In this paper, construction microwaves induced plasma jet(MIPJ) system. This system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate by using flow meter, to diagnose microwave plasma optical emission spectroscopy(OES) was used to measure the important plasma parameters such as electron temperature (Te), residence time (Rt), plasma frequency (?pe), collisional skin depth (?), plasma conductivity (?dc), Debye length(?D). Also, the density of the plasma electron is calculated with the use of Stark broadened profiles

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

This present work is concerned with one of the syntactic issues that has been researched by many linguists, grammarians, and specialists in Islamic studies, the estimated answer to a condition. However, this topic is researched this time by examining Imam Al-Qurtbi’s opinions in interpreting related ayas from the holly Quraan in his book (Collector of Quranic Rules) or its transliteration (Al-Jami’ Li Ahkam Al-Quran). Such a step involves commenting on, tracking what Al-Qurtbi said in this regard, discussing it from the points of view of other grammarians, and judging  it accordingly, taking into account the apparent surface structures of the examples collected. To achieve this objective, the inductive analytical approach has be

Is the chemical industries of great importance for the economy of any country, through what is borne by these industries is an important part of the changes contained in the industrial output of transfer and, moreover, that these industries are overlaps and intricacies of sector-wide with the rest of the manufacturing sectors, with agriculture and services , through the offering of these industries produce Production requirements intervention such as chemical fertilizer used in the production of agricultural crops, in addition to the various areas for the use of phosphorus in the food industry, to the extent that it is difficult to find material Food preparation is not included i

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

   In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the  traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data