Rolling bearing fault diagnosis under small sample conditions based on WDCNN-BiLSTM Siamese network by Chenxu Bian, Chunni Jia, Jibo Li, Xiangjun Chen, Pei Wang

“…To address this problem, a novel Siamese Neural Network (SNN) model, integrating Deep Convolutional Neural Networks with Wide First-layer Kernel (WDCNN) and Bidirectional Long Short-Term Memory (BiLSTM) network is proposed. This model constructs a feature extraction system that combines WDCNN and BiLSTM to extract local spatial features and global temporal dependencies from vibration signals. …”
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Laser Induced Fluorescence for In Situ Detection of Typical Heavy Metals in Groundwater by Kang MAO, Jiaqi XUE, Zhuo CHEN, Hua ZHANG

“…These synthesized probes and the corresponding constructed sensors indicate that LIF holds significant advantages in heavy metal detection in groundwater. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…A parallel residual network tool prediction model (DAMResNet) was constructed to optimize the model’s weight allocation to different features, achieving multi-channel and multi-dimensional feature fusion. …”
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A lightweight multi scale fusion network for IGBT ultrasonic tomography image segmentation by Meng Song, Zhaoba Wang, Youxing Chen, Ya Li, Yong Jin, Bei Jia

“…To address these challenges, this paper constructs a dedicated IGBT ultrasonic tomography (IUT) dataset using Scanning Acoustic Microscopy (SAM) and proposes a lightweight Multi-Scale Fusion Network (LMFNet) aimed at improving segmentation accuracy and processing efficiency in ultrasonic images analysis. …”
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A Relative Attitude Detection Method for Unmanned Aerial Vehicles Based on You Only Look Once Framework by Jingting Qiu, Feifan Yu, Fengrui Xu, Xinmin Chen, Jiqiang Wang

“…To tackle these challenges, we first constructed a dataset on UAV landing markers called the UAV landing marker dataset (ULMD). …”
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Nanocomposite Hydrogel for Real‐Time Wound Status Monitoring and Comprehensive Treatment by Huan Lei, Xueqing Yu, Daidi Fan

“…Tannins and siRNA containing matrix metalloproteinase‐9 gene siRNA interference are self‐assembled to construct a degradable nanogel and modified with bovine serum albumin. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…To address the limitations of existing knowledge graph-based recommendation algorithms, including insufficient utilization of semantic information and inadequate modeling of user behavior motivations, we propose SKGRec, a novel recommendation model that integrates knowledge graph and semantic features. The model constructs a semantic interaction graph (USIG) of user behaviors and employs a self-attention mechanism and a ranked optimization loss function to mine user interactions in fine-grained semantic associations. …”
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The Decision-Making Process of Men Applying for Divorce: A Narrative Perspective by Zeinab Saboohi Golkar, Hossein Afrasiabi

“…Consequently, researchers are prompted to inquire about the decision-making process among men and the narratives they construct surrounding their choice to pursue divorce.  …”
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Question-answering enhancement method for large educational models based on re-ranking and post-retrieval reflection by SUN Haoran, WANG Zhihao, WU Yifan, GAO Xiaoying, XIANG Yang

“…We collected computer-related textbooks and knowledge documents, dividing them into knowledge document blocks according to the content structure to construct an external knowledge database. On this base, we introduced the large educational models question-answering enhancement method based on re-ranking and post-retrieval reflection, which utilized a high-performance multilingual re-ranking model based on a cross-encoder to capture deep semantic information, filter the retrieval information, filter out irrelevant information to improve the retrieval quality. …”
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Experience of Virtual Help in a Simulated BCI Stroke Rehabilitation Serious Game and How to Measure It by Bastian Ilsø Hougaard, Hendrik Knoche, Mathias Sand Kristensen, Mads Jochumsen

“…Future studies should validate or control for the constructs of perceived help quantity and appeal.…”
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Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration by Xiaodong Cui, Jiale Zhang, Lingling Zhang, Qunfei Zhang, Jing Han

“…The SOCA-YOLO framework first constructs a high-resolution SSS (sidescan sonar image) enhancement pipeline through image restoration techniques to extract fine-grained features of micro-scale targets. …”
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Artificial MiRNA Knockdown of Platelet Glycoprotein lbα: A Tool for Platelet Gene Silencing. by Tim Thijs, Katleen Broos, Stefaan J Soenen, Aline Vandenbulcke, Karen Vanhoorelbeke, Hans Deckmyn, Isabelle I Salles-Crawley

“…CHO GPIb-IX cells transfected with the miGPIBA construct displayed a significant decrease in their ability to aggregate characterized by lower aggregate numbers and size compared to control CHO GPIb-IX cells. …”
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YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. …”
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Image Matching Algorithm for Transmission Towers Based on CLAHE and Improved RANSAC by Ruihua Chen, Pan Yao, Shuo Wang, Chuanlong Lyu, Yuge Xu

“…First, the improved AKAZE enhances image contrast using Contrast-Limited Adaptive Histogram Equalization (CLAHE), which highlights target features and improves robustness against environmental interference. Subsequently, the original AKAZE algorithm is employed to detect feature points and construct binary descriptors. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…Specifically, we design a lightweight cross-scale feature fusion module that adaptively fuses multi-scale feature information, enhancing small target detection while reducing model complexity. Additionally, we construct a hybrid attention enhancement module, integrating convolutional operations with a self-attention mechanism to improve feature discrimination without compromising computational efficiency. …”
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Deep learning-enhanced signal detection for communication systems. by Yang Liu, Peng Liu, Yu Shi, Xue Hao

“…Based on this, the study innovatively combines Multiple Input Multiple Output (MIMO) with orthogonal frequency division multiplexing technology to construct a data-driven detection system. The system adopts a Multi-DNN method with a dual-DNN cascade structure and mixed activation function design to optimize the channel estimation and signal detection coordination process of the MIMO part. …”
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Looming Detection in Complex Dynamic Visual Scenes by Interneuronal Coordination of Motion and Feature Pathways by Bo Gu, Jianfeng Feng, Zhuoyi Song

“…An artificial neural network is employed to construct a combined‐pathway model based on Drosophila anatomy. …”
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Development of hop transcriptome to support research into host-viroid interactions. by Tine Pokorn, Sebastjan Radišek, Branka Javornik, Nataša Štajner, Jernej Jakše

“…To study these interactions, we constructed a deep hop NGS transcriptome based on 35 Gb paired-end sequencing data assembled into over 74 Mb of contigs. …”
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Method for EEG signal recognition based on multi-domain feature fusion and optimization of multi-kernel extreme learning machine by Shan Guan, Tingrui Dong, Long-kun Cong

“…Firstly, the EEG signals are preprocessed using the Improved Comprehensive Ensemble Empirical Mode Decomposition (ICEEMD) algorithm combined with the Pearson correlation coefficient to eliminate noise and interference. Secondly, multivariate autoregressive (MVAR) model, wavelet packet decomposition, and Riemannian geometry methods are used to extract features from the time domain, frequency domain, and spatial domain, respectively, to construct a joint time-frequency-space feature vector. …”
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ESTIMATION OF SOFTWARE COMPLEXITY OF CALCULATION OF AUTOREGRESSION COEFFICIENTS AT DIGITAL SPECTRAL ANALYSIS by Andrey Zuev, Andrey Ivashko, Denis Lunin

“…Conclusions: When constructing spectrum analyzers for the diagnosis of technological equipment, it is advisable to use the Yul-Walker method. …”
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