Abstract

This study aims at identifying the impact of the application of IFRS 15 "Revenue from contracts with customers on the quality of financial reporting, through application to faculty members in the accounting departments of Iraqi universities and auditors. The problem of the study was the multiplicity of accounting rules and standards Which deals with the issues of revenue recognition , as well as the lack of consistency of most of them with the common framework of financial accounting, which results in low quality of financial reporting in the current financial statements, where the formulation of one hypothesis was the lack of relationship of significant significance The application of IFRS 15 "Recognition of rev

The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also

The printing designer's creative thinking is a deliberate  mental process based on specific skills that stimulate the motivation of  the student to learn and call for  new information for the investigation and research to discover the problems and attitudes and through reformulating the experience in new patterns depending on the active imagination and the flexible scientific thinking through providing the largest number possible  of various unfamiliar  printing design models, and testing their suitability and then readjusting the results with the availability of  suitable educational, learning and academic atmosphere.

The designer's creative thinking depends on main skills. Fluency skill is to put t

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

Different parameters of double pipe helical coil were investigation experimentally. Four coils were used; three with a curvature ratio (0.037, 0.031, and 0.028) and 11mm diameter of the inner tube while the fourth with 0.033 curvature ratio and 13 mm diameter of the inner tube. The hot water flow in the inner tube whereas the cold water flows in the annulus. The inlet temperatures of hot and cold water are 50 ⁰C and 18 ⁰C respectively. The inner mass flow rate ranges from 0.0167 to 0.0583 kg/s. The results show the Nusselt number increase with increase curvature ratio. The Nusselt number of the coil with 0.037 curvature ratio increases by approximately 12.3 % as compare with 0.028 curvature ratio. The results also r

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus