Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R2 of 0.93 and a mean squared error (MSE) of 0.0039. Results based on the sensitivity analysis and variable importance techniques showed that the percentage of aggregate passing the 4.75 mm sieve and the (rice) theoretical maximum specific gravity (Gmm) were the most significant factors in predicting axial permanent strain (εp). Furthermore, the connection weight method highlighted input variables’ distinct positive and negative impacts on permanent deformation.
In this paper, the concept of soft closure spaces is defined and studied its basic properties. We show that the concept soft closure spaces are a generalization to the concept of
Previous experimental studies have suggested that hot mixed asphalt (HMA) concrete using hydrated lime (HL) to partially replace the conventional limestone dust filler at 2.5% by the total weight of all aggregates showed an optimum improvement on several key mechanical properties, fatigue life span and moisture susceptibility. However, so far, the knowledge of the thermal response of the modified asphalt concrete and thermal influence on the durability of the pavement constructed are still relatively limited but important to inform pavement design. This paper, at first, reports an experimental study of the tensile fatigue life of HMA concrete mixes designed for wearing layer application. Tests were conducted under three different temperatur
... Show MoreBackground: The main drawback of soft lining materials was that they debonded from the denture base after a certain period of usage. Therefore, the purpose of this research was to determine the impact of oxygen and argon plasma treatment on the shear bonding strength of soft liners to two different kinds of denture base materials: conventional acrylic resin and high impact acrylic resin. Materials and Methods: Heat cure conventional and high impact acrylic blocks (40 for each group) were prepared. A soft liner connected the final test specimen of two blocks of each acrylic material. Shear bond strength (SBS) was assessed using universal testing machine. Additional blocks were also prepared for analyzing Vickers microhardness, contact ang
... Show MoreEstimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust M method after their development through the use of sequential approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate
... Show MoreEuphemism is an important linguistic phenomenon that tends to soften written or oral expressions. Thus, when translators or interpreters face expressions including euphemism, they need to know how to deal with them. The problem of the current paper lies in the effect of rendering euphemistic expressions inaccurately, as such expressions represent the cultural and terminological sense of the original language. Thus, rendering them improperly will affect the sense of the interpreted speech. For this, it is essential for translators in general and simultaneous interpreters in particular to know the importance of utilizing euphemism in the simultaneous interpreting field, which is the main aim of this paper. To this end, a systematic review
... Show MoreThe study aimed to test the hypothesis of Caldor to estimate the relationship between industrial production and GDP growth in Iraq using with Integration Framework and to determine the causal relationship in the short and long term using the error correction vector model for the period 1990-2016. the results showed a long-term equilibrium relationship between GDP and industrial output, while Ganger causality tests showed a causal relationship in the long run of GDP to output Subliminal thus illustrated the extent of the recession suffered by the industrial sector, which is supposed to be the driving force of the economy and the development and expansion of the productive base of the industry, so this study recommends attent
... Show MoreIn this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .
Abstract:
This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.
The comparison was done by simulation using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood with sample size (n = 30) is the best to represent the maternal mortality data after it has been reliance value param
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