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Ultrafiltration and Reverse Osmosis Membranes for Treating Wastewater Effluent from Gas Turbine Power Plants using the Statistical Method of Taguchi
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A study on the treatment and reuse of oily wastewater generated from the process of fuel oil treatment of gas turbine power plant was performed. The feasibility of using hollow fiber ultrafiltration (UF) membrane and reverse osmosis (RO) membrane type polyamide thin-film composite in a pilot plant was investigated. Three different variables: pressure (0.5, 1, 1.5 and 2 bars), oil content (10, 20, 30 and 40 ppm), and temperature (15, 20, 30 and 40 ᵒC) were employed in the UF process while TDS was kept constant at 150 ppm. Four different variables: pressure (5, 6, 7 and 8 bar), oil content (2.5, 5, 7.5 and 10 ppm), total dissolved solids (TDS) (100, 200,300 and 400 ppm), and temperature (15, 20, 30 and 40 ᵒC) were manipulated with the help of statistical method of Taguchi in the RO process. Analysis of variable (ANOVA) and optimum condition was investigated. The study shows that pressure has the greatest impact on the flux of UF process, while it was temperature for RO process. It was noticed that more than 99% oil removal can be achieved and flux of 580 L/m2.hr by UF process and that the fouling mechanism of UF process follows the cake/gel layer filtration model. It was concluded that 100% removal of oil content can be achieved along with 99% for the TDS rejection and flux of 76 L/m2.hr by RO process. The result shows fouling in RO process follows the standard pore blocking model. Process optimization was conducted with confirmation test. It was concluded that the observed values are within ±5% of that the predicted which reflects a strong representative model. The treated wastewater has the characteristics of that used as fresh water and it can be reused to the process to reduce the operation cost.

 

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Rationalization the costs and improve seed quality under the application of biotechnology: An Applied Research in Ministry of Agriculture - the Directorate of Inspection &Certification of Seeds
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The importance of this research has been to rationalize the cost of producing maize seeds through the followers of modern techniques and methods in agricultural activities such as genetic engineering for the purpose of increasing production efficiency of maize seeds as well as the importance of calculating seed cost rationalization through the ABC system and thus rationalizing government spending. The research is based on a single hypothesis that the use of genetic engineering on corn seeds works to:increase production efficiency of seeds and savings in agricultural inputs, calculation of rationalization through the cost system on the basis of activity ABC The research reached a number of conclus

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Strategic Command and its role in activating the Organisational performance analytical study of the views of the heads of academic departments at General Authority of groundwater.
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Abstract

The research aims to identify the strategic leadership and its role in activating the Organisational Performance, which is an analytical study of the views of the heads of scientific departments at General Authority of groundwater researcher's quest focused towards building a theoretical framework suitable for strategic leadership and performance Organisational and itُs dimensions.To achieve the aims of the research is designed to identify the researcher included (35) items to collect the raw data from the research sample consisting of 33 of the heads of departments. Data was collected by questionnaire, field visits, interviews and some official documents to complete the search data. It has also been used a numb

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Publication Date
Fri May 01 2020
Journal Name
Applied Thermal Engineering
Thermal performance of a flat-plate solar collector using aqueous colloidal dispersions of graphene nanoplatelets with different specific surface areas
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The effects of using aqueous nanofluids containing covalently functionalized graphene nanoplatelets with triethanolamine (TEA-GNPs) as novel working fluids on the thermal performance of a flat-plate solar collector (FPSC) have been investigated. Water-based nanofluids with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% of TEA-GNPs with specific surface areas of 300, 500, and 750 m2/g were prepared. An experimental setup was designed and built and a simulation program using MATLAB was developed. Experimental tests were performed using inlet fluid temperatures of 30, 40, and 50 °C; flow rates of 0.6, 1.0, and 1.4 kg/min; and heat flux intensities of 600, 800, and 1000 W/m2. The FPSC’s efficiency increased as the flow rate and hea

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Publication Date
Mon Mar 15 2004
Journal Name
Sciences Journal Of Physical Education
Setting standards for some offensive skill abilities according to basketball playing positions for Iraqi youth
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لا يزال المهتمون بلعبة كرة السلة يبحثون عن إيجاد الوسائل الأكثر أهمية وصولاً إلى ما تطمح إليه الدول لتحقيق افضل المستويات في نواحي اللعبة كافة من خلال التغلب على المعوقات التي تحول دون تقدمها إلى الأمام بالدراسة والبحث. ومن هذا المنطلق انصب البحث في ضرورة معالجة القصور الناتج عن عدم وجود المعايير ذات العلاقة باختبارات قدرات اللاعبين وعلى وفق مراكز اللعب ولا سيما المهارية الهجومية مما شكل ذلك ضعفاً في أعداد و

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Analysis Based on Well Logging Data for Tight Carbonate Reservoir: The SADI Formation Case in Halfaya Oil Field
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Carbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
The Numerical Technique Based on Shifted Jacobi-Gauss-Lobatto Polynomials for Solving Two Dimensional Multi-Space Fractional Bioheat Equations
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This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Spectroscopic Study for Resonance Effects on the Carbonyl Double Bond Order in Urea Schiff Bases Which Contain Conjugated System
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In this work we prepared some schiff bases by condensation urea and benzaldehyde or its derevative ( bromo benzaldehyde or hydroxy benzaldehyde ) as ( 1 : 1 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A1 , B1 , C1 , D1 , E1 , F1 , G1 ) and ( 1 : 2 ) mole ( urea : benzaldehyde or its substitution ) to prepare compounds ( A2 , B2 , C2 , D2 , E1 , F2 , G2 ) . The prepared compounds identified spectroscopic by infrared spectroscopy FT-IR and Thin layer chromotography T.L.C . The force constant calculated from the wave number for the carbonyl stretching from FT-IR chart and by using the following equation K = 4?2C2?'2? The change in double bond order for carbonyl deteremined in according with some past re

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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