To 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

Autorías: Muayad Kadhim Raheem, Lina Fouad Jawad. Localización: Opción: Revista de Ciencias Humanas y Sociales. Nº. 21, 2019. Artículo de Revista en Dialnet.

In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

The technological developments in the field of communication have witnessed considerable impact in the variables which exist in following up and conveying the events which link it’s meaning to political implications. This makes a number of satellite channels depend on the techniques of propaganda and use them in the news bulletins to achieve political aims and ends related to its formational directives where those channels allotted a considerable time in its programming transmission map to concentrate on the security and political status to complete the image of the informational scene according to the logic of its propaganda and styles in processing news for daily events.The technological developments in the field of communication hav

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de