This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

In this study different methodological approaches are used and described by many features (indicators) of complex socio-economic process. Outcome of analysis has the most reliable and acceptable representation of the studied process specific to chosen case. In order to solve problems in this area (depending on the situation, case under consideration), methods from two groups are most often used: multidimensional comparative analysis and multi-criteria decision analysis. The first of these cases concern problems at the macro level (socio-economic development, demographic situation, population's living standards, etc.), in which the decisionmaker's participation is relatively small (eg the selection of diagnostic variables or expert assess

In earthquake engineering problems, uncertainty exists not only in the seismic excitations but also in the structure's parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of a multi-story moment resisting frame subjected to random ground motion. The North-south component of the Ali Gharbi earthquake in 2012, Iraq, is selected as ground excitation. Using the power spectral density function (PSD), the two-dimensional finite element model of the moment resisting frame's base motion is modified to account for random ground motion. The probabilistic study of the moment resisting frame structure using stochastic fin

      This research evaluates the optical properties of an inhomogeneous and non-paraxial system using a solar ball lens (SBL) as a new thermal solar concentrated collector. This evaluation is based on detecting a diacaustic curve in a straightforward and accurate manner, with the diagnostic relying on image processing as a computational tool using the MATLAB program rather than a complicated numerical analytic procedure. The circle of least confusion (CLC) of the (SBL), (Fluorinated ethylene propylene (FEP) polymer – water core), was calculated. Furthermore, the study evaluated the maximum geometrical concentration ratio (G C) of refracted solar radiation that can be captured by a receiver of the (SBL). Without energy losses due

 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned m

We extended the characterization of strict local minimizers of order two in ward,s
theorem for nonlinear problem to a certain class of nonsmooth semi-infinite problems with inequality constraints in the nonparametric constraint case.

Environmental pollution is regarded as a major problem, and traditional strategies such as chemical or physical remediation are not sufficient to overcome the problems of pollution. Petroleum-contaminated soil results in ecological problems, representing a danger to human health. Bioremediation has received remarkable attention, and it is a procedure that uses a biological agent to remove toxic waste from contaminated soil. This approach is easy to handle, inexpensive, and environmentally friendly; its results are highly satisfactory. Bioremediation is a biodegradation process in which the organic contaminants are completely mineralized to inorganic compounds, carbon dioxide, and water. This review discusses the bioremediation of petroleum-

In this study, the feasibility of Forward–Reverse osmosis processes was investigated for treating the oily wastewater. The first stage was applied forward osmosis process to recover pure water from oily wastewater. Sodium chloride (NaCl) and magnesium chloride (MgCl2) salts were used as draw solutions and the membrane that was used in forward osmosis (FO) process was cellulose triacetate (CTA) membrane. The operating parameters studied were: draw solution concentrations (0.25 – 0.75 M), oil concentration in feed solution (FS) (100-1000 ppm), the temperature of FS and draw solution (DS) (30 - 45 °C), pH of FS (4-10) and the flow rate of both DS and FS (20 - 60 l/h). It was found that the water flux and oil concentration in FS increas

Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.

The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non