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

KE Sharquie, JR Al-Rawi, AA Noaimi, MM Jabir, Iraqi Postgraduate Medical Journal, 2009

S Khalifa E, AR Jamal R, N Adil A, J Munqithe M…, 2009

     In this article, we aim to define a universal set consisting of the subscripts of the fuzzy differential equation (5) except the two elements  and , subsets of that universal set are defined according to certain conditions. Then, we use the constructed universal set with its subsets for suggesting an analytical method which facilitates solving fuzzy initial value problems of any order by using the strongly generalized H-differentiability. Also, valid sets with graphs for solutions of fuzzy initial value problems of higher orders are found.

The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky the

The use of credit cards for online purchases has significantly increased in recent years, but it has also led to an increase in fraudulent activities that cost businesses and consumers billions of dollars annually. Detecting fraudulent transactions is crucial for protecting customers and maintaining the financial system's integrity. However, the number of fraudulent transactions is less than legitimate transactions, which can result in a data imbalance that affects classification performance and bias in the model evaluation results. This paper focuses on processing imbalanced data by proposing a new weighted oversampling method, wADASMO, to generate minor-class data (i.e., fraudulent transactions). The proposed method is based on th

The paper probes into minute identification of the data of the methods followed in the electronic newspapers that aim to promote terrorist organizations like Al Qaeda and ISIS to draw emotional empathy and sympathy with them.
The paper aims at identifying:
How emotional empathy was utilized by terrorists in E-newspapers.
How useful utilizing emotional empathy was in attracting supporters. The sample that is used in the paper is based on the opening articles of E-newspapers that propagate Al Qaeda and ISIS, e.g. (Sawtu el jihad) “The Sound of Fighting in the Name of God”, (Mua’skar el Battar wal Shamikha wal Khansaa) “Camps of Al Battar, Shamika, and Khansaa”, “Inspire” and (Thurwatu el Sanam, Dabiq, and Rumiyah)