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Experimental influence assessments of water drive and gas breakthrough through the CO2-assisted gravity drainage process in reservoirs with strong aquifers
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Mature oil reservoirs surrounded with strong edge and bottom water drive aquifers experience pressure depletion and water coning/cresting. This laboratory research investigated the effects of bottom water drive and gas breakthrough on immiscible CO2-Assisted Gravity Drainage (CO2-AGD), focusing on substantial bottom water drive. The CO2-AGD method vertically separates the injected CO2 to formulate a gas cap and Oil. Visual experimental evaluation of CO2-AGD process performance was performed using a Hele-Shaw model. Water-wet sand was used for the experiments. The gas used for injection was pure CO2, and the “oleic” phase was n-decane with a negative spreading coefficient. The aqueous phase was deionized water. To evaluate the feasibility of the CO2-AGD process without any bottom water drives, it was first used. The experimental results demonstrated that existence of bottom water drive affected oil recoveries due to pressure support. Oil recovery before gas breakthrough increases proportionally with bottom water drive intensity. The gas breakthrough time recoveries for CO2-AGD1, CO2-AGD2, and CO2-AGD3 runs were 38.68%, 50.70%, and 60.85% of OOIP. The pressure gradient along the physical model decreases as bottom water drive intensity increases. The CO2-AGD approach delayed gas breakout by 72 min. As aquifer strength increases, gas breakthrough is delayed. In the three CO2-AGD runs and after breakthrough occurrence, the injector-producer pressure difference decreased due to the residual heads of oil and water columns above the horizontal well. As long as oil and water exist in the model, the pressure differential will not be zero, and the relative permeability and capillary trapping also control this phenomenon. Finally, it was demonstrated that there is a direct correlation between the strength of the aquifer and the oil recovery factor. The strength of the aquifer positively affects the oil recovery at breakthrough and the ultimate oil recovery.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Removal of Cadmium from Simulated Wastewaters Using a Fixed Bed Bio-electrochemical Reactor
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In this research, the removal of cadmium (Cd) from simulated wastewater was investigated by using a fixed bed bio-electrochemical reactor. The effects of the main controlling factors on the performance of the removal process such as applied cell voltage, initial Cd concentration, pH of the catholyte, and the mesh number of the cathode were investigated. The results showed that the applied cell voltage had the main impact on the removal efficiency of cadmium where increasing the applied voltage led to higher removal efficiency. Meanwhile increasing the applied voltage was found to be given lower current efficiency and higher energy consumption.  No significant effect of initial Cd concentration on the removal efficiency of cadmium b

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Engineering
Fabrication Of TiO2 , V2O5 Thin Film (Super Hydrophobic Surface )By Powder Coating Technique
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In this research, deposition of titanium oxide (TiO2) and vanadium oxide (V2O5) thin film  in different mixing percentage  (0, 25 ,50, 75 and100)%   on the substrate of glass .The coating thickness was ( 50 nm  ).

In this research contact angle was measured and the effect of weather conditions. Results showed that the value of the contact angle of the prepared films reached its highest value at 50% (TiO2+V2O5) was 160º.

The results showed that the optical transmittance of TiO2 and V2O5 thin film decrease with increasing the deposition angle and decrease with increasing V2O5 pro

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Publication Date
Tue Dec 03 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
New adaptive satellite image classification technique for al Habbinya region west of Iraq
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Publication Date
Tue Oct 05 2010
Journal Name
Journal Of College Of Education For Women
Conversation Analysis of Forum: a Selected Text from Paul S. Kemp Online Journal
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Language as a means of communication has long been the concern of many conversation analysts in their studies such as: Sacks et al. (1974), Schegloff et al. (1977), Duncan (1972), Grice (1975) and Burton (1980). Burton has attempted analyzing the first ten transitions of the play “The Dumb Waiter” for mere a presentation of her approach. This paper aims at analyzing the conversational structure of forum on the subject of literary fiction and genre fiction by applying Burton’s model (1980) of analysis to answer the question to what extent this model is applicable in analyzing the presented text. The findings of the investigation have proved the applicability of the structure of conversation formulated by Burton (1980) in her model wit

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Theoretical Studies of Sum Optical Properties for InAs (001) by Surface Differential Reflectivity
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The real and imaginary part of complex dielectric constant for InAs(001) by adsorption of oxsagen atoms has been calculated, using numerical analysis method (non-linear least square fitting). As a result a mathematical model built-up and the final result show a fairly good agreement with other genuine published works.

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An exploratory study of history-based test case prioritization techniques on different datasets
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In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement

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