Preferred Language
Articles
/
bRb1DIcBVTCNdQwCUTOQ
A Viscoplastic Modeling for Permanent Deformation Prediction of Rubberized and Conventional Mix Asphalt
...Show More Authors

Crossref
View Publication
Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
INFLUENCE OF AMBIENT TEMPERATURE ON STIFFNESS OF ASPHALT PAVING MATERIALS
...Show More Authors

Asphalt pavement properties in Iraq are highly affected by elevated summer air temperatures. One of these properties is stiffness (resilient modulus). To explain the effect of air temperatures on stiffness of asphalt concrete, it is necessary to determine the distribution of temperatures through the pavement asphalt concrete layers. In this study, the distribution of pavement temperatures at three depths (2cm,7cm, 10cm) below the pavement surface is determined by using the temperature data logger instrument. A relationship for determining pavement temperature as related to depth and air temperature has been suggested. To achieve the objective of this thesis, the prepared specimens have been tested for indirect tension in accordance with

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Influence of Temperature on Mechanical Properties of Asphalt Concrete Mixture
...Show More Authors

Asphalt binder is a thermoplastic material that conducts as an elastic solid at lower service temperatures or throughout fast loading rate. At a high temperature or slow rate of loading, asphalt binder conducts as a different liquid. The classical duplication generates a required to assess the mechanical properties of asphalt concrete at the anticipated service temperature to reduce the stress cracking, which happens at lower temperatures, fatigue, and the plastic deformation at higher temperatures (rutting). In this study, an achievement was made to assess the effect of temperature on the mechanical characteristics of asphalt concrete mixes. A total of 132 asphalt concrete samples were attended utilizing two asphalt cement grades (40-50) a

... Show More
Preview PDF
Scopus (5)
Crossref (4)
Scopus Crossref
Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Effect of Hydrated Lime on Moisture Susceptibility of Asphalt Mixtures
...Show More Authors

Moisture induced damage can cause a progressive deterioration in the performance of asphalt pavement by the loss of adhesion between asphalt binder and aggregate surface and/or loss of cohesion within the binder in the presence of water. The objective of this paper is to improve the asphalt mixtures resistance to moisture by using hydrated lime as an anti-stripping additive. For this purpose, two types of asphalt binder were utilized; asphalt grades (40-50) and (60-70) with one type of aggregate of 19.0 mm aggregate nominal maximum size, and limestone dust as a mineral filler. Marshall method was adopted to find the optimum asphalt content. Essentially, two parameters were determined to evaluate the moisture susceptibili

... Show More
View Publication Preview PDF
Crossref (8)
Crossref
Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering
Effect of Filler Types on Moisture Damage of Asphalt Mixtures
...Show More Authors

The filler in the asphalt mixture is essential since it plays a significant role in toughening and stiffening the asphalt. Changes in filler type can lead the asphalt mixtures to perform satisfactorily during their design life or degrade rapidly when traffic and environmental effects are considered. This study aims to assess the impact of filler types such as limestone dust (LS) and hydrated lime (HL) on Marshall characteristics and moisture damage in asphalt mixtures. Three different percentages of HL were employed in this study to partially replace the LS mineral filler: 1.5, 2.0, and 2.5% by aggregate weight. Furthermore, a control mixture was created with 7% LS by overall aggregate weight for the wearing course layer. The Marsha

... Show More
View Publication
Scopus Crossref
Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Two Domain Flow Method for Leachate Prediction Through Municipal Solid Waste Layers in Al–Amari Landfill Site
...Show More Authors

Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

... Show More
View Publication Preview PDF
Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Effect of Testosterone Enanthate Modeling of Polycystic Ovary on Liver Irs-2 mRNA Expression in Rats: A Brief Report
...Show More Authors

There are many animal models for polycystic ovary (PCO); using exogenous testosterone enanthate is one of the methods of induction of these models. However, induction of insulin resistance should also be studied in the modeling technics. Therefore, the present study aims to investigate the expression of insulin receptor substrate (Irs)-2 mRNA in the liver tissue of rat PCO model. Nineteen Wistar rats were divided into three groups; (1) PCO modeling group (N =7) received daily 1.0 mg/100g testosterone enanthate solved in olive oil along with free access dextrose water 5%, (2) vehicle group (N =6), which handled like the PCO group, but did not receive testosterone enanthate, (3) control group (N =6) with standard care. Al

... Show More
View Publication Preview PDF
Scopus (3)
Scopus Clarivate Crossref
Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
...Show More Authors

View Publication
Crossref
Publication Date
Fri Aug 18 2023
Journal Name
Journal Of Research In Medical And Dental Science
Morphologic Evaluation of the Permanent Mandibular First Molar within an Iraqi Population Using Cone Beam Computed Tomography (Retrospective Study)
...Show More Authors

Preview PDF
Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
...Show More Authors

Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

... Show More
View Publication
Crossref (2)
Crossref
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
...Show More Authors

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

... Show More
View Publication Preview PDF
Scopus (7)
Crossref (4)
Scopus Crossref