This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

Silver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm

in this paper copper oxide (cuO thin films were prepared by the method of vacum thermal evaporation a pressure.

In this work, ZnS thin films have been deposited by developed laser deposition technique on glass substrates at room temperature. After deposition process, the films were annealed at different temperatures (200ºC , 300 ºC and 400ºC ) using thermal furnace.The developed technique was used to obtain homogeneous thin films of ZnS depending on vaporization of this semiconductor material by continuous CO2 laser with a simple fan to ensure obtaining homogeneous films. ZnS thin films were annealed at temperature 200ºC, 300 ºC and 400ºC for (20) minute in vacuum environment. Optical properties of ZnS thin film such as absorbance, transmittance, reflectance, optical band gap, refractive index extinction coefficient and absorption coefficien

Silver selenide telluride Semiconducting (Ag2Se0.8Te0.2) thin films were by thermal evaporation at RT with thickness350 nm at annealing temperatures (300, 348, 398, and 448) °K for 1 hour on glass substrates .using X-ray diffraction, the structural characteristics were calculated as a function of annealing temperatures with no preferential orientation along any plane. Atomic force microscopy (AFM) and X-ray techniques are used to analyze the Ag2SeTe thin films' physical makeup and properties. AFM techniques were used to analyze the surface morphology of the Ag2SeTe films, and the results showed that the values for average diameter, surface roughness, and grain size mutation increased with annealing temperature (116.36-171.02) nm The transm

Preparation of superposed thin film (CdTe)1-xSex / ZnS) with concentration of (x= 0.1, 0.3, 0.5) at a temperature of substrate (Ts= 80 0C) by using Thermal Vacuum Evaporation System. The measurement of X-ray diffraction shows that the compounds CdTe, ZnS, (CdTe)1-xSex and (CdTe)1-xSex / ZnS have a polycrystalline structure, the C-V characteristic shows that the capacitance degrease by increasing the concentration (x) in reverse bias, while the I-V characteristic shows the current dark (Id) increase in forward and reverse bias by increasing (x) and the photocurrent (Iph) increase in reverse bias by increasing the concentration (x), the values of photocurrent are greater than from the values of the dark current for all concentrations

The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P^*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

The method of operational matrices based on different types of polynomials such as Bernstein, shifted Legendre and Bernoulli polynomials will be presented and implemented to solve the nonlinear Blasius equations approximately. The nonlinear differential equation will be converted into a system of nonlinear algebraic equations that can be solved using Mathematica®12. The efficiency of these methods has been studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as the polynomial degree (n) increases, since the errors decrease. Moreover, the approximate solutions obtained by the proposed methods are compared with the solution of the 4th order Runge-Kutta method (RK4), which gives very

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

  There are many researches deals with constructing an efficient solutions for real problem having Multi - objective confronted with each others. In this paper we construct a decision for Multi – objectives based on building a mathematical model formulating a unique objective function by combining the confronted objectives functions. Also we are presented some theories concerning this problem. Areal application problem has been presented to show the efficiency of the performance of our model and the method. Finally we obtained some results by randomly generating some problems.