In this review paper, several studies and researches were surveyed for assisting future researchers to identify available techniques in the field of classification of Synthetic Aperture Radar (SAR) images. SAR images are becoming increasingly important in a variety of remote sensing applications due to the ability of SAR sensors to operate in all types of weather conditions, including day and night remote sensing for long ranges and coverage areas. Its properties of vast planning, search, rescue, mine detection, and target identification make it very attractive for surveillance and observation missions of Earth resources. With the increasing popularity and availability of these images, the need for machines has emerged to enhance the ability to identify and interpret these images effectively. This is due to the fact that SAR image processing requires the formation of an image from the measured radar scatter returns, followed by a treatment to discover and define the image's composition. After reviewing several previous studies that succeeded in achieving a classification of SAR images for specific goals, it became obvious that they could be generalized to all types of SAR images. The most prominent use of Convolutional Neural Networks (CNN) was successful in extracting features from the images and training the neural network to analyze and classify them into classes according to these features. The dataset used in this model was obtained from the Moving and Stationary Target Acquisition and Recognition (MSTAR) database, which consists of a set of SAR images of military vehicles, for which the application of the CNN approach achieved a final accuracy of 97.91% on ten different classes.
The study includes collection of data about cholera disease from six health centers from nine locations with 2500km2 and a population of 750000individual. The average of infection for six centers during the 2000-2003 was recorded. There were 3007 cases of diarrhea diagnosed as cholera caused by Vibrio cholerae. The percentage of male infection was 14. 7% while for female were 13. 2%. The percentage of infection for children (less than one year) was 6.1%, it while for the age (1-5 years) was 6.9%and for the ages more than 5 years was 14.5%.The total percentage of the patients stayed in hospital was 7.7%(4.2%for male and 3.4%for female). The bacteria was isolated and identified from 7cases in the Central Laboratory for Health in Baghdad. In
... Show MoreThis study included a survey and review of the scientific names of the marsh insects (aquatic and surrounding it) for the purpose of unifying and updating the database.
The survey reveals 109 species under 77 genera that belong to 32 families and 7 orders as follow: Coleoptera (44 species), Diptera (7 species) Ephemeroptera (2 species), Hemiptera (14 species), Hymenoptera (11 species), Lepidoptera (2 species) and Odonata with 29 species.
Information of specimens' collection for each species, synonyms and geographical distribution were provided.
Fundamentals Concept in Metorology an Introductory Survey - ISBNiraq.org
Many Iraqi provinces had collective cemeteries, especially in the middle and southern regions of Iraq, but many of those cemetery locations are undefined yet. Ground penetration radar has two features that make it optimal from a geophysical perspective for shallowly detecting sensitive materials near the surface. First, the instantaneous image is formed upon scanning, called a radargram. Second, the non-destructive inference of the scanned materials. For these two reasons, this technique was chosen to conduct a simulation process to reveal the old human remains in Iraq's central and southern areas using another model with the same physical feature (old burial) at the AL-Khamisiya site, Thi-Qar province.
The demanded stage
... Show MoreA land magnetic survey was carried out along regional profile, which is located at the north part of the Iraqi western desert. It starts from al –Qaam City (at north) toward Rutba City (at south) with a total length of 238km. The survey was carried out along the paved road between the two cities, About 113 measuring points were done with inter-station distance of 2 km (for 198 km) and 2 to 5km (for 40km). Two proton magnetometers were used in this survey. One of them is used for base station monitoring, which was fixed as of Salah Aldin field (Akkas). Its readings were used for diurnal corrections. All magnetic measurements were corrected for normal and topographic corrections. The readings were reduced to a certain base level. The resu
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This research aims to understand complexity management and its impact on the use of the dynamic capabilities of a sample of private colleges. Private colleges are currently facing many crises, changes, unrest and high competitive pressures. Which is sometimes difficult or even impossible to predict. The recruitment of dynamic capabilities is also one of the challenges facing senior management at private colleges to help them survive and survive. Thus, the problem of research was (there is a clear insufficiency of interest in Complexity Management and trying to employ it in improving the dynamic capabilities of Colleges that have been discussed?). A group of private colleges was selected as a
... Show MoreBackground and objective: Viral Hepatitis Type B&C is serious public health challenge throughout the world.Hepatitis B and C viruses still remain to be the major causes of chronic hepatitis.It is estimated that around 350-400 million people in the world are chronic carriers of HBV, which represents approximately 7% of the total populationwhereas infection with HCV is found in approximately 3% of the world population, which represents 160 million people. Hepatitis B infection has a wide range of seroprevalence in the Mediterranean countries ranging from intermediate (=>2% ) to high prevalence ( =>7%). World Health Organization estimated a prevalence rate for HCV infection of about 4.6% in Eastern Mediterranean in 1999. During the eightieths
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreIn this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water
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