An acidic environment causes surface changes of resin composites. Filler particlesize and filler distribution also have a direct effect on these surface changes. This invitro study evaluated the influence of Pepsi Cola drink on the surface roughness ofComposan LCM and Composan Ceram over time. Sixteen disc shaped specimens(10mm diameter, 2mm thickness) of each resin composite were fabricated, therebyforming two groups (n= 8). Surface roughness (Ra) was analyzed after 24 hrs beforeexposure to beverage. The specimens were submitted to a five minutes immersion inPepsi Cola three times daily interrupted by immersion in deionized distilled water (37C˚). Surface roughness measurements were done at 10, 30, and 60 days intervals. Datawere

Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021

In the present work, the effect of size of zinc dust particles on
AC argon discharge characteristics are investigated
experimentally. The plasma characteristics are determined by
using optical emission spectroscopy (OES) techniques. The
results illustrated that the electron temperature (Te) in the present
and absent of Zinc dust particle is reduced with increasing of
pressure. The electron temperature decreases with increasing of
Zinc dust size. Excitation temperature Tex is reduces with
increasing of Ar pressure in present and absent of zinc dust
particles. The present of Zinc dust reduce the Tex of Ar in both
Zinc dust size. The electron density increasing in the present and
absent of both zinc dust siz

This paper is concerned with introducing and studying the new approximation operators based on a finite family of d. g. 'swhich are the core concept in this paper. In addition, we study generalization of some Pawlak's concepts and we offer generalize the definition of accuracy measure of approximations by using a finite family of d. g. 's.

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.