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The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.</p>
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improving Wear Properties of 392 Al Alloy Using Centrifugal Casting
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The microstructure and wear properties of 392 Al alloy with different Mg contents were studied using centrifugal casting. All melted alloys were heated to 800 ºC and poured into the preheated centrifugal casting mold (200-250 ºC) at different mould rotational speeds (1500, 1900 and 2300 r.p.m).  It is clear from the results obtained that wear rate was dependent on the Mg content, applied load and mould rotational speed. Furthermore, wear test showed that the minimum wear rate was found in the inner layer of produced rings at mould rotational speed of 1900 r.p.m and Mg content of 5%.

 

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Publication Date
Wed Oct 05 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
Biosorption of Pollutants in Diyala River by Using Irrigated Vegetables
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In the absence of environmental regulation, food stays to be contaminated with heavy metals, which is becoming a big worry for human health. The present research focusses on the environmental and health effects of irrigating a number of crops grown in the soils surrounding the Al-Rustamia old plant using treated wastewater generated by the plant. The physicochemical properties, alkalinity, and electrical conductivity of the samples were evaluated, and vegetable samples were tested for Cd, Pb, Ni, and Zn, levels, and even the transfer factor (TF) from soils to crops and crop and multi-targeted risk, daily intake (DIM) of metals, and health risk index (HRI) was calculated. The findings found that the average contents of Zn, Pb, Ni, and Cd in

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Two Stage Evaporative Cooling of Residential Building Using Geothermal Energy
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The weather of Iraq has longer summer season compared with other countries. The ambient temperature during this season reaches over 50 OC which makes the evaporative cooling system suitable for this climate. In present work, the two-stage evaporative cooling system is studied. The first stage is indirect evaporative cooling (IEC) represented by two heat exchangers with the groundwater flow rate (5 L/min). The second stage is direct evaporative cooling (DEC) which represents three pads with groundwater flow rates of (4.5 L/min). The experimental work was conducted in July, August, September, and October in Baghdad. Results showed that overall evaporative efficiency of the system (two coils with three pads each

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity.

Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Stimulation of Macrophage Cells Against Cutaneous Leishmaniasis Using Silver Nanoparticles
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Cutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production.  This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Biosorption of Methylene Blue from Aqueous Solution Using Mixed Algae
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A mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 25

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
Bioremediation of Petroleum Hydrocarbons Contaminated Soil using Bio piles System
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This study was focused on biotreatment of soil which polluted by petroleum compounds (Diesel) which caused serious environmental problems. One of the most effective and promising ways to treat diesel-contaminated soil is bioremediation. It is a choice that offers the potential to destroy harmful pollutants using biological activity. Four bacterial strains were isolated from diesel contaminated soil samples. The isolates were identified by the Vitek 2 system, as Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae. The potential of biological surfactant production was tested using the Sigma 703D stand-alone tensiometer showed that these isolates are biological surfactant producers. The bet

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Publication Date
Thu Feb 01 2024
Journal Name
Ain Shams Engineering Journal
Performance enhancement of high degree Charlier polynomials using multithreaded algorithm
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