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Eike Blomeier, Sebastian Schmidt and Bernd Resch
In the early stages of a disaster caused by a natural hazard (e.g., flood), the amount of available and useful information is low. To fill this informational gap, emergency responders are increasingly using data from geo-social media to gain insights fro...
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Yao Meng, Xianku Zhang, Guoqing Zhang, Xiufeng Zhang and Yating Duan
In order to establish a sparse and accurate ship motion prediction model, a novel Bayesian probability prediction model based on relevance vector machine (RVM) was proposed for nonparametric modeling. The sparsity, effectiveness, and generalization of RV...
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Silvia Golia, Luigi Grossi and Matteo Pelagatti
In this paper we assess how intra-day electricity prices can improve the prediction of zonal day-ahead wholesale electricity prices in Italy. We consider linear autoregressive models with exogenous variables (ARX) with and without interactions among pred...
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Suraj Kumar Nayak, Bikash Pradhan, Biswaranjan Mohanty, Jayaraman Sivaraman, Sirsendu Sekhar Ray, Jolanta Wawrzyniak, Maciej Jarzebski and Kunal Pal
Heart rate variability (HRV) has emerged as an essential non-invasive tool for understanding cardiac autonomic function over the last few decades. This can be attributed to the direct connection between the heart?s rhythm and the activity of the sympathe...
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Abdelhafid El Alaoui El Fels, Laila Mandi, Aya Kammoun, Naaila Ouazzani, Olivier Monga and Moulay Lhassan Hbid
The concept of using wastewater as a substitute for limited water resources and environmental protection has enabled this sector to make major technological advancements and, as a result, has given us an abundance of physical data, including chemical, bi...
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Anastasia Fedotova, Aleksandr Romanov, Anna Kurtukova and Alexander Shelupanov
Authorship attribution is one of the important fields of natural language processing (NLP). Its popularity is due to the relevance of implementing solutions for information security, as well as copyright protection, various linguistic studies, in particu...
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Jinwan Park and Jung-Sik Jeong
According to the statistics of maritime collision accidents over the last five years (2016?2020), 95% of the total maritime collision accidents are caused by human factors. Machine learning algorithms are an emerging approach in judging the risk of colli...
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Marvin F. Li, Patricia M. Glibert and Vyacheslav Lyubchich
Harmful algal blooms (HABs), events that kill fish, impact human health in multiple ways, and contaminate water supplies, have increased in frequency, magnitude, and impacts in numerous marine and freshwaters around the world. Blooms of the toxic dinofla...
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Anis Malekzadeh, Assef Zare, Mahdi Yaghoobi and Roohallah Alizadehsani
This paper proposes a new method for epileptic seizure detection in electroencephalography (EEG) signals using nonlinear features based on fractal dimension (FD) and a deep learning (DL) model. Firstly, Bonn and Freiburg datasets were used to perform exp...
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Mattia Zanon, Giuliano Zambonin, Gian Antonio Susto and Seán McLoone
In knowledge-based systems, besides obtaining good output prediction accuracy, it is crucial to understand the subset of input variables that have most influence on the output, with the goal of gaining deeper insight into the underlying process. These re...
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