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| We consider the problem of segmenting a digitized image consisting of two univariate populations. Assume a-priori knowledge allows incomplete assignment of voxels in the image, in the sense that a fraction of the vox-els can be identiied as belonging to population 0 , a second fraction to 1 , and the remaining fraction have no a-priori identiication.(More)
We have developed a numerical algorithm to generate realizations of a stochastic, isotropic, scalar eld covering a rectangular domain in two and three spatial dimensions. The eld is characterized by heterogeneity variation over all numerical length scales contained within the domain. The variation is described by a two point covariance function of the form(More)
Numerical methods for free surface MHD flows have been developed and numerical simulations of the Richtmyer Meshkov type instability in liquid jets in strong magnetic fields caused by an external energy deposition have been performed. Numerical results shed light on the evolution of the proposed Muon Collider target which will be designed as a pulsed jet of(More)
| We consider the problem of segmenting a digitized 2D or 3D image consisting of two univariate populations. Assume a-priori knowledge allows incomplete assignment of voxels in the image, in the sense that a fraction of the voxels can be identiied as belonging to population 0 , a second fraction to 1 , and the remaining fraction have no a-priori(More)
PEST is a numerical algorithm developed for the simulation in a rectangular R 2 or R 3 domain of a stochastic, isotropic, scalar eld which is conditioned pointwise to a set of measurements. The eld is characterized by heterogeneity variation described either by a two point covariance function C(r) or semivariogram (r) for pairs of points separated by(More)
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