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Laura Viola, Elisabetta Ronchieri and Claudia Cavallaro
Context?Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence and machine learning techniques to either log files or monit...
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Iman I. M. Abu Sulayman, Peter Voege and Abdelkader Ouda
The increasing significance of data analytics in modern information analysis is underpinned by vast amounts of user data. However, it is only feasible to amass sufficient data for various tasks in specific data-gathering contexts that either have limited...
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Smrithy G S,Ramadoss Balakrishnan
Pág. 225 - 232
The main objective of online anomaly detection is to identify abnormal/unusual behavior such as network intrusions, malware infections, over utilized system resources due to design defects etc from real time data stream. Terrabytes of performance data ge...
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Tianyuan Lu, Lei Wang and Xiaoyong Zhao
With the rapid development of emerging technologies such as self-media, the Internet of Things, and cloud computing, massive data applications are crossing the threshold of the era of real-time analysis and value realization, which makes data streams ubi...
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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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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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Esmaeil Zahedi, Mohamad Saraee, Fatemeh Sadat Masoumi and Mohsen Yazdinejad
Unsupervised anomalous sound detection, especially self-supervised methods, plays a crucial role in differentiating unknown abnormal sounds of machines from normal sounds. Self-supervised learning can be divided into two main categories: Generative and C...
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Steve de Rose, Philippe Meyer and Frédéric Bertrand
Accurate sizing systems of a population permit the minimization of the production costs of the textile apparel industry and allow firms to satisfy their customers. Hence, information about human body shapes needs to be extracted in order to examine, comp...
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Chouaib El Hachimi, Salwa Belaqziz, Saïd Khabba, Badreddine Sebbar, Driss Dhiba and Abdelghani Chehbouni
Smart management of weather data is an essential step toward implementing sustainability and precision in agriculture. It represents an important input for numerous tasks, such as crop growth, development, yield, and irrigation scheduling, to name a few....
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Marie Bieber, Wim J. C. Verhagen, Fabrice Cosson and Bruno F. Santos
Spacecraft systems collect health-related data continuously, which can give an indication of the systems? health status. While they rarely occur, the repercussions of such system anomalies, faults, or failures can be severe, safety-critical and costly. T...
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Nan Chen, Chun-Feng Li, Yong-Lin Wen, Peng Wang, Xiu-Lian Zhao and Xiao-Li Wan
In this study, we process four new multichannel reflection seismic profiles acquired in 2015 and 2016 in the continent?ocean transition zone (COT) of the northern South China Sea (SCS). We apply a multi-domain, progressive, and seabed-controlled denoisin...
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Juliet Chebet Moso, Stéphane Cormier, Cyril de Runz, Hacène Fouchal and John Mwangi Wandeto
Intelligent transportation systems (ITS) enhance safety, comfort, transport efficiency, and environmental conservation by allowing vehicles to communicate wirelessly with other vehicles and road infrastructure. Cooperative awareness messages (CAMs) conta...
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Fumin Zou, Yue Xing, Qiang Ren, Feng Guo, Zhaoyi Zhou and Zihan Ye
With the wide application of Electronic Toll Collection (ETC) systems, the effectiveness of the operation and maintenance of gantry equipment still need to be improved. This paper proposes a dynamic anomaly detection method for gantry transactions, utili...
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Zichen Yan, Jianzhong Sun, Yang Yi, Caiqiong Yang and Jingbo Sun
Data analysis is an important part of aero engine health management. In order to complete accurate condition monitoring, it is necessary to establish more effective analysis tools. Therefore, an integrated algorithm library dedicated for engine anomaly d...
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Guoying Wang, Jiafeng Ai, Lufeng Mo, Xiaomei Yi, Peng Wu, Xiaoping Wu and Linjun Kong
Anomaly detection has an important impact on the development of unmanned aerial vehicles, and effective anomaly detection is fundamental to their utilization. Traditional anomaly detection discriminates anomalies for single-dimensional factors of sensing...
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Giacomo Gori, Lorenzo Rinieri, Amir Al Sadi, Andrea Melis, Franco Callegati and Marco Prandini
The correct and efficient measurement of security properties is key to the deployment of effective cyberspace protection strategies. In this work, we propose GRAPH4, which is a system that combines different security metrics to design an attack detection...
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Rahul Agrahari, Matthew Nicholson, Clare Conran, Haytham Assem and John D. Kelleher
In this paper, we compare and assess the efficacy of a number of time-series instance feature representations for anomaly detection. To assess whether there are statistically significant differences between different feature representations for anomaly d...
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Abdul Razaque, Marzhan Abenova, Munif Alotaibi, Bandar Alotaibi, Hamoud Alshammari, Salim Hariri and Aziz Alotaibi
Time series data are significant, and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introduce a...
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Riku-Pekka Nikula, Mika Ruusunen and Stephan André Böhme
Machine learning techniques are commonly used in the vibration-based condition monitoring of rotating machines. However, few research studies have focused on model training from a practical viewpoint, namely, how to select representative training samples...
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Zehua Liu, Xuefeng Ding, Jun Tang, Yuming Jiang and Dasha Hu
At present, many manufacturing enterprises have business systems such as MES, SPC, etc. In the manufacturing process, a large amount of data with periodic time series will be generated. How to evaluate the timeliness of periodically generated data accord...
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