The purpose of this study is to show the constants and variables geography in Russian
policy in light of variables geostrategic witnessed by the world, especially after the collapse
of the Soviet Union and the disintegration to fifteen Republic became the Russian Federation
and the heir to the Soviet Union, Geography particularly important because the impact of its
data in policy making less change ofothers, and explain the political choices cannot achieve
security through its relationship constants geographical (natural or human) paint forms of
economic activity and determine the points they national security. issue is the geographical
this or that country is determined by its policy also specifies the way in which

This research paper studies the alienation of the intellectuals in the modern novel through the study of two alienated characters, John Marcher in Henry James's The Beast in the Jungle, and Mr. Duffy in James's Joyce's "A Painful Case." As a result of the complexity of life in the industrial societies, the individuals, especially the intellectual ones, feel themselves unable to integrate into social life; they fear society and feel that it endangers their individuality and independence. Thus, these characters live on the fringe of the societ

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

Discretionary Punishment, Public Regulation, Interest

Films of pure Poly (methyl methacrylate) PMMA and Iron chromate doped PMMA have been prepared using casting method. Transmission and absorptance spectra have been recorded in the wavelength range (300-900) nm, in order to calculate, single oscillator energy, dispersion energy proposed by Wemple - DiDomenico model, average oscillator strength, average oscillator wavelength. The refractive index data at infinite wavelength which was found to obey single oscillator model which was found to increase from 2.27-2.56 as the doping percentage increase. The decreasing in the optical energy gap which was found according to Tauc model were (3.74-3.63) eV , is in good agreement with that obtained by wimple-DiDomenico model. The inverse behavior comp