Effectively visualizing large graphs is challenging. Capturing the statistical properties of these large graphs is also difficult. Sampling algorithms, developed to more feasibly observe and analyze large graphs, are indispensable for this task. Many sampling approaches for graph simplification have been proposed. These methods can be grouped into three categories: node sampling, edge sampling,...

As a bioaerosol sampling standard, Andersen type impactor is widely used since its invention in 1950s, including the investigation of the anthrax attacks in the United States in 2001. However, its related problems such as impaction and desiccation stress as well as particle bounce have not been solved. Here, we improved its biological collection efficiencies by plating a mineral oil layer (100 ...

The purpose of this survey is to present some approximation and shape preserving properties of the so-called nonlinear (more exactly sublinear) and positive, max-product operators, constructed by starting from any discrete linear approximation operators, obtained in a series of recent papers jointly written with B. Bede and L. Coroianu. We will present the main results for the max-product opera...

We present an importance sampling algorithm that can produce realisations of Markovian epidemic models that exactly match observations, taken to be the number of a single event type over a period of time. The importance sampling can be used to construct an efficient particle filter that targets the states of a system and hence estimate the likelihood to perform Bayesian parameter inference. Whe...

This study aimed at developing a LC-MS method to compare the efficiency of various sampling materials for the collection and subsequent analysis of organic gunshot residues (OGSR). Seven sampling materials, namely two "swab"-type and five "stub"-type collection materials, were tested. The evaluation of sampling materials was systematically carried out by first analyzing blank extracts of the ma...

Abstract: In this paper we consider estimation of R = P (Y < X), when X and Y are distributed as two independent four-parameter generalized gamma random variables with same location and scale parameters. A modified maximum likelihood method and a Bayesian technique have been used to estimate R on the basis of independent samples. As the Bayes estimator cannot be obtained in a closed form, it ha...

Sampling biases are often assumed to arise from the type of information that learners sample (Fiedler, 2008), the possibility of negative payoffs (Denrell, 2001), or the prevalence of small samples (Kareev et al., 2002). Here, we show that even in a natural sampling situation (repeated Bernoulli trials), in which a learner’s only decision is when to stop sampling, different sampling goals can h...