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Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parameters. A databases from one well drilled in carbonate environments were subjected to the predictive methods. Each raw dataset is described by eight parameters including rate of penetration (ROP), true vertical depth (TVD), weight on bit (WOB), bit rotational speed (RPM), torque (TQ), flow rate (Q), equivalent circulating density (ECD), standpipe pressure (SPP), and unconfined compressive strength (UCS). First, both MRA and ANNs are tested as predictive methods. The prediction capacity of each model was also verified by using two-based error metrics: the determination coefficient (R2) and the mean square error (MSE).</p><p>The current results support the evidence that MRA and ANNs are able to be effectively utilize the drilling data, and thus provide accurate ROP prediction. However, more attention to the multiple regression analysis is required where it is implemented for ROP prediction. ANNs appear to be more conservative in predicting ROP than MRA as indicated by a higher value R2 (0.96) and lower value MSE (1.89) of the ANN model. Considering the input parameters, the obtained results showed that TVD, WOB, RPM, SPP, and ECD had the greatest effect on estimated ROP-conditions, followed in decreasing by pump flow rate, drilling torque, and rock strength. Another important point that highlights in this study is that the drilling rate may increase with depth in carbonate rocks because of their heterogeneity. This study presents new models to estimate ROP from other parameters which can help the driller to achieve an optimal drilling rate through monitoring controllable parameters.</p>
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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering Science And Technology
Air entrained vortex occurrence at sump for inclined multiple intake pipes using cfd
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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Tue Aug 31 2021
Journal Name
Al-kindy College Medical Journal
Assessment of the Effects of SARS-Cov-2 Infection on Multiple Organs Using Laboratory Indices
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Background: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is still a severe threaft for human health currently, and the researches about it is a focus topic worldwide.

Aim of the study: In this study, we will collect some laboratory results of the patients with coronavirus disease (COVID-19) to assess the function of liver, heart, kidney and even pancreas. 

Subjects and Methods: Laboratory results of the patients with COVID-19 are collected. The biochemical indices are classified and used to assess the according function of liver, heart, kidney; meantime, and blood glucose is also observed and taken as an index to roughly evaluate pancreas.

Results: There were some in

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Publication Date
Tue May 11 2021
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Paediatric multiple sclerosis: a case report of missed and dismissed diagnosis
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Multiple Sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS). Up to 10 % of MS patients have onset in paediatric age group. Although the clinical profile of MS appears similar to that seen in adults, several features may differ and specific issues arise in children. Here, we reported a 12-year old girl who presented with 3-year history of episodes of seizures and facial nerve palsy and finally fatigue and cognitive impairment were noted and interfered with her academic performance. Because of the presumed atypical clinical presentations, the diagnosis was missed then dismissed despite neuroimaging features and CSF immunological findings that were highly suggestive of MS. Later, evolution of the

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Estimating the Population Mean in Stratified Random Sampling Using Combined Regression with the Presence of Outliers
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In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

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Publication Date
Sun Jul 03 2011
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Assessment of bone marrow angiogenesis using F VIII-related antigen and its relationship to proliferating cell nuclear antigen (PCNA) in multiple myeloma.
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Background: Multiple myeloma (MM) is a malignant clonal expansion of plasma cells. Previous studies had demonstrated that both bone marrow angiogenesis as measured by microvessel density (MVD) and PCNA were increased in variety of malignant disorders, including multiple myeloma.
Objective: Assessment of angiogenesis in bone marrow of MM patients by using immunohistochemical stain to measure microvessel density (MVD) using factor VIII –related antigen and to evaluate the expression of PCNA antigen in plasma cells of MM bone marrow sections . Also to find the correlation between these two parameters and between them and the percentage of plasma cells infiltration in bone marrow of MM.
Patients, materia

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Publication Date
Wed Aug 28 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Structural and Stress Analysis of NACA0012 Wing Using SolidWorks
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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Analyzing big data sets by using different panelized regression methods with application: Surveys of multidimensional poverty in Iraq
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Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

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Scopus
Publication Date
Mon Aug 01 2022
Journal Name
Communications In Mathematical Biology And Neuroscience
Stability analysis of a competitive ecological system in a polluted environment
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The interplay of species in a polluted environment is one of the most critical aspects of the ecosystem. This paper explores the dynamics of the two-species Lokta–Volterra competition model. According to the type I functional response, one species is affected by environmental pollution. Whilst the other degrades the toxin according to the type II functional response. All equilibrium points of the system are located, with their local and global stability being assessed. A numerical simulation examination is carried out to confirm the theoretical results. These results illustrate that competition and pollution can significantly change the coexistence and extinction of each species.

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