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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
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
The communicative dimension of Andalusian-Moroccan poetry In the classification and refining book (The pleasure of the soul of the five senses)
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The heritage of the human peoples remains a beacon of data, after renewed awareness of them, open to their propositions, which are born from the womb of intertwined elements of customs, knowledge, arts, and literature ... Misleading the reception process, it may be something intriguing to identify with caution with the text sample selected by the current search procedures prepared according to the adoption of a descriptive therapist in a three-dimensional approach, as well as a comprehensive textual reference for that specific communication dimension within Anthology Andalusian - Moroccan poetry in the book of pleasure in the perception of the five senses Tahdib ibn Manzoor (d. 711 e) from the origin of Tivashi (d. 651 e) Tagged: Separat

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Sun Jan 01 2017
Journal Name
Al–bahith Al–a'alami
Arabic language and tongue violence in Arab satellite channels
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This study aimed at identifying the effect of violence on speech disorders concerning Arab Broadcasting . Language is a pot of thought and a mirror of human civilization and communication tool, but the Arabic language is suffering a lot of extraneous terms them, particularly through the media. This study attempts to answer the following question: Is the phenomenon of linguistic duality in the Media reflected negatively on the rules of the classical language? The study deals with the explanation and interpretation of the phenomenon that has become slang exist in our Media More. And the study suggests re- consideration of the value in the Media ,hence the problem will be resolved.   

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of The College Of Languages (jcl)
A Stylistic Analysis of Two Selected, English and Arabic, War Poems
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War as a human phenomenon, has its own literature. Poetry is a major genre in this literature. This paper is an attempt to investigate and analyse some stylistic features in two selected, English and Arabic, war poems. These poems share the same theme.Both promote the principle of sacrificing one’s own life for the sake of homeland.  This paper limits itself to analyse, thecontent words, tenses, semantic grouping of vocabulary and foregrounding in the two poems. The areas of analysis show great similarities in distributing the general content words (nouns, verbs, adjectives, and adverbs). In the analysis of the semantic areas of each content word, these poems reveal some similarities and some differences in their frequency rates.

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