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Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
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Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the reversibility of NP adsorption onto carbonate surfaces was measured using dynamic light scattering (DLS), scanning electron microscope (SEM) images, energy dispersive X-ray spectroscope (EDS), and atomic force microscope (AFM) measurement. Results show that the initial hydrophilicity of the NP and the carbonate rock surface can influence the NPs adsorption onto the rock surfaces. Typically, oppositely charged NP and rock surface are attracted to each other, forming a mono or multilayers of NPs on the rock. Operation conditions including pressure and temperature have shown minor influence on nano-treatment efficiency. Moreover, DLS measurement proved the impact of hydrophilicity on the stability and adsorption trend of NPs. This was also confirmed by SEM images. Further, AFM results indicated that a wide-ranging adsorption scenario of NPs on the carbonate surface exists. Similar results were obtained from the EDS measurements. This study thus gives the first insight into NPs adsorption onto carbonate surfaces at reservoirs conditions.

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Publication Date
Sat Sep 01 2018
Journal Name
2018 11th International Conference On Developments In Esystems Engineering (dese)
Natural Rivers Longitudinal Dispersion Coefficient Simulation Using Hybrid Soft Computing Model
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Publication Date
Wed Mar 16 2022
Journal Name
2022 Muthanna International Conference On Engineering Science And Technology (micest)
A hybrid feature selection technique using chi-square with genetic algorithm
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Publication Date
Thu Sep 13 2018
Journal Name
Baghdad Science Journal
Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks
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Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simula

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Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Gas sensing performance of Sol-gel grown NiO-doped Cr2O3 nanoparticles
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The sensors based on Nickel oxide doped chromic oxide (NiO: Cr2O3) nanoparticals were fabricated using thick-film screen printing of sol-gel grown powders. The structural, morphological investigations were carried out using XRD, AFM, and FESEM. Furthermore, the gas responsivity were evaluated towards the NH3 and NO2 gas. The NiO0.10: Cr2O3 nanoparticles exhibited excellent response of 95 % at 100oC and better selectivity towards NH3 with low response and recovery time as compared to pure Cr2O3 and can stand as reliable sensor element for NH3 sensor related applications.

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Publication Date
Wed Mar 01 2023
Journal Name
Iraqi Journal Of Physics
Photocatalytic Degradation of Methyl blue by TiO2 Nanoparticles Incorporated in Cement
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In this study, titanium dioxide (TiO2) nanoparticles incorporated with cement were synthesis by a simple casting method as a function concentration of TiO2 (0.2, 0.4, 0.8, 1, and 2 wt%). The prepared samples were characterized using the technique of Field Emission Scanning Electron Microscope (FESEM) and UV-Visible spectrophotometer, which was used to measure the adsorption spectra. The observed photocatalytic efficiency of TiO2 nanoparticles (NP) incorporated with cement was investigated by decomposing the dye methyl blue (MB) solution under sunlight irradiation. According to the slope, the value of the k constant at the best sample is 0.8wt%, k=0.8265 min-1. FESEM image of the TiO2

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Publication Date
Fri Feb 01 2019
Journal Name
Sci.int.(lahore)
TIME MANAGEMENT AND ITS RELATIONSHIP TO THE STAFF PERFORMANCE IN THE FACULTIES OF PHYSICAL EDUCATION AND SPORTS SCIENCES AT UNIVERSITY OF BAGHDAD
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The study aimed to identify the importance of time in the Faculties of Physical Education and Sports Sciences at the University of Baghdad, as well as to identify the relationship between time management and the level of staff functional performance. The research population consisted of the staff members who work in the Faculties of Physical Education and Sports Sciences for Girls in Al-Jadriya for the academic year 2017-2018. A random sample of 50 staff members from each faculty were selected, that is the total number was (100) staff members. The researchers identified the concept of time management and functional performance, after that a questionnaire consisting of (39) statements and (6) parts presented to a specialized group of experts

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