Zobrazeno 1 - 10
of 224
pro vyhledávání: '"Luca Oneto"'
Publikováno v:
IEEE Access, Vol 12, Pp 76102-76120 (2024)
Optimizing vessel hull resistance is pivotal for enhancing maritime performance and minimizing environmental impacts. Traditional methods combine expert intuition with Data-Driven Models (DDMs), relying on parametrization to predict and optimize hull
Externí odkaz:
https://doaj.org/article/04405607232a44288e378d40243ba492
Publikováno v:
IEEE Access, Vol 12, Pp 6494-6517 (2024)
Due to increasing environmental concerns and global energy demand, the development of Floating Offshore Wind Turbines (FOWTs) is on the rise. FOWTs offer a promising solution to expand wind farm deployment into deeper waters with abundant wind resour
Externí odkaz:
https://doaj.org/article/ab42775c86e946b5aa1365e098561316
Autor:
Gabriele Cecchetti, Anna Lina Ruscelli, Cristian Ulianov, Paul Hyde, Airy Magnien, Luca Oneto, Jose Bertolin
Publikováno v:
Transportation Engineering, Vol 15, Iss , Pp 100222- (2024)
Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this ne
Externí odkaz:
https://doaj.org/article/8b6e9b6bac8f472a9174e7ecef5c1dec
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 12 (2022)
Applying computational statistics or machine learning methods to data is a key component of many scientific studies, in any field, but alone might not be sufficient to generate robust and reliable outcomes and results. Before applying any discovery m
Externí odkaz:
https://doaj.org/article/32379077850a48e2bb6e3e43f6df4159
Autor:
Sebastiano Barco, Chiara Lavarello, Davide Cangelosi, Martina Morini, Alessandra Eva, Luca Oneto, Paolo Uva, Gino Tripodi, Alberto Garaventa, Massimo Conte, Andrea Petretto, Giuliana Cangemi
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
Neuroblastoma (NB) is the most common extracranial malignant tumor in children. Although the survival rate of NB has improved over the years, the outcome of NB still remains poor for over 30% of cases. A more accurate risk stratification remains a ke
Externí odkaz:
https://doaj.org/article/7a8128a33d5945b2aca2068cbc2d064d
Autor:
Davide Chicco, Luca Oneto
Publikováno v:
BioData Mining, Vol 14, Iss 1, Pp 1-22 (2021)
Abstract Background Sepsis is a life-threatening clinical condition that happens when the patient’s body has an excessive reaction to an infection, and should be treated in one hour. Due to the urgency of sepsis, doctors and physicians often do not
Externí odkaz:
https://doaj.org/article/258879fbb1334e78bbcd7fa0e8339bab
Autor:
Patricia Ruiz Martino, Luca Oneto, Irene Buselli, Christian Verdonk Gallego, Carlo Dambra, Anthony Smoker, Miguel García Martínez, Tamara Pejovic, Nnenna Ike
Publikováno v:
Open Research Europe, Vol 1 (2022)
Background: The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it
Externí odkaz:
https://doaj.org/article/66521eb36feb41e5b09bb41ba9280387
Publikováno v:
IEEE Access, Vol 9, Pp 165132-165144 (2021)
Chronic kidney disease (CKD) describes a long-term decline in kidney function and has many causes. It affects hundreds of millions of people worldwide every year. It can have a strong negative impact on patients, especially when combined with cardiov
Externí odkaz:
https://doaj.org/article/87404400f110453886f767b2d57a5044
Publikováno v:
Entropy, Vol 23, Iss 8, p 1047 (2021)
In many decision-making scenarios, ranging from recreational activities to healthcare and policing, the use of artificial intelligence coupled with the ability to learn from historical data is becoming ubiquitous. This widespread adoption of automate
Externí odkaz:
https://doaj.org/article/7e6b14c55845485b9126066f0975be1a
Autor:
Luca Oneto, Sandro Ridella
Publikováno v:
Entropy, Vol 23, Iss 1, p 101 (2021)
In this paper, we deal with the classical Statistical Learning Theory’s problem of bounding, with high probability, the true risk R(h) of a hypothesis h chosen from a set H of m hypotheses. The Union Bound (UB) allows one to state that PLR^(h),δqh
Externí odkaz:
https://doaj.org/article/2f1ac63c34f44d52b7ae824395f62142