In a given problem, the Bayesian statistical paradigm requires the specification of a prior distribution that quantifies relevant information about the unknowns of main interest external to the data. In cases where little such information is available, the problem under study may possess an invariance under a transformation group that encodes a lack of information, leading to a unique prior—thi...

We propose a new prior distribution for classical (non-hierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, and then placing independent Student-t prior distributions on the coefficients. As a default choice, we recommend the Cauchy distribution with center 0 and scale 2.5, which in the simplest setting is a lo...

In this work, we explore an innovative strategy for image denoising by using convolutional neural networks (CNN) to learn pixel-distribution from noisy data. By increasing CNN’s width with large reception fields and more channels in each layer, CNNs can reveal the ability of learning pixel-distribution, which is a prior excising in many different types of noise. The key to our approach is a dis...

INTRODUCTION Gold- (Au-) based nanomaterials have shown promising potential in nanomedicine. The individual health status is an important determinant of the response to injury/exposure. It is, therefore, critical to evaluate exposure to Au-nanomaterials with varied preexisting health status. OBJECTIVE The goal of this research was to determine the extent of extrapulmonary translocation from h...

We adapt the formalism of the statistical theory of 2D turbulence in the case where the Casimir constraints are replaced by the specification of a prior vorticity distribution. A new relaxation equation is obtained for the evolution of the coarse-grained vorticity. It can be used as a thermodynamical parametrization of forced 2D turbulence (determined by the prior), or as a numerical algorithm ...

As various applications of wireless ad hoc network have been proposed, security has become one of the big research challenges and is receiving increasing attention. In contrast with conventional networks, mobile ad hoc networks usually do not provide online access to trusted authorities or to centralized servers, and they exhibit frequent partitioning due to link and node failures and to node m...

In near future, the Wireless Sensor Networks (WSN) is widely used in many applications like military and civil domains. The wireless sensor networks are always deployed in hostile and pervasive environment. Security is major concern in the wireless sensor network. The traditional network security methods are not suitable for wireless sensor networks because of limited resource. Several Key mana...