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Numerical Simulation of Solar Granulation Dynamics Using Optical Correction Techniques
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High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods, the study aims to understand system behavior under varying atmospheric turbulence conditions and provide recommendations for Zonal AO system enhancement for solar observations. Performance metrics, including Strehl Ratio, Correction Stability, Root Mean Squared Error (RMSE), and Correction Rate, were used to assess system performance under varying turbulence levels. However, challenges arise with increasing turbulence strength, impacting correction precision, stability, and speed. The results showed the weakness of the Zonal AO in treating high distortions in wavefront, as is evident by the decreases in Strehl Ratio values from 0.98 to 0.085 for disturbance strength values from 0.2 to 1, respectively.

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Publication Date
Thu Aug 08 2024
Journal Name
Computation
Evaluation of the Dynamics of Psychological Panic Factor, Glucose Risk and Estrogen Effects on Breast Cancer Model
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Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the empirical bayes method with moments method to estimate the affiliation parameter in the clinical trials using simulation
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In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
comparison Bennett's inequality and regression in determining the optimum sample size for estimating the Net Reclassification Index (NRI) using simulation
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 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
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      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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Publication Date
Mon Aug 01 2016
Journal Name
Arpn Journal Of Engineering And Applied Sciences
SURVEY ON VANET TECHNOLOGIES AND SIMULATION MODELS
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Vehicular ad hoc network (VANET) is a distinctive form of Mobile Ad hoc Network (MANET) that has attracted increasing research attention recently. The purpose of this study is to comprehensively investigate the elements constituting a VANET system and to address several challenges that have to be overcome to enable a reliable wireless communications within a vehicular environment. Furthermore, the study undertakes a survey of the taxonomy of existing VANET routing protocols, with particular emphasis on the strengths and limitations of these protocols in order to help solve VANET routing issues. Moreover, as mobile users demand constant network access regardless of their location, this study seeks to evaluate various mobility models for vehi

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Theoretical Calculation of the Electron Transport Parameters and Energy Distribution Function for CF3I with noble gases mixtures using Monte Carlo simulation program
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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Newtonian and modified newtonian gravitational simulation of spiral galaxies
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One of the most powerful tools for any stellar dynamics is the N-body simulation. In an N-body simulation the motion of N particles is followed under their mutual gravitational attraction. In this paper the gravitational N-body simulation is described to investigate Newtonian and non- Newtonian (modified Newtonian dynamics) interaction between the stars of spiral galaxies. It is shown that standard Newtonian interaction requires dark matter to produce the flat rotational curves of the systems under consideration, while modified Newtonian dynamics (MOND) theorem provides a flat rotational curve and gives a good agreement with the observed rotation cu

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Publication Date
Tue Nov 01 2011
Journal Name
International Journal Of Mechanical And Materials Engineering
Simulation and design optimization of magneto rheological control valve
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Magneto-rheological (MR) Valve is one of the devices generally used to control the speed of Hydraulic actuator using MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. The finite element analysis is carried out on this valve to optimize its design. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMM). The Model dimensions of MR valve, material properties and the circuit properties of valve coil are taken into account. The results of analysis are presented in terms of magnetic strength and magnetic flux density. The valve can be operated with variable flow rate by varying the current. It i

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Scopus
Publication Date
Mon Sep 01 2008
Journal Name
Journal Of Engineering
MATHEMATICAL SIMULATION OF UNSTEADY FLOW THROUGH HOLLOW FIBER MEMBRANE
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Publication Date
Mon Mar 14 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Mathematical simulation of memristive for classification in machine learning
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