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Prediction of Ryznar Index for the treated water from WTPs on Al-Karakh side of Baghdad City using Artificial Neural Network (ANN) technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

Publication Date
Wed Jul 08 2020
Journal Name
Plant Archives
ISOLATION AND DIAGNOSIS OF SOME CANDIDA SPECIES FROM SOME BAGHDAD CITY HOSPITALS WITH PCR TECHNIQUE AND EVALUATION OFTHE EFFECTIVENESS OF SOME ANTIFUNGALS
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The current study aimed to isolate and diagnose Candida spp yeasts that cause candidiasis with a PCR device from patients reviewed for some hospitals in Baghdad city and by 190 samples, the study recorded 123 isolates and the total percentage of infection was 64.7% .Samples were taken from different clinical cases of the vagina, blood and mouth and the Candida spp were (70.37%, 41.26%, 86.95%) respectively. Five types of yeasts were isolated and diagnosed, namely C. albicans, C. tropicalis, C. parapsilosis, C. krusei and C.glabarta. They were confirmed by PCR device and the most notable were yeast C. albicans, where 91 isolates were found, 73.98%, while the lowest infection was recorded. C.glabartawith 3 isolates, at 2.43%, significant diff

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Monitoring Vegetation Area in Baghdad Using Normalized Difference Vegetation Index
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       Vegetation monitoring is considered an important application in remote sensing task due to variation of vegetation types and their distribution. The vegetation concentration around the Earth is increase in 5% in 2000 according to NASA monitoring. This increase is due to the Indian vegetable programs. In this research, the vegetation monitoring in Baghdad city was done using Normalized Difference Vegetation Index (NDVI) for temporal Landsat satellite images (Landsat 5 TM& Landsat 8 OIL). These images had been used and utilize in different times during the period from 2000, 2010, 2015 & 2017. The outcomes of the study demonstrate that a change in the vegetation Cover (VC) in Baghdad city. (NDVI) generally shows a

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Publication Date
Sat Sep 01 2018
Journal Name
Water Resources
Carcinogenic Risk Assessment of Trihalomethanes in Major Drinking Water Sources of Baghdad City
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
The study of water quality changes using GIS and remote sensing for Tigris River through Salah Al-Din province, Iraq
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The most significant water supply, which is the basis of agriculture, industry and human and wildlife needs, is the river. In order to determine its suitability for drinking purposes, this study aims to measure the Water Quality Index (WQI) of the Tigris River in the Salah Al-Din Province (center of Tikrit), north of Baghdad. For ten (9) physio-chemical parameters, namely turbidity, total suspended sediments, PH, electrical conductivity, total dissolved solids, alkalinity, chloride, nitrogen as nitrate, sulphate, and then transported for examination to the laboratory, water samples were collected from 13 locations along the Tigris river. Using the weighted arithmetic index method, the WQI was measured and found to be 105,87 in up-stream, wh

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Minimization of Toxic Ions in Waste Water Using Emulsion Liquid Membrane Technique
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In the present study, the removal of zinc from synthetic waste water using emulsion liquid membrane extraction technique was investigated. Synthetic surfactant solution is used as the emulsifying agent. Diphenylthiocarbazon (ditizone) was used as the extracting agent dissolved in carbon tetrachloride as the organic solvent and sulfuric acid is used as the stripping agent. The parameters that influence the extraction percentage of Zn+2 were studied. These are the ratio of volume of organic solvent to volume of aqueous feed (0.5-4), ratio of volume of surfactant solution to volume of aqueous feed (0.2-1.6), pH of the aqueous feed solution (5-10), mixing intensity (100-1000) rpm, concentration of extracting agent (20-400) ppm, surfactant co

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of Educational And Psychological Researches
The Factorial Structure of The Emotional Intelligence Scale to Bar-On Applied on Students from Preparatory School in Baghdad City.
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The aim of the study was to know the factors analysis of scale Bar-On & Parker, post analysis is found fourteen factors for the first degree of the scale. Also we extracted five factors from the second degree.

  The scale consists of (60) items , applied on sample of (200) students (Male &Female ) age (15-18) years randomly chosen from preparatory schools . The scale unveiled satis factors  validity and reliability. An others aims is to low the  emotional  Intelligence level and  know the difference of statistical in sex , age variable and the specialization variable .The result was no difference of statistical in sex and specialization variable , but the difference appear

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