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Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Wed Dec 28 2022
Journal Name
Al–bahith Al–a'alami
Content of Data Journalism in Security Topics - Security Media Cell Model Research extracted from a master’s thesis
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This paper aims at the analytical level to know the security topics that were used with data journalism, and the expression methods used in the statements of the Security Media Cell, as well as to identify the means of clarification used in data journalism. About the Security Media Cell, and the methods preferred by the public in presenting press releases, especially determining the strength of the respondents' attitude towards the data issued by the Security Media Cell. On the Security Media Cell, while the field study included the distribution of a questionnaire to the public of Baghdad Governorate. The study reached several results, the most important of which is the interest of the security media cell in presenting its data in differ

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Publication Date
Fri Jun 16 2023
Journal Name
Journal Of Humanities And Social Sciences Researches
The Role and Importance of Electronic Automation in Banking Service Development: A Case Study of the Commercial Bank of Iraq
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Electronic banking services appeared as a result of laying the foundations for the application of electronic automation in the banking field, and despite the clear expansion in its adoption and implementation as an inevitable necessity imposed by international and national developments, its application was not ideal according to the level that was expected to occur after the abandonment of traditional banking services, which produced some risks Which is evident in the absence of a legal system, whether at the level of proving and authoritative electronic banking services such as electronic signature, Or at the level of protecting the confidentiality of these services and ensuring that they are not exp

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Prepare Maps For Greenhouse Gases With Some Weather Elements For Baghdad City Using Data Observation And Arc-GIS Techniques
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Abstract<p>Air pollution refers to the release of pollutants into the air that are detrimental to human health and the planet as a whole.In this research, the air pollutants concentration measurements such as Total Suspended Particles(TSP), Carbon Monoxides(CO),Carbon Dioxide (CO2) and meteorological parameters including temperature (T), relative humidity (RH) and wind speed & direction were conducted in Baghdad city by several stations measuring numbered (22) stations located in different regions, and were classified into (industrial, commercial and residential) stations. Using Arc-GIS program ( spatial Analyses), different maps have been prepared for the distribution of different pollutant</p> ... Show More
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Photoacoustic Imaging for Tumor Detection: An in vitro Simulation Study
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Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4

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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
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Data visualization and distinct features extraction of the comet Ison 2013
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The distribution of the intensity of the comet Ison C/2013 is studied by taking its histogram. This distribution reveals four distinct regions that related to the background, tail, coma and nucleus. One dimensional temperature distribution fitting is achieved by using two mathematical equations that related to the coordinate of the center of the comet. The quiver plot of the gradient of the comet shows very clearly that arrows headed towards the maximum intensity of the comet.

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Publication Date
Sun Jun 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Recent Tools of Software-Defined Networking Traffic Generation and Data Collection
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أثبتت الشبكات المحددة بالبرمجيات (SDN) تفوقها في معالجة مشاكل الشبكة العادية مثل قابلية التوسع وخفة الحركة والأمن. تأتي هذه الميزة من SDN بسبب فصل مستوى التحكم عن مستوى البيانات. على الرغم من وجود العديد من الأوراق والدراسات التي تركز على إدارة SDN، والرصد، والتحكم، وتحسين QoS، إلا أن القليل منها يركز على تقديم ما يستخدمونه لتوليد حركة المرور وقياس أداء الشبكة. كما أن المؤلفات تفتقر إلى مقارنات بين الأدوات والأ

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
A Comparison between Ericson's Formulae Results and Experimental Data Using New Formulae of Single Particle Level Density
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The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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