The pure and Sb doped GeSe thin films have been prepared by thermal flash evaporation technique. Both the structural and optical measurement were carried out for as deposited and annealed films at different annealing temperatures.XRD spectra revealed that the all films have one significant broad amorphous peak except for pure GeSe thin film which annealed at 573 K, it has sharp peak belong to orthorhombic structure nearly at 2θ=33o . The results of the optical studies showed that the optical transition is direct and indirect allowed. The energy gap in general increased with increasing annealing temperature and decreased with increase the ratio of Sb dopant. The optical parameters such as refractive index, extinction coefficient and r

The pure and Sb doped GeSe thin films have been prepared by thermal flash evaporation technique. Both the structural and optical measurement were carried out for as deposited and annealed films at different annealing temperatures.XRD spectra revealed that the all films have one significant broad amorphous peak except for pure GeSe thin film which annealed at 573 K, it has sharp peak belong to orthorhombic structure nearly at 2θ=33o. The results of the optical studies showed that the optical transition is direct and indirect allowed. The energy gap in general increased with increasing annealing temperature and decreased with increase the ratio of Sb dopant. The optical parameters such as refractive index, extinction coefficient and real and

This paper introduces the Multistep Modified Reduced Differential Transform Method (MMRDTM). It is applied to approximate the solution for Nonlinear Schrodinger Equations (NLSEs) of power law nonlinearity. The proposed method has some advantages. An analytical approximation can be generated in a fast converging series by applying the proposed approach. On top of that, the number of computed terms is also significantly reduced. Compared to the RDTM, the nonlinear term in this method is replaced by related Adomian polynomials prior to the implementation of a multistep approach. As a consequence, only a smaller number of NLSE computed terms are required in the attained approximation. Moreover, the approximation also converges rapidly over a

In 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

In 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