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Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
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Publication Date
Fri Dec 23 2022
Journal Name
Innovative Infrastructure Solutions
Experimental modeling of a single pile in liquefiable soil under the effect of coupled static-dynamic loads
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In this work, a single pile is physically modeled and embedded in an upper liquefiable loose sand layer overlying a non-liquefiable dense layer. A laminar soil container is adopted to simulate the coupled static-dynamic loading pile response during earthquake motions: Ali Algharbi, Halabjah, El-Centro, and Kobe earthquakes. During seismic events with combined loading, the rotation along the pile, the lateral and vertical displacements at the pile head as well as the pore pressure ratio in loose sandy soil were assessed. According to the experimental findings, combined loading that ranged from 50 to 100% of axial load would alter the pile reaction by reducing the pile head peak ground acceleration, rotation of the pile, and lateral displacem

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Black Carbon and Alumina Nanofluid on Thermal and Dynamic Efficiency in Upward Spraying Cooling Tower
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In cooling water systems, cooling towers play a critical role in removing heat from the water. Cooling water systems are commonly used in industry to dispose the waste heat. An upward spray cooling water systems was especially designed and investigated in this work. The effect of two nanofluids (Al2O3/ water, black carbon /water) on velocity and temperature distributions along reverse spray cooling tower at various concentrations (0.02, 0.08, 0.1, 0.15, and 0.2 wt.%) were investigated, beside the effect of the inlet water temperature (35 ,40, and 45 ͦ C) and water to air flow ratio (L/G) of 0.5, 0.75, and 1.  The best thermal performance was found when the working solution contained 0.1 wt.% for each of Al2

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Publication Date
Mon Jan 01 2024
Journal Name
Scripta Medica
The value of dynamic contrast-enhanced MRI and diffusion-weighted sequence in the evaluation of endometrial lesions
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Background/Aim: Endometrial abnormalities represent a diagnostic challenge due to overlapping imaging features with normal endometrium. Aim of this study was to assess accuracy of dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging (MRI) in evaluation of endometrial lesions in comparison with T2 and to assess local staging validity and degree of myometrial invasion in malignancy. Methods: Forty patients with abnormal vaginal bleeding or sonographic thickened endometrial were recruited. MRI examination of pelvis was per-formed using 1.5 T scanner with a pelvic array coil. Conventional T1-and T2, dynamic contrast-enhanced (DCE) sequences and diffusion-weighted image (DWI) were performed. Results: Mean age of pa

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Applied Geophysics
Predicting dynamic shear wave slowness from well logs using machine learning methods in the Mishrif Reservoir, Iraq
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Publication Date
Fri Feb 19 2016
Journal Name
International Journal Of Pure And Applied Mathematics
THE ROLE OF DYNAMIC PROGRAMMING IN THE DISTRIBUTION OF INVESTMENT ALLOCATIONS BETWEEN PRODUCTION LINES WITH AN APPLICATION
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At present, the ability to promote national economy by adjusting to political, economic, and technological variables is one of the largest challenges faced by organization productivity. This challenge prompts changes in structure and line productivity, given that cash has not been invested. Thus, the management searches for investment opportunities that have achieved the optimum value of the annual increases in total output value of the production line workers in the laboratory. Therefore, the application of dynamic programming model is adopted in this study by addressing the division of investment expenditures to cope with market-dumping policy and to strive non-stop production at work.

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Artificial Neural Networks Modeling of Total Dissolved Solid in the Selected Locations on Tigris River, Iraq
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge

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Publication Date
Sat Jun 30 2018
Journal Name
Science International
WORK STRESS AND ITS RELATION TO COGNITIVE FAILURES AMONG ADMINISTRATORS OF UNIVERSITY LECTURERS
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This paper aimed to investigate the relationship between work stress and cognitive failures among administrators of university professors and included a sample by searching from (474) teachers’ administrators and those who obtaining master degree or doctorate. Work stress scale was used, which is prepared by Amina Boashiri supporting by that, a measure of cognitive failures has also been used which is prepared by Khamis Shaeal Al Badri. In order to obtain the results statistical methods were used including (one-sample t-test, Pearson correlation coefficient) results indicated a high level of stress Work stress and high level of cognitive failures among professors as administrators, and also there is a positive correlation, as well as stat

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