Abstract :- In this paper, silver nanoparticles had been prepared by chemical reduction method. Many tests had been done to it such as UV-Visible spectrophotometer, XRD, AFM&SEM test. finally an attempt had been done to get the optimum condition to control the grain size of silver Nanoparticles by variation the heating period and other parameters which has an effect in silver Nanoparticles synthesis process. in this method we can get a silver nanoparticles in the size range from 52 to 97 nm.

Nanoparticle has pulled in expanding consideration with the developing enthusiasm for nanotechnology which hold potential as essential segments for development applications. In the present work, a copper nanoparticle is manufactured as a suspension in distilled water by beating a bulk copper target with laser source (532 nm wavelength, 10 ns pulse duration and 10 Hz repletion rate) via method. UV- visible absorption spectra and AFM analysis has been done to observe the effect of repetition rate for the pulsation of laser. Copper nanoparticles (Cu-NPs) were successfully synthesized with green color. The Cu- NPs have very high purity because the preparation was managed in aqueous media to eliminate ambient contaminations.  Absorption

In present work examined the oxidation desulfurization in batch system for model fuels with 2250 ppm sulfur content using air as the oxidant and ZnO/AC composite prepared by thermal co-precipitation method. Different factors were studied such as composite loading 1, 1.5 and 2.5 g, temperature 25 ^oC, 30 ^oC and 40 ^oC and reaction time 30, 45 and 60 minutes. The optimum condition is obtained by using Tauguchi experiential design for oxidation desulfurization of model fuel. the highest percent sulfur removal is about 33 at optimum conditions. The kinetic and effect of internal mass transfer were studied for oxidation desulfurization of model fuel, also an empirical kinetic model was calculated for model fuels

In this study, plain concrete simply supported beams subjected to two points loading were analyzed for the flexure. The numerical model of the beam was constructed in the meso-scale representation of concrete as a two phasic material (aggregate, and mortar). The fracture process of the concrete beams under loading was investigated in the laboratory as well as by the numerical models. The Extended Finite Element Method (XFEM) was employed for the treatment of the discontinuities that appeared during the fracture process in concrete. Finite element method with the feature standard/explicitlywas utilized for the numerical analysis. Aggregate particles were assumedof elliptic shape. Other properties such as grading and sizes of the aggr

This paper proposes a new method to tune a fractional order PID controller. This method utilizes both the analytic and numeric approach to determine the controller parameters. The control design specifications that must be achieved by the control system are gain crossover frequency, phase margin, and peak magnitude at the resonant frequency, where the latter is a new design specification suggested by this paper. These specifications results in three equations in five unknown variables. Assuming that certain relations exist between two variables and discretizing one of them, a performance index can be evaluated and the optimal controller parameters that minimize this performance index are selected. As a case study, a third order linear time

This research include building mathematical models for aggregating planning and shorting planning by using integer programming technique for planning master production scheduling in order to control on the operating production for manufacturing companies to achieve their objectives of increasing the efficiency of utilizing resources and reduce storage and  improving customers service  through  deliver in the actual dates and reducing delays.

In this paper the method of singular value decomposition  is used to estimate the ridge parameter of ridge regression estimator which is an alternative to ordinary least squares estimator when the general linear regression model suffer from near multicollinearity.

This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COV