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Effect of nanoparticles on the interfacial tension of CO2-oil system at high pressure and temperature: An experimental approach
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In the recent decade, injection of nanoparticles (NPs) into underground formation as liquid nanodispersions has been suggested as a smart alternative for conventional methods in tertiary oil recovery projects from mature oil reservoirs. Such reservoirs, however, are strong candidates for carbon geo-sequestration (CGS) projects, and the presence of nanoparticles (NPs) after nanofluid-flooding can add more complexity to carbon geo-storage projects. Despite studies investigating CO2 injection and nanofluid-flooding for EOR projects, no information was reported about the potential synergistic effects of CO2 and NPs on enhanced oil recovery (EOR) and CGS concerning the interfacial tension (γ) of CO2-oil system. This study thus extensively investigates the effect of silica NPs on the γ of CO2/decane system at elevated pressure and temperature to recognise the potential impact of NPs-injection on the future CGS projects. To achieve this, a wide-ranging series of tests have been conducted to reveal the role of hydrophilic and hydrophobic silica NPs on γ of the CO2/oil system. n-decane was utilized as model oil and different amounts of NPs were mixed with the oil phase. Oil-NPs dispersions were formulated using an ultrasonic homogenizer. The γ of the CO2/oil system was measured at different pressures (0.1 to 20 MPa) and temperatures (25 to 70 °C) using a high-pressure temperature optical cell. The γ data were measured using the pendant drop technique via axisymmetric drop shape analysis (ADSA). The results showed that, generally, CO2/oil γ subjected mainly to pressure, temperature, and with less extent to NPs load in the oil phase. γ decreases with increased pressure until reaching a plateau where no more significant decrease in γ was observed. The γ trend with increased temperature, on the other hand, was more completed. No significant impact of temperature on γ was recorded with low pressure (≤ 5 MPa). Similarly, at relatively high pressure (≥ 25 MPa), only a slight variation of IFT with temperature change was recorded. However, for the pressure range from 5 – 25 MPa, IFT was increased remarkably with temperature. Furthermore, NPs in the oil phase exhibit a remarkable influence on IFT. In this context, the presence of hydrophilic silica NPs in the oil phase can significantly reduce the γ of the CO2/decane system. However, hydrophobic silica NPs showed less influence on IFT reduction. The outcomes of this work afford good understandings into applications of NP for EOR and CGS applications and help to de-risk CO2-geological storage projects.

Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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Publication Date
Wed Oct 10 2018
Journal Name
Al-kindy College Medical Journal
Recurrent Laryngeal Nerve Injury With Versus Without Nerve Identification In Different Thyroidectomy Procedures
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Background: The world health organization estimates that worldwide 2 billion people still have iodine deficiency Objectives: Is to make comparison between the effect of identification of recurrent laryngeal nerve (RLN) and non-identification of the nerve on incidence of recurrent laryngeal nerve injury (RLNI) in different thyroidectomy procedures.

Type of the study: cross –sectional study.

Methods: 132 patients with goiters underwent thyroidectomy .Identification of RLN visually by exposure were done for agroup of them and non-identification of the nerves for the other group. The outcomes of RLNI in the two groupsanalyzed statistically for the effect of

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
S-Coprime Submodules
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  In this paper, we introduce and study the concept of S-coprime submodules, where a proper submodule N of an R-module M is called S-coprime submodule if M N is S-coprime Rmodule. Many properties about this concept are investigated.

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamic Channel Assignment Using Neural Networks
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This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Semimaximal Submodules
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     Let R be a commutative ring with unity and an R-submodule N is called semimaximal if and only if

 the sufficient conditions of F-submodules to be semimaximal .Also the concepts of (simple , semisimple) F- submodules and quotient F- modules are  introduced and given some  properties .

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Publication Date
Fri Dec 30 2016
Journal Name
Al-kindy College Medical Journal
Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining
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Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment. Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors. Type of the study:A cross- secti

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Publication Date
Sun Mar 30 2025
Journal Name
Samarra Journal Of Engineering Science And Research
Proposed low Xilinx FPGA power consumption for recursive NOMA applied in optical visible light communication
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Today the NOMA has exponential growth in the use of Optical Visible Light Communication (OVLC) due to good features such as high spectral efficiency, low BER, and flexibility. Moreover, it creates a huge demand for electronic devices with high-speed processing and data rates, which leads to more FPGA power consumption. Therefore; it is a big challenge for scientists and researchers today to recover this problem by reducing the FPGA power and size of the devices. The subject matter of this article is producing an algorithm model to reduce the power consumption of (Field Programmable Gate Array) FPGA used in the design of the Non-Orthogonal Multiple Access (NOMA) techniques applied in (OVLC) systems combined with a blue laser. However, The po

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Publication Date
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
Energy Calculation for Excited Lithium Atom in Position Space
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The energy expectation values for Li and Li-like ions ( , and ) have been calculated and examined within the ground state and the excited state in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wave functions.

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