Zobrazeno 1 - 10
of 2 725
pro vyhledávání: '"A. Spinello"'
Publikováno v:
Brain and Spine, Vol 2, Iss , Pp 101513- (2022)
Externí odkaz:
https://doaj.org/article/2f9923fe666a4013b02aa31ab6733bcd
Publikováno v:
Journal of Dynamic Systems, Measurement, and Control. February 2023; 145(2)
We propose a Kullback-Leibler Divergence (KLD) filter to extract anomalies within data series generated by a broad class of proximity sensors, along with the anomaly locations and their relative sizes. The technique applies to devices commonly used i
Externí odkaz:
http://arxiv.org/abs/2405.03047
Autor:
Marta Canuti, Federico Fassio, Camilla Genovese, Andrea Giacomelli, Anna Lisa Ridolfo, Erika Asperges, Giuseppe Albi, Raffaele Bruno, Spinello Antinori, Antonio Muscatello, Bianca Mariani, Ciro Canetta, Francesco Blasi, Alessandra Bandera, Andrea Gori, Marta Colaneri
Publikováno v:
Infectious Diseases and Therapy, Vol 13, Iss 11, Pp 2471-2474 (2024)
Externí odkaz:
https://doaj.org/article/65c76b3a66754ce09287c3cdf1ba4413
Publikováno v:
IEEE International Symposium on Robotic and Sensors Environments (ROSE) 2021
The flocking motion control is concerned with managing the possible conflicts between local and team objectives of multi-agent systems. The overall control process guides the agents while monitoring the flock-cohesiveness and localization. The underl
Externí odkaz:
http://arxiv.org/abs/2303.10035
Publikováno v:
IEEE International Symposium on Robotic and Sensors Environments (ROSE) 2021
Model-reference adaptive systems refer to a consortium of techniques that guide plants to track desired reference trajectories. Approaches based on theories like Lyapunov, sliding surfaces, and backstepping are typically employed to advise adaptive c
Externí odkaz:
http://arxiv.org/abs/2303.09994
Publikováno v:
IEEE International Conference on Robotics and Automation (ICRA) 2021
The flock-guidance problem enjoys a challenging structure where multiple optimization objectives are solved simultaneously. This usually necessitates different control approaches to tackle various objectives, such as guidance, collision avoidance, an
Externí odkaz:
http://arxiv.org/abs/2303.09946
Real-Time Measurement-Driven Reinforcement Learning Control Approach for Uncertain Nonlinear Systems
Publikováno v:
Engineering Applications of Artificial Intelligence (Elsevier), vol. 122, June 2023
The paper introduces an interactive machine learning mechanism to process the measurements of an uncertain, nonlinear dynamic process and hence advise an actuation strategy in real-time. For concept demonstration, a trajectory-following optimization
Externí odkaz:
http://arxiv.org/abs/2303.08745
Optical satellite-to-ground communication (OSGC) has the potential to improve access to fast and affordable Internet in remote regions. Atmospheric turbulence, however, distorts the optical beam, eroding the data rate potential when coupling into sin
Externí odkaz:
http://arxiv.org/abs/2303.07516
Autor:
Richard A. Spinello
Publikováno v:
Studia Gilsoniana, Vol 13, Iss 2, Pp 369-398 (2024)
After a cursory review of Wojtyła’s anthropology and his philosophy of freedom as self-transcendence aiming at the true good, this paper turned to his treatment of intersubjective relationships. We explained the core concept of participation, a pr
Externí odkaz:
https://doaj.org/article/ee905aa2f9d743fdb61f426b7e3493bd
Autor:
Valentina Mazzotta, Silvia Nozza, Simone Lanini, Davide Moschese, Alessandro Tavelli, Roberto Rossotti, Francesco Maria Fusco, Lorenzo Biasioli, Giulia Matusali, Angelo Roberto Raccagni, Davide Mileto, Chiara Maci, Giuseppe Lapadula, Antonio Di Biagio, Luca Pipitò, Enrica Tamburrini, Antonella d’Arminio Monforte, Antonella Castagna, Andrea Antinori, Spinello Antinori, Chiara Baiguera, Gianmaria Baldin, Matteo Bassetti, Paolo Bonfanti, Giorgia Brucci, Elena Bruzzesi, Caterina Candela, Antonio Cascio, Antonella d'Arminio Monforte, Andrea Delama, Gabriella D'Ettorre, Damiano Farinacci, Maria Rita Gismondo, Andrea Gori, Massimiliano Lanzafame, Miriam Lichtner, Giulia Mancarella, Alessandro Mancon, Giulia Marchetti, Emanuele Nicastri, Alessandro Pandolfo, Francesca Panzo, Stefania Piconi, Carmela Pinnetti, Alessandro Raimondi, Marco Ridolfi, Giuliano Rizzardini, Alessandra Rodanò, Margherita Sambo, Vincenzo Sangiovanni, Nadia Sangiovanni, Daniele Tesoro, Serena Vita
Publikováno v:
EBioMedicine, Vol 107, Iss , Pp 105289- (2024)
Summary: Background: Severe and prolonged mpox courses have been described during the 2022–2023 outbreak. Identifying predictors of severe evolution is crucial for improving management and therapeutic strategies. We explored the predictors of mpox
Externí odkaz:
https://doaj.org/article/ee0528c861034ad8aa54758b34334546