Search results for "Random"
showing 10 items of 3931 documents
Some notes on a second-order random boundary value problem
2017
We consider a two-point boundary value problem of second-order random differential equation. Using a variant of the α-ψ-contractive type mapping theorem in metric spaces, we show the existence of at least one solution.
Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery
2021
Laparoscopy is an operation carried out in the abdomen or pelvis through small incisions with external visual control by a camera. This technique needs the abdomen to be insufflated with carbon dioxide to obtain a working space for surgical instruments' manipulation. Identifying the critical point at which insufflation should be limited is crucial to maximizing surgical working space and minimizing injurious effects. Bayesian nonlinear growth mixed-effects models are applied to data coming from a repeated measures design. This study allows to assess the relationship between the insufflation pressure and the intra--abdominal volume.
CORRELATIONS AMONG FORWARD RETURNS IN THE NORDIC ELECTRICITY MARKET
2009
I analyze empirical correlations of electricity forward returns from the perspective of a random field model that specifies the correlations in terms of the temporal separation between forward maturities. It turns out that temporal separation cannot fully account for the empirical forward return correlations. Specifically, the relation between correlations and temporal separation does not seem to be invariant across segments of the electricity forward market or trading periods.
A Multiresolution Approach Based on MRF and Bak–Sneppen Models for Image Segmentation
2006
The two major Markov Random Fields (MRF) based algorithms for image segmentation are the Simulated Annealing (SA) and Iterated Conditional Modes (ICM). In practice, compared to the SA, the ICM provides reasonable segmentation and shows robust behavior in most of the cases. However, the ICM strongly depends on the initialization phase. In this paper, we combine Bak-Sneppen model and Markov Random Fields to define a new image segmentation approach. We introduce a multiresolution technique in order to speed up the segmentation process and to improve the restoration process. Image pixels are viewed as lattice species of Bak-Sneppen model. The a-posteriori probability corresponds to a local fitn…
Thickness Dependence of Random Field Distribution in Thin Films Made of Disordered Ferroelectrics
2005
Abstract We present the calculation of first moment E 0 and variance ΔE of distribution function of random fields in a ferroelectric of finite size. Specific calculations have been performed for the case of slab-shaped ferroelectric thin film. We have shown that E 0 and ΔE can be expressed through the integrals from first and second degree of Green's function of ferroelectric in k-space. To obtain the Green's function, we solve the differential equation minimizing Landau free energy of a ferroelectric with respect to the boundary conditions on its surfaces. We show that both E 0 and ΔE depend on film thickness L.
Evolutionary Spectrum for Random Field and Missing Observations
2012
There are innumerable situations where the data observed from a non-stationary random field are collected with missing values. In this work a consistent estimate of the evolutionary spectral density is given where some observations are randomly missing.
Finite-size scaling in Ising-like systems with quenched random fields: Evidence of hyperscaling violation
2010
In systems belonging to the universality class of the random field Ising model, the standard hyperscaling relation between critical exponents does not hold, but is replaced by a modified hyperscaling relation. As a result, standard formulations of finite size scaling near critical points break down. In this work, the consequences of modified hyperscaling are analyzed in detail. The most striking outcome is that the free energy cost \Delta F of interface formation at the critical point is no longer a universal constant, but instead increases as a power law with system size, \Delta F proportional to $L^\theta$, with $\theta$ the violation of hyperscaling critical exponent, and L the linear ex…
Random forest analysis: a new approach for classication of Beta Thalassemia
2020
In recent years, Thalassemia care providers started classifying patients as transfusion- dependent-Thalassemia (TDT) or non-transfusion-dependent-Thalassemia (NTDT) owing to the established role of transfusion therapy in dening the clinical complication prole, although this classication was also based on expert opinion and is limited by reliance on patients'current transfusion status. Starting from a vast set of variables indicating severity phenotype, through the use of both classication and clustering techniques we want to explore the presence of two (TDT vs NTDT) or more clusters, in order to approaching to a new denition for the classication of Beta-Thalassemia in Thalassemia Syndromes …
Inferring networks from high-dimensional data with mixed variables
2014
We present two methodologies to deal with high-dimensional data with mixed variables, the strongly decomposable graphical model and the regression-type graphical model. The first model is used to infer conditional independence graphs. The latter model is applied to compute the relative importance or contribution of each predictor to the response variables. Recently, penalized likelihood approaches have also been proposed to estimate graph structures. In a simulation study, we compare the performance of the strongly decomposable graphical model and the graphical lasso in terms of graph recovering. Five different graph structures are used to simulate the data: the banded graph, the cluster gr…
Structure of eigenvectors of random regular digraphs
2018
Let $d$ and $n$ be integers satisfying $C\leq d\leq \exp(c\sqrt{\ln n})$ for some universal constants $c, C>0$, and let $z\in \mathbb{C}$. Denote by $M$ the adjacency matrix of a random $d$-regular directed graph on $n$ vertices. In this paper, we study the structure of the kernel of submatrices of $M-z\,{\rm Id}$, formed by removing a subset of rows. We show that with large probability the kernel consists of two non-intersecting types of vectors, which we call very steep and gradual with many levels. As a corollary, we show, in particular, that every eigenvector of $M$, except for constant multiples of $(1,1,\dots,1)$, possesses a weak delocalization property: its level sets have cardin…