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Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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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%.

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Sat Jan 02 2021
Journal Name
Journal Of The College Of Languages (jcl)
Pragmatic Analysis of the Translation of English Culture-Specific Proverbs into Arabic
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Translating culture-specific proverbs (CSPs) is a challenging task since they often occur in a peculiar context. Further, CSPs are intended to imply meanings that extend far beyond the literal meaning of such a kind of proverbs. As far as English and Arabic are concerned, translators often encounter problems in translating CSPs due to cultural differences between the source language(SL) and the target language (TL) as well as what seems to be the lack of equivalence for some CSPs.

In view of this, the present study aims at investigating the translation of CSPs in three English-Arabic dictionaries of proverbs, namely Dictionary of Common English Proverbs Translated and Explained (2004), One thousand and One English Pr

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Publication Date
Tue Jun 20 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
A COMPARATIVE-MORPHOLOGICAL STUDY OF SKULLS IN TWO SPECIES OF CARNIVOROUS AND HERBIVOROUS MAMMALS
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The skull is one of the largest bones in the body. It is classified into flat bones that maintain the important organic structures; which are the brain, eyes, and tongue. The skull is a strong support for preserving these organs but they are various according to the type of animals and the environments in which they live and the nature of their nutrition. There are many differences among living organisms in terms of the bones in the skull, their difference or disappearance and their length in the shape of the head. The samples were taken from the scientific storage in the Iraq Natural History Research Center and Museum; Cape hare Lepus capensis (Linnaeus, 1758) and Red fox Vulpes vulpes (Linnaeus, 1758) and the study was conducted o

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Multiple Intelligences on the Acquisition of Science Operations by Middle School Students of Arabic Grammar
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The current research aims to identify the multiple intelligences in the fourth students’ acquisition of the literary processes of Arabic grammar and to identify the differences in multiple intelligence according to gender (males - females). The study was determined for students of the fourth literary preparatory Al-Hakim Preparatory (for males) and Rabat Preparatory (for females) of the Second Karkh Education Directorate, topics from the Arabic grammar subject (past tense, present tense, imperative, subject, and object) for the first semester of the academic year 2019-2020. The results showed that there were no statistically significant differences at the significance level (0.05) between the average scores of the students who were tau

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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of The College Of Education For Women
Analytical study of the images and roles of women and men in the books of the Arabic language at the elementary level
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Importance of the research:
The importance of any educational or scientific research through its intellectual arena of facts supply the individual and society, Supports Knowledge and Science Group, which raised will be locked in these topics in the future.
This research seeks to shed light on the image and the role of women and men in the books of the Arabic language in primary education (primary), To illustrate the negative effects of the phenomenon of sexism in textbooks, And its negative impact on emerging, And stay away as much as possible about the distinction between the sexes in the roles and qualities in textbooks traditional stereotypes and remove that put both sexes templates hinder the development of the individual and t

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Convergence Analysis for the Homotopy Perturbation Method for a Linear System of Mixed Volterra-Fredholm Integral Equations
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           In this paper, the homotopy perturbation method (HPM) is presented for treating a linear system of second-kind mixed Volterra-Fredholm integral equations. The method is based on constructing the series whose summation is the solution of the considered system. Convergence of constructed series is discussed and its proof is given; also, the error estimation is obtained. Algorithm is suggested and applied on several examples and the results are computed by using MATLAB (R2015a). To show the accuracy of the results and the effectiveness of the method, the approximate solutions of some examples are compared with the exact solution by computing the absolute errors.

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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