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 alphabets are detected using the mathematical algorithm of the morphological gradient. After that, the images are passed to the CNN architecture. The available database of Arabic handwritten alphabets on Kaggle is utilized for examining the model. This database consists of 16,800 images divided into two datasets: 13,440 images for training and 3,360 for validation. As a result, the model gives a remarkable accuracy equal to 99.02%.
In this paper, a new form of 2D-plane curves is produced and graphically studied. The name of my daughter "Noor" has been given to this curve; therefore, Noor term describes this curve whenever it is used in this paper. This curve is a form of these opened curves as it extends in the infinity along both sides from the origin point. The curve is designed by a circle/ ellipse which are drawing curvatures that tangent at the origin point, where its circumference is passed through the (0,2a). By sharing two vertical lined points of both the circle diameter and the major axis of the ellipse, the parametric equation is derived. In this paper, a set of various cases of Noor curve are graphically studied by two curvature cases;
... Show MoreThe conjunctive ''and'' and its Arabic counterpart ''و'' are discourse markers that express certain meanings and presuppose the presence of other elements in discourse. They are indispensable aids to both the text writers and readers. The present study aims to show that such cohesive ties help the writer to organize his main argument and communicate his ideas vividly and smoothly. They also serve as explicit signals that help readers unfold text and follow its threads as realized in the progression of context. The researcher has utilized the Quirk Model of Semantic Implication for data analysis. A total of 42 (22 for English and 20 for Arabic) political texts selected from different elite newspapers in both Arabic and English for the analy
... Show MoreThe aim of the current research is to recognizing the impact of mind and informational strategy on the achievement with the second intermediate students in the grammar of arabic language, the researcher used a partial-set experimental design and intentionally selected a sample out of the second intermediate class from (AL- Markazya Intermediate school) in the district of Hilla, affiliated which belongs to General Directorate of Babylon Education in the year (2020-2021) for applying the experiment. The sample was composed of (50) students, (25) ones for each group, the experimental group and normal one. The researcher balanced between the two groups in various changes including: (the chronological age counted by months, the academic achie
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The aim of the current research is to identify the level of availability of written expression skills included in the Arabic language curriculum document among middle school students from the teachers' point of view. The researcher used the descriptive approach. To analyze the data and access the research results, he used the (SPSS) program. The research was conducted during the first semester of the academic year 1442/1443 AH on a random sample of Arabic language teachers in the Bisha Education Department. They reached about (213) male and female teachers. The results revealed a number of indicators: the level of availability of written expression skills among middle school students in Bisha governorate
... Show MoreIn this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
... Show MoreThis research is concerned with the re-analysis of optical data (the imaginary part of the dielectric function as a function of photon energy E) of a-Si:H films prepared by Jackson et al. and Ferlauto et al. through using nonlinear regression fitting we estimated the optical energy gap and the deviation from the Tauc model by considering the parameter of energy photon-dependence of the momentum matrix element of the p as a free parameter by assuming that density of states distribution to be a square root function. It is observed for films prepared by Jackson et al. that the value of the parameter p for the photon energy range is is close to the value assumed by the Cody model and the optical gap energy is which is also close to the value
... Show MoreDiscriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.
ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
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