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Fabrication and Characterization of Nanofibers Membranes using Electrospinning Technology for Oil Removal
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Oily wastewater is one of the most challenging streams to deal with especially if the oil exists in emulsified form. In this study, electrospinning method was used to prepare nanofiberous polyvinylidene fluoride (PVDF) membranes and study their performance in oil removal. Graphene particles were embedded in the electrospun PVDF membrane to enhance the efficiency of the membranes. The prepared membranes were characterized using a scanning electron microscopy (SEM) to verify the graphene stabilization on the surface of the membrane homogeneously; while FTIR was used to detect the functional groups on the membrane surface. The membrane wettability was assessed by measuring the contact angle. The PVDF and PVDF / Graphene membranes efficiency was tested in separation of emulsified oil from aqueous solutions. The results showed that PVDF-Graphene nanofiber membrane exhibited better performance than the plain PVDF nanofiber membrane with average water flux of 210 and 180 L.m-2.h-1, respectively. Both membranes showed high oil rejection with more than 98%.

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Publication Date
Wed Jun 28 2023
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PREPARATION OF A COMBINATION OF NANO- MEDICINAL PLANTS AS ANTIOXIDANTS AND MICROORGANISMS: PREPARATION OF A COMBINATION OF NANO- MEDICINAL PLANTS AS ANTIOXIDANTS AND MICROORGANISMS
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ABSTRACT

            The controversy is currently revolving around industrial additives, including antioxidants, their negative effects on consumer health and the emergence of various and various diseases, which led scientists and researchers to intensify most studies on natural antioxidants and their synthesis from medicinal plants mentioned in ancient medicine and in divine books as potential antioxidants of increasing importance. Therefore, this study was designed to synthesize silver nitrate particles from plant leaf extracts (Figs, Olives, and Moringa) and study their effect on bacterial inhibition of each of the undesirable Coliform bacteria (E-Coli,

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Publication Date
Sun Dec 31 2017
Journal Name
College Of Islamic Sciences
Mask technique in the poem "Christ after the crucifixion" for Bder Shaker Al_Sayab
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Research summary

Perhaps the methods of mask that Arab poets resorted to in our time are due to the conditions of oppression and political and social repression that the Arab poet suffered from; So he strived to circumvent it, and it became a justification for hiding behind it. The research is available on a number of topics that lead to the definition of the mask technique and the beginning of its prevalence in Arabic literature after the Second World War, especially in recent decades by benefiting from historical stories, fairy tales and legends of all kinds. As well as defining the mask idiomatically and linguistically, and the beginning of its use in ancient religious rituals, and the special place it had in Greek plays. Poets

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation
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 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

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Publication Date
Wed Mar 20 2019
Journal Name
Al-khwarizmi Engineering Journal
Enhancement of Heat Exchanger Performance by Using Dimpled Tube
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The enhancement of heat exchanger performance was investigated using dimpled tubes tested at different Reynolds numbers, in the present work four types of dimpled tubes with a specified configuration manufactured, tested and then compared performance with the smooth tube and other passive techniques performance. Two dimpled arrangements along the tube were investigated, these are inline and staggered at constant pitch ratio X/d=4, the test results showed that Nusselts number (heat transfer) of the staggered array is higher than the inline array by 13%.  The effect of different depths of the dimple (14.5 mm and 18.5 mm) has been also investigated; a tube with large dimple diameter enhanced the Nusselts number by about 25% for the ran

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Publication Date
Mon Jan 01 2018
Journal Name
دراسات في آثار الوطن العربي
Chemistry technology in ancient Mesopotamia
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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Geological Journal
Geological Model for Mauddud Reservoir Khabaz Oil Field
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The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

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Publication Date
Tue Sep 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
New Viscosity Correlation for Different Iraqi Oil Fields
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Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting crude oil viscosity. However, these correlations are limited to predict the oil viscosity at specified conditions. In the present work, an extensive experimental data of oil viscosities collected from different samples of Iraqi oil reservoirs was applied to develop a new correlation to calculate the oil viscosity at various operating conditions either for dead, satura

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Publication Date
Tue Jan 01 2013
Journal Name
Communications And Network
Link and Cost Optimization of FTTH Network Implementation through GPON Technology
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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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