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Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are complex images in their interpretation. In this article, two deep convolutional neural network (DCNN) classifiers, such as Inception-v2 and VGG-16, are utilized to detect COVID-19 from a set of chest X-ray images. The dataset for this article was collected from the Kaggle platform (COVID-19 Radiography Database) and consists of images of positive and healthy people. This article concludes that the most suitable performance is the Inception-v2 classifier, which has achieved an accuracy of 97% in comparison to the VGG-16 classifier, which has achieved an accuracy of 93%.

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Improved Firefly Algorithm with Variable Neighborhood Search for Data Clustering
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Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Skin Detection using Improved ID3 Algorithm
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Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Tue Jun 05 2018
Journal Name
Journal Of Molecular Structure
Synthesis, characterization, experimental and theoretical structure of novel Dichloro(bis{2-[1-(4-methoxyphenyl)-1H-1,2,3-triazol-4-ylkN3] pyridine-kN})metal(II) compounds, metal ¼ Mn, Co and Ni
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The syntheses, characterizations and structures of three novel dichloro(bis{2-[1-(4-methoxyphenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II), [M(L)2Cl2], complexes (metal = Mn, Co and Ni) are presented. In the solid state the molecules are arranged in infinite hydrogen-bonded 3D supramolecular structures, further stabilized by weak intermolecular π…π interactions. The DFT results for all the different spin states and isomers of dichloro(bis{2-[1-phenyl-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II) complexes, [M(L1)2Cl2], support experimental measurements, namely that (i) d5 [Mn(L1)2Cl2] is high spin with S = 5/2; (ii) d7 [Co(L1)2Cl2] has a spin state of S = 3/2, (iii) d8 [Ni(L1)2Cl2] has a spin state of S =

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Publication Date
Tue Jan 01 2019
Journal Name
Inorganica Chimica Acta
Synthesis, characterisation and electrochemistry of eight Fe coordination compounds containing substituted 2-(1-(4-R-phenyl-1H-1,2,3-triazol-4-yl)pyridine ligands, R = CH3, OCH3, COOH, F, Cl, CN, H and CF3.
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Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.

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Publication Date
Sat Dec 01 2012
Journal Name
Asian Journal Of Chemistry
Microwave assisted synthesis of new heterocyclic compounds: 1, 2, 3-triazoles and tetrazoles and study of their biological activity
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The work includes synthesis of 1,2,3-triazoles via click conditions and using the microwave irradiation starting from two synthesized azides: 2,3,4,6-tetra-O-acetyl-β-D-glucopyranosyl azide (5) and perfluorobutylethyl azide (10) and different terminal alkynes. It also includes microwave enhanced synthesis of tetrazoles via the reaction of two synthesized azides i.e., perfluorobutylethyl azide (10) and 1,5-diazidopentane (13) with benzoyl cyanide. Most of the prepared compounds have been characterized by: TLC, FT-IR, 1H NMR, 13C NMR, LC-MS and microelemental analysis

Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Nano MgO catalyst for chemical depolymerization of polyethylene terephthalate (PET)
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This paper focuses firstly on the production of monomers bis (2-hydroxyethyl) terephthalate (BHET) and oligomers by using two different form of MgO light active and Nano Magnesium oxide with different weight ratio (0.15, 0.25 and 0.5) by using chemical recycling glass condenser at 190 ˚C. The second purpose is to study the effect of catalyst ratio, time of reaction and yield of products of the product. Elemental analysis for Carbon –Hydrogen and Nitrogen (CHN), differential scanning calorimetry (DSC), infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA) have been investigated. Results indicated the catalytic activity was found to correlate with surface area; however, LA MgO has shown an exceptional activity, still it is h

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Publication Date
Wed Apr 12 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Characterization of Some New Thiazine , Azetidine and Thiazolidine Compounds Containing 1,3,4Thiadiazole Moiety And Their Antibacterial Study
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     2-amino-5-mercapto-1,3,4-thiadiazole [I] were prepared by the cyclization of thiosemecarbazide with carbon disulphide and anhydrous  sodium carbonate in ethanol as a solvent. The reaction of compound [I] with alkyl halides yielded 2- amino-5-thioalkyl-1,3,4- thiadiazole [II] and [III] . Compound [II] and [III] were reacted with different aromatic aldehydes to yieled 2-[(substituted benzyliden ) amino] -5- thioalkyl-1,3,4- thiadiazole [IV]a-c , [V]a-d and [VI]a-d .  Schiff ,s bases [IV]a-c , [V]a-d and [VI]a-d  were found to react with  2mercapto benzoic acid in the triethyl amine to give 3-[ 5-( alkylthio) -1,3,4- thiadiazol-2-yl] 2,3- dihydro- 2- (aryl) benzo [e] [1,3] thiazine -4-one [VII]a-

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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Assessment of Serum Level of Protein Carbonyl as a Marker of Protein Oxidation in Patients with Type 2 Diabetes Mellitus
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Background: Diabetes mellitus is a chronic disease with an increasing prevalence worldwide and characterized by an increase in oxidative stress and inflammation. The most important factor that is responsible for oxidative stress and production of reactive oxygen species (ROS) is hyperglycemia. The major targets of ROS are proteins. The most common and widely used biomarker of severe oxidative protein damage is protein carbonyl content.

The study was designed to assess the serum level of protein carbonyl as a marker of protein oxidation in patients with type 2 diabetes mellitus and to evaluate the effect of age, body weight, waist circumference, diabetic control and disease duration on the level

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