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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 with a medium validity of 76%. There are two kinds of methods, manual and automated, for distress evaluation that are used to assess pavement condition. A committee of three expert engineers in the maintenance department of the Mayoralty of Baghdad did the manual assessment of a highway in Baghdad city by using a Pavement Condition Index (PCI). The automated method was assessed by processing the videos of the road. By comparing the automated with the manual method, the accuracy percentage for this case study was 88.44%. The suggested method proved to be an encouraging solution for identifying cracks and potholes in asphalt pavements and sorting their severity. This technique can replace manual road damage assessment.

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Publication Date
Wed Mar 05 2025
Journal Name
Iraqi Journal Of Biotechnology,
Molecular Detection of Esp and Ace Genes in Enterococcus faecalis Isolated from Endodontic Infections
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Enterococcus faecalis is a natural inhabitant of the human gastrointestinal tract but can become dominant and cause infections when the intestinal homeostasis is disrupted. Enterococcal bacteria are considered one of the main reasons for the failure of endodontic treatment. This study aim to isolation and identification of E.faecalis depended on phenotype and molecular method, the phenotypic patterns using traditional biochemical methods, and then diagnosed it based on the genotypes and using specialized primers for 16srRNA and D-Ala: D-Ala ligase genes using polymerase chain reaction, In order to achieve successful treatment, it is necessary to study the bacterial behavior within the root canal system together with their resistance and def

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Detection of Type 2 Diabetes Mellitus in Serum from Women with Polycystic Ovarian Syndrome
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Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti ?-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ? 0.05) and there was negative results for anti-GAD Ab and anti ?-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ? 0.05), these

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Publication Date
Sat Jun 15 2024
Journal Name
Iraqi Journal Of Laser
Estimation of mean photon number based on single photon detection of weak coherent pulses
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The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB

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Publication Date
Sun Jun 25 2023
Journal Name
World's Veterinary Journal
Phylogenetic Analysis and Detection of Drug Resistance Gene in Theileria annulata Isolated from Buffaloes
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Bovine theileriosis, caused by Theileria annulate, is disease affecting cattle and buffaloes worldwide. The current study aimed to screen the blood samples of 30 naturally suspected local buffaloes infected with Theileria species. The blood samples were initially examined by light microscopic and then the positive samples were subjected to PCR reactions. All 30 animals indicated clinical symptoms, such as high fever, loss of appetite, the presence of the hard tick, and enlargement of lymph nodes. The amplified products of 18S rRNA were analyzed, along with molecular detection of the drug-binding site alterations and interrelated changes in the cytochrome b (cyto b) gene. Blood smears revealed the presence of infected erythrocytes wi

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Publication Date
Mon Dec 01 2025
Journal Name
Sensors And Actuators A: Physical
IoT based hybrid optical-wireless microstructured optical fiber sensor network for cadmium ions detection
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Publication Date
Tue Jun 24 2025
Journal Name
Baghdad Science Journal
Accelerating Face Mask Detection Training Model Based on Multi-GPUs and Multi-core CPU
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Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

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Publication Date
Sun Aug 21 2022
Journal Name
International Journal Of Health Sciences
Molecular detection of fimH& mrkDgenes of strong biofilm producers & MDR Klebsiella pneumoniae
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Klebsiella pneumoniae is an adaptable pathogen that forms biofilms on a variety of surfaces. This study's objective was to identify the presence of fimbrial genes (types 1 and 3) in K. pneumoniae strains isolated from various clinical sources based on their antibiotic resistance and ability to form biofilms. According to identification utilizing the vitek 2 technology and confirmation by molecular identification targeting the 16S rRNA gene with a particular primer, forty isolates were identified from clinical specimens. The vitek 2 compact system was utilized to evaluate the antibiotic susceptibility of all the isolates. The findings revealed a range of resistance percentages, including 52.5% for Penicillin, 40.5% for Trimethoprim/S

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparative Study for the Early Detection of the most Important Factors Leading to Preeclampsia
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The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

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Publication Date
Tue May 05 2015
Journal Name
The 16th Science Conference/ College Of Basic Education.
Detection of Microbial and Chemical Contamination in Canned Meat Available in Baghdad Local Markets
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