Owing to constant changes in user needs, new technologies have been introduced keep pace by building sustainable applications. Researchers and practitioners are keen understand the factors that create an attractive interface. Although use of cross-platform applications services is increasing, limited research has examined evaluated cross-platforms for developing mobile different operating syste...

This paper aims to optimize the machining parameters of drilling process woven-glass-fiber reinforced epoxy (WGFRE) composites. It will focus on modeling and optimizing drill spindle speed feed with different laminate thicknesses, respect torque delamination factor. The response surface analysis artificial neural networks are utilized model evaluate effect control their interaction outcomes. pa...

This paper presents the results of a large number of experiments performed on the Hiwire cockpit database with a hybrid HMM-ANN speech recognition model. The Hiwire database is a noisy and non-native English speech corpus for cockpit communication. The noisy component of the database has been used to test two noise reduction methods recently introduced, while the adaptation component is exploit...

We review some of the Artificial Neural Network (ANN) approaches used in speech recognition. Some basic principles of neural networks are briefly described as well as their current applications and performances in speech recognition. Strenghtnesses and weaknesses of pure connectionnist networks in the particular context of the speech signal are then evoqued. The emphasis is put on the capabilit...

The authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the re...

The subject of this paper is the integration of multi-layered Artificial Neural Networks (ANN) with probability density functions such as Gaussian mixtures found in continuous density Hidden Markov Models (HMM). In the first part of this paper we present an ANN/HMM hybrid in which all the parameters of the the system are simultaneously optimized with respect to a single criterion. In the second...

Abstract Analyses based on precipitation data may be limited by the quality of data, size available historical series and efficiency adopted methodologies; these factors are especially limiting when conducting analyses at daily scale. Thus, methodologies sought to overcome barriers. The objective this work is develop a hybrid model through maximum overlap discrete wavelet transform (MODWT) esti...