Zobrazeno 1 - 10
of 304
pro vyhledávání: '"Roberto Ruíz"'
Publikováno v:
Symmetry, Vol 16, Iss 6, p 726 (2024)
Currently, Internet of Things (IoT)-based cloud systems face several problems such as privacy leakage, failure in centralized operation, managing IoT devices, and malicious attacks. The data transmission between the cloud and healthcare IoT needs tru
Externí odkaz:
https://doaj.org/article/0b25c9fa5ca545398aa5d376af70f897
Autor:
Attila Szabo, Ricardo de la Vega, Rita Kovácsik, Lucia Jiménez Almendros, Roberto Ruíz-Barquín, Zsolt Demetrovics, Szilvia Boros, Ferenc Köteles
Publikováno v:
Addictive Behaviors Reports, Vol 16, Iss , Pp 100451- (2022)
This study was performed to investigate further the two-dimensional aspect of passion and its relationship to the risk of exercise addiction (REA) in nine nations and to clarify the unresolved gender differences. The here reported results stem from t
Externí odkaz:
https://doaj.org/article/320a805743c04732b9f00e5a924aa734
Autor:
Albert, Joshua, Balazs, Csaba, Fowlie, Andrew, Handley, Will, Hunt-Smith, Nicholas, de Austri, Roberto Ruiz, White, Martin
For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of their free parameters. In this study, we review and compare a wide ran
Externí odkaz:
http://arxiv.org/abs/2409.18464
Autor:
Caron, Sascha, Dobreva, Nadezhda, Sánchez, Antonio Ferrer, Martín-Guerrero, José D., Odyurt, Uraz, Bazan, Roberto Ruiz de Austri, Wolffs, Zef, Zhao, Yue
High-Energy Physics experiments are facing a multi-fold data increase with every new iteration. This is certainly the case for the upcoming High-Luminosity LHC upgrade. Such increased data processing requirements forces revisions to almost every step
Externí odkaz:
http://arxiv.org/abs/2407.07179
Autor:
Caron, Sascha, Navarro, José Enrique García, Llácer, María Moreno, Moskvitina, Polina, Rovers, Mats, Jímenez, Adrián Rubio, de Austri, Roberto Ruiz, Zhang, Zhongyi
In this work, we present a novel approach to transform supervised classifiers into effective unsupervised anomaly detectors. The method we have developed, termed Discriminatory Detection of Distortions (DDD), enhances anomaly detection by training a
Externí odkaz:
http://arxiv.org/abs/2406.18469
The detection of Dark Matter (DM) remains a significant challenge in particle physics. This study exploits advanced machine learning models to improve detection capabilities of liquid xenon time projection chamber experiments, utilizing state-of-the-
Externí odkaz:
http://arxiv.org/abs/2406.10372
Autor:
Raquel Menendez-Ferreira, Antonio Gonzalez-Pardo, Roberto Ruíz Barquín, Antonio Maldonado, David Camacho
Publikováno v:
Vietnam Journal of Computer Science, Vol 6, Iss 1, Pp 57-67 (2019)
Nowadays, it is quite common to find violent acts in grassroot sports, such as football. Almost every week, it is possible to find news about team supporters fighting against each other, or football players arguing aggressively to the referee. And th
Externí odkaz:
https://doaj.org/article/99185acaea4a4b4db15b7e168ffd560d
Autor:
Odyurt, Uraz, Dobreva, Nadezhda, Wolffs, Zef, Zhao, Yue, Sánchez, Antonio Ferrer, Bazan, Roberto Ruiz de Austri, Martín-Guerrero, José D., Varbanescu, Ana-Lucia, Caron, Sascha
Track reconstruction is a vital aspect of High-Energy Physics (HEP) and plays a critical role in major experiments. In this study, we delve into unexplored avenues for particle track reconstruction and hit clustering. Firstly, we enhance the algorith
Externí odkaz:
http://arxiv.org/abs/2405.17325
Autor:
Arina, Chiara, Di Mauro, Mattia, Fornengo, Nicolao, Heisig, Jan, Jueid, Adil, de Austri, Roberto Ruiz
The energy spectra of particles produced from dark matter (DM) annihilation or decay are one of the fundamental ingredients to calculate the predicted fluxes of cosmic rays and radiation searched for in indirect DM detection. We revisit the calculati
Externí odkaz:
http://arxiv.org/abs/2312.01153
Autor:
Aehle, Max, Arsini, Lorenzo, Barreiro, R. Belén, Belias, Anastasios, Bury, Florian, Cebrian, Susana, Demin, Alexander, Dickinson, Jennet, Donini, Julien, Dorigo, Tommaso, Doro, Michele, Gauger, Nicolas R., Giammanco, Andrea, Gray, Lindsey, González, Borja S., Kain, Verena, Kieseler, Jan, Kusch, Lisa, Liwicki, Marcus, Maier, Gernot, Nardi, Federico, Ratnikov, Fedor, Roussel, Ryan, de Austri, Roberto Ruiz, Sandin, Fredrik, Schenk, Michael, Scarpa, Bruno, Silva, Pedro, Strong, Giles C., Vischia, Pietro
In this article we examine recent developments in the research area concerning the creation of end-to-end models for the complete optimization of measuring instruments. The models we consider rely on differentiable programming methods and on the spec
Externí odkaz:
http://arxiv.org/abs/2310.05673