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 this research we prepared CdS thin films by Spray pyrolysis method on a glass substrates and we study its structural , optical , electrical properties .The result of (X-Ray ) diffraction showed that all thin films have a polycrystalline structure , The relation of the transmission as a function of wavelength for the CdS films had been studied , The investigated of direct energy gap of the CdS its value is (2.83 eV). In Hall effect measurement of the CdS we find the charge carriers is p – type and Hall coefficient 1157.33(cm3/c) ,Hall mobility 6.77(cm2/v.s)

       Modification of gas chromatographic technique for the separation and determination of methyl ethoy silane compounds which were synthesized by the addition of absolute ethanol to methyl chlorosilane compounds have been elaborated experimentally.  The addition of absolute dry ethanol to methyl chlorosilane compounds in the presence of a dry stream of nitrogen gas led to sweep out the liberated HCl gas. This method was found to be the suitable method for the preparation of methyl ethoxy silane compounds. The optimum parameter selected after careful and precise studies was between 20 – 30 ml \ min to carrieir gas flow rate, while applied temperatures of detector and injection part were 250 Â

Poverty is defined as a low standard of living in the sense that a poor person can not afford a minimum standard of living. The phenomenon of poverty is one of the most serious problems that must be dealt with seriously. This phenomenon has persisted in Iraq for decades because of the harsh economic conditions and unstable security conditions due to the crises it has faced since 2013. This study requires much study and analysis. And rural areas as a special case. In this study, the researcher examined the poverty line as a criterion in estimating the poverty indicators, which include (poverty percentage H, poverty gap PG, poverty intensity PS), based on the continuous social and economic survey data for households in 2014. The ma

In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.

In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,