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

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

The research deals with the interchange of the sign transformed from the universal to the local in the theatrical show through the direction processing in the production of a communicative artistic discourse and message, thus making the process of reading the speech and recognizing it by taking into account the cultural differences, customs and local rituals of each country, region, or area. The problem of the research was focused on answering the following question: What are the requirements for the sign in terms of its transformation between the universality and locality in the read-out?

               The importance of research is to determine the requiremen

Traditionally, style is defined as the expressive, emotive or aesthetic emphasis added linguistically to the discourse with its meaning is the same. In the current study, however, style is defined as the linguistic choice that the language users can make for specific purposes.

    This study, thus, aims at analyzing political Arabic and English speeches to find out whether there are differences of style between English and Arabic and whether the choices the language users make  can show any traits of their psychological status.

    To fulfill the above aims, the study hypothesizes that English and Arabic  speeches can be analyzed stylistically and that there are stylistic difference

     Estimating multivariate location and scatter with both affine equivariance and positive break down has always been difficult. Awell-known estimator which satisfies both properties is the Minimum volume Ellipsoid Estimator (MVE) Computing the exact (MVE) is often not feasible, so one usually resorts to an approximate Algorithm. In the regression setup, algorithm for positive-break down estimators like Least Median of squares typically recomputed the intercept at each step, to improve the result. This approach is called intercept adjustment. In this paper we show that a similar technique, called location adjustment, Can be applied to the (MVE). For this purpose we use the Minimum Volume Ball (MVB). In order

The current research aims at knowing the impact of the mind-clearing method in teaching second year intermediate students “reading book”. To achieve the study objective, the researchers intentionally chose Arjwan middle school, located in Baghdad Directorate of Education Al-Rusafa/2, which includes five classes for the second intermediate class. Division (A) was chosen randomly to represent the experimental group, which is taught in the mind-clearing method, while Division (B) represented the control group, which is taught in the traditional way. The sample of the research included (79) female students divided into (39) students in the experimental group, and (40) female students in the control group.To achieve the objective of the res

Generalized Additive Model has been considered as a multivariate smoother that appeared recently in Nonparametric Regression Analysis. Thus, this research is devoted to study the mixed situation, i.e. for the phenomena that changes its behaviour from linear (with known functional form) represented in parametric part, to nonlinear (with unknown functional form: here, smoothing spline) represented in nonparametric part of the model. Furthermore, we propose robust semiparametric GAM estimator, which compared with two other existed techniques.

The study aimed to assess the frequency of invasive fungal infection in patients with respiratory diseases by conventional and molecular methods. This study included 117 Broncho alveolar lavage (BAL) samples were collected from patients with respiratory disease (79 male and 38 female) with ages ranged between (20-80) years, who attended Medicine Baghdad Teaching hospital and AL-Emamain AL-Khadhymian Medical City, during the period from September 2019 to April 2020. The results in PCR versus culture methods in this study showed that out of 117 samples of fungal infections 30(25.6 %) were detected by culture method, while the 24(20.5%) samples were detected by PCR technique, the most commonly diagnosed pathogenic fungi is Candida spp.