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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
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamical Study of An SIR Epidemic Model With Nonlinear Incidence Rate and Regress of Treatment
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   In this research, dynamical study of an SIR epidemical model with nonlinear direct incidence rate (Beddington-De Angelis ) type, and regress of treatment investigated .An  analytical study  to the model shows that there are two equilibrium points appear, the discussed successfully with sufficient condition, the existence of local bifurcation and Hopf bifurcation was analyzed, finally numerical simulations are done to explain the analytic studies.

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Publication Date
Sun Apr 16 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Structure,Rietveld Refinement Study of BaCoxTixFe12-2xO19 ferrite Using Powder XRD Analysis
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    BaCoxTixFe12-2xO19 (x=0.1, 0.5, 0.7, 0.9, 1.7) were prepared using powder technology technique . X-ray diffraction with diffractometer CuKα radiation analysis and Rietveld refinement of the samples were studied and showed a single phase of hexagonal structure with SP63/mmc space group . Lattice parameters, cell volume , crystallite size and x-ray density were determined .The hexagonal structure was represented by using PowderCell program showing the atomic positions of Co ,Ti, and Fe ions.
 

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Publication Date
Tue Sep 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of estimation methods for regression model parametersIn the case of the problem of linear multiplicity and abnormal values
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 A simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Maximum Likelihood and Bayesian Methods For Estimating The Gamma Regression With Practical Application
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In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
N – Topological Space and Its Applications in Artificial Neural Networks
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   In this paper we give definitions, properties and examples of the notion of  type Ntopological space. Throughout this paper  N is a finite positive  number, N 2. The task of this paper is to study and investigate some properties of such spaces with the existence of a relation between this space and artificial Neural Networks (NN'S), that is we applied the definition of this space in computer field and specially in parallel processing

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Publication Date
Sun Jun 21 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Enhancement of Aqueous Solubility and Dissolution Rate of Etoricoxib by Solid Dispersion Technique
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Etoricoxib (EXB) is a highly selective cox-2 inhibitor which belongs to the non-steroidal anti-inflammatory drug (NSAID). EXB is a class II drug according to the biopharmaceutical classification system (BCS), which possess a very low aqueous solubility in water.  In the present study, many trials were made to improve the aqueous solubility and dissolution rate of EXB by solid dispersion technique.

Eighteenth EXB formulas were formulated as a solid dispersion using a variety of hydrophilic polymers (as carriers)   including poloxamer 407 (PXM 407), poloxamer 188 (PXM 188) and polyethylene glycol 4000 (PEG 4000) at different drug: polymer ratios (1:1, 1:3 and 1:5). These formulas were prepared by two methods; solvent

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Publication Date
Mon Dec 10 2007
Journal Name
Iraqi Journal Of Laser
The Effect of He:Ne Laser on Viability and Growth Rate of Leishmania Major
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An isolate of Leishmania major was grown on the semisolid medium and incubated at 26ºC. The isolate was irradiated by He: Ne laser (632.8 nm, 10 mW) at exposure times (5, 10, 15, 20, 25, 30) minutes in their respective order. The unirradiated groups represent control group. Growth rate and percentage of viability were examined during six days after irradiation. The change in these two parameters reflects the effect of irradiation on the parasite. The results refers that the general growth effected by irradiation in comparison with un irradiation group, The growth rate of parasite decrease with increasing the exposure time in comparison with control group. Parasite viability decrease with irradiation and the percentage of living cell dec

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Extinction Cross-Section Modeling of Metallic Nanoparticles
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Localized surface plasmons (LSPs) are a potentially valuable property for the practical use of small size metallic particles. Exploiting the LSPs in metallic nanoparticle (NP)-based solar cells was shown to increase the efficiency of solar panels. A large extinction cross section of NPs allows for high scattering of light at the surface of the panel, which reduces the panel thickness, allowing for small size and low-cost solar cells. In this paper, the extinction cross-section of spherical nanoparticles is studied and simulated numerically. Surface plasmons were first modeled using the Drude’s model then the scattering and absorption cross-sections were derived. Commercial3D simulation software was used to model the near field dis

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Assessment of surface water quality using statistical analysis methods: Orontes River (Case study)
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The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

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