Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The increasing penetration of renewable energy into power systems has intensified transient power quality (PQ) disturbances, demanding efficient detection and classification methods to enable timely operational decisions. …”
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Detection and diagnosis of unknown threats in power equipment using machine learning and Spark technology by Li Di, Cen Chen, Zhuo Lv, Mingyan Li, Nuannuan Li, Hao Chang

“…This approach allows for more efficient and accurate detection of unknown threat attacks on power grid equipment, providing robust network security for power systems. …”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

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Anomaly detection method for cyber physical power system based on bilateral data fusion by Tianlei Zang, Shijun Wang, Chuangzhi Li, Yunfei Liu, Yujian Xiao, Zian Wang, Xueying Yu

“…A cyber-physical bilateral data-driven composite model is proposed in this paper to achieve efficient and accurate anomaly detection of CPPS. The novel model can depict data decomposition and feature extraction from both cyber and physical domains. …”
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Defects Localization and Classification Method of Power Transmission Line Insulators Aerial Images Based on YOLOv5 EfficientNet and SVM by Lin Li, Qiaoling Yin, Xiaofeng Wang, Hang Wang

“…The framework specifically targets overcoming the challenges associated with low signal-to-noise ratios in defect detection. The proposed approach divides the task into two primary modules: 1) YOLOv5-based object detection for accurate defect localization, and 2) defect classification using EfficientNet and SVM. …”
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Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art by Daniela F. Niste, Radu Tîrnovan, Sorin Pavel, Horia Beleiu, Cziker Andrei, Marius Misaroș

“…The present paper explores the significance of examining power losses in power grids and proposes methods to identify and reduce them. …”
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Optimising Solar Power Plant Reliability Using Neural Networks for Fault Detection and Diagnosis by Mohammed Bouzidi, Abdelfatah Nasri, Omar Ouledali, Messaoud Hamouda

“…This study introduces an intelligent method to monitor grid-connected solar power stations, focussing on detecting problems in their energy output through the use of artificial neural networks (ANN). …”
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Research on Detection and Optimization Measures of High-speed EMU Power Network Voltage Interruption by Hong SHEN, Dong CHEN, Gang FU

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Research on Suspended Monorail Traction Power Return Grounding Fault Detection Protection Mechanism by ZHANG Kun, YUAN Wenye, LIU Xiang, WANG Lichao

“…In order to avoid the impact on other normal equipment, and help maintenance personnel locking the fault area quickly and accurately, improvements were made by canceling the grounding overvoltage relay on the train and increasing the differential current detection device of the on-board equipment. Meanwhile, a hierarchical grounding detection and protection mechanism was proposed for the protection and fast positioning of traction power return grounding fault. …”
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A Comparative Study of Customized Algorithms for Anomaly Detection in Industry-Specific Power Data by Minsung Jung, Hyeonseok Jang, Woohyeon Kwon, Jiyun Seo, Suna Park, Beomdo Park, Junseong Park, Donggeon Yu, Sangkeum Lee

“…This study compares and analyzes statistical, machine learning, and deep learning outlier-detection methods on real power-usage data from the metal, food, and chemical industries to propose the optimal model for improving energy-consumption efficiency. …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…The performance of the optimized model in fault detection is increased by more than 36%. In conclusion, the proposed model improves the accuracy and scope of inspection, provides a more scientific strategy for electric power inspection, and ensures inspection efficiency.…”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…This study presents a novel adaptation of the Hoeffding Adaptive Tree (HAT) classifier with an instance selection algorithm that detects and identifies cyber and non-cyber contingencies in real time to enhance the situational awareness of cyber-physical power systems (CPPS). …”
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Sensor Switching-Based Automatic Misalignment Detection and Correction System for Wireless Power Transfer by Ali Younis Al Dahhan, Shayok Mukhopadhyay, Mohamed S. Hassan, Ahmed H. Osman

“…Misalignment between the transmitting and receiving coils is an inevitable problem for electric vehicle (EV) wireless power transfer (WPT) systems. Regardless of the WPT system being static or dynamic, coil misalignment reduces the efficiency of the charging system. …”
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PPLA-Transformer: An Efficient Transformer for Defect Detection with Linear Attention Based on Pyramid Pooling by Xiaona Song, Yubo Tian, Haichao Liu, Lijun Wang, Jinxing Niu

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SFG-YOLOv8: efficient and lightweight small-feature gesture keypoint detector by Weimin Che, Hui Zhang, Bangxue Wu, Qun Li, Hongji Zhang, Shilong Yuan, Hongcheng Yang

“…This paper introduces SFG-YOLOv8, an efficient and lightweight gesture keypoint detector designed for low-computational-power AR scenarios. …”
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Energy-Efficient SAR Coherent Change Detection Based on Deep Multithreshold Spiking-UNet by Xinyi Ye, Yanxing Liu, Zihan Wang, Yizhe Fan, Bingchen Zhang

“…Spiking neural networks (SNNs) not only infer results more energy-efficiently but also have the potential to drive ultralow-power neuromorphic computers which ANNs lack. …”
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An Energy Efficient, Robust, Sustainable, and Low Computational Cost Method for Mobile Malware Detection by Rohan Chopra, Saket Acharya, Umashankar Rawat, Roheet Bhatnagar

“…Several machine learning and deep learning techniques have been proposed to retaliate to such problems; nevertheless, they demand high computational power and are not energy efficient. Hence, this article presents an approach to distinguish between benign and malicious malware, which is robust, cost-efficient, and energy-saving by characterizing CNN-based architectures such as the traditional CNN, AlexNet, ResNet, and LeNet-5 and using transfer learning to determine the most efficient framework. …”
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HiViT-IDS: An Efficient Network Intrusion Detection Method Based on Vision Transformer by Hai Zhou, Haojie Zou, Wei Li, Di Li, Yinchun Kuang

“…To balance high detection accuracy with reduced time consumption, this study introduces an efficient intrusion detection approach based on the Vision Transformer (ViT), utilizing its powerful feature extraction capabilities to enhance performance. …”
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NFE-YOLO: A Lightweight and Efficient Detection Network for Low, Slow, and Small Drones by Dan Tian, Chen Wang, Dong Zhou, Xin Yan, Liaoyuan Zeng

“…To address these challenges, we propose a lightweight and efficient drone detection network called NFE-YOLO. …”
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Assessing acoustic receiver detection efficiency using autocorrelation adjusted machine learning models by Devon A. Smith, James A. Crossman, Eduardo G. Martins

“…It is influenced by environmental (e.g., discharge), technological (e.g., transmitter power), and habitat (e.g., noise) factors, making predictions of detection efficiency a challenging task in the field of movement ecology. …”
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