The porosity of materials is important in many applications, products and processes, such as electrochemical devices (electrodes, separator, active components in batteries), porous thin film, ceramics, soils, construction materials, ..etc. This can be characterized in many different methods, and the most important methods for industrial purposes are the N2 gas adsorption and mercury porosimetry. In the present paper, both of these techniques have been used to characterize some of Iraqi natural raw materials deposits. These are Glass Sand, Standard Sand, Flint Clay and Bentonite. Data from both analyses on the different types of natural raw materials deposits are critically examined and discussed. The results of specific surface are

Aim: To evaluate the effect of two bonding systems and two curing systems on sealing ability of class V composite restorative materials. Materials and methods: This study was performed in vitro on 40 caries free upper first premolar teeth. The Standardized class V cavity preparation on buccal and lin- gual surfaces of each tooth was done. Then the teeth were randomly divided into two major groups each of twenty. 40 cavities were performed on these teeth and the first group7th generation bonding agent (i Bond) were applied according to the manufacturer instructions and single increment of univer- sal composite (XRV Herculite) from kerr were applied and twenty of the cavities were cured with con- ventional light cure device (astralis-5) and t

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

In this paper, a theoretical study to the effect of journal misalignment on the static characteristics of oil filled porous journal bearing when lubricated with couple stress fluid has been carried out.

The analytical model used through this work is for a bearing with isotropic permeability. Considering isotropic permeability the Reynolds' equation for the oil film is modified to include a so – called filter term and the effect of fluid coupled stress. The pressure equation for the porous medium is obtained from Darcy's law and continuity equation. The equation which was used to evaluate the oil film thickness was modified to include the effect of possible misalignment in longitudinal and transverse directions. The governing eq