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Zwitterionic ion chromatography coupled with ultraviolet detection for the quantification of 2-deoxyguanosine in human serum
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Scopus
Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment Knowledge and Attitudes of Baghdad University Students’ toward Human immunodeficiency virus / acquired immunodeficiency syndrome
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Objective(s): To assess Baghdad University students’ knowledge and attitudes toward HIV/AIDS, and to find out
the relationship of Baghdad University students’ knowledge and attitudes with certain variables (gender,
socioeconomic status, field of study).
Methodology: A descriptive analytic study was used to assess the knowledge and attitudes of Baghdad University
Students’ toward HIV/AIDS. The study was conducted (November 1st 2012 to July 15th 2013). A non-probability
(purposive sample) of 400 students (males-138 and females-262) were selected from four colleges and they were
in the fourth class, a probability (stratified random) method was used to select four colleges at University of
Baghdad as a study settin

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Publication Date
Mon May 09 2022
Journal Name
Biochemical And Cellular Archieve
INFLUENCE OF HUMAN LEUKOCYTE ANTIGEN HLA-DRB1 ON SUSCEPTIBILITY TO GIARDIA LAMBLIA INFECTION OF IRAQI PATIENTS
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Giardia lamblia is the worldwide most common intestinal protozoan parasite. It was indicated that Giardia is the most important agent that causes acute and chronic diarrhea in infants, young children and travelers. The aim was to detect the influence of host HLA alleles on the susceptibility to infection with G. lamblia in a sample of Iraqi patients. A total of (40) patients with giardiasis aged (14-39) years were registered. All of them were symptomatic and (40) healthy individuals matched age and sexes were included as controls. All patients were prepared to stool examination to detect G. lamblia and eliminated other pathogens, as well as human leukocyte antigen (HLA) class II alleles (DRB1) typing. The most common detected alleles in pat

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Publication Date
Sat Mar 08 2025
Journal Name
Fusion: Practice And Applications
Fast Numeric Sign Detection Using Adaptive Thresholding and Geometry of Optimized Fingers
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A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

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Scopus
Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi

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Scopus (1)
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Publication Date
Tue Jan 01 2019
Journal Name
Biochemical And Cellular Archives
Phenotypic and molecular detection of Escherichia coli efflux pumps from UTI patients
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Scopus (5)
Scopus
Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Crossref
Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Crossref (1)
Crossref
Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Scopus (32)
Crossref (22)
Scopus Crossref
Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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