Searched for: author%3A%22Taormina%2C+R.%22
(1 - 19 of 19)
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Grosfeld, J. J. (author), Schoor, M. M. (author), Taormina, R. (author), Luxemburg, W.M.J. (author), Collas, F. P.L. (author)
Current research on riverine macrolitter does not yet provide a theoretic framework on the dynamics behind its accumulation and distribution along riverbanks. In an attempt to better understand these dynamics a detailed field survey of three months was conducted in which location of macrolitter items within a single groyne field along the...
journal article 2024
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do Lago, Cesar A.F. (author), Giacomoni, Marcio H. (author), Bentivoglio, Roberto (author), Taormina, R. (author), Gomes, Marcus N. (author), Mendiondo, Eduardo M. (author)
Two-dimensional hydrodynamic models are computationally expensive. This drawback can limit their application to solving problems requiring real-time predictions or several simulation runs. Although the literature presented improvements in using Deep Learning as an alternative to hydrodynamic models, Artificial Neural Networks applications for...
journal article 2023
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Estebanez Camarena, M. (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
Food and economic security in West Africa rely heavily on rainfed agriculture and are threatened by climate change and demographic growth. Accurate rainfall information is therefore crucial to tackling these challenges. Particularly, information about the occurrence and length of droughts as well as the onset date of the rainy season is...
journal article 2023
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Murillo, Andrés (author), Taormina, R. (author), Tippenhauer, Nils Ole (author), Salaorni, Davide (author), van Dijk, Robert (author), Jonker, Luc (author), Vos, Simcha (author), Weyns, Maarten (author), Galelli, Stefano (author)
Numerical simulation models are a fundamental tool for planning and managing smart water networks—an evolution of water distribution systems in which physical assets are monitored and controlled by information and communication technologies. While simulation models allow us to understand the interactions between physical processes and abstract...
journal article 2023
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Wilbrand, K. (author), Taormina, R. (author), ten Veldhuis, Marie-claire (author), Visser, Martijn (author), Hrachowitz, M. (author), Nuttall, Jonathan (author), Dahm, Ruben (author)
Streamflow predictions remain a challenge for poorly gauged and ungauged catchments. Recent research has shown that deep learning methods based on Long Short-Term Memory (LSTM) cells outperform process-based hydrological models for rainfall-runoff modeling, opening new possibilities for prediction in ungauged basins (PUB). These studies usually...
journal article 2023
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Bentivoglio, Roberto (author), Isufi, E. (author), Jonkman, Sebastiaan N. (author), Taormina, R. (author)
Numerical modelling is a reliable tool for flood simulations, but accurate solutions are computationally expensive. In recent years, researchers have explored data-driven methodologies based on neural networks to overcome this limitation. However, most models are only used for a specific case study and disregard the dynamic evolution of the...
journal article 2023
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Jia, T. (author), Vallendar, A.J. (author), de Vries, Rinze (author), Kapelan, Z. (author), Taormina, R. (author)
Supervised Deep Learning (DL) methods have shown promise in monitoring the floating litter in rivers and urban canals but further advancements are hard to obtain due to the limited availability of relevant labeled data. To address this challenge, researchers often utilize techniques such as transfer learning (TL) and data augmentation (DA)....
journal article 2023
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Kerimov, B. (author), Bentivoglio, Roberto (author), Garzón Díaz, J.A. (author), Isufi, E. (author), Tscheikner-Gratl, Franz (author), Steffelbauer, David Bernhard (author), Taormina, R. (author)
Metamodels accurately reproduce the output of physics-based hydraulic models with a significant reduction in simulation times. They are widely employed in water distribution system (WDS) analysis since they enable computationally expensive applications in the design, control, and optimisation of water networks. Recent machine-learning-based...
journal article 2023
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Murillo, Andrés (author), Taormina, R. (author), Tippenhauer, Nils Ole (author), Galelli, Stefano (author)
A fundamental problem in the realm of cyber-physical security of smart water networks is attack detection, a key step towards designing adequate countermeasures. This task is typically carried out by algorithms that analyze time series of process data. However, the nature of the data available to develop these algorithms limits their...
journal article 2023
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Estebanez Camarena, M. (author), Curzi, Fabio (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
West African food systems and rural socio-economics are based on rainfed agriculture, which makes society highly vulnerable to rainfall uncertainty and frequent floods and droughts. Reliable rainfall information is currently missing. There is a sparse and uneven rain gauge distribution and, despite continuous efforts, rainfall satellite products...
journal article 2023
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Jia, T. (author), Kapelan, Z. (author), de Vries, Rinze (author), Vriend, Paul (author), Peereboom, Eric Copius (author), Okkerman, Imke (author), Taormina, R. (author)
Plastic pollution in water bodies is an unresolved environmental issue that damages all aquatic environments, and causes economic and health problems. Accurate detection of macroplastic litter (plastic items >5 mm) in water is essential to estimate the quantities, compositions and sources, identify emerging trends, and design preventive...
review 2023
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Glynis, K.G. (author), Kapelan, Z. (author), Bakker, Martijn (author), Taormina, R. (author)
Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new...
journal article 2023
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Vrachimis, Stelios G. (author), Eliades, Demetrios G. (author), Taormina, R. (author), Kapelan, Z. (author), Ostfeld, Avi (author), Liu, Shuming (author), Kyriakou, Marios (author), Pavlou, Pavlos (author), Qiu, Mengning (author), Polycarpou, Marios M. (author)
A key challenge in designing algorithms for leakage detection and isolation in drinking water distribution systems is the performance evaluation and comparison between methodologies using benchmarks. For this purpose, the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) competition was organized in 2020 with the aim to...
journal article 2022
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Garzón Díaz, J.A. (author), Kapelan, Z. (author), Langeveld, J.G. (author), Taormina, R. (author)
Surrogate models replace computationally expensive simulations of physically-based models to obtain accurate results at a fraction of the time. These surrogate models, also known as metamodels, have been employed for analysis, control, and optimization of water distribution and urban drainage systems. With the advent of machine learning (ML),...
review 2022
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Bentivoglio, Roberto (author), Isufi, E. (author), Jonkman, Sebastiaan N. (author), Taormina, R. (author)
Deep learning techniques have been increasingly used in flood management to overcome the limitations of accurate, yet slow, numerical models and to improve the results of traditional methods for flood mapping. In this paper, we review 58 recent publications to outline the state of the art of the field, identify knowledge gaps, and propose future...
review 2022
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Nardo, Armando Di (author), Boccelli, Dominic L. (author), Herrera, Manuel (author), Creaco, Enrico (author), Cominola, Andrea (author), Sitzenfrei, Robert (author), Taormina, R. (author)
contribution to periodical 2021
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Erba, Alessandro (author), Taormina, R. (author), Galelli, Stefano (author), Pogliani, Marcello (author), Carminati, Michele (author), Zanero, Stefano (author), Tippenhauer, Nils Ole (author)
Recently, reconstruction-based anomaly detection was proposed as an effective technique to detect attacks in dynamic industrial control networks. Unlike classical network anomaly detectors that observe the network traffic, reconstruction-based detectors operate on the measured sensor data, leveraging physical process models learned a priori....
conference paper 2020
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Hassanzadeh, Amin (author), Rasekh, Amin (author), Galelli, Stefano (author), Aghashahi, Mohsen (author), Taormina, R. (author), Ostfeld, Avi (author), Banks, M. Katherine (author)
This study presents a critical review of disclosed, documented, and malicious cybersecurity incidents in the water sector to inform safeguarding efforts against cybersecurity threats. The review is presented within a technical context of industrial control system architectures, attack-defense models, and security solutions. Fifteen incidents...
review 2020
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Pournaras, Evangelos (author), Taormina, R. (author), Thapa, Manish (author), Galelli, Stefano (author), Palleti, Venkata (author), Kooij, Robert (author)
The manageability and resilience of critical infrastructures, such as power and water networks, is challenged by their increasing interdependence and interconnectivity. Power networks often experience cascading failures, i.e. blackouts, that have unprecedented economic and social impact. Al- though knowledge exists about how to control such...
journal article 2020
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