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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 lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.

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Publication Date
Mon Feb 07 2022
Journal Name
Cogent Engineering
A partial image encryption scheme based on DWT and texture segmentation
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Publication Date
Wed Dec 25 2024
Journal Name
الذكوات البيض
Artificial Intelligence and its Impact on Education and Media
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Abstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison Study of Electromyography Using Wavelet and Neural Network
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In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

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Publication Date
Wed Mar 15 2023
Journal Name
Al-academy
Geometrical Foundations of Shape in Structural Design of Contemporary Ceramic Pots "The artist "IBRAHIM SAEED" is a model"
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Each era has advantages in terms of innovation and development in form, technology, style, and design in ceramic vessels, both at the level of functional and aesthetic performance, so this study aimed to demonstrate the importance of geometrical foundations in the design structure of contemporary ceramic vessels, and also to reveal the constructive skills in The structure of the ceramic figure.
The researchers used the descriptive analytical approach to suit the nature of the study, and they described and analyzed the ceramic works in terms of geometric shape systems, elements and foundations of design in construction, formal diversity in the general design of ceramic vessels, and references and sources of artwork. In addition to th

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Dynamic algorithm (DRBLTS) and potentially weighted (WBP) to estimate hippocampal regression parameters using a techniqueBootstrap (comparative study)
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Bootstrap is one of an important re-sampling technique which has given the attention of  researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such  Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con

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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Design and Evaluation of a Polarizer Filter
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This research includes theoretical and evaluation design of a polarizer filter of high transmission in the near IR region of (900-1200nm) for different incidence angles to obtain a long wave and short wave pass filter using analytical calculations. Results refer to a new configuration design in fewer layers than used in previous studies in the long wave pass at incidence angles (45o,50o,55o). Adopted Hafnium dioxide (HfO2) and Magnesium fluoride (MgF2) as coating material at design wavelength (933nm), the study also included design short wave pass polarizer by using the same coating material.

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Design and Implementation of a Vlsm Simulator
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Variable-Length Subnet Masks (VLSM), often referred to as "subnetting a subnet", is used to maximize addressing efficiency. The network administrator is able to use a long mask on networks with few hosts, and a short mask on subnets with many hosts. This addressing scheme allows growth and does not involve wasting addresses. VLSM gives a way of subnetting a network with
minimal loses of IP addresses for a specific range. Unfortunately, the network administrator has to perform several mathematical steps (or use charts) to get the required results from VLSM. In this paper, a simple graph simulator is proposed (using Visual Basic 6.0 Language) to perform all the required mathematical steps and to display the obtained required informatio

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Publication Date
Wed Sep 12 2012
Journal Name
Journal Of Engineering
Design and Implementation of a Vlsm Simulator
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Variable-Length Subnet Masks (VLSM), often referred to as "subnetting a subnet", is used to maximize addressing efficiency. The network administrator is able to use a long mask on networks with few hosts, and a short mask on subnets with many hosts. This addressing scheme allows growth and does not involve wasting addresses. VLSM gives a way of subnetting a network with minimal loses of IP addresses for a specific range. Unfortunately, the network administrator has to perform several mathematical steps (or use charts) to get the required results from VLSM. In this paper, a simple graph simulator is proposed (using Visual Basic 6.0 Language) to perform all the required mathematical steps and to display the obtained required information (the

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of The College Of Languages (jcl)
The Role of Gender and Culture in Dealing with the Arab Woman's Issues Embodied in Caricatures: A Cognitive Linguistic Analysis
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Gender and culture are among the factors that influence the process of understanding and interpreting different types of communication, especially images. The current study, which is a part of a master’s thesis, aims at investigating the role of gender and culture in interpreting and understanding the caricatures that deal with women’s issues in Arab societies. To this end, the researchers adopted Barthes’ (1957) concepts of denotation and connotation in his theory of mythologies in addition to Langacker’s (1987) theory of (Domains). The research concludes that the female subjects have better cognitive abilities in investing the signs within the selected caricatures. The other factor the study reached to is that the respondents

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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