Based on the technological process of obtaining tea products, factors determining its quality are considered. The analysis these and their classification. optimization labor costs time to perform control raw materials using methods probability theory. a simple discrete Markov chain, proposed system selective products by variable samples.

The objective of this inVestigation was to evaluate the effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of Landsat MSS data. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Four sampling schemes involving different numbers of samples and diff...

Heavy quark production has been a major topic of investigation at hadron-hadron, electron-proton and electron-positron colliders. Here a review is given of some topics which are of interest primarily for electronproton colliders. We concentrate on this reaction because a theoretical treatment can be based on the operator product expansion, and also because data are available for deep-inelastic ...

This is a summary of the author’s PhD thesis, supervised by Marcello Sanguineti and defended on April 2, 2009 at Università degli Studi di Genova. The thesis is written in English and a copy is available from the author upon request. Functional optimization problems arising in Operations Research are investigated. In such problems, a cost functional Φ has to be minimized over an admissible set ...

We introduce a method for solving the variable coefficient Poisson equation on non-graded Cartesian grids that yields second order accuracy for the solutions and their gradients. We employ quadtree (in 2D) and octree (in 3D) data structures as an efficient means to represent the Cartesian grid, allowing for constraint-free grid generation. The schemes take advantage of sampling the solution at ...

Introduction Mapping complex fiber orientations with diffusion spectrum imaging (DSI) technique has been demonstrated as a potentially useful neuroimaging tool for investigating the brain structural connective network [1]. To sample DSI data, a large number of diffusion-weighted images are needed to be acquired for filling the 3-dimensional (3D) q-space. However, such sampling scheme prolongs t...

This paper suggests to use rounded Gaussians in place of discrete Gaussians in rejection-sampling-based lattice signature schemes like BLISS. We show that this distribution can efficiently be sampled from while additionally making it easy to sample in constant time, systematically avoiding recent timing-based side-channel attacks on lattice-based signatures. We show the effectiveness of the new...

Importance sampling is a variance reduction technique for efficient estimation of rare-event probabilities by Monte Carlo. In standard importance sampling schemes, the system is simulated using an a priori fixed change of measure suggested by a large deviation lower bound analysis. Recent work, however, has suggested that such schemes do not work well in many situations. In this paper we consid...