Objective: This paper aims to introduce a modified kernel-type ridge estimator for partially linear models under randomly-right censored data. Such models include two main issues that need to be solved: multi-collinearity and censorship. To address these issues, we improved the kernel estimator based on synthetic data transformation and kNN imputation techniques. The key idea of this paper is t...

degenerate kernel approximation method is generalized to solve hammerstein system of fredholm integral equations of the second kind. this method approximates the system of integral equations by constructing degenerate kernel approximations and then the problem is reduced to the solution of a system of algebraic equations. convergence analysis is investigated and on some test problems, the propo...

volatile constituents of the seed kernel and leaf of cultivated moringa peregrina (forssk.) fiori, agricolt collected after hydrolysis were analyzed by gc and gc/ms. five glucosinolate degradation products which constituted almost the whole isolated oil of the seed kernel were identified to be: isobutyl isothiocyanate (94.0%), isopropyl isothiocyanate (4.9%), sec-butyl isothiocyanate (0.5%), n-...

We study the concentration of random kernel matrices around their mean. derive nonasymptotic exponential inequalities for Lipschitz kernels assuming that data points are independent draws from a class multivariate distributions on $\mathbb{R}^{d}$, including strongly log-concave under affine transformations. A feature our result is need not have identical or zero mean, which key in certain appl...

An adversary's user process can compromise the security of operating system (OS) kernel, and subsequent invocation vulnerable kernel code cause memory corruption. The could overwrite data containing privilege information processes or related to features (i.e., mandatory access control). As a means protection, OS researchers have proposed multiple address space approach that partitions protect f...

Monitoring and controlling air quality parameters form an important subject of atmospheric and environmental research today due to the health impacts caused by the different pollutants present in the urban areas. The support vector machine (SVM), as a supervised learning analysis method, is considered an effective statistical tool for the prediction and analysis of air quality. The work present...