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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
Tue Dec 31 2024
Journal Name
Sabrao Journal Of Breeding And Genetics
MORPHOLOGICAL AND ANATOMICAL STUDY OF THE FLORAL PARTS OF LILY (LILIUM CANDIDUM L.) CULTIVATED IN IRAQ
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Publication Date
Sun Jun 21 2020
Journal Name
Baghdad Science Journal
Synthesis of Gold Nanoparticles by using Batch Method and Study its Antibacterial Activity
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The research involves preparing gold nanoparticles (AuNPs) and studying the factors that influence the shape, sizes and distribution ratio of the prepared particles according to Turkevich method. These factors include (reaction temperature, initial heating, concentration of gold ions, concentration and quantity of added citrate, reaction time and order of reactant addition). Gold nanoparticles prepared were characterized by the following measurements: UV-Visible spectroscopy, X-ray diffraction and scanning electron microscopy. The average size of gold nanoparticles was formed in the range (20 -35) nm. The amount of added citrate was changed and studied. In addition, the concentration of added gold ions was changed and the calibration cur

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Publication Date
Sat Mar 30 2024
Journal Name
Journal Of Kufa For Mathematics And Computer
Approximate Solution of Linear and Nonlinear Partial Differential Equations Using Picard’s Iterative Method
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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
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Thu Apr 01 2021
Journal Name
Computer Methods And Programs In Biomedicine
A hybrid approach based on multiple Eigenvalues selection (MES) for the automated grading of a brain tumor using MRI
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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Building a Reliable Steganography System Using Random Key in a spatial Domain of Image
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With time progress importance of hiding information become more and more and all steganography applications is like computer games between hiding and extracting data, or like thieves and police men always thieve hides from police men in different ways to keep him out of prison. The sender always hides information in new way in order not to be understood by the attackers and only the authorized receiver can open the hiding message. This paper explores our proposed random method in detail, how chooses locations of pixel in randomly , how to choose a random bit to hide information in the chosen pixel, how it different from other approaches, how applying information hiding criteria on the proposed project, and attempts to test out in code, and

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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
Effect of pH on the Structural and Optical Properties of Cadmium oxide Thin Films Prepared Using the Successive Ionic Layer Adsorption and Reaction (SILAR) Method
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Cadmium oxide (CdO) thin films were deposited using the sequencing ion layer adsorption and reaction (SILAR) method. In this study, the effect of the pH value of an aqueous solution of cadmium acetate at a concentration of 0.2 mol of the cadmium oxide film was determined. The solution source for the cadmium oxide film was cadmium ions and an aqueous ammonia solution. The CdO films were deposited on glass substrates at a temperature of 90 ℃. The cadmium oxide film thickness was determined by the weight difference method at pH values ​​(7.2, 8.2). X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the size of the crystals increased with the increase in the solution (pH). While the UV-visible spectra of the fil

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
A Comparative Study on the Active Constituents, Antioxidant Capacity and Anti-Cancer Activity of Cruciferous Vegetable Residues
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This study is pointed out to estimate the effectiveness of two solvents in the extraction and evaluating the active ingredients and their antioxidant activity as well as anti-cancer efficiency. Therefore, residues from four different Brassica vegetables viz. broccoli, Brussels sprout, cauliflower, and red cherry radish were extracted using two procedures methods: methanolic and water crude extracts. Methanol extracts showed the highest content of total phenolic (TP), total flavonoids (TF), and total tannins (TT) for broccoli and Brussels sprouts residues. Methanolic extract of broccoli and Brussels sprouts residues showed the highest DPPH· scavenging activity (IC50 = 15.39 and 18.64 µg/ml). The methanol and water ex

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