Trace Elements (Cd, Pb, Cu, Zn, Ni) level were examined in hair of donors from industrial areas, cities and village, and in permanent contact with a polluted workplace environment in lattakia. Hair sample were analyzed for their contents of the trace elements by inductivity coupled plasma- mass spectrometer (ICP- MS). It was found that the contents of (Cd, Pb, Cu, Zn, Ni) in the hair were significantly higher in the industrial areas and cities, while in the village had the lower concentration of elements. Correlation coefficients between the levels of the elements in hair found in this study showed that hair is a good indicator of Environmental Pollution.

Surficial sediment samples were collected from four stations at Shatt Al-Hilla from Western Zoer area to Almaimirh in Babylon province for the period from August 2016 to April 2017.The level of contamination in the sediments of Shatt Al-Hilla, by Lead (Pb), Copper (Cu), Nickle (Ni), Manganese (Mn), Zinc (Zn), Arsenic (As), and Cobalt (Co) has been evaluated using the index of Geo-accumulation (I-Geo), Contamination factor (CF), pollution load index (PLI) and Potential ecological risk index (Eire). In the present study the levels of heavy metals in sediment samples were found in the range of (10-15.22 ppm) for Pb, (25.6-46.09 ppm) for Cu,(144.9-413.7 ppm) for Ni, (666.1- 906.3 ppm) for Mn, (68.69- 119.2 ppm) for Zn, for As (5.22- 8.25 ppm

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

     Getting knowledge from raw data has delivered beneficial information in several domains. The prevalent utilizing of social media produced extraordinary quantities of social information. Simply, social media delivers an available podium for employers for sharing information. Data Mining has ability to present applicable designs that can be useful for employers, commercial, and customers. Data of social media are strident, massive, formless, and dynamic in the natural case, so modern encounters grow. Investigation methods of data mining utilized via social networks is the purpose of the study, accepting investigation plans on the basis of criteria, and by selecting a number of papers to serve as the foundation for this arti

Evaluation study was conducted for seismic interpretation using two-dimensional seismic data for Subba oil field, which is located in the southern Iraq. The Subba oil field was discovered in 1973 through the results of the seismic surveys and the digging of the first exploratory well SU-1 in 1975 to the south of the Subba oil field. The entire length of the field is 35 km and its width is about 10 km. The Subba oil field contains 15 wells most of them distributed in the central of the field.

     This study is dealing with the field data and how to process it for the purpose of interpretation; the processes included conversion of field data format, compensation of lost data and noise disposal, as well as the a

     A mineralogical study using X-ray diffraction supported by scanning electron microscopic examination on the Paleocene- Eocene Kolosh and Gercus formations from northern Iraq is conducted to show the distribution of clay minerals and their paleoenvironmental implications. Smectite palygorskite, kaolinite, illite, and chlorite are commonly present in varying proportions within the Kolosh and Gercus formations. Association of smectite and chlorite in the claystone of the Paleocene Kolosh Formation refers to marine environment of this formation, whereas development of palygorskite fibers from smectite precursor may relate to post-depositional diagenesis. In addition, the abundance of illite and kaolinite in the Eocen

The ability of using aluminum filings which is locally solid waste was tested as a mono media in gravity rapid filter. The present study was conducted to evaluate the effect of variation of influent water turbidity (10, 20and 30 NTU); flow rate(30, 40, and 60 l/hr) and bed height (30and60)cm on the performance of aluminum filings filter media for 5 hours run time and compare it with the conventional sand filter. The results indicated that aluminum filings filter showed better performance than sand filter in the removal of turbidity and in the reduction of head loss. Results showed that the statistical model developed by the multiple linear regression was proved to be
valid, and it could be used to predict head loss in aluminum filings

15 sediment samples were collected; 8 samples from the eastern bank, and 7 samples from the western bank of Al-Wind River in Diyala governorate to assess the sediment pollution in some trace elements such as Fe, Ni, Cd, Zr, Zn and Cu in addition to some oxides such as Al₂O₃, CaO, Na₂O and K₂O to find the effect of anthropogenic pollution and the industrial production on the sediment closed especially Naftkhana by using some geochemical pollution indices such as: geoaccumulation factor (I-geo), enrichment factor (EF),contamination factor (CF), pollution loud index (PLI) and to evaluate the degree of weathering by Applying the Chemical Index of Alteration (CIA)in both banks of Al-Wind River. The

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of