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 current study is concerned with the analysis of spatial and temporal to death the elderly population in the city of Baghdad and at the level of administrative units Minor (districts and the areas) depending on the general population census of the province of Baghdad, data for 1997 and data from the Ministry of Health Department of Health and Vital Statistics for 2013.
The study showed differing age and quality of mortality rates at the level of administrative units of the study area, and notes the high mortality rates of elderly people of all age groups in 2013 compared to 1997, and this is due to security conditions after the USA occupation, and the accompanying conditions have affected the increase in mortality rates.

The use  analysis  value chain such  information in the provision as financial  so information quality meet and satisfy the needs of users such information , particularly investors and lenders   as the identification needs   financial information and the knowledge as their behavior influenced by that information can be based on the accounting profession to focus on improving their function in order to achieve its goal that satisfying their needs and rationalize their decisions . In accounting thought discovered fertile ground for users preferences as one of the entrances   theorising positive which is based on the need to include knowledge on accounting hypothesis that explain the

Sediment accumulated in sewers is a major concern source as it induces numerous operational and environmental problems. For instance, during wet weather flow, the re-suspension of this sediment accompanied by the combined sewer overflow may cause huge pollutant load to the receiving water body. The characteristics of the sewer sediment are important as it shapes its behaviour and determines the extent of the pollution load. In this paper, an investigation of sewer sediment and its characterization is done for a case study in Baghdad city. Sediment depth covers more than 50% of the sewer cross-sectional area; several operational causes are comprised to cause this huge depths of sediment depositions. The testing and analysis of the s

Noor oil field is one of smallest fields in Missan province. Twelve well penetrates the Mishrif Formation in Noor field and eight of them were selected for this study. Mishrif formation is one of the most important reservoirs in Noor field and it consists of one anticline dome and bounded by the Khasib formation at the top and the Rumaila formation at the bottom. The reservoir was divided into eight units separated by isolated units according to partition taken by a rounding fields.

In this paper histograms frequency distribution of the porosity, permeability, and water saturation were plotted for MA unit of Mishrif formation in Noor field, and then transformed to the normal distribution by applying the Box-Cox transformation alg

The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also