Chemical Vapor Deposition (CVD) is one of the most popular methods for producing Carbon Nanotubes (CNTs). The growth rate of CNTs based on CVD technique is investigated by using a numerical model based on finite volume method. Inlet gas mixture, including xylene as carbon source and mixture of argon and hydrogen as carrier gas enters into a horizontal CVD reactor at atmospheric pressure. In thi...

We address the issue of 'topic analysis,' by which is determined a text's topic structure, which indicates what topics are included in a text, and how topics change within the text. We propose a novel approach to this issue, one based on statistical modeling and learning. We represent topics by means of word clusters, and employ a finite mixture model to represent a word distribution within a t...

We propose a new method of classifying documents into categories. We define for each category a finite mixture model based on soft clustering of words. We treat the problem of classifying documents as that of conducting statistical hypothesis testing over finite mixture models, and employ the EM algorithm to efficiently estimate parameters in a finite mixture model. Experimental results indicat...

This paper illustrates the implementation of resampling methods in flexmix as well as the application of resampling methods for model diagnostics of fitted finite mixture models. Convenience functions to perform these methods are available in package flexmix. The use of the methods is illustrated with an artificial example and the seizure data set.

Finite mixture models have a long history in statistics, having been used to model pupulation heterogeneity, generalize distributional assumptions, and lately, for providing a convenient yet formal framework for clustering and classification. This paper provides a detailed review into mixture models and model-based clustering. Recent trends in the area, as well as open problems are also discussed.

Recent studies have shown that speech recognizers may benefit from data in languages other than the target language through efficient acoustic modelor feature-level adaptation. Crosslingual Tandem-Subspace Gaussian Mixture Models (SGMM) are successfully able to combine acoustic modeland featurelevel adaptation techniques. More specifically, we focus on under-resourced languages (Afrikaans in ou...

‎This paper presents a new mixture model via considering the univariate skew Laplace distribution‎. ‎The new model can handle both heavy tails and skewness and is multimodal‎. ‎Describing some properties of the proposed model‎, ‎we present a feasible EM algorithm for iteratively‎ ‎computing maximum likelihood estimates‎. ‎We also derive the observ...