Considering the magneto-hydrodynamic equations in a non-relativistic multi uid framework, we study the behavior of small amplitude perturbations in cold quark matter. Magneto-hydrodynamic equations, along with a suitable equation of state for the cold quark matter, are expanded using the reductive perturbation method. It is shown that in small amplitude approximation, such a medium should be co...

Cloud computing is a technology that uses the internet and central remote servers to keep up data and applications. As becomes more mature, many organizations and individuals are attracted in storing more accessible data e.g. personal data files, company related information in the cloud. This technology allows for much more efficient computing by centralizing storage, memory, processing and ban...

In this paper, we investigate a new discriminative training technique which focuses on optimizing a keyword error rate, rather than the error rate on all words. We hypothesize that improvements in keyword error rate correlate with improvements in understanding error rates. Keyword-based discriminative training is accomplished by modifying a standard minimum classification error (MCE) training a...

This paper proposes a new approach for keyword spotting, which is not based on HMMs. The proposed method employs a new discriminative learning procedure, in which the learning phase aims at maximizing the area under the ROC curve, as this quantity is the most common measure to evaluate keyword spotters. The keyword spotter we devise is based on nonlinearly mapping the input acoustic representat...

Keyword spotting is a detection task consisting in discovering the presence of specific spoken words in unconstrained speech. The majority of keyword spotting systems are based on generative hidden Markov models and lack discriminative capabilities. However, discriminative keyword spotting systems are based on the estimation of a posteriori probabilities at the frame-level, hence they make use ...