Zobrazeno 1 - 10
of 833
pro vyhledávání: '"PAOLETTI, M."'
Convolutional neural networks (CNNs) are trained using stochastic gradient descent (SGD)-based optimizers. Recently, the adaptive moment estimation (Adam) optimizer has become very popular due to its adaptive momentum, which tackles the dying gradien
Externí odkaz:
http://arxiv.org/abs/2105.10190
We present a method to determine, using only velocity field data, the time-averaged energy flux $\left<\boldsymbol{J}\right>$ and total radiated power $P$ for two-dimensional internal gravity waves. Both $\left<\boldsymbol{J}\right>$ and $P$ are dete
Externí odkaz:
http://arxiv.org/abs/1401.2484
Autor:
Paoletti, M. S., Swinney, Harry L.
Publikováno v:
Journal of Fluid Mechanics 706, 571-583 (2012)
We present experimental and computational studies of the propagation of internal waves in a stratified fluid with an exponential density profile that models the deep ocean. The buoyancy frequency profile $N(z)$ (proportional to the square root of the
Externí odkaz:
http://arxiv.org/abs/1202.5290
Autor:
Paoletti, M. S., van Gils, Dennis P. M., Dubrulle, B., Sun, Chao, Lohse, Detlef, Lathrop, D. P.
Publikováno v:
A&A 547, A64 (2012)
We present angular momentum transport (torque) measurements in two recent experimental studies of the turbulent flow between independently rotating cylinders. In addition to these studies, we reanalyze prior torque measurements to expand the range of
Externí odkaz:
http://arxiv.org/abs/1111.6915
By analyzing trajectories of solid hydrogen tracers in superfluid $^4$He, we identify tens of thousands of individual reconnection events between quantized vortices. We characterize the dynamics by the minimum separation distance $\delta(t)$ between
Externí odkaz:
http://arxiv.org/abs/0810.5521
Publikováno v:
Physical Review Letters 101, 154501 (2008)
By analyzing trajectories of solid hydrogen tracers, we find that the distributions of velocity in decaying quantum turbulence in superfluid $^4$He are strongly non-Gaussian with $1/v^3$ power-law tails. These features differ from the near-Gaussian s
Externí odkaz:
http://arxiv.org/abs/0808.1103
Akademický článek
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Publikováno v:
Economic Botany, 2002 Dec 01. 56(4), 306-314.
Externí odkaz:
https://www.jstor.org/stable/4256603
Autor:
Paoletti, M. E.1 (AUTHOR), Tao, X.2 (AUTHOR), Haut, J. M.3 (AUTHOR) juanmariohaut@unex.es, Moreno-Álvarez, S.2 (AUTHOR), Plaza, A.2 (AUTHOR)
Publikováno v:
Journal of Supercomputing. Aug2021, Vol. 77 Issue 8, p9190-9201. 12p.
Publikováno v:
Epidemiology and Infection, 2016 Feb 01. 144(3), 635-646.
Externí odkaz:
https://www.jstor.org/stable/26515545