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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Luis Alberto Vargas-León and Juan Diego Giraldo-Osorio
In this work, the influence of the El Niño Southern Oscillation (ENSO) on the Extreme Precipitation Indices (EPIs) was analyzed, and these ENSO-forced anomalies were compared with the long-term change in the EPIs. The annual time series of the EPIs were ...
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Sergey Loginov, Evgeniia Moraru, Elena Kharyutkina and Ivan Sudakow
The analysis of spatial and temporal variability in the number of non-Gaussian extreme anomalies of climatic parameters was carried out for both the initial time series and synoptic variability in the troposphere of the Northern Hemisphere over the perio...
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Mohamed Shenify, Fokrul Alom Mazarbhuiya and A. S. Wungreiphi
There are many applications of anomaly detection in the Internet of Things domain. IoT technology consists of a large number of interconnecting digital devices not only generating huge data continuously but also making real-time computations. Since IoT d...
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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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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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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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Yussuf Ahmed, Muhammad Ajmal Azad and Taufiq Asyhari
In recent years, there has been a notable surge in both the complexity and volume of targeted cyber attacks, largely due to heightened vulnerabilities in widely adopted technologies. The Prediction and detection of early attacks are vital to mitigating p...
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Roberto Besteiro, Tamara Arango, Manuel R. Rodríguez and María D. Fernández
This study characterizes the growth of weaned Large White × Landrace hybrid piglets from 6 to 20 kg live body weight (BW) under real farm conditions. Batches of 50 castrated male pigs and 50 gilts were weighed repeatedly over two 6-week breeding cycles. ...
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