In this work, silicon nitride (Si₃N₄) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N₂ gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both

The present study is considered the first on this sector of the Tigris River after 2003. It is designed for two aims, the first is to demonstrate the seasonal variations in physicochemical parameters of Tharthar-Tigris Canal and Tigris River; the second is to explain the possible effects of canal on some environmental properties in the Tigris River. Water samples were being collected monthly. Six sampling sites were selected, two on Tharthar Canal and four along the Tigris River, one before the confluence as a control site and the others downstream the confluence with the canal. For a period from January to December 2020, nineteen physicochemical parameters were investigated including air and water temperature, turbidity, electrical cond

In the current research, the work concentrated on studying the effect of curvature of solar parabolic trough solar collector on wind loading coefficients and dynamic response of solar collector. The response of collector to the aerodynamic loading was estimated numerically and experimentally. The curvature of most public parabolic trough solar collectors was investigated and compared. The dynamic response of solar collector due to wind loading was investigated by using numerical solution of fluid-structure interaction concept. The experimental work was done to verify the numerical results and shows good agreement with numerical results. The numerical results were obtained by using finite element software package (ANSYS 14). It was found

ABSTRACT

            A laboratory experiment was carried out during winter season of 2021 in the Seed Technology Laboratory- College of Agricultural Engineering Sciences/ University of Baghdad, to find out the allopathic effects of aerobic and terrestrial aqueous extracts of Artemisia vulgaris L. on the seed germination and seedling growth of linseed. A factorial experiment according to a completely randomized design (CRD)at three replicates was used; the first factor in clouded type of aqueous extract for two plant parts which were aerobic (stems and leaves) and terrestrial (root and rhizomes), while the second factor included five concentrations

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr