We introduce the terms strong suband super-Gaussianity to refer to the previously introduced class of densities log-concave is x and log-convex in x respectively. We derive relationships among the various definitions of suband super-Gaussianity, and show that strong suband super-Gaussianity are related to the score function being star-shaped upward or downward with respect to the origin. We ill...

in this paper, we first introduce the notion of $c$-affine functions for $c> 0$.then we deal with some properties of strongly convex functions in real inner product spaces by using a quadratic support function at each point which is $c$-affine. moreover, a hyers–-ulam stability result for strongly convex functions is shown.

We present a spatiotemporally integrated formulation of the optimal fractionation problem using the standard log-linear-quadratic survival model. Our objective is to choose a fluencemap and a number of fractions so as to maximize the biological effect of tumor dose averaged over its voxels subject to maximum dose, mean dose, and dose-volume constraints for various normal tissues. Constrains are...

The database skyline query (or non-domination query) has a spatial form: Given set P with n point sites, and S of m locations interest, site p ∈ is if only for each q ∖ { } , there exists at least one location s that closer to than . We reduce the problem determining points finding sites have non-empty cells in an additively weighted Voronoi diagram under convex distance function. weights said ...

Based on a new parametric kernel function, this paper presents a primaldual large-update interior-point algorithm (IPM) for semi-definite optimization (SDO) problems. The new parametric function is neither self-regular function nor the usual logarithmic barrier function. It is strongly convex and possesses some novel analytic properties. We analyse this new parametric kernel function and show t...

We study the fixed point for a non-linear transformation in the set of Hausdorff moment sequences, defined by the formula: T ((an))n = 1/(a0 + · · ·+an). We determine the corresponding measure μ, which has an increasing and convex density on ]0, 1[, and we study some analytic functions related to it. The Mellin transform F of μ extends to a meromorphic function in the whole complex plane. It ca...

The analysis of flow in water-distribution networks with several pumps by the Content Model may be turned into a non-convex optimization uncertain problem with multiple solutions. Newton-based methods such as GGA are not able to capture a global optimum in these situations. On the other hand, evolutionary methods designed to use the population of individuals may find a global solution even for ...