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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 Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Building a High Accuracy Transfer Learning-Based Quality Inspection System at Low Costs
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      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

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Publication Date
Fri Nov 21 2025
Journal Name
Journal Of Advances In Information Technology
Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata
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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of industry specialization of audit companies in detecting fraud in the financial statement
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Abstract:

The aim of the research is to demonstrate the impact of the professional specialization of the audit companies in the detection of fraud in the financial statements of the economic units listed in the Iraqi market for securities for the period 2014-2015 through the application of the model (Carcello) to test the hypothesis of research on the impact of professional specialization of audit companies in the detection of fraud in lists The effect of the variables was revealed through the use of statistical models of logistic regression model and correlation coefficient. After testing the hypotheses of the research, a number of conclusions were reached. The most important was the existence of a signi

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
PROJECT MANAGEMENT OF BALAD`S MAJOR SEWERAGE SYSTEM BY USING THE GOAL PROGRAMMING METHOD
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Abstract

          The project of balad's major sewerage system is one of the biggest projects who is still in progress in salahulddin province provincial - development plan that was approved in 2013 . This project works in two parts ; the 1st is installing the sewerage networks (both of heavy sewerage & rain sewerage) and the 2nd is installing the     life – off units (for heavy sewerage & rain sewerage , as well) . the directorate of salahuiddin is aiming that at end of construction it will be able to provide services for four residential quarters , one of the main challenges that project's  management  experience is how to achieve thes

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Publication Date
Sun Apr 06 2014
Journal Name
Journal Of Educational And Psychological Researches
Build a scale to measure the moral reasoning of students at the preparatory stage in Baghdad
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    The moral aspect is an important one in the structure of personality , and the lack of moral aspect is responsible for what we suffering today from problems . there is no exaggeration to say that many of our current problems are moral problems , and reflects the lack of moral growth.                            

 The goal of research is to build scale in order to detect the level of moral reasoning among junior high school students in Baghdad , The researcher followed the procedures in the construction of scientific standards in order to measur

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Publication Date
Tue Jul 01 2014
Journal Name
International Journal Of Artificial Intelligence And Mechatronics
Machining Polylines and Ellipses using Three-Axis CNC Milling Machine
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CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance
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Publication Date
Sun Mar 31 2024
Journal Name
قضايا سياسية
The Iraqi Woman in the Face of Climate Change: Challenges, Obstacles, and Empowerment Strategies
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استهدف البحث تشخيص وتحليل الاسباب التي تجعل المرأة العراقية أكثر تأثراً من الرجل بعوامل التغيرات المناخية، فضلاً عن زيادة الوعي بقضية المرأة في هذا المجال، لأن موضوع دمجها في صياغة السياسات والاستراتيجيات المتعلقة بالتغير المناخي أصبح قضية عالمية، ويحتل مرتبة متقدمة في مؤشرات تحقيق أهداف التنمية المستدامة، وأستخدمت الباحثة المنهج الوصفي والتحليلي والاحصائي في تحليل محاور البحث، وتوصل البحث الى إستن

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