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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 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Tue Sep 23 2025
Journal Name
Journal Of Plant Protection Research
Smart sprayer for weed control using an object detection algorithm (yolov5)
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Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore, researchers have been encouraged to...

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Tue Nov 20 2012
Journal Name
J. Of University Of Anbar For Pure Science
Laser Processing For Nanoscale Size Quantum Wires of AlGaAs/GaAs
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In this work we investigate and calculate theoretically the variation in a number of optoelectronic properties of AlGaAs/GaAs quantum wire laser, with emphasis on the effect of wire radius on the confinement factor, density of states and gain factor have been calculated. It is found that there exist a critical wire radius (rc) under which the confinement of carriers are very weak. Whereas, above rc the confinement factor and hence the gain increase with increasing the wire radius.

Publication Date
Fri Jun 30 2017
Journal Name
Journal Of Engineering
Aluminium Matrix Composites Fabricated by Friction Stir Processing A Review
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      Aluminum alloys widely use in production of the automobile and the aerospace because
they have low density, attractive mechanical properties with respect to their weight, better
corrosion and wear resistance, low thermal coefficient of expansion comparison with traditional
metals and alloys. Recently, researchers have shifted from single material to composite materials
to reduce weight and cost, improve quality, and high performance in structural materials.
Friction stir processing (FSP) has been successfully researched for manufacturing of metal
matrix composites (MMCs) and functional graded materials (FGMs), find out new possibilities
to chemically change the surfaces. It is shown th

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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Sat Nov 07 2020
Journal Name
Journal Of Advanced Research In Fluid Mechanics And Thermal Sciences
Fully Automated Measurement Setup for Photovoltaic Panel Performance Evaluation and Testing under LabVIEW Platform
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Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was

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