Sea buckthorn is an extremely drought-tolerant, resilient and sustainable crop that can be grown in areas with harsh climates scarce resources to provide a source of nutrition income for the local population. The use image-based yield estimation methods allows better management sea cultivation improve its productivity sustainability, while error fruit information due occlusion well reduced by c...

Much effort has been devoted to the synthesis of gold nanoparticles with different shapes, including the zero-dimensional nanospheres, one dimensional nanorods, and two-dimensional nanoplates. Compared to zero or one dimensional nanostructures, the synthesis of two-dimensional nanostructures in high yield has always been more involved, often requiring complex and timeconsuming steps such as mor...

The method of the estimation of the probability of an event occurring under the influence of the causal and random effects is considered. Epistemological differences from the traditional approaches to causality are discussed, and a new model of the statistical estimation of the parameters of each effect is proposed. The simple and effective algorithms of the model parameters estimation are pres...

In this paper, extensions to conventional stochastic estimation techniques are presented, whereby uncertainties in individual estimates may be deduced. Test applications to time series of velocity measurements in a turbulent boundary layer confirm the fidelity of the uncertainty estimation procedure and illustrate how the optimal choice of stochastic estimation model can be strongly dependent o...

This letter proposes a multiple parametric dictionary learning algorithm for direction of arrival (DOA) estimation in presence of array gain-phase error and mutual coupling. It jointly solves both the DOA estimation and array imperfection problems to yield a robust DOA estimation in presence of array imperfection errors and off-grid. In the proposed method, a multiple parametric dictionary lear...

Abstract. Shape constraints play an increasingly prominent role in nonparametric function estimation. While considerable recent attention has been focused on log concavity as a regularizing device in nonparametric density estimation, weaker forms of concavity constraints encompassing larger classes of densities have received less attention but offer some additional flexibility. Heavier tail beh...

Probability estimation is important for the application of probabilistic models as well as for any evaluation in IR. We discuss the interdependencies between parameter estimation and certain properties of probabilistic models: dependence assumptions, binary vs. nonbinary features, estimation sample selection. Then we define an optimum estimate for binary features which can be applied to various...