Abstract: The power and the size of the final spot of the laser beam reaching the target are very important requirements in most of the laser applications and fields such as medical, military, and scientific, so studying laser propagation in the atmosphere is a very important topic. The propagation of the laser beam through the atmosphere is subject to several attenuation processes that deplete the power and expand the beam. Through the simulation results of the free electron laser within the visible region of the electromagnetic spectrum (400-700nm), it was found that the attenuation increases with decreasing wavelength. Laser propagation in the presence of rain and snow leads to a very large l

The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH₄) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH₄) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH₄VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH₄ were in 2003 while the maximum values were in 2016. The vertical distribution of CH_4<

In this paper the effect of nonthermal atmospheric argon plasma on the optical properties of the cadmium oxide CdO thin films prepared by chemical spray pyrolysis was studied. The prepared films were exposed to different time intervals (0, 5, 10, 15, 20) min. For every sample, the transmittance, Absorbance, absorption coefficient, energy gap, extinction coefficient and dielectric constant were studied. It is found that the transmittance and the energy gap increased with exposure time, and absorption. Absorption coefficient, extinction coefficient, dielectric constant decreased with time of exposure to the argon plasma

Green nanotechnology is a thrilling and rising place of technology and generation that braces
the ideas of inexperienced chemistry with ability advantages for sustainability, protection, and
the general protection from the race human. The inexperienced chemistry method introduces a
proper technique for the production, processing, and alertness of much less dangerous chemical
substances to lessen threats to human fitness and the environment. The technique calls for inintensity expertise of the uncooked materials, particularly in phrases in their creation into
nanomaterials and the resultant bioactivities that pose very few dangerous outcomes for people
and the environment. In the twenty-first century, nanotec

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

Green nanotechnology is a thrilling and rising place of technology and generation that braces the ideas of inexperienced chemistry with ability advantages for sustainability, protection, and the general protection from the race human. The inexperienced chemistry method introduces a proper technique for the production, processing, and alertness of much less dangerous chemical substances to lessen threats to human fitness and the environment. The technique calls for in- intensity expertise of the uncooked materials, particularly in phrases in their creation into nanomaterials and the resultant bioactivities that pose very few dangerous outcomes for people and the environment. In the twenty-first century, nanotechnology has become a systematic

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