Lagrange series and the Bessel function are two classical methods that were created by series expanding from Taylor series. In this paper, the purpose of those two methods was to find the values of the eccentric anomaly for one period (0–360)°. The Matlab program is used to apply the results, the input parameters were eccentricity (0–1), mean anomaly (0–360)°, and finally the parameter W (1–13). The program does not need a tolerance to obtain a precise value for eccentric anomaly like other iterative and non-iterative methods to stop the program; it will stop after completing the required period from 0° to 360° for a body that is determined by the solver. The output will be the final value of the eccentric anomaly. Furthermore, a compression between the Lagrange series and the Bessel function was studied to determine the eccentricity required for each method. The results showed that there was an increase in the relationship between the eccentric anomaly and the mean anomaly. Also, these two methods were used at eccentricity smaller or equal to 0.35 and for all ranges of W (1–13). More values for W in the Lagrange series produced a very large shift from the ideal solution. All of those results were in good agreement as compared with other published studies in this field.
Background:Periodontal diseases and dental caries are the most common oral diseases, but they can be adequately prevented by adopting a specific health behavior and plaque control.The study was carried out to determine and compare oral health status; it included both caries experience, gingival health and oral hygiene behavior betweenfirst and fifth yearsof Al-Mustansiriyahdental students. Materials and methods: Total sample of the study consisted of 50 students at first year (25 males, 25 females)and 60 students at fifth year (30 males, 30 females). Plaque andgingival indices,dental caries indices (DMFS and DMFT) wererecorded to evaluateoral health status for each student. Further questionnaires were given to evaluate different oral hyg
... Show MoreIn this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho
... Show MoreIn this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending
<p>Daftardar Gejji and Hossein Jafari have proposed a new iterative method for solving many of the linear and nonlinear equations namely (DJM). This method proved already the effectiveness in solved many of the ordinary differential equations, partial differential equations and integral equations. The main aim from this paper is to propose the Daftardar-Jafari method (DJM) to solve the Duffing equations and to find the exact solution and numerical solutions. The proposed (DJM) is very effective and reliable, and the solution is obtained in the series form with easily computed components. The software used for the calculations in this study was MATHEMATICA<sup>®</sup> 9.0.</p>