Zobrazeno 1 - 10
of 10 023
pro vyhledávání: '"Santos,João"'
Publikováno v:
2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON), Porto, Portugal, 2024, pp. 1321-1326
In the ever-evolving landscape of computing, the advent of edge and fog computing has revolutionized data processing by bringing it closer to end-users. While cloud computing offers numerous advantages, including mobility, flexibility and scalability
Externí odkaz:
http://arxiv.org/abs/2412.01412
In this work, we developed a cosmological model in $ f(Q, C) $ gravity within the framework of symmetric teleparallel geometry. In addition to the non-metricity scalar $Q $, our formulation includes the boundary term $ C $, which accounts for its dev
Externí odkaz:
http://arxiv.org/abs/2411.00032
Autor:
Manfio, Fernando, Santos, João Batista Marques dos, Santos, João Paulo dos, Van der Veken, Joeri
We classify the hypersurfaces of $\mathbb{Q}^3\times\mathbb{R}$ with three distinct constant principal curvatures, where $\varepsilon \in \{1,-1\}$ and $\mathbb{Q}^3$ denotes the unit sphere $\mathbb{S}^3$ if $\varepsilon = 1$, whereas it denotes the
Externí odkaz:
http://arxiv.org/abs/2409.07978
We study electromagnetic radiation reaction on a charged particle around a weakly magnetized Kerr black hole. We solve numerically the Teukolsky equation to find energy fluxes in electromagnetic radiation at the horizon and at spatial infinity. We al
Externí odkaz:
http://arxiv.org/abs/2409.17225
In this investigation, we perform an observational statistical analysis in the theory of $ f(R, L_m) $ gravity. The proposed theoretical model is based on the Ricci scalar's non-linear contribution. We use a distinct parameterization for the decelera
Externí odkaz:
http://arxiv.org/abs/2408.16038
Autor:
Fathalla, Efat Samir, Zargarzadeh, Sahar, Xin, Chunsheng, Wu, Hongyi, Jiang, Peng, Santos, Joao F., Kibilda, Jacek, da, Aloizio Pereira
This paper presents an experimental study on mmWave beam profiling on a mmWave testbed, and develops a machine learning model for beamforming based on the experiment data. The datasets we have obtained from the beam profiling and the machine learning
Externí odkaz:
http://arxiv.org/abs/2408.13403
Autor:
Santos, João Victor V., Schreck, Marco
The focus of this article is on a modification of General Relativity (GR) governed by a dynamical scalar field. The latter is able to acquire a nonzero spacetime-dependent vacuum expectation value, which gives rise to a spontaneous violation of space
Externí odkaz:
http://arxiv.org/abs/2407.20688
Autor:
Santos, Joao F., Huff, Alexandre, Campos, Daniel, Cardoso, Kleber V., Both, Cristiano B., DaSilva, Luiz A.
The Open Radio Access Network (O-RAN) Alliance proposes an open architecture that disaggregates the RAN and supports executing custom control logic in near-real time from third-party applications, the xApps. Despite O-RAN's efforts, the creation of x
Externí odkaz:
http://arxiv.org/abs/2407.09619
Autor:
Lavado, Diogo, Soares, Cláudia, Micheletti, Alessandra, Santos, Ricardo, Coelho, André, Santos, João
Research on supervised learning algorithms in 3D scene understanding has risen in prominence and witness great increases in performance across several datasets. The leading force of this research is the problem of autonomous driving followed by indoo
Externí odkaz:
http://arxiv.org/abs/2405.13989
Autor:
Dzaferagic, Merim, Ruffini, Marco, Slamnik-Krijestorac, Nina, Santos, Joao F., Marquez-Barja, Johann, Tranoris, Christos, Denazis, Spyros, Kyriakakis, Thomas, Karafotis, Panagiotis, DaSilva, Luiz, Pandey, Shashi Raj, Shiraishi, Junya, Popovski, Petar, Jensen, Soren Kejser, Thomsen, Christian, Pedersen, Torben Bach, Claussen, Holger, Du, Jinfeng, Zussman, Gil, Chen, Tingjun, Chen, Yiran, Tirupathi, Seshu, Seskar, Ivan, Kilper, Daniel
Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical dom
Externí odkaz:
http://arxiv.org/abs/2407.01544