This paper proposes the use of latent topic modeling for spoken language recognition, where a topic is defined as a discrete distribution over phone n-grams. The latent topics are trained in an unsupervised manner using the latent Dirichlet allocation (LDA) technique. Language recognition is then performed in a low dimensional simplex defined by the latent topics. We apply the Bhattacharyya mea...

This paper discussed Bayesian variable selection methods for models from split-plot mixture designs using samples Metropolis-Hastings within the Gibbs sampling algorithm. is easy to implement due improvement in computing via MCMC sampling. We described methodology by introducing framework, and explaining Markov Chain Monte Carlo (MCMC) The was used draw dependent full conditional distributions ...

We consider the problem of cardinality penalized optimization of a convex function over the probability simplex with additional convex constraints. The classical `1 regularizer fails to promote sparsity on the probability simplex since `1 norm on the probability simplex is trivially constant. We propose a direct relaxation of the minimum cardinality problem and show that it can be efficiently s...

Composting is a good recycling method to fully utilise all the organic wastes present in kitchen waste due to its high nutritious matter within the waste. In this present study, the optimised mixture proportions of kitchen waste containing vegetable scraps (V), fish processing waste (F) and newspaper (N) or onion peels (O) were determined by applying the simplex-centroid mixture design method t...

The aim of this work is to ascertain the potentials of different agroforestry wastes to be used as biosorbents in the removal of a mixture of heavy metals. Fern (FE), rice husk (RI) and oak leaves (OA) presented the best removal percentages for Cu(II) and Ni(II), Mn(II) and Zn(II) and Cr(VI), respectively. The performance of a mixture of these three biosorbents was evaluated, and an improvement...

A hyperspectral image can be represented as a set of materials called endmembers, where each pixel corresponds to a mixture of several of these materials. More precisely pixels are described by the quantity of each material, this quantity is often called abundance and is positive and of sum equal to one. This leads to the characterization of a hyperspectral image as a set of points in a probabi...

We tested laboratory rabbits from 2 US vendors for antibodies against hepatitis E virus (HEV); Seroprevalences were 40% and 50%. Retrospective analysis of an ocular herpes simplex 1 experiment demonstrated that HEV seropositivity had no effect on experiment outcome. HEV probably is widespread in research rabbits, but effects on research remain unknown.

The production of concretes with a hard hardening rate is not feasible without the use modifying additives. development chemical industry has led to emergence large number additives different properties. Some increase frost and corrosion resistance, strength building materials, while others affect setting concrete water-cement ratio. Of greatest interest joint work in composition cement stone. ...

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the mult...

This paper addresses the problem of the adaptation of a Gaussian Mixture Regression (GMR) to a new input distribution, using a limited amount of input-only examples. We propose a new model for GMR adaptation, called Joint GMR (J-GMR), that extends the previously published framework of Cascaded GMR (C-GMR). We provide an exact EM training algorithm for the J-GMR. We discuss the merits of the J-G...