Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

The research aims at the possibility of measuring the technical and scale efficiency (SE) of the departments of the College of Administration and Economics at the University of Baghdad for a period lasting 8 years, from the academic year 2013-2014 to 2018-2019 using the method of Applied Data Analysis with an input and output orientation to maintain the distinguished competitive position and try to identify weaknesses in performance and address them. Nevertheless, the research problem lies in diagnosing the most acceptable specializations in the labor market and determining the reasons for students’ reluctance to enter some departments. Furthermore, the (Win4DEAp) program was used to measure technical and scale efficiency (SE) and rely on

The levels of lead (pb), copper (cu), cobalt (co) and cadmium (cd) were determined in different kinds of milk and the health risks were evaluated. The mean levels were 0.73±0.21, 0.06±0.01, 0.12±0.01 and 0.14±0.01 ppm for these metals respectively. The levels of pb and cu were found to be insignificant differences (p<0.05), whereas the levels of co and cd, were no significant differences (p>0.05). The dry and liquid kinds of milk were different significantly (p<0.05), whereas the original, was no significant differences (p>0.05). The values for all metals were more than one. The metals pb and cd were detected at highest concentrations in most dry and liquid milk samples.