The gamma dose rates and specific activity of 137Cs, 60Co and 40K in
samples of soil taken from places near the landfill radiation at Al-
Tuwaitha site were measured using a portable NaI(Tl) detector. The
results of gamma dose rates in samples were ranged from 52.6
nGy.h-1 to 131nGy.h-1. Then the specific activity of 137Cs, 60Co and
40K in soil were determined using high pure germanium (HPGe)
detector. The specific activities were varied from 1.9 to 115500 Bq.
kg-1 for 137Cs, from 6.37 to 616.5 Bq. kg-1 for 60Co, and from 3 to
839.5 Bq. kg-1 for 40K. The corresponding health risk for the annual
effective dose equivalent varied from 1.85×10-14 to 15.7mSv/y. The
results were compared with various internationa

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

In the era of the digital economy, public organizations need to consolidation the capabilities of entrepreneurial alertness to reduce the risks of sudden transformations and changes, and to find effective mechanisms to discover and invest in environmental opportunities proactively, as this concern has become a knowledge gap in public sector institutions, the current research aims to identify the role of digital competence in influencing on entrepreneurial alertness in the Central Bank of Iraq (CBI), the descriptive analytical approach was used as a research method to describe and analyze the main research variables. digital competence as an explanatory variable includes three dimensions: digital infrastructure, digital integration, and d

The research studied and analyzed the hybrid parallel-series systems of asymmetrical components by applying different experiments of simulations used to estimate the reliability function of those systems through the use of the maximum likelihood method as well as the Bayes standard method via both symmetrical and asymmetrical loss functions following Rayleigh distribution and Informative Prior distribution. The simulation experiments included different sizes of samples and default parameters which were then compared with one another depending on Square Error averages. Following that was the application of Bayes standard method by the Entropy Loss function that proved successful throughout the experimental side in finding the reliability fun

This study presents the results of atmospheric particulates sampling using high volume air sampler for selected places at Al Tuwaitha nuclear site. The collected samples were analyzed for gross alpha /beta radioactivity using Ludlum model 3030 and measurement particles activity in Al Tuwaitha nuclear site and the surrounding areas for the period from 28/12/2016 to 13/4/2017.The measurement of activity concentrations ranged from (0.42±0.03 to 4.18±0.13) Bq/m3 for alpha particles and from(0.93±0.06 to 9.21±0.26) Bq/m3for beta particles. The activity concentration of nuclides inversely proportional with air temperature and wind speed while humidity is directly proportional with it. Highest value of activity concentration has been found at(

Water flooding is one of the most important methods used in enhanced production; it was a pioneer method in use, but the development of technology within the oil industry, takes this subject toward another form in the oil production and application in oil fields with all types of oils and oil reservoirs. Now days most of the injection wells directed from the vertical to re-entry of full horizontal wells in order to get full of horizontal wells advantages.
This paper describes the potential benefits for using of re-entry horizontal injection wells as well as combination of re –entry horizontal injection and production wells. Al Qurainat productive sector was selected for study, which is one of the four main productive sectors of Sout

Objective: To assess the Impact of Socio-economic status on age at menarche among secondary school students at
AL-Dora city in Baghdad, Iraq.
Methodology: This is a cross sectional study with multi-stage sampling was carried out during the period from the
3
th of December2013 to 12th of March 2014. The Sample comprised of 1760 girls, 1510 girls from urban area and
250 from rural area was included in the study. In first stage, selection of schools was done, and one class was
selected randomly from each level of Education, The data collection through a special questionnaire which Contain
the age of girl by year, class level, birth order, number of household, number of rooms, residency (urban/rural),
education level