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French Language in Iraq: Study of the Relationship between University Education and Social Activities (The Case of the University of Baghdad)
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Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Sosyal Bilimler Dergisi | Volume: 48 Issue: 2

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Publication Date
Tue Jun 30 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Immiscible CO2-Assisted Gravity Drainage Process for Enhancing Oil Recovery in Bottom Water Drive reservoir
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The CO2-Assisted Gravity Drainage process (GAGD) has been introduced to become one of the mostinfluential process to enhance oil recovery (EOR) methods in both secondary and tertiary recovery through immiscibleand miscible mode. Its advantages came from the ability of this process to provide gravity-stable oil displacement forenhancing oil recovery. Vertical injectors for CO2 gas have been placed at the crest of the pay zone to form a gas capwhich drain the oil towards the horizontal producing oil wells located above the oil-water-contact. The advantage ofhorizontal well is to provide big drainage area and small pressure drawdown due to the long penetration. Manysimulation and physical models of CO2-AGD process have been implemented

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Publication Date
Sun Jun 27 2021
Journal Name
Journal Of The College Of Education For Women
Persuasive Strategies in WHO COVID-19 Virtual Press Conferences: فراس مجيت حماد , جمعة قادر حسين
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Persuasion is an indispensable skill in everyday life; that is why, it has aroused researchers’ interest. This study aims to investigate the most frequently used persuasive strategies in texting WHO COVID-19 Virtual Press Conferences and explore how these strategies are employed to achieve persuasive messages.To this end, a text of WHO COVID-19 Virtual Press Conferences has been chosen randomly to be analyzed based on Dillard and Shen’s (2013) “Persuasive strategies in Health Campaigns”. A qualitative method has been adopted in analyzing the selected data to investigate the credibility and validity of the persuasive strategies used in such a domain. Findings have shown that most of the persuasive appeals based on the adopted mode

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Highly-charged EDTA-2Na salt as a novel draw solution in pressure-retarded Osmosis process
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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
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Tue Jan 15 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Natural Convective Heat Transfer in an Inclined Open Porous Cavity with Non-Uniformly Heated Wall
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Theoretical and experimental investigations of free convection through a cubic cavity with sinusoidal heat flux at bottom wall, the top wall is exposed to an outside ambient while the other walls are adiabatic saturated in porous medium had been approved in the present work. The range of Rayleigh number was and Darcy number values were . The theoretical part involved a numerical solution while the experimental part included a set of tests carried out to study the free convection heat transfer in a porous media (glass beads) for sinusoidal heat flux boundary condition. The investigation enclosed values of Rayleigh number (5845.6, 8801, 9456, 15034, 19188 and 22148) and angles of inclinations (0, 15, 30, 45 and 60 degree). The numerical an

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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