Concentration of NORM then radiological hazard indices were investigated and assessed in different stages of oil and gas production industry that belongs to East Baghdad Oil Field. Sixteen samples of different types of materials were collected representing oil and gas production from first stage to final stage. The samples are prepared then sent to Radiation Protection Center (RPC) / Ministry of Environment for radioactivity analysis using gamma ray spectrometry system based on HPGe. The results show that max value of Ra-226 is 252.4 Bq/kg in sediment sample collected from the final stage of water treatment before it is transferred to disposal well and min value is 1.2 Bq/kg in formation water. The max. activity of Th-232 is 79.4Bq/kg al

      Face Detection by skin color in the field of computer vision is a difficult challenge. Detection of human skin focuses on the identification of pixels and skin-colored areas of a given picture. Since skin colors are invariant in orientation and size and rapid to process, they are used in the identification of human skin. In addition features like ethnicity, sensor, optics and lighting conditions that are different are sensitive factors for the relationship between surface colors and lighting (an issue that is strongly related to color stability). This paper presents a new technique for face detection based on human skin. Three methods of Probability Density Function (PDF) were applied to detect the face by skin color; these ar

The existing investigation explains the consequence of irradiation of violet laser on the structure properties of MawsoniteCu₆Fe₂SnS₈ [CFTS] thin films. The film was equipped by the utilization of semi-computerized spray pyrolysis technique (SCSPT), it is the first time that this technique is used in the preparation and irradiation using a laser. when the received films were processed by continuous red laser (700 nm) with power (>1000mW) for different laser irradiation time using different number of times a laser scan (0, 6, 9, 12, 15 and 18 times) with total irradiation time (0,30,45,60,75,90 min) respectively at room temperature.. The XRD diffraction gave polycrysta

This research deals with a shrinking method concerned with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained

     The ambient temperature is the major parameter that influences wind speed. When temperature rises, air will be extended and wind will flow with different speeds in all directions, increasing of temperature means that wind speed will be increased and vice versa. The relative humidity and atmospheric pressure affected with temperature, too. Climate changes making significant effects on the atmospheric temperature. In this project, the data of thirty four years (1981 – 2004) has been analyzed to get an idea about the changes occurred in the meteorological parameters in Al-Nasiriya city, which was chosen because it has a distinctive wind speed.

      The Mishrif Formation (Cenomanian – Early Turonian) is an important geologic formation in southern Iraq due to its petrophysical properties and geographic extensions, making it a good reservoir of hydrocarbons. Petrophysical properties of the Mishrif Formation in the current study at the Nasiriya oil field were determined from the interpretation of three open-hole logs data of (NS-1, NS-2, and NS-3) wells.

The results of the Mishrif petrophysical evaluation showed that the formation consists of five variable units (CRI, MA, CRII, MB1 and MB2), each one characterized by distinct petrophysical characteristics.

The upper (MA) and lower (MB) units were determined using electrical, porosity and gamma-ray logs. A sha

n this work, it have earthquakes data been analytized as a result of ground water injection attendant to dig wells and oil, which affects the pressure pores in the rock and is according to cause a medium-sized earthquake that have already occurred more than 20 times. according to the publication of the Department of Attenba, the dangers of earthquakes and movement flooring in Guy-Greenbrie-United area of one of United States of America cities, where these data represent a monitor magnitudes of earthquakes from September 2008 the September 2011, we conducted statistical analysis and create a model for earthquakes flooring that was chosen for four dis-tributions and results i the optima reveal the best distribution is the Burr X11 then Gen

The ligand Schiff base [(E)-3-(2-hydroxy-5-methylbenzylideneamino)- 1- phenyl-1H-pyrazol-5(4H) –one] with some metals ion as Mn(II); Co(II); Ni(II); Cu(II); Cd(II) and Hg(II) complexes have been preparation and characterized on the basic of mass spectrum for L, elemental analyses, FTIR, electronic spectral, magnetic susceptibility, molar conductivity measurement and functions thermodynamic data study (∆H°, ∆S° and ∆G°). Results of conductivity indicated that all complexes were non electrolytes. Spectroscopy and other analytical studies reveal distorted octahedral geometry for all complexes. The antibacterial activity of the ligand and preparers metal complexes was also studied against gram and negative bacteria.

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att