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Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
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In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss is a gathering of numerous issues for example rheology of mud), flow regime and the well geometry. An artificial neural network (ANN) that used in this effort is an accurate or computational model stimulated by using JMP software. The aim of this study is to find out the effect of rheological models on the hydraulic system and to use the artificial neural network to simulate the parameters that were used as emotional parameters and then find an equation containing the parameters μp, Yp and P Yp/ μp to calculate the pressure losses in a hydraulic system. Data for 7 intermediate casing wells with 12.25" hole size and 95/8" intermediate casing size are taken from the southern Iraq field used for the above purpose. Then compare the result with common equations used to calculate pressure losses in a hydraulic system. Also, we calculate the optimum flow by the maximum impact force method and then offset in Equation obtained by (Joint Marketing Program) JMP software. Finally, the equation that was found to calculate pressure losses instead of using common hydraulic equations with long calculations gave very close results with less calculation.                                                                                 

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Publication Date
Mon Jan 29 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Role of Ultrasound in Antenatal Detection of Echogenic Amniotic Fluid and Pregnancy Outcome
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Background: Ultrasound is a valuable tool for evaluating fetal problems throughout pregnancy. Amniotic fluid anomalies have been associated with unfavorable maternal, fetal, and obstetrical outcomes. Objective: To determine the effect of echogenic amniotic fluid during term pregnancy on the presence of meconium stain liquor and pregnancy outcome. Methods: A cross-sectional study was conducted on 1080 term pregnant women who visited Al-Elwiya Maternity Teaching Hospital from May 1st, 2021, to May 1st, 2023. Ultrasound was used to analyze echogenic amniotic fluid and turbid liquor. The liquor state was tested either after an artificial membrane rupture in the vaginal delivery trial or during a cesarean section. Results: Echogenic amni

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Optimization of Cutting Parameters on Delamination of Drilling Glass-Polyester Composites
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This paper attempted to study the effect of cutting parameters (spindle speed and feed rate) on delamination phenomena during the drilling glass-polyester composites. Drilling process was done by CNC machine with 10 mm diameter of high-speed steel (HSS) drill bit. Taguchi technique with L16 orthogonal layout was used to analyze the effective parameters on delamination factor. The optimal experiment was no. 13 with spindle speed 1273 rpm and feed 0.05 mm/rev with minimum delamination factor 1.28.                                       &

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Hypomagnesemia in Iraqi Diabetic Patients and Healthy Controls: An Exploratory study
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Background: Diabetes mellitus has been suggested
to be the most common metabolic disorder
associated with magnesium deficiency, and because
available data suggest that adverse outcomes are
associated with hypomagnesemia, it is prudent that
routine surveillance for hypomagnesemia be done
and the condition be treated whenever possible.
Aim of the study:To explore the serum Mg
concentrations of diabetic patients and healthy
controls in our locality.
Mehtods: One hundred and forty four diabetic
patients (22 with type I and 122 with type II diabetes
mellitus) recruited from the outpatient diabetes clinic
at the Specialized Center For Endocrine DiseasesBaghdad (62 patients), National Diabetes Center-Al

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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Development and Assessment of Feed Forward Back Propagation Neural Network Models to Predict Sunshine Duration
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         The duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp

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Publication Date
Sat Jun 04 2022
Journal Name
Al–bahith Al–a'alami
paratexte in specialized literary journals : AL ADEEB AL IRAQI magazine is a model
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Post-structural critical studies highlighted the importance of studying the texts surrounding the text as an important part in the process of receiving and understanding texts, and although this topic was dealt with by the ancient Arabs and Europeans, interest in it appeared clearly after the appearance of Gerard Genet's book (SEUILS), which separated it Text Thresholds. Or what he called paratexte, and dealt with them with interest as he reads them on books. With the development of semiotic studies, interest in paratexte studies began in a broader way and in various literary and non-literary texts, including journalistic texts. And since specialized magazines are one of the press releases that enjoy their privacy in terms of topics and

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