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Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City
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This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding techniques within ANN. The results of the ANN were in sequence: 41.2813, 0.6914. The results of the ANN were in sequence 41.2813, 0.6914. These results provide insights into how well the hidden information is concealed within the image and the extent to which the visual integrity of the image is preserved.

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Publication Date
Fri Dec 14 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Monitoring Indicators for Maternal, Newborn and Child Health at Sub Primary Health Care Centers in Baghdad City: An Evaluative Study
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Objectives: The study aims to evaluate the application of monitoring indicators for maternal, newborn and
child health through the evaluation of impact and coverage health indicators and to evaluate the usefulness of the
application of these indicators at sub primary health care centers in Baghdad City.
Methodology: A descriptive comparative design, which is using the evaluation approach, has been steered at
Sub Primary Health Centers of Baghdad City in order to evaluate the application; impact and coverage, and the
usefulness of monitoring indicators for maternal, newborn and child health from December 4th 2017 to April 29th
2018. A multistage, "non-probability" convenient, sample is selected for the present study. A t

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Monitoring Changes in the Spectral Reflectivity of Baghdad City and the Impact of the Atmospheric Elements on it using R.S and GIS
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Abstract<p>Climate change in recent years has greatly affected the distribution of ground covers. Monitoring these changes has become very easy due to the development of remote sensitivity science and the use of satellites to monitor these changes. The aim of this research is to monitor changes in the spectral reflectivity of the Baghdad governorate center for the month (March, June, September, December) of the year 2021 using remote sensing and satellite images Sentinel 2 and knowing the climate imact on them. Fifty-one samples were selected for four types of ground cover (agricultural land, water, buildings and open space) and their spectral reflectivity was calculated using satellite images. </p> ... Show More
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Publication Date
Sun Jun 30 2024
Journal Name
Tikrit Journal For Agricultural Sciences
First record to the spider Scytodes univittata (Araneae:Scytodidae)in Baghdad, Iraq
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This study is  the first and  new record  to the spider Scytodes univittata Simon, 1882  (Araneae:Scytodidae)in Baghdad /Iraq , the spiders Scytodes univittata  were collect from province Baghdad in Iraq , genus Scytodes belong to the  family Scytodidae  it is one of the most family are wide  distribution around the world have 6 eyes and are slow moving  , the genus Scytodes are known from the names spitting spiders ,.Female Scytodes univittata   can be characteristic by :large round cephalothorax length:4.45 mm , abdomen length 3.50, total body length  7.95 mm and V-shaped of  fovea, scutela triangle and large  with long  thin legs femur I have two row of spines then  spineless are in IV femur , coloration  is yello

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Publication Date
Fri Mar 06 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Building HEC-RAS model to detect the areas of Water Cycle Interruption in river stream and their sections
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The purpose of this paper is to build a simulation model by using HEC-RAS software to simulate the reality of water movement in the main river of Basra City (South of Iraq) which is known as Siraji-Khoura River. The main objective of the simulation is to detect areas where the water cycle is interrupted in some stations of the river stream, as this river has become an outlet for the disposal of sewage, leading to pollution and causing weakness in some sections of the river & obstructing the water cycle that takes place between this river and Shatt al – Arab river. A field survey data of the river and its banks were adopted to derive the grades, longitudinal and cross sections of the river, these data included three-dimensional coordinates

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
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     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Sat Dec 02 2023
Journal Name
International Journal Of Applied Engineering & Technology
ASSESSING THE CONCENTRATIONS OF SOME HEAVY METALS IN BLOOD SAMPLES OF CHILDREN DIAGNOSED WITH AUTISM SPECTRUM DISORDERS IN BAGHDAD CITY
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Environmental Science And Development
Estimation of the Concentrations of Some Pollutants Resulting from the Use of Arabian Bakhour and Their Effect in Patients with Asthma in the City of Baghdad
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This research focus on studying 3 types of Bakhour in the markets of Baghdad city and assessing their impact on the quality of life for asthmatic whom used Bakhour at their houses through investigating particles physical properties, also estimating the levels of heavy metals (Cd, Cu, Mn, Pb and Zn), Particulate Matter PM2.5, PM10, Total Volatile Organic Compounds (TVOC) and formaldehyde (HCHO). The quality of life for asthmatic patients whom use Bakhour was assessing by Mini Asthma Quality of Life Questionnaire. The results indicated that shapes of Bakhour particles were irregular or spherical. Burning process generated the higher percent of PM ˂1μm. Type 2 Bakhour showed the highest percent of <1μm which was 73%.The amount of

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