In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

Let R be a commutative ring with identity and M be unitary (left) R-module. The principal aim of this paper is to study the relationships between relatively cancellation module and multiplication modules, pure submodules and Noetherian (Artinian) modules.

A study of some mite species of alfalfa. wheat, and barley was conducted in central Iraq.
The mites were extracted using a tullgren funnel method. Twelve species were recorded. 10 of
them belong to suborder Trombidiformes and 2 belong to suborder Sarcoptiforms. Three
mites, Irnpar(pes hystricinus, Scutacarus longitarsus, and Rhizoglyphus echin opus are new
records for Iraqi mite fauna, and 11 are new host records in alfalfa soil.

     The purpose of this  paper is to show that for a holomorphic and univalent function in class S, an omitted –value transformation  yields a class of starlike functions as a rotation transformation of  the Koebe function, allowing both the image and rotation of the function

   to be connected. Furthermore, these functions have several properties that are not far from a convexity properties. We also show that Pre- Schwarzian derivative is not invariant since the convexity property of the function   is so weak.

The preparation of a new Azo compounds of highly conjugated dimeric and polymeric liquid crystal to achieve the crystalline characteristics Which have structures assigned based on elemental analysis, IR 1HNMR and CHNS-O while mesogenic properties have been set for DSC and hot-stage polarizing optical microscopy. The compounds show enantiotropicnematic phase being displayed. The compounds show photoluminescence properties in the organic solution at room temperature, with the fluorescence band centered around 400 nm.

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application