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Detection of Microbial and Chemical Contamination in Canned Meat Available in Baghdad Local Markets
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Publication Date
Fri Jul 01 2011
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
CONTRACAECUMRUDOLPHII HARTWICH, 1964 (NEMATODA: ANISAKIDAE) IN THE CORMORANT PHALACROCORAXCARBO (LINNAEUS, 1758) WINTERING IN BAGHDAD AREA: A NEW HOST RECORD IN IRAQ
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The ascaroid nematode Contracaecum rudolphii was recovered in large numbers from the
digestive tract of Phalacrocorax carbo collected in Baghdad area, Central Iraq. The infection
rates of the two sexes of the bird and some meristic and morphometric characters of the
parasite that allowed species determination of the nematode Contracaecum rudolphii were
discussed. This finding represents a new host record for this nematode in Iraq.

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Historical Paths and the Growth of Baghdad Old Center
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Urban growth of cities is connected with three related problems, the first one, is the deterioration of the center, which is a mark for historical origin. The second is the emergence of city edge, which contradicts by the center. The third one is the rapid semi urbanism of the edge. Literature review showed that Baghdad historical center (Old Rusafa and Karkh) had grown in four morphological stages, during which main paths had been changed from those which were perpendicular to the river front to those parallel to it. Research problem is that “there is a knowledge gap about the direction and origin of paths within Baghdad old center, after its growth”. The first research hypothesis is, “the direction of paths within old Baghdad cen

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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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Publication Date
Thu Feb 28 2019
Journal Name
Multimedia Tools And Applications
Shot boundary detection based on orthogonal polynomial
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Publication Date
Wed Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Mon Feb 23 2026
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Sun Feb 02 2025
Journal Name
Engineering, Technology & Applied Science Research
Automated Glaucoma Detection Techniques: A Literature Review
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Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

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Publication Date
Mon Feb 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Differential evolution detection models for SMS spam
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With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

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Publication Date
Tue Jun 23 2020
Journal Name
Annal S Of Tropical Medicine & Public Health
Histological Evaluation of local application of Phyllunthus amarus extracted powder and its combination with fibronectin protein on Wound Healing of rats
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Background: A wound is defined as a break or damage in the skin, resulting from physical or thermal damage or as a result of the presence of an underlying medical or physical condition. Herbal medicine can be called one of the branches of medicine in various forms.Phyllunthus amarus is a small herb well known for its medicinal properties and widely used worldwide. P. amarus is an important plant of Indian Ayurvedic system of medicine. Fibronectin is a major component of the extracellular matrix. It is secreted by various cells, primarily fibroblasts, as a soluble protein dimer and is then assembled into an insoluble matrix in a complex cell-mediated process. Materials and methods: Forty rats will be subjected for a surgical operation

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