Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

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

This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

Xanthomonas axonopodis pv glycines (Xag) is a pathogen that causes pustule disease in soybeans. Many
techniques for controlling this disease have been widely developed, one of which is the use of biological agents.
Bacillus sp. from the soybean phyllosphere is a biological agent that has the potential to suppress the
development of pustule disease. One of the biological control mechanisms is through biochemical induction
of plant resistance which includes the accumulation of phenols, salicylic acid compounds, and peroxidase
enzymes. Bacillus subtilis JB12 and Bacillus velezensis ST32 are two bacteria isolated from the soybean
phyllosphere which have previously been known to suppress Xag through an anti

Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

These search summaries in building a mathematical model to the issue of Integer linear Fractional programming and finding the best solution of Integer linear Fractional programming (I.L.F.P) that maximize the productivity of the company^,s revenue by using the largest possible number of production units and maximizing denominator objective which represents^,s proportion of profits to the costs, thus maximizing total profit of the company at the lowest cost through using Dinkelbach algorithm and the complementary method on the Light industries company data for 2013 and comparing results with Goal programming methods results.

It is clear that the final results of resolution and Dinkelbac