Green synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o

In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

The valley Dwiridj of drainage basins task that lies east of Iraq and thus we have in this study the application of tow models athletes on the three basins of the valley to get Mor e values accurate to Estimate the volume of runoff and peak discharge and time climax and through the use of Technology remote sensing (GIS),has been show through the application of both models, that the maximum value for the amount of Dwiridj valley of (1052/m3/s) According to Equation (SCS-CN) and about (1370.2/m3/s)by approach (GIUH) that difference is the amount of discharge to the Equation (SCS-CN) ar not accurate as(GIUH) approaches Equation ecalling the results of the Field ces Department of damand reservoirs that the volume of runoff to the valley wase

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

Lowering specific energy consumption (SEC) in reverse osmosis (RO) plants is one of the most important criteria in water treatment industry. The present work focused on best suggested RO pilot plant configurations for minimizing specific energy consumption, finding the best configurations experimentally to recover the water with minimizing salts in permeate side in RO module, study the factors affecting the performance of single and two stage systems, TFC membrane is used in spiral wound module. Brackish water is used as feed solution with different concentrations (2000, 3000, 4000 and 5000 ppm). The operating parameters studied were permeate flux, rejection and SEC. The experimental results showed the permeate concentration increased and w

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

in this paper cquations of the per capita growth rate are considered sufficient conditions for oscillation of all solutions are obtained the asymptotie behavior of the nonoscillatory solution of all souliotions are obtained

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in