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Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Simulation and Modeling of Detailed Load flow Analysis for the 400kVA and 132kVA Iraqi Grid
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A load flow program is developed using MATLAB and based on the Newton–Raphson method,which shows very fast and efficient rate of convergence as well as computationally the proposed method is very efficient and it requires less computer memory through the use of sparsing method and other methods in programming to accelerate the run speed to be near the real time.
The designed program computes the voltage magnitudes and phase angles at each bus of the network under steady–state operating conditions. It also computes the power flow and power losses for all equipment, including transformers and transmission lines taking into consideration the effects of off–nominal, tap and phase shift transformers, generators, shunt capacitors, sh

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Women's Satisfaction Regarding Care Provided by Nurse-Midwives During Labor in Bint AL-Huda Hospital in AL Al-Nasiriyah City
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Objectives: To assess the woman satisfaction with nursing care during labor.

Methodology: A descriptive analytic study about conducted for a purposive (non probability) sample of one hundred  labor women interview validity and reliability of questionnaire are determined through panel of experts and pilot study. Descriptive and inferential statistical procedures were used to analyze the data, which collected by using interview technique.

Results: The study sample indicated that in general the women were satisfied in nursing care that provided during labor.

Recommendations: The study recommended educational tra

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Bayesian methods to estimate the failure probability for electronic systems in case the life time data are not available
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In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Research In Social Sciences & Humanities
The effect of the green value chain in reducing environmental failure costs
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The research aims to apply the activities of the green value chain as one of the modern administrative techniques that economic units resort to develop solutions to the pollution problems that occur due to the activity of economic units and their products that may cause damage to the environment as well as the waste of natural resources and to identify the production of environmentally friendly products and reduce the costs of environmental failure of both types Internal and external that may be borne by economic units such as taxes, fines and compensation due to nonobservance of environmental requirements and the preservation of human health and protection of the environment. To achieve the goal of the research, the researchers rel

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Publication Date
Fri Mar 10 2023
Journal Name
Journal Of Namibian Studies : History Politics Culture
The Costs of Environmental Failure and The Impact of The Green Value Chain in Reducing Them
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The research aims to apply the activities of the green value chain as one of the modern administrative techniques that economic units resort to develop solutions to the pollution problems that occur due to the activity of economic units and their products that may cause damage to the environment as well as the waste of natural resources and to identify the production of environmentally friendly products and reduce the costs of environmental failure of both types Internal and external that may be borne by economic units such as taxes, fines and compensation due to non- observance of environmental requirements and the preservation of human health and protection of the environment.To achieve the goal of the research, the researchers re

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Wellbore Breakouts Prediction from Different Rock Failure Criteria
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One of the wellbore instability problems in vertical wells are breakouts in Zubair oilfield. Breakouts, if exceeds its critical limits will produce problems such as loss circulation which will add to the non-productive time (NPT) thus increasing loss in costs and in total revenues. In this paper, three of the available rock failure criteria (Mohr-Coulomb, Mogi-Coulomb and Modified-Lade) are used to study and predict the occurrence of the breakouts. It is found that there is an increase over the allowable breakout limit in breakout width in Tanuma shaly formation and it was predicted using Mohr-Coulomb criterion. An increase in the pore pressure was predicted in Tanuma shaly formation, thus; a new mud weight and casing pr

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Publication Date
Tue Oct 11 2022
Journal Name
College Of Islamic Sciences
Modeling strategy in the subject of recitation provisions for students of Islamic sciences colleges
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on the subject of the provisions of recitation among students of the Islamic Sciences Colleges).

The researchers adopted the experimental method and chose an experimental design for the two equivalent groups by post-test. The research sample consisted of (60) male and female students from (second stage) - Department of Qur’an Sciences and Islamic Education - University of Diyala, and the two researchers were rewarded between the two groups of research in the following variables: (Chronological age calculated in months, degrees of recitation rulings subject in the previous year, the two researchers studied the same research groups, and lasted for an entire semester, the researchers prepared the observation card to measure the ru

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