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Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Chemical Engineering
Phosphorus Removal from Wastewater Using Oven-Dried Alum Sludge
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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Removal of Cadmium from Industrial Wastewater using Electrocoagulation Process
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Cadmium is one of the heavy metal found in the wastewater of many industries. The electrocoagulation offers many advantages for the removal of cadmium over other methods. So the removal of cadmium from wastewater by using electrocoagulation was studied to investigate the effect of operating parameters on the removal efficiency. The studied parameters were the initial pH, initial concentration, and applied voltage. The study experiments were conducted in a batch reactor with  with two pairs of aluminum electrodes with dimension  and 2mm in thick with 1.5 cm space between them. The optimum removal was obtained at pH =7, initial concentration = 50 mg/L, and applied voltage = 20 V and it was 90%.

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Structure dependence of gamma ray irradiation effects on polyurethane and epoxy resin studied by PAL technique
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Positron annihilation lifetime (PAL) technique has been employed to
study the microstructural changes of polyurethane (PU), EUXIT 101
and epoxy risen (EP), EUXIT 60 by Gamma-ray irradiation with the
dose range (95.76 - 957.6) kGy. The size of the free volume hole and
their fraction in PU and EP were determined from ortho-positronium
lifetime component and its intensity in the measured lifetime spectra.
The results show that the irradiation causes significant changes in the
free volume hole size (Vh) and the fractional free volume (Fh), and
thereby the microstructure of PU and EP. The results indicate that
the γ-dose increases the crystallinity in the amorphous regions of PU
and increas

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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
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
Tue Mar 02 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education
Deep understanding skills and their relationship to mathematical modelling among fifth grader
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Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Evaluation of D-Dimer in the diagnosis of suspected deep vein thrombosis
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Background: Deep vein thrombosis is a multi causal disease and its one of most common venous disorder, but only one quarter of the patients who have signs and symptoms of a clot in the vein actually have thrombosis and need treatment .The disease can be difficult to diagnose. Venous ultrasound in combination with clinical finding is accurate for venous thromboembolism, its costly because a large number of patients with suspicious signs and symptoms. Venography still the gold standard for venous thromboembolism but it is invasive. The D-dimer increasingly is being seen as valuable tool rolling out venous thromboembolism and sparing low risk patients for further workup.Objectives: this study has designed the role of D-dimer to confirm diag

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Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey of deepfakes in terms of deep learning and multimedia forensics
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Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Physics: Conference Series
An investigation into the implications of partial substitution of selenium with lead on the thermal properties for S<sub>60</sub>Se<sub>40-X</sub>Pb<sub>X</sub> Chalcogenide Compound
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Abstract<p>This study includes the manufacture of four ternary alloys represented S<sub>60</sub>Se<sub>40-X</sub>Pb<sub>X</sub> with weight ratios x = 0, 10, 20, and 30 by the melting point method. The components of each alloy were mixed separately, then placed in quartz ampoules and vacuumed out with a vacuum of roger that 10<sup>−4</sup> Torr. The ampule was heated in two stages to avoid sudden dissipation and precipitation of selenium on the inner mass of the quartz tube. The ampoule was gradually heated and kept at 450°C for approximately 4 hours followed by 950°C for 10 hours.at a rate of 10 degrees Celsius, the temperature of the electric furnace</p> ... Show More
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