Dell Hymesin 1964coined The Ethnography of Communication in an attempt to explain the ways in which people use the language to interact. It hypothesizes that ethnography is less applicable among participants who have the same sociocultural background. It was proven that all the basic speech components occur whenever there is an interactional situation. The elements of (SPEAKING) schema are closely connected. However, the findings establish the fact that these elements take place effectively among participants who have the same sociocultural background.One of the most outstanding conclusions is the capability of the (SPEAKING) model to analyze not only an interaction between two or more participants, but also any event which consists of a mo

DBNRAHA Hameed, IJRSSH PUBLICATION, 2018

The sustainable competitive advantage for organizations is one of the requirements for value creation, which centered on the possession of scarce resources that achieve maximum flows to invest in intellectual capital, if what has been interest in them, measured and employed the way properly and style, so I figured the need for new technologies to enable organizations to measure the intellectual and physical assets and to assess its performance accordingly, so it sheds search light on the measurement of the added value of existing knowledge using the standard value-added factor is the intellectual (value added intellectual coefficient) (VAIC) and to develop a set of assumptions about the extent of the difference between the sample

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t