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.
The research shows that the visual image plays an important role when Farzdaq in the issue of aesthetic perception, it enables him to feel a sense of artistic and mental perception to raise astonishment and admiration through his ability to link the optics through the suggestive image to carry us to a new vision imagined full of visual images.
Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co
... Show MoreIn today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har
... Show MoreAcute Respiratory Distress Syndrome (ARDS) causes up to 40% mortality in humans and is difficult to treat. ARDS is also one of the major triggers of mortality associated with coronavirus-induced disease (COVID-19). We used a mouse model of ARDS induced by Staphylococcal enterotoxin B (SEB), which triggers 100% mortality, to investigate the mechanisms through which Δ9-tetrahydrocannabinol (THC) attenuates ARDS. SEB was used to trigger ARDS in C3H mice. These mice were treated with THC and analyzed for survival, ARDS, cytokine storm, and metabolome. Additionally, cells isolated from the lungs were used to perform single-cell RNA sequencing and transcriptome analysis. A database analysis of human COVID-19 patients was also performed t
... Show MoreObjective(s): This study aims to evaluate the hardness of two commercially available cold cured acrylic resin material
(Vertex and PAN) when polymerized at different temperature in comparison to those polymerized by conventional
methods in air at 23C ± 5C.
Methodology: Eighty specimens, forty from cold cured acrylic (Vertex Type) and forty from cold cured acrylic (PAN
type) were prepared, flasking and packing procedure were done according to manufacturer direction and divided
according to processing as follow: 20 specimens (10 from Vertex type and 10 from PAN type) were processed in air for
two hours at 23C ± 5C under press (bench curing) as a control, and 60 specimens (30 from Vertex type and 30 from
PAN type) wer