In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.
Abstract: In accordance with contemporary Western thinking, power is an organized force with a high ability to achieve stability and social security because it possesses tools based on rational organization, which helps it to control the behavior of the individual and society and prevent them from practicing the processes of exclusion and discrimination against others in pursuit of their interests and needs. Vision The philosophers and thinkers of the theory of social contract can consolidate it, which changed the form and nature of power from the traditional heritage to the constructionWhich has contributed to the development and development of civil society - Western political, and despite the success of this experiment, especially aft
... Show MoreIn this work, we studied the effect of power variation on inductively coupled plasma parameters using numerical simulation. Different values were used for input power (750 W-1500 W), gas temperature 300K, gas pressure (0.02torr), 5 tourns of the copper coil and the plasma was produced at radio frequency (RF) 13.56 MHZ on the coil above the quartz chamber. For the previous purpose, a computer simulation in two dimensions axisymmetric, based on finite element method, was implemented for argon plasma. Based on the results we were able to obtain plasma with a higher density, which was represented by obtaining the plasma parameters (electron density, electric potential, total power, number density of argon ions, el
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Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
... Show MoreThe deliberation and exchanged of power is a matter of political importance For the Iraqi political system after 2003, The deliberation of power and its democratic transition and electoral integrity Is a good indicator of political stability and progress In the Iraqi parliamentary political system , The transfer of authority in terms of adopting the deliberative approach represents a structural and institutional dimension of the political process , it led the power to become Authority of the Foundation Exercised in accordance with the Constitution and the law not real power , And lead to the recognition of the existence of an official parliamentary opposition and its right to take political power later through the ballot box Makes the pr
... Show MoreIn this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of the Holling type-II prey-first predator and Lotka-Volterra for first predator-second predator model. The conditions, have been examined that assurance the existence of equilibrium points. Uniqueness and boundedness of the solution of the system have been achieve. The local and global dynamical behaviors are discussed and analyzed. In the end, numerical simulations are confirmed the theoretical results that obtained and to display the effectiveness of varying each parameter
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In order to determine what type of photovoltaic solar module could best be used in a thermoelectric photovoltaic power generation. Changing in powers due to higher temperatures (25oC, 35oC, and 45oC) have been done for three types of solar modules: monocrystalline , polycrystalline, and copper indium gallium (di) selenide (CIGS). The Prova 200 solar panel analyzer is used for the professional testing of three solar modules at different ambient temperatures; 25oC, 35oC, and 45oC and solar radiation range 100-1000 W/m2. Copper indium gallium (di) selenide module has the lowest power drop (with the average percent
... Show MoreThe dependence of the energy losses or the stopping power for the ion contribution in D- T hot plasma fuels upon the corresponding energies and the related penetrating factorare arrive by using by a theoretical approximation models. In this work we reach a compatible agreement between our results and the corresponding experimental results.
Abstract
The aim of this work is to create a power control system for wind turbines based on fuzzy logic. Three power control loop was considered including: changing the pitch angle of the blade, changing the length of the blade and turning the nacelle. The stochastic law was given for changes and instant inaccurate assessment of wind conditions changes. Two different algorithms were used for fuzzy inference in the control loop, the Mamdani and Larsen algorithms. These two different algorithms are materialized and developed in this study in Matlab-Fuzzy logic toolbox which has been practically implemented using necessary intelligent control system in electrical engineerin
... Show MoreIn this paper, for the first time we introduce a new four-parameter model called the Gumbel- Pareto distribution by using the T-X method. We obtain some of its mathematical properties. Some structural properties of the new distribution are studied. The method of maximum likelihood is used for estimating the model parameters. Numerical illustration and an application to a real data set are given to show the flexibility and potentiality of the new model.
Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo