Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.

The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w

The main problem of this research is the delay of implementation of the investment plan projects for the period (2013-2016) and the weakness of the staff ability in the ministries and they don’t have the sufficient experience to carry out the implementation process.

Therefore, the research aims to evaluate the implementation of programs and projects of the investment plan in a manner consistent with the objectives set for them without any wasteful of efforts, time and money. And then identify the problems and obstacles to determine the deviations of the implementation of the specific for each sector according to the criteria of evaluation and the form of cost, quality, time and implementation.<

Echinococcosis is a zoonotic disease caused by the larval stage of the tapeworm Echinococcus granulosus. This disease is an important public health and a significant economic issue in Iraq, where the lungs and livers are the popular places of infection. The aim of the current study focused on using the molecular techniques in the detection of an E. granulosus strain that causes cystic echinococcosis to human, sheep and cattle in Thi-Qar province, Iraq. In the current study, thirty isolates of E. granulosus were collected from 10 human hydatid cysts through surgery done at Al-Hussein Imam Teaching Hospital in Thi-Qar province and 10 sheep with 10 cattle hydatid cysts were obtained from the slaughterhouse in Thi-

Random laser gain media is synthesized with different types of dye at the same concentration (1×10^-3 M) as an active material and silicon dioxide NPs (silica SiO₂) as scatter centers through the Sol-Gel technique. The prepared samples are tested with UV–Vis spectroscopy, Fluorescence Spectroscopy, Field Emission Scanning Electron Microscopy (FESEM), and Energy Dispersive X-ray Diffraction (EDX). The end result demonstrates that doped dyes with silica nanoparticles at a concentration of 0.0016 mol/ml have lower absorbance and higher fluorescence spectra than pure dyes. FESEM scans revealed that the morphology of nanocrystalline silica is clusters of nano-sized spherical particles in the range (25-67) nm. It is con

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod