The image restoration methods based on the Bayesian’s framework and Markov random fields (MRF) have been widely used in the image-processing field. The basic idea of all these methods is to use calculus of variation and mathematical statistics to average or estimate a pixel value by the values of its neighbors. After applying this averaging process to the whole image a number of times, the nois...

${\mathrm{Li}}_{2}\mathrm{Sr}{[\mathrm{MnN}]}_{2}$ single crystals were successfully grown out of Li-rich flux. The crystal structure was determined by single-crystal x-ray diffraction and revealed almost linear $\ensuremath{-}\mathrm{N}\ensuremath{-}\mathrm{Mn}\ensuremath{-}\mathrm{N}\ensuremath{-}\mathrm{Mn}\ensuremath{-}$ chains as central structural motif. Tetragonal blocks air moisture-sen...

BACKGROUND Neighborhood environments affect children's health outcomes. Observational methods used to assess neighborhoods can be categorized as indirect, intermediate, or direct. Direct methods, involving in-person audits of the neighborhoods conducted by trained observers, are recognized as an accurate representation of current neighborhood conditions. The authors investigated the association...

We derive a formula for the adjoint Ā of square-matrix operation form f(A), where f is holomorphic in neighborhood each eigenvalue.We consider special cases such as spectral decomposition A = UDU-1 and spectrum cutoff f(A) A+ symmetric A. then apply to closed-form expressions particular interest quantitative finance “nearest correlation matrix” routine regularized linear regression.

This paper presents a meta-heuristic, which is based on the Threshold Accepting combined with modified Nearest Neighbor and Exchange procedures, to solve the Vehicle Routing Problem with Backhauls and Time Windows (VRPBTW). The VRPBTW assumes that trucks initially start from the depot, deliver goods to the linehaul customers, successively pickup goods from the backhaul consumers, and finally re...

Nearest neighbor classification is one of the simplest and popular methods for statistical pattern recognition. It classifies an observation x to the class, which is the most frequent in the neighborhood of x. The size of this neighborhood is usually determined by a predefined parameter k. Normally, one uses cross-validation techniques to estimate the optimum value of this parameter, and that e...