movement of sediment in the river causes many changes in the river bed. these changes are called bedform. river bedform has significant and direct effects on bed roughness, flow resistance, and water surface profile. thus, having adequate knowledge of the bedform is of special importance in river engineering. several methods have been developed by researchers for estimation of bed form dimensio...

Subspace identification methods, such as canonical variate analysis (CVA), are noniterative tools suitable for the state-space modeling of multi-input, multi-output processes, e.g., industrial using input-output data. To learn nonlinear system behavior, kernel subspace techniques commonly used. However, issue design must be given more attention because type can influence kind nonlinearities tha...

background : kernel smoothing method is a non-parametric or graphical method for statistical estimation. in the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. methods : by employing non-parametric regression methods, the curve estimation, may have some complexity.  in this article, four indices of epanechnikov, b...

prunus armeniaca l. (apricot) is a tree cultivated in different parts of the world. apricot kernel as a good dietary supplement has shown antioxidant, anti-inflammatory and other pharmacologic properties which suggest that it may be functional as an anticolitis agent. in this study we evaluated the effects of apricot kernel extract and oil on ulcerative colitis in rats. rats were fasted for 36 ...

Extracting biomedical relations such as drug-drug interaction (DDI) from text is an important task in biomedical NLP. Due to the large number of complex sentences in biomedical literature, researchers have employed some sentence simplification techniques to improve the performance of the relation extraction methods. However, due to difficulty of the task, there is no noteworthy improvement in t...

‎This paper presents the numerical solution for a class of fractional differential equations. The fractional derivatives are described in the Caputo cite{1} sense. We developed a reproducing kernel method (RKM) to solve fractional differential equations in reproducing kernel Hilbert space. This method cannot be used directly to solve these equations, so an equivalent transformation is made by u...

Let {Xn ,n=>1} be a strictly stationary sequence of negatively associated random variables, with common distribution function F. In this paper, we consider the estimation of the two-dimensional distribution function of (X1, Xk+1) for fixed $K /in N$ based on kernel type estimators. We introduce asymptotic normality and properties and moments. From these we derive the optimal bandwidth...