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Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific public area by using CCTV (closed-circuit television). The problem also occurs in case the software tool is inaccurate. The technique of this notion is to use large data of face images, some faces are wearing masks, and others are not wearing masks. The methodology is by using machine learning, which is characterized by a HOG (histogram orientation gradient) for extraction of features, then an SVM(support vector machine) for classification, as it can contribute to the literature and enhance mask detection accuracy. Several public datasets for masked and unmasked face images have been used in the experiments. The findings for accuracy are as follows: 97.00%, 100.0%, 97.50%, 95.0% for RWMFD (Real-world Masked Face Dataset)& GENK14k, SMFDB (Simulated Masked Face Recognition Dataset), MFRD (Masked Face Recognition Dataset), and MAFA (MAsked FAces)& GENK14k for databases, respectively. The results are promising as a comparison of this work has been made with the state-of-the-art. The workstation of this research used a webcam programmed by Matlab for real-time testing.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Assessment of surface water quality using statistical analysis methods: Orontes River (Case study)
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The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Evaluations of Potable Water Tanks Epoxy Coatings Performance Using Electrochemical Impedance Spectroscopic Method
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Abstract  

The aim of this paper is to investigate and discuss the mechanisms of corrosion of epoxy coatings used for potable water tanks. Two distinct types of Jotun epoxy coatings: Tankguard 412 contained polyamine cured epoxy and Penguard HB contained polyamide cured epoxy, were tested and studied using the electrochemical impedance spectroscopic (EIS) method. The porosity of epoxy coatings was determined using EIS method. The obtained results showed that the two epoxy coatings have excellent behavior when applied and tested in potable water of Basrah city. Polyamine is more resistance to water corrosion compared to polyamide curing epoxy and has high impedance values. Microscopic inspection after te

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Publication Date
Fri Jan 04 2019
Journal Name
Journal Of Planner And Development
نمذجة توزيع المدارس الابتدائية في مدينة الفلوجة باستخدام نظم المعلومات الجغرافية G.I.S
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Publication Date
Mon Nov 19 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Study of the impact of foreign direct investment in the Iraqi tax system using the factorial analysis: (principal components)
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The tax system, like any other system, as a set of elements and parts that complement each other and are interrelated and interact to achieve specific goals, and is a natural  reflection of the economic, social and political conditions prevailing in society, and therefore the objectives of tax policy formulated in line with the objectives of economic policy in general, which means that any change in economic policy clearly affects fiscal policy measures and fiscal policy in particular.

The problem of searching for the impact of foreign direct investment in the Iraqi tax system was focused on the study  the of foreign direct investment and therole played in developing and improving the economic reality and its implicatio

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Removal of Suspended Solids Using Pumice Stone in Integrated Fixed Film Activated Sludge Process
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Wastewater treatment plants operators prefer to make adjustments because they are more cost effective, to use the existing tank instead of building new ones. In this case an imported materials would be  used as bio-loads to increase biomass and thus maintain efficiency as the next organic loading increases.In the present study, a local substance "pumice stone" was used as a biological carrier in the aeration tank, and the experiments were carried out in five stages: without biological carriers, filling ratio of 4%,10%,20%, and25% with pumice stone, the maximum organic loading at each stage (1.1884, 1.2144, 1.9432, 2.7768, 3.3141)g BOD /l.d respectively.Other experiments were carried out to determine the best filling ratio, the SS remova

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Numerical Solution of Fractional Volterra-Fredholm Integro-Differential Equation Using Lagrange Polynomials
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In this study, a new technique is considered for solving linear fractional Volterra-Fredholm integro-differential equations (LFVFIDE's) with fractional derivative qualified in the Caputo sense. The method is established in three types of Lagrange polynomials (LP’s), Original Lagrange polynomial (OLP), Barycentric Lagrange polynomial (BLP), and Modified Lagrange polynomial (MLP). General Algorithm is suggested and examples are included to get the best effectiveness, and implementation of these types. Also, as special case fractional differential equation is taken to evaluate the validity of the proposed method. Finally, a comparison between the proposed method and other methods are taken to present the effectiveness of the proposal meth

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Publication Date
Sun Dec 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Solving the Inverse Kinematic Equations of Elastic Robot Arm Utilizing Neural Network
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The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Stimulation of Macrophage Cells Against Cutaneous Leishmaniasis Using Silver Nanoparticles
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Cutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production.  This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Numerical Solutions of Two-Dimensional Vorticity Transport Equation Using Crank-Nicolson Method
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This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

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