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New multispectral images classification method based on MSR and Skewness implementing on various sensor scenes
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Synthesis and Characterization of New Bis-Schiff Bases Linked to Various Imide Cycles
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       This research includes the synthesis of new bis-Schiff bases linked to different imide cycles. There were some steps involved in the synthesis of the novel Schiff bases with succinimide, phthalimide, tetrachlorophthalimide, and tetrabromophthalimide cycles. The first step involved the preparation of 4,4`-bis[(4-aminophenyl) methyl benzylidene]tolidine (1) via the condensation reaction of 3,3'-dimethyl-(1,1'-biphenyl)-4,4'-diamine with 4-amino acetophenone. In the second step, compound 1 reacted with various cyclic anhydrides, affording bis-amic acid Schiff bases 2-5. In the third step, the products 2-5 were dehydrated using the fusion method to prod

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Publication Date
Tue Jun 09 2020
Journal Name
Article In Journal Of Engineering Science And Technology
English Numbers Recognition Based on Sign Language Using Line-Slope Features and PSO-DBN Optimization Method
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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Unsupervised Segmentation Method for Thyroid Nodules in Ultrasound Images
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Thyroid is a small butterfly shaped gland located in the front of the neck just below the Adams apple. Thyroid is one of the endocrine gland, which produces hormones that help the body to control metabolism. A different thyroid disorder includes Hyperthyroidism, Hypothyroidism, and thyroid nodules (benign/malignant). Ultrasound imaging is most commonly used to detect and classify abnormalities of the thyroid gland. Segmentation method is a tool that used widely in many applications including medical image processing. One of the common applications of segmentation is in medical image analysis for clinical diagnosis that has an important role in terms of quality and quantity.
The main objective of this research is to use the Computer-Ai

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Publication Date
Fri Sep 01 2023
Journal Name
Iraqi Journal Of Physics
Photometry Technique to Map Elements’ Distribution on Comets’ Nuclei Surfaces Using a New Method
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This study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Satellite image classification using proposed singular value decomposition method
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In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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Publication Date
Mon May 31 2021
Journal Name
Iraqi Journal Of Science
Simultaneous Approximation by a New Sequence of Integral Type Based on Two Parameters
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This paper introduces a generalization sequence of positive and linear operators of integral type based on two parameters to improve the order of approximation. First, the simultaneous approximation is studied and a Voronovskaja-type asymptotic formula is introduced. Next, an error of the estimation in the simultaneous approximation is found. Finally, a numerical example to approximate a test function and its first derivative of this function is given for some values of the parameters. 

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the 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. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Tue Feb 01 2022
Journal Name
Civil Engineering Journal
Calibration of a New Concrete Damage Plasticity Theoretical Model Based on Experimental Parameters
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

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Publication Date
Wed Nov 24 2021
Journal Name
Iraqi Journal Of Science
A proposal of Multimedia Steganography Algorithm based on Improved Least Significant Bit (LSB) Method
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Because of the rapid development and use of the Internet as a communication media emerged to need a high level of security during data transmission and one of these ways is "Steganography". This paper reviews the Least Signification Bit steganography used for embedding text file with related image in gray-scale image. As well as we discuss the bit plane which is divided into eight different images when combination them we get the actual image. The findings of the research was the stego-image is indistinguishable to the naked eye from the original cover image when the value of bit less than four Thus we get to the goal is to cover up the existence of a connection or hidden data. The Peak to Signal Noise Ratio(PSNR) and Mean Square Error (

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