The Flexible Rare Event Sampling Harness System (FRESHS)

We present the software package FRESHS (http://www.freshs.org) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms.     

On Sequenial Tests of the Bincknial Distribution

In this paper, we consider the detailed characteristics of the standard sequential test of a simple hypothesis versus a single alternative for the case of the binomial distribution. A method is developed which permits evaluation of the associated probabilities of acceptance and/or rejection of the null hypothesis at each stage. From this information, the quantitative features of the test (Operating Characteristic and test termination probability) are completely determined. Curves are presented to facilitate assessment of the sequential procedure in practical cases. A sequential test is compared with a fixed sample size test having approximately the same Operating Characteristic. Wald's approximation for the average sample number is compared with exact values.     

Windowed linear canonical transform and its applications

In this paper, we generalize the windowed Fourier transform to the windowed linear canonical transform by substituting the Fourier transform kernel with the linear canonical transform kernel in the windowed Fourier transform definition. It offers local contents, enjoys high resolution, and eliminates cross terms. Some useful properties of the windowed linear canonical transform are derived. Those include covariance property, orthogonality property and inversion formulas. As applications analogues of the Poisson summation formula, sampling formulas and series expansions are given.     

INTELLIGENT CONTROL SYSTEM FOR STREAM SAMPLING

This article introduces an intelligent sampling controller to assist the actions taken by a plant operator to correct sampling conditions. This hybrid system includes a sampling error filter (SEF), a sampling performance indexer (SPI), a sampling correctness inspector (SCI), and a sampling error evaluator (SEE). First, the SEF upgrades the measured variables in a mineral-processing system by material balance. Then, the SPI employs fuzzy logic to assess the sampling performance. In addition, the expert system SCI checks the correctness of the sampling process. Finally, the sampling error is computed by the expert system SEE.     

Efficiently sampling exchangeable Cuadras-Augé copulas in high dimensions

An n-dimensional random vector is constructed whose survival copula is given by a copula that was first presented in Cuadras and Augé [C.M. Cuadras, J. Augé, A continuous general multivariate distribution and its properties, Communications in Statistics - Theory and Methods 10 (4) (1981) 339-353]. This construction adds a Poisson subordinator as mixing variable to initially independent exponentially distributed random variables. It is shown how the choice of Poisson process relates to the parameter of the induced Cuadras-Augé copula. Based on this construction, a sampling algorithm for this multivariate distribution is presented which has average computational efficiency O(nloglogn).     

An Almost Sure Result on Sampling of Bandlimited Random Signals

The Shannon-Nyquist sampling theorem for deterministic signals is a fundamental result in the field of telecommunication and signal processing, and many re- sults on this topic have been obtained. However, very few results on random signals have been published, after Kol- mogorov mentioned the importance of Shannon-formula for stochastic signals in 1956. In this paper, following the almost sure result for bandlimited stochastic processes pro- posed by Seip in 1990, we give an almost sure result of the classical sampling theorem for bandlimited random signals with local average sampling.     

Effective sampling strategy to detect food and feed contamination: Herbs and spices case

Sampling plans for food safety hazards are aimed to be used to determine whether a lot of food is contaminated (with microbiological or chemical hazards) or not. One of the components of sampling plans is the sampling strategy. The aim of this study was to compare the performance of three different sampling strategies, being simple random sampling (SRS), stratified random sampling (STRS), and systematic sampling (SS), with each other for their probability of detecting a heterogeneously distributed contamination in a lot of herbs or spices (i.e., a dry food product). To this end, a simulation model was developed, and applied to different scenarios for contamination level and numbers of samples collected. In addition, as a case study, the sampling plan of a company processing herbs and spices was evaluated using the simulation model. Results showed that the effectiveness of the sampling plan is influenced by the sampling strategy. With expected low contamination levels the SS strategy performs better than the two other strategies. At higher expected contaminated levels, the STRS strategy is preferred.     

Air Quality Monitoring Network Design to Control Nitrogen Dioxide and Ozone,Applied in Granada,Spain

This paper describes a method to design air quality monitoring networks for nitrogen dioxide and ozone and its application in Granada, a city located in Andalusia, southern Spain. The city has a population of 236,988 inhabitants, and traffic is its main source of air pollution. Sampling campaigns with passive diffusion samplers at 88 sites were carried out to obtain information on the pollution distribution in Granada. The average concentrations found for NO₂ and O₃ were 36.5 μg/m³ and 51.6 μg/m³, respectively. Maximum values of up to 57.1 μg/m³ NO₂ were found in Granada city center and O₃ reached 77.2 μg/m³ downwind from the emission source. After spatial interpolation of the obtained values with Geographical Information Systems, a selection of the best locations for the monitoring stations was made, in line with the macro- and microscale siting requirements of the European Directive 2008/50/EC on ambient air quality and cleaner air for Europe. Another sampling campaign with diffusive samplers was carried out in 2007 to determine if the locations of the air quality assessment stations were still representative for their zone. A correction was made in the control network following results of this verification campaign.