NGC 6946 have been observed with BVRI filters, on October 15-18,
2012, with the Newtonian focus of the 1.88m telescope, Kottamia
observatory, of the National Research Institute of Astronomy and
Geophysics, Egypt (NRIAG), then we combine the BVRI filters to
obtain an astronomical image to the spiral galaxy NGC 6946 which
is regarded main source of information to discover the components of
this galaxy, where galaxies are considered the essential element of
the universe. To know the components of NGC 6946, we studied it
with the Variable Precision Rough Sets technique to determine the
contribution of the Bulge, disk, and arms of NGC 6946 according to
different color in the image. From image we can determined th

This research was carried out at University of Baghdad - College of Agricultural Engineering Sciences during the fall season of 2020 and spring season of 2021 in order to evaluate the effect of organic fertilizer and the foliar application of boron on the growth and yield of industrial potatoes (Solanum tuberosum L.). Using factorial experiment (5*4) within Randomized Complete Block Design  with three replicates, the organic fertilizer (palm fronds peat) was applied at four levels (0, 12, 24, and 36 ton ha-1) in addition to the treatment of the recommended of chemical fertilizer. The foliar application of Boron was applied at four concentrations which were 0, 100, 150 and 200 mg (H3Bo3). L-1. The results Revealed a significant incr

The research aims to identify ways of upgrading the quality level of university education at the Middle Technical University in light of its application for the National Ranking project for the quality of Iraqi universities in order to obtain advanced grades among the Iraqi universities , Which is qualified to enter the Ranking of universities worldwide, through displaying the mechanism of the Application of  National Ranking project for the quality of Iraqi universities in the Middle Technical University and its formations consisting of (5) technical colleges and (11) technical institute.

        The results of the application showed several observations: The most

6. coli K12 and B. subtilis 168 were investigated for their cadmium and mercury tolerance abilities. They were developed by UV mutagenesis technique to increase their tolerances either to cadmium or mercury, and their names then were designated depend on the name and concentration of metals. E. coli K12 Cd3^R exhibited bioremediation amount of 6.5 mg Cd/g dry biomass cell. At the same time, its wild-type (E. coli K12 Cd3) was able to remove 5.2 mg Cd/g dry biomass cell in treatment of 17 mg Cd /L within 72 hours of incubation at 37 °C (pH=7) in vitro assays. The results show that E.coli K12 Hg 20 was able to remove 0.050 µg Hg/g dry biomass cell

The technological developments in the field of communication have witnessed considerable impact in the variables which exist in following up and conveying the events which link it’s meaning to political implications. This makes a number of satellite channels depend on the techniques of propaganda and use them in the news bulletins to achieve political aims and ends related to its formational directives where those channels allotted a considerable time in its programming transmission map to concentrate on the security and political status to complete the image of the informational scene according to the logic of its propaganda and styles in processing news for daily events.The technological developments in the field of communication hav

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Objective: This study aimed to investigate the relationship between high blood pressure and
different variables, such as (weight, smoking, amount of salt and water taken daily, and number
of hours of natural sleep per person) for young people.
Methodology: The study was conducted on students at the student community of the Technical
Institute in Baquba and the University of Diyala during the period from September 2015
until June 2016. The patients ranged in age from 18-24 years. All data were collected through
a questionnaire that included the main reasons and periodic follow-up of the disease.
Results: The total number of samples was 450.The results showed that 33% of all samples
have high blood pressure. The rel