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Tamper Detection in Color Image
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In this work a fragile watermarking scheme is presented. This scheme is applied to digital color images in spatial domain. The image is divided into blocks, and each block has its authentication mark embedded in it, we would be able to insure which parts of the image are authentic and which parts have been modified. This authentication carries out without need to exist the original image. The results show the quality of the watermarked image is remaining very good and the watermark survived some type of unintended modification such as familiar compression software like WINRAR and ZIP

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Publication Date
Wed Dec 20 2023
Journal Name
Migration Letters
Women's Image in Arabic Songs (An Analytical Study of how Women Appear in the Most Viewed Songs on YouTube for the Year 2021)
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Publication Date
Thu Apr 30 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Detection of Commercial Cheating for Some Kinds of Local Markets retailed Medicinal Oils: Detection of Commercial Cheating for Some Kinds of Local Markets retailed Medicinal Oils
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The aims of this study are to explore the commercial artifacts in the following three kinds of vegetables oils, Nigella Sativa, Trigonella foenum-graecum Linn,and Zingiber officinale. These oils have been very popular medicinal plants which are commonly used in traditional medicine .These commercial oils have been compared with the extracts of these plants.
The physical properties of extracts and commercial oils of these plants have been stuied. We observed that the refractive index of the plants matches and non-significant, while specific gravity of Nigella Sativa has similar specific gravity in both extracts and commercial oil in contrast with Trigonella foenum Linn,and Zingiber officinale and we found significant difference (P&lt

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Publication Date
Sat Oct 04 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Validity of 3D Reconstructed Computed Tomographic Image in Using Craniometrical Measurements of the Skull for Sex Differentiation (An Iraqi Study)
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Background: The skull offers a high resistance of adverse environmental conditions over time, resulting in the greater stability of the dimorphic features as compared to other skeletal bony pieces. Sex determination of human skeletal considered an initial step in its identification. The present study is undertaken to evaluate the validity of 3D reconstructed computed tomographic images in sex differentiation by using craniometrical measurements at various parts of the skull. Materials and Method: 3D reconstructed computed tomographic scanning of 100 Iraqi subject, (50 males and 50 females) were analyzed with their age range from20-70 years old. Craniometrical linear measurements were located and marked on both side of the 3D skull images.

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Publication Date
Sat Jun 04 2022
Journal Name
Al–bahith Al–a'alami
The Media Image of Afghan Women as Reflected by News Websites in 2021: an Analytical Study of Russia Today site
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International news websites, including Russia Today, pay special attention to the media image of Afghan women, especially after the Taliban movement took control of Afghanistan. Therefore, it was necessary to know the image of the Afghan woman, the fate of the rights she acquired in recent years, and the transformations that affected her after the Taliban took control of the government, and studied them on international news sites, specifically Russia Today.

          The researcher summarized the problem of this study in the following question: What is the media image of the Afghan woman on the Russia Today news site?

         

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Publication Date
Tue Jan 01 2013
Journal Name
The Iraqi Journal Of Veterinary Medicine
Detection of methicillin or multidrug resistant Staphylococcus aureus (MRSA) in locally produced raw milk and soft cheese in Baghdad markets.
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In order to investigate the presence of methicillin or multidrug resistant Staphylococcus aureus in food-chain especially Cows raw milk and white raw soft cheese and its whey, a total of 30 samples were collected randomly from different markets in Baghdad Province during December 2012 till February 2013, in which samples were analyzed by a standard isolation protocols of food microbiology with some modification processing by new, modern and rapid technology tools such as chromogenic medium Baird-Parker agar, Electronic RapIDTM Staph Plus Code Compendium Panel System (ERIC®) Dryspot Staphytect Plus and Penicillin Binding Protein (PBP2') Plus assays; as well as, studying the susceptibility of isolates to different selected antibiotics. The r

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Publication Date
Tue Apr 20 2021
Journal Name
Ndian Journal Of Forensic Medicine & Toxicology,
Detection Levels of Cytokines (IL-6 and IL-18) and Microbial Parameters in Patients with Renal Failure in Diyala Province
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Publication Date
Wed Mar 28 2018
Journal Name
Indian Journal Of Natural Sciences
Detection of the Main Mycotoxins in Feed of Horses in Al-Zawra'a Park and Study their Effects on Hematological Feature
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Publication Date
Thu Jan 07 2021
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Assessment of Employees’ Knowledge Concerning Contributing Factors and Early Detection for Prostate Cancer in Baghdad University Colleges in bab-Almudam
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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