Diffused expectation maximisation is a novel algorithm for image segmentation. The method models an image as a finite mixture, where each mixture component corresponds to a region class and uses a maximum likelihood approach to estimate the parameters of each class, via the expectation maximisation algorithm, coupled with anisotropic diffusion on classes, in order to account for the spatial dep...

This study adopts Neo-Institutional Theory (NIT) to address the underlying differences in information security policy compliance between the banking industry and the higher education. Drawing on NIT, this study examines how regulative, normative, and cognitive expectations influence the internal organizational efforts of staying compliant across both industries. Using the Partial Least Square (...

the notion of a $d$-poset was introduced in a connection withquantum mechanical models. in this paper, we introduce theconditional expectation of  random variables on thek^{o}pka's $d$-poset and prove the basic properties ofconditional expectation on this  structure.

We consider the variance of the reward until absorption in a Markov chain. This variance is usually calculated from the second moment (expectation of the square). We present a direct system of equations for the variance, involving the first moment (expectation) but not the second moment. This method is numerically superior to the calculation from the second moment.

From the perspective of selecting service by QoS attributes, a computation method of QoS expectation value, which is based on Algorithm Prim, was presented to provide support for selection of service. On the basis of the ability of service providers, by Algorithm Prim, this method succeeded in calculating a set of balanced expectation values of QoS. Selection of service based on these QoS value...

A Monte Carlo algorithm for computing quantum mechanical expectation values of coordinate operators in many body problems is presented. The algorithm , that relies on the forward walking method, fits naturally in a Green's Function Monte Carlo calculation, i.e., it does not require side walks or a bilin-ear sampling method. Our method evidences stability regions large enough to accurately sampl...

This article examines a new approach which solves Linear Programming (LP) problems with stochastic parameters as a generalized model of the fuzzy mathematical model analyzed by Verdegay. An expectation model is provided for solving the problem. A multi-parametric programming is applied to access to a solution with different desired degrees as well as problem constraints. Additionally, we presen...

Psychological factors, market sentiments, and shifts in beliefs are believed by many to play a nontrivial role in inducing and amplifying economic fluctuations. Yet, these forces are rarely considered in macroeconomic models. This paper provides an attempt to evaluate the empirical role of expectational shocks on business cycle fluctuations. The paper relaxes the conventional assumption of rati...