|
|
|
|
|
Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Eleonora Congiu, Giuseppe Desogus, Caterina Frau, Gianluca Gatto and Stefano Pili
In this paper, we present the final results from the research project ?Urban Abacus of Building Energy Performances (Abaco Urbano Energeticodegli Edifci?AUREE)? aimed at supporting the renovation process and energy efficiency enhancement of urban buildin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Michele Placido Antonio Gatto
Extreme and prolonged rainfall resulting from global warming determines a growing need for reliable Landslide Early Warning Systems (LEWS) to manage the risk of rainfall-induced shallow landslides (also called soil slips). Regional LEWS are typically bas...
ver más
|
|
|
|
|
|
|
|
|
|
|
Muriel Cabianca, Maria Laura Clemente, Gianluca Gatto, Carlo Impagliazzo, Lidia Leoni, Martino Masia and Riccardo Piras
This paper presents an exploratory activity with a drone inspection service for environmental control. The aim of the service is to provide technical support to decision-makers in environmental risk management. The proposed service uses IoT for the inter...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrea Gatto, Valeria Aloisi, Gabriele Accarino, Francesco Immorlano, Marco Chiarelli and Giovanni Aloisio
Since December 2019, the novel coronavirus disease (COVID-19) has had a considerable impact on the health and socio-economic fabric of Italy. The effective reproduction number Rt is one of the most representative indicators of the contagion status as it ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giovanni Falisi, Giordano Foffo, Marco Severino, Carlo Di Paolo, Serena Bianchi, Sara Bernardi, Davide Pietropaoli, Sofia Rastelli, Roberto Gatto and Gianluca Botticelli
The preparation of the implant site in guided surgery procedure takes place without irrigation, which could lead to increased friction of the drills with the formation and release of debris or metal particles. The presence of metal particles in the peri-...
ver más
|
|
|
|
|
|
|
|
|
|
|
Corrado Gatto, Gerald C. Blazey, Alexandre Dychkant, Jeffrey W. Elam, Michael Figora, Todd Fletcher, Kurt Francis, Ao Liu, Sergey Los, Cole Le Mahieu, Anil U. Mane, Juan Marquez, Michael J. Murray, Erik Ramberg, Christophe Royon, Michael J. Syphers, Robert W. Young and Vishnu Zutshi
A novel high-granularity, dual-readout calorimetric technique (ADRIANO2) is under development as part of the research program of T1604 Collaboration. (Talk Presented at the 19th International Conference on Calorimetry in Particle Physics (CALOR 2022), Un...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giuseppe Gallo, Adriano Isoldi, Dario Del Gatto, Raffaele Savino, Amedeo Capozzoli, Claudio Curcio and Angelo Liseno
The present work is focused on a detailed description of an in-house, particle-in-cell code developed by the authors, whose main aim is to perform highly accurate plasma simulations on an off-the-shelf computing platform in a relatively short computation...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrea Gatto, Gabriele Accarino, Valeria Aloisi, Francesco Immorlano, Francesco Donato and Giovanni Aloisio
Compartmental models have long been used in epidemiological studies for predicting disease spread. However, a major issue when using compartmental mathematical models concerns the time-invariant formulation of hyper-parameters that prevent the model from...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gabriele Accarino, Marco Chiarelli, Francesco Immorlano, Valeria Aloisi, Andrea Gatto and Giovanni Aloisio
One of the most important open challenges in climate science is downscaling. It is a procedure that allows making predictions at local scales, starting from climatic field information available at large scale. Recent advances in deep learning provide new...
ver más
|
|
|
|
|
|