liquid-liquid equilibria for the (water + lactic acid + benzyl alcohol or p-xylene) ternary systems were investigated at atmospheric pressure and in the temperature range from 298.15-318.15 k. the studied systems exhibit two types of liquid-liquid equilibrium (lle) behavior. the system consisting of benzyl alcohol displays type-1 lle behavior, while a type-2 behavior is exhibited by the other s...

Little is known about the factors affecting pastoralists' livestock vaccination decisions. In this thesis, we use a novel survey-based dataset on pastoralists living in the Ruaha landscape in Tanzania, and employ several econometric approaches to identify the factors affecting pastoralists' decision-making process about livestock vaccination when disease occurrence and severity, vaccination and...

* Corresponding author. Abstract –Adaptive subspace detectors are widely used for low probability and anomaly detection. The complex remote sensing conditions in which hyperspectral imagery is obtained make the detector performance evaluation a non-trivial task. Many of the detector design parameters can only be studied empirically for their effects on detection performance. In this paper, hype...

Consider the task of summarizing the data in Figure 1. A common technique for performing this task is to use a statistical model known as a mixture model. Relative to many other models for estimating densities, mixture models have a number of advantages. First, mixture models can summarize data that contain multiple modes. In this sense, they are more powerful than distributions from the expone...

Flexible and reliable probability density estimation is fundamental in unsupervised learning and classification. Finite Gaussian mixture models are commonly used to serve this purpose. However, they fail to estimate unknown probability density functions when used for nonparametric probability density estimation, as severe numerical difficulties may occur when the number of components increases....

A finite probability mixture model is combined with a contingent valuation model to analyze the existence of differential market segments in a hypothetical market. The approach has at least two principle benefits. First, the model is capable of identifying market segments within the hypothetical market. Second, the model can be used to estimate WTP/WTA within each segment. The model is illustra...

We apply machine learning techniques in the form of Gaussian mixture models to functional brain activation data. The dataset was extracted through the WWW interface to the BrainMap (Research Imaging Center, University of Texas Health Science Center at San Antonio) neuroimaging database. Modeling of the joint probability structure of activation foci and other database entries (e.g. behavioral do...

The Gaussian mixture probability density (GM-PHD) filter has become a popular approach to solve the multiple-target tracking (MTT) problem because it can effectively and efficiently estimate number of targets target states that change over time from noisy measurements. In GM-PHD filter, detection survival probabilities, birth rate are assumed be constant, irrespective state. However, in some ap...

The best-performing method in the data compression literature for computing probability estimates of sequences on-line using a su x-tree model is the blending technique used by PPM. Blending can be viewed as a bottomup recursive procedure for computing a mixture, barring one missing term for each level of the recursion, where a mixture is basically a weighted average of several probability esti...