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Stress Ratio Method to Predict Fracture Pressure Gradient in Southern Iraqi Deep Wells
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This research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertical effective stress are obtained for each well and used to calculate fracture pressure gradient. Similar equations are found for group of formations that calculate fracture pressure gradient and to find the most accurate correlation among them

Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Fri Jun 08 2018
Journal Name
Advances In Intelligent Systems And Computing
Improve Memory for Alzheimer Patient by Employing Mind Wave on Virtual Reality with Deep Learning
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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Wed Aug 05 2020
Journal Name
Advances In Structural Engineering
Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

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Publication Date
Wed Aug 05 2020
Journal Name
Advances In Civil Engineering
Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Numerical investigation on heat transfer enhancement and turbulent flow characteristics in a high aspect ratio rectangular duct roughened by intersecting ribs with inclined ribs
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In this study, the effect of intersecting ribs with inclined ribs on the heat transfer and flow characteristics of a high aspect ratio duct has been numerically investigated. The Relative roughness pitch (P/e) is 10 and the Reynolds number range from 35,700 to 72,800. ANSYS (Fluent-Workbench 18.0) software has been utilized to solve the Reynolds averaged Navier-Stokes (RANS) equations with the Standard k-ε turbulence model. Three ribbed models have been used in this study. Model 1 which is a just inclined ribs, Model 2 which has a single longitudinal rib at the center with inclined ribs and Model 3 which has two longitudinal ribs at the sides. The results showed that the heat transfer rate has been enhanced when the int

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
The slenderness ratio effect on the response of closed-end pipe piles in liquefied and non-liquefied soil layers under coupled static-seismic loading
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Abstract<p>This study presents the findings of a 3D finite element modeling on the performance of a single pile under various slenderness ratios (25, 50, 75, 100). These percentages were assigned to cover the most commonly configuration used in such kind of piles. The effect of the soil condition (dry and saturated) on the pile response was also investigated. The pile was modeled as a linear elastic, the surrounded dry soil layers were simulated by adopting a modified Mohr-Coulomb model, and the saturated soil layers were simulated by the modified UBCSAND model. The soil-pile interaction was represented by interface elements with a reduction factor (R) of 0.6 in the loose sand layer and 0.7 in t</p> ... Show More
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Publication Date
Wed Sep 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Genetic Polymorphism in TNF-α Promoter Region: Its Association with Severity and Susceptibility to Rheumatoid Arthritis in Iraqi Patients with Active Disease
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Objectives: To study the prevalence of rs1799964 (-1031 T/C) and rs361525 (- 238 G/A) SNPs and their effect on the disease activity, severity, and cytokines production in newly diagnosed Iraqi rheumatoid arthritis patients. Patients and Methods: sixty-three patients were diagnosed by a specialist physician while attending the rheumatology unit and twenty control participated. The inflammatory markers were measured and PCR amplification and sequencing were performed to demonstrate TNF-α SNPs. Results: Regarding (-1031 C/T) SNP, the TT genotype and allele C were significantly present in the controls, and the CT genotype was distributed significantly in the patients. The TT genotype was mostly distributed in the mild-moder

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Effect of Argon and oxygen pressure on Zn magnetron plasma produced by RF power supply
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In this work, the plasma parameters (electron temperature and
electron density) were determined by optical emission spectroscopy
(OES) produced by the RF magnetron Zn plasma produced by
oxygen and argon at different working pressure. The spectrum was
recorded by spectrometer supplied with CCD camera, computer and
NIST standard of neutral and ionic lines of Zn, argon and oxygen.
The effects of pressure on plasma parameters were studied and a
comparison between the two gasses was made.

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