Parallel Sampling Scheme Research Articles

An efficient parallel sampling technique for Multivariate Poisson-Lognormal model: Analysis with two crash count datasets

This study investigates the Multivariate Poisson-lognormal (MVPLN) model that jointly models crash frequency and severity accounting for correlations. The ordinary univariate count models analyze crashes of different severity level separately ignoring the correlations among severity levels. The MVPLN model is capable to incorporate the general correlation structure and also takes account of the overdispersion in the data that leads to a superior data fitting. However, the traditional estimation approach for MVPLN model is computationally expensive, which often limits the use of MVPLN model in practice. In this work, a parallel sampling scheme is introduced to improve the original Markov Chain Monte Carlo (MCMC) estimation approach of the MVPLN model, which significantly reduces the model estimation time. Two MVPLN models are developed using the pedestrian–vehicle crash data collected in New York City from 2002 to 2006, and the highway-injury data from Washington State (5-year data from 1990 to 1994) The Deviance Information Criteria (DIC) is used to evaluate the model fitting. The estimation results show that the MVPLN models provide a superior fit over univariate Poisson-lognormal (PLN), univariate Poisson, and Negative Binomial models. Further, the correlations among the latent effects of different severity levels are found significant in both datasets,that justifies the importance of jointly modeling crash frequency and severity accounting for correlations.

Knowledge, perceptions, and environmental risk factors among Jamaican households with a history of leptospirosis.

Leptospirosis is a globally important zoonotic disease caused by pathogenic Leptospira, and outbreaks typically follow heavy rainfall and flooding. This study examined the knowledge and perceptions concerning leptospirosis, factors associated with environmental hygiene and sanitation, and the presence of Leptospira in water samples from households with or without a history of the disease in the parish of St. Mary, Jamaica. The study employed a cross-sectional design in 43 communities within the parish of St. Mary, Jamaica between September 2008 and March 2009. Households that had at least one confirmed case of leptospirosis during the 2005 or 2007 outbreaks were assessed for living conditions, environmental hygiene, and for knowledge and risk perceptions about leptospirosis. A parallel sampling scheme was used for households with no reported cases during the outbreak years. Almost 97% of the participants reported having heard of leptospirosis; however, less than 40% of respondents from households with a history of leptospirosis agreed that leptospirosis was a problem in the parish. Among households without a history of leptospirosis, this perception was greater in urban/peri-urban households than in rural households (59% vs. 21%; p=0.04). Risk behaviors or living conditions were common; however, there was a high level of awareness about the health risks associated with flooding. Among households with history of leptospirosis, the perception that nothing can be done to control rodents was significantly higher (p<0.04) in rural (50%) than in urban/peri-urban (17.6%) households. Nine (4%) water samples were positive for Leptospira; 56% of these were from water stored for domestic purposes. Overall, residence in rural communities, presence of a garbage dump, and leptospiral DNA in water samples correlated with households with the history of the disease (p<0.01). Education of rural communities regarding leptospirosis and its prevention through proper waste disposal and rodent control should be urgently initiated.

Reconstruction of UWB Impulse Train by Parallel Sampling of Cascaded Identical RC Filters

In this framework we present a new method for measurement of the UWB impulse train based on the parallel sampling of the cascaded identical RC filters. We show that the amplitudes and time locations of p sequential impulses can be reconstructed from simultaneous measurement of the outputs from 2p cascaded identical RC filters. The parallel sampling scheme has a wide range of applications including the detection of the ultra wideband (UWB) impulses. Due to identical analog RC filters and buffer amplifiers, the parallel sampling scheme is flexible to implement in VLSI applications.

Sampling and Reconstruction of Zero-Order Hold Signals by Parallel RC Filters

In this work we describe a reconstruction algorithm for zero-order hold (ZOH) waveforms measured by a parallel sam-pling scheme. In the method the ZOH signal is fed to a parallel network consisting of resistor-capacitor (RC) filters, whose outputs are sampled simultaneously. The algorithm reconstructs N previous samples of the input signal from output samples of N parallel RC circuits. The method is especially useful in sampling and reconstruction of the ZOH signals produced by the digital-to-analog converters. Using the parallel sampling method the sampling rate of the analog-to-digital converters can be increased by a factor of N. We discuss a variety of applications such as reconstruction of ZOH pulse sequences produced by ultra wide band (UWB) transmitters.

The least square support vector regression coupled with parallel sampling scheme metamodeling technique and application in sheet forming optimization

The least square support vector regression (LS-SVR) metamodel technique is proposed for sheet metal forming optimization. The major advantage of proposed approach is to build metamodel by consideration of empirical risk minimization (ERM) and structure risk minimization (SRM). In order to construct robust and accurate metamodel based LS-SVR, suitable quantity and intervals of samples are recommended. Thus, a parallel intelligent sampling scheme based on a boundary and best neighbor searching method (BBNS) is proposed to improve the efficiency and accuracy of metamodel. The BBNS was suggested and corresponding practical engineer problems were successfully solved by Hu and Li [Hu W, Li GY, Zhong ZH. Optimization of sheet metal forming processes by adaptive response surface based on intelligent sampling method. J Mater Process Technol 2008;197(1–3):77–88; Hu Wang, Li GY, Li Enying, Zhong ZH. Development of metamodeling based optimization system for high nonlinear engineering problems. Adv Eng Software 2008;39(8)629–45]. To increase the efficiency of metamodel based optimization method, the parallel architecture is implemented for BBNS due to its drawbacks. For validation of developed method, both of serial and parallel BBNS scheme are applied for the nonlinear function. The parallel BBNS is also verified to be an accuracy and efficiency scheme. Finally, the practical nonlinear engineering problems are optimized by suggested methodology and satisfied results are also obtained.