Effect of water gas shift reaction (CO+H2O=CO2+H2) on wustite reduction has been investigated by a transient, non-isothermal mathematical model based on grain model. In this model, wustite porous pellet is reduced using Syngas, namely a mixture of hydrogen, carbon monoxide, carbon dioxide and water vapor. For this purpose, governing equations containing continuity equation of species and energy...

You’ve collected the data and performed a preliminary analysis with a linear regression. But the residuals have several modes, and transformations don’t help. You need a different approach, and that calls for the FMM procedure. PROC FMM fits finite mixture models, which enable you to describe your data with mixtures of different distributions so you can account for underlying heterogeneity and ...

Statistical Spatial Color Information Modeling in Images and Applications Walid Elguebaly Image processing, among its vast applications, has proven particular efficiency in quality control systems. Quality control systems such as the ones in the food industry, fruits and meat industries, pharmaceutic, and hardness testing are highly dependent on the accuracy of the algorithms used to extract im...

The present paper reports the results of a numerical analysis of electric fields in random dielectric materials. The effective permittivity of a three-dimensional (3-D) dielectric mixture is calculated by the finite difference method. The results show the distribution of the effective permittivity of a mixture with different random inclusion positionings. New empirical mixing models are created...

We present a strategy for learning Deep-Neural-Network (DNN)-based Acoustic-to-Articulatory Mapping (AAM) functions where the contribution of an articulatory feature (AF) to the global reconstruction error is weighted by its relevance. We first empirically show that when an articulator is more crucial for the production of a given phone it is less variable, confirming previous findings. We then...

Speech recognizers typically use high-dimensional feature vectors to capture the essential cues for speech recognition purposes. The acoustics are then commonly modeled with a Hidden Markov Model with Gaussian Mixture Models as observation probability density functions. Using unrestricted Gaussian parameters might lead to intolerable model costs both evaluationand storagewise, which limits thei...

Articulatory data have gained increasing interest in speech recognition with or without acoustic data. Electromagnetic articulograph (EMA) is one of the affordable, currently used techniques for tracking the movement of flesh points on articulators (e.g., tongue) during speech. Determining an optimal set of sensors is important for optimizing the clinical applications of EMA data, due to the in...