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kRhqLJQBVTCNdQwChgOI
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
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Detection and Classification of The Osteoarthritis in Knee Joint Using Transfer Learning with Convolutional Neural Networks (CNNs)
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    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin

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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Impact of Health Education Program upon Knowledge of Patients with End-Stage Renal Failure
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Objective(s): To determine the impact of health education program toward their end-stage renal failure (ESRF)
patients’ knowledge through a follow-up approach each two months post program implementation for six months.
Methodology: "Follow-up" longitudinal design by using time series approach of data analysis and the application of
pre-post tests approach for the study group and the control group. The study is conducted in Al-Shahid Ghazi Hariri
Teaching Hospital for Surgical Specialties/Centre for Disease and Renal Transplant, and Al-Khayal private Hospital for
renal disease and transplantation during the period from August, 29th
, 2010 through February, 28th
, 2011. To achieve
the objectives of the study, purp

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Publication Date
Wed Dec 29 2021
Journal Name
Al-khwarizmi Engineering Journal
Evaluation of the Main Causes of Diesel Engine Injector Failure using Fault Tree Analysis
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The maintenance of the diesel engine parts in any electric power station contains many problems that lead to stopping. Several reasons lead to such problems; these reasons should be analyzed and evaluated in order to eliminate their effects. This paper is based on evaluation of the main causes that lead to diesel engine injector failure as a main part of electric power stations, using fault tree analysis (FTA). The FTA is the most broadly utilized strategies in the industrial area to perform reliability analysis of complex designing frameworks. A fault tree is a logical representation of the relationship of basic events that lead to a given unwanted event (i.e., top event).

Starting with introducing the FTA and how it could be uti

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Publication Date
Mon Nov 19 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Use of Logistic Regression Approach to Determine the Effective Factors Causing Renal Failure Disease
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    The main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
The Technique Features of the 1990s Prose Poem in Iraq: The Technique Features of the 1990s Prose Poem in Iraq
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Abstract:
The prose poem of the 1990s is considered one of the important
contributions of the Iraqi poetic scene. The poem found a position in the Iraqi
poetry because of the favor of a group of youth poets who lefty clear traces.
Their linguistic techniques often violate the domain o9f language, significance
and image.
The poems of those youth poets moved the verse towards reality to
drink from its abundant springs in order to stand on a rigid ground. Their
linguistic traces are characterized by paradox and astonishment that are used
by the poet to construct his poem.

The paradox was considered an ideal means for constructing a
poem by some of them. The poem moved towards definitions and these
de

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study of the Anti-Diuretic Hormone (ADH) on End Stage Renal Failure Disease (ESRD) Pre-Hemodialysis in Iraqi Patients
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     Chronic renal disease (CRD) is a pathophysiologic process with multiple etiologies, resulting in the inexorable attrition of Nephron number and function and frequently leading to end-stage renal disease (ESRD). In turn, ESRD represents a clinical state or condition in which there has been an irreversible loss of endogenous renal function, of a degree sufficient to render the patient permanently dependent upon renal replacement therapy (dialysis of transplantation) in order to avoid life threatening uremia, reflecting a dysfunction of all organ systems as a result of untreated or under treated acute or chronic renal failure. The current study was involved 80 patients, the age range within 25-70 ye

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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Symposium On Networks, Computers And Communications (isncc)
An Interference Mitigation Scheme for Millimetre Wave Heterogeneous Cloud Radio Access Network with Dynamic RRH Clustering
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Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Ultra Wideband Cognitive Network Objective Issues
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Due to that the Ultra Wide Band (UWB) technology has some attractive features like robustness to multipath fading, high data rate, low cost and low power consumption, it is widely use to implement cognitive radio network. Intuitively, one of the most important tasks required for cognitive network is the spectrum sensing. A framework for implementing spectrum sensing for UWB-Cognitive Network will be presented in this paper. Since the information about primary licensed users are known to the cognitive radios then the best spectrum sensing scheme for UWB-cognitive network is the matched filter detection scheme. Simulation results verified and demonstrated the using of matched filter spectrum sensing in cognitive radio network with UWB and pro

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Publication Date
Wed Feb 29 2012
Journal Name
Al-khwarizmi Engineering Journal
WLAN Integrated with GPRS Network Securely
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In this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.

      Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy  was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP ad

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