in this research, the bending analysis of rectangular nanoplates subjected to mechanical loading is investigated. for this purpose, the strain gradient elasticity theory with one gradient parameter is presented to study the nanoplates. from the best knowledge of authors, it is the first time that the exponential shear deformation formulation based on strain gradient elasticity theory is carried...

Most cosmological parameter estimations are based on the same set of observations and are therefore not independent. Here, we test the consistency of parameter estimations using a combination of large-scale structure and supernovae data, without cosmic microwave background (CMB) data. We combine observations from the IRAS 1.2 Jy and Las Campanas redshift surveys, galaxy peculiar velocities and ...

In this article we describe a Bayesian model for integration of multi-scale image data. The approach is based on the concept of a reference resolution. Data at this and lower resolutions are connected to the reference resolution through a fully specified statistical model. Algorithms for parameter estimation and classification based on the multi-scale model are proposed, and results and compari...

This work is concerned with approximating the smallest eigenvalue of a parameterdependent Hermitian matrix A(μ) for many parameter values μ ∈ R . The design of reliable and efficient algorithms for addressing this task is of importance in a variety of applications. Most notably, it plays a crucial role in estimating the error of reduced basis methods for parametrized partial differential equati...

In this paper we introduce a general purpose graphical processing unit (GPGPU) based method for performing a sweep across a set of the scale invariant feature transform (SIFT) parameters for pairs of images. The focus of the paper is the analysis of the data generated using information visualisation techniques including a cross brushing technique between parallel coordinates, scatter plots and ...

This paper argues that the half-Cauchy distribution should replace the inverseGamma distribution as a default prior for a top-level scale parameter in Bayesian hierarchical models, at least for cases where a proper prior is necessary. Our arguments involve a blend of Bayesian and frequentist reasoning, and are intended to complement the original case made by Gelman (2006) in support of the fold...

In this paper, we train a Latent Dirichlet Allocation (LDA) topic model on the ClueWeb12 data set, a 27-terabyte Web crawl. We extend Spark, a popular tool for performing large-scale data analysis, with an asynchronous parameter server. Such a parameter server provides a distributed and concurrently accessed parameter space for the model. A Metropolis-Hastings based collapsed Gibbs sampler is i...

Reaching as high structural resolution as possible in 3D electron microscopy of biological specimens is crucial to understanding their function and interactions. Technical and biological limitations make electron microscopy projections of such specimens quite noisy. Under those circumstances, the broadly used Weighted Back-Projection algorithm presents some limitations for 3D reconstruction. It...

In algebraic quantum field theory the (inverse) temperature is shown to be a macroscopic order parameter arising from the broken scale invariance associated with renormalization group to parametrize mutually disjoint thermal sectors. This is accomplished in a mathematical formalism for the consistent treatment of explicitly broken symmetries such as broken scale invariance, on the basis of a cl...

In the present article, some shrinkage testimators for the scale parameter of a two – parameter Weibull life testing model have been suggested under the LINEX loss function assuming the shape parameter is to be known. The comparisons of the proposed testimators have been made with the improved estimator.