Adaptive zero velocity correction method for fiber optic inertial navigation system in coal mining roadheader by Qinghua MAO, Qing ZHOU, Jianquan CHAI, Yanzhang CHEN, Wenjuan YANG, Xusheng XUE

“…Therefore, an adaptive zero-speed correction method for fiber-optic inertial navigation of coal mine roadheader based on zero-speed detection and extended Kalman filter is proposed.Aiming at the problem of inaccurate zero-speed detection of traditional threshold method for roadheader fiber-optic inertial navigation, a zero-speed detection method based on PCA−SCSO−SVM ( Principal Component Analysis PCA, Sand Cat Swarm Optimization SCSO, Support Vector Machine SVM ) is proposed. …”
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Assessing change point detection methods to enable robust detection of early stage Artisanal and Small-Scale mining (ASM) in the tropics using Sentinel-1 time series data by Mensah Isaac Obour, Barrett Brian, Cahalane Conor

“…This study utilised a time series smoothing technique to improve Sentinel-1 (S-1) SAR time series data, reducing SAR noise and atmospheric effects from heavy rainfall for early ASM activity detection. We tested three change point detection (CPD) methods, including cumulative sum (CuSuM), pruned exact linear time (PELT), and binary segmentation (BinSeg) in the Western and Ashanti wet regions in southern Ghana using the smoothed S-1 data for early ASM detection. …”
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CM-YOLO: Typical Object Detection Method in Remote Sensing Cloud and Mist Scene Images by Jianming Hu, Yangyu Wei, Wenbin Chen, Xiyang Zhi, Wei Zhang

“…However, the degradation and loss of features caused by the obstruction of cloud and mist elements still pose a challenging problem for this technology. To enhance object detection performance in adverse weather conditions, we propose a novel target detection method named CM-YOLO that integrates background suppression and semantic context mining, which can achieve accurate detection of targets under different cloud and mist conditions. …”
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Wavelet-Based Texture Mining and Enhancement for Face Forgery Detection by Xin Li, Hui Zhao, Bingxin Xu, Hongzhe Liu

“…Due to the abuse of deep forgery technology, the research on forgery detection methods has become increasingly urgent. The corresponding relationship between the frequency spectrum information and the spatial clues, which is often neglected by current methods, could be conducive to a more accurate and generalized forgery detection. …”
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Business process mining based insider threat detection system by Tai-ming ZHU, Yuan-bo GUO, An-kang JU, Jun MA

“…Current intrusion detection systems are mostly for detecting external attacks,but sometimes the internal staff may bring greater harm to organizations in information security.Traditional insider threat detection methods of-ten do not combine the behavior of people with business activities,making the threat detection rate to be improved.An insider threat detection system based on business process mining from two aspects was proposed,the implementation of insider threats and the impact of threats on system services.Firstly,the normal control flow model of business ac-tivities and the normal behavior profile of each operator were established by mining the training log.Then,the actual behavior of the operators was compared with the pre-established normal behavior contours during the operation of the system,which was supplemented by control flow anomaly detection and performance anomaly detection of business processes,in order to discover insider threats.A variety of anomalies were defined and the corresponding detection algorithms were given.Experiments were performed on the ProM platform.The results show the designed system is effective.…”
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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…With the continuous development of artificial intelligence technology and the gradual advancement of the smart mining concept, traditional open-pit mining operations are being replaced by automated methods. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…In the context of intelligent coal mine safety monitoring, an integrated prediction and early-warning method named MTGNN-Bayesian-IF-DBSCAN (Multi-Task Graph Neural Network–Bayesian Optimization–Isolation Forest–Density-Based Spatial Clustering of Applications with Noise) is proposed to address the challenges of gas concentration prediction and anomaly detection in coal mining faces. …”
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Study on the effect of pulsed eddy current lift-off characteristics for feeding metallic foreign objects detection in coal mine crushers by Benchang Meng, Zezheng Zhuang, Jiahao Ma, Sihai Zhao

“…Abstract This study addresses the challenges of low accuracy and poor timeliness in feeding metallic foreign object detection during high-output continuous crushing operations in coal mines. …”
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Enhancing Retail Strategies Through Anomaly Detection in Association Rule Mining by Bijayini Mohanty, Santi Lata Champati, Swadhin Kumar Barisal

“…Traditional association rule mining (TARM) methods sometimes fail to handle inconsistencies and contradictions for Boolean logic concepts. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…This method provides efficient and reliable dynamic early-warning technology support for coal-mine gas disaster prevention and control, demonstrating significant engineering application value.…”
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Optimized YOLO Model for Accurate and Real-Time Detection of Machinery Around Shovels in Copper Mining by Mohaddeseh Ghiasi, MasoudReza Aghabozorgi

“…This study proposes an enhanced version of the YOLO model for the precise and rapid detection of vehicles around the shovel in copper mining environments. …”
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Fisher Information of Mine Collapse Hole Detection Based on Sensor Nodes Connectivity by Shengbo Hu, Heng Shu, Xiaowei Song

“…Comparing three types of the hole detection methods, it is seen that the connectivity-based methods are used to detect coal mine collapse better than other methods. …”
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Multilevel Feature Fusion-Based GCN for Rumor Detection with Topic Relevance Mining by Shenyu Chen, Meng Li, Weifeng Yang

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APT Detection via Hypergraph Attention Network with Community-Based Behavioral Mining by Qijie Song, Tieming Chen, Tiantian Zhu, Mingqi Lv, Xuebo Qiu, Zhiling Zhu

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Financial Fraud Detection on Social Networks Based on a Data Mining Approach by Victoria Bozhenko, Serhii Mynenko, Artem Shtefan

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Detecting and localizing cervical lesions in colposcopic images with deep semantic feature mining by Li Wang, Ruiyun Chen, Jingjing Weng, Huiping Li, Shi Ying, Jinghui Zhang, Zehao Yu, Chengbin Peng, Siming Zheng

“…ObjectiveThis study aims to investigate the feasibility of employing artificial intelligence models for the detection and localization of cervical lesions by leveraging deep semantic features extracted from colposcopic images.MethodsThe study employed a segmentation-based deep learning architecture, utilizing a deep decoding network to integrate prior features and establish a semantic segmentation model capable of distinguishing normal and pathological changes. …”
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Integrated physical detection technology in complicated surface subsidence area of mining area by Zhen-tao LI, Quan-ming LI, Hong ZHANG

“…In this study, a high-density resistivity method and shallow seismic reflection method were used to detect the surface subsidence area in a mine in Shandong, China. …”
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Small target detection in coal mine underground based on improved RTDETR algorithm by Feng Tian, Cong Song, Xiaopei Liu

“…Abstract Aiming at the problem of low detection accuracy of small targets such as helmets and self-rescuers in complex scenarios in coal mines, a small target detection method based on improved Real-Time DEtection TRansformer (RTDETR) for underground coal mines is proposed. …”
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Trajectory analysis using data mining techniques by Gary Reyes

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Research on Quantitative Analysis Method of Infrared Spectroscopy for Coal Mine Gases by Feng Zhang, Yuchen Zhu, Lin Li, Suping Zhao, Xiaoyan Zhang, Chaobo Chen

“…Accurate and reliable detection of coal mine gases is the key to ensuring the safe service of coal mine production. …”
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