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Classification of al-hammar marshes satellite images in Iraq using artificial neural network based on coding representation
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Publication Date
Sat Jul 12 2025
Journal Name
Al–bahith Al–a'alami
The Reliance of the Public of Baghdad on News Broadcasts on Satellite Channels as a Source of Information
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The importance of news broadcasts in society has increased after the domination of television over the mass media, especially after emerging the satellite channels, and spreading the satellite dishes among the public at large.

As well as the great role played by the modern technology in the transmission of news and events happening at once. Such role has contributed, significantly, in changing the concept and values ​​of the news. The live broadcast of the events filmed is the news itself.

In the midst of the great transformations and circumstances that Iraq went through after 2003, which witnessed political and security instability, and the large increase in the number of media, especially satellite channels, in Iraq

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Publication Date
Mon Jul 01 2019
Journal Name
Biocatalysis And Agricultural Biotechnology
Determination of Diazinon in fruit samples using electrochemical sensor based on carbon nanotubes modified carbon paste electrode
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
The role of satellite channels in the dissemination of consumer culture
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This study is concerned look at the role of satellite channels in the dissemination of
consumer culture that has become part of our everyday lives , which is a dangerous
phenomenon on society , so the study is aimed at introducing the concept of consumer culture
and the risks to individuals , which conducted a field study on a sample of students from the
University of Baghdad, as they represent an important category of the society they are a class
of young people to get to know the impact of satellite television on them through their various
programs and serials, films and ads may develop consumer culture they have , including in
respect of ideas and information , where the questionnaire was developed to ensure diffe

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Publication Date
Thu Apr 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Phytoplankton community within Al-Auda marsh in maysan province southern Iraq
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Abstract<p>Phytoplankton assemblage in relation to physical and chemical characteristics of water in Al-Auda marsh of Maysan province southern Iraq was assessed from November 2012 to July 2013. Six sampling sites were chosen to examine all phytoplankton species in the study area. A total of 246 species and seventy-five genera have been recognized belonging to twelve phytoplankton classes as follows: Bacillariophyceae (106 taxa), Chlorophyceae (34 taxa), Euglenophyceae (29 taxa), Cyanophyceae (29 taxa), Conjugatophyceae (19 taxa), Mediophyceae (10 taxa), Cryptophyceas (5 taxa), Coscinodiscophyceae (4 taxa), Chrysophyceae (4 taxa), Dinophyceae (3 taxa), Trebouxiophyceae (2 taxa) whereas Compsopogonophyceae record</p> ... Show More
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Publication Date
Sat Oct 01 2022
Journal Name
Al–bahith Al–a'alami
AL-AILM MAGAZINE: The Beginning Of The Era Of Specialized Journalism In Iraq
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The winds of change witnessed by the Ottoman Empire after the constitutional coup in 1908 carried the breezes of freedom, writers and journalists were finally able to express themselves, this change was reflected on intellectual and cultural life and on freedom of publication and expression , perhaps the first thing that was affected by this change was the press, it entered a new phase in which it got rid of those restrictions and limitations imposed by the Ottoman Sultanate concerning the right to issue newspapers and freedom of publication. Iraq was the first to witness a new phase of press relief, before the constitutional coup, it was possible to count on the fingers of the hand how many newspapers were issued, that number doubled to

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Publication Date
Mon Jan 01 2018
Journal Name
Asian Journal Of Chemistry
Levels and Distribution of Trace Metals in Surface Soils of Al-Diwaniya, Iraq
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In this work, monitoring of monthly variation (from May 2016 to October 2016) in the concentration of the metals (Co, Zn, Cd, Pb, Ni and Fe) from Al-Diwaniya city of Iraq. Investigation about the pollution with these metals was achieved from five selected sites locate in study area by flame atomic absorption spectroscopy. The results showed a wide variation in the levels of heavy metals from site to site and from month to month. A total of 180 surface soil samples were analyzed to detecting the pollution with selected samples. The resultsshowed that the highest concentration with Ni was 6.290 mg kg-1 while the lowest concentration detected with Ni was 0.080 mg kg-1. The results of pollution index (enrichment factor, contamination factor, po

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Publication Date
Fri Dec 15 2023
Journal Name
Bionatura
Evaluation of the quality of potable water in Al-Rusafa side, Baghdad, Iraq
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Safe drinking water is essential for the present and future generations' health. This study aims to assess drinking water quality in Baghdad's Al-Rusafa neighborhood. Water samples were taken from 32 neighborhoods on this side. The quality of the examined potable water samples differed depending on the water source. This investigation's pH, chlorine, EC, TDS, TSS, Cd, and Pb levels were below acceptable ranges. TDS levels in Al-Mada'in are more significant than acceptable (>600ppm) water levels. Bacteria have polluted six communities (Shigella, Salmonella, Escherichia coli, and Klebsiella). Bacterial quality of drinking water and gram-negative bacteria resistant to chlorine in Baghdad's municipal water supply. Regarding pH, the w

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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