A MultiScale Coordinate Attention Feature Fusion Network for Province-Scale Aquatic Vegetation Mapping From High-Resolution Remote Sensing Imagery by Yuzhe Wang, Yunfei Sun, Peng Zhang, Yanlan Wu, Hui Yang

“…Specifically, we propose a feature fusion module based on the squeeze-and-excitation coordinate attention mechanism. …”
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Design of CMOS Charge-sensitive Amplifier for Coaxial High Purity Germanium Detector by LIU Zhan, HE Gaokui, LIU Haifeng

“…However, larger transistor sizes can lead to gate leakage currents, which can alter the baseline of the amplifier output. To address this issue, a low-noise CSA circuit with a feedback resistor module for leakage current compensation was developed. …”
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Undergraduate Students in a Medical College in Manipur by Rajkumar Arbind Singh, Ronal Singh Rajkumar, Abhijeet Srivastava, Hawaibam Budhichandra Singh

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Branch error reduction criterion-based signal recursive decomposition and its application to wind power generation forecasting. by Fen Xiao, Siyu Yang, Xiao Li, Junhong Ni

“…Due to the ability of sidestepping mode aliasing and endpoint effects, variational mode decomposition (VMD) is usually used as the forecasting module of a hybrid model in time-series forecasting. …”
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CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network by Qingyang Chen, Hong Lin, Zhenping Qiang, Hui Liu, Kaifan Ji, Zhenhong Shang

“…The network comprises a multiscale feature extraction module and a coarse-to-fine global optical flow calculation module. …”
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MCIDN: Deblurring Network for Metal Corrosion Images by Jiaxiang Wang, Meng Wan, Pufen Zhang, Sijie Chang, Hao Du, Peng Shi, Hongying Yu, Dongbai Sun, Jue Wang, Yangang Wang

“…While self-attention is widely used in visual tasks, its quadratic complexity often leads to high computational costs. To address this issue, we introduce a new spatial channel attention module (SCAM) that employs dynamic group convolutions to achieve self-attention, effectively integrating information from local regions and enhancing representation learning capabilities. …”
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Studyimg methods for controlling the condition of milling machines based on the analysis of vibration characteristics by E.S. Yanov, S.V. Antonychev, A.V. Antsev, M.S. Vorotilin, E.I. Minakov

“…In the context of sanctions pressure, the issue of production intensification has again become relevant. …”

Increasing the mass of the cargo party for the account of a rational choice of the transportation tara by Ilesaliev D.I.

“…The parameters of the transport packages formed on standard pallets 1200×1000 mm, 1200×800 mm and the internal dimensions of the covered wagons and containers are not multiples of each other and do not have a common module. In this regard, there is a need to study this issue on a scientific basis. …”
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Selected Determinants of the Quality of Life after Surgical Treatment of Brain Tumors by Agnieszka Królikowska, Renata Jabłońska, Anna Antczak, Beata Haor, Piotr Zieliński, Marek Harat

“…Relevant consent was issued by the Bioethics Committee at the Ludwik Rydygier Medical College in Bydgoszcz (Consent No. …”
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A novel deep neural network for hidden target detection in images by Rabeb Hendaoui, Vasif Nabiyev

“…Hence, it is hard to ascertain these concealed targets. To address this issue, a novel deep neural network is proposed in this paper that produces an estimated mask within the hidden target for an input image. …”
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Design and implementation of online learning assisted intelligent receiver by Lingjin KONG, Kai MEI, Xiaoran LIU, Jun XIONG, Haitao ZHAO, Jibo WEI

“…To address the issue of reliable communication under complicated scenarios, an online learning-assisted intelligent OFDM receiver was proposed.The variations of the channel environment could be precepted by the receiver, and the optimal parameters of the receiver under the current scenario were obtained by collecting data and training online.In the channel estimation module of the OFDM system, a performance comparator based on the mean square error of noisy channel samples was designed as the indicator of channel environment variations.To accelerate the online training progress, a lightweight neural network structure was applied.The proposed method was further implemented and verified based on universal software radio peripherals.The numerical simulation and over-the-air experimental results demonstrate that the proposed receiver can perceive and adapt to new environments effectively, and outperforms existing machine learning methods in terms of receiving performance and convergence rate with a limited number of pilots.…”
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SSM-based detection of rice seedling deficiency by Youran Xia, Zhengtao Zhu, Xiaobin Liu

“…Abstract In large-scale rice cultivation, seedling deficiency is a common issue that significantly impacts timely replanting decisions. …”
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Design of a Wearable Exoskeleton Piano Practice Aid Based on Multi-Domain Mapping and Top-Down Process Model by Qiujian Xu, Meihui Li, Guoqiang Chen, Xiubo Ren, Dan Yang, Junrui Li, Xinran Yuan, Siqi Liu, Miaomiao Yang, Mufan Chen, Bo Wang, Peng Zhang, Huiguo Ma

“…By closely combining layout constraints with the design model, this method significantly improves the accuracy and efficiency of module configuration, offering a new path for the development of piano practice assistance devices. …”
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Federated XAI IDS: An Explainable and Safeguarding Privacy Approach to Detect Intrusion Combining Federated Learning and SHAP by Kazi Fatema, Samrat Kumar Dey, Mehrin Anannya, Risala Tasin Khan, Mohammad Mamunur Rashid, Chunhua Su, Rashed Mazumder

“…IDS is a safeguarding module that is designed to identify unauthorized activities in network environments. …”
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Real time counting method for coal mine drill pipes based on deep learning by Fukai ZHANG, Yiran SUN, Xufeng WU, Aijun LI, Peiyang LI, Dengke WANG, Guan YUAN, Shan ZHAO, Haiyan ZHANG

“…A real-time counting method for coal mine drill pipes based on deep learning technology is proposed to address the above issues. It consists of two parts: the drill recognition model Drill-YOLOv8 optimized based on AM-NT and the drill pipe counting inference algorithm Pipe Count based on two-level judgment regions. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…First, we introduce the SobelMaxDS module, designed to enhance the network’s ability to extract edge and spatial features, thereby enabling more effective capture of the fish’s behavioral contours and preserving rich target information. …”
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AsGCL: Attentive and Simple Graph Contrastive Learning for Recommendation by Jie Li, Changchun Yang

“…However, most existing models fail to distinguish the importance of different nodes, which limits their performance. To address this issue, we propose the asGCL model. To mitigate the prevalent issue of popularity bias and to learn more uniform embedding representations, we have integrated a lightweight contrastive learning module into our model. …”
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Contextual Analysis of Financial Time Series by Nadezhda Yarushkina, Aleksey Filippov, Anton Romanov

“…The evaluation of the financial state of small and medium-sized companies is a pressing issue today. This article introduces a novel method to evaluate a company’s financial state, implemented as a module within a decision support system. …”
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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…Combined with the spatial channel convolution (SCConv) to enhance the feature fusion module, the cross-modal interaction between texture and structural features is optimized through a dynamic gating mechanism. …”
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Design and Simulation of Bias Fork Chain Drive in Vertical Circular Stereo Garage by Wang Qi, Yan Zhengliang, Chen Yuanhua

“…The motion simulation module of software is used to simulate the trajectory curvature of the chain plate and the feasibility of the motion of the detection mechanism. …”
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