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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
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
The Effect of Special Exercises for those with (Cognitive Concentration) in the Development of Motor Satisfaction and Learning Some Types of Scoring Basketball for Students
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The importance of the research in the preparation of special exercises to develop some types of basketball scoring as a contribution to help the physical education teacher to find successful educational alternatives. The purpose of the study was to prepare special exercises for the cognitive (cognitive) survey in the development of motor satisfaction and learning some types of Scoring for basketball for students. Learn about the effect of cognitive exercises in cognitive development in students. The survey included students from the first stage of the Faculty of Physical Education and Sports Science \ University of Diyala (159) divided into 6 people. The sample was randomized by (b) and (b) D) and after dispersion by the standard method In

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Study of Aerodynamic Surface Roughness for Baghdad City Using Signal-Level Measurements
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Roughness length is one of the key variables in micrometeorological studies and environmental studies in regards to describing development of cities and urban environments. By utilizing the three dimensions ultrasonic anemometer installed at Mustansiriyah university, we determined the rate of the height of the rough elements (trees, buildings and bridges) to the surrounding area of the university for a radius of 1 km. After this, we calculated the zero-plane displacement length of eight sections and calculated the length of surface roughness. The results proved that the ranges of the variables above are ZH (9.2-13.8) m, Zd (4.3-8.1) m and Zo (0.24-0.48) m.

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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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
Wed May 12 2021
Journal Name
Annals Of The Romanian Society For Cell Biology
Contribution Ratio of Cognitive Learning Outcome in the Performance of the Two Skills of Mastering by Parallel Spherical Standing and Equilibrium on the Balance Beam
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The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Building the optimal portfolio for stock using multi-objective genetic algorithm - comparative analytical research in the Iraqi stock market
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Abstract:

The main objective of the research is to build an optimal investment portfolio of stocks’ listed at the Iraqi Stock Exchange after employing the multi-objective genetic algorithm within the period of time between 1/1/2006 and 1/6/2018 in the light of closing prices (43) companies after the completion of their data and met the conditions of the inspection, as the literature review has supported the diagnosis of the knowledge gap and the identification of deficiencies in the level of experimentation was the current direction of research was to reflect the aspects of the unseen and untreated by other researchers in particular, the missing data and non-reversed pieces the reality of trading at the level of compani

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Building discriminant function for repeated measurements data under compound symmetry (CS) covariance structure and applied in the health field
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Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of  groups based on a linear combination of a set of relevant variables know discriminant function. In this research  discriminant analysis used to analysis data from repeated measurements design. We  will  deal  with the problem of  discrimination  and  classification in the case of  two  groups by assuming the Compound Symmetry covariance structure  under  the  assumption  of  normality for  univariate  repeated measures data.

 

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Publication Date
Mon Jul 01 2019
Journal Name
J. Pharm. Sci. & Res.
Synthesis of coumarin by Pechman reaction - A Review
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Phenol condensed with β-keto esters via Pechmann condensation to form derivatives of Coumarin in various reaction conditions by two ways. Present paper is comparative study of synthesis Coumarin with the yield of product , reaction time and reaction conditions.

Publication Date
Wed Aug 15 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study the Effect of Tool Design on the Mechanical Properties of Bobbin Friction Stir Welded 6061-T6 Aluminum Alloy
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Bobbin friction stir welding (BFSW) is a variant of the conventional friction stir welding (CFSW); it can weld the upper and lower surface of the work-piece in the same pass. This technique involves the bonding of materials without melting. In this work, the influence of tool design on the mechanical properties of welding joints of 6061-T6 aluminum alloy with 6.25 mm thickness produced by FSW bobbin tools was investigated and the best bobbin tool design was determined. Five different probe shapes (threaded straight cylindrical, straight cylindrical with 3 flat surfaces, straight cylindrical with 4 flat surfaces, threaded straight cylindrical with 3 flat surface and threaded straight cylindrical with 4 flat surfaces) with various dimensio

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Fabrication and Characterization of Gas Sensor from ZrO2: MgO Nanostructure Thin Films by R.F. Magnetron Sputtering Technique
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Thin films ZrO2: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO2. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the

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