The performance of asphalt concrete pavement has affected by many factors, the temperature is the most important environmental one which has a large effect on the structural behavior of flexible pavement materials. The main cause of premature failure of pavement is the rutting, Due to the viscoelastic nature of the asphalt cement, rutting is more pronounced in hot climate areas because the viscosity of the asphalt binder which is
inversely related to rutting is significantly reduced with the increase in temperature resulting in a more rut susceptible paving mixtures. The objective of this study is to determine the effect of temperatures variations on the permanent deformation parameters (permanent strain (p), intercept (a), slope (b), Alpha and Mu) as well as resilient strain (r) and resilient modulus (Mr). To achieve this objective, one aggregate gradation with 12.5mm nominal maximum size, two grades of asphalt cements (40-50 and 60-70) brought form Al- Daurah refinery, limestone dust filler has been used to prepare the asphalt concrete mixtures. 30 Marshall specimens were prepared to determine the optimum asphalt cement content. Thereafter, 30 cylindrical asphalt concrete specimens (102mm in diameter and 203 mm in height) are prepared in optimum asphalt cement and optimum ±0.5 percent. The prepared specimens were used in uniaxial repeated load test to evaluate the permanent deformation parameters of asphalt concrete mixes under the following testing temperature (5, 15, 25, 40 and 60c). The test result analyses appeared that Mr is decrease 51 percent when temperature increased from 5 c to 25 c and then decrease 22 percent with further increase in temperature from 25 c to 60 c. Also, the Alpha value decreases by a factor of 1.25 and 1.13 when temperature increases from 5 c to 25 c and 25 c to 60 c, espectively.
Finally, statistical models were developed to predict the Alpha and Mu parameters of permanent deformation.
The aim of the research is to investigate the effect of cold plasma on the bacteria grown on texture of sesame paste in its normal particle and nano particle size. Starting by using the image segmentation process depending on the threshold method, it is used to get rid of the reflection of the glass slides on which the sesame samples are placed. The classification process implemented to separate the sesame paste texture from normal and abnormal texture. The abnormal texture appears when the bacteria has been grown on the sesame paste after being left for two days in the air, unsupervised k-mean classification process used to classify the infected region, the normal region and the treated region. The bacteria treated with cold plasma, t
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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The reality of the field of construction projects in Iraq refers to needing for the development of performance in order to improve quality and reduce defects and errors and to control the time and cost, so there is needing for the application of effective methods in this area, one of the methods that can be applied in this area is the manner of Six Sigma. This research aims to enhance the performance and quality improvement for the construction projects by improving performance in the work of the implementation of the concrete structure depending on the Six Sigma methodology, and for the purpose of achieving the aim of the research, the researcher firstly depends on the theoretical study that include the concepts of qual
... Show MoreChronic kidney Failure, a progressive disease, includes both medical and biochemical features that damage kidneys and decrease their abilities to work effectively, this disease is characterized by a chronic disorders to both the innate and adaptive immune systems, generate a complex and not fully understood immune dysfunction. In the present study, (30) men suffering from chronic kidney failure with age in range (40-55) year and (30) healthy men within the same range of age were enrolled in this study. The aim of this study is to highlight the role of immunological aspect (IL-35), hormonal aspects (PTH), some functional proteins and immunological electrolytes in sera of chronic kidney failure (CKF) patients. Biochemical parameters were dete
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Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s
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Objective(s) : This study aimed at evaluating the seroprevalence of anti -HCV and studying the
correlation between hemophilia and risk factors for acquiring HCV such as age , marital status &
occupation among hemophilic patients .
Methodology : 210 hemophilic patients in children welfare teaching hospital/medical city/Baghdad–Iraq
(hemophilia center) were investigated using prepared questionnaire and tested for HCV infection, those
were measuring patient’s age, hemophilia types and severity, marital status, residency and history of
previous HCV infection .
Results : Most hemophilic patients were hemophilia A at severe , hemophilia was at age group 20 – 29
years , the majority of patients were unmarried a
This study was done to compare the morphometric parameters of placentas in well controlled patients with preeclampsia, diabetes, and preeclampsia-diabetes with that of normal uncomplicated placentas. Patients & Methods: A total of Twenty four placentas were freshly collected. Six placentas for control group and eighteen placentas for complicated group (preeclamptic-diabetic and preeclamptic--diabetic subgroups). The placentas were grossly examined (shape, number of cotyledons, weight, and thickness). After suitable fixation, tissue processing and sectioning, the sections were stained by hematoxylin and eosin to study the general morphology and morphometry of the following parameters: number of terminal villi, number of syncytial knots, numb
... Show MoreAbstract: Lymphoproliferative Disorders (LPDs) are a group of neoplasms affecting various cells within lymphoid system. Each type has different treatment a..70619
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The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete
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