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Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Mon Sep 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Design of Cylinderical Ectrode Using Neural Network Modeling for Electrochemical Finishing
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The finishing operation of the electrochemical finishing technology (ECF) for tube of steel was investigated In this study. Experimental procedures included qualitative
and quantitative analyses for surface roughness and material removal. Qualitative analyses utilized finishing optimization of a specific specimen in various design and operating conditions; value of gap from 0.2 to 10mm, flow rate of electrolytes from 5 to 15liter/min, finishing time from 1 to 4min and the applied voltage from 6 to 12v, to find out the value of surface roughness and material removal at each electrochemical state. From the measured material removal for each process state was used to verify the relationship with finishing time of work piece. Electrochemi

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Thu Mar 06 2025
Journal Name
Aip Conference Proceedings
Solving 5th order nonlinear 4D-PDEs using efficient design of neural network
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study the Effect of Manganese Ion Doping on the Size- Strain of SnO2 nanoparticles Using X-Ray Diffraction Data
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In this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nano

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Publication Date
Mon Nov 30 2020
Journal Name
Iraqi Geological Journal
EXPERIMENTAL STUDY OF MICRO SILICA BEHAVIOR AND ITS EFFECT ON IRAQI CEMENT PERFORMANCE BY USING X-RAY FLUORESCENCE ANALYSIS
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The cement slurry is a mixture of cement, water and additives which is established at the surface for injecting inside hole. The compressive strength is considered the most important properties of slurry for testing the slurry reliability and is the ability of slurry to resist deformation and formation fluids. Compressive strength is governed by the sort of raw materials that include additives, cement structure, and exposure circumstances. In this work, we use micro silica like pozzolanic materials. Silica fume is very fine noncrystalline substantial. Silica fume can be utilized like material for supplemental cementations for increasing the compressive strength and durability of cement. Silica fume has very fine particles size less

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Publication Date
Fri May 20 2022
Journal Name
Al-kindy College Medical Journal
Potential Influence of Parasitic Diseases as Protective Agents from Infection with Pandemic COVID-19
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Parasitic diseases can affect infection with COVID-19 obviously, as protective agents, or by reducing severity of this viral infection. This current review mentions the common symptoms between human parasites and symptoms of COVID-19, and explains the mechanism actions of parasites, which may prevent or reduce severity of this viral infection. Pre-existing parasitic infections provide prohibition against pathogenicity of COVID-19, by altering the balance of gut microbiota that can vary the immune response to this virus infection.  

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Wed Jul 10 2024
Journal Name
The Open Neuroimaging Journal
The Efficacy of Bedside Chest Ultrasound in the Detection of Traumatic Pneumothorax
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Background

Chest X-rays have long been used to diagnose pneumothorax. In trauma patients, chest ultrasonography combined with chest CT may be a safer, faster, and more accurate approach. This could lead to better and quicker management of traumatic pneumothorax, as well as enhanced patient safety and clinical results.

Aim

The purpose of this study was to assess the efficacy and utility of bedside US chest in identifying traumatic pneumothorax and also its capacity to estimate the extent of the lesion in comparison to the gold standard modality chest computed tomography.

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Spiking Neural Network in Precision Agriculture
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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