Zobrazeno 1 - 10
of 16 547
pro vyhledávání: '"Formica"'
Autor:
Mashinistov Ruslan, Gerlach Lino, Laycock Paul, Formica Andrea, Govi Giacomo, Pinkenburg Chris
Publikováno v:
EPJ Web of Conferences, Vol 295, p 01051 (2024)
Conditions data is the subset of non-event data that is necessary to process event data. It poses a unique set of challenges, namely a heterogeneous structure and high access rates by distributed computing. The HSF Conditions Databases activity is a
Externí odkaz:
https://doaj.org/article/397f7797890342bea8c48bd1bfbe52c1
Autor:
Alexandrov Evgeny, Canali Luca, Costanzo Davide, Formica Andrea, Gallas Elizabeth J., Mineev Mikhail, Ozturk Nurcan, Roe Shaun, Tsulaia Vakho, Vogel Marcelo
Publikováno v:
EPJ Web of Conferences, Vol 295, p 01013 (2024)
The ATLAS experiment is preparing a major change in the conditions data infrastructure in view of LHC Run 4. In this paper we describe the ongoing changes in the database architecture which have been implemented for Run 3, and describe the motivation
Externí odkaz:
https://doaj.org/article/2227bd0e309d40d297bd6e5fec21972a
Autor:
Ahmed, Irshaad, Fiorenza, Alberto, Formica, Maria Rosaria, Gogatishvili, Amiran, Hamidi, Abdallah El
We present some regularity results on the gradient of the weak or entropic-renormalized solution $u$ to the homogeneous Dirichlet problem for the quasilinear equations of the form \begin{equation*}\label{p-laplacian_eq} -{\rm div~}(|\nabla u|^{p-2}\n
Externí odkaz:
http://arxiv.org/abs/2411.00367
We establish an ordinary as well as a logarithmical convexity of the Moment Generating Function (MGF) for the centered random variable and vector (r.v.) satisfying the Kramer's condition. Our considerations are based on the theory of the so-called Gr
Externí odkaz:
http://arxiv.org/abs/2409.05085
We derive in this short report the exact exponential decreasing tail of distribution for naturel normed sums of independent centered random variables (r.v.), applying the theory of Grand Lebesgue Spaces (GLS). We consider also some applications into
Externí odkaz:
http://arxiv.org/abs/2409.05083
We construct an optimal exponential tail decreasing confidence region for an unknown density of distribution in the Lebesgue-Riesz as well as in the uniform} norm, built on the sample of the random vectors based of the famous recursive Wolverton-Wagn
Externí odkaz:
http://arxiv.org/abs/2409.01451
We offer in this short report the so-called adaptive functional smoothness estimation in the Hilbert space norm sense in the three classical problems of non-parametrical statistic: regression, density and spectral (density) function measurement (esti
Externí odkaz:
http://arxiv.org/abs/2409.00491
Autor:
Araujo, Gabriel, Caldas, Ricardo, Formica, Federico, Rodrigues, Genaína, Pelliccione, Patrizio, Menghi, Claudio
Cyber-physical systems (CPS) development requires verifying whether system behaviors violate their requirements. This analysis often considers system behaviors expressed by execution traces and requirements expressed by signal-based temporal properti
Externí odkaz:
http://arxiv.org/abs/2406.17268
Autor:
Mashinistov, Ruslan, Gerlach, Lino, Laycock, Paul, Formica, Andrea, Govi, Giacomo, Pinkenburg, Chris
Conditions data is the subset of non-event data that is necessary to process event data. It poses a unique set of challenges, namely a heterogeneous structure and high access rates by distributed computing. The HSF Conditions Databases activity is a
Externí odkaz:
http://arxiv.org/abs/2401.16274
We derive sharp non - asymptotical Lebesgue - Riesz as well as Grand Lebesgue Space norm estimations for different norms of matrix martingales through these norms for the correspondent martingale differences and through the entropic dimension of the
Externí odkaz:
http://arxiv.org/abs/2401.13326