Preferred Language
Articles
/
uRbDGIcBVTCNdQwC7TY_
Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
...Show More Authors

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.                                                                                 

Crossref
View Publication
Publication Date
Fri Sep 01 2006
Journal Name
Journal Of Faculty Of Medicine Baghdad
The Significance Of Maternal Total Serum Homocysteine Level In Iraqi Mothers Who Had Previous Babies With Neural Tube Defects
...Show More Authors

Background: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials

... Show More
Publication Date
Tue Feb 19 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Suggested Model to Audit the Health Institutions to Achieve Sustainable Development: Suggested Model to Audit the Health Institutions to Achieve Sustainable Development
...Show More Authors

Sustainable development is longer that meet the needs of the present generation without compromising the ability of future generations to meet their own needs as it seeks to harmonize economic, social, Why research aims to check the availability of a proposed program takes into account the evidence and scrutiny of financial commitment and performance audit in accordance with the dimensions of sustainable development (economic, environmental, social and institutional) to measure the extent of the province on the needs of current and future generations, The problem with research that there is no audit program ensures the audit of financial statements, commitment and performance of health services in order to achieve sustainable development

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Jun 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Promising Gains of 5G Networks with Enhancing Energy Efficiency Using Improved Linear Precoding Schemes
...Show More Authors

Scopus (2)
Scopus Crossref
Publication Date
Wed Dec 31 2025
Journal Name
Modern Sport
The Contribution of Design Thinking to Reducing Excessive Sensitivity to Criticism Among Athletes in Selected Track and Field Events
...Show More Authors

View Publication
Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Numerical solution for Wiener-Hopf integral equation using artificial neural network
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
...Show More Authors

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

... Show More
View Publication Preview PDF
Scopus (18)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
...Show More Authors

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Fri May 31 2019
Journal Name
International Review Of Civil Engineering (irece)
An Experimental Study on Geotechnical and Electrical Properties of an Oil-Contaminated Soil at Thi-Qar Governorate/Iraq
...Show More Authors

In Iraq, the risk of soil pollution by petroleum products increases with the growth of oil exploration, production and shipping large quantities of oil through pipelines over thousands of kilometers. Numerous oil spills have been documented recently in many sites due to damage in the oil industry infrastructures, which have led to soil contamination causing serious environmental hazards and deterioration to the soil and its engineering properties. So, it is essential to investigate the impact of oil leakage through the soil stratum consequently, assessing the eligibility of the contaminated soil for construction projects or identifying the appropriate treatment method. The paper investigates the general behaviour and the associated variatio

... Show More
View Publication
Scopus (11)
Crossref (3)
Scopus Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
...Show More Authors
Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p> ... Show More
Scopus (9)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Transylvanian Review
The role of the ABC system in determining the costs of services in Iraqi banks
...Show More Authors

The role of the ABC system in determining the costs of services in Iraqi banks