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Evangelos D. Spyrou, Ioannis Tsoulos and Chrysostomos Stylios
Software-Defined Networking (SDN) stands as a pivotal paradigm in network implementation, exerting a profound influence on the trajectory of technological advancement. The critical role of security within SDN cannot be overstated, with distributed denial...
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Evangelos Rozos
Machine learning has been used in hydrological applications for decades, and recently, it was proven to be more efficient than sophisticated physically based modelling techniques. In addition, it has been used in hybrid frameworks that combine hydrologic...
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Muhammad Usman, Mahnoor Ejaz, Janet E. Nichol, Muhammad Shahid Farid, Sawaid Abbas and Muhammad Hassan Khan
Farmland trees are a vital part of the local economy as trees are used by farmers for fuelwood as well as food, fodder, medicines, fibre, and building materials. As a result, mapping tree species is important for ecological, socio-economic, and natural r...
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Ashokkumar Palanivinayagam and Robertas Dama?evicius
The existence of missing values reduces the amount of knowledge learned by the machine learning models in the training stage thus affecting the classification accuracy negatively. To address this challenge, we introduce the use of Support Vector Machine ...
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Violeta Migallón, Héctor Penadés, José Penadés and Antonio José Tenza-Abril
Lightweight aggregate concrete (LWAC) is an increasingly important material for modern construction. However, although it has several advantages compared with conventional concrete, it is susceptible to segregation due to the low density of the incorpora...
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Evangelos Rozos, Demetris Koutsoyiannis and Alberto Montanari
Uncertainty is inherent in the modelling of any physical processes. Regarding hydrological modelling, the uncertainty has multiple sources including the measurement errors of the stresses (the model inputs), the measurement errors of the hydrological pro...
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Yifan Gao, Vicente A. González, Tak Wing Yiu, Guillermo Cabrera-Guerrero and Ruiqi Deng
Dynamic environmental circumstances can sometimes be incompatible with proactive human intentions of being safe, leading individuals to take unintended risks. Behaviour predictions, as performed in previous studies, are found to involve environmental cir...
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Luca Braidotti, Marko Valcic and Jasna Prpic-Or?ic
Recently, progressive flooding simulations have been applied onboard to support decisions during emergencies based on the outcomes of flooding sensors. However, only a small part of the existing fleet of passenger ships is equipped with flooding sensors....
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Julien Chevallier, Dominique Guégan and Stéphane Goutte
This paper focuses on forecasting the price of Bitcoin, motivated by its market growth and the recent interest of market participants and academics. We deploy six machine learning algorithms (e.g., Artificial Neural Network, Support Vector Machine, Rando...
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Erjon Skenderi, Jukka Huhtamäki and Kostas Stefanidis
In this paper, we consider the task of assigning relevant labels to studies in the social science domain. Manual labelling is an expensive process and prone to human error. Various multi-label text classification machine learning approaches have been pro...
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