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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
Tue Dec 13 2011
Journal Name
Iraqi Journal Of Laser
The Efficacy of Er:YAG Laser on Intrapulpal Temperature Rise of Class V Cavity Preparation
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The objective of this study is to determine the efficacy of class V Er:YAG laser (2940 nm) cavity preparation and conventional bur cavity preparation regarding Intrapulpal temperature rise during cavity preparation in extracted human premolar teeth. Twenty non carious premolar teeth extracted for orthodontic purposes were used and class V cavity preparation was applied both buccal and lingual sides for each tooth .Samples were equally grouped into two major groups according to cavity depth (1mm and 2mm). Each major group was further subdivided into two subgroupsof ten teeth for each (twenty cavities for each subgroup). TwinlightEr:YAG laser (2940 nm) with 500mJ pulse energy, P.R.R of 10 Hz and 63.69 J/cm2 energy density was used. The ana

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Publication Date
Tue Mar 25 2025
Journal Name
Italian Journal Of Medicine
Cytokine profile in COVID-19 infection: focus on interleukin-13, interleukin-33, and tumor necrosis factor-α as immunological markers
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COVID-19 is a pandemic disease that has a wide spectrum of symptoms from asymptomatic to severe fatal cases due to hyperactivation of the immune system and secretion of pro-inflammatory cytokines. This study aimed to assess the level and impact of interleukin (IL)-13, IL-33, and tumor necrosis factor (TNF)-α cytokines on immune responses in mild and moderate COVID-19-infected Iraqi patients. A prospective case-control study was conducted from January 2023 to January 2024; it included 80 patients infected with moderate COVID-19 infection who consulted in different private clinics and 40 healthy controls. The serum of both groups was tested for quantification of serum IL-13, IL-33, and TNF-α using the human enzyme-linked immunosorbe

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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
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
A realistic vision of the ration card system in Iraq for the duration (1997-2003) and (2017-2003)
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Abstract:

The researcher shed light on a diet in Iraq before 2003 became in this period. And how the ration card has a variety of vocabulary and cover the need of the population of commodities and have a key role in saving Iraq from a real crisis in the period of economic siege, especially in light of the State's direction to support the agricultural sector, which in that period able to fill half of the market needs of food the basic. As well as providing strategic storage at the Ministry of Commerce enough for six months But after the events of 2003 and the crises that hit the country and the unstable security situation began to rise voices calling for reform of the ration card system as a system that is a burden on the

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Publication Date
Fri Nov 01 2019
Journal Name
International Journal On Interactive Design And Manufacturing (ijidem)
A real-time automated sorting of robotic vision system based on the interactive design approach
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Publication Date
Fri Jan 02 2026
Journal Name
Journal Of Engineering
Design and Implementation of ICT-Based Recycle-Rewarding System for Green Environment
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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
Dependence on Media and the Formation of the Level of the Academic Elite's Knowledge concerning United Nations' Affairs (A research based on a doctoral thesis)
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The UN organization is considered one of the most important organizations at the international level. It has accomplished multiple tasks and roles of many different issues and events that hit the developing and advanced world countries. It has performed a series of procedures and laws that have had an impact on ending the wars and conflicts that plagued some countries and continued for a period of time in the past. Moreover, it has improved the level of the international relations between a number of countries due to the problems and incidents took place between them. It has relied on finding solutions and treatments for humanitarian problems such as the preservation of the environment, preventing the spread of epidemics and diseases Thi

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Publication Date
Wed Dec 22 2021
Journal Name
Antibiotics
Classic vs. Novel Antibacterial Approaches for Eradicating Dental Biofilm as Adjunct to Periodontal Debridement: An Evidence-Based Overview
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Periodontitis is a multifactorial chronic inflammatory disease that affects tooth-supporting soft/hard tissues of the dentition. The dental plaque biofilm is considered as a primary etiological factor in susceptible patients; however, other factors contribute to progression, such as diabetes and smoking. Current management utilizes mechanical biofilm removal as the gold standard of treatment. Antibacterial agents might be indicated in certain conditions as an adjunct to this mechanical approach. However, in view of the growing concern about bacterial resistance, alternative approaches have been investigated. Currently, a range of antimicrobial agents and protocols have been used in clinical management, but these remain largely non-v

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Publication Date
Mon Aug 15 2022
Journal Name
Revis Bionatura
ND2 Gene Sequencing of Sub fertile Patients Recovered from COVID-19 in Association with Toxoplasmosis
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A total of (90) blood samples were collected from male patients infected with Toxoplasmosis who recovered from COVID- 19 and attended Kamal Alsamiraai Hospital from 15 January to 15 September 2021. We measured anti-Toxoplasma antibodies (IgG and IgM) detected by ELISA, whereas Anti-COVID-19 antibodies (IgG and IgM) were estimated using Elisa and Afilias. The semen characteristics were also studied among fertile, healthy individuals (control group) and sub-fertile patients. Results showed that the mean sperm count was high among the control group (40.5±1.3x 106/ml) compared with that of the sub-fertile patients (10.3±1.75 and 8.8±1.9 x 106/ml for oligozoospermia, and oligoasthenozoospermia respectively), and it was the highest (44.7±1.4

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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