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

Enhancing quality image fusion was proposed using new algorithms in auto-focus image fusion. The first algorithm is based on determining the standard deviation to combine two images. The second algorithm concentrates on the contrast at edge points and correlation method as the criteria parameter for the resulted image quality. This algorithm considers three blocks with different sizes at the homogenous region and moves it 10 pixels within the same homogenous region. These blocks examine the statistical properties of the block and decide automatically the next step. The resulted combined image is better in the contras

The feature extraction step plays major role for proper object classification and recognition, this step depends mainly on correct object detection in the given scene, the object detection algorithms may result with some noises that affect the final object shape, a novel approach is introduced in this paper for filling the holes in that object for better object detection and for correct feature extraction, this method is based on the hole definition which is the black pixel surrounded by a connected boundary region, and hence trying to find a connected contour region that surrounds the background pixel using roadmap racing algorithm, the method shows a good results in 2D space objects.
Keywords: object filling, object detection, objec

    Kinetic experiments were performed to induce of the green methyl dye adsorption from aqueous solution on the bauxite clay. This study includes  determination of  the adsorption capacity of  bauxite clay to methyl green dye adsorption and study the effect of some parameters  ( temperature , time ) on the kinetic of the adsorption process of the dye were studied. Quantity of dye adsorbed was increased when the temperature increases from 298 to 318K which indicates that methyl green adsorption processes are endothermic nature . In order to describe the kinetic data and the rate adsorption constants of the pseudo-first-order and  second-order kinetics were used . The kinetics data were applied well

The evaluation process of transportation problem required finding basic feasible solution (bfs). Represent the base of decision making process. To purpose start anther batter solution to able from decisions taking process, consider the decision making process, find (bfs) represent the standard form in linear programming (LP). Most important stage of update (bsf) stages that achieved minimum cost (the optimal solution). the goal of paper to improving & evaluation (bfs) by new procedure (proposed method) comparison with Vogel method.

Over the last few decades the mean field approach using selfconsistent
Haretree-Fock (HF) calculations with Skyrme effective
interactions have been found very satisfactory in reproducing
nuclear properties for both stable and unstable nuclei. They are
based on effective energy-density functional, often formulated in
terms of effective density-dependent nucleon–nucleon interactions.
In the present research, the SkM, SkM*, SI, SIII, SIV, T3, SLy4,
Skxs15, Skxs20 and Skxs25 Skyrme parameterizations have been
used within HF method to investigate some static and dynamic
nuclear ground state proprieties of ^84-108Mo isotopes. In particular,
the binding energy, proton, neutron, mass and charge densities

The effective Skyrme type interactions have been used in the Haretree-Fock
mean-field model for several decades, and many different parameterizations of the
interaction have been realized to better reproduce nuclear masses, radii, and various
other data. In the present research, the SkM, SkM*, SI, SIII, SIV, T3, Sly4, Skxs15,
Skxs20 and Skxs25 Skyrme parameterizations have been used within Haretree-Fock
(HF) method to investigate some static and dynamic nuclear ground state properties
of 174-206Hg isotopes. In particular, the binding energy per nucleon, proton, neutron,
mass and charge densities and corresponding root mean square radii, neutron skin
thickness and charge form factor. The calculated results are comp

Background: Dental implants act as infrastructure for fixed restoration to look like as a natural tooth. Osseointegration is a biological events and considered as a base for success of dental implant. The aim of this study is to evaluate the bond strength between bone and Ti implant coated with mixture of nano hydroxyapatite-chitosan-collagen compared with Ti implants coated with nano hydroxyapatite implanted in rabbit tibia, after different period of implantation time (two and six weeks) by torque removal test. Material and methods: 36 screws of commercially pure titanium; 8mm in length and 3mm diameter , 18 screws coated with mixture of nano hydroxyapatite-chitosan-collagen and18 screws coated with nano hydroxyapatite by dip coating. St

In this article, an inverse problem of finding timewise-dependent thermal conductivity has been investigated numerically. Numerical solution of forward (direct) problem has been solved by finite-difference method (FDM). Whilst, the inverse (indirect) problem solved iteratively using Lsqnonlin   routine  from MATLAB. Initial guess for unknown coefficient expressed by explicit relation   based on nonlocal overdetermination conditions and intial input data .The obtained numrical results are presented and discussed in several figures and tables. These results are accurate and stable even in the presense of noisy data.