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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
Fri Oct 10 2025
Journal Name
Journal Of Visualized Experiments
Explainable AI for Visual Inspection: A Comparative Analysis and Review
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Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
A Cognitive Hybrid Tuning Control Algorithm Design for Nonlinear Path-Tracking Controller for Wheeled Mobile Robot
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Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
A Proposed Artificial Intelligence Algorithm for Assessing of Risk Priority for Medical Equipment in Iraqi Hospital
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This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
A Visual Interface Design for Evaluating the Quality of Google Map Data for some Engineering Applications
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Today, there are large amounts of geospatial data available on the web such as Google Map (GM), OpenStreetMap (OSM), Flickr service, Wikimapia and others. All of these services called open source geospatial data. Geospatial data from different sources often has variable accuracy due to different data collection methods; therefore data accuracy may not meet the user requirement in varying organization. This paper aims to develop a tool to assess the quality of GM data by comparing it with formal data such as spatial data from Mayoralty of Baghdad (MB). This tool developed by Visual Basic language, and validated on two different study areas in Baghdad / Iraq (Al-Karada and Al- Kadhumiyah). The positional accuracy was asses

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Publication Date
Thu Dec 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The design of a proposed model for the application of the insurance policy for medical errors
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The aim of this study is to design a proposed model for a document to insure the mistakes of the medical profession in estimating the compensation for medical errors. The medical profession is an honest profession aimed primarily at serving human and human beings. In this case, the doctor may be subject to error and error , And the research has adopted the descriptive approach and the research reached several conclusions, the most prominent of which is no one to bear the responsibility of medical error, although the responsibility shared and the doctor contributes to them, doctors do not deal with patients according to their educational level and cultural and there are some doctors do not inform patients The absence of a document to insu

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Publication Date
Tue Nov 01 2022
Journal Name
Optik
Design new D-π-A materials for sensitizers for dye-sensitized solar cells: Quantum chemical study
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Within this paper, we developed a new series of organic chromophores based on triphenyleamine (TPA) (AL1, AL-2, AL-11 and AL-22) by engineering the structure of the electron donor (D) unit via replacing a phenyle ring or inserting thiophene as a π-linkage. For the sake of scrutinizing the impact of the TPA donating ability and the spacer upon the photovoltaic, absorptional, energetic, and geometrical characteristic of these sensitizers, density functional theory (DFT) and time-dependent DFT (TD-DFT) have been utilized. According to structural characteristics, incorporating the acceptor, π-bridge and TPA does not result in a perfect coplanar conformation in AL-22. We computed EHOMO, ELUMO and bandgap (Eg) energies by performing frequency a

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Engineering
A Comprehensive Review for Integrating Petrophysical Properties, Rock Typing, and Geological Modeling for Enhanced Reservoir Characterization
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Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

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Publication Date
Sat Dec 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
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The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Effects of Macroeconomic Variables on Gross Domestic Product in Saudi Arabia using ARDL model for the period 1993-2019
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This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo

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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
Forward and Reverse Osmosis Process for Recovery and Re-use of Water from Polluted Water by Phenol
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The research aims to apply the novel forward osmosis (FO) process to recover pure water
from contaminated water. Phenol was used as organic substance in the feed solution, while sodium
chloride salt was used as draw solution. Membranes used in the FO process is the cellulose
triacetate (CTA) and polyamide (thin film composite (TFC)) membrane. Reverse osmosis process
was used to treatment the draw solution, the exterior from the forward osmosis process. In the FO
process the active layer of the membrane faces the feed solution and the porous support layer faces
the draw solution and this will show the effect of dilutive internal concentration polarization and
concentrative external concentration polarization.
In th

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