Joint modeling of spatially oriented dependent variables is commonplace in the environmental sciences, where scientists seek to estimate relationships among a set outcomes accounting for dependence these and spatial each outcome. Such now sought massive data sets with measured at very large number locations. Bayesian inference, while attractive accommodating uncertainties through hierarchical s...

We determine the Smith normal forms of the incidence matrices of points and projective (r − 1)-dimensional subspaces of PG(n, q) and of the incidence matrices of points and r-dimensional affine subspaces of AG(n, q) for all n, r, and arbitrary prime power q.

The semi-classical stability of several AdS NUT instantons is studied. Throughout, the notion of stability is that of stability at the one-loop level of Euclidean Quantum Gravity. Instabilities manifest themselves as negative eigenmodes of a modified Lichnerowicz Laplacian acting on the transverse traceless perturbations. An instability is found for one branch of the AdS-Taub-Bolt family of met...

We propose in this paper a new strategy to estimate surface normals from sparse data for reconstruction. Our approach is based on tensorial fields morphologically adapted to infer normals forming smooth surfaces. They act as three-dimensional structuring elements in the reconstruction step. An enhanced accumulation process for finding precise normals is also proposed. We present several results...

This article presents a method to estimate flow variables for an open channel network governed by first-order, linear hyperbolic partial differential equations and subjected to periodic forcing. The selected external boundary conditions of the system are defined as the model input; the flow properties at internal locations, as well as the other external boundary conditions, are defined as the o...