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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
Fri May 01 2020
Journal Name
Iraqi Geological Journal
DETERMINATION OF PORE TYPES AND POROSITY TRENDS USING OF VELOCITY-DEVIATION LOG FOR THE CARBONATE MISHRIF RESERVOIR IN HALFAYA OIL FIELD, SOUTHEAST IRAQ
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system
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These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ENHANCE THE QUALITATIVE SENSORY CHARACTERISTICS AND ANTIMICROBIAL ACTIVITY OF BOVINE MILK BY USING (Hibiscus sabdariffa): ENHANCE THE QUALITATIVE SENSORY CHARACTERISTICS AND ANTIMICROBIAL ACTIVITY OF BOVINE MILK BY USING (Hibiscus sabdariffa)
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Bovine milk is one of the richest nutrients that contain minerals and vitamins that enhance immunity, especially in children, but because many children do not want to drink the raw milk, therefore this study aimed to enhance the sensory characteristics of raw milk by using hibiscus plant extract, which is characterized by red color and distinctive flavor as well as studying the effect of aqueous extract of Hibiscus sabdariffa on inhibiting the growth of microorganisms, by using three concentrations of the aqueous extract (0.5, 1.0 and 1.5%), where the statistical results showed a significant difference (P≤0.05) between the concentrations in color, texture and general acceptance, and the best results appeared when using

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Automatic Block Selection for Synthesizing Texture Images using Genetic Algorithms
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Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.

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Publication Date
Mon Mar 15 2021
Journal Name
Applied Sciences
Leading Edge Blowing to Mimic and Enhance the Serration Effects for Aerofoil
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Leading edge serration is now a well-established and effective passive control device for the reduction of turbulence–leading edge interaction noise, and for the suppression of boundary layer separation at high angle of attack. It is envisaged that leading edge blowing could produce the same mechanisms as those produced by a serrated leading edge to enhance the aeroacoustics and aerodynamic performances of aerofoil. Aeroacoustically, injection of mass airflow from the leading edge (against the incoming turbulent flow) can be an effective mechanism to decrease the turbulence intensity, and/or alter the stagnation point. According to classical theory on the aerofoil leading edge noise, there is a potential for the leading edge blowi

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Comparison the effectiveness of using a magnetic field to control theColi phages isolated from rivulet water with water-treatment using magnetic field added iron filings
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The present study aimed to use the magnetic field and nanotechnology in the field of water purification, which slots offering high efficiency to the possibility of removing biological contaminants such as viruses and bacteria rather than the use of chemical and physical transactions such as chlorine and bromine, and ultraviolet light and boiling and sedimentation and distillation, ozone and others that have a direct negative impact on human safety and the environment. Where they were investigating the presence in water samples under study Coli phages using Single agar layer method and then treated samples positive for phages to three types of magnetic field fixed as follows (North Pole - South Pole - Bipolar) and compare the re

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Publication Date
Wed Nov 17 2021
Journal Name
Sustainability
The Role of Accounting Information System and Knowledge Management to Enhancing Organizational Performance in Iraqi SMEs
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Small and Medium Enterprises (SMEs) in Iraq have experienced low performance due to the limited usage of accounting information systems (AIS) and the inability to exploit knowledge of management capabilities (KMC). These deficiencies have led to competitive pressures in the marketplace that have adversely affected their sales and production. This study investigates the role of AIS in terms of operation support, knowledge support, regulatory support, and the role of KMC, including knowledge acquisition, knowledge transfer, and knowledge utilized to enhance organizational performance in Iraqi SMEs. The target population was managers and owners in SMEs using AIS in Iraq’s cities. A non-probability purposive sampling technique was use

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Science And Research (ij
Simulation of Chlorine Decay in Al-Gukook WaterDistribution Networks Using EPANET
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The approach of the research is to simulate residual chlorine decay through potable water distribution networks of Gukookcity. EPANET software was used for estimating and predicting chlorine concentration at different water network points . Data requiredas program inputs (pipe properties) were taken from the Baghdad Municipality, factors that affect residual chlorine concentrationincluding (pH ,Temperature, pressure ,flow rate) were measured .Twenty five samples were tested from November 2016 to July 2017.The residual chlorine values varied between ( 0.2-2mg/L) , and pH values varied between (7.6 -8.2) and the pressure was very weak inthis region. Statistical analyses were used to evaluated errors. The calculated concentrations by the calib

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Publication Date
Sun Jan 01 2017
Journal Name
Lecture Notes In Computer Science
The Art of Using Cross-Layer Design in Cognitive Radio Networks
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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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