The Hidden Markov Chain (HMC) model has been extended to take into consideration the multi-component representation of an hyperspectral data cube. Parameters estimation is performed using the general Iterative Conditional Estimation (ICE) method. The vectorial extension of the model is straightforward since the vectorial point of view joints the observation of each pixel as a spectral signature...

Obtaining information about particle dispersion in a room is crucial in reducing the risk of infectious disease transmission among occupants. This study developed a Markov chain model for quickly obtaining the information on the basis of a steady-state flow field calculated by computational fluid dynamics. When solving the particle transport equations, the Markov chain model does not require it...

The inventory control of the products which have intermittent demand is essential for many organizations since these items have a low lead time demand but a high price. Since the intermittent demand pattern is irregular, the estimation of the lead time demand is challenging. A modified Markov chain model (MMCM) has been proposed for modeling and estimating intermittent demand data, motivated by...

this paper aims to predict and determine the net supply of manpower in islamic azad university - firouzkouh branch of for a specific period of time. for this purpose, markov chain model is used to analyze human resources data obtained previously. at last, the number of labors, arrivals, departures, shortages and also surpluses of each unit will be predicted for the next 5 years during 2011-2015...

We propose a way of presenting and computing a counterexample in probabilistic LTL model checking for discrete-time Markov chains. In qualitative probabilistic model checking, we present a counterexample as a pair (α,γ), where α,γ are finite words such that all paths that extend α and have infinitely many occurrences of γ violate the specification. In quantitative probabilistic model checking, ...

Multivariate Markov chain models have previously been proposed in for studying dependent multiple categorical data sequences. For a given multivariate Markov chain model, an important problem is to study its joint stationary distribution. In this paper, we use two techniques to present some perturbation bounds for the joint stationary distribution vector of a multivariate Markov chain with s ca...

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random e...

The estimation of ground subsidence processes is an important subject for the asset management of civil infrastructures on soft ground, such as airport facilities. In the planning and design stage, there exist many uncertainties in geotechnical conditions, and it is impossible to estimate the ground subsidence process by deterministic methods. In this paper, the sets of sample paths designating...

The major goal of this study was to create a continuous time Markov chain (CTMC) models of voltage gating of gap junction (GJ) channels formed of connexin protein. This goal was achieved by using the Piece Linear Aggregate (PLA) formalism to describe the function of GJs and transforming PLA into Markov process. Infinitesimal generator of CTMC was used to automate construction of Markov chain mo...

aspirin is one of the certified medicines commonly used for the secondary prevention of myocardial infarction (mi). aspirin side effects and gastrointestinal bleeding, in particular, have arisen debates on its use for the primary prevention of mi. the present research evaluates the cost-effectiveness of the use of aspirin in the primary prevention of mi among iranian men with average cardiovasc...