Serrano

“…By incorporating these variables into a unified probabilistic framework, the model not only predicts packet loss and interference patterns but also provides insights into optimizing network parameters. …”
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Trigger-Free and Low-Cross-Sensitivity Displacement Sensing System Using a Wavelength-Swept Laser and a Cascaded Balloon-like Interferometer by Jianming Zhou, Jinying Fan, Junkai Zhang, Jianping Yao, Jiejun Zhang

“…At the same time, the temperature cross-sensitivity is as low as 5 pm/°C or 0.25 ms/°C, making it a strong candidate for displacement sensing in harsh environments with significant temperature interference.…”
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The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

“…The existing identification systems and methods do not completely solve the problem of identification, namely, identification in difficult conditions: interference, lighting, various changes on the face, etc. …”
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NSMO-Based Adaptive Finite-Time Command-Filtered Backstepping Speed Controller for New Energy Hybrid Ship PMSM Propulsion System by Dan Zhang, Suijun Xiao, Hongfen Bai, Diju Gao, Baonan Wang

“…In this paper, a novel Adaptive Finite-Time Command-Filtered Backstepping Controller (AFTCFBC) is proposed, featuring a faster response time and the elimination of overshoot. …”
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Research on Interval Probability Prediction and Optimization of Vegetation Productivity in Hetao Irrigation District Based on Improved TCLA Model by Jie Ren, Delong Tian, Hexiang Zheng, Guoshuai Wang, Zekun Li

“…This model employs TTHHO to effectively navigate the search space and adaptively optimize network node positions, integrates CNN-LSSVM for feature extraction and regression analysis, and incorporates ABKDE for probability density function estimation and outlier detection, resulting in accurate interval probability prediction and enhanced model resilience to interference. …”
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Sorting misorganized books in libraries based on ant colony algorithm by Ling Chen

“…In the anti-noise interference test, the algorithm reduced the false detection rate of the Aerial dataset from 22.3 % of ACO to 9.8 % through the neighborhood gray-scale fusion mechanism of two-dimensional OTSU. …”
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A new-generation internal tide model based on 30 years of satellite sea surface height measurements: multiwave decomposition and isolated beams by Z. Zhao, Z. Zhao

“…The decomposition reveals unprecedented features previously masked by multiwave interference. …”
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kMetha-Mamba: K-means clustering mamba for methane plumes segmentation by Yuquan Liu, Hailiang Shi, Ke Cao, Shichao Wu, Hanhan Ye, Xianhua Wang, Erchang Sun, Yunfei Han, Wei Xiong

“…They are also susceptible to interference from species with similar spectral features, resulting in high false positive rates. …”
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Efficient one-stage detection of shrimp larvae in complex aquaculture scenarios by Guoxu Zhang, Tianyi Liao, Yingyi Chen, Ping Zhong, Zhencai Shen, Daoliang Li

“…Firstly, different from the ordinary detection methods, it exploits an efficient FasterNet backbone, constructed with partial convolution, to extract effective multi-scale shrimp larvae features. Meanwhile, we construct an adaptively bi-directional fusion neck to integrate high-level semantic information and low-level detail information of shrimp larvae in a matter that sufficiently merges features and further mitigates noise interference. …”
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Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring by Sui Zhende, Zhang Ke, Zhang Kai, Lin Qibin

“…By synergistically employing Fast Fourier Transform (FFT) and Empirical Mode Decomposition (EMD), high-frequency noise interference within the seismic signals is effectively mitigated, yielding more robust signal features. …”
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DermViT: Diagnosis-Guided Vision Transformer for Robust and Efficient Skin Lesion Classification by Xuejun Zhang, Yehui Liu, Ganxin Ouyang, Wenkang Chen, Aobo Xu, Takeshi Hara, Xiangrong Zhou, Dongbo Wu

“…Our visualization results further validate DermViT’s ability to locate lesions under interference conditions. By introducing a modular design that mimics a physician’s observation mode, DermViT achieves more logical feature extraction and decision-making processes for medical diagnosis, providing an efficient and reliable solution for dermoscopic image analysis.…”
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Identification Method of Dynamic Propagation Process of Rock Fracture Based on Ground Penetrating Radar by CHEN Jun, ZHANG Bo, ZHUANG Xingyue, SONG Zhishu, ZHENG Jun

“…As the fractures continue to propagate, they enter the "collaborative coupling" stage, where the wavefields from each fracture interact, leading to interference patterns and amplitude modulation. This stage is characterized by the emergence of wavefield interference stripes and spectral overlapping. …”
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Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning by Kai Yang, Fan Wu, Hongxu Guo, Dongbin Chen, Yirong Deng, Zaoquan Huang, Cunliang Han, Zhiliang Chen, Rongbo Xiao, Pengcheng Chen

“…First, the soil spectral data were preprocessed using Savitzky–Golay (SG) smoothing, multiplicative scattering correction (MSC), and continuous wavelet transform (CWT) to reduce noise interference. Next, principal components analysis (PCA) was employed to reduce the dimensionality of the preprocessed spectral data, eliminating redundant features and lowering the computational complexity. …”
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Wild ActionFormer: Enhancing wildlife action recognition for 11 endangered species in Wolong by Dan Liu, Qianqian Sun, Jin Hou, Bochuan Zheng, Jindong Zhang, Desheng Li, Tomas Norton, Jifeng Ning

“…We utilize UniformerV2 as the base backbone network, integrating self-supervised learning methods to enhance feature extraction capabilities. We constructed a differential dispersion regularization loss function to maintain the alignment of self-supervised learning features and improve the network’s robustness against interference. …”
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UPE-Net: A Spatial Information Enhanced Network for Ulva Prolifera Extraction From GF-1 WFV Images by Hui Sheng, Manman Jia, Shiqing Wei, Lie Sun, Mingming Xu, Shanwei Liu, Jianhua Wan

“…Second, we propose a dual attention spatial pyramid pooling module that effectively suppresses noise interference while capturing multiscale spatial information on Ulva prolifera. …”
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