Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examined: water vapor and smoke. Experiments were conducted using these pollutants to calibrate the system and determine its detection sensitivity. With this technique the absorption coefficients, types of pollutants and their concentrations were determined.
Wireless communications are characterized by their fastest growth in history, as they used ever-evolving and renewed technologies, which have allowed them to spread widely. Every day, communication technology introduces a new invention with features that differ from its predecessor. Bell Laboratories first suggested mobile wireless communication services to the general population in the late 1940s. Still, it wasn't easy at that time to use on a large scale due to its high costs. This paper aims to describe the state of cellular mobile networks; by comparing the sources of electromagnetic pollution caused by these networks, measure the level of power density in some residential areas, and compare them with international standards adopted in
... Show MoreThree types of medical commercial creams Silvazine, Cinolon Tar and Hydroquinon Domina were incorporated in this study. The medical creams were taken directly and placed uniformly on the glass slide. Each type of pharmaceutical was weighed at 1 mg and dispersed on an area of 1x1 cm. This process ensures same thickness for all samples. The creams were analyzed by using double-beam UV/visible spectrophotometer Metertech SP8001. The absorption spectrum for each of samples was measured against wavelength range of 300–700 nm.
PVC/Kaolinite composites were prepared by the melt intercalation method. Mechanical properties, thermal properties, flammability and water absorption percentage of prepared samples were tested. Mechanical characteristic such as tensile strength, elongation at break; hardness and impact strength (charpy type) were measured for all samples. It was found that the tensile strength and elongation at break of PVC composites decreased with increasing kaolinite loading. Also, the hardness of the composites increases with increase in filler content .The impact strength of the composites at the beginning increases at lower kaolinite loadings is due to the lack of kaolin adhesion to the matrix. However, at higher kaolin loadings. This severe agglom
... Show MoreThe aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.
The goal of this paper is to study dynamic behavior of a sporadic model (prey-predator). All fixed points of the model are found. We set the conditions that required to investigate the local stability of all fixed points. The model is extended to an optimal control model. The Pontryagin's maximum principle is used to achieve the optimal solutions. Finally, numerical simulations have been applied to confirm the theoretical results.
This work is aimed to design a system which is able to diagnose two types of tumors in a human brain (benign and malignant), using curvelet transform and probabilistic neural network. Our proposed method follows an approach in which the stages are preprocessing using Gaussian filter, segmentation using fuzzy c-means and feature extraction using curvelet transform. These features are trained and tested the probabilistic neural network. Curvelet transform is to extract the feature of MRI images. The proposed screening technique has successfully detected the brain cancer from MRI images of an almost 100% recognition rate accuracy.