The primary aim of this paper, is to introduce the rough probability from topological view. We used the Gm-topological spaces which result from the digraph on the stochastic approximation spaces to upper and lower distribution functions, the upper and lower mathematical expectations, the upper and lower variances, the upper and lower standard deviation and the upper and lower r th moment. Different levels for those concepts are introduced, also we introduced some results based upon those concepts.

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

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

Conjugated Linoleic Acid (CLA) is an essential polyunsaturated omega fatty acid that occurs naturally in vegetable oils. It also plays an important role in preserving meat for longer periods by preventing oxidation of other fats. Thus, it can be used in the production of functional foods with high biological value and low cholesterol levels by adding poultry diets. Objective: The aim of the present study was to evaluate the effect of adding CLA to broiler diets on production performance and fatty acid content in the meat. Methodology: One-day-old Ross-308 chicks were randomly distributed into four dietary treatment groups: control (0 g CLA kgG1 diet; A1), 0.5 g CLA kgG1 diet (A2), 0.75 g CLA kgG1 diet (A3) and 1 g CLA kgG1 diet (A4). Diets

This study was carried out at Poultry Research Station, State Board of Agricultural Research, Ministry of Agriculture for the period from 27 September 2014 to 9 November 2014 to evaluate the Supplementation of different levels of Conjugated Linoleic Acid (CLA) on productive performance of broiler. Four hundred eighty chicks (Ross-308),one day old were randomly distributed to four dietary treatments for 42 days of age with 3 replicates/vtreatment (40 bird/replicate). Experimental treatments were as follow; T1 (Control diet) without supplement, while the treatment T2,T3 and T4  were Supplemented with 1, 1.5, 2 g CLA /kg diet  respectively. The results showed significant (P ≤ 0.05) increased in mean of body weight, weight gain, ave