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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Kyle DeMedeiros, Chan Young Koh and Abdeltawab Hendawi
The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to a p...
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Woo-Hyun Choi and Jongwon Kim
Industrial control systems (ICSs) play a crucial role in managing and monitoring critical processes across various industries, such as manufacturing, energy, and water treatment. The connection of equipment from various manufacturers, complex communicati...
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Ishaani Priyadarshini
The swift proliferation of the Internet of Things (IoT) devices in smart city infrastructures has created an urgent demand for robust cybersecurity measures. These devices are susceptible to various cyberattacks that can jeopardize the security and funct...
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Min Hu, Fan Zhang and Huiming Wu
Various abnormal scenarios might occur during the shield tunneling process, which have an impact on construction efficiency and safety. Existing research on shield tunneling construction anomaly detection typically designs models based on the characteris...
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Marcelo Fabian Guato Burgos, Jorge Morato and Fernanda Paulina Vizcaino Imacaña
This review can be used as a guiding reference to how studies of distinct types of smart grid abnormalities are approached.
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Zitong Wang, Enrang Zheng, Jianguo Liu and Tuo Guo
Traditional methods of orthogonal basis function decomposition have been extensively used to detect magnetic anomaly signals. However, the determination of the relative velocity between the detection platform and the magnetic target remains elusive in pr...
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Ji-Woon Lee and Hyun-Soo Kang
The escalating use of security cameras has resulted in a surge in images requiring analysis, a task hindered by the inefficiency and error-prone nature of manual monitoring. In response, this study delves into the domain of anomaly detection in CCTV secu...
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George Papageorgiou, Vangelis Sarlis and Christos Tjortjis
This study utilized advanced data mining and machine learning to examine player injuries in the National Basketball Association (NBA) from 2000?01 to 2022?23. By analyzing a dataset of 2296 players, including sociodemographics, injury records, and financ...
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Alexios Lekidis, Angelos Georgakis, Christos Dalamagkas and Elpiniki I. Papageorgiou
The scheduled maintenance of industrial equipment is usually performed with a low frequency, as it usually leads to unpredicted downtime in business operations. Nevertheless, this confers a risk of failure in individual modules of the equipment, which ma...
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