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

The response of the combustor’s liner to the air-flow that passes through it is the key reason for the combustion chambers noise, hence the instabilities of those chambers that decreases the mechanical efficiency of such sections, by increased its mechanical vibrations, which increases the failure rate created during originating of the cracks spreading by the shakes producing by the series of high-level frequencies. Accordingly, any work debating the impact of the context of liners in the combustion chamber can provide grasping for the combustion noise generated by the undesirable vibrations, and benefits the industrial firms to design an ideal production procedure which increases the lifespan of the combustor. The goal of this wo

The response of the combustor’s liner to the air-flow that passes through it is the key reason for the combustion chambers noise, hence the instabilities of those chambers that decreases the mechanical efficiency of such sections, by increased its mechanical vibrations, which increases the failure rate created during originating of the cracks spreading by the shakes producing by the series of high-level frequencies. Accordingly, any work debating the impact of the context of liners in the combustion chamber can provide grasping for the combustion noise generated by the undesirable vibrations, and benefits the industrial firms to design an ideal production procedure which increases the lifespan of the combustor. The goal of this work is

The proposed work is an attempt to investigate the stability of the nonlinear system by using a whale optimization algorithm as of one of the meta-heuristic optimization methods, and this investigation was conducted on a single inverted pendulum as a study model. The evaluation measures which were used in this article values of gain and sliding surface of the conventional sliding mode controller to illustrate the extent of the system`s stability. Furthermore, control action, the relationship between error and its derivative, desired, and actual position in addition to sliding response graphically showed the feasibility of the proposed solution. The attained results illustrated considerable improvement in the settling time and minimizing the

          In this study, ultraviolet (UV), ozone techniques with hydrogen peroxide oxidant were used to treat the wastewater which is produced from South Baghdad Power Station using lab-scale system. From UV-H₂O₂ experiments, it was shown that the optimum exposure time was 80 min. At this time, the highest removal percentages of oil, COD, and TOC were 84.69 %, 56.33 % and 50 % respectively. Effect of pH on the contaminants removing was studied in the range of (2-12). The best oil, COD, and TOC removal percentages (69.38 %, 70 % and 52 %) using H₂O₂/UV were at pH=12. H₂O₂/ozone experiments exhibited better performance compared to

The relationship between the elements of the climate and the productivity of citrus (kg
/ tree) in the province of Karbala has been determined through the use of simple correlation
coefficient of Pearson (rp) and (t) test. The result for each of oranges, limes and tangerine had
all shown moral and relevant statistical indications; except for relative humidity, which were
not linked to a moral relationship with productivity of tangerine, oranges and limes.As for the
relationship between climatic factors and yield of bitter orange were all not significant
statistically and very weak.
In order to determine the strength of the correlation between fluctuations in the
climatic elements and fluctuations in the productivi

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow