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Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different resolutions. By considering features from multiple levels, the detection algorithm can better capture both global and local characteristics of the manipulated regions, enhancing the accuracy of forgery detection. To achieve a high accuracy rate, this paper presents a variety of scenarios based on a machine-learning approach. In Copy-Move detection, artifacts and their properties are used as image features and support Vector Machine (SVM) to determine whether an image is tampered with. The dataset is manipulated to train and test each classifier; the target is to learn the discriminative patterns that detect instances of copy-move forgery. Media Integration and Call Center Forgery (MICC-F2000) were utilized in this paper. Experimental evaluations demonstrate the effectiveness of the proposed methodology in detecting copy-move. The implementation phases in the proposed work have produced encouraging outcomes. In the case of the best-implemented scenario involving multiple trials, the detection stage achieved a copy-move accuracy of 97.8 %. 

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
The Influence of NMI against Modularity in Community Detection Problem: A Case Study for Unsigned and Signed Networks
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Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

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Publication Date
Wed Oct 07 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Assessment the Effect of Lactobacillus Acidophilus on Escherichia Coli Serotype O157:H7 with Detection of Some Virulence Factors
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Aim: To evaluation the effect of Lactobacillus acidophilus on Enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7 with detection of some virulence factors. Methods: Two hundred and fifty specimens (stool) from children under five years for both sexes were collected from some hospitals. All isolates were diagnosed according to morphological characteristics, biochemical tests. Monoplex pattern of PCR was used also for detection different genes in (7) Escherichia coli )O157:H7 (isolates; include 16SrRNA, eae, lifA, Stx1,Stx2 that encoded for ribosomal RNA, intimin, lymphocyte inhibitory factor, shiga toxins. Three types of probiotics strains were obtained, Lactobacillus fermentum, Lactobacillus plantarum and Lactobacillus acidophilus (A

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Detection of 16S rRNA Methylases and Co-Resistance with β-lactams among Klebsiella pneumoniae Isolates from Iraqi Patients
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Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 25 (50%) of isolates were resistant to gentamicin (≥16µg/ml), 22 (44%) of isolates were resistant to amikacin (≥64 µg/ml), 21 (42%) of isolates were resistant to ertapenem (≥8 µg/ml), 18 (36%) of isolates were resistant to imipenem (4- ≥16µg/ml), 43 (86%) of isolates were resistant to ceftriaxone (4- ≥64 µg/ml), 42 (84%) of isolates were resistant to ceftazidime (1

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Fri May 23 2025
Journal Name
Reproductive Health Of Woman
Molecular detection of Rubella virus (1E genotype) in clinical sample of pregnant women, and it’s related to abortion
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Pregnant women who have rubella may potentially pass the infection on to their unborn offspring. A congenital rubella infection can result in a miscarriage, stillbirth, and congenital rubella syndrome. The only member of the Togaviridae family’s Rubivirus genus, the Rubella virus (RV) is a positive-polarity, single-stranded RNA virus genome surrounded by a lipoprotein envelope with spike-like, hemagglutinin-containing surface projections.The objective: to determine the Rubella virus (1E genotype) in pregnant woman and its relation to spontaneous miscarriage.Materials and methods. A total of 174 women which visited Al-Elweya Teaching Hospital, Baghdad, Iraq, were screened according to the following criteria: women with a history of

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Publication Date
Sun May 18 2025
Journal Name
Discover Food
Analysis of the effectiveness of natural treatments for preserving apricots and the YOLOv7 application for early damage detection
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Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa

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Publication Date
Thu May 01 2025
Journal Name
Microbes And Infectious Diseases
Molecular detection and the frequency of a pore-forming toxin in Enterococcus faecalis isolated from urinary tract infections
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Publication Date
Tue Jul 01 2025
Journal Name
Egyptian Journal Of Medical Microbiology
Human Mammary Tumor Virus Detection and APOBEC3G Expression in Breast Cancer: A Molecular Analysis of Iraqi FFPE Tissues
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Publication Date
Wed Sep 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
UAV-STNet: A Hybrid U-Net–Transformer–LSTM Architecture for Real-Time Object Detection in UAV Video Surveillance
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It is difficult to perform real time object detection in Uncrewed Aerial Vehicle(UAV) based video surveillance because of the dynamic movement of camera, scale, occlusion, variation of illumination and limited power availability on-board of the computer. Purpose: In this paper of researches, the author suggests the proposed UAV Spatial-Temporal Network(UAV-STNet), which is a hybrid model of spatio-temporal deep learning model that is expected to improve the accuracy of the detection, balance of time, and real-time performance. Approaches: techniques: The proposed framework incorporates U-Net representing the system of total encoder involving extraction of multiscale space features mode, Transformer attention module which will involve global

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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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