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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
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Distribution of Some Heavy Metals in Tigris River middle of Iraq
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This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Tue Dec 15 2020
Journal Name
Aip Conference Proceedings
Land cover change for Baghdad City in the period 1986 to 2019
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Earth cover of the city of Baghdad was studied exclusively within its administrative border during the period 1986-2019 using satellite scenes every five years, as Landsat TM5 and OLI8 satellite images were used. The land has been classified into ten subclasses according to the characteristics of the land cover and was classified using the Maximum Likelihood classifier. A study of the changing urban reality of the city of Baghdad during that period and the change of vegetation due to environmental factors, human influences and some human phenomena that affected the accuracy of the classification for some areas east of the city of Baghdad is presented. The year 2019 has been highlighted because of its privacy in changing the land cover of th

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design an Algorithm to Calculate the Inverse Permutations Of the Symmetric Group Sn In Computer
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  The search is an application for one of the problems of mathematics in the computer; as providing construction and design of a major program to calculate the inverse permutations of the symmetric group Sn , where 1 ≤ n ≤ 13; using some of the methods used in the Number Theory by computer . Also the research includes design flow chart for the main program and design flow chart for the program inverse permutations and we give some illustrative examples for different symmetric groups and their inverse permutations.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Applying Geoaccumulation Index and Enrichment Factor for Assessing Metal Contamination in the Sediments of Euphrates River, Iraq
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The current study looked into heavy metal poisoning of the Euphrates river which runs from Al-Kifl to Kufa in Iraq. One of the goals of this research was to determine the pollution levels and the contamination sources. We looked at six heavy metal (Cd, Pb, Zn, Cr, Fe, and Mn) characteristics in sediment, taking samples from six sites along the Euphrates every season from March 2020 to January 2021. To assess pollution levels, three indices were chosen: enrichment factor (EF), geo-accumulation index (I-geo) and contamination factor (CF). According to EF, the Cd and Pb elements recorded considerable enrichment, very high enrichment and extremely high pollution at practically all sites in four seasons, while the remainder of the HMs recorde

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Evaluation of Vanadium Contamination in Some Soils of the East Baghdad Oil Field
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     Since oil is the primary source of vanadium in the environment and crude oil has a correspondingly high percentage of vanadium. Vanadium is crucial as a sign of oil contamination. Twenty soil samples were taken from various locations surrounding the East Baghdad oil field in Iraq during February 2022 and then analyzed to determine the effects of industrialization along with urbanization-related pollutants. The soil samples were analyzed using spectrophotometry analysis. In soil samples taken from the research area, vanadium concentrations range from (0.26 to 1.2 ppm). The contamination (CF), geoaccumulation (Igeo) and Enrichment factors (EF) indicated that all the soil samples are uncontaminated.

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
A Proposed Approach to Determine the Edges in SAR images
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Radar is the most eminent device in the prolonged scattering era The mechanisms involve using electromagnetic waves to take Synthetic Aperture Radar (SAR) images for long reaching. The process of setting edges is one of the important processes used in many fields, including radar images, which assists in showing objects such as mobile vehicles, ships, aircraft, and meteorological and terrain forms. In order to accurately identify these objects, their edges must be detected. Many old-style methods are used to isolate the edges but they do not give good results in the  determination process. Conservative methods use an operator to detect the edges, such as the Sobel operator which is used to perform edge detection where the edge does

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Publication Date
Fri Jan 18 2019
Journal Name
Asian Journal Of Chemistry
Determination of Chemicals and its Isotopic Composition in Tigris River,Iraq
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Stable isotope (?18O, ?D) values were determined along with the chemical compositions at 10 different locations along the Tigris river between Baghdad-Ammara cities of Iraq. The physico-chemical parameters and isotopic data were measured. The sampling site represents 34 % of total Tigris river in the republic of Iraq. The systematically increased in values of stable isotope as move from the downstream of the river and the most significantly appears at Kut lake. This increase occurs as a result of several factors, viz. (a) evaporation occurs low water level in the river and its tributaries, and (b) return flow water to the river from irrigation water in groundwater systems. The change in ion distribution and in the isotopic values related di

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Publication Date
Thu Mar 21 2019
Journal Name
J. Eng. Appl. Sci
Developing an Arabic handwritten recognition system by means of artificial neural network
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The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

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