background: in the case of sensitive questions such as number of alcoholics known, majority of respondents might give an answer of zero. poisson regression model (p) is the standard tool to analyze count data. however, p provides poor fit in the case of zero inflated counts, when over-dispersion exists. therefore, the questions to be addressed are to compare performance of alternative count reg...

let denote the unit circle in the complex plane. given a function , one uses t usual (harmonic) poisson kernel for the unit disk to define the poisson integral of , namely . here we consider the biharmonic poisson kernel for the unit disk to define the notion of -integral of a given function ; this associated biharmonic function will be denoted by . we then consider the dilations for and . the ...

A hybrid method that combines experimental and numerical approaches for determining the material properties of Nd:YVO4 is reported. In the experimental investigations a laser interferometer is proposed for measuring the physical deformation of lasing materials at the end-pump surface. By matching with the measured end bulging, we have implemented a numerical solution with finite-element analyse...

S1. Geometry dependence of circuit components: a) Geometric Capacitance )) : For a parallel plate system, the geometric (dielectric) capacitance is given by where is the area of the electrodes, permittivity of the medium separating the electrodes and the separation between the electrodes. This results from the solution of Poisson equation and is determined by the ratio of charge on the electrod...

This paper describes a novel model for term frequency distributions that is derived from queuing-theory. It is compared with Poisson distributions, in terms of how well the models describe the observed distributions of terms, and it is demonstrated that a model for term frequency distributions based on queue utilisation generally gives a better fit. It is further demonstrated that the ratio of ...

We present a novel statistical framework for detecting pre-determined shape classes in 2D cluttered point clouds, that are in turn extracted from images. In this model-based approach, we use a 1D Poisson process for sampling points on shapes, a 2D Poisson process for points from background clutter, and an additive Gaussian model for noise. Combining these with a past stochastic models on shapes...