Continuous flow injection analysis (CFIA) is one of the simplest, easiest, and multilateral analytical automation methods in moist chemical analysis. This method depends on changing the physical and chemical properties of a part of the specimen spread out from the specimen injected into the carrier stream. The CFIA technique uses automatic analysis of samples with high efficiency. The CFIA PC compatibility also allows specimens to be treated automatically, reagents to be added, and reaction conditions to be closely monitored. The CFIA is one of the automated chemical analysis methods in which a successive specimen sample is to be estimated and injected into a vector stream from a flowing solution that meets the reagent and mixes at a spe

In this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes  n=40,60,100,variances used σ²=0.5,1,1.5 the results  for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the

This piece of research work aims to study one of the most difficult reaction and determination due to continuous and rapid variation of reaction products and the reactants. As molybdenum (VI) aid in the decomposition of hydrogen peroxide in alkaline medium of ammomia, thus means a continuous liberation of oxygen which cuases and in a continuous manner a distraction in the measurement process. On this basis pyrogallol was used to absorbe all liberated oxygen and the result is an a clean undisturbed signals. Molybdenum (VI) was determined in the range of 4-100 ?g.ml-1 with percentage linearity of 99.8% or (4-300 ?g.ml-1 with 94.4%) while L.O.D. was 3.5 ?g.ml-1. Interferring ions (cations and anions) were studied and their main effect was red

In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

This researchpaper includes the incorporation of Alliin at various energy levels and angles 

With Metformin using Gaussian 09 and Gaussian view 06. Two computers were used in this work. Samples were generated to draw, integrate, simulate and measure the value of the potential energy surface by means of which the lowest energy value was (-1227.408au). The best correlation compound was achieved between Alliin and Metformin through the low energy values where the best place for metformin to b

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f

The aim of this paper is to determine the feasibility of using fluorometric methods as an indicator for quality and contamination of milk with E.coli bacteria, and selection the suitable wavelength to be used with laser induced auto fluorescence. Three groups of milk samples were used in this study: Fresh pasteurized milk samples, milk samples containing different concentration of E.coli bacteria which were added artificially, and milk samples that were kept in refrigerator for 3-5 days. Thirteen excitation wavelengths were used to get the emission spectra for all milk samples using spectroflourometer .The results showed that the emission spectra at 275nm excitation wavelength gave a good differentiation between these three groups.