This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.

Convergence prop erties of Jackson polynomials have been considered by Zugmund
[1,ch.X] in (1959) and J.Szbados [2], (p =ï‚¥) while in (1983) V.A.Popov and J.Szabados [3]
(1 ï‚£p ï‚£ ï‚¥) have proved a direct inequality for Jackson polynomials in L
p-sp ace of 2-periodic bounded Riemann integrable functions (f R) in terms of some modulus of
continuity .
In 1991 S.K.Jassim proved direct and inverse inequality for Jackson polynomials in
locally global norms (L
,p) of 2-p eriodic bounded measurable functions (f L) in terms of
suitable Peetre K-functional [4].
Now the aim of our paper is to proved direct and inverse inequalities for Jackson
polynomials

     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

--The objective of the current research is to identify: 1) Preparing a scale level for e-learning applications, 2) What is the relationship between the applications of e-learning and the students of the Department of Chemistry at the Faculty of Education for Pure Sciences/ Ibn Al-Haytham – University of Baghdad. To achieve the research objectives, the researcher used the descriptive approach because of its suitability to the nature of the study objectives. The researcher built a scale for e-learning applications that consists of (40) items on the five-point Likrat scale (I agree, strongly agree, neutral, disagree, strongly disagree). He also adopted the scale of scientific values, and it consists of (40) items on a five-point scale as wel

     The applications of Ruscheweyh derivative are studied and discussed of class of meromorphic multivalent application. We get some interesting geometric properties, such as coefficient bound, Convex linear combination, growth and distortion bounds, radii of starlikenss ,  convexity and neighborhood property.

The main goal of this paper is to study applications of the fractional calculus techniques for a certain subclass of multivalent analytic functions on Hilbert Space. Also, we obtain the coefficient estimates, extreme points, convex combination and hadamard product.

В статье рассматривается вопрос об использовании мультимедийных средств для оптимизации процесса формирования коммуникативной компетенции  в иракской аудитории с привлечением компьютерных технологий. Статья посвящена  использованию мультимедийных технологий  и  различных  приемов формирования интереса к русскому языку. Включение в процесс обучения коммуникативно-значимого, аутентичн

The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

     In this research, we study the dynamics of one parameter family of meromorphic functions . Furthermore, we describe the nature of fixed points of the functions in ,and we explain the numbers of real fixed points depending on the critical point . So, we develop some necessary conditions for the convergence of the sequence when .