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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
Sat Mar 18 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of The Electromagnetic Field Intensity and Duration of Time on Some of The Morphological Characteristics of The Plant Safflower Carthamus tinctorius L.
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 The experiment was carried out in the field of botanical garden belonging to the Department of Biology Sciences, College of Education for Pure Science -Ibn AL-Haitham ,Baghdad University. for the growing season. 2014 -2013 to study the effect of the electromagnetic field which included five different intensities (0,5,10,15,20) MT and three periods of time, namely, (1,2,3) an hour and their interaction on  some of the morphological characteristics of the safflower plant . designed experiment by Randomized Complete Block Design (RCBD) and three replicates per treatment, compared to the average using  less significant difference at the level of probability (0.05) , the results showed the following:- 1-Exposing seeds to diffe

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Institutional Performance Assessment using a model of the European Foundation for Quality Management (EFQM) A case study at an organization
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The study aims to use the European Excellence Model (EFQM) in assessing the institutional performance of the National Center for Administrative Development and Information Technology in order to determine the gap between the actual reality of the performance of the Center and the standards adopted in the model, in order to know the extent to which the Center seeks to achieve excellence in performance to improve the level of services provided and the adoption of methods Modern and contemporary management in the evaluation of its institutional performance.

The problem of the study was the absence of an institutional performance evaluation system at the centre whereby weaknesses (areas of improvement) and st

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Publication Date
Tue Mar 31 2020
Journal Name
College Of Islamic Sciences
The position of women In Literary Literature Models of the Arabic and Kurdish literature
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This research deals with the topic of "the status of women" in the literature of Sufism. The researcher cites a bundle of mystical yarns, and examples of verses and poems from this high literature that look at women with reverence and appreciation. The researcher tried to find an appropriate explanation and away from the arbitrariness of the symbols used by the poets of Islamic Sufism In their poems.

    The research is considered a comparative study of the Arabic and Kurdish dialects, by selecting six famous poets from the literature of literature, three of them from Arabic literature, and the other three from Kurdish literature, so the research is di

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Publication Date
Tue Jun 30 2020
Journal Name
College Of Islamic Sciences
The position of women In Literary Literature Models of the Arabic and Kurdish literature
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This research deals with the topic (the position of women) in the literature literature, and the researcher cites a bouquet of woolen yarn, examples of verses and poems from this fine literature that looks at the woman with respect and appreciation. In their poems.
The research is a comparative search for Arab and Kurdish literature, by selecting six famous poets in the literature, three of them are from Arabic literature, and the other three are from Kurdish literature, and thus the research is divided into two subjects and six demands.
Finally, the researcher tried to set a brick that would be an entry point to find an indicative explanation and a suitable explanation that would break those symbols and signs that caused the exp

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Financial performance evaluation using some indicators of value creation (Analytical study of selected sample of Iraqi banks)
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The research of three-based financial indicators to create value for shareholders, have been identified research problem in a number of the questions revolved around the extent to which it can express its based performance metrics to create value for the essence and the reality of the surveyed enterprises performance, Can the departments surveyed companies to choose the scale or the most harmonizing index and an expression of the actual performance of the company, has the goal of research is to diagnose the strengths and weaknesses in the performance of the surveyed enterprises through the use of a number of based on the concept of creating economic value and the search for the most suitable indicator to the reality of the perfor

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Jun 28 2021
Journal Name
Journal Of Engineering
Effective quality control of a municipal wastewater treatment plant using Geographic information systems: A Review
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Inefficient wastewater disposal and wastewater discharge problems in water bodies have led to increasing pollution in water bodies.  Pollutants in the river contribute to increasing the biological oxygen demand (BOD), total suspended solids (SS), total dissolved solids (TDS), chemical oxygen demand (COD), and toxic metals render this water unsuitable for consumption and even pose a significant risk to human health. Over the last few years, water conservation has been the subject of growing awareness and concern throughout the world, so this research focused on review studies of researches that studied the importance of water quality of wastewater treated disposal in water bodies and modern technology to management w

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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