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Three Dimensional MHD Simulationof Comet Hale-Bopp Tail
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The interaction between comet Hale-Bopp tail with the solar wind is investigated in the present paper using magneto-hydrodynamic (MHD) numerical simulation, which accounts for the presence of the interplanetary magnetic field (IMF). The simulation is based on three-dimensional Lax-Wendroff explicit scheme, providing second-order accuracy in space and time. The ions produced from the nucleus of the comet will add considerable effects on the microstructure of the solar wind, thus severely altering its physical properties. The present simulation focuses on careful analysis of these properties by means of simulating the behavior of the comet Hale-Bopp’s tail at 1 AU from the sun. These properties include the changes of the plasma density, particle velocity, IMF changes, pressure, and internal energy. The results indicated that comet tail will highly disturb the physical properties of the solar wind for a considerable distance. These changes reflect the effect of including the source term in the present simulation. It is shown that the comet tail will retain its original shape faster as it approaches the sun. Practical comparisons are also presented in the present research with earlier work. The present simulation was made using MATLAB program.

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
A Comparison of Different Estimation Methods to Handle Missing Data in Explanatory Variables
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Missing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Baysian and NonBaysian Methods to Estimate the two parameters of Logistic Distribution
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In this paper ,the problem of point estimation for the two parameters of logistic distribution has been investigated using simulation technique. The rank sampling set estimator method which is one of the Non_Baysian procedure and Lindley approximation estimator method which is one of the Baysian method were used to estimate the parameters of logistic distribution. Comparing between these two mentioned methods by employing mean square error measure and mean absolute percentage error measure .At last simulation technique used to generate many number of samples sizes to compare between these methods.

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Mean Latin Hypercube Runge-Kutta Method to Solve the Influenza Model
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     In this study, we propose a suitable solution for a non-linear system of ordinary differential equations (ODE) of the first order with the initial value problems (IVP) that contains multi variables and multi-parameters with missing real data. To solve the mentioned system, a new modified numerical simulation method is created for the first time which is called Mean Latin Hypercube Runge-Kutta (MLHRK). This method can be obtained by combining the Runge-Kutta (RK) method with the statistical simulation procedure which is the Latin Hypercube Sampling (LHS) method. The present work is applied to the influenza epidemic model in Australia in 1919  for a previous study. The comparison between the numerical and numerical simulation res

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Publication Date
Mon May 04 2020
Journal Name
Offshore Technology Conference
Hydrate Equilibrium Model for Gas Mixtures Containing Methane, Nitrogen and Carbon Dioxide
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Abstract<p>Gas hydrate formation is considered one of the major problems facing the oil and gas industry as it poses a significant threat to the production, transportation and processing of natural gas. These solid structures can nucleate and agglomerate gradually so that a large cluster of hydrate is formed, which can clog flow lines, chokes, valves, and other production facilities. Thus, an accurate predictive model is necessary for designing natural gas production systems at safe operating conditions and mitigating the issues induced by the formation of hydrates. In this context, a thermodynamic model for gas hydrate equilibrium conditions and cage occupancies of N2 + CH4 and N2 + CO4 gas mix</p> ... Show More
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Publication Date
Sun Oct 13 2019
Journal Name
Spe Kuwait Oil & Gas Show And Conference
Optimization of Fracture Parameters for Hydraulic Fractured Horizontal Well in a Heterogeneous Tight Reservoir: An Equivalent Homogeneous Modelling Approach
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Abstract<p>Building numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr</p> ... Show More
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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Bayes and Non-Bayes Estimation Methods for the Parameter of Maxwell-Boltzmann Distribution
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In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Reliability Estimation for the Exponential-Pareto Hybrid System
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     The reliability of hybrid systems is important in modern technology, specifically in engineering and industrial fields; it is an indicator of the machine's efficiency and ability to operate without interruption for an extended period of time. It also allows for the evaluation of machines and equipment for planning and future development. This study looked at reliability of hybrid (parallel series) systems with asymmetric components using exponential and Pareto distributions. Several simulation experiments were performed to estimate the reliability function of these systems using the Maximum Likelihood method  and the Standard Bayes method  with a quadratic loss (QL) function and two priors: non-informative (Jeffery) and inform

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Selection of the initial value of the time series generating the first-order self-regression model in simulation modeAnd their impact on the accuracy of the model
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In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

                  

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Poisson Regression and Conway Maxwell Poisson Models Using Simulation
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Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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Publication Date
Fri Jan 31 2025
Journal Name
Journal Of Studies And Researches Of Sport Education
The effect of using the educational bag on the level of learning some offensive skills with the epee weapon
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