Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

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Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

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Multimodal Fake News Detection Incorporating External Knowledge and User Interaction Feature by Lifang Fu, Shuai Liu

“…However, in terms of content, most existing methods lack the mining of background knowledge hidden in the news content and ignore the connection between background knowledge and existing knowledge system. …”
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Field Measurement and Mechanical Analysis of Height of the Water Flowing Fracture Zone in Short-Wall Block Backfill Mining beneath the Aquifer: A Case Study in China by Yun Zhang, Shenggen Cao, Tong Wan, Jijun Wang

“…Therefore, based on the theory of elastic foundation beam and SBBM characteristics, a mechanical model for calculating the height of a water flowing fracture zone in the overlying strata of SBBM was established, and this model calculated that the height of the water flowing fracture zone was 27.0 m in the experimental working face, and the height of the water flowing fracture zone was measured as 26.8 m according to washing fluid loss in the hole, core damage analysis, and drilling TV imaging detection. The comparison results demonstrated that the calculated value almost fit well with the field-measured data, validating the accuracy of the proposed mechanical model, while the predicted value (48.7 m) in the Regulations of coal mining under building, railways and water-bodies deviates greatly from the measured results. …”
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Modality-based Modeling with Data Balancing and Dimensionality Reduction for Early Stunting Detection by Yohanes Setiawan, Mohammad Hamim Zajuli Al Faroby, Mochamad Nizar Palefi Ma’ady, I Made Wisnu Adi Sanjaya, Cisa Valentino Cahya Ramadhani

“…This high prevalence underscores the urgent need for effective early detection methods. Traditional data mining approaches for stunting detection have primarily focused on unimodal data, either tabular or image data alone, limiting the comprehensiveness and accuracy of the detection models. …”
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Application of a UAV-borne GPR system in the detection of water bodies and cavities by Ying WANG, Chenchen SUN, Lu ZHANG, Yifei CHEN, Song LU, Feng ZHOU

“…Objective and Methods The unmanned aerial vehicle (UAV)-borne ground-penetrating radar (GPR) system, enjoying the advantages of high resolution and non-contact detection, is applicable to the detection of water accumulation in coal seams and goaves in mines. …”
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DMCF-Net: Dilated Multiscale Context Fusion Network for SAR Flood Detection by Zhimin Wang, Lingli Zhao, Nan Jiang, Weidong Sun, Jie Yang, Lei Shi, Hongtao Shi, Pingxiang Li

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A Method for Determining the Thicknesses of the Reserved Protective Layers in Complex Goafs Using a Joint-Modeling Method of GTS and Flac3D by Xin Zhao, Dianshu Liu, Shenglin Li, Meng Wang, Shuaikang Tian, Xiaoming Niu, Lin Mo

“…In this study, a C-ALS underground cavity scanner was used to detect the shapes of mining goafs. In addition, GTS software was adopted to establish a three-dimensional geological model based on the status of the stopes, geological data, and mechanical parameters of each rock mass and to analyze the roof areas of the goafs. …”
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Anomaly Detection of Wind Turbines Based on Deep Small-World Neural Network by Yaguang LI, Meng LI

“…In recent years, the intelligent anomaly detection method based on deep neural networks (DNN) has been receiving increasing attention. …”
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Belt conveyor idler fault detection algorithm based on improved YOLOv5 by Cen Pan, Qing Tao, Hao Pei, Biao Wang, Wei Liu

“…The safe and stable operation of belt conveyor idlers is crucial not only for ensuring efficient coal production but also for safeguarding the lives of coal mine workers. Therefore, this paper proposes a method based on deep learning for real-time detection of conveyor idler faults. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…To enhance public safety, crowd detection and prevention systems have essentially become a natural means to manage diverse crowded areas, such as urban settings, transportation hubs, and event venues. …”
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Deep-learning-based detection of underwater fluids in multiple multibeam echosounder data by Tyméa Perret, Gilles Le Chenadec, Arnaud Gaillot, Yoann Ladroit, Stéphanie Dupré

“…Fluids can be detected in the water column using multibeam echosounder data. …”
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Ship Detection Transformer in SAR Images Based on Key Scattering Points Feature Aggregation and Context Feature Refinement by Yifei Yin, Zhu Yang, Hao Shi, Fanyu Meng, Wei Li

“…In recent years, deep learning algorithms have demonstrated significant advancements in the field of ship detection using synthetic aperture radar (SAR). Nevertheless, two primary challenges persist in the task of SAR ship detection: first, owing to the unique imaging mechanism, targets in SAR images are typically represented by scattering points, posing challenges for accurate feature extraction and leading to issues of inaccurate localization. …”
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Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements by Liansheng Deng, Yugang Xiao, Qusen Chen, Wei Peng, Zhao Li, Hua Chen, Zhiwen Wu

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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

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A Review of Numerical Techniques for Frictional Contact Analysis by Govind Vashishtha, Sumika Chauhan, Riya Singh, Manpreet Singh, Ghanshyam G. Tejani

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T-UNet: triplet UNet for change detection in high-resolution remote sensing images by Huan Zhong, Chen Wu

“…Current change detection methods mainly use Siamese or early fusion structures. …”
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Data augmentation based multi-view contrastive learning graph anomaly detection by LI Yifan, LI Jiayin, LIN Xingpeng, DAI Yuanfei, XU Li

“…Although contrast-based anomaly detection methods could effectively mine anomaly information based on the inconsistency of anomalous node instance pairs, avoiding the drawback of using self-coding architecture that led to the need for full graph training for the model. …”
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Semi-supervised dynamic community detection based on non-negative matrix factorization by Zhen-chao CHANG, Hong-chang CHEN, Rui-yang HUANG, Hong-tao YU, Yang LIU

“…Experiments on the real network dat sets show that the method has a higher community detection quality compared with existing methods, which can accurately mine the relationship among different time, and explore network evolution and the law of development more adva geously.…”
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