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Measurement of Radiation Background and Estimation of the Annual Effective Dose for Workers in the Radiochemistry Laboratories at the Al-Tuwaitha Site
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      This study was achieved to calculate the annual effective dose equivalent (AEDE) in units of (mSv.y-1), and the average radiation dose rate (ADR) in units of (μSv.h-1) which were measured by portable devices.   The study was carried out on the workers of the destroyed radiochemistry laboratory located at Al-Twuitha nuclear site (south of Baghdad). Radiation background was determined for comparison with the radioactive dose of soil samples measured with HPGe detector and portable devices type LUDLUM.  The radioactivity levels of the area around the radiochemistry laboratory building were within the limits of radiation background.  The result showed a significant increase of the annual effective dose of C1 laboratory workers, as the annual effective dose of the lysate cell 1 (AHC1)in the lab was about 18.995 mSv/y, with an occupancy factor of 0.042, for an average working hours of  one hour per day.  An annual effective dose of 24.073 mSv/y was also recorded in hot cell 2 (HCL2), an increase of more than 4 mSv/y, for an occupancy factor of 0.083, equivalent to 2 hours of work per day.  The glove boxes 11 (GB11) of Laboratory C2 recorded an annual effective dose of 19,720 mSv/y for an occupancy factor of 0.125, equivalent to 3 working hours per day.  The C3 Laboratory and the rest of the laboratories and the health physics rooms recorded an annual effective dose within the workers’ allowable limits of 20 mSv/y.

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Improved 𝑫−𝑯𝒆 𝟑 Fusion Reaction Characteristics Parameters
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   The most likely fusion reaction to be practical is Deuterium and Helium-3 (𝐷−𝐻𝑒
 3 ), which is highly desirable because both Helium -3 and Deuterium are stable and the reaction produces a 14 𝑀𝑒𝑉 proton instead of a neutron and the proton can be shielded by magnetic fields. The strongly dependency of the basically hot plasma parameters such as reactivity, reaction rate, and energy for the emitted protons, upon the total cross section, make the problems for choosing the desirable formula for the cross section, the main goal for our present work.

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
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      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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