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Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensities. In the third stage, the boundary of the target object is extracted, and in the fourth and fifth stages, respectively, the region of interest (ROI) is highlighted and reconstructed. Our model was tested and evaluated using realistic scenarios which include outdoor and indoor scenes. The results reflect the ability of our approach to detect and remove shadows and reconstruct a shadow free image with a small error of approximately 6%.

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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 Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Isolation and Identification of Salmosamonella typhi from clinical samples with molecular detection of O-antigen encoded genes
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Abstract

Antibiotic treatment of  S.typhi is difficult as compared to treatment of acute infection. Antibiotic resistance carried against S.typhi  by using 6 kinds of antibiotics from  different classes, their results  showed that all isolates were  high resistance to Ampicillin (99%), Gentamicin (98%), Amikacin (79%) and   less  resistances  Trimethoprim (55%) ,  Imipenem (60%)  and Ceftriaxone(66%)  .

The present study focused on the molecular detection of Wzx flippase, Wzy polymerase genes in some Salmonella typhi isolates, Samples were collected from typhoid patients by classical lab work. Antibiotics susceptibilit

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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
Sat Jun 30 2018
Journal Name
International Journal Of Medical Research & Health Sciences
Assessment of the Healthy Women by Detection and Determination of Cells in Conventional Pap Stained Cervical Smear Images
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Introduction: A Pap test can detect pre-cancerous and cancerous cells in the vagina and uterine cervix. Cervical cancer is the easiest gynecologic cancer to be prevented and diagnosed using regular screening tests and follow-up. This study aimed to estimate the cytological changes and the precancerous lesions using Pap smear test and visual inspection of the cervices of Iraqi women, and also to determine the possible relationship of this cancer with patients’ demographic characteristics. Methods: The study included 140 women aged (18-67) years old referred to the National Cancer Research Center (NCRC), Baghdad, Iraq, during the period 2011-2016. Both visual inspections of the uterine cervix and Papanicolaou smear screening were performed

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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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
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Detection of Leishmania tropica Using Nested-PCR and Some of Their Virulence Factors in Thi-Qar Province, Iraq
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Cutaneous leishmaniasis is one of endemic diseases in Iraq. It is considered as widely health problem and is an uncontrolled disease. The aim of the study is to identify of Leishmania species that cause skin lesions among patients in Thi-Qar Province, South of Iraq, also to detect some virulence factors of L. tropica. This study includes three local locations, Al-Hussein Teaching, Suq Al-Shyokh General and Al-Shatrah General Hospitals in Province for the period from the beginning of December 2018 to the end of September 2019. The samples were collected from 80 patients suffering from cutaneous leishmaniasis, both genders, different ages, various residence places and single and multiple lesions. Nested-PCR technique was

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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
Wed Mar 02 2022
Journal Name
International Journal Of Early Childhood Special Education
Understanding the life applications of green chemistry among students of the College of Education for Pure Sciences, Ibn al-Haytham in Iraq
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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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