Zobrazeno 1 - 10
of 10 664
pro vyhledávání: '"A, Bettini"'
Autor:
Baibussinov, B., Bettini, M., Fabris, F., Guglielmi, A., Marchini, S., Meng, G., Nicoletto, M., Pietropaolo, F., Rampazzo, G., Triozzi, R., Varanini, F.
The use of double-faced, metallized, perforated PCB planes, segmented into strips for the anodic read-out of ionization signals in liquid argon TPCs, is emerging as a promising technology for charge readout in liquid argon TPCs used in large volume d
Externí odkaz:
http://arxiv.org/abs/2407.19105
Recognizing daily activities with unobtrusive sensors in smart environments enables various healthcare applications. Monitoring how subjects perform activities at home and their changes over time can reveal early symptoms of health issues, such as co
Externí odkaz:
http://arxiv.org/abs/2408.06352
The sensor-based recognition of Activities of Daily Living (ADLs) in smart home environments enables several applications in the areas of energy management, safety, well-being, and healthcare. ADLs recognition is typically based on deep learning meth
Externí odkaz:
http://arxiv.org/abs/2407.01238
Autor:
GERDA Collaboration, Agostini, M., Alexander, A., Araujo, G. R., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., Belogurov, S., Bettini, A., Bezrukov, L., Biancacci, V., Bossio, E., Bothe, V., Brugnera, R., Caldwell, A., Calgaro, S., Cattadori, C., Chernogorov, A., Chiu, P. -J., Comellato, T., D'Andrea, V., Demidova, E. V., Di Marco, N., Doroshkevich, E., Fomina, M., Gangapshev, A., Garfagnini, A., Gooch, C., Grabmayr, P., Gurentsov, V., Gusev, K., Hakenmüller, J., Hemmer, S., Hofmann, W., Huang, J., Hult, M., Inzhechik, L. V., Csáthy, J. Janicskó, Jochum, J., Junker, M., Kazalov, V., Kermaïdic, Y., Khushbakht, H., Kihm, T., Kilgus, K., Kirpichnikov, I. V., Klimenko, A., Knöpfle, K. T., Kochetov, O., Kornoukhov, V. N., Krause, P., Kuzminov, V. V., Laubenstein, M., Lindner, M., Lippi, I., Lubashevskiy, A., Lubsandorzhiev, B., Lutter, G., Macolino, C., Majorovits, B., Maneschg, W., Marshall, G., Misiaszek, M., Morella, M., Müller, Y., Nemchenok, I., Neuberger, M., Pandola, L., Pelczar, K., Pertoldi, L., Piseri, P., Pullia, A., Ransom, C., Rauscher, L., Redchuk, M., Riboldi, S., Rumyantseva, N., Sada, C., Sailer, S., Salamida, F., Schönert, S., Schreiner, J., Schütz, A-K., Schulz, O., Schwarz, M., Schwingenheuer, B., Selivanenko, O., Shevchik, E., Shirchenko, M., Shtembari, L., Simgen, H., Smolnikov, A., Stukov, D., Sullivan, S., Vasenko, A. A., Veresnikova, A., Vignoli, C., von Sturm, K., Wester, T., Wiesinger, C., Wojcik, M., Yanovich, E., Zatschler, B., Zhitnikov, I., Zhukov, S. V., Zinatulina, D., Zschocke, A., Zuber, K., Zuzel, G.
A search for full energy depositions from bosonic keV-scale dark matter candidates of masses between 65 keV and 1021 keV has been performed with data collected during Phase II of the GERmanium Detector Array (GERDA) experiment. Our analysis includes
Externí odkaz:
http://arxiv.org/abs/2405.15954
The study of behavioral diversity in Multi-Agent Reinforcement Learning (MARL) is a nascent yet promising field. In this context, the present work deals with the question of how to control the diversity of a multi-agent system. With no existing appro
Externí odkaz:
http://arxiv.org/abs/2405.15054
Compact robotic platforms with powerful compute and actuation capabilities are key enablers for practical, real-world deployments of multi-agent research. This article introduces a tightly integrated hardware, control, and simulation software stack o
Externí odkaz:
http://arxiv.org/abs/2405.02198
Autor:
Lucchini, Francesco, Frescura, Alessandro, Torchio, Riccardo, Alotto, Piergiorgio, Bettini, Paolo
The real-time monitoring of the structural displacement of the Vacuum Vessel (VV) of thermonuclear fusion devices caused by electromagnetic (EM) loads is of great interest. In this paper, Model Order Reduction (MOR) is applied to the Integral Equatio
Externí odkaz:
http://arxiv.org/abs/2405.01406
Autor:
Ek, Sannara, Presotto, Riccardo, Civitarese, Gabriele, Portet, François, Lalanda, Philippe, Bettini, Claudio
Human Activity Recognition (HAR) based on the sensors of mobile/wearable devices aims to detect the physical activities performed by humans in their daily lives. Although supervised learning methods are the most effective in this task, their effectiv
Externí odkaz:
http://arxiv.org/abs/2404.15331
Context-aware Human Activity Recognition (HAR) is a hot research area in mobile computing, and the most effective solutions in the literature are based on supervised deep learning models. However, the actual deployment of these systems is limited by
Externí odkaz:
http://arxiv.org/abs/2403.06586
Autor:
Cardoso, Micaele Niobe Martins, Azevedo, Fernanda, Dias, Alan, de Almeida, Ana Carolina Sousa, Senna, André R., Marques, Antonio C., Rezende, Dafinny, Hajdu, Eduardo, Lopes-Filho, Erick Alves Pereira, Pitombo, Fábio Bettini, de Oliveira, Gabriela Moura, Doria, João Gabriel, Carraro, João Luís, De-Paula, Joel Campos, Bahia, Juliana, de Araujo, Juliana Magalhães, Paresque, Karla, Vieira, Leandro Manzoni, Fernandes, Luanny Martins, Santos, Luciano N., Miranda, Lucília Souza, Lorini, Maria Lucia, Klautau, Michelle, Pagliosa, Paulo Roberto, Clerier, Pedro Henrique Braga, de Moura, Rafael B., da Rocha Fortes, Rafael, Neves, Raquel A. F., da Rocha, Rosana Moreira, Stampar, Sérgio N., Salani, Sula, Miranda, Thaís Pires, Pinheiro, Ulisses, Venekey, Virág, Oliveira, Ubirajara
Publikováno v:
Diversity and Distributions, 2024 Jun 01. 30(6), 1-10.
Externí odkaz:
https://www.jstor.org/stable/48771599