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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 results profile showed isolation, identification, confirmation and enumeration of 10 (33.4%) isolates of MRSA as 4 (13.4%) isolates from raw milk and 6 (20%) isolates from white raw soft cheese with its whey. These findings suggest presence of MRSA type in locally produced raw milk and soft cheeses in Baghdad markets thus recommended to monitoring these products periodically to inshore public health.

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Publication Date
Mon May 15 2017
Journal Name
International Journal Of Image And Data Fusion
Image edge detection operators based on orthogonal polynomials
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Scopus (33)
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Scopus (7)
Scopus
Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Wearable Detection Systems for Epileptic Seizure: A review
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The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Disc damage likelihood scale recognition for Glaucoma detection
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Abstract<p>Glaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to other eye illness such as myopia and cataracts. The impact of glaucoma can’t be cured; The Disc Damage Likelihood Scale (DDLS) can be used to assess the Glaucoma. The proposed methodology suggested simple method to extract Neuroretinal rim (NRM) region then dividing the region into four sectors after that calculate the width for each sector and select the minimum value to use it in DDLS factor. The feature was fed to the SVM classification algorithm, the DDLS successfully classified Glaucoma d</p> ... Show More
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Scopus (8)
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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Scopus (8)
Scopus
Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Scopus (31)
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Publication Date
Sun Dec 01 2024
Journal Name
Al-khwarizmi Engineering Journal
Defect Detection Using Thermography Camera Techniques: A review
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Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect

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Scopus (7)
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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of The College Of Education For Women
Assessing the Brief Book of the Modern and Contemporary History of Asia from the Perspective of the Students in the Department of History - University of Baghdad
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The current research aims to assess the Brief Book of the Modern and Contemporary History of Asia from the perspective of the students in the Department of History, University of Baghdad. The study is carried out in Iraq and the research group has included students of the Department of History in the College of Education--Ibn Rushd and the College of Education for Women- University of Baghdad. The chosen sample of the assigned research consisted of (72) students from third stage in the Department of History, which equals (0.38%) of the total group members amounted (188) female and male students representing (40) students from the College of Education--Ibn Rushd, and 32 students from

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Integration between hydrochemical and physical data with geographic information systems (GIS) for selecting the best locations groundwater wells in Baghdad city
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