91 research outputs found
Topological Homogeneity for Electron Microscopy Images
In this paper, the concept of homogeneity is defined, from a
topological perspective, in order to analyze how uniform is the material
composition in 2D electron microscopy images. Topological multiresolution
parameters are taken into account to obtain better results than
classical techniques.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0
Fluid Particle Accelerations in Fully Developed Turbulence
The motion of fluid particles as they are pushed along erratic trajectories
by fluctuating pressure gradients is fundamental to transport and mixing in
turbulence. It is essential in cloud formation and atmospheric transport,
processes in stirred chemical reactors and combustion systems, and in the
industrial production of nanoparticles. The perspective of particle
trajectories has been used successfully to describe mixing and transport in
turbulence, but issues of fundamental importance remain unresolved. One such
issue is the Heisenberg-Yaglom prediction of fluid particle accelerations,
based on the 1941 scaling theory of Kolmogorov (K41). Here we report
acceleration measurements using a detector adapted from high-energy physics to
track particles in a laboratory water flow at Reynolds numbers up to 63,000. We
find that universal K41 scaling of the acceleration variance is attained at
high Reynolds numbers. Our data show strong intermittency---particles are
observed with accelerations of up to 1,500 times the acceleration of gravity
(40 times the root mean square value). Finally, we find that accelerations
manifest the anisotropy of the large scale flow at all Reynolds numbers
studied.Comment: 7 pages, 4 figure
Non-Parametric Approximations for Anisotropy Estimation in Two-dimensional Differentiable Gaussian Random Fields
Spatially referenced data often have autocovariance functions with elliptical
isolevel contours, a property known as geometric anisotropy. The anisotropy
parameters include the tilt of the ellipse (orientation angle) with respect to
a reference axis and the aspect ratio of the principal correlation lengths.
Since these parameters are unknown a priori, sample estimates are needed to
define suitable spatial models for the interpolation of incomplete data. The
distribution of the anisotropy statistics is determined by a non-Gaussian
sampling joint probability density. By means of analytical calculations, we
derive an explicit expression for the joint probability density function of the
anisotropy statistics for Gaussian, stationary and differentiable random
fields. Based on this expression, we obtain an approximate joint density which
we use to formulate a statistical test for isotropy. The approximate joint
density is independent of the autocovariance function and provides conservative
probability and confidence regions for the anisotropy parameters. We validate
the theoretical analysis by means of simulations using synthetic data, and we
illustrate the detection of anisotropy changes with a case study involving
background radiation exposure data. The approximate joint density provides (i)
a stand-alone approximate estimate of the anisotropy statistics distribution
(ii) informed initial values for maximum likelihood estimation, and (iii) a
useful prior for Bayesian anisotropy inference.Comment: 39 pages; 8 figure
Penalized KS method to fit data sets with power law distribution over a bounded subinterval
Spectra and correlation functions of surface layer atmospheric turbulence in unstable thermal stratification
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