A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Silver Indium Aluminum Selenium AgIn1xAlxSe2 AIAS for x=01 thin films was deposited by thermal evaporation at RT and different︣︢︡ ︠︣1thickness 100 150 and 200 nm on the glass Substrate and p2Si wafer to produce AIAS/p3Si heterojunctionsolarcell4 Structural optical electrical and photovoltaicproperties6 are investigated for the samples XRD analysis reveals that all the deposited AIAS films show polycrystalline structure without any change due to increase of thickness Average diameter and roughness calculated from AFM images shows an increase in its value with increasing thickness The optical absorbance and transmittance for samples are measured using a spectrometer type UV Visible 1800 spectra1photometer to study the energy6gap The

This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p

This work was conducted to study the coefficient of performance for solar absorption refrigeration by using direct solar energy using aqueous ammonia 0.45 mass fraction (ammonia – water).The experiments were carried out in solar absorption system .The system consisted of solar collector generator (0.25 m × 0.25 m × 0.04m) and condenser cooled by a water bath followed by liquid receiver and evaporator. The results showed that the maximum generator temperature was (92° - 97°) during June 2009, and the minimum evaporator temperature was (5°C - 10°C) for aqua ammonia system.. It was, also, found that the coefficient of performance, cooling ratio and amount of cooling obtainable increased with increasing maximum generator temperature

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

This paper reports a.c., d.c. conductivity and dielectric behavior of Ep-hybrid composite with12 Vol.% Kevlar-Carbon hybrid . D.C. conductivity measurements are conducted on the graded composites by using an electrometer over the temperature range from (293-413) K. It was shown then that conductivity increases by increasing number of Kevlar –Carbon fiber layers (Ep1, Ep2, Ep3), due to the high electrical conductivity of Carbon fiber. To identify the mechanism governing the conduction, the activation energies at low temperature region (LTR) and at high temperature region (HTR) have been calculated. The activation energy values for hybrid composite decrease with increasing number of fiber layers. The a.c. conductivity was measured over fr