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.
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
... Show MoreWildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreOne 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
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
ST Alawi, NA Mustafa, Al-Mustansiriyah Journal of Science, 2013
The performance and lifetime of the flexible asphalt pavement are mainly dependent on the interfacial bond strength between layer courses. To enhance the bond between layers, adhesive materials, such as tack coats, are used. The tack coat itself is a bituminous material, which is applied on an existing relatively non-absorbent surface to ensure a strong bond between the old and newly paved layer. The primary objective of this study was to evaluate the effects of various types of tack coat materials on interlayer bond strength and to determine the optimal application rate for each type. The tack coat types used in this paper were RC-70, RC-250, and CSS-1h. Both laboratory-prepared and field-constructed hot mix asphalt concrete pavements usin
... Show MoreTo decrease the impact on the environment of building waste, the recycled aggregate may be used in various sustainable engineering applications, such as roller compacted concrete pavement (RCCP). This research examined how using recycled aggregate as a partial replacement for natural aggregate as coarse or fine affected the mechanical properties of roller-compacted concrete pavement. The recycled aggregate was crushed and sieved to coarse and fine aggregate before being used in the roller-compacted concrete pavement. Compressive strength, splitting tensile strength, and flexural strength were all evaluated after the samples were prepared at 28 and 90 days of curing. According to the study's findings, the partial replacem
... Show MoreDue to economic reasons or need for environmental conservatism or also preserve the natural resources; there has been an increasing shift towards the use of reclaimed asphalt pavement (RAP) materials in the pavement construction industry. Therefore, use the Reclaimed Asphalt Pavement (RAP) has been enormously increased in pavement construction and has been become common practice in many countries. Nevertheless, this is a relatively new concept in Iraq, and has to be remarked that is not used RAP in the production of HMA and this valuable material is mostly degraded. For this purpose, the reclaimed materials were collected from deteriorated pavement segments. The components of asphalt mixtures consist of: two asphalt penetration grades (40-5
... Show MoreFlexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac
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