Research and analysis of the TCN-Multihead-Attention prediction model of landslide deformation in the Three Gorges Reservoir area, China by Huan Chen, Huan Chen, Yixuan Li, Yimin Liu

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DEDSWIN-Net: Dual Encoder Dilated Convolution and Swin Transformer Network for the Classification of Liver CT Images by Jyoshna Allenki, Hemant Kumar Soni

“…To resolve this concern, this paper suggests a novel dual encoder deep learning structure named DEDSWIN-Net to mitigate this problem. …”
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Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics by Gayatri Gogoi, Gayatri Gogoi, Sarangthem Dinamani Singh, Sarangthem Dinamani Singh, Devpratim Koch, Devpratim Koch, Emon Kalyan, Rashmi Rani Boro, Aradhana Devi, Hridoy Jyoti Mahanta, Hridoy Jyoti Mahanta, Pankaj Bharali, Pankaj Bharali

“…After data preprocessing, correlation analyses identified 19 relevant environmental parameters. Unsupervised learning algorithms, including K-means and K-medoid clustering, were employed to categorize the data into four distinct clusters, revealing patterns of viral positivity and environmental conditions.ResultsCluster analysis indicated that seasonal variations and water quality characteristics significantly influenced SARS-CoV-2 positivity rates. …”
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Combination of InSAR and neural networks for the deformation monitoring and prediction of Fanjiaping landslide by Wenzheng XU, Shuqiang LU, Zhen LIN, Wangmin ZHOU

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Landslide susceptibility assessment based on an interpretable coupled FR-RF model: A case study of Longyan City, Fujian Province, Southeast China by Zong-yue Lu, Gen-yuan Liu, Xi-dong Zhao, Kang Sun, Yan-si Chen, Zhi-hong Song, Kai Xue, Ming-shan Yang

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Damage Identification Using Measured and Simulated Guided Wave Damage Interaction Coefficients Predicted Ad Hoc by Deep Neural Networks by Christoph Humer, Simon Höll, Martin Schagerl

“…This technique employs the so-called wave damage interaction coefficients (WDICs) as highly sensitive damage features that describe the unique scattering pattern around possible damage. The DNNs learn intricate relationships between damage characteristics, e.g., size or orientation, and corresponding WDIC patterns from only a limited number of damage cases. …”
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Research on High-Resolution Modeling of Satellite-Derived Marine Environmental Parameters Based on Adaptive Global Attention by Ruochu Cui, Liwen Ma, Yaning Hu, Jiaji Wu, Haiying Li

“…The analysis of marine environmental parameters plays an important role in areas such as sea surface simulation modeling, analysis of sea clutter characteristics, and environmental monitoring. …”
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Application of a hybrid algorithm of LSTM and Transformer based on random search optimization for improving rainfall-runoff simulation by Wenzhong Li, Chengshuai Liu, Caihong Hu, Chaojie Niu, Runxi Li, Ming Li, Yingying Xu, Lu Tian

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Assessment of the effect of the process-induced porosity defects on the fatigue properties of wire arc additive manufactured Al–Si–Mg alloy by Teng Zhan, Ke Xu, Zhipeng Fan, Hanlin Xiang, Congchang Xu, Tianjiao Mei, Yuanyuan Wei, Wentao Chen, Luoxing Li

“…In this study, the influence of process-induced porosity defect characteristics on the fatigue properties of wire arc additive manufacturing (WAAM) Al–Si–Mg parts was quantitatively analyzed using the Kitagawa-Takahashi diagram and machine learning methods. …”
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A novel framework to identify delamination location/size in BFRP pipe based on convolutional neural network (CNN) algorithm hybrid with capacitive sensors by Wael A. Altabey

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Remote Sensing Fine Estimation Model of PM_2.5 Concentration Based on Improved Long Short-Term Memory Network: A Case Study on Beijing–Tianjin–Hebei Urban Agglomeration i... by Yiye Ji, Yanjun Wang, Cheng Wang, Xuchao Tang, Mengru Song

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Non-Subsampled Contourlet Transform-Based Domain Feedback Information Distillation Network for Suppressing Noise in Seismic Data by Kang Chen, Guangzhi Zhang, Cong Tang, Qi Ran, Long Wen, Song Han, Han Liang, Haiyong Yi

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The Application of the Gestalt Theory in Music Psychotherapy for Piano by Fukun Cai

“…The paper focuses on how to apply the “whole and part” and “epiphany” perspectives of the Gestalt learning theory to singing and music appreciation lessons. …”
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Urban subsidence zones prone to flooding: mitigated deformation trends post-2024 Guilin megaflood by Pinglang Kou, Xu Dong, Qiang Xu, Ali P. Yunus, Ying Xia, Yuxiang Tao, Rui Liu, Qin Ji, Ruikun Chen, Zhengwu Yuan

“…This study uses the 2024 Guilin flood event as a case study, integrating SBAS-InSAR, DInSAR techniques, and various machine learning methods to explore the complex interactions between surface deformation, soil characteristics, and flooding. …”
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Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia by M. Zoldoš, M. Zoldoš, T. Džoić, J. Jurković, F. Matić, S. Jambrošić, I. Ljuština, M. Telišman Prtenjak

“…<p>A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. …”
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Research on blindsight technology for object recognition and attitude determination based on tactile pressure analysis by Chen Li, Li HuiJun, Song Aiguo

“…Through training and learning the mechanical features of the contact surface, the paper achieves perception and posture determination of objects during pressing and grasping processes. …”
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Vehicle load identification based on bridge response using deep convolutional neural network by Sadaqat Hussain, Syed M. Hussain, Yu Xin, Zuo-Cai Wang

“…Two popular deep learning frameworks, ResNet and Inception models, were employed to assess their capability to identify these critical vehicle-bridge interaction characteristics accurately. …”
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Theoretical and simulation analysis of a rectangular crack in the piezoelectric material by Yani Zhang, Junlin Li

“…Finally, The random forest machine learning and response surface method are used for the first time to study rectangular cracks in piezoelectric materials.A random forest regression model is applied to predict the data, and from the residual scatter plot provided, the accuracy of the prediction model is found to be high. …”
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A unified ensemble soil moisture dataset across the continental United States by Lingcheng Li, Xinming Lin, Yilin Fang, Z. Jason Hou, L. Ruby Leung, Yaoping Wang, Jiafu Mao, Yaping Xu, Elias Massoud, Mingjie Shi

“…The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. …”
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An intelligent non-destructive method to identify the quality of self-compacting concrete based on convolutional neural networks via image recognition by Zhong Xiao, Zixuan Liu, Xuying Guo, Jun Liu

“…The optimal model employed the largest size of polished surface images with a pixel resolution of 1266 × 1266 as the input data under the situation that learning rate and dropout ratio are 0.1 and 0, respectively. …”
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