Parameter Optimisation of Support Vector Machine using Genetic Algorithm for Cyberbullying Detection by Mohd Qorib Alqowiy, Ema Utami

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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

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Community Detection Framework Using Deep Learning in Social Media Analysis by Ao Shen, Kam-Pui Chow

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abnormal data detection and learning their behavior by abnormality and satisficing theory by masood abessi, Elahe Hajigol Yazdi

“…Learning of abnormalities is a considerable challenge in data mining and knowledge discovery. Exceptional phenomena detect among huge records of the database which contains a large number of normal records and very few abnormal ones. …”
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Data-driven bottleneck detection on Tehran highways by Hamid Mirzahossein, Pedram Nobakht, Iman Gholampour

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Age-stratified pharmacovigilance of azithromycin: a multimethod signal detection analysis in the FAERS database by Zhenpo Zhang, Jiangxiong Li, Jingping Zheng, Yankun Liang, Lin Ma, Ling Su

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Automated detection of hospital outbreaks: A systematic review of methods. by Brice Leclère, David L Buckeridge, Pierre-Yves Boëlle, Pascal Astagneau, Didier Lepelletier

“…<h4>Results</h4>Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). …”
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APPLICATION OF CLASSIFICATION BASED ASSOCIATION (CBA) FOR MONKEYPOX DISEASE DETECTION by Qoria Yudi Pratama, Mohammad Isa Irawan

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Damage Detection Method for High-Strength Aramid Conveyor Belts by Ling Yang, Yimin Wang, Di Miao, Xiaoxian Duan

“…Mining conveyor belts play a crucial role in the mining transportation system, and the detection of damage caused to them can affect productivity and safety. …”
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Utilizing a Transient Electromagnetic Inversion Method with Lateral Constraints in the Goaf of Xiaolong Coal Mine, Xinjiang by Yingying Zhang, Bin Xie, Xinyu Wu

“…The abandoned goaf resulting from coal resource integration in China poses a significant threat to coal mine safety. The transient electromagnetic method (TEM) has emerged as a crucial technology for detecting goafs in coal mines due to its adaptable equipment and efficient implementation. …”
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Hard-coded backdoor detection method based on semantic conflict by Anxiang HU, Da XIAO, Shichen GUO, Shengli LIU

“…The current router security issues focus on the mining and utilization of memory-type vulnerabilities, but there is low interest in detecting backdoors.Hard-coded backdoor is one of the most common backdoors, which is simple and convenient to set up and can be implemented with only a small amount of code.However, it is difficult to be discovered and often causes serious safety hazard and economic loss.The triggering process of hard-coded backdoor is inseparable from string comparison functions.Therefore, the detection of hard-coded backdoors relies on string comparison functions, which are mainly divided into static analysis method and symbolic execution method.The former has a high degree of automation, but has a high false positive rate and poor detection results.The latter has a high accuracy rate, but cannot automate large-scale detection of firmware, and faces the problem of path explosion or even unable to constrain solution.Aiming at the above problems, a hard-coded backdoor detection algorithm based on string text semantic conflict (Stect) was proposed since static analysis and the think of stain analysis.Stect started from the commonly used string comparison functions, combined with the characteristics of MIPS and ARM architectures, and extracted a set of paths with the same start and end nodes using function call relationships, control flow graphs, and branching selection dependent strings.If the strings in the successfully verified set of paths have semantic conflict, it means that there is a hard-coded backdoor in the router firmware.In order to evaluate the detection effect of Stect, 1 074 collected device images were tested and compared with other backdoor detection methods.Experimental results show that Stect has a better detection effect compared with existing backdoor detection methods including Costin and Stringer: 8 hard-coded backdoor images detected from image data set, and the recall rate reached 88.89%.…”
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Current status and prospects of mining technology in metal mines by Liancheng WANG, Anlin SHAO, Fuming QU, Xingtong YUE, Huaiyuan WANG, Xingfan ZHANG, Xiaobo LIU

“…This gap is particularly noticeable in ultra-deep mining, where practical experience is especially lacking. (2) Future mining technologies that require urgent attention can be categorized into four types based on their criticality and urgency: bottleneck technologies, foundational technologies, urgent technologies, and forward-looking technologies. (3) The current “bottleneck” technical challenges facing China’s mining sector include the development of intelligent and unmanned technologies for open-pit mining, advanced deep mining technologies for underground operations, and the research and application of specialized mining software. (4) The urgent technologies identified in this study include precise detection and safety management technologies for goaf areas, ultra-large-scale filling mining technologies for metallic mines, and intelligent ore grade detection technologies. (5) Foundational technologies encompass rock mechanics modeling for deep mining, multi-scale fracture simulation processes under geothermal system rock–hydraulic coupling, and dynamic control theories for managing disasters associated with deep mining activities. (6) Forward-looking technologies include a range of innovations, such as new transportation technologies for deep open-pit mines, advanced deep-well lifting techniques, novel efficient rock-breaking technologies, integrated mining and beneficiation technologies, co-extraction methods for both mineral and geothermal resources, and fluidized mining techniques for metallic minerals. …”
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Text mining of hypertension researches in the west Asia region: a 12-year trend analysis by Mohammad Rezapour, Mohsen Yazdinejad, Faezeh Rajabi Kouchi, Masoomeh Habibi Baghi, Zahra Khorrami, Morteza Khavanin Zadeh, Elmira Pourbaghi, Hassan Rezapour

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Technical advances and research directions of borehole geophysical prospecting for coal mines by Jianyuan CHENG, Yu YAN, Yuteng LI, Pan WANG, Rui ZHAO, Bici JIANG

“…BackgroundHigh-precision and long-distance exploration of geological conditions is required for coal extraction and disaster prevention in coal mines. However, traditional drilling and geophysical prospecting methods face technical bottlenecks such as insufficient exploration accuracy and limited exploration ranges. …”
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Multi-scale target intelligent detection method for coal, foreign object and early damage of conveyor belt surface under low illumination and dust fog by Hongwei FAN, Jinpeng LIU, Xiangang CAO, Chao ZHANG, Xuhui ZHANG, Man LI, Hongwei MA, Qinghua MAO

“…The intelligent transportation system of coal mine needs to carry out integrated visual detection of foreign object such as gangue and belt damage. …”
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Multi-scale fusion network for coal mine drill rod counting based on directional object detection in complex scenes by Fukai Zhang, Shuo Zhao, Haiyan Zhang, Yongqiang Ma, Qiang Zhang, Shaopu Wang, Wenjing Chang

“…However, challenges such as dim lighting, small target sizes, diverse object perspectives, and complex visual interference in coal mine environments significantly limit the accuracy and real-time performance of existing object detection methods. …”
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Enhanced Ground Fissure Detection in Mining Areas Based on Visible&#x2013;Infrared Image Fusion and YOLOv5 by Yixin Zhao, Liangchen Zhao, Jihong Guo, Kangning Zhang, Chunwei Ling, Shirui Wang, Hua Bian

“…This article proposes FisFusionYOLO, a novel method that integrates visible&#x2013;infrared image fusion with a YOLOv5 deep learning network to enhance fissure detection accuracy and efficiency. …”
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Seq2Seq-based GRU autoencoder for anomaly detection and failure identification in coal mining hydraulic support systems by Kai Zhan, Cong Wang, Xigui Zheng, Chao Kong, Guangming Li, Wei Xin, Longhe Liu

“…However, the nonlinear, non-stationary characteristics and noise interference in hydraulic support pressure data pose significant challenges for anomaly detection and fault diagnosis. This study proposes an anomaly detection and failure identification method based on Gated Recurrent Unit Autoencoder (GRU-AE), aimed at achieving anomaly detection in hydraulic support pressure data and equipment failure early warning. …”
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Advanced Phishing Detection: Leveraging t-SNE Feature Extraction and Machine Learning on a Comprehensive URL Dataset by Taha Etem, Mustafa Teke

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Camera-Adaptive Foreign Object Detection for Coal Conveyor Belts by Furong Peng, Kangjiang Hao, Xuan Lu

“…We evaluate CAFOD on a dataset collected from real coal mines using three distinct cameras. Experimental results demonstrate that CAFOD outperforms State-of-the-Art object detection methods, achieving superior accuracy and robustness across varying camera perspectives.…”
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