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Prediction of Raw Water Turbidity at the Intakes of the Water Treatment Plants along Tigris River in Baghdad, Iraq using Frequency Analysis
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Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit.  The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al-Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-Wehda WTP Weibull distributions, was the best model. The best fitted distributions were used to forecast ten sets of monthly data for each plant that were compared with the observed data for years (2012-2014). The Kolmogorov-Smirnov test results indicated the capability of these models to produce data that has the same frequency distribution of the observed data. Moreover the frequency of occurrence of the observed and generated series in each plant indicated the capability of the model to produce results with frequency occurrence of probabilities of turbidity values > 50, 80, 100, 120, and 150 NTU.

 

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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Cytotoxic Activity of CuO NPs Prepared by PLAL Against Liver Cancer (Hep-G2) Cell Line and HdFn Cell Lines
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A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

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Publication Date
Fri Mar 10 2017
Journal Name
Superconductor Science And Technology
Conceptual designs of conduction cooled MgB<sub>2</sub> magnets for 1.5 and 3.0 T full body MRI systems
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Fri Nov 29 2019
Journal Name
Iraqi Journal Of Physics
CDD Study of Charge Density Distributions and Elastic Electron Scattering Cross Sections for some Stable Nuclei: Charge Density Distributions
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Publication Date
Sat Sep 01 2018
Journal Name
Iraqi Journal Of Science
Estimate Antimicrobial activity and Anti-biofilm formation of bark Cinnamomum zeylanicum on Klebsiella pneumoniae isolated from Urinary Tract Infections
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study of Antibiotic Resistance to Pseudomonas aeruginosa that Iisolate from Burns and Ggeneral Surgery from Al-Yarmouk Teaching Hospital
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     Pseudomonas aeruginosa is common gram negative rod – shaped bacterium, a species of considerable medical importance, P. aeruginosa is prototypical "multi drug resistant (MDR) Pathogen" that is recognised for its ubiquity, its intrinsically advanced antibiotic resistance mechanisms, and its associatation with serious illnesses – especially nosocomial infection such as ventilator – associated pneumonia and various sepsis syndromes. This study was conducted from March 2014 to July 2014, the patients were males and females. Total samples of 613 patients, selected from burns wards and general surgery wards, the samples were sending to teaching laboratories from the same hospital. The present study

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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
Addition of Some Primary and Secondary Amines to Graphene Oxide, and Studying Their Effect on Increasing its Electrical Properties
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Previously many properties of graphene oxide in the field of medicine, biological environment and in the field of energy have been studied. This diversity in properties is due to the possibility of modification on the composition of this Nano compound, where the Graphene oxide is capable of more modification via addition other functional groups on its surface or at the edges of the sheet. The reason for this modification possibility is that the Sp3 hybridization (tetrahedral structure) of the carbon atoms in graphene oxide, and it contains many oxygenic functional groups that are able to reac with other groups. In this research the effect of addition of some amine compounds on electrical properties of graphene oxide has been studied by the

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
ESTIMATION OF COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES WITH APPLICATIONS
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In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

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Publication Date
Fri Jul 12 2024
Journal Name
Biomass Conversion And Biorefinery
Chitosan-triphosphate/food grade algae/montmorillonite clay for adsorptive removal of methyl violet 2B dye removal: Behnken design optimization
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