In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
The present work evaluated the differences in mechanical properties of two athletic prosthetic feet samples when subjected to impact while running. Two feet samples designated as design A and B were manufactured using layers of different orientations of woven glass fiber reinforced with unsaturated polyester resin as bonding epoxy. The samples’ layers were fabricated with hand lay-up method. A theoretical study was carried out to calculate the mechanical properties of the composite material used in feet manufacturing, then experimental load-deflection test was applied at 0 degree position and 25 degree dorsiflexion feet position and impact test were applied for both feet designs to observe the behavior
... Show MoreThis paper proposed a theoretical treatment to study underwater wireless optical communications (UWOC) system with different modulation schemes by multiple input-multiple output (MIMO) technology in coastal water. MIMO technology provides high-speed data rates with longer distance link. This technique employed to assess the system by BER, Q. factor and data rate under coastal water types. The reliability of the system is examined by the techniques of 1Tx/1Rx, 2Tx/2Rx, 3Tx/3Rx and 4Tx/4Rx. The results shows the proposed technique by MIMO can get the better performance compared with the other techniques in terms of BER. Theoretical results were obtained to compare between PIN and APD
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreThe energy expectation values for Li and Li-like ions ( , and ) have been calculated and examined within the ground state and the excited state in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wave functions.
Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col
... Show MoreThe detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed
... Show MoreIn the present study, advanced oxidation process / heterogeneous photocatalytic process (UV/TiO2/Fenton) system was investigated to the treatment of oily wastewater. The present study was conducted to evaluate the effect of hydrogen peroxide concentration H2O2, initial amount of the iron catalyst Fe+2, pH, temperature, amount of TiO2 and the concentration of oil in the wastewater. The removal efficiency for the system UV/TiO2/Fenton at optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=5, temperature =30oC, TiO2=75mg/L) for 1000mg/L load was found to be 77%.
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