Induction Machine Bearing Fault Detection Using Empirical Wavelet Transform by Ricardo Lopez-Gutierrez, Jose de Jesus Rangel-Magdaleno, Carlos Javier Morales-Perez, Arturo García-Perez

“…The detection of faults related to the optimal condition of induction motors is an important task to avoid the malfunction or loss of the motor, thus avoiding high repair or replacement costs and faults in the efficiency of the process to which they belong. …”
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The Case of a Primary Tuberculosis Complex in a Child With Late Detection by Irina Yu. Petrakova, Marina F. Gubkina, Yury S. Berezovsky, Mamed A. Bagirov, Bagirov V. Yukhimenko

“…We present a case of late detection and course of the primary tuberculosis complex in a child who was previously in an unknown contact with a tuberculosis patient at the first year of life. …”
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Detection of grains in aluminium metal matrix composites using image fusion by Tapasmini Sahoo, Sweta Rani Biswal, Kunal Kumar Das

“…This piece of work illustrates an image fusion approach using discrete wavelet transform (DWT) for the detection of grains present in the hybrid composite to study the metallographic characterization. …”
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Dual Feature-Based Intrusion Detection System for IoT Network Security by A. Biju, S. Wilfred Franklin

“…The proposed method utilizes the bald eagle search (BES) algorithm and butterfly optimization algorithm (BOA) to capture both flow and packet level features to enhance the accuracy of the intrusion detection process. Moreover, a multi-head attention-based bidirectional gated recurrent unit (MHA-BiGRU) is utilized to classify Attack and Non-Attack classes with high precision. …”
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Application of Sinusoidal Function in Financial Crisis Early Warning and Detection System by Xueyin Wang

“…Therefore, this paper studies the application of sine signal function in financial crisis early warning and detection system. According to the principle of “different frequencies are uncorrelated,” the derivation process of a single sinusoidal signal with noise in the crisis warning period is also applicable to the case of multiple sinusoidal signals, so the program can also be used to detect multiple sinusoidal signals in the crisis warning period at the same time. …”
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Early Heart Attack Detection Using Hybrid Deep Learning Techniques by Niga Amanj Hussain, Aree Ali Mohammed

“…These algorithms can process large datasets, extracting valuable insights that help mitigate the risk of fatal outcomes. …”
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Approach of detecting low-rate DoS attack based on combined features by Zhi-jun WU, Jing-an ZHANG, Meng YUE, Cai-feng ZHANG

“…LDoS (low-rate denial of service) attack is a kind of RoQ (reduction of quality) attack which has the characteristics of low average rate and strong concealment.These characteristics pose great threats to the security of cloud computing platform and big data center.Based on network traffic analysis,three intrinsic characteristics of LDoS attack flow were extracted to be a set of input to BP neural network,which is a classifier for LDoS attack detection.Hence,an approach of detecting LDoS attacks was proposed based on novel combined feature value.The proposed approach can speedily and accurately model the LDoS attack flows by the efficient self-organizing learning process of BP neural network,in which a proper decision-making indicator is set to detect LDoS attack in accuracy at the end of output.The proposed detection approach was tested in NS2 platform and verified in test-bed network environment by using the Linux TCP-kernel source code,which is a widely accepted LDoS attack generation tool.The detection probability derived from hypothesis testing is 96.68%.Compared with available researches,analysis results show that the performance of combined features detection is better than that of single feature,and has high computational efficiency.…”
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Fault Detection of Aircraft Control System Based on Negative Selection Algorithm by Jie Chen, Senyao Chen, Cunbao Ma, Zhengdong Jing, Qingshan Xu

“…The aircraft control system controls the whole flight movement process. Its fault detection can assist the aircraft PHM system in making decisions and completing the targeted maintenance, which is of great significance to improve the safety and reliability of the aircraft. …”
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Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks by Mrinal Nandi, Anup Dewanji, Bimal Roy, Santanu Sarkar

“…We propose fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. …”
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Ventricular Fibrillation Prediction and Detection: A Comprehensive Review of Modern Techniques by Monica Fira, Hariton-Nicolae Costin, Liviu Goraș

“…This review offers a detailed examination of modern ECG signal processing techniques employed in the prediction and detection of ventricular fibrillation (VF). …”
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Collision detection method for anchor digging machine water drilling rig by Zhi-xiang Liu, Shu-tong Yan, Kang Zou, Miao Xie

“…In order to avoid the interference between the water drilling rig and the anchor machine in the working process, it is necessary to calculate the joint variables of the drilling rig accurately. …”
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VAD-CLVA: Integrating CLIP with LLaVA for Voice Activity Detection by Andrea Appiani, Cigdem Beyan

“…Voice activity detection (VAD) is the process of automatically determining whether a person is speaking and identifying the timing of their speech in an audiovisual data. …”
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Rare plants detection using a YOLOv3 neural network by L.A. Gorodetskaya, A.Y. Denisova, L.M. Kavelenova, V.A. Fedoseev

“…To reduce the human impact on the natural habitat of plants and simplify the monitoring process, we propose the use of automatic analysis of unmanned aerial vehicles (UAVs) data using the Yolov3 neural network. …”
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Portable motorized telescope system for wind turbine blades damage detection by Alejandro Carnero, Cristian Martín, Manuel Díaz

“…In addition, the manual inspection process involves a great risk. To address this challenge, in this article a preventive maintenance system for wind turbines based on deep computational learning techniques is presented. …”
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Deep Learning in motion analysis for false start detection in speedway racing by Jacek Krakowian, Łukasz Jeleń

“…This paper introduces an automated approach that leverages computer vision methods to enhance detection precision. Here, we have expanded its use to detect false starts in speedway racing. …”
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Security anomaly detection for enterprise management network based on attention mechanism by Zhaohan You, Yucai Zheng

“…This effectively reduces the loss of critical security information in the detection process. Finally, through comparative experiments, it is verified that AMSCN-GADetector exhibits superior detection performance compared to other models, providing solid technical support for the stable operation and long-term development of enterprise management.…”
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The evolution of S-nitrosylation detection methodology and the role of protein S-nitrosylation in various cancers by Feng Liang, Min Wang, Jiannan Li, Jie Guo

“…Due to the presence of reducing agents, the SNO modification process mediated by NO derivatives is often reversible and unstable. …”
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Improving esports viewing experience through hierarchical scene detection and tracking by Ho-Taek Joo, Sung-Ha Lee, Insik Chung, Kyung-Joong Kim

“…Abstract The role of an observer in esports is to provide spectators with the most engaging scenes in real time. To automate this process, various research has been conducted. In this study, we utilize Vision Transformer (ViT)-based object detection to enhance the accuracy of automatic observers. …”
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A review of underground coal fire detection technology and engineering application by ZHAO Yushen, XU Xianlei, CAO Shilong, ZHU Pengqiao

“…Based on the formation process of coal fire, this paper combines literature review, numerical analysis, physical experiments, field investigation and other methods to study the underground coal fire detection technologyies and their engineering applications. …”
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Fresh Tea Sprouts Detection via Image Enhancement and Fusion SSD by Bin Chen, Jili Yan, Ke Wang

“…In order to improve the detection performance, we rethink the process of FTSD. …”
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