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.

The Supreme Judicial Council decided on July 3, 2003, to set up a court to deal with the issues of publication and media. This court tries to solve the problems of media and publishing in both its civil and penal aspects. The decision of establishing the court represents a new and important step to be taken by the Iraqi Judicial Council for the tremendous development witnessed by media sector in general and press in particular especially after 2003.
This study includes two main axes: the first one deals with the most important crimes of publication in the Iraqi legislations such as the crimes of defamation, libel, insult, indecency, and incitement; the second deals with an analytical survey of the completed cases i.e. the issues tha

Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.

Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.

Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).

Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated

The problem of the current research addressed the close link between the psychological stress and social isolation as behavior and experience, as well as, the stress of the displaced pupils by the sense of alienation and isolation from the society to which they had moved. It reflects a sense of mystery to the displaced pupils about their lives in the present and future. Therefore, the current research aims to identify the psychological presence and the level of social isolation among secondary school displaced pupils and identify whether there were statistically significant differences in the variables between the displaced pupils (males-females). Moreover, it attempts to identify the relationship between psychological stress and social

Background: Most adult smokers start smoking regularly some time before 18 years of age. Cigarette smoking is a major ‘preventable’ cause of morbidity and mortality worldwide. It is well-known that smoking has hazardous effect on many systems like pulmonary and cardiovascular system.

Objectives: Study the prevalence of smoking among school pupils according to the mode of smoking, age, school grade, school environment and possible health risk associated with smoking. Type of the study: A cross-sectional study.

Methods: Study was conducted between 1st of March 2014 to 30th of May 2014 at Al-Doura/Al- Kurkh/Baghdad by using convenient sample, including all pupils from 6 schools. The schools were 2 secondary schools, 3 in

Abstract

Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three  financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera  , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f