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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
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Spectrophotometric and Spectrofluorimetric Determination of Terazosin in Tablets by Eosin Y
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Simple, sensitive and accurate two methods were described for the determination of terazosin. The spectrophotometric method (A) is based on measuring the spectral absorption of the ion-pair complex formed between terazosin with eosin Y in the acetate buffer medium pH 3 at 545 nm. Method (B) is based on the quantitative quenching effect of terazosin on the native fluorescence of Eosin Y at the pH 3. The quenching of the fluorescence of Eosin Y was measured at 556 nm after excitation at 345 nm. The two methods obeyed Beer’s law over the concentration ranges of 0.1-8 and 0.05-7 µg/mL for method A and B respectively. Both methods succeeded in the determination of terazosin in its tablets

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Improving Shear Strength of Soft Clay by Using Torn Belts Chips
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Random throwing of industrial waste has a significant impact on the environment unless it takes into account the conditions of engineered destroying and/or re-used. Taking the advantage of re-using waste materials in engineering projects represents a well-planned project in order to resolve a lot of engineering problems for some difficult soils. The objective of this study was to evaluate the capability and effects of Rubber Shreds (RS) from scrap torn belts towards improving the shear strength of soft clay. A direct shear tests were conducted on soft clay-RS mixture. The following parameters were investigated to study the influence of RS content, water content, normal stress, and dilation ratio. From experimental test results it was fou

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Deep Reinforcement Learning: Bridging Learning and Control in Intelligent Systems
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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Determination Of The Efficient Production Plans For Al-Shaheed Public Company By Using Tatget Motad Model Under Risk And Uncertainty
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The research aims to derive the efficient industrial plans for Al – shaheed public company under risk by using Target MOTAD as a linear alternative  model for the quadratic programming models.

The results showed that there had been a sort of (trade- off) between risk and the expected gross margins. And if the studied company strives to get high gross margin, it should tolerate risk and vice versa. So the management  of Al- Shaheed Company to be invited to apply the suitable procedures in the production process, in order to get efficient plans that improves it's  performance .

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Evaluation of direct withholding tax procedures as a tool to increase tax proceeds : applied research in the General Tax Authority / Direct Deduction Department
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The research aims to evaluate the direct deduction department’s procedures for the process of collecting income tax using the direct deduction method for state departments and the public sector in light of direct deduction tax instructions No. (1) of 2007 and Income Tax Law No. (113) of 1982 (amended) through Giving a clear idea of ​​the reality of tax collection procedures because this type of tax is one of great importance because it contributes to the provision of financial revenues to the state to finance its expenses and direct the economy towards achieving its social, economic and political goals. The researcher makes comparisons between the procedures of the General Tax Authority in collecting the tax and what was approved b

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Real Time Wireless Monitoring and Controlling of 3-D Single Point Incremental Tool
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Maintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the

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