the effective factors of forward speed, cylinder rotation, and clearance between a combine’s cylinder and concave on wheat kernel breakage and seed germination were studied in karaj area using a 955 model john dear combine. this study was conducted on three levels of adjustment for each of the variables, 1.2, 1.8 and 2.5 km/hr for forward speed, 800, 900, 1000 rpm for cylinder rotation as well ...

The purpose of this paper is to highlight some hidden Markovian structure the concave majorant Brownian motion. Several distributional identities are implied by joint law a standard one-dimensional motion B and its almost surely unique K on [0,∞). In particular, distribution 2Kt−Bt that R5(t), where R5 5-dimensional Bessel process with R5(0)=0. 2K−B shares number other properties R5, we conject...

We consider a different L-Minkowski combination of compact sets in R than the one introduced by Firey and we prove an L-BrunnMinkowski inequality, p ∈ [0, 1], for a general class of measures called convex measures that includes log-concave measures, under unconditional assumptions. As a consequence, we derive concavity properties of the function t 7→ μ(t 1 pA), p ∈ (0, 1], for unconditional con...

We consider a different L-Minkowski combination of compact sets in R than the one introduced by Firey and we prove an L-BrunnMinkowski inequality, p ∈ [0, 1], for a general class of measures called convex measures that includes log-concave measures, under unconditional assumptions. As a consequence, we derive concavity properties of the function t 7→ μ(t 1 pA), p ∈ (0, 1], for unconditional con...

Abstract. The aim of this paper is to represent given sets of concave functions by Radon probability measures. We define sets Kp (for p ∈ [1,∞]) of concave functions from the spaces L((0, 1)) having some additional properties. These sets of functions are convex and compact so that Choquet’s theorem can be used to obtain existence of representing measures. Uniqueness is examined on a case-by-cas...

Two important goals of high-dimensional modeling are prediction and variable selection. In this article, we consider regularization with combined L1 and concave penalties, and study the sampling properties of the global optimum of the suggested method in ultra-high dimensional 10 settings. The L1-penalty provides the minimum regularization needed for removing noise variables in order to achieve...