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

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Due to the rapid advancement of technology and the technology of things, modern industries start to need a highprecision equipment and surface finishing, so many finishing processes began to develop. One of the modern processes is Magnetic Abrasive Finishing (MAF), which is a high-precision process for internal and external finishing under the influence of a magnetic field of abrasive particles. Boron Carbide (B4C) ceramics was tested by mixing it with iron (Fe) and produced abrasive particles to reduce the intensity of scraping on the surface, reduce the economic cost and achieve a high finishing addition to remove the edges at the same time. The material selected for the samples was mild steel (ASTM E415) under (Quantity of Abrasives, Mac

Non-thermal or cold plasma create many reactive species and charged particles when brought into contact with plant extracts. The major constituents involve reactive oxygen species, reactive nitrogen species and plasma ultra-violets. These species can be used to synthesize biologically important nanoparticles. The current study addressed the effect of the green method-based preparation approach on the volumetric analysis of Zn nanoparticles. Under different operating conditions, the traditional thermal method and the microwave method as well as the plasma generation in dielectric barrier discharge reactor were adopted as a preparation approach in this study. The results generally show that the type of method used plays an important role in d

Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

The research aims to identify banking stress tests, which is one of the modern and important tools in managing banking risks by applying the equations of that tool to the sample. The banking sector considered one of the most vulnerable to sudden and rapid changes in an unstable economic environment, making it more vulnerable. Therefore, it is necessary to establish a special risk management section to reduce the banking risks of the banking business that negatively affect its performance.

The research concluded that there is a direct relationship between stress tests and risk management, as stress tests are an essential tool in risk management. They also considered a unified approach in managing bank risks that helps the bank to

The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo