Assessment of resampling methods for causality testing: A note on the US inflation behavior.

Science.gov (United States)

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling techniques, time-shifted surrogates and the stationary bootstrap, are combined with three independence settings (giving a total of six resampling methods), all approximating the null hypothesis of no Granger causality. In these three settings, the level of dependence is changed, while the conditioning variables remain intact. The empirical null distribution of the PTE, as the surrogate and bootstrapped time series become more independent, is examined along with the size and power of the respective tests. Additionally, we consider a seventh resampling method by contemporaneously resampling the driving and the response time series using the stationary bootstrap. Although this case does not comply with the no causality hypothesis, one can obtain an accurate sampling distribution for the mean of the test statistic since its value is zero under H0. Results indicate that as the resampling setting gets more independent, the test becomes more conservative. Finally, we conclude with a real application. More specifically, we investigate the causal links among the growth rates for the US CPI, money supply and crude oil. Based on the PTE and the seven resampling methods, we consistently find that changes in crude oil cause inflation conditioning on money supply in the post-1986 period. However this relationship cannot be explained on the basis of traditional cost-push mechanisms.

Comparison of standard resampling methods for performance estimation of artificial neural network ensembles

OpenAIRE

Green, Michael; Ohlsson, Mattias

2007-01-01

Estimation of the generalization performance for classification within the medical applications domain is always an important task. In this study we focus on artificial neural network ensembles as the machine learning technique. We present a numerical comparison between five common resampling techniques: k-fold cross validation (CV), holdout, using three cutoffs, and bootstrap using five different data sets. The results show that CV together with holdout $0.25$ and $0.50$ are the best resampl...

Efficient p-value evaluation for resampling-based tests

KAUST Repository

Yu, K.

2011-01-05

The resampling-based test, which often relies on permutation or bootstrap procedures, has been widely used for statistical hypothesis testing when the asymptotic distribution of the test statistic is unavailable or unreliable. It requires repeated calculations of the test statistic on a large number of simulated data sets for its significance level assessment, and thus it could become very computationally intensive. Here, we propose an efficient p-value evaluation procedure by adapting the stochastic approximation Markov chain Monte Carlo algorithm. The new procedure can be used easily for estimating the p-value for any resampling-based test. We show through numeric simulations that the proposed procedure can be 100-500 000 times as efficient (in term of computing time) as the standard resampling-based procedure when evaluating a test statistic with a small p-value (e.g. less than 10( - 6)). With its computational burden reduced by this proposed procedure, the versatile resampling-based test would become computationally feasible for a much wider range of applications. We demonstrate the application of the new method by applying it to a large-scale genetic association study of prostate cancer.

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

International Nuclear Information System (INIS)

Gur-Dedeoglu, Bala; Konu, Ozlen; Kir, Serkan; Ozturk, Ahmet Rasit; Bozkurt, Betul; Ergul, Gulusan; Yulug, Isik G

2008-01-01

Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results. The

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

Directory of Open Access Journals (Sweden)

Ergul Gulusan

2008-12-01

Full Text Available Abstract Background Accuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures. Methods A resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC, and invasive lobular carcinoma (ILC samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis. Results The two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively. The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real

Improved efficiency of multi-criteria IMPT treatment planning using iterative resampling of randomly placed pencil beams

Science.gov (United States)

van de Water, S.; Kraan, A. C.; Breedveld, S.; Schillemans, W.; Teguh, D. N.; Kooy, H. M.; Madden, T. M.; Heijmen, B. J. M.; Hoogeman, M. S.

2013-10-01

This study investigates whether ‘pencil beam resampling’, i.e. iterative selection and weight optimization of randomly placed pencil beams (PBs), reduces optimization time and improves plan quality for multi-criteria optimization in intensity-modulated proton therapy, compared with traditional modes in which PBs are distributed over a regular grid. Resampling consisted of repeatedly performing: (1) random selection of candidate PBs from a very fine grid, (2) inverse multi-criteria optimization, and (3) exclusion of low-weight PBs. The newly selected candidate PBs were added to the PBs in the existing solution, causing the solution to improve with each iteration. Resampling and traditional regular grid planning were implemented into our in-house developed multi-criteria treatment planning system ‘Erasmus iCycle’. The system optimizes objectives successively according to their priorities as defined in the so-called ‘wish-list’. For five head-and-neck cancer patients and two PB widths (3 and 6 mm sigma at 230 MeV), treatment plans were generated using: (1) resampling, (2) anisotropic regular grids and (3) isotropic regular grids, while using varying sample sizes (resampling) or grid spacings (regular grid). We assessed differences in optimization time (for comparable plan quality) and in plan quality parameters (for comparable optimization time). Resampling reduced optimization time by a factor of 2.8 and 5.6 on average (7.8 and 17.0 at maximum) compared with the use of anisotropic and isotropic grids, respectively. Doses to organs-at-risk were generally reduced when using resampling, with median dose reductions ranging from 0.0 to 3.0 Gy (maximum: 14.3 Gy, relative: 0%-42%) compared with anisotropic grids and from -0.3 to 2.6 Gy (maximum: 11.4 Gy, relative: -4%-19%) compared with isotropic grids. Resampling was especially effective when using thin PBs (3 mm sigma). Resampling plans contained on average fewer PBs, energy layers and protons than anisotropic

Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.

Science.gov (United States)

Han, Guanghui; Liu, Xiabi; Zheng, Guangyuan; Wang, Murong; Huang, Shan

2018-06-06

Ground-glass opacity (GGO) is a common CT imaging sign on high-resolution CT, which means the lesion is more likely to be malignant compared to common solid lung nodules. The automatic recognition of GGO CT imaging signs is of great importance for early diagnosis and possible cure of lung cancers. The present GGO recognition methods employ traditional low-level features and system performance improves slowly. Considering the high-performance of CNN model in computer vision field, we proposed an automatic recognition method of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNN models in this paper. Our hybrid resampling is performed on multi-views and multi-receptive fields, which reduces the risk of missing small or large GGOs by adopting representative sampling panels and processing GGOs with multiple scales simultaneously. The layer-wise fine-tuning strategy has the ability to obtain the optimal fine-tuning model. Multi-CNN models fusion strategy obtains better performance than any single trained model. We evaluated our method on the GGO nodule samples in publicly available LIDC-IDRI dataset of chest CT scans. The experimental results show that our method yields excellent results with 96.64% sensitivity, 71.43% specificity, and 0.83 F1 score. Our method is a promising approach to apply deep learning method to computer-aided analysis of specific CT imaging signs with insufficient labeled images. Graphical abstract We proposed an automatic recognition method of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNN models in this paper. Our hybrid resampling reduces the risk of missing small or large GGOs by adopting representative sampling panels and processing GGOs with multiple scales simultaneously. The layer-wise fine-tuning strategy has ability to obtain the optimal fine-tuning model. Our method is a promising approach to apply deep learning method to computer-aided analysis

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Science.gov (United States)

Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.

2017-06-01

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

Energy Technology Data Exchange (ETDEWEB)

Holoien, Thomas W.-S.; /Ohio State U., Dept. Astron. /Ohio State U., CCAPP /KIPAC, Menlo Park /SLAC; Marshall, Philip J.; Wechsler, Risa H.; /KIPAC, Menlo Park /SLAC

2017-05-11

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

Directory of Open Access Journals (Sweden)

Yeqing Zhang

2018-02-01

Full Text Available For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

Science.gov (United States)

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

An add-in implementation of the RESAMPLING syntax under Microsoft EXCEL.

Science.gov (United States)

Meineke, I

2000-10-01

The RESAMPLING syntax defines a set of powerful commands, which allow the programming of probabilistic statistical models with few, easily memorized statements. This paper presents an implementation of the RESAMPLING syntax using Microsoft EXCEL with Microsoft WINDOWS(R) as a platform. Two examples are given to demonstrate typical applications of RESAMPLING in biomedicine. Details of the implementation with special emphasis on the programming environment are discussed at length. The add-in is available electronically to interested readers upon request. The use of the add-in facilitates numerical statistical analyses of data from within EXCEL in a comfortable way.

On removing interpolation and resampling artifacts in rigid image registration.

Science.gov (United States)

Aganj, Iman; Yeo, Boon Thye Thomas; Sabuncu, Mert R; Fischl, Bruce

2013-02-01

We show that image registration using conventional interpolation and summation approximations of continuous integrals can generally fail because of resampling artifacts. These artifacts negatively affect the accuracy of registration by producing local optima, altering the gradient, shifting the global optimum, and making rigid registration asymmetric. In this paper, after an extensive literature review, we demonstrate the causes of the artifacts by comparing inclusion and avoidance of resampling analytically. We show the sum-of-squared-differences cost function formulated as an integral to be more accurate compared with its traditional sum form in a simple case of image registration. We then discuss aliasing that occurs in rotation, which is due to the fact that an image represented in the Cartesian grid is sampled with different rates in different directions, and propose the use of oscillatory isotropic interpolation kernels, which allow better recovery of true global optima by overcoming this type of aliasing. Through our experiments on brain, fingerprint, and white noise images, we illustrate the superior performance of the integral registration cost function in both the Cartesian and spherical coordinates, and also validate the introduced radial interpolation kernel by demonstrating the improvement in registration.

A New Method to Implement Resampled Uniform PWM Suitable for Distributed Control of Modular Multilevel Converters

DEFF Research Database (Denmark)

Huang, Shaojun; Mathe, Laszlo; Teodorescu, Remus

2013-01-01

Two existing methods to implement resampling modulation technique for modular multilevel converter (MMC) (the sampling frequency is a multiple of the carrier frequency) are: the software solution (using a microcontroller) and the hardware solution (using FPGA). The former has a certain level...

Resampling Approach for Determination of the Method for Reference Interval Calculation in Clinical Laboratory Practice▿

Science.gov (United States)

Pavlov, Igor Y.; Wilson, Andrew R.; Delgado, Julio C.

2010-01-01

Reference intervals (RI) play a key role in clinical interpretation of laboratory test results. Numerous articles are devoted to analyzing and discussing various methods of RI determination. The two most widely used approaches are the parametric method, which assumes data normality, and a nonparametric, rank-based procedure. The decision about which method to use is usually made arbitrarily. The goal of this study was to demonstrate that using a resampling approach for the comparison of RI determination techniques could help researchers select the right procedure. Three methods of RI calculation—parametric, transformed parametric, and quantile-based bootstrapping—were applied to multiple random samples drawn from 81 values of complement factor B observations and from a computer-simulated normally distributed population. It was shown that differences in RI between legitimate methods could be up to 20% and even more. The transformed parametric method was found to be the best method for the calculation of RI of non-normally distributed factor B estimations, producing an unbiased RI and the lowest confidence limits and interquartile ranges. For a simulated Gaussian population, parametric calculations, as expected, were the best; quantile-based bootstrapping produced biased results at low sample sizes, and the transformed parametric method generated heavily biased RI. The resampling approach could help compare different RI calculation methods. An algorithm showing a resampling procedure for choosing the appropriate method for RI calculations is included. PMID:20554803

Testing for Granger Causality in the Frequency Domain: A Phase Resampling Method.

Science.gov (United States)

Liu, Siwei; Molenaar, Peter

2016-01-01

This article introduces phase resampling, an existing but rarely used surrogate data method for making statistical inferences of Granger causality in frequency domain time series analysis. Granger causality testing is essential for establishing causal relations among variables in multivariate dynamic processes. However, testing for Granger causality in the frequency domain is challenging due to the nonlinear relation between frequency domain measures (e.g., partial directed coherence, generalized partial directed coherence) and time domain data. Through a simulation study, we demonstrate that phase resampling is a general and robust method for making statistical inferences even with short time series. With Gaussian data, phase resampling yields satisfactory type I and type II error rates in all but one condition we examine: when a small effect size is combined with an insufficient number of data points. Violations of normality lead to slightly higher error rates but are mostly within acceptable ranges. We illustrate the utility of phase resampling with two empirical examples involving multivariate electroencephalography (EEG) and skin conductance data.

A comparison of resampling schemes for estimating model observer performance with small ensembles

Science.gov (United States)

Elshahaby, Fatma E. A.; Jha, Abhinav K.; Ghaly, Michael; Frey, Eric C.

2017-09-01

In objective assessment of image quality, an ensemble of images is used to compute the 1st and 2nd order statistics of the data. Often, only a finite number of images is available, leading to the issue of statistical variability in numerical observer performance. Resampling-based strategies can help overcome this issue. In this paper, we compared different combinations of resampling schemes (the leave-one-out (LOO) and the half-train/half-test (HT/HT)) and model observers (the conventional channelized Hotelling observer (CHO), channelized linear discriminant (CLD) and channelized quadratic discriminant). Observer performance was quantified by the area under the ROC curve (AUC). For a binary classification task and for each observer, the AUC value for an ensemble size of 2000 samples per class served as a gold standard for that observer. Results indicated that each observer yielded a different performance depending on the ensemble size and the resampling scheme. For a small ensemble size, the combination [CHO, HT/HT] had more accurate rankings than the combination [CHO, LOO]. Using the LOO scheme, the CLD and CHO had similar performance for large ensembles. However, the CLD outperformed the CHO and gave more accurate rankings for smaller ensembles. As the ensemble size decreased, the performance of the [CHO, LOO] combination seriously deteriorated as opposed to the [CLD, LOO] combination. Thus, it might be desirable to use the CLD with the LOO scheme when smaller ensemble size is available.

Efficient p-value evaluation for resampling-based tests

KAUST Repository

Yu, K.; Liang, F.; Ciampa, J.; Chatterjee, N.

2011-01-01

The resampling-based test, which often relies on permutation or bootstrap procedures, has been widely used for statistical hypothesis testing when the asymptotic distribution of the test statistic is unavailable or unreliable. It requires repeated

Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'.

Science.gov (United States)

de Nijs, Robin

2015-07-21

In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics for counts below 100. Only Poisson resampling was not affected by this, while Gaussian redrawing was less affected by it than Poisson redrawing. Poisson resampling is the method of choice, when simulating half-count (or less) images from full-count images. It simulates correctly the statistical properties, also in the case of rounding off of the images.

Community level patterns in diverse systems: A case study of litter fauna in a Mexican pine-oak forest using higher taxa surrogates and re-sampling methods

Science.gov (United States)

Moreno, Claudia E.; Guevara, Roger; Sánchez-Rojas, Gerardo; Téllez, Dianeis; Verdú, José R.

2008-01-01

Environmental assessment at the community level in highly diverse ecosystems is limited by taxonomic constraints and statistical methods requiring true replicates. Our objective was to show how diverse systems can be studied at the community level using higher taxa as biodiversity surrogates, and re-sampling methods to allow comparisons. To illustrate this we compared the abundance, richness, evenness and diversity of the litter fauna in a pine-oak forest in central Mexico among seasons, sites and collecting methods. We also assessed changes in the abundance of trophic guilds and evaluated the relationships between community parameters and litter attributes. With the direct search method we observed differences in the rate of taxa accumulation between sites. Bootstrap analysis showed that abundance varied significantly between seasons and sampling methods, but not between sites. In contrast, diversity and evenness were significantly higher at the managed than at the non-managed site. Tree regression models show that abundance varied mainly between seasons, whereas taxa richness was affected by litter attributes (composition and moisture content). The abundance of trophic guilds varied among methods and seasons, but overall we found that parasitoids, predators and detrivores decreased under management. Therefore, although our results suggest that management has positive effects on the richness and diversity of litter fauna, the analysis of trophic guilds revealed a contrasting story. Our results indicate that functional groups and re-sampling methods may be used as tools for describing community patterns in highly diverse systems. Also, the higher taxa surrogacy could be seen as a preliminary approach when it is not possible to identify the specimens at a low taxonomic level in a reasonable period of time and in a context of limited financial resources, but further studies are needed to test whether the results are specific to a system or whether they are general

NAIP Aerial Imagery (Resampled), Salton Sea - 2005 [ds425

Data.gov (United States)

California Natural Resource Agency — NAIP 2005 aerial imagery that has been resampled from 1-meter source resolution to approximately 30-meter resolution. This is a mosaic composed from several NAIP...

Re-sampling of the KLX02 deep borehole at Laxemar

International Nuclear Information System (INIS)

Laaksoharju, M.; Andersson, Cecilia; Tullborg, E.L.; Wallin, B.; Ekwall, K.; Pedersen, K.

1999-01-01

The project focuses on the origin and changes of deep groundwaters, which are important for understanding the stability of the groundwater surrounding the final repository. The results from the sampling campaign in 1997 down to a depth of 1500m are compared with the results from 1993 sampled in the same borehole. The analytical results and some preliminary calculations are presented. The changes since the last sampling campaign 4 years ago indicate a high degree of mixing and dynamics in the system. The following conclusions are drawn: More changes in the water composition than expected compared with the results from the sampling campaign in 1993; Larger portions of meteoric water in the upper part of the borehole; Less glacial water in the intermediate part of the borehole; More brine water in the lower part of the borehole. The conclusion is that there has been a relatively large change in the groundwater system during the last 4 years in the Laxemar deep borehole. The disturbance removed the effect from the last glaciation and pulled in groundwater, which resulted in a mixture mainly consisting of meteoric and brine waters. The most probable reason is that the annual fluctuation and flow in the open borehole play an important role as a modificator especially for the isotopes. The results show the sensitivity of deep groundwater to changes in the prevailing hydrogeological situation

Inferring microevolution from museum collections and resampling: lessons learned from Cepaea

Directory of Open Access Journals (Sweden)

Małgorzata Ożgo

2017-10-01

Full Text Available Natural history collections are an important and largely untapped source of long-term data on evolutionary changes in wild populations. Here, we utilize three large geo-referenced sets of samples of the common European land-snail Cepaea nemoralis stored in the collection of Naturalis Biodiversity Center in Leiden, the Netherlands. Resampling of these populations allowed us to gain insight into changes occurring over 95, 69, and 50 years. Cepaea nemoralis is polymorphic for the colour and banding of the shell; the mode of inheritance of these patterns is known, and the polymorphism is under both thermal and predatory selection. At two sites the general direction of changes was towards lighter shells (yellow and less heavily banded, which is consistent with predictions based on on-going climatic change. At one site no directional changes were detected. At all sites there were significant shifts in morph frequencies between years, and our study contributes to the recognition that short-term changes in the states of populations often exceed long-term trends. Our interpretation was limited by the few time points available in the studied collections. We therefore stress the need for natural history collections to routinely collect large samples of common species, to allow much more reliable hind-casting of evolutionary responses to environmental change.

AND/OR Importance Sampling

OpenAIRE

Gogate, Vibhav; Dechter, Rina

2012-01-01

The paper introduces AND/OR importance sampling for probabilistic graphical models. In contrast to importance sampling, AND/OR importance sampling caches samples in the AND/OR space and then extracts a new sample mean from the stored samples. We prove that AND/OR importance sampling may have lower variance than importance sampling; thereby providing a theoretical justification for preferring it over importance sampling. Our empirical evaluation demonstrates that AND/OR importance sampling is ...

Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling

Directory of Open Access Journals (Sweden)

Vinicius Silva dos Santos

2015-06-01

Full Text Available This study aimed at investigating the genetic divergence of eighteen accessions of cupuaçu trees based on fruit morphometric traits and comparing usual methods of cluster analysis with the proposed multiscale bootstrap resampling methodology. The data were obtained from an experiment conducted in Tomé-Açu city (PA, Brazil, arranged in a completely randomized design with eighteen cupuaçu accessions and 10 repetitions, from 2004 to 2011. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction (REML/BLUP methodology. The predicted breeding values were used in the study on genetic divergence through Unweighted Pair Cluster Method with Arithmetic Mean (UPGMA hierarchical clustering and Tocher’s optimization method based on standardized Euclidean distance. Clustering consistency and optimal number of clusters in the UPGMA method were verified by the cophenetic correlation coefficient (CCC and Mojena’s criterion, respectively, besides the multiscale bootstrap resampling technique. The use of the clustering UPGMA method in situations with and without multiscale bootstrap resulted in four and five clusters, respectively, while the Tocher’s method resulted in seven clusters. The multiscale bootstrap resampling technique proves to be efficient to assess the consistency of clustering in hierarchical methods and, consequently, the optimal number of clusters.

Comment on: 'A Poisson resampling method for simulating reduced counts in nuclear medicine images'

DEFF Research Database (Denmark)

de Nijs, Robin

2015-01-01

In order to be able to calculate half-count images from already acquired data, White and Lawson published their method based on Poisson resampling. They verified their method experimentally by measurements with a Co-57 flood source. In this comment their results are reproduced and confirmed...... by a direct numerical simulation in Matlab. Not only Poisson resampling, but also two direct redrawing methods were investigated. Redrawing methods were based on a Poisson and a Gaussian distribution. Mean, standard deviation, skewness and excess kurtosis half-count/full-count ratios were determined for all...... methods, and compared to the theoretical values for a Poisson distribution. Statistical parameters showed the same behavior as in the original note and showed the superiority of the Poisson resampling method. Rounding off before saving of the half count image had a severe impact on counting statistics...

Using vis-NIR to predict soil organic carbon and clay at national scale: validation of geographically closest resampling strategy

DEFF Research Database (Denmark)

Peng, Yi; Knadel, Maria; Greve, Mette Balslev

2016-01-01

geographically closest sampling points. The SOC prediction resulted in R2: 0.76; RMSE: 4.02 %; RPD: 1.59; RPIQ: 0.35. The results for clay prediction were also successful (R2: 0.84; RMSE: 2.36 %; RPD: 2.35; RPIQ: 2.88). For SOC predictions, over 90% of soil samples were well predicted compared...... samples) for soils from each 7-km grid sampling point in the country. In the resampling and modelling process, each target sample was predicted by a specific model which was calibrated using geographically closest soil spectra. The geographically closest 20, 30, 40, and 50 sampling points (profiles) were...

Conditional Monthly Weather Resampling Procedure for Operational Seasonal Water Resources Forecasting

Science.gov (United States)

Beckers, J.; Weerts, A.; Tijdeman, E.; Welles, E.; McManamon, A.

2013-12-01

To provide reliable and accurate seasonal streamflow forecasts for water resources management several operational hydrologic agencies and hydropower companies around the world use the Extended Streamflow Prediction (ESP) procedure. The ESP in its original implementation does not accommodate for any additional information that the forecaster may have about expected deviations from climatology in the near future. Several attempts have been conducted to improve the skill of the ESP forecast, especially for areas which are affected by teleconnetions (e,g. ENSO, PDO) via selection (Hamlet and Lettenmaier, 1999) or weighting schemes (Werner et al., 2004; Wood and Lettenmaier, 2006; Najafi et al., 2012). A disadvantage of such schemes is that they lead to a reduction of the signal to noise ratio of the probabilistic forecast. To overcome this, we propose a resampling method conditional on climate indices to generate meteorological time series to be used in the ESP. The method can be used to generate a large number of meteorological ensemble members in order to improve the statistical properties of the ensemble. The effectiveness of the method was demonstrated in a real-time operational hydrologic seasonal forecasts system for the Columbia River basin operated by the Bonneville Power Administration. The forecast skill of the k-nn resampler was tested against the original ESP for three basins at the long-range seasonal time scale. The BSS and CRPSS were used to compare the results to those of the original ESP method. Positive forecast skill scores were found for the resampler method conditioned on different indices for the prediction of spring peak flows in the Dworshak and Hungry Horse basin. For the Libby Dam basin however, no improvement of skill was found. The proposed resampling method is a promising practical approach that can add skill to ESP forecasts at the seasonal time scale. Further improvement is possible by fine tuning the method and selecting the most

Spatial Quality Evaluation of Resampled Unmanned Aerial Vehicle-Imagery for Weed Mapping.

Science.gov (United States)

Borra-Serrano, Irene; Peña, José Manuel; Torres-Sánchez, Jorge; Mesas-Carrascosa, Francisco Javier; López-Granados, Francisca

2015-08-12

Unmanned aerial vehicles (UAVs) combined with different spectral range sensors are an emerging technology for providing early weed maps for optimizing herbicide applications. Considering that weeds, at very early phenological stages, are similar spectrally and in appearance, three major components are relevant: spatial resolution, type of sensor and classification algorithm. Resampling is a technique to create a new version of an image with a different width and/or height in pixels, and it has been used in satellite imagery with different spatial and temporal resolutions. In this paper, the efficiency of resampled-images (RS-images) created from real UAV-images (UAV-images; the UAVs were equipped with two types of sensors, i.e., visible and visible plus near-infrared spectra) captured at different altitudes is examined to test the quality of the RS-image output. The performance of the object-based-image-analysis (OBIA) implemented for the early weed mapping using different weed thresholds was also evaluated. Our results showed that resampling accurately extracted the spectral values from high spatial resolution UAV-images at an altitude of 30 m and the RS-image data at altitudes of 60 and 100 m, was able to provide accurate weed cover and herbicide application maps compared with UAV-images from real flights.

ROSETTA-ORBITER SW RPCMAG 4 CR2 RESAMPLED V3.0

Data.gov (United States)

National Aeronautics and Space Administration — 2010-07-30 SBN:T.Barnes Updated and DATA_SET_DESCThis dataset contains RESAMPLED DATA of the CRUISE 2 phase (CR2). (Version 3.0 is the first version archived.)

A steady-State Genetic Algorithm with Resampling for Noisy Inventory Control

NARCIS (Netherlands)

Prestwich, S.; Tarim, S.A.; Rossi, R.; Hnich, B.

2008-01-01

Noisy fitness functions occur in many practical applications of evolutionary computation. A standard technique for solving these problems is fitness resampling but this may be inefficient or need a large population, and combined with elitism it may overvalue chromosomes or reduce genetic diversity.

RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

K. Gong

2017-05-01

Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

KAUST Repository

Liang, Faming; Cheng, Yichen; Song, Qifan; Park, Jincheol; Yang, Ping

2013-01-01

large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate

Resampling to accelerate cross-correlation searches for continuous gravitational waves from binary systems

Science.gov (United States)

Meadors, Grant David; Krishnan, Badri; Papa, Maria Alessandra; Whelan, John T.; Zhang, Yuanhao

2018-02-01

Continuous-wave (CW) gravitational waves (GWs) call for computationally-intensive methods. Low signal-to-noise ratio signals need templated searches with long coherent integration times and thus fine parameter-space resolution. Longer integration increases sensitivity. Low-mass x-ray binaries (LMXBs) such as Scorpius X-1 (Sco X-1) may emit accretion-driven CWs at strains reachable by current ground-based observatories. Binary orbital parameters induce phase modulation. This paper describes how resampling corrects binary and detector motion, yielding source-frame time series used for cross-correlation. Compared to the previous, detector-frame, templated cross-correlation method, used for Sco X-1 on data from the first Advanced LIGO observing run (O1), resampling is about 20 × faster in the costliest, most-sensitive frequency bands. Speed-up factors depend on integration time and search setup. The speed could be reinvested into longer integration with a forecast sensitivity gain, 20 to 125 Hz median, of approximately 51%, or from 20 to 250 Hz, 11%, given the same per-band cost and setup. This paper's timing model enables future setup optimization. Resampling scales well with longer integration, and at 10 × unoptimized cost could reach respectively 2.83 × and 2.75 × median sensitivities, limited by spin-wandering. Then an O1 search could yield a marginalized-polarization upper limit reaching torque-balance at 100 Hz. Frequencies from 40 to 140 Hz might be probed in equal observing time with 2 × improved detectors.

Hardware Architecture of Polyphase Filter Banks Performing Embedded Resampling for Software-Defined Radio Front-Ends

DEFF Research Database (Denmark)

Awan, Mehmood-Ur-Rehman; Le Moullec, Yannick; Koch, Peter

2012-01-01

, and power optimization for field programmable gate array (FPGA) based architectures in an M -path polyphase filter bank with modified N -path polyphase filter. Such systems allow resampling by arbitrary ratios while simultaneously performing baseband aliasing from center frequencies at Nyquist zones......In this paper, we describe resource-efficient hardware architectures for software-defined radio (SDR) front-ends. These architectures are made efficient by using a polyphase channelizer that performs arbitrary sample rate changes, frequency selection, and bandwidth control. We discuss area, time...... that are not multiples of the output sample rate. A non-maximally decimated polyphase filter bank, where the number of data loads is not equal to the number of M subfilters, processes M subfilters in a time period that is either less than or greater than the M data-load’s time period. We present a load...

Measuring environmental change in forest ecosystems by repeated soil sampling: a North American perspective

Science.gov (United States)

Lawrence, Gregory B.; Fernandez, Ivan J.; Richter, Daniel D.; Ross, Donald S.; Hazlett, Paul W.; Bailey, Scott W.; Oiumet, Rock; Warby, Richard A.F.; Johnson, Arthur H.; Lin, Henry; Kaste, James M.; Lapenis, Andrew G.; Sullivan, Timothy J.

2013-01-01

Environmental change is monitored in North America through repeated measurements of weather, stream and river flow, air and water quality, and most recently, soil properties. Some skepticism remains, however, about whether repeated soil sampling can effectively distinguish between temporal and spatial variability, and efforts to document soil change in forest ecosystems through repeated measurements are largely nascent and uncoordinated. In eastern North America, repeated soil sampling has begun to provide valuable information on environmental problems such as air pollution. This review synthesizes the current state of the science to further the development and use of soil resampling as an integral method for recording and understanding environmental change in forested settings. The origins of soil resampling reach back to the 19th century in England and Russia. The concepts and methodologies involved in forest soil resampling are reviewed and evaluated through a discussion of how temporal and spatial variability can be addressed with a variety of sampling approaches. Key resampling studies demonstrate the type of results that can be obtained through differing approaches. Ongoing, large-scale issues such as recovery from acidification, long-term N deposition, C sequestration, effects of climate change, impacts from invasive species, and the increasing intensification of soil management all warrant the use of soil resampling as an essential tool for environmental monitoring and assessment. Furthermore, with better awareness of the value of soil resampling, studies can be designed with a long-term perspective so that information can be efficiently obtained well into the future to address problems that have not yet surfaced.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

Science.gov (United States)

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Synchronizing data from irregularly sampled sensors

Science.gov (United States)

Uluyol, Onder

2017-07-11

A system and method include receiving a set of sampled measurements for each of multiple sensors, wherein the sampled measurements are at irregular intervals or different rates, re-sampling the sampled measurements of each of the multiple sensors at a higher rate than one of the sensor's set of sampled measurements, and synchronizing the sampled measurements of each of the multiple sensors.

On uniform resampling and gaze analysis of bidirectional texture functions

Czech Academy of Sciences Publication Activity Database

Filip, Jiří; Chantler, M.J.; Haindl, Michal

2009-01-01

Roč. 6, č. 3 (2009), s. 1-15 ISSN 1544-3558 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:EC Marie Curie(BE) 41358 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF * texture * eye tracking Subject RIV: BD - Theory of Information Impact factor: 1.447, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-on uniform resampling and gaze analysis of bidirectional texture functions.pdf

The Bootstrap, the Jackknife, and the Randomization Test: A Sampling Taxonomy.

Science.gov (United States)

Rodgers, J L

1999-10-01

A simple sampling taxonomy is defined that shows the differences between and relationships among the bootstrap, the jackknife, and the randomization test. Each method has as its goal the creation of an empirical sampling distribution that can be used to test statistical hypotheses, estimate standard errors, and/or create confidence intervals. Distinctions between the methods can be made based on the sampling approach (with replacement versus without replacement) and the sample size (replacing the whole original sample versus replacing a subset of the original sample). The taxonomy is useful for teaching the goals and purposes of resampling schemes. An extension of the taxonomy implies other possible resampling approaches that have not previously been considered. Univariate and multivariate examples are presented.

Computer Vision Tracking Using Particle Filters for 3D Position Estimation

Science.gov (United States)

2014-03-27

List of Acronyms Acronym Definition AFIT Air Force Institute of Technology ASIR Auxiliary Sampling Importance Re-sampling BPF Bootstrap Particle Filter...Auxiliary Sampling Importance Re-sampling ( ASIR ) filter, and Regularized Particle Filter (RPF), also seek to eliminate weight collapse through a variety

A Particle Smoother with Sequential Importance Resampling for soil hydraulic parameter estimation: A lysimeter experiment

Science.gov (United States)

Montzka, Carsten; Hendricks Franssen, Harrie-Jan; Moradkhani, Hamid; Pütz, Thomas; Han, Xujun; Vereecken, Harry

2013-04-01

An adequate description of soil hydraulic properties is essential for a good performance of hydrological forecasts. So far, several studies showed that data assimilation could reduce the parameter uncertainty by considering soil moisture observations. However, these observations and also the model forcings were recorded with a specific measurement error. It seems a logical step to base state updating and parameter estimation on observations made at multiple time steps, in order to reduce the influence of outliers at single time steps given measurement errors and unknown model forcings. Such outliers could result in erroneous state estimation as well as inadequate parameters. This has been one of the reasons to use a smoothing technique as implemented for Bayesian data assimilation methods such as the Ensemble Kalman Filter (i.e. Ensemble Kalman Smoother). Recently, an ensemble-based smoother has been developed for state update with a SIR particle filter. However, this method has not been used for dual state-parameter estimation. In this contribution we present a Particle Smoother with sequentially smoothing of particle weights for state and parameter resampling within a time window as opposed to the single time step data assimilation used in filtering techniques. This can be seen as an intermediate variant between a parameter estimation technique using global optimization with estimation of single parameter sets valid for the whole period, and sequential Monte Carlo techniques with estimation of parameter sets evolving from one time step to another. The aims are i) to improve the forecast of evaporation and groundwater recharge by estimating hydraulic parameters, and ii) to reduce the impact of single erroneous model inputs/observations by a smoothing method. In order to validate the performance of the proposed method in a real world application, the experiment is conducted in a lysimeter environment.

Assessment of Resampling Methods for Causality Testing: A note on the US Inflation Behavior

NARCIS (Netherlands)

Papana, A.; Kyrtsou, C.; Kugiumtzis, D.; Diks, C.

2017-01-01

Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial

Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods

Science.gov (United States)

MacKinnon, David P.; Lockwood, Chondra M.; Williams, Jason

2010-01-01

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall. PMID:20157642

Implementing reduced-risk integrated pest management in fresh-market cabbage: influence of sampling parameters, and validation of binomial sequential sampling plans for the cabbage looper (Lepidoptera Noctuidae).

Science.gov (United States)

Burkness, Eric C; Hutchison, W D

2009-10-01

Populations of cabbage looper, Trichoplusiani (Lepidoptera: Noctuidae), were sampled in experimental plots and commercial fields of cabbage (Brasicca spp.) in Minnesota during 1998-1999 as part of a larger effort to implement an integrated pest management program. Using a resampling approach and the Wald's sequential probability ratio test, sampling plans with different sampling parameters were evaluated using independent presence/absence and enumerative data. Evaluations and comparisons of the different sampling plans were made based on the operating characteristic and average sample number functions generated for each plan and through the use of a decision probability matrix. Values for upper and lower decision boundaries, sequential error rates (alpha, beta), and tally threshold were modified to determine parameter influence on the operating characteristic and average sample number functions. The following parameters resulted in the most desirable operating characteristic and average sample number functions; action threshold of 0.1 proportion of plants infested, tally threshold of 1, alpha = beta = 0.1, upper boundary of 0.15, lower boundary of 0.05, and resampling with replacement. We found that sampling parameters can be modified and evaluated using resampling software to achieve desirable operating characteristic and average sample number functions. Moreover, management of T. ni by using binomial sequential sampling should provide a good balance between cost and reliability by minimizing sample size and maintaining a high level of correct decisions (>95%) to treat or not treat.

A PLL-based resampling technique for vibration analysis in variable-speed wind turbines with PMSG: A bearing fault case

Science.gov (United States)

Pezzani, Carlos M.; Bossio, José M.; Castellino, Ariel M.; Bossio, Guillermo R.; De Angelo, Cristian H.

2017-02-01

Condition monitoring in permanent magnet synchronous machines has gained interest due to the increasing use in applications such as electric traction and power generation. Particularly in wind power generation, non-invasive condition monitoring techniques are of great importance. Usually, in such applications the access to the generator is complex and costly, while unexpected breakdowns results in high repair costs. This paper presents a technique which allows using vibration analysis for bearing fault detection in permanent magnet synchronous generators used in wind turbines. Given that in wind power applications the generator rotational speed may vary during normal operation, it is necessary to use special sampling techniques to apply spectral analysis of mechanical vibrations. In this work, a resampling technique based on order tracking without measuring the rotor position is proposed. To synchronize sampling with rotor position, an estimation of the rotor position obtained from the angle of the voltage vector is proposed. This angle is obtained from a phase-locked loop synchronized with the generator voltages. The proposed strategy is validated by laboratory experimental results obtained from a permanent magnet synchronous generator. Results with single point defects in the outer race of a bearing under variable speed and load conditions are presented.

Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren; Korup Andersen, Aske; Larsen, Anders Badsberg

2017-01-01

Continuous and long rainfall series are a necessity in rural and urban hydrology for analysis and design purposes. Local historical point rainfall series often cover several decades, which makes it possible to estimate rainfall means at different timescales, and to assess return periods of extreme...... includes climate changes projected to a specific future period. This paper presents a framework for resampling of historical point rainfall series in order to generate synthetic rainfall series, which has the same statistical properties as an original series. Using a number of key target predictions...... for the future climate, such as winter and summer precipitation, and representation of extreme events, the resampled historical series are projected to represent rainfall properties in a future climate. Climate-projected rainfall series are simulated by brute force randomization of model parameters, which leads...

PERPADUAN COMBINED SAMPLING DAN ENSEMBLE OF SUPPORT VECTOR MACHINE (ENSVM UNTUK MENANGANI KASUS CHURN PREDICTION PERUSAHAAN TELEKOMUNIKASI

Directory of Open Access Journals (Sweden)

Fernandy Marbun

2010-07-01

Full Text Available Churn prediction adalah suatu cara untuk memprediksi pelanggan yang berpotensial untuk churn. Data mining khususnya klasifikasi tampaknya dapat menjadi alternatif solusi dalam membuat model churn prediction yang akurat. Namun hasil klasifikasi menjadi tidak akurat disebabkan karena data churn bersifat imbalance. Kelas data menjadi tidak stabil karena data akan lebih condong ke bagian data yang memiliki komposisi data yang lebih besar. Salah satu cara untuk menangani permasalahan ini adalah dengan memodifikasi dataset yang digunakan atau yang lebih dikenal dengan metode resampling. Teknik resampling ini meliputi over-sampling, under-sampling, dan combined-sampling. Metode Ensemble of SVM (EnSVM diharapkan dapat meminimalisir kesalahan klasifikasi kelas mayor dan minor yang dihasilkan oleh classifier SVM tunggal. Dalam penelitian ini akan dicoba untuk memadukan combined sampling dan EnSVM untuk churn predicition. Pengujian dilakukan dengan membandingkan hasil klasifikasi CombinedSampling-EnSVM dengan SMOTE-SVM (perpaduan oversamping-SVM dan pure-SVM. Hasil pengujian menunjukkan bahwa metode CombinedSampling-EnSVM secara umum hanya mampu menghasilkan performansi Gini Index yang lebih baik daripada metode SMOTE-SVM dan tanpa resampling (pure-SVM.

Importance sampling the Rayleigh phase function

DEFF Research Database (Denmark)

Frisvad, Jeppe Revall

2011-01-01

Rayleigh scattering is used frequently in Monte Carlo simulation of multiple scattering. The Rayleigh phase function is quite simple, and one might expect that it should be simple to importance sample it efficiently. However, there seems to be no one good way of sampling it in the literature....... This paper provides the details of several different techniques for importance sampling the Rayleigh phase function, and it includes a comparison of their performance as well as hints toward efficient implementation....

A practitioners guide to resampling for data analysis, data mining, and modeling: A cookbook for starters

NARCIS (Netherlands)

van den Broek, Egon

A practitioner’s guide to resampling for data analysis, data mining, and modeling provides a gentle and pragmatic introduction in the proposed topics. Its supporting Web site was offline and, hence, its potentially added value could not be verified. The book refrains from using advanced mathematics

Honest Importance Sampling with Multiple Markov Chains.

Science.gov (United States)

Tan, Aixin; Doss, Hani; Hobert, James P

2015-01-01

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π 1 , is used to estimate an expectation with respect to another, π . The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π 1 is replaced by a Harris ergodic Markov chain with invariant density π 1 , then the resulting estimator remains strongly consistent. There is a price to be paid however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this paper, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general set up, where we assume that Markov chain samples from several probability densities, π 1 , …, π k , are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effects models under different priors. The second involves Bayesian variable

Evaluation of resampling applied to UAV imagery for weed detection using OBIA

OpenAIRE

Borra, I.; Peña Barragán, José Manuel; Torres Sánchez, Jorge; López Granados, Francisca

2015-01-01

Los vehículos aéreos no tripulados (UAVs) son una tecnología emergente en el estudio de parámetros agrícolas por sus características y por portar sensores en diferente rango espectral. En este trabajo se ha detectado y cartografiado rodales de malas hierbas en fase temprana mediante análisis OBIA para elaborar mapas que optimicen el tratamiento herbicida localizado. Se ha aplicado resampling (resampleo) sobre imágenes tomadas en campo desde un UAV (UAV-I) para crear una nueva imagen con disti...

Importance Sampling for Stochastic Timed Automata

DEFF Research Database (Denmark)

Jegourel, Cyrille; Larsen, Kim Guldstrand; Legay, Axel

2016-01-01

We present an importance sampling framework that combines symbolic analysis and simulation to estimate the probability of rare reachability properties in stochastic timed automata. By means of symbolic exploration, our framework first identifies states that cannot reach the goal. A state-wise cha......We present an importance sampling framework that combines symbolic analysis and simulation to estimate the probability of rare reachability properties in stochastic timed automata. By means of symbolic exploration, our framework first identifies states that cannot reach the goal. A state...

Adaptive Importance Sampling with a Rapidly Varying Importance Function

International Nuclear Information System (INIS)

Booth, Thomas E.

2000-01-01

It is known well that zero-variance Monte Carlo solutions are possible if an exact importance function is available to bias the random walks. Monte Carlo can be used to estimate the importance function. This estimated importance function then can be used to bias a subsequent Monte Carlo calculation that estimates an even better importance function; this iterative process is called adaptive importance sampling.To obtain the importance function, one can expand the importance function in a basis such as the Legendre polynomials and make Monte Carlo estimates of the expansion coefficients. For simple problems, Legendre expansions of order 10 to 15 are able to represent the importance function well enough to reduce the error geometrically by ten orders of magnitude or more. The more complicated problems are addressed in which the importance function cannot be represented well by Legendre expansions of order 10 to 15. In particular, a problem with a cross-section notch and a problem with a discontinuous cross section are considered

Resampling: An optimization method for inverse planning in robotic radiosurgery

International Nuclear Information System (INIS)

Schweikard, Achim; Schlaefer, Alexander; Adler, John R. Jr.

2006-01-01

By design, the range of beam directions in conventional radiosurgery are constrained to an isocentric array. However, the recent introduction of robotic radiosurgery dramatically increases the flexibility of targeting, and as a consequence, beams need be neither coplanar nor isocentric. Such a nonisocentric design permits a large number of distinct beam directions to be used in one single treatment. These major technical differences provide an opportunity to improve upon the well-established principles for treatment planning used with GammaKnife or LINAC radiosurgery. With this objective in mind, our group has developed over the past decade an inverse planning tool for robotic radiosurgery. This system first computes a set of beam directions, and then during an optimization step, weights each individual beam. Optimization begins with a feasibility query, the answer to which is derived through linear programming. This approach offers the advantage of completeness and avoids local optima. Final beam selection is based on heuristics. In this report we present and evaluate a new strategy for utilizing the advantages of linear programming to improve beam selection. Starting from an initial solution, a heuristically determined set of beams is added to the optimization problem, while beams with zero weight are removed. This process is repeated to sample a set of beams much larger compared with typical optimization. Experimental results indicate that the planning approach efficiently finds acceptable plans and that resampling can further improve its efficiency

ASSESSING SMALL SAMPLE WAR-GAMING DATASETS

Directory of Open Access Journals (Sweden)

W. J. HURLEY

2013-10-01

Full Text Available One of the fundamental problems faced by military planners is the assessment of changes to force structure. An example is whether to replace an existing capability with an enhanced system. This can be done directly with a comparison of measures such as accuracy, lethality, survivability, etc. However this approach does not allow an assessment of the force multiplier effects of the proposed change. To gauge these effects, planners often turn to war-gaming. For many war-gaming experiments, it is expensive, both in terms of time and dollars, to generate a large number of sample observations. This puts a premium on the statistical methodology used to examine these small datasets. In this paper we compare the power of three tests to assess population differences: the Wald-Wolfowitz test, the Mann-Whitney U test, and re-sampling. We employ a series of Monte Carlo simulation experiments. Not unexpectedly, we find that the Mann-Whitney test performs better than the Wald-Wolfowitz test. Resampling is judged to perform slightly better than the Mann-Whitney test.

Speckle reduction in digital holography with resampling ring masks

Science.gov (United States)

Zhang, Wenhui; Cao, Liangcai; Jin, Guofan

2018-01-01

One-shot digital holographic imaging has the advantages of high stability and low temporal cost. However, the reconstruction is affected by the speckle noise. Resampling ring-mask method in spectrum domain is proposed for speckle reduction. The useful spectrum of one hologram is divided into several sub-spectra by ring masks. In the reconstruction, angular spectrum transform is applied to guarantee the calculation accuracy which has no approximation. N reconstructed amplitude images are calculated from the corresponding sub-spectra. Thanks to speckle's random distribution, superimposing these N uncorrelated amplitude images would lead to a final reconstructed image with lower speckle noise. Normalized relative standard deviation values of the reconstructed image are used to evaluate the reduction of speckle. Effect of the method on the spatial resolution of the reconstructed image is also quantitatively evaluated. Experimental and simulation results prove the feasibility and effectiveness of the proposed method.

Time-Scale and Time-Frequency Analyses of Irregularly Sampled Astronomical Time Series

Directory of Open Access Journals (Sweden)

S. Roques

2005-09-01

Full Text Available We evaluate the quality of spectral restoration in the case of irregular sampled signals in astronomy. We study in details a time-scale method leading to a global wavelet spectrum comparable to the Fourier period, and a time-frequency matching pursuit allowing us to identify the frequencies and to control the error propagation. In both cases, the signals are first resampled with a linear interpolation. Both results are compared with those obtained using Lomb's periodogram and using the weighted waveletZ-transform developed in astronomy for unevenly sampled variable stars observations. These approaches are applied to simulations and to light variations of four variable stars. This leads to the conclusion that the matching pursuit is more efficient for recovering the spectral contents of a pulsating star, even with a preliminary resampling. In particular, the results are almost independent of the quality of the initial irregular sampling.

Analyzing Repeated Measures Marginal Models on Sample Surveys with Resampling Methods

Directory of Open Access Journals (Sweden)

James D. Knoke

2005-12-01

Full Text Available Packaged statistical software for analyzing categorical, repeated measures marginal models on sample survey data with binary covariates does not appear to be available. Consequently, this report describes a customized SAS program which accomplishes such an analysis on survey data with jackknifed replicate weights for which the primary sampling unit information has been suppressed for respondent confidentiality. First, the program employs the Macro Language and the Output Delivery System (ODS to estimate the means and covariances of indicator variables for the response variables, taking the design into account. Then, it uses PROC CATMOD and ODS, ignoring the survey design, to obtain the design matrix and hypothesis test specifications. Finally, it enters these results into another run of CATMOD, which performs automated direct input of the survey design specifications and accomplishes the appropriate analysis. This customized SAS program can be employed, with minor editing, to analyze general categorical, repeated measures marginal models on sample surveys with replicate weights. Finally, the results of our analysis accounting for the survey design are compared to the results of two alternate analyses of the same data. This comparison confirms that such alternate analyses, which do not properly account for the design, do not produce useful results.

Radioactivity monitoring of export/import samples - an update

International Nuclear Information System (INIS)

Shukla, V.K.; Murthy, M.V.R.; Sartandel, S.J.; Negi, B.S.; Sadasivan, S.

2001-01-01

137 Cs activity was measured in food samples exported from and imported into India during the period from 1993 to 2000. At present, on an average of about 1200 sample are estimated every year. Results showed no contamination of 137 Cs activity in samples that are exported from India. The few samples of diary products, imported in India during 1995 and 1996, showed low levels of 137 Cs activity. However, the levels were well with in the permissible values of Atomic Energy Regulatory Board (AERB). (author)

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

Science.gov (United States)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

Spatial Distribution and Sampling Plans With Fixed Level of Precision for Citrus Aphids (Hom., Aphididae) on Two Orange Species.

Science.gov (United States)

Kafeshani, Farzaneh Alizadeh; Rajabpour, Ali; Aghajanzadeh, Sirous; Gholamian, Esmaeil; Farkhari, Mohammad

2018-04-02

Aphis spiraecola Patch, Aphis gossypii Glover, and Toxoptera aurantii Boyer de Fonscolombe are three important aphid pests of citrus orchards. In this study, spatial distributions of the aphids on two orange species, Satsuma mandarin and Thomson navel, were evaluated using Taylor's power law and Iwao's patchiness. In addition, a fixed-precision sequential sampling plant was developed for each species on the host plant by Green's model at precision levels of 0.25 and 0.1. The results revealed that spatial distribution parameters and therefore the sampling plan were significantly different according to aphid and host plant species. Taylor's power law provides a better fit for the data than Iwao's patchiness regression. Except T. aurantii on Thomson navel orange, spatial distribution patterns of the aphids were aggregative on both citrus. T. aurantii had regular dispersion pattern on Thomson navel orange. Optimum sample size of the aphids varied from 30-2061 and 1-1622 shoots on Satsuma mandarin and Thomson navel orange based on aphid species and desired precision level. Calculated stop lines of the aphid species on Satsuma mandarin and Thomson navel orange ranged from 0.48 to 19 and 0.19 to 80.4 aphids per 24 shoots according to aphid species and desired precision level. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans (RVSP) software. This sampling program is useful for IPM program of the aphids in citrus orchards.

Winter Holts Oscillatory Method: A New Method of Resampling in Time Series.

Directory of Open Access Journals (Sweden)

Muhammad Imtiaz Subhani

2016-12-01

Full Text Available The core proposition behind this research is to create innovative methods of bootstrapping that can be applied in time series data. In order to find new methods of bootstrapping, various methods were reviewed; The data of automotive Sales, Market Shares and Net Exports of the top 10 countries, which includes China, Europe, United States of America (USA, Japan, Germany, South Korea, India, Mexico, Brazil, Spain and, Canada from 2002 to 2014 were collected through various sources which includes UN Comtrade, Index Mundi and World Bank. The findings of this paper confirmed that Bootstrapping for resampling through winter forecasting by Oscillation and Average methods give more robust results than the winter forecasting by any general methods.

A Fixed-Precision Sequential Sampling Plan for the Potato Tuberworm Moth, Phthorimaea operculella Zeller (Lepidoptera: Gelechidae), on Potato Cultivars.

Science.gov (United States)

Shahbi, M; Rajabpour, A

2017-08-01

Phthorimaea operculella Zeller is an important pest of potato in Iran. Spatial distribution and fixed-precision sequential sampling for population estimation of the pest on two potato cultivars, Arinda ® and Sante ® , were studied in two separate potato fields during two growing seasons (2013-2014 and 2014-2015). Spatial distribution was investigated by Taylor's power law and Iwao's patchiness. Results showed that the spatial distribution of eggs and larvae was random. In contrast to Iwao's patchiness, Taylor's power law provided a highly significant relationship between variance and mean density. Therefore, fixed-precision sequential sampling plan was developed by Green's model at two precision levels of 0.25 and 0.1. The optimum sample size on Arinda ® and Sante ® cultivars at precision level of 0.25 ranged from 151 to 813 and 149 to 802 leaves, respectively. At 0.1 precision level, the sample sizes varied from 5083 to 1054 and 5100 to 1050 leaves for Arinda ® and Sante ® cultivars, respectively. Therefore, the optimum sample sizes for the cultivars, with different resistance levels, were not significantly different. According to the calculated stop lines, the sampling must be continued until cumulative number of eggs + larvae reached to 15-16 or 96-101 individuals at precision levels of 0.25 or 0.1, respectively. The performance of the sampling plan was validated by resampling analysis using resampling for validation of sampling plans software. The sampling plant provided in this study can be used to obtain a rapid estimate of the pest density with minimal effort.

A support vector density-based importance sampling for reliability assessment

International Nuclear Information System (INIS)

Dai, Hongzhe; Zhang, Hao; Wang, Wei

2012-01-01

An importance sampling method based on the adaptive Markov chain simulation and support vector density estimation is developed in this paper for efficient structural reliability assessment. The methodology involves the generation of samples that can adaptively populate the important region by the adaptive Metropolis algorithm, and the construction of importance sampling density by support vector density. The use of the adaptive Metropolis algorithm may effectively improve the convergence and stability of the classical Markov chain simulation. The support vector density can approximate the sampling density with fewer samples in comparison to the conventional kernel density estimation. The proposed importance sampling method can effectively reduce the number of structural analysis required for achieving a given accuracy. Examples involving both numerical and practical structural problems are given to illustrate the application and efficiency of the proposed methodology.

State-dependent importance sampling for a Jackson tandem network

NARCIS (Netherlands)

Miretskiy, D.I.; Scheinhardt, W.R.W.; Mandjes, M.R.H.

2008-01-01

This paper considers importance sampling as a tool for rare-event simulation. The focus is on estimating the probability of overflow in the downstream queue of a Jacksonian two-node tandem queue – it is known that in this setting ‘traditional’ stateindependent importance-sampling distributions

State-dependent importance sampling for a Jackson tandem network

NARCIS (Netherlands)

D.I. Miretskiy; W.R.W. Scheinhardt (Werner); M.R.H. Mandjes (Michel)

2008-01-01

htmlabstractThis paper considers importance sampling as a tool for rare-event simulation. The focus is on estimating the probability of overflow in the downstream queue of a Jacksonian two-node tandem queue – it is known that in this setting ‘traditional’ stateindependent importance-sampling

A novel approach for epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model

Science.gov (United States)

Jannati, Mojtaba; Valadan Zoej, Mohammad Javad; Mokhtarzade, Mehdi

2018-03-01

This paper presents a novel approach to epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model (OPM). The backbone of the proposed method relies on modification of attitude parameters of linear array stereo imagery in such a way to parallelize the approximate conjugate epipolar lines (ACELs) with the instantaneous base line (IBL) of the conjugate image points (CIPs). Afterward, a complementary rotation is applied in order to parallelize all the ACELs throughout the stereo imagery. The new estimated attitude parameters are evaluated based on the direction of the IBL and the ACELs. Due to the spatial and temporal variability of the IBL (respectively changes in column and row numbers of the CIPs) and nonparallel nature of the epipolar lines in the stereo linear images, some polynomials in the both column and row numbers of the CIPs are used to model new attitude parameters. As the instantaneous position of sensors remains fix, the digital elevation model (DEM) of the area of interest is not required in the resampling process. According to the experimental results obtained from two pairs of SPOT and RapidEye stereo imagery with a high elevation relief, the average absolute values of remained vertical parallaxes of CIPs in the normalized images were obtained 0.19 and 0.28 pixels respectively, which confirm the high accuracy and applicability of the proposed method.

Iterative importance sampling algorithms for parameter estimation

OpenAIRE

Morzfeld, Matthias; Day, Marcus S.; Grout, Ray W.; Pau, George Shu Heng; Finsterle, Stefan A.; Bell, John B.

2016-01-01

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov Chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is ...

Some connections between importance sampling and enhanced sampling methods in molecular dynamics.

Science.gov (United States)

Lie, H C; Quer, J

2017-11-21

In molecular dynamics, enhanced sampling methods enable the collection of better statistics of rare events from a reference or target distribution. We show that a large class of these methods is based on the idea of importance sampling from mathematical statistics. We illustrate this connection by comparing the Hartmann-Schütte method for rare event simulation (J. Stat. Mech. Theor. Exp. 2012, P11004) and the Valsson-Parrinello method of variationally enhanced sampling [Phys. Rev. Lett. 113, 090601 (2014)]. We use this connection in order to discuss how recent results from the Monte Carlo methods literature can guide the development of enhanced sampling methods.

A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

KAUST Repository

Liang, Faming

2013-03-01

The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate of the parameters is updated accordingly under the framework of stochastic approximation. Since the proposed method makes use of only a small proportion of the data at each iteration, it avoids inverting large covariance matrices and thus is scalable to large datasets. The proposed method also leads to a general parameter estimation approach, maximum mean log-likelihood estimation, which includes the popular maximum (log)-likelihood estimation (MLE) approach as a special case and is expected to play an important role in analyzing large datasets. Under mild conditions, it is shown that the estimator resulting from the proposed method converges in probability to a set of parameter values of equivalent Gaussian probability measures, and that the estimator is asymptotically normally distributed. To the best of the authors\\' knowledge, the present study is the first one on asymptotic normality under infill asymptotics for general covariance functions. The proposed method is illustrated with large datasets, both simulated and real. Supplementary materials for this article are available online. © 2013 American Statistical Association.

MapReduce particle filtering with exact resampling and deterministic runtime

Science.gov (United States)

Thiyagalingam, Jeyarajan; Kekempanos, Lykourgos; Maskell, Simon

2017-12-01

Particle filtering is a numerical Bayesian technique that has great potential for solving sequential estimation problems involving non-linear and non-Gaussian models. Since the estimation accuracy achieved by particle filters improves as the number of particles increases, it is natural to consider as many particles as possible. MapReduce is a generic programming model that makes it possible to scale a wide variety of algorithms to Big data. However, despite the application of particle filters across many domains, little attention has been devoted to implementing particle filters using MapReduce. In this paper, we describe an implementation of a particle filter using MapReduce. We focus on a component that what would otherwise be a bottleneck to parallel execution, the resampling component. We devise a new implementation of this component, which requires no approximations, has O( N) spatial complexity and deterministic O((log N)2) time complexity. Results demonstrate the utility of this new component and culminate in consideration of a particle filter with 224 particles being distributed across 512 processor cores.

Monte Carlo parametric importance sampling with particle tracks scaling

International Nuclear Information System (INIS)

Ragheb, M.M.H.

1981-01-01

A method for Monte Carlo importance sampling with parametric dependence is proposed. It depends upon obtaining over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adopted and others rejected. The proposed method is applied to the finite slab penetration problem. When the exponential transformation is used, our method involves scaling of the generated particle tracks, and is a new application of Morton's method of similar trajectories. The method constitutes a generalization of Spanier's multistage importance sampling method, obtained by proper weighting over a single stage the curves he obtains over several stages, and preserves the statistical correlations between histories. It represents an extension of a theory by Frolov and Chentsov on Monte Carlo calculations of smooth curves to surfaces and to importance sampling calculations. By the proposed method, it seems possible to systematically arrive at minimum variance results and to avoid the infinite variances and effective biases sometimes observed in this type of calculation. (orig.) [de

Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

KAUST Repository

Cheon, Sooyoung

2013-02-16

Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities

KAUST Repository

Cheon, Sooyoung; Liang, Faming; Chen, Yuguo; Yu, Kai

2013-01-01

Importance sampling and Markov chain Monte Carlo methods have been used in exact inference for contingency tables for a long time, however, their performances are not always very satisfactory. In this paper, we propose a stochastic approximation Monte Carlo importance sampling (SAMCIS) method for tackling this problem. SAMCIS is a combination of adaptive Markov chain Monte Carlo and importance sampling, which employs the stochastic approximation Monte Carlo algorithm (Liang et al., J. Am. Stat. Assoc., 102(477):305-320, 2007) to draw samples from an enlarged reference set with a known Markov basis. Compared to the existing importance sampling and Markov chain Monte Carlo methods, SAMCIS has a few advantages, such as fast convergence, ergodicity, and the ability to achieve a desired proportion of valid tables. The numerical results indicate that SAMCIS can outperform the existing importance sampling and Markov chain Monte Carlo methods: It can produce much more accurate estimates in much shorter CPU time than the existing methods, especially for the tables with high degrees of freedom. © 2013 Springer Science+Business Media New York.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications.

Directory of Open Access Journals (Sweden)

Elias Chaibub Neto

Full Text Available In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.

Adaptive Importance Sampling Simulation of Queueing Networks

NARCIS (Netherlands)

de Boer, Pieter-Tjerk; Nicola, V.F.; Rubinstein, N.; Rubinstein, Reuven Y.

2000-01-01

In this paper, a method is presented for the efficient estimation of rare-event (overflow) probabilities in Jackson queueing networks using importance sampling. The method differs in two ways from methods discussed in most earlier literature: the change of measure is state-dependent, i.e., it is a

Estimating variability in functional images using a synthetic resampling approach

International Nuclear Information System (INIS)

Maitra, R.; O'Sullivan, F.

1996-01-01

Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods

Coalescent: an open-science framework for importance sampling in coalescent theory.

Science.gov (United States)

Tewari, Susanta; Spouge, John L

2015-01-01

Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner. Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3) for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux). Extensive tests and coverage make the framework reliable and maintainable. Conclusions. In coalescent theory, many studies of computational efficiency consider only

Coalescent: an open-science framework for importance sampling in coalescent theory

Directory of Open Access Journals (Sweden)

Susanta Tewari

2015-08-01

Full Text Available Background. In coalescent theory, computer programs often use importance sampling to calculate likelihoods and other statistical quantities. An importance sampling scheme can exploit human intuition to improve statistical efficiency of computations, but unfortunately, in the absence of general computer frameworks on importance sampling, researchers often struggle to translate new sampling schemes computationally or benchmark against different schemes, in a manner that is reliable and maintainable. Moreover, most studies use computer programs lacking a convenient user interface or the flexibility to meet the current demands of open science. In particular, current computer frameworks can only evaluate the efficiency of a single importance sampling scheme or compare the efficiencies of different schemes in an ad hoc manner.Results. We have designed a general framework (http://coalescent.sourceforge.net; language: Java; License: GPLv3 for importance sampling that computes likelihoods under the standard neutral coalescent model of a single, well-mixed population of constant size over time following infinite sites model of mutation. The framework models the necessary core concepts, comes integrated with several data sets of varying size, implements the standard competing proposals, and integrates tightly with our previous framework for calculating exact probabilities. For a given dataset, it computes the likelihood and provides the maximum likelihood estimate of the mutation parameter. Well-known benchmarks in the coalescent literature validate the accuracy of the framework. The framework provides an intuitive user interface with minimal clutter. For performance, the framework switches automatically to modern multicore hardware, if available. It runs on three major platforms (Windows, Mac and Linux. Extensive tests and coverage make the framework reliable and maintainable.Conclusions. In coalescent theory, many studies of computational efficiency

Automotive FMCW Radar-Enhanced Range Estimation via a Local Resampling Fourier Transform

Directory of Open Access Journals (Sweden)

Cailing Wang

2016-02-01

Full Text Available In complex traffic scenarios, more accurate measurement and discrimination for an automotive frequency-modulated continuous-wave (FMCW radar is required for intelligent robots, driverless cars and driver-assistant systems. A more accurate range estimation method based on a local resampling Fourier transform (LRFT for a FMCW radar is developed in this paper. Radar signal correlation in the phase space sees a higher signal-noise-ratio (SNR to achieve more accurate ranging, and the LRFT - which acts on a local neighbour as a refinement step - can achieve a more accurate target range. The rough range is estimated through conditional pulse compression (PC and then, around the initial rough estimation, a refined estimation through the LRFT in the local region achieves greater precision. Furthermore, the LRFT algorithm is tested in numerous simulations and physical system experiments, which show that the LRFT algorithm achieves a more precise range estimation than traditional FFT-based algorithms, especially for lower bandwidth signals.

On the Use of Importance Sampling in Particle Transport Problems

Energy Technology Data Exchange (ETDEWEB)

Eriksson, B

1965-06-15

The idea of importance sampling is applied to the problem of solving integral equations of Fredholm's type. Especially Bolzmann's neutron transport equation is taken into consideration. For the solution of the latter equation, an importance sampling technique is derived from some simple transformations at the original transport equation into a similar equation. Examples of transformations are given, which have been used with great success in practice.

On the Use of Importance Sampling in Particle Transport Problems

International Nuclear Information System (INIS)

Eriksson, B.

1965-06-01

The idea of importance sampling is applied to the problem of solving integral equations of Fredholm's type. Especially Bolzmann's neutron transport equation is taken into consideration. For the solution of the latter equation, an importance sampling technique is derived from some simple transformations at the original transport equation into a similar equation. Examples of transformations are given, which have been used with great success in practice

Adaptive multiple importance sampling for Gaussian processes

Czech Academy of Sciences Publication Activity Database

Xiong, X.; Šmídl, Václav; Filippone, M.

2017-01-01

Roč. 87, č. 8 (2017), s. 1644-1665 ISSN 0094-9655 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Gaussian Process * Bayesian estimation * Adaptive importance sampling Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.757, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0469804.pdf

Simulation of a Jackson tandem network using state-dependent importance sampling

NARCIS (Netherlands)

Miretskiy, D.I.; Scheinhardt, W.R.W.; Mandjes, M.R.H.

2008-01-01

This paper considers importance sampling as a tool for rare-event simulation. The focus is on estimating the probability of overflow in the downstream queue of a Jackson two-node tandem queue. It is known that in this setting 'traditional' state-independent importance-sampling distributions perform

Sampling frequency affects ActiGraph activity counts

DEFF Research Database (Denmark)

Brønd, Jan Christian; Arvidsson, Daniel

that is normally performed at frequencies higher than 2.5 Hz. With the ActiGraph model GT3X one has the option to select sample frequency from 30 to 100 Hz. This study investigated the effect of the sampling frequency on the ouput of the bandpass filter.Methods: A synthetic frequency sweep of 0-15 Hz was generated...... in Matlab and sampled at frequencies of 30-100 Hz. Also, acceleration signals during indoor walking and running were sampled at 30 Hz using the ActiGraph GT3X and resampled in Matlab to frequencies of 40-100 Hz. All data was processed with the ActiLife software.Results: Acceleration frequencies between 5......-15 Hz escaped the bandpass filter when sampled at 40, 50, 70, 80 and 100 Hz, while this was not the case when sampled at 30, 60 and 90 Hz. During the ambulatory activities this artifact resultet in different activity count output from the ActiLife software with different sampling frequency...

Minimum variance Monte Carlo importance sampling with parametric dependence

International Nuclear Information System (INIS)

Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

1981-01-01

An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

Joint importance sampling of low-order volumetric scattering

DEFF Research Database (Denmark)

Georgiev, Iliyan; Křivánek, Jaroslav; Hachisuka, Toshiya

2013-01-01

Central to all Monte Carlo-based rendering algorithms is the construction of light transport paths from the light sources to the eye. Existing rendering approaches sample path vertices incrementally when constructing these light transport paths. The resulting probability density is thus a product...... of the conditional densities of each local sampling step, constructed without explicit control over the form of the final joint distribution of the complete path. We analyze why current incremental construction schemes often lead to high variance in the presence of participating media, and reveal...... that such approaches are an unnecessary legacy inherited from traditional surface-based rendering algorithms. We devise joint importance sampling of path vertices in participating media to construct paths that explicitly account for the product of all scattering and geometry terms along a sequence of vertices instead...

Testing of a method of importance sampling for use with SYVAC

International Nuclear Information System (INIS)

Dalrymple, G.J.; Prust, J.O.; Edwards, H.H.

1985-10-01

The Importance Sampling Scheme is designed to concentrate sampling in the high dose region of the parameter space. A sensitivity analysis of an intitial case study is used to roughly define the high dose and risk region of the parameter space. By applying modified distribution to the individual parameter ranges it was possible to concentrate sampling in regions of the parameter range that lead to high doses and risks. Comparison of risk estimates and cumulative distribution functions of dose for an increasing number of runs of the SYVAC model indicated that the risk estimate had converged at 1200 Importance Sampling runs. Examination of a plot of risk in various dose bands supported this conclusion. It was clear that the random sampling had not achieved convergence at 400 runs. (author)

Failure Probability Calculation Method Using Kriging Metamodel-based Importance Sampling Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Seunggyu [Korea Aerospace Research Institue, Daejeon (Korea, Republic of); Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2017-05-15

The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

Fine-mapping additive and dominant SNP effects using group-LASSO and Fractional Resample Model Averaging

Science.gov (United States)

Sabourin, Jeremy; Nobel, Andrew B.; Valdar, William

2014-01-01

Genomewide association studies sometimes identify loci at which both the number and identities of the underlying causal variants are ambiguous. In such cases, statistical methods that model effects of multiple SNPs simultaneously can help disentangle the observed patterns of association and provide information about how those SNPs could be prioritized for follow-up studies. Current multi-SNP methods, however, tend to assume that SNP effects are well captured by additive genetics; yet when genetic dominance is present, this assumption translates to reduced power and faulty prioritizations. We describe a statistical procedure for prioritizing SNPs at GWAS loci that efficiently models both additive and dominance effects. Our method, LLARRMA-dawg, combines a group LASSO procedure for sparse modeling of multiple SNP effects with a resampling procedure based on fractional observation weights; it estimates for each SNP the robustness of association with the phenotype both to sampling variation and to competing explanations from other SNPs. In producing a SNP prioritization that best identifies underlying true signals, we show that: our method easily outperforms a single marker analysis; when additive-only signals are present, our joint model for additive and dominance is equivalent to or only slightly less powerful than modeling additive-only effects; and, when dominance signals are present, even in combination with substantial additive effects, our joint model is unequivocally more powerful than a model assuming additivity. We also describe how performance can be improved through calibrated randomized penalization, and discuss how dominance in ungenotyped SNPs can be incorporated through either heterozygote dosage or multiple imputation. PMID:25417853

Screen Space Ambient Occlusion Based Multiple Importance Sampling for Real-Time Rendering

Science.gov (United States)

Zerari, Abd El Mouméne; Babahenini, Mohamed Chaouki

2018-03-01

We propose a new approximation technique for accelerating the Global Illumination algorithm for real-time rendering. The proposed approach is based on the Screen-Space Ambient Occlusion (SSAO) method, which approximates the global illumination for large, fully dynamic scenes at interactive frame rates. Current algorithms that are based on the SSAO method suffer from difficulties due to the large number of samples that are required. In this paper, we propose an improvement to the SSAO technique by integrating it with a Multiple Importance Sampling technique that combines a stratified sampling method with an importance sampling method, with the objective of reducing the number of samples. Experimental evaluation demonstrates that our technique can produce high-quality images in real time and is significantly faster than traditional techniques.

Convergence and Efficiency of Adaptive Importance Sampling Techniques with Partial Biasing

Science.gov (United States)

Fort, G.; Jourdain, B.; Lelièvre, T.; Stoltz, G.

2018-04-01

We propose a new Monte Carlo method to efficiently sample a multimodal distribution (known up to a normalization constant). We consider a generalization of the discrete-time Self Healing Umbrella Sampling method, which can also be seen as a generalization of well-tempered metadynamics. The dynamics is based on an adaptive importance technique. The importance function relies on the weights (namely the relative probabilities) of disjoint sets which form a partition of the space. These weights are unknown but are learnt on the fly yielding an adaptive algorithm. In the context of computational statistical physics, the logarithm of these weights is, up to an additive constant, the free-energy, and the discrete valued function defining the partition is called the collective variable. The algorithm falls into the general class of Wang-Landau type methods, and is a generalization of the original Self Healing Umbrella Sampling method in two ways: (i) the updating strategy leads to a larger penalization strength of already visited sets in order to escape more quickly from metastable states, and (ii) the target distribution is biased using only a fraction of the free-energy, in order to increase the effective sample size and reduce the variance of importance sampling estimators. We prove the convergence of the algorithm and analyze numerically its efficiency on a toy example.

Performance evaluation of an importance sampling technique in a Jackson network

Science.gov (United States)

brahim Mahdipour, E.; Masoud Rahmani, Amir; Setayeshi, Saeed

2014-03-01

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.

Adaptive control of theophylline therapy: importance of blood sampling times.

Science.gov (United States)

D'Argenio, D Z; Khakmahd, K

1983-10-01

A two-observation protocol for estimating theophylline clearance during a constant-rate intravenous infusion is used to examine the importance of blood sampling schedules with regard to the information content of resulting concentration data. Guided by a theory for calculating maximally informative sample times, population simulations are used to assess the effect of specific sampling times on the precision of resulting clearance estimates and subsequent predictions of theophylline plasma concentrations. The simulations incorporated noise terms for intersubject variability, dosing errors, sample collection errors, and assay error. Clearance was estimated using Chiou's method, least squares, and a Bayesian estimation procedure. The results of these simulations suggest that clinically significant estimation and prediction errors may result when using the above two-point protocol for estimating theophylline clearance if the time separating the two blood samples is less than one population mean elimination half-life.

The study of importance sampling in Monte-carlo calculation of blocking dips

International Nuclear Information System (INIS)

Pan Zhengying; Zhou Peng

1988-01-01

Angular blocking dips around the axis in Al single crystal of α-particles of about 2 Mev produced at a depth of 0.2 μm are calculated by a Monte-carlo simulation. The influence of the small solid angle emission of particles and the importance sampling in the solid angle emission have been investigated. By means of importance sampling, a more reasonable results with high accuracy are obtained

Evaluation of the Validity of Groundwater Samples Obtained Using the Purge Water Management System at SRS

International Nuclear Information System (INIS)

Beardsley, C.C.

1999-01-01

As part of the demonstration testing of the Purge Water Management System (PWMS) technology at the Savannah River Site (SRS), four wells were equipped with PWMS units in 1997 and a series of sampling events were conducted at each during 1997-1998. Three of the wells were located in A/M Area while the fourth was located at the Old Radioactive Waste Burial Ground in the General Separations Area.The PWMS is a ''closed-loop'', non-contact, system used to collect and return purge water to the originating aquifer after a sampling event without having significantly altered the water quality. One of the primary concerns as to its applicability at SRS, and elsewhere, is whether the PWMS might resample groundwater that is returned to the aquifer during the previous sampling event. The purpose of the present investigation was to compare groundwater chemical analysis data collected at the four test wells using the PWMS vs. historical data collected using the standard monitoring program methodology to determine if the PWMS provides representative monitoring samples.The analysis of the groundwater chemical concentrations indicates that the PWMS sampling methodology acquired representative groundwater samples at monitoring wells ABP-1A, ABP-4, ARP-3 and BGO-33C. Representative groundwater samples are achieved if the PWMS does not resample groundwater that has been purged and returned during a previous sampling event. Initial screening calculations, conducted prior to the selection of these four wells, indicated that groundwater velocities were high enough under the ambient hydraulic gradients to preclude resampling from occurring at the time intervals that were used at each well. Corroborating evidence included a tracer test that was conducted at BGO-33C, the high degree of similarity between analyte concentrations derived from the PWMS samples and those obtained from historical protocol sampling, as well as the fact that PWMS data extend all previously existing concentration

Hybrid algorithm of ensemble transform and importance sampling for assimilation of non-Gaussian observations

Directory of Open Access Journals (Sweden)

Shin'ya Nakano

2014-05-01

Full Text Available A hybrid algorithm that combines the ensemble transform Kalman filter (ETKF and the importance sampling approach is proposed. Since the ETKF assumes a linear Gaussian observation model, the estimate obtained by the ETKF can be biased in cases with nonlinear or non-Gaussian observations. The particle filter (PF is based on the importance sampling technique, and is applicable to problems with nonlinear or non-Gaussian observations. However, the PF usually requires an unrealistically large sample size in order to achieve a good estimation, and thus it is computationally prohibitive. In the proposed hybrid algorithm, we obtain a proposal distribution similar to the posterior distribution by using the ETKF. A large number of samples are then drawn from the proposal distribution, and these samples are weighted to approximate the posterior distribution according to the importance sampling principle. Since the importance sampling provides an estimate of the probability density function (PDF without assuming linearity or Gaussianity, we can resolve the bias due to the nonlinear or non-Gaussian observations. Finally, in the next forecast step, we reduce the sample size to achieve computational efficiency based on the Gaussian assumption, while we use a relatively large number of samples in the importance sampling in order to consider the non-Gaussian features of the posterior PDF. The use of the ETKF is also beneficial in terms of the computational simplicity of generating a number of random samples from the proposal distribution and in weighting each of the samples. The proposed algorithm is not necessarily effective in case that the ensemble is located distant from the true state. However, monitoring the effective sample size and tuning the factor for covariance inflation could resolve this problem. In this paper, the proposed hybrid algorithm is introduced and its performance is evaluated through experiments with non-Gaussian observations.

Time-dependent importance sampling in semiclassical initial value representation calculations for time correlation functions.

Science.gov (United States)

Tao, Guohua; Miller, William H

2011-07-14

An efficient time-dependent importance sampling method is developed for the Monte Carlo calculation of time correlation functions via the initial value representation (IVR) of semiclassical (SC) theory. A prefactor-free time-dependent sampling function weights the importance of a trajectory based on the magnitude of its contribution to the time correlation function, and global trial moves are used to facilitate the efficient sampling the phase space of initial conditions. The method can be generally applied to sampling rare events efficiently while avoiding being trapped in a local region of the phase space. Results presented in the paper for two system-bath models demonstrate the efficiency of this new importance sampling method for full SC-IVR calculations.

Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.

Science.gov (United States)

Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B

2013-03-01

Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.

Decomposition and (importance) sampling techniques for multi-stage stochastic linear programs

Energy Technology Data Exchange (ETDEWEB)

Infanger, G.

1993-11-01

The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.

Estimation of functional failure probability of passive systems based on adaptive importance sampling method

International Nuclear Information System (INIS)

Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing

2012-01-01

In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)

A cautionary note on substituting spatial subunits for repeated temporal sampling in studies of site occupancy

Science.gov (United States)

Kendall, William L.; White, Gary C.

2009-01-01

1. Assessing the probability that a given site is occupied by a species of interest is important to resource managers, as well as metapopulation or landscape ecologists. Managers require accurate estimates of the state of the system, in order to make informed decisions. Models that yield estimates of occupancy, while accounting for imperfect detection, have proven useful by removing a potentially important source of bias. To account for detection probability, multiple independent searches per site for the species are required, under the assumption that the species is available for detection during each search of an occupied site. 2. We demonstrate that when multiple samples per site are defined by searching different locations within a site, absence of the species from a subset of these spatial subunits induces estimation bias when locations are exhaustively assessed or sampled without replacement. 3. We further demonstrate that this bias can be removed by choosing sampling locations with replacement, or if the species is highly mobile over a short period of time. 4. Resampling an existing data set does not mitigate bias due to exhaustive assessment of locations or sampling without replacement. 5. Synthesis and applications. Selecting sampling locations for presence/absence surveys with replacement is practical in most cases. Such an adjustment to field methods will prevent one source of bias, and therefore produce more robust statistical inferences about species occupancy. This will in turn permit managers to make resource decisions based on better knowledge of the state of the system.

Comparison of T-Square, Point Centered Quarter, and N-Tree Sampling Methods in Pittosporum undulatum Invaded Woodlands

Directory of Open Access Journals (Sweden)

Lurdes Borges Silva

2017-01-01

Full Text Available Tree density is an important parameter affecting ecosystems functions and management decisions, while tree distribution patterns affect sampling design. Pittosporum undulatum stands in the Azores are being targeted with a biomass valorization program, for which efficient tree density estimators are required. We compared T-Square sampling, Point Centered Quarter Method (PCQM, and N-tree sampling with benchmark quadrat (QD sampling in six 900 m2 plots established at P. undulatum stands in São Miguel Island. A total of 15 estimators were tested using a data resampling approach. The estimated density range (344–5056 trees/ha was found to agree with previous studies using PCQM only. Although with a tendency to underestimate tree density (in comparison with QD, overall, T-Square sampling appeared to be the most accurate and precise method, followed by PCQM. Tree distribution pattern was found to be slightly aggregated in 4 of the 6 stands. Considering (1 the low level of bias and high precision, (2 the consistency among three estimators, (3 the possibility of use with aggregated patterns, and (4 the possibility of obtaining a larger number of independent tree parameter estimates, we recommend the use of T-Square sampling in P. undulatum stands within the framework of a biomass valorization program.

Monte Carlo importance sampling optimization for system reliability applications

International Nuclear Information System (INIS)

Campioni, Luca; Vestrucci, Paolo

2004-01-01

This paper focuses on the reliability analysis of multicomponent systems by the importance sampling technique, and, in particular, it tackles the optimization aspect. A methodology based on the minimization of the variance at the component level is proposed for the class of systems consisting of independent components. The claim is that, by means of such a methodology, the optimal biasing could be achieved without resorting to the typical approach by trials

Food and feed safety assessment: the importance of proper sampling.

Science.gov (United States)

Kuiper, Harry A; Paoletti, Claudia

2015-01-01

The general principles for safety and nutritional evaluation of foods and feed and the potential health risks associated with hazardous compounds are described as developed by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO) and further elaborated in the European Union-funded project Safe Foods. We underline the crucial role of sampling in foods/feed safety assessment. High quality sampling should always be applied to ensure the use of adequate and representative samples as test materials for hazard identification, toxicological and nutritional characterization of identified hazards, as well as for estimating quantitative and reliable exposure levels of foods/feed or related compounds of concern for humans and animals. The importance of representative sampling is emphasized through examples of risk analyses in different areas of foods/feed production. The Theory of Sampling (TOS) is recognized as the only framework within which to ensure accuracy and precision of all sampling steps involved in the field-to-fork continuum, which is crucial to monitor foods and feed safety. Therefore, TOS must be integrated in the well-established FAO/WHO risk assessment approach in order to guarantee a transparent and correct frame for the risk assessment and decision making process.

Improved importance sampling technique for efficient simulation of digital communication systems

Science.gov (United States)

Lu, Dingqing; Yao, Kung

1988-01-01

A new, improved importance sampling (IIS) approach to simulation is considered. Some basic concepts of IS are introduced, and detailed evolutions of simulation estimation variances for Monte Carlo (MC) and IS simulations are given. The general results obtained from these evolutions are applied to the specific previously known conventional importance sampling (CIS) technique and the new IIS technique. The derivation for a linear system with no signal random memory is considered in some detail. For the CIS technique, the optimum input scaling parameter is found, while for the IIS technique, the optimum translation parameter is found. The results are generalized to a linear system with memory and signals. Specific numerical and simulation results are given which show the advantages of CIS over MC and IIS over CIS for simulations of digital communications systems.

Bootstrap resampling: a powerful method of assessing confidence intervals for doses from experimental data

International Nuclear Information System (INIS)

Iwi, G.; Millard, R.K.; Palmer, A.M.; Preece, A.W.; Saunders, M.

1999-01-01

Bootstrap resampling provides a versatile and reliable statistical method for estimating the accuracy of quantities which are calculated from experimental data. It is an empirically based method, in which large numbers of simulated datasets are generated by computer from existing measurements, so that approximate confidence intervals of the derived quantities may be obtained by direct numerical evaluation. A simple introduction to the method is given via a detailed example of estimating 95% confidence intervals for cumulated activity in the thyroid following injection of 99m Tc-sodium pertechnetate using activity-time data from 23 subjects. The application of the approach to estimating confidence limits for the self-dose to the kidney following injection of 99m Tc-DTPA organ imaging agent based on uptake data from 19 subjects is also illustrated. Results are then given for estimates of doses to the foetus following administration of 99m Tc-sodium pertechnetate for clinical reasons during pregnancy, averaged over 25 subjects. The bootstrap method is well suited for applications in radiation dosimetry including uncertainty, reliability and sensitivity analysis of dose coefficients in biokinetic models, but it can also be applied in a wide range of other biomedical situations. (author)

An Importance Sampling Simulation Method for Bayesian Decision Feedback Equalizers

OpenAIRE

Chen, S.; Hanzo, L.

2000-01-01

An importance sampling (IS) simulation technique is presented for evaluating the lower-bound bit error rate (BER) of the Bayesian decision feedback equalizer (DFE) under the assumption of correct decisions being fed back. A design procedure is developed, which chooses appropriate bias vectors for the simulation density to ensure asymptotic efficiency of the IS simulation.

A hybrid reliability algorithm using PSO-optimized Kriging model and adaptive importance sampling

Science.gov (United States)

Tong, Cao; Gong, Haili

2018-03-01

This paper aims to reduce the computational cost of reliability analysis. A new hybrid algorithm is proposed based on PSO-optimized Kriging model and adaptive importance sampling method. Firstly, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of Kriging model. A typical function is fitted to validate improvement by comparing results of PSO-optimized Kriging model with those of the original Kriging model. Secondly, a hybrid algorithm for reliability analysis combined optimized Kriging model and adaptive importance sampling is proposed. Two cases from literatures are given to validate the efficiency and correctness. The proposed method is proved to be more efficient due to its application of small number of sample points according to comparison results.

Adaptive importance sampling for probabilistic validation of advanced driver assistance systems

NARCIS (Netherlands)

Gietelink, O.J.; Schutter, B. de; Verhaegen, M.

2006-01-01

We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The

Non-parametric adaptive importance sampling for the probability estimation of a launcher impact position

International Nuclear Information System (INIS)

Morio, Jerome

2011-01-01

Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.

Adaptive importance sampling of random walks on continuous state spaces

International Nuclear Information System (INIS)

Baggerly, K.; Cox, D.; Picard, R.

1998-01-01

The authors consider adaptive importance sampling for a random walk with scoring in a general state space. Conditions under which exponential convergence occurs to the zero-variance solution are reviewed. These results generalize previous work for finite, discrete state spaces in Kollman (1993) and in Kollman, Baggerly, Cox, and Picard (1996). This paper is intended for nonstatisticians and includes considerable explanatory material

Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models

NARCIS (Netherlands)

Koopman, S.J.; Lucas, A.; Scharth, M.

2015-01-01

We propose a general likelihood evaluation method for nonlinear non-Gaussian state-space models using the simulation-based method of efficient importance sampling. We minimize the simulation effort by replacing some key steps of the likelihood estimation procedure by numerical integration. We refer

Sampling high-altitude and stratified mating flights of red imported fire ant.

Science.gov (United States)

Fritz, Gary N; Fritz, Ann H; Vander Meer, Robert K

2011-05-01

With the exception of an airplane equipped with nets, no method has been developed that successfully samples red imported fire ant, Solenopsis invicta Buren, sexuals in mating/dispersal flights throughout their potential altitudinal trajectories. We developed and tested a method for sampling queens and males during mating flights at altitudinal intervals reaching as high as "140 m. Our trapping system uses an electric winch and a 1.2-m spindle bolted to a swiveling platform. The winch dispenses up to 183 m of Kevlar-core, nylon rope and the spindle stores 10 panels (0.9 by 4.6 m each) of nylon tulle impregnated with Tangle-Trap. The panels can be attached to the rope at various intervals and hoisted into the air by using a 3-m-diameter, helium-filled balloon. Raising or lowering all 10 panels takes approximately 15-20 min. This trap also should be useful for altitudinal sampling of other insects of medical importance.

40 CFR 80.335 - What gasoline sample retention requirements apply to refiners and importers?

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false What gasoline sample retention... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Gasoline Sulfur Sampling, Testing and Retention Requirements for Refiners and Importers § 80.335 What gasoline sample...

Importance Sampling Simulation of Population Overflow in Two-node Tandem Networks

NARCIS (Netherlands)

Nicola, V.F.; Zaburnenko, T.S.; Baier, C; Chiola, G.; Smirni, E.

2005-01-01

In this paper we consider the application of importance sampling in simulations of Markovian tandem networks in order to estimate the probability of rare events, such as network population overflow. We propose a heuristic methodology to obtain a good approximation to the 'optimal' state-dependent

The use of importance sampling in a trial assessment to obtain converged estimates of radiological risk

International Nuclear Information System (INIS)

Johnson, K.; Lucas, R.

1986-12-01

In developing a methodology for assessing potential sites for the disposal of radioactive wastes, the Department of the Environment has conducted a series of trial assessment exercises. In order to produce converged estimates of radiological risk using the SYVAC A/C simulation system an efficient sampling procedure is required. Previous work has demonstrated that importance sampling can substantially increase sampling efficiency. This study used importance sampling to produce converged estimates of risk for the first DoE trial assessment. Four major nuclide chains were analysed. In each case importance sampling produced converged risk estimates with between 10 and 170 times fewer runs of the SYVAC A/C model. This increase in sampling efficiency can reduce the total elapsed time required to obtain a converged estimate of risk from one nuclide chain by a factor of 20. The results of this study suggests that the use of importance sampling could reduce the elapsed time required to perform a risk assessment of a potential site by a factor of ten. (author)

A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS) measurements

Science.gov (United States)

Dohe, S.; Sherlock, V.; Hase, F.; Gisi, M.; Robinson, J.; Sepúlveda, E.; Schneider, M.; Blumenstock, T.

2013-08-01

The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2-0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS measurements

Directory of Open Access Journals (Sweden)

S. Dohe

2013-08-01

Full Text Available The Total Carbon Column Observing Network (TCCON has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment. Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y at both sites show discrepancies of 0.2–0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

STATE ESTIMATION IN ALCOHOLIC CONTINUOUS FERMENTATION OF ZYMOMONAS MOBILIS USING RECURSIVE BAYESIAN FILTERING: A SIMULATION APPROACH

Directory of Open Access Journals (Sweden)

Olga Lucia Quintero

2008-05-01

Full Text Available This work presents a state estimator for a continuous bioprocess. To this aim, the Non Linear Filtering theory based on the recursive application of Bayes rule and Monte Carlo techniques is used. Recursive Bayesian Filters Sampling Importance Resampling (SIR is employed, including different kinds of resampling. Generally, bio-processes have strong non-linear and non-Gaussian characteristics, and this tool becomes attractive. The estimator behavior and performance are illustrated with the continuous process of alcoholic fermentation of Zymomonas mobilis. Not too many applications with this tool have been reported in the biotechnological area.

Importance Sampling for Failure Probabilities in Computing and Data Transmission

DEFF Research Database (Denmark)

Asmussen, Søren

We study efficient simulation algorithms for estimating P(Χ > χ), where Χ is the total time of a job with ideal time T that needs to be restarted after a failure. The main tool is importance sampling where one tries to identify a good importance distribution via an asymptotic description...... of the conditional distribution of T given Χ > χ. If T ≡ t is constant, the problem reduces to the efficient simulation of geometric sums, and a standard algorithm involving a Cramér type root  γ(t) is available. However, we also discuss  an algorithm avoiding the rootfinding. If T is random, particular attention...... is given to T having either a gamma-like tail or a regularly varying tail, and to failures at Poisson times. Different type of conditional limits occur, in particular exponentially tilted Gumbel distributions and Pareto distributions. The algorithms based upon importance distributions for T using...

Importance sampling for failure probabilities in computing and data transmission

DEFF Research Database (Denmark)

Asmussen, Søren

2009-01-01

In this paper we study efficient simulation algorithms for estimating P(X›x), where X is the total time of a job with ideal time $T$ that needs to be restarted after a failure. The main tool is importance sampling, where a good importance distribution is identified via an asymptotic description...... of the conditional distribution of T given X›x. If T≡t is constant, the problem reduces to the efficient simulation of geometric sums, and a standard algorithm involving a Cramér-type root, γ(t), is available. However, we also discuss an algorithm that avoids finding the root. If T is random, particular attention...... is given to T having either a gamma-like tail or a regularly varying tail, and to failures at Poisson times. Different types of conditional limit occur, in particular exponentially tilted Gumbel distributions and Pareto distributions. The algorithms based upon importance distributions for T using...

System health monitoring using multiple-model adaptive estimation techniques

Science.gov (United States)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

KAUST Repository

Beck, Joakim

2018-02-19

In calculating expected information gain in optimal Bayesian experimental design, the computation of the inner loop in the classical double-loop Monte Carlo requires a large number of samples and suffers from underflow if the number of samples is small. These drawbacks can be avoided by using an importance sampling approach. We present a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop. We derive the optimal values for the method parameters in which the average computational cost is minimized for a specified error tolerance. We use three numerical examples to demonstrate the computational efficiency of our method compared with the classical double-loop Monte Carlo, and a single-loop Monte Carlo method that uses the Laplace approximation of the return value of the inner loop. The first demonstration example is a scalar problem that is linear in the uncertain parameter. The second example is a nonlinear scalar problem. The third example deals with the optimal sensor placement for an electrical impedance tomography experiment to recover the fiber orientation in laminate composites.

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

Science.gov (United States)

Beck, Joakim; Dia, Ben Mansour; Espath, Luis F. R.; Long, Quan; Tempone, Raúl

2018-06-01

In calculating expected information gain in optimal Bayesian experimental design, the computation of the inner loop in the classical double-loop Monte Carlo requires a large number of samples and suffers from underflow if the number of samples is small. These drawbacks can be avoided by using an importance sampling approach. We present a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop. We derive the optimal values for the method parameters in which the average computational cost is minimized according to the desired error tolerance. We use three numerical examples to demonstrate the computational efficiency of our method compared with the classical double-loop Monte Carlo, and a more recent single-loop Monte Carlo method that uses the Laplace method as an approximation of the return value of the inner loop. The first example is a scalar problem that is linear in the uncertain parameter. The second example is a nonlinear scalar problem. The third example deals with the optimal sensor placement for an electrical impedance tomography experiment to recover the fiber orientation in laminate composites.

Subsolutions of an Isaacs Equation and Efficient Schemes for Importance Sampling: Convergence Analysis

National Research Council Canada - National Science Library

Dupuis, Paul; Wang, Hui

2005-01-01

Previous papers by authors establish the connection between importance sampling algorithms for estimating rare-event probabilities, two-person zero-sum differential games, and the associated Isaacs equation...

Role of importance of X-ray fluorescence analysis of forensic samples

International Nuclear Information System (INIS)

Jha, Shailendra; Sharma, M.

2009-01-01

Full text: In the field of forensic science, it is very important to investigate the evidential samples obtained at various crime scenes. X-ray fluorescence (XRF) is used widely in forensic science [1]. Its main strength is its non-destructive nature, thus preserving evidence [2, 3]. In this paper, we report the application of XRF to examine the evidences like purity gold and silver jewelry (Indian Ornaments), remnants of glass pieces and paint chips recovered from crime scenes. The experimental measurements on these samples have been made using X-ray fluorescence spectrometer (LAB Center XRF-1800) procured from Shimazdu Scientific Inst., USA. The results are explained in terms of quantitative/ qualitative analysis of trace elements. (author)

Fast Generation of Ensembles of Cosmological N-Body Simulations via Mode-Resampling

Energy Technology Data Exchange (ETDEWEB)

Schneider, M D; Cole, S; Frenk, C S; Szapudi, I

2011-02-14

We present an algorithm for quickly generating multiple realizations of N-body simulations to be used, for example, for cosmological parameter estimation from surveys of large-scale structure. Our algorithm uses a new method to resample the large-scale (Gaussian-distributed) Fourier modes in a periodic N-body simulation box in a manner that properly accounts for the nonlinear mode-coupling between large and small scales. We find that our method for adding new large-scale mode realizations recovers the nonlinear power spectrum to sub-percent accuracy on scales larger than about half the Nyquist frequency of the simulation box. Using 20 N-body simulations, we obtain a power spectrum covariance matrix estimate that matches the estimator from Takahashi et al. (from 5000 simulations) with < 20% errors in all matrix elements. Comparing the rates of convergence, we determine that our algorithm requires {approx}8 times fewer simulations to achieve a given error tolerance in estimates of the power spectrum covariance matrix. The degree of success of our algorithm indicates that we understand the main physical processes that give rise to the correlations in the matter power spectrum. Namely, the large-scale Fourier modes modulate both the degree of structure growth through the variation in the effective local matter density and also the spatial frequency of small-scale perturbations through large-scale displacements. We expect our algorithm to be useful for noise modeling when constraining cosmological parameters from weak lensing (cosmic shear) and galaxy surveys, rescaling summary statistics of N-body simulations for new cosmological parameter values, and any applications where the influence of Fourier modes larger than the simulation size must be accounted for.

USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT

Directory of Open Access Journals (Sweden)

Boris Radovanov

2012-12-01

Full Text Available This paper contains a comparison of in-sample and out-of-sample performances between the resampled efficiency technique, patented by Richard Michaud and Robert Michaud (1999, and traditional Mean-Variance portfolio selection, presented by Harry Markowitz (1952. Based on the Monte Carlo simulation, data (samples generation process determines the algorithms by using both, parametric and nonparametric bootstrap techniques. Resampled efficiency provides the solution to use uncertain information without the need for constrains in portfolio optimization. Parametric bootstrap process starts with a parametric model specification, where we apply Capital Asset Pricing Model. After the estimation of specified model, the series of residuals are used for resampling process. On the other hand, nonparametric bootstrap divides series of price returns into the new series of blocks containing previous determined number of consecutive price returns. This procedure enables smooth resampling process and preserves the original structure of data series.

Communication Optimizations for a Wireless Distributed Prognostic Framework

Science.gov (United States)

Saha, Sankalita; Saha, Bhaskar; Goebel, Kai

2009-01-01

Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication overhead is an important design problem for such systems. In this paper we focus on communication issues faced in the distributed implementation of an important class of algorithms for prognostics - particle filters. In spite of being computation and memory intensive, particle filters lend well to distributed implementation except for one significant step - resampling. We propose new resampling scheme called parameterized resampling that attempts to reduce communication between collaborating nodes in a distributed wireless sensor network. Analysis and comparison with relevant resampling schemes is also presented. A battery health management system is used as a target application. A new resampling scheme for distributed implementation of particle filters has been discussed in this paper. Analysis and comparison of this new scheme with existing resampling schemes in the context for minimizing communication overhead have also been discussed. Our proposed new resampling scheme performs significantly better compared to other schemes by attempting to reduce both the communication message length as well as number total communication messages exchanged while not compromising prediction accuracy and precision. Future work will explore the effects of the new resampling scheme in the overall computational performance of the whole system as well as full implementation of the new schemes on the Sun SPOT devices. Exploring different network architectures for efficient communication is an importance future research direction as well.

Estimating cross-validatory predictive p-values with integrated importance sampling for disease mapping models.

Science.gov (United States)

Li, Longhai; Feng, Cindy X; Qiu, Shi

2017-06-30

An important statistical task in disease mapping problems is to identify divergent regions with unusually high or low risk of disease. Leave-one-out cross-validatory (LOOCV) model assessment is the gold standard for estimating predictive p-values that can flag such divergent regions. However, actual LOOCV is time-consuming because one needs to rerun a Markov chain Monte Carlo analysis for each posterior distribution in which an observation is held out as a test case. This paper introduces a new method, called integrated importance sampling (iIS), for estimating LOOCV predictive p-values with only Markov chain samples drawn from the posterior based on a full data set. The key step in iIS is that we integrate away the latent variables associated the test observation with respect to their conditional distribution without reference to the actual observation. By following the general theory for importance sampling, the formula used by iIS can be proved to be equivalent to the LOOCV predictive p-value. We compare iIS and other three existing methods in the literature with two disease mapping datasets. Our empirical results show that the predictive p-values estimated with iIS are almost identical to the predictive p-values estimated with actual LOOCV and outperform those given by the existing three methods, namely, the posterior predictive checking, the ordinary importance sampling, and the ghosting method by Marshall and Spiegelhalter (2003). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Importance sampling and histogrammic representations of reactivity functions and product distributions in Monte Carlo quasiclassical trajectory calculations

International Nuclear Information System (INIS)

Faist, M.B.; Muckerman, J.T.; Schubert, F.E.

1978-01-01

The application of importance sampling as a variance reduction technique in Monte Carlo quasiclassical trajectory calculations is discussed. Two measures are proposed which quantify the quality of the importance sampling used, and indicate whether further improvements may be obtained by some other choice of importance sampling function. A general procedure for constructing standardized histogrammic representations of differential functions which integrate to the appropriate integral value obtained from a trajectory calculation is presented. Two criteria for ''optimum'' binning of these histogrammic representations of differential functions are suggested. These are (1) that each bin makes an equal contribution to the integral value, and (2) each bin has the same relative error. Numerical examples illustrating these sampling and binning concepts are provided

Sampling strategies in antimicrobial resistance monitoring: evaluating how precision and sensitivity vary with the number of animals sampled per farm.

Directory of Open Access Journals (Sweden)

Takehisa Yamamoto

Full Text Available Because antimicrobial resistance in food-producing animals is a major public health concern, many countries have implemented antimicrobial monitoring systems at a national level. When designing a sampling scheme for antimicrobial resistance monitoring, it is necessary to consider both cost effectiveness and statistical plausibility. In this study, we examined how sampling scheme precision and sensitivity can vary with the number of animals sampled from each farm, while keeping the overall sample size constant to avoid additional sampling costs. Five sampling strategies were investigated. These employed 1, 2, 3, 4 or 6 animal samples per farm, with a total of 12 animals sampled in each strategy. A total of 1,500 Escherichia coli isolates from 300 fattening pigs on 30 farms were tested for resistance against 12 antimicrobials. The performance of each sampling strategy was evaluated by bootstrap resampling from the observational data. In the bootstrapping procedure, farms, animals, and isolates were selected randomly with replacement, and a total of 10,000 replications were conducted. For each antimicrobial, we observed that the standard deviation and 2.5-97.5 percentile interval of resistance prevalence were smallest in the sampling strategy that employed 1 animal per farm. The proportion of bootstrap samples that included at least 1 isolate with resistance was also evaluated as an indicator of the sensitivity of the sampling strategy to previously unidentified antimicrobial resistance. The proportion was greatest with 1 sample per farm and decreased with larger samples per farm. We concluded that when the total number of samples is pre-specified, the most precise and sensitive sampling strategy involves collecting 1 sample per farm.

Importance of sampling frequency when collecting diatoms

KAUST Repository

Wu, Naicheng

2016-11-14

There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms’ temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected and analyzed daily riverine diatom samples over a 1-year period (25 April 2013–30 April 2014) at the outlet of a German lowland river. The samples were classified into five clusters (1–5) by a Kohonen Self-Organizing Map (SOM) method based on similarity between species compositions over time. ASFs were determined to be 25 days at Cluster 2 (June-July 2013) and 13 days at Cluster 5 (February-April 2014), whereas no specific ASFs were found at Cluster 1 (April-May 2013), 3 (August-November 2013) (>30 days) and Cluster 4 (December 2013 - January 2014) (<1 day). ASFs showed dramatic seasonality and were negatively related to hydrological wetness conditions, suggesting that sampling interval should be reduced with increasing catchment wetness. A key implication of our findings for freshwater management is that long-term bio-monitoring protocols should be developed with the knowledge of tracking algal temporal dynamics with an appropriate sampling frequency.

Importance of sample preparation for molecular diagnosis of lyme borreliosis from urine.

Science.gov (United States)

Bergmann, A R; Schmidt, B L; Derler, A-M; Aberer, E

2002-12-01

Urine PCR has been used for the diagnosis of Borrelia burgdorferi infection in recent years but has been abandoned because of its low sensitivity and the irreproducibility of the results. Our study aimed to analyze technical details related to sample preparation and detection methods. Crucial for a successful urine PCR were (i) avoidance of the first morning urine sample; (ii) centrifugation at 36,000 x g; and (iii) the extraction method, with only DNAzol of the seven different extraction methods used yielding positive results with patient urine specimens. Furthermore, storage of frozen urine samples at -80 degrees C reduced the sensitivity of a positive urine PCR result obtained with samples from 72 untreated erythema migrans (EM) patients from 85% in the first 3 months to samples was proven by hybridization with a GEN-ETI-K-DEIA kit and for a 10 further positive amplicons by sequencing. By using all of these steps to optimize the urine PCR technique, B. burgdorferi infection could be diagnosed by using urine samples from EM patients with a sensitivity (85%) substantially better than that of serological methods (50%). This improved method could be of future importance as an additional laboratory technique for the diagnosis of unclear, unrecognized borrelia infections and diseases possibly related to Lyme borreliosis.

Brief communication: Is variation in the cranial capacity of the Dmanisi sample too high to be from a single species?

Science.gov (United States)

Lee, Sang-Hee

2005-07-01

This study uses data resampling to test the null hypothesis that the degree of variation in the cranial capacity of the Dmanisi hominid sample is within the range variation of a single species. The statistical significance of the variation in the Dmanisi sample is examined using simulated distributions based on comparative samples of modern humans, chimpanzees, and gorillas. Results show that it is unlikely to find the maximum difference observed in the Dmanisi sample in distributions of female-female pairs from comparative single-species samples. Given that two sexes are represented, the difference in the Dmanisi sample is not enough to reject the null hypothesis of a single species. Results of this study suggest no compelling reason to invoke multiple taxa to explain variation in the cranial capacity of the Dmanisi hominids. (c) 2004 Wiley-Liss, Inc

40 CFR 80.330 - What are the sampling and testing requirements for refiners and importers?

Science.gov (United States)

2010-07-01

... and importers shall collect a representative sample from each batch of gasoline produced or imported... January 1, 2004, any refiner who produces gasoline using computer-controlled in-line blending equipment is... listed in § 80.46(a)(3) to measure the sulfur content of gasoline they produce or import. (2) Except as...

Proposed hardware architectures of particle filter for object tracking

Science.gov (United States)

Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

2012-12-01

In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

Relative contributions of sampling effort, measuring, and weighing to precision of larval sea lamprey biomass estimates

Science.gov (United States)

Slade, Jeffrey W.; Adams, Jean V.; Cuddy, Douglas W.; Neave, Fraser B.; Sullivan, W. Paul; Young, Robert J.; Fodale, Michael F.; Jones, Michael L.

2003-01-01

We developed two weight-length models from 231 populations of larval sea lampreys (Petromyzon marinus) collected from tributaries of the Great Lakes: Lake Ontario (21), Lake Erie (6), Lake Huron (67), Lake Michigan (76), and Lake Superior (61). Both models were mixed models, which used population as a random effect and additional environmental factors as fixed effects. We resampled weights and lengths 1,000 times from data collected in each of 14 other populations not used to develop the models, obtaining a weight and length distribution from reach resampling. To test model performance, we applied the two weight-length models to the resampled length distributions and calculated the predicted mean weights. We also calculated the observed mean weight for each resampling and for each of the original 14 data sets. When the average of predicted means was compared to means from the original data in each stream, inclusion of environmental factors did not consistently improve the performance of the weight-length model. We estimated the variance associated with measures of abundance and mean weight for each of the 14 selected populations and determined that a conservative estimate of the proportional contribution to variance associated with estimating abundance accounted for 32% to 95% of the variance (mean = 66%). Variability in the biomass estimate appears more affected by variability in estimating abundance than in converting length to weight. Hence, efforts to improve the precision of biomass estimates would be aided most by reducing the variability associated with estimating abundance.

Pesticides in Wyoming Groundwater, 2008-10

Science.gov (United States)

Eddy-Miller, Cheryl A.; Bartos, Timothy T.; Taylor, Michelle L.

2013-01-01

Groundwater samples were collected from 296 wells during 1995-2006 as part of a baseline study of pesticides in Wyoming groundwater. In 2009, a previous report summarized the results of the baseline sampling and the statistical evaluation of the occurrence of pesticides in relation to selected natural and anthropogenic (human-related) characteristics. During 2008-10, the U.S. Geological Survey, in cooperation with the Wyoming Department of Agriculture, resampled a subset (52) of the 296 wells sampled during 1995-2006 baseline study in order to compare detected compounds and respective concentrations between the two sampling periods and to evaluate the detections of new compounds. The 52 wells were distributed similarly to sites used in the 1995-2006 baseline study with respect to geographic area and land use within the geographic area of interest. Because of the use of different types of reporting levels and variability in reporting-level values during both the 1995-2006 baseline study and the 2008-10 resampling study, analytical results received from the laboratory were recensored. Two levels of recensoring were used to compare pesticides—a compound-specific assessment level (CSAL) that differed by compound and a common assessment level (CAL) of 0.07 microgram per liter. The recensoring techniques and values used for both studies, with the exception of the pesticide 2,4-D methyl ester, were the same. Twenty-eight different pesticides were detected in samples from the 52 wells during the 2008-10 resampling study. Pesticide concentrations were compared with several U.S. Environmental Protection Agency drinking-water standards or health advisories for finished (treated) water established under the Safe Drinking Water Act. All detected pesticides were measured at concentrations smaller than U.S. Environmental Protection Agency drinking-water standards or health advisories where applicable (many pesticides did not have standards or advisories). One or more pesticides

Subsolutions of an Isaacs Equation and Efficient Schemes for Importance Sampling: Examples and Numerics

National Research Council Canada - National Science Library

Dupuis, Paul; Wang, Hui

2005-01-01

It has been established that importance sampling algorithms for estimating rare-event probabilities are intimately connected with two-person zero-sum differential games and the associated Isaacs equation...

Sparsity-weighted outlier FLOODing (OFLOOD) method: Efficient rare event sampling method using sparsity of distribution.

Science.gov (United States)

Harada, Ryuhei; Nakamura, Tomotake; Shigeta, Yasuteru

2016-03-30

As an extension of the Outlier FLOODing (OFLOOD) method [Harada et al., J. Comput. Chem. 2015, 36, 763], the sparsity of the outliers defined by a hierarchical clustering algorithm, FlexDice, was considered to achieve an efficient conformational search as sparsity-weighted "OFLOOD." In OFLOOD, FlexDice detects areas of sparse distribution as outliers. The outliers are regarded as candidates that have high potential to promote conformational transitions and are employed as initial structures for conformational resampling by restarting molecular dynamics simulations. When detecting outliers, FlexDice defines a rank in the hierarchy for each outlier, which relates to sparsity in the distribution. In this study, we define a lower rank (first ranked), a medium rank (second ranked), and the highest rank (third ranked) outliers, respectively. For instance, the first-ranked outliers are located in a given conformational space away from the clusters (highly sparse distribution), whereas those with the third-ranked outliers are nearby the clusters (a moderately sparse distribution). To achieve the conformational search efficiently, resampling from the outliers with a given rank is performed. As demonstrations, this method was applied to several model systems: Alanine dipeptide, Met-enkephalin, Trp-cage, T4 lysozyme, and glutamine binding protein. In each demonstration, the present method successfully reproduced transitions among metastable states. In particular, the first-ranked OFLOOD highly accelerated the exploration of conformational space by expanding the edges. In contrast, the third-ranked OFLOOD reproduced local transitions among neighboring metastable states intensively. For quantitatively evaluations of sampled snapshots, free energy calculations were performed with a combination of umbrella samplings, providing rigorous landscapes of the biomolecules. © 2015 Wiley Periodicals, Inc.

Submersible UV-Vis spectroscopy for quantifying streamwater organic carbon dynamics: implementation and challenges before and after forest harvest in a headwater stream.

Science.gov (United States)

Jollymore, Ashlee; Johnson, Mark S; Hawthorne, Iain

2012-01-01

Organic material, including total and dissolved organic carbon (DOC), is ubiquitous within aquatic ecosystems, playing a variety of important and diverse biogeochemical and ecological roles. Determining how land-use changes affect DOC concentrations and bioavailability within aquatic ecosystems is an important means of evaluating the effects on ecological productivity and biogeochemical cycling. This paper presents a methodology case study looking at the deployment of a submersible UV-Vis absorbance spectrophotometer (UV-Vis spectro::lyzer model, s::can, Vienna, Austria) to determine stream organic carbon dynamics within a headwater catchment located near Campbell River (British Columbia, Canada). Field-based absorbance measurements of DOC were made before and after forest harvest, highlighting the advantages of high temporal resolution compared to traditional grab sampling and laboratory measurements. Details of remote deployment are described. High-frequency DOC data is explored by resampling the 30 min time series with a range of resampling time intervals (from daily to weekly time steps). DOC export was calculated for three months from the post-harvest data and resampled time series, showing that sampling frequency has a profound effect on total DOC export. DOC exports derived from weekly measurements were found to underestimate export by as much as 30% compared to DOC export calculated from high-frequency data. Additionally, the importance of the ability to remotely monitor the system through a recently deployed wireless connection is emphasized by examining causes of prior data losses, and how such losses may be prevented through the ability to react when environmental or power disturbances cause system interruption and data loss.

Submersible UV-Vis Spectroscopy for Quantifying Streamwater Organic Carbon Dynamics: Implementation and Challenges before and after Forest Harvest in a Headwater Stream

Directory of Open Access Journals (Sweden)

Iain Hawthorne

2012-03-01

Full Text Available Organic material, including total and dissolved organic carbon (DOC, is ubiquitous within aquatic ecosystems, playing a variety of important and diverse biogeochemical and ecological roles. Determining how land-use changes affect DOC concentrations and bioavailability within aquatic ecosystems is an important means of evaluating the effects on ecological productivity and biogeochemical cycling. This paper presents a methodology case study looking at the deployment of a submersible UV-Vis absorbance spectrophotometer (UV-Vis spectro::lyzer model, s::can, Vienna, Austria to determine stream organic carbon dynamics within a headwater catchment located near Campbell River (British Columbia, Canada. Field-based absorbance measurements of DOC were made before and after forest harvest, highlighting the advantages of high temporal resolution compared to traditional grab sampling and laboratory measurements. Details of remote deployment are described. High-frequency DOC data is explored by resampling the 30 min time series with a range of resampling time intervals (from daily to weekly time steps. DOC export was calculated for three months from the post-harvest data and resampled time series, showing that sampling frequency has a profound effect on total DOC export. DOC exports derived from weekly measurements were found to underestimate export by as much as 30% compared to DOC export calculated from high-frequency data. Additionally, the importance of the ability to remotely monitor the system through a recently deployed wireless connection is emphasized by examining causes of prior data losses, and how such losses may be prevented through the ability to react when environmental or power disturbances cause system interruption and data loss.

Some advances in importance sampling of reliability models based on zero variance approximation

NARCIS (Netherlands)

Reijsbergen, D.P.; de Boer, Pieter-Tjerk; Scheinhardt, Willem R.W.; Juneja, Sandeep

We are interested in estimating, through simulation, the probability of entering a rare failure state before a regeneration state. Since this probability is typically small, we apply importance sampling. The method that we use is based on finding the most likely paths to failure. We present an

Importance sampling of rare events in chaotic systems

DEFF Research Database (Denmark)

Leitão, Jorge C.; Parente Lopes, João M.Viana; Altmann, Eduardo G.

2017-01-01

space of chaotic systems. As examples of our general framework we compute the distribution of finite-time Lyapunov exponents (in different chaotic maps) and the distribution of escape times (in transient-chaos problems). Our methods sample exponentially rare states in polynomial number of samples (in......Finding and sampling rare trajectories in dynamical systems is a difficult computational task underlying numerous problems and applications. In this paper we show how to construct Metropolis-Hastings Monte-Carlo methods that can efficiently sample rare trajectories in the (extremely rough) phase...... both low- and high-dimensional systems). An open-source software that implements our algorithms and reproduces our results can be found in reference [J. Leitao, A library to sample chaotic systems, 2017, https://github.com/jorgecarleitao/chaospp]....

Sworn testimony of the model evidence: Gaussian Mixture Importance (GAME) sampling

Science.gov (United States)

Volpi, Elena; Schoups, Gerrit; Firmani, Giovanni; Vrugt, Jasper A.

2017-07-01

What is the "best" model? The answer to this question lies in part in the eyes of the beholder, nevertheless a good model must blend rigorous theory with redeeming qualities such as parsimony and quality of fit. Model selection is used to make inferences, via weighted averaging, from a set of K candidate models, Mk; k=>(1,…,K>), and help identify which model is most supported by the observed data, Y>˜=>(y˜1,…,y˜n>). Here, we introduce a new and robust estimator of the model evidence, p>(Y>˜|Mk>), which acts as normalizing constant in the denominator of Bayes' theorem and provides a single quantitative measure of relative support for each hypothesis that integrates model accuracy, uncertainty, and complexity. However, p>(Y>˜|Mk>) is analytically intractable for most practical modeling problems. Our method, coined GAussian Mixture importancE (GAME) sampling, uses bridge sampling of a mixture distribution fitted to samples of the posterior model parameter distribution derived from MCMC simulation. We benchmark the accuracy and reliability of GAME sampling by application to a diverse set of multivariate target distributions (up to 100 dimensions) with known values of p>(Y>˜|Mk>) and to hypothesis testing using numerical modeling of the rainfall-runoff transformation of the Leaf River watershed in Mississippi, USA. These case studies demonstrate that GAME sampling provides robust and unbiased estimates of the evidence at a relatively small computational cost outperforming commonly used estimators. The GAME sampler is implemented in the MATLAB package of DREAM and simplifies considerably scientific inquiry through hypothesis testing and model selection.

Monte Carlo importance sampling for the MCNP trademark general source

International Nuclear Information System (INIS)

Lichtenstein, H.

1996-01-01

Research was performed to develop an importance sampling procedure for a radiation source. The procedure was developed for the MCNP radiation transport code, but the approach itself is general and can be adapted to other Monte Carlo codes. The procedure, as adapted to MCNP, relies entirely on existing MCNP capabilities. It has been tested for very complex descriptions of a general source, in the context of the design of spent-reactor-fuel storage casks. Dramatic improvements in calculation efficiency have been observed in some test cases. In addition, the procedure has been found to provide an acceleration to acceptable convergence, as well as the benefit of quickly identifying user specified variance-reduction in the transport that effects unstable convergence

Soil classification basing on the spectral characteristics of topsoil samples

Science.gov (United States)

Liu, Huanjun; Zhang, Xiaokang; Zhang, Xinle

2016-04-01

Soil taxonomy plays an important role in soil utility and management, but China has only course soil map created based on 1980s data. New technology, e.g. spectroscopy, could simplify soil classification. The study try to classify soils basing on the spectral characteristics of topsoil samples. 148 topsoil samples of typical soils, including Black soil, Chernozem, Blown soil and Meadow soil, were collected from Songnen plain, Northeast China, and the room spectral reflectance in the visible and near infrared region (400-2500 nm) were processed with weighted moving average, resampling technique, and continuum removal. Spectral indices were extracted from soil spectral characteristics, including the second absorption positions of spectral curve, the first absorption vale's area, and slope of spectral curve at 500-600 nm and 1340-1360 nm. Then K-means clustering and decision tree were used respectively to build soil classification model. The results indicated that 1) the second absorption positions of Black soil and Chernozem were located at 610 nm and 650 nm respectively; 2) the spectral curve of the meadow is similar to its adjacent soil, which could be due to soil erosion; 3) decision tree model showed higher classification accuracy, and accuracy of Black soil, Chernozem, Blown soil and Meadow are 100%, 88%, 97%, 50% respectively, and the accuracy of Blown soil could be increased to 100% by adding one more spectral index (the first two vole's area) to the model, which showed that the model could be used for soil classification and soil map in near future.

Calculation of parameter failure probability of thermodynamic system by response surface and importance sampling method

International Nuclear Information System (INIS)

Shang Yanlong; Cai Qi; Chen Lisheng; Zhang Yangwei

2012-01-01

In this paper, the combined method of response surface and importance sampling was applied for calculation of parameter failure probability of the thermodynamic system. The mathematics model was present for the parameter failure of physics process in the thermodynamic system, by which the combination arithmetic model of response surface and importance sampling was established, then the performance degradation model of the components and the simulation process of parameter failure in the physics process of thermodynamic system were also present. The parameter failure probability of the purification water system in nuclear reactor was obtained by the combination method. The results show that the combination method is an effective method for the calculation of the parameter failure probability of the thermodynamic system with high dimensionality and non-linear characteristics, because of the satisfactory precision with less computing time than the direct sampling method and the drawbacks of response surface method. (authors)

Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

Science.gov (United States)

Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

2014-01-01

There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

Limited sampling hampers "big data" estimation of species richness in a tropical biodiversity hotspot.

Science.gov (United States)

Engemann, Kristine; Enquist, Brian J; Sandel, Brody; Boyle, Brad; Jørgensen, Peter M; Morueta-Holme, Naia; Peet, Robert K; Violle, Cyrille; Svenning, Jens-Christian

2015-02-01

Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with "big data" collections.

Catching Stardust and Bringing it Home: The Astronomical Importance of Sample Return

Science.gov (United States)

Brownlee, D.

2002-12-01

orbit of Mars will provide important insight into the materials, environments and processes that occurred from the central regions to outer fringes of the solar nebula. One of the most exciting aspects of the January 2006 return of comet samples will be the synergistic linking of data on real comet and interstellar dust samples with the vast amount of astronomical data on these materials and analogous particles that orbit other stars Stardust is a NASA Discovery mission that has successfully traveled over 2.5 billion kilometers.

Application of importance sampling method in sliding failure simulation of caisson breakwaters

Science.gov (United States)

Wang, Yu-chi; Wang, Yuan-zhan; Li, Qing-mei; Chen, Liang-zhi

2016-06-01

It is assumed that the storm wave takes place once a year during the design period, and N histories of storm waves are generated on the basis of wave spectrum corresponding to the N-year design period. The responses of the breakwater to the N histories of storm waves in the N-year design period are calculated by mass-spring-dashpot mode and taken as a set of samples. The failure probability of caisson breakwaters during the design period of N years is obtained by the statistical analysis of many sets of samples. It is the key issue to improve the efficiency of the common Monte Carlo simulation method in the failure probability estimation of caisson breakwaters in the complete life cycle. In this paper, the kernel method of importance sampling, which can greatly increase the efficiency of failure probability calculation of caisson breakwaters, is proposed to estimate the failure probability of caisson breakwaters in the complete life cycle. The effectiveness of the kernel method is investigated by an example. It is indicated that the calculation efficiency of the kernel method is over 10 times the common Monte Carlo simulation method.

Binomial and enumerative sampling of Tetranychus urticae (Acari: Tetranychidae) on peppermint in California.

Science.gov (United States)

Tollerup, Kris E; Marcum, Daniel; Wilson, Rob; Godfrey, Larry

2013-08-01

The two-spotted spider mite, Tetranychus urticae Koch, is an economic pest on peppermint [Mentha x piperita (L.), 'Black Mitcham'] grown in California. A sampling plan for T. urticae was developed under Pacific Northwest conditions in the early 1980s and has been used by California growers since approximately 1998. This sampling plan, however, is cumbersome and a poor predictor of T. urticae densities in California. Between June and August, the numbers of immature and adult T. urticae were counted on leaves at three commercial peppermint fields (sites) in 2010 and a single field in 2011. In each of seven locations per site, 45 leaves were sampled, that is, 9 leaves per five stems. Leaf samples were stratified by collecting three leaves from the top, middle, and bottom strata per stem. The on-plant distribution of T. urticae did not significantly differ among the stem strata through the growing season. Binomial and enumerative sampling plans were developed using generic Taylor's power law coefficient values. The best fit of our data for binomial sampling occurred using a tally threshold of T = 0. The optimum number of leaves required for T urticae at the critical density of five mites per leaf was 20 for the binomial and 23 for the enumerative sampling plans, respectively. Sampling models were validated using Resampling for Validation of Sampling Plan Software.

Bounded Memory, Inertia, Sampling and Weighting Model for Market Entry Games

Directory of Open Access Journals (Sweden)

Yi-Shan Lee

2011-03-01

Full Text Available This paper describes the “Bounded Memory, Inertia, Sampling and Weighting” (BI-SAW model, which won the http://sites.google.com/site/gpredcomp/Market Entry Prediction Competition in 2010. The BI-SAW model refines the I-SAW Model (Erev et al. [1] by adding the assumption of limited memory span. In particular, we assume when players draw a small sample to weight against the average payoff of all past experience, they can only recall 6 trials of past experience. On the other hand, we keep all other key features of the I-SAW model: (1 Reliance on a small sample of past experiences, (2 Strong inertia and recency effects, and (3 Surprise triggers change. We estimate this model using the first set of experimental results run by the competition organizers, and use it to predict results of a second set of similar experiments later ran by the organizers. We find significant improvement in out-of-sample predictability (against the I-SAW model in terms of smaller mean normalized MSD, and such result is robust to resampling the predicted game set and reversing the role of the sets of experimental results. Our model’s performance is the best among all the participants.

Tamaños de muestra para estimar la estructura de tallas de las capturas de langostino colorado en la zona centro-norte de Chile: una aproximación a través de remuestreo Sample sizes for estimating the catch size distribution of squat lobster in north-central Chile: a resampling approach

Directory of Open Access Journals (Sweden)

Carlos Montenegro Silva

2009-01-01

Full Text Available Se analizó el desempeño de distintos tamaños de muestra para estimar la composición de tallas de las capturas del langostino colorado (Pleuroncodes monodon, a partir de un procedimiento de remuestreo computacional. Se seleccionaron datos recolectados en mayo de 2002 entre los 29°10'S y 32°10'S. A partir de éstos, se probaron siete escenarios de muestreo de viajes de pesca (1-7 viajes, 12 escenarios de número de ejemplares muestreados (25, 50,...300, cada 25 ejemplares y dos estrategias de muestreo de lances de pesca al interior de un viaje de pesca (censo de lances y muestreo sistemático. Se probó la combinación de todos estos escenarios, lo que permitió analizar el desempeño de 168 escenarios de tamaño de muestra para estimar la composición de tallas por sexo. Los resultados indicaron una disminución en el índice de error en la estimación de la distribución de frecuencia de tallas, conforme aumentó el número de viajes de pesca, con disminuciones progresivamente menores entre escenarios adyacentes. Del mismo modo, se verificó una disminución en el índice de error al aumentar el número de ejemplares muestreados, con mejoras marginales sobre los 175 ejemplares.The performances of different sample sizes for estimating the size distribution of squat lobster (Pleuroncodes monodon catches were analyzed using a computer resampling procedure. The data selected were gathered in May 2002 between 29°10'S and 32°10'S. These data were used to test seven sampling scenarios for fishing trips (1-7 trips, twelve scenarios of the number of individuals sampled per tow (25, 50,..., 300, and two within-trip sampling strategies (sampling all tows and systematic tow sampling. By testing the combination of all these scenarios, we were able to analyze the performance of 168 scenarios of sample size for estimating the composition of sizes by sex. The results indicate a lower error index for estimates of the size frequency distribution as the

Simple and efficient importance sampling scheme for a tandem queue with server slow-down

NARCIS (Netherlands)

Miretskiy, D.I.; Scheinhardt, W.R.W.; Mandjes, M.R.H.

2008-01-01

This paper considers importance sampling as a tool for rare-event simulation. The system at hand is a so-called tandem queue with slow-down, which essentially means that the server of the first queue (or: upstream queue) switches to a lower speed when the second queue (downstream queue) exceeds some

Importance of sampling frequency when collecting diatoms

KAUST Repository

Wu, Naicheng; Faber, Claas; Sun, Xiuming; Qu, Yueming; Wang, Chao; Ivetic, Snjezana; Riis, Tenna; Ulrich, Uta; Fohrer, Nicola

2016-01-01

There has been increasing interest in diatom-based bio-assessment but we still lack a comprehensive understanding of how to capture diatoms’ temporal dynamics with an appropriate sampling frequency (ASF). To cover this research gap, we collected

Sample sufficiency of chinese pink grown in different substrates

Directory of Open Access Journals (Sweden)

Sidinei José lopes

2016-04-01

Full Text Available The cravina is an excellent plant to build up gardens due to its early flowering, abundant flowering and great performance in spring and autumn. The objective was to estimate the sample size for plant chinese pink, grown on different substrates, and check the variability of the sample size between growth parameters and production and substrates. They used seven treatments (substrates: S1 = 50% soil + 50% rice husk ash; S2 = 80% soil + 20% earthworm castings; S3 = 80% rice husk ash + 20% earthworm castings; S4 = 40% soil + 40% rice husk ash + 20% earthworm castings; S5 = 100% peat; S6 = 100% commercial substrate Mecplant®; S7 = 50% peat + 50% rice husk ash, with 56 repetitions each, totaling 392 plants of garden pink, which was evaluated in 17 of growth and production parameters. The methodology used to bootstrap resampling, with replacement, for each character within each substrate with predetermined error: 5, 10, 20 and 40% of the average (D%. To a 95% confidence interval, with D = 20%, the substrate 50% soil and 50% of rice husk ash had the largest sample size 11 characters; when comparing the characters , the number of flower buds had the highest sample size on average 113 plants. Using samples of 44 plant chinese pink for commercial substrate Mecplant® meet the lower precisions or equal to 20% for all variables. There is variation in sample size in relation to the substrate used and the variable evaluated in chinese pink plants.

Bayesian estimation of Weibull distribution parameters

International Nuclear Information System (INIS)

Bacha, M.; Celeux, G.; Idee, E.; Lannoy, A.; Vasseur, D.

1994-11-01

In this paper, we expose SEM (Stochastic Expectation Maximization) and WLB-SIR (Weighted Likelihood Bootstrap - Sampling Importance Re-sampling) methods which are used to estimate Weibull distribution parameters when data are very censored. The second method is based on Bayesian inference and allow to take into account available prior informations on parameters. An application of this method, with real data provided by nuclear power plants operation feedback analysis has been realized. (authors). 8 refs., 2 figs., 2 tabs

The importance of sound methodology in environmental DNA sampling

Science.gov (United States)

T. M. Wilcox; K. J. Carim; M. K. Young; K. S. McKelvey; T. W. Franklin; M. K. Schwartz

2018-01-01

Environmental DNA (eDNA) sampling - which enables inferences of species’ presence from genetic material in the environment - is a powerful tool for sampling rare fishes. Numerous studies have demonstrated that eDNA sampling generally provides greater probabilities of detection than traditional techniques (e.g., Thomsen et al. 2012; McKelvey et al. 2016; Valentini et al...

Sampling and Analysis for Assessment of Body Burdens

International Nuclear Information System (INIS)

Harley, J.H.

1964-01-01

A review of sampling criteria and techniques and of sample processing methods for indirect assessment of body burdens is presented. The text is limited to the more recent developments in the field of bioassay and to the nuclides which cannot be readily determined in the body directly. A selected bibliography is included. The planning of a bioassay programme should emphasize the detection of high or unusual exposures and the concentrated study of these cases when detected. This procedure gives the maximum amount of data for the dosimetry of individuals at risk and also adds to our scientific background for an understanding of internal emitters. Only a minimum of effort should be spent on sampling individuals having had negligible exposure. The chemical separation procedures required for bioassay also fall into two categories. The first is the rapid method, possibly of low accuracy, used for detection. The second is the more accurate method required for study of the individual after detection of the exposure. Excretion, whether exponential or a power function, drops off rapidly. It is necessary to locate the exposure in time before any evaluation can be made, even before deciding if the exposure is significant. One approach is frequent sampling and analysis by a quick screening technique. More commonly, samples are collected at longer intervals and an arbitrary level of re-sampling is set to assist in the detection of real exposures. It is probable that too much bioassay effort has gone into measurements on individuals at low risk and not enough on those at higher risk. The development of bioassay procedures for overcoming this problem has begun, and this paper emphasizes this facet of sampling and sample processing. (author) [fr

Burnout and Engagement: Relative Importance of Predictors and Outcomes in Two Health Care Worker Samples.

Science.gov (United States)

Fragoso, Zachary L; Holcombe, Kyla J; McCluney, Courtney L; Fisher, Gwenith G; McGonagle, Alyssa K; Friebe, Susan J

2016-06-09

This study's purpose was twofold: first, to examine the relative importance of job demands and resources as predictors of burnout and engagement, and second, the relative importance of engagement and burnout related to health, depressive symptoms, work ability, organizational commitment, and turnover intentions in two samples of health care workers. Nurse leaders (n = 162) and licensed emergency medical technicians (EMTs; n = 102) completed surveys. In both samples, job demands predicted burnout more strongly than job resources, and job resources predicted engagement more strongly than job demands. Engagement held more weight than burnout for predicting commitment, and burnout held more weight for predicting health outcomes, depressive symptoms, and work ability. Results have implications for the design, evaluation, and effectiveness of workplace interventions to reduce burnout and improve engagement among health care workers. Actionable recommendations for increasing engagement and decreasing burnout in health care organizations are provided. © 2016 The Author(s).

Soil map disaggregation improved by soil-landscape relationships, area-proportional sampling and random forest implementation

DEFF Research Database (Denmark)

Møller, Anders Bjørn; Malone, Brendan P.; Odgers, Nathan

implementation generally improved the algorithm’s ability to predict the correct soil class. The implementation of soil-landscape relationships and area-proportional sampling generally increased the calculation time, while the random forest implementation reduced the calculation time. In the most successful......Detailed soil information is often needed to support agricultural practices, environmental protection and policy decisions. Several digital approaches can be used to map soil properties based on field observations. When soil observations are sparse or missing, an alternative approach...... is to disaggregate existing conventional soil maps. At present, the DSMART algorithm represents the most sophisticated approach for disaggregating conventional soil maps (Odgers et al., 2014). The algorithm relies on classification trees trained from resampled points, which are assigned classes according...

40 CFR 80.583 - What alternative sampling and testing requirements apply to importers who transport motor vehicle...

Science.gov (United States)

2010-07-01

... requirements apply to importers who transport motor vehicle diesel fuel, NRLM diesel fuel, or ECA marine fuel... (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Motor Vehicle Diesel Fuel... alternative sampling and testing requirements apply to importers who transport motor vehicle diesel fuel, NRLM...

Design and implementation of new design of numerical experiments for non linear models; Conception et mise en oeuvre de nouvelles methodes d'elaboration de plans d'experiences pour l'apprentissage de modeles non lineaires

Energy Technology Data Exchange (ETDEWEB)

Gazut, St

2007-03-15

This thesis addresses the problem of the construction of surrogate models in numerical simulation. Whenever numerical experiments are costly, the simulation model is complex and difficult to use. It is important then to select the numerical experiments as efficiently as possible in order to minimize their number. In statistics, the selection of experiments is known as optimal experimental design. In the context of numerical simulation where no measurement uncertainty is present, we describe an alternative approach based on statistical learning theory and re-sampling techniques. The surrogate models are constructed using neural networks and the generalization error is estimated by leave-one-out, cross-validation and bootstrap. It is shown that the bootstrap can control the over-fitting and extend the concept of leverage for non linear in their parameters surrogate models. The thesis describes an iterative method called LDR for Learner Disagreement from experiment Re-sampling, based on active learning using several surrogate models constructed on bootstrap samples. The method consists in adding new experiments where the predictors constructed from bootstrap samples disagree most. We compare the LDR method with other methods of experimental design such as D-optimal selection. (author)

Design and implementation of new design of numerical experiments for non linear models

International Nuclear Information System (INIS)

Gazut, St.

2007-03-01

This thesis addresses the problem of the construction of surrogate models in numerical simulation. Whenever numerical experiments are costly, the simulation model is complex and difficult to use. It is important then to select the numerical experiments as efficiently as possible in order to minimize their number. In statistics, the selection of experiments is known as optimal experimental design. In the context of numerical simulation where no measurement uncertainty is present, we describe an alternative approach based on statistical learning theory and re-sampling techniques. The surrogate models are constructed using neural networks and the generalization error is estimated by leave-one-out, cross-validation and bootstrap. It is shown that the bootstrap can control the over-fitting and extend the concept of leverage for non linear in their parameters surrogate models. The thesis describes an iterative method called LDR for Learner Disagreement from experiment Re-sampling, based on active learning using several surrogate models constructed on bootstrap samples. The method consists in adding new experiments where the predictors constructed from bootstrap samples disagree most. We compare the LDR method with other methods of experimental design such as D-optimal selection. (author)

Collateral Information for Equating in Small Samples: A Preliminary Investigation

Science.gov (United States)

Kim, Sooyeon; Livingston, Samuel A.; Lewis, Charles

2011-01-01

This article describes a preliminary investigation of an empirical Bayes (EB) procedure for using collateral information to improve equating of scores on test forms taken by small numbers of examinees. Resampling studies were done on two different forms of the same test. In each study, EB and non-EB versions of two equating methods--chained linear…

Importance Sampling for a Markov Modulated Queuing Network with Customer Impatience until the End of Service

Directory of Open Access Journals (Sweden)

Ebrahim MAHDIPOUR

2009-01-01

Full Text Available For more than two decades, there has been a growing of interest in fast simulation techniques for estimating probabilities of rare events in queuing networks. Importance sampling is a variance reduction method for simulating rare events. The present paper carries out strict deadlines to the paper by Dupuis et al for a two node tandem network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We derive a closed form solution for the probability of missing deadlines. Then we have employed the results to an importance sampling technique to estimate the probability of total population overflow which is a rare event. We have also shown that the probability of this rare event may be affected by various deadline values.

Air-to-Air Missile Vector Scoring

Science.gov (United States)

2012-03-22

SIR sampling-importance resampling . . . . . . . . . . . . . . 53 EPF extended particle filter . . . . . . . . . . . . . . . . . . . . 54 UPF unscented...particle filter ( EPF ) or a unscented particle fil- ter (UPF) [20]. The basic concept is to apply a bank of N EKF or UKF filters to move particles from...Merwe, Doucet, Freitas and Wan provide a comprehensive discussion on the EPF and UPF, including algorithms for implementation [20]. 2Result based on

Specific determination of clinical and toxicological important substances in biological samples by LC-MS

International Nuclear Information System (INIS)

Mitulovic, G.

2001-02-01

This thesis of this dissertation is the specific determination of clinical and toxicological important substances in biological samples by LC-MS. Nicotine was determined in serum after application of nicotine plaster and nicotine nasal spray with HPLC-ESI-MS. Cotinine was determined direct in urine with HPLC-ESI-MS. Short time anesthetics were determined in blood and cytostatics were determined in liquor with HPLC-ESI-MS. (botek)

Methods of soil resampling to monitor changes in the chemical concentrations of forest soils

Science.gov (United States)

Gregory B. Lawrence; Ivan J. Fernandez; Paul W. Hazlett; Scott W. Bailey; Donald S. Ross; Thomas R. Villars; Angelica Quintana; Rock Ouimet; Michael R. McHale; Chris E. Johnson; Russell D. Briggs; Robert A. Colter; Jason Siemion; Olivia L. Bartlett; Olga Vargas; Michael R. Antidormi; Mary M. Koppers

2016-01-01

Recent soils research has shown that important chemical soil characteristics can change in less than a decade, often the result of broad environmental changes. Repeated sampling to monitor these changes in forest soils is a relatively new practice that is not well documented in the literature and has only recently been broadly embraced by the scientific community. The...

Quality of omeprazole purchased via the Internet and personally imported into Japan: comparison with products sampled in other Asian countries.

Science.gov (United States)

Rahman, Mohammad Sofiqur; Yoshida, Naoko; Sugiura, Sakura; Tsuboi, Hirohito; Keila, Tep; Kiet, Heng Bun; Zin, Theingi; Tanimoto, Tsuyoshi; Kimura, Kazuko

2018-03-01

To evaluate the quality of omeprazole personally imported into Japan via the Internet and to compare the quality of these samples with previously collected samples from two other Asian countries. The samples were evaluated by observation, authenticity investigation and pharmacopoeial quality analysis. Quality comparison of some selected samples was carried out by dissolution profiling, Raman spectroscopy and principle component analysis (PCA). Observation of the Internet sites and samples revealed some discrepancies including the delivery of a wrong sample and the selling of omeprazole without a prescription, although it is a prescription medicine. Among the 28 samples analysed, all passed the identification test, 26 (93%) passed the quantity and content uniformity tests and all passed the dissolution test. Dissolution profiling confirmed that all the personally imported omeprazole samples remained intact in the acid medium. On the other hand, six samples from two of the same manufacturers, previously collected during surveys in Cambodia and Myanmar, frequently showed premature omeprazole release in acid. Raman spectroscopy and PCA showed significant variation between omeprazole formulations in personally imported samples and the samples from Cambodia and Myanmar. Our results indicate that the pharmaceutical quality of omeprazole purchased through the Internet was sufficient, as determined by pharmacopeial tests. However, omeprazole formulations distributed in different market segments by the same manufacturers were of diverse quality. Measures are needed to ensure consistent quality of products and to prevent entry of substandard products into the legitimate supply chain. © 2018 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.

Improved metamodel-based importance sampling for the performance assessment of radioactive waste repositories

International Nuclear Information System (INIS)

Cadini, F.; Gioletta, A.; Zio, E.

2015-01-01

In the context of a probabilistic performance assessment of a radioactive waste repository, the estimation of the probability of exceeding the dose threshold set by a regulatory body is a fundamental task. This may become difficult when the probabilities involved are very small, since the classically used sampling-based Monte Carlo methods may become computationally impractical. This issue is further complicated by the fact that the computer codes typically adopted in this context requires large computational efforts, both in terms of time and memory. This work proposes an original use of a Monte Carlo-based algorithm for (small) failure probability estimation in the context of the performance assessment of a near surface radioactive waste repository. The algorithm, developed within the context of structural reliability, makes use of an estimated optimal importance density and a surrogate, kriging-based metamodel approximating the system response. On the basis of an accurate analytic analysis of the algorithm, a modification is proposed which allows further reducing the computational efforts by a more effective training of the metamodel. - Highlights: • We tackle uncertainty propagation in a radwaste repository performance assessment. • We improve a kriging-based importance sampling for estimating failure probabilities. • We justify the modification by an analytic, comparative analysis of the algorithms. • The probability of exceeding dose thresholds in radwaste repositories is estimated. • The algorithm is further improved reducing the number of its free parameters

Gap-Filling of Landsat 7 Imagery Using the Direct Sampling Method

KAUST Repository

Yin, Gaohong

2016-12-28

The failure of the Scan Line Corrector (SLC) on Landsat 7 imposed systematic data gaps on retrieved imagery and removed the capacity to provide spatially continuous fields. While a number of methods have been developed to fill these gaps, most of the proposed techniques are only applicable over relatively homogeneous areas. When they are applied to heterogeneous landscapes, retrieving image features and elements can become challenging. Here we present a gap-filling approach that is based on the adoption of the Direct Sampling multiple-point geostatistical method. The method employs a conditional stochastic resampling of known areas in a training image to simulate unknown locations. The approach is assessed across a range of both homogeneous and heterogeneous regions. Simulation results show that for homogeneous areas, satisfactory results can be obtained by simply adopting non-gap locations in the target image as baseline training data. For heterogeneous landscapes, bivariate simulations using an auxiliary variable acquired at a different date provides more accurate results than univariate simulations, especially as land cover complexity increases. Apart from recovering spatially continuous fields, one of the key advantages of the Direct Sampling is the relatively straightforward implementation process that relies on relatively few parameters.

Changes in tundra pond limnology: re-sampling Alaskan ponds after 40 years.

Science.gov (United States)

Lougheed, Vanessa L; Butler, Malcolm G; McEwen, Daniel C; Hobbie, John E

2011-09-01

The arctic tundra ponds at the International Biological Program (IBP) site in Barrow, AK, were studied extensively in the 1970s; however, very little aquatic research has been conducted there for over three decades. Due to the rapid climate changes already occurring in northern Alaska, identifying any changes in the ponds' structure and function over the past 30-40 years can help identify any potential climate-related impacts. Current research on the IBP ponds has revealed significant changes in the physical, chemical, and biological characteristics of these ponds over time. These changes include increased water temperatures, increased water column nutrient concentrations, the presence of at least one new chironomid species, and increased macrophyte cover. However, we have also observed significant annual variation in many measured variables and caution that this variation must be taken into account when attempting to make statements about longer-term change. The Barrow IBP tundra ponds represent one of the very few locations in the Arctic where long-term data are available on freshwater ecosystem structure and function. Continued monitoring and protection of these invaluable sites is required to help understand the implications of climate change on freshwater ecosystems in the Arctic.

An antithetic variate to facilitate upper-stem height measurements for critical height sampling with importance sampling

Science.gov (United States)

Thomas B. Lynch; Jeffrey H. Gove

2013-01-01

Critical height sampling (CHS) estimates cubic volume per unit area by multiplying the sum of critical heights measured on trees tallied in a horizontal point sample (HPS) by the HPS basal area factor. One of the barriers to practical application of CHS is the fact that trees near the field location of the point-sampling sample point have critical heights that occur...

Avoiding misdiagnosis of imported malaria: screening of emergency department samples with thrombocytopenia detects clinically unsuspected cases

NARCIS (Netherlands)

Hänscheid, Thomas; Melo-Cristino, José; Grobusch, Martin P.; Pinto, Bernardino G.

2003-01-01

BACKGROUND: Misdiagnosis of imported malaria is not uncommon and even abnormal routine laboratory tests may not trigger malaria smears. However, blind screening of all thrombocytopenic samples might be a possible way to detect clinically unsuspected malaria cases in the accident and emergency

Phase 1 sampling and analysis plan for the 304 Concretion Facility closure activities

International Nuclear Information System (INIS)

Adler, J.G.

1994-01-01

This document provides guidance for the initial (Phase 1) sampling and analysis activities associated with the proposed Resource Conservation and Recovery Act of 1976 (RCRA) clean closure of the 304 Concretion Facility. Over its service life, the 304 Concretion Facility housed the pilot plants associated with cladding uranium cores, was used to store engineering equipment and product chemicals, was used to treat low-level radioactive mixed waste, recyclable scrap uranium generated during nuclear fuel fabrication, and uranium-titanium alloy chips, and was used for the repackaging of spent halogenated solvents from the nuclear fuels manufacturing process. The strategy for clean closure of the 304 Concretion Facility is to decontaminate, sample (Phase 1 sampling), and evaluate results. If the evaluation indicates that a limited area requires additional decontamination for clean closure, the limited area will be decontaminated, resampled (Phase 2 sampling), and the result evaluated. If the evaluation indicates that the constituents of concern are below action levels, the facility will be clean closed. Or, if the evaluation indicates that the constituents of concern are present above action levels, the condition of the facility will be evaluated and appropriate action taken. There are a total of 37 sampling locations comprising 12 concrete core, 1 concrete chip, 9 soil, 11 wipe, and 4 asphalt core sampling locations. Analysis for inorganics and volatile organics will be performed on the concrete core and soil samples. Separate concrete core samples will be required for the inorganic and volatile organic analysis (VOA). Analysis for inorganics only will be performed on the concrete chip, wipe, and asphalt samples

76 FR 65165 - Importation of Plants for Planting; Risk-Based Sampling and Inspection Approach and Propagative...

Science.gov (United States)

2011-10-20

..., this 14th day of October 2011. Kevin Shea, Acting Administrator, Animal and Plant Health Inspection... DEPARTMENT OF AGRICULTURE Animal and Plant Health Inspection Service [Docket No. APHIS-2011-0092] Importation of Plants for Planting; Risk-Based Sampling and Inspection Approach and Propagative Monitoring and...

Important aspects of residue sampling in drilling dikes; Aspectos importantes para a amostragem de residuos em diques de perfuracao

Energy Technology Data Exchange (ETDEWEB)

Silva, Gilvan Ferreira da [PETROBRAS, Rio de Janeiro (Brazil). Centro de Pesquisas. Div. de Explotacao

1990-12-31

This paper describes the importance of sampling in the evaluation of physical and chemical properties of residues found in drilling dikes, considering the later selection of treatment methods or discard of these residues. We present the fundamental concepts of applied statistics, which are essential to the elaboration of sampling plans, with views of obtaining exact and precise results. Other types of samples are also presented, as well as sampling equipment and methods for storage and preservation of the samples. As a conclusion, we the example of the implementation of a sampling plan. (author) 3 refs., 9 figs., 3 tabs.

Important aspects of residue sampling in drilling dikes; Aspectos importantes para a amostragem de residuos em diques de perfuracao

Energy Technology Data Exchange (ETDEWEB)

Silva, Gilvan Ferreira da [PETROBRAS, Rio de Janeiro (Brazil). Centro de Pesquisas. Div. de Explotacao

1989-12-31

This paper describes the importance of sampling in the evaluation of physical and chemical properties of residues found in drilling dikes, considering the later selection of treatment methods or discard of these residues. We present the fundamental concepts of applied statistics, which are essential to the elaboration of sampling plans, with views of obtaining exact and precise results. Other types of samples are also presented, as well as sampling equipment and methods for storage and preservation of the samples. As a conclusion, we the example of the implementation of a sampling plan. (author) 3 refs., 9 figs., 3 tabs.

Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot

DEFF Research Database (Denmark)

Engemann, Kristine; Enquist, Brian J.; Sandel, Brody Steven

2015-01-01

in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second-order Jackknife and Bootstrapping resampling...

Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants

Science.gov (United States)

Sofaer, Helen R.; Jarnevich, Catherine S.

2017-01-01

AimThe distributions of exotic species reflect patterns of human-mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.LocationGlobal.Time periodMuseum records, generally from the 1800s up to 2015.Major taxa studiedPlant species exotic to the United States.MethodsWe used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world-wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.ResultsAccounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.Main conclusionsOur work provides support for broad-scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the

Sample size for estimation of the Pearson correlation coefficient in cherry tomato tests

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Bruno Giacomini Sari

2017-09-01

Full Text Available ABSTRACT: The aim of this study was to determine the required sample size for estimation of the Pearson coefficient of correlation between cherry tomato variables. Two uniformity tests were set up in a protected environment in the spring/summer of 2014. The observed variables in each plant were mean fruit length, mean fruit width, mean fruit weight, number of bunches, number of fruits per bunch, number of fruits, and total weight of fruits, with calculation of the Pearson correlation matrix between them. Sixty eight sample sizes were planned for one greenhouse and 48 for another, with the initial sample size of 10 plants, and the others were obtained by adding five plants. For each planned sample size, 3000 estimates of the Pearson correlation coefficient were obtained through bootstrap re-samplings with replacement. The sample size for each correlation coefficient was determined when the 95% confidence interval amplitude value was less than or equal to 0.4. Obtaining estimates of the Pearson correlation coefficient with high precision is difficult for parameters with a weak linear relation. Accordingly, a larger sample size is necessary to estimate them. Linear relations involving variables dealing with size and number of fruits per plant have less precision. To estimate the coefficient of correlation between productivity variables of cherry tomato, with a confidence interval of 95% equal to 0.4, it is necessary to sample 275 plants in a 250m² greenhouse, and 200 plants in a 200m² greenhouse.

Suppression of AC railway power-line interference in ECG signals recorded by public access defibrillators

Directory of Open Access Journals (Sweden)

Dotsinsky Ivan

2005-11-01

Full Text Available Abstract Background Public access defibrillators (PADs are now available for more efficient and rapid treatment of out-of-hospital sudden cardiac arrest. PADs are used normally by untrained people on the streets and in sports centers, airports, and other public areas. Therefore, automated detection of ventricular fibrillation, or its exclusion, is of high importance. A special case exists at railway stations, where electric power-line frequency interference is significant. Many countries, especially in Europe, use 16.7 Hz AC power, which introduces high level frequency-varying interference that may compromise fibrillation detection. Method Moving signal averaging is often used for 50/60 Hz interference suppression if its effect on the ECG spectrum has little importance (no morphological analysis is performed. This approach may be also applied to the railway situation, if the interference frequency is continuously detected so as to synchronize the analog-to-digital conversion (ADC for introducing variable inter-sample intervals. A better solution consists of rated ADC, software frequency measuring, internal irregular re-sampling according to the interference frequency, and a moving average over a constant sample number, followed by regular back re-sampling. Results The proposed method leads to a total railway interference cancellation, together with suppression of inherent noise, while the peak amplitudes of some sharp complexes are reduced. This reduction has negligible effect on accurate fibrillation detection. Conclusion The method is developed in the MATLAB environment and represents a useful tool for real time railway interference suppression.

Suppression of AC railway power-line interference in ECG signals recorded by public access defibrillators.

Science.gov (United States)

Dotsinsky, Ivan

2005-11-26

Public access defibrillators (PADs) are now available for more efficient and rapid treatment of out-of-hospital sudden cardiac arrest. PADs are used normally by untrained people on the streets and in sports centers, airports, and other public areas. Therefore, automated detection of ventricular fibrillation, or its exclusion, is of high importance. A special case exists at railway stations, where electric power-line frequency interference is significant. Many countries, especially in Europe, use 16.7 Hz AC power, which introduces high level frequency-varying interference that may compromise fibrillation detection. Moving signal averaging is often used for 50/60 Hz interference suppression if its effect on the ECG spectrum has little importance (no morphological analysis is performed). This approach may be also applied to the railway situation, if the interference frequency is continuously detected so as to synchronize the analog-to-digital conversion (ADC) for introducing variable inter-sample intervals. A better solution consists of rated ADC, software frequency measuring, internal irregular re-sampling according to the interference frequency, and a moving average over a constant sample number, followed by regular back re-sampling. The proposed method leads to a total railway interference cancellation, together with suppression of inherent noise, while the peak amplitudes of some sharp complexes are reduced. This reduction has negligible effect on accurate fibrillation detection. The method is developed in the MATLAB environment and represents a useful tool for real time railway interference suppression.

Estimation variance bounds of importance sampling simulations in digital communication systems

Science.gov (United States)

Lu, D.; Yao, K.

1991-01-01

In practical applications of importance sampling (IS) simulation, two basic problems are encountered, that of determining the estimation variance and that of evaluating the proper IS parameters needed in the simulations. The authors derive new upper and lower bounds on the estimation variance which are applicable to IS techniques. The upper bound is simple to evaluate and may be minimized by the proper selection of the IS parameter. Thus, lower and upper bounds on the improvement ratio of various IS techniques relative to the direct Monte Carlo simulation are also available. These bounds are shown to be useful and computationally simple to obtain. Based on the proposed technique, one can readily find practical suboptimum IS parameters. Numerical results indicate that these bounding techniques are useful for IS simulations of linear and nonlinear communication systems with intersymbol interference in which bit error rate and IS estimation variances cannot be obtained readily using prior techniques.

Gas and Isotope Geochemistry of 81 Steam Samples from Wells in The Geysers Geothermal Field, Sonoma and Lake Counties, California

Science.gov (United States)

Lowenstern, Jacob B.; Janik, Cathy J.; Fahlquist, Lynne; Johnson, Linda S.

1999-01-01

The Geysers geothermal field in northern California, with about 2000-MW electrical capacity, is the largest geothermal field in the world. Despite its importance as a resource and as an example of a vapor-dominated reservoir, very few complete geochemical analyses of the steam have been published (Allen and Day, 1927; Truesdell and others, 1987). This report presents data from 90 steam, gas, and condensate samples from wells in The Geysers geothermal field in northern California. Samples were collected between 1978 and 1991. Well attributes include sampling date, well name, location, total depth, and the wellhead temperature and pressure at which the sample was collected. Geochemical characteristics include the steam/gas ratio, composition of noncondensable gas (relative proportions of CO2, H2S, He, H2, O2, Ar, N2, CH4, and NH3), and isotopic values for deltaD and delta18O of H2O, delta13C of CO2, and delta34S of H2S. The compilation includes 81 analyses from 74 different production wells, 9 isotopic analyses of steam condensate pumped into injection wells, and 5 complete geochemical analyses on gases from surface fumaroles and bubbling pools. Most samples were collected as saturated steam and plot along the liquid-water/steam boiling curve. Steam-togas ratios are highest in the southeastern part of the geothermal field and lowest in the northwest, consistent with other studies. Wells in the Northwest Geysers are also enriched in N2/Ar, CO2 and CH4, deltaD, and delta18O. Well discharges from the Southeast Geysers are high in steam/gas and have isotopic compositions and N2/Ar ratios consistent with recharge by local meteoric waters. Samples from the Central Geysers show characteristics found in both the Southeast and Northwest Geysers. Gas and steam characteristics of well discharges from the Northwest Geysers are consistent with input of components from a high-temperature reservoir containing carbonrich gases derived from the host Franciscan rocks. Throughout the

Time-dependent importance sampling in semiclassical initial value representation calculations for time correlation functions. II. A simplified implementation.

Science.gov (United States)

Tao, Guohua; Miller, William H

2012-09-28

An efficient time-dependent (TD) Monte Carlo (MC) importance sampling method has recently been developed [G. Tao and W. H. Miller, J. Chem. Phys. 135, 024104 (2011)] for the evaluation of time correlation functions using the semiclassical (SC) initial value representation (IVR) methodology. In this TD-SC-IVR method, the MC sampling uses information from both time-evolved phase points as well as their initial values, and only the "important" trajectories are sampled frequently. Even though the TD-SC-IVR was shown in some benchmark examples to be much more efficient than the traditional time-independent sampling method (which uses only initial conditions), the calculation of the SC prefactor-which is computationally expensive, especially for large systems-is still required for accepted trajectories. In the present work, we present an approximate implementation of the TD-SC-IVR method that is completely prefactor-free; it gives the time correlation function as a classical-like magnitude function multiplied by a phase function. Application of this approach to flux-flux correlation functions (which yield reaction rate constants) for the benchmark H + H(2) system shows very good agreement with exact quantum results. Limitations of the approximate approach are also discussed.

Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F.; Amidan, Brett G.; Matzke, Brett D.

2009-02-16

This report describes the experimental and sampling design developed to assess sampling approaches and methods for detecting contamination in a building and clearing the building for use after decontamination. An Idaho National Laboratory (INL) building will be contaminated with BG (Bacillus globigii, renamed Bacillus atrophaeus), a simulant for Bacillus anthracis (BA). The contamination, sampling, decontamination, and re-sampling will occur per the experimental and sampling design. This INL-2 Sample Collection Operational Test is being planned by the Validated Sampling Plan Working Group (VSPWG). The primary objectives are: 1) Evaluate judgmental and probabilistic sampling for characterization as well as probabilistic and combined (judgment and probabilistic) sampling approaches for clearance, 2) Conduct these evaluations for gradient contamination (from low or moderate down to absent or undetectable) for different initial concentrations of the contaminant, 3) Explore judgment composite sampling approaches to reduce sample numbers, 4) Collect baseline data to serve as an indication of the actual levels of contamination in the tests. A combined judgmental and random (CJR) approach uses Bayesian methodology to combine judgmental and probabilistic samples to make clearance statements of the form "X% confidence that at least Y% of an area does not contain detectable contamination” (X%/Y% clearance statements). The INL-2 experimental design has five test events, which 1) vary the floor of the INL building on which the contaminant will be released, 2) provide for varying the amount of contaminant released to obtain desired concentration gradients, and 3) investigate overt as well as covert release of contaminants. Desirable contaminant gradients would have moderate to low concentrations of contaminant in rooms near the release point, with concentrations down to zero in other rooms. Such gradients would provide a range of contamination levels to challenge the sampling

Importance sampling large deviations in nonequilibrium steady states. I

Science.gov (United States)

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T.

2018-03-01

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

Importance sampling large deviations in nonequilibrium steady states. I.

Science.gov (United States)

Ray, Ushnish; Chan, Garnet Kin-Lic; Limmer, David T

2018-03-28

Large deviation functions contain information on the stability and response of systems driven into nonequilibrium steady states and in such a way are similar to free energies for systems at equilibrium. As with equilibrium free energies, evaluating large deviation functions numerically for all but the simplest systems is difficult because by construction they depend on exponentially rare events. In this first paper of a series, we evaluate different trajectory-based sampling methods capable of computing large deviation functions of time integrated observables within nonequilibrium steady states. We illustrate some convergence criteria and best practices using a number of different models, including a biased Brownian walker, a driven lattice gas, and a model of self-assembly. We show how two popular methods for sampling trajectory ensembles, transition path sampling and diffusion Monte Carlo, suffer from exponentially diverging correlations in trajectory space as a function of the bias parameter when estimating large deviation functions. Improving the efficiencies of these algorithms requires introducing guiding functions for the trajectories.

Sampling efficacy for the red imported fire ant Solenopsis invicta (Hymenoptera: Formicidae).

Science.gov (United States)

Stringer, Lloyd D; Suckling, David Maxwell; Baird, David; Vander Meer, Robert K; Christian, Sheree J; Lester, Philip J

2011-10-01

Cost-effective detection of invasive ant colonies before establishment in new ranges is imperative for the protection of national borders and reducing their global impact. We examined the sampling efficiency of food-baits and pitfall traps (baited and nonbaited) in detecting isolated red imported fire ant (Solenopsis invicta Buren) nests in multiple environments in Gainesville, FL. Fire ants demonstrated a significantly higher preference for a mixed protein food type (hotdog or ground meat combined with sweet peanut butter) than for the sugar or water baits offered. Foraging distance success was a function of colony size, detection trap used, and surveillance duration. Colony gyne number did not influence detection success. Workers from small nests (0- to 15-cm mound diameter) traveled no >3 m to a food source, whereas large colonies (>30-cm mound diameter) traveled up to 17 m. Baited pitfall traps performed best at detecting incipient ant colonies followed by nonbaited pitfall traps then food baits, whereas food baits performed well when trying to detect large colonies. These results were used to create an interactive model in Microsoft Excel, whereby surveillance managers can alter trap type, density, and duration parameters to estimate the probability of detecting specified or unknown S. invicta colony sizes. This model will support decision makers who need to balance the sampling cost and risk of failure to detect fire ant colonies.

Influence of short-term sampling parameters on the uncertainty of the Lden environmental noise indicator

International Nuclear Information System (INIS)

Mateus, M; Carrilho, J Dias; Da Silva, M Gameiro

2015-01-01

The present study deals with the influence of the sampling parameters on the uncertainty of noise equivalent level in environmental noise measurements. The study has been carried out through the test of different sampling strategies doing resampling trials over continuous monitoring noise files obtained previously in an urban location in the city of Coimbra, in Portugal. On short term measurements, not only the duration of the sampling episodes but also its number have influence on the uncertainty of the result. This influence is higher for the time periods where sound levels suffer a greater variation, such as during the night period. In this period, in case both parameters (duration and number of sampling episodes) are not carefully selected, the uncertainty level can reach too high values contributing to a loss of precision of the measurements. With the obtained data it was investigated the sampling parameters influence on the long term noise indicator uncertainty, calculated according the Draft 1st CD ISO 1996-2:2012 proposed method. It has been verified that this method allows the possibility of defining a general methodology which enables the setting of the parameters once the precision level is fixed. For the three reference periods defined for environmental noise (day, evening and night), it was possible to derive a two variable power law representing the uncertainty of the determined values as a function of the two sampling parameters: duration of sampling episode and number of episodes

Polyphase Filter Banks for Embedded Sample Rate Changes in Digital Radio Front-Ends

DEFF Research Database (Denmark)

Awan, Mehmood-Ur-Rehman; Le Moullec, Yannick; Koch, Peter

2011-01-01

. A non-maximally-decimated polyphase filter bank (where the number of data loads is not equal to the number of M subfilters) processes M subfilters in a time period that is less than or greater than the M data loads. A polyphase filter bank with five different resampling modes is used as a case study...

The importance of plot size and the number of sampling seasons on capturing macrofungal species richness.

Science.gov (United States)

Li, Huili; Ostermann, Anne; Karunarathna, Samantha C; Xu, Jianchu; Hyde, Kevin D; Mortimer, Peter E

2018-07-01

The species-area relationship is an important factor in the study of species diversity, conservation biology, and landscape ecology. A deeper understanding of this relationship is necessary, in order to provide recommendations on how to improve the quality of data collection on macrofungal diversity in different land use systems in future studies, a systematic assessment of methodological parameters, in particular optimal plot sizes. The species-area relationship of macrofungi in tropical and temperate climatic zones and four different land use systems were investigated by determining the macrofungal species richness in plot sizes ranging from 100 m 2 to 10 000 m 2 over two sampling seasons. We found that the effect of plot size on recorded species richness significantly differed between land use systems with the exception of monoculture systems. For both climate zones, land use system needs to be considered when determining optimal plot size. Using an optimal plot size was more important than temporal replication (over two sampling seasons) in accurately recording species richness. Copyright © 2018 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Wayside Bearing Fault Diagnosis Based on Envelope Analysis Paved with Time-Domain Interpolation Resampling and Weighted-Correlation-Coefficient-Guided Stochastic Resonance

Directory of Open Access Journals (Sweden)

Yongbin Liu

2017-01-01

Full Text Available Envelope spectrum analysis is a simple, effective, and classic method for bearing fault identification. However, in the wayside acoustic health monitoring system, owing to the high relative moving speed between the railway vehicle and the wayside mounted microphone, the recorded signal is embedded with Doppler effect, which brings in shift and expansion of the bearing fault characteristic frequency (FCF. What is more, the background noise is relatively heavy, which makes it difficult to identify the FCF. To solve the two problems, this study introduces solutions for the wayside acoustic fault diagnosis of train bearing based on Doppler effect reduction using the improved time-domain interpolation resampling (TIR method and diagnosis-relevant information enhancement using Weighted-Correlation-Coefficient-Guided Stochastic Resonance (WCCSR method. First, the traditional TIR method is improved by incorporating the original method with kinematic parameter estimation based on time-frequency analysis and curve fitting. Based on the estimated parameters, the Doppler effect is removed using the TIR easily. Second, WCCSR is employed to enhance the diagnosis-relevant period signal component in the obtained Doppler-free signal. Finally, paved with the above two procedures, the local fault is identified using envelope spectrum analysis. Simulated and experimental cases have verified the effectiveness of the proposed method.

Gap-Filling of Landsat 7 Imagery Using the Direct Sampling Method

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Gaohong Yin

2016-12-01

Full Text Available The failure of the Scan Line Corrector (SLC on Landsat 7 imposed systematic data gaps on retrieved imagery and removed the capacity to provide spatially continuous fields. While a number of methods have been developed to fill these gaps, most of the proposed techniques are only applicable over relatively homogeneous areas. When they are applied to heterogeneous landscapes, retrieving image features and elements can become challenging. Here we present a gap-filling approach that is based on the adoption of the Direct Sampling multiple-point geostatistical method. The method employs a conditional stochastic resampling of known areas in a training image to simulate unknown locations. The approach is assessed across a range of both homogeneous and heterogeneous regions. Simulation results show that for homogeneous areas, satisfactory results can be obtained by simply adopting non-gap locations in the target image as baseline training data. For heterogeneous landscapes, bivariate simulations using an auxiliary variable acquired at a different date provides more accurate results than univariate simulations, especially as land cover complexity increases. Apart from recovering spatially continuous fields, one of the key advantages of the Direct Sampling is the relatively straightforward implementation process that relies on relatively few parameters.

A review of electro analytical determinations of some important elements (Zn, Se, As) in environmental samples

International Nuclear Information System (INIS)

Lichiang; James, B.D.; Magee, R.J.

1991-01-01

This review covers electro analytical methods reported in the literature for the determination of zinc, cadmium, selenium and arsenic in environmental and biological samples. A comprehensive survey of electro analytical techniques used for the determination of four important elements, i.e. zinc, cadmium, selenium and arsenic is reported herein with 322 references up to 1990. (Orig./A.B.)

Importance sampling with imperfect cloning for the computation of generalized Lyapunov exponents

Science.gov (United States)

Anteneodo, Celia; Camargo, Sabrina; Vallejos, Raúl O.

2017-12-01

We revisit the numerical calculation of generalized Lyapunov exponents, L (q ) , in deterministic dynamical systems. The standard method consists of adding noise to the dynamics in order to use importance sampling algorithms. Then L (q ) is obtained by taking the limit noise-amplitude → 0 after the calculation. We focus on a particular method that involves periodic cloning and pruning of a set of trajectories. However, instead of considering a noisy dynamics, we implement an imperfect (noisy) cloning. This alternative method is compared with the standard one and, when possible, with analytical results. As a workbench we use the asymmetric tent map, the standard map, and a system of coupled symplectic maps. The general conclusion of this study is that the imperfect-cloning method performs as well as the standard one, with the advantage of preserving the deterministic dynamics.

The importance of cooling of urine samples for doping analysis

NARCIS (Netherlands)

Kuenen, J. Gijs; Konings, Wil N.

Storing and transporting of urine samples for doping analysis, as performed by the anti-doping organizations associated with the World Anti-Doping Agency, does not include a specific protocol for cooled transport from the place of urine sampling to the doping laboratory, although low cost cooling

Communication: importance sampling including path correlation in semiclassical initial value representation calculations for time correlation functions.

Science.gov (United States)

Pan, Feng; Tao, Guohua

2013-03-07

Full semiclassical (SC) initial value representation (IVR) for time correlation functions involves a double phase space average over a set of two phase points, each of which evolves along a classical path. Conventionally, the two initial phase points are sampled independently for all degrees of freedom (DOF) in the Monte Carlo procedure. Here, we present an efficient importance sampling scheme by including the path correlation between the two initial phase points for the bath DOF, which greatly improves the performance of the SC-IVR calculations for large molecular systems. Satisfactory convergence in the study of quantum coherence in vibrational relaxation has been achieved for a benchmark system-bath model with up to 21 DOF.

Identifying the Threshold of Dominant Controls on Fire Spread in a Boreal Forest Landscape of Northeast China

Science.gov (United States)

Liu, Zhihua; Yang, Jian; He, Hong S.

2013-01-01

The relative importance of fuel, topography, and weather on fire spread varies at different spatial scales, but how the relative importance of these controls respond to changing spatial scales is poorly understood. We designed a “moving window” resampling technique that allowed us to quantify the relative importance of controls on fire spread at continuous spatial scales using boosted regression trees methods. This quantification allowed us to identify the threshold value for fire size at which the dominant control switches from fuel at small sizes to weather at large sizes. Topography had a fluctuating effect on fire spread across the spatial scales, explaining 20–30% of relative importance. With increasing fire size, the dominant control switched from bottom-up controls (fuel and topography) to top-down controls (weather). Our analysis suggested that there is a threshold for fire size, above which fires are driven primarily by weather and more likely lead to larger fire size. We suggest that this threshold, which may be ecosystem-specific, can be identified using our “moving window” resampling technique. Although the threshold derived from this analytical method may rely heavily on the sampling technique, our study introduced an easily implemented approach to identify scale thresholds in wildfire regimes. PMID:23383247

Support, shape and number of replicate samples for tree foliage analysis.

Science.gov (United States)

Luyssaert, Sebastiaan; Mertens, Jan; Raitio, Hannu

2003-06-01

Many fundamental features of a sampling program are determined by the heterogeneity of the object under study and the settings for the error (alpha), the power (beta), the effect size (ES), the number of replicate samples, and sample support, which is a feature that is often overlooked. The number of replicates, alpha, beta, ES, and sample support are interconnected. The effect of the sample support and its shape on the required number of replicate samples was investigated by means of a resampling method. The method was applied to a simulated distribution of Cd in the crown of a Salix fragilis L. tree. Increasing the dimensions of the sample support results in a decrease in the variance of the element concentration under study. Analysis of the variance is often the foundation of statistical tests, therefore, valid statistical testing requires the use of a fixed sample support during the experiment. This requirement might be difficult to meet in time-series analyses and long-term monitoring programs. Sample supports have their largest dimension in the direction with the largest heterogeneity, i.e. the direction representing the crown height, and this will give more accurate results than supports with other shapes. Taking the relationships between the sample support and the variance of the element concentrations in tree crowns into account provides guidelines for sampling efficiency in terms of precision and costs. In terms of time, the optimal support to test whether the average Cd concentration of the crown exceeds a threshold value is 0.405 m3 (alpha = 0.05, beta = 0.20, ES = 1.0 mg kg(-1) dry mass). The average weight of this support is 23 g dry mass, and 11 replicate samples need to be taken. It should be noted that in this case the optimal support applies to Cd under conditions similar to those of the simulation, but not necessarily all the examinations for this tree species, element, and hypothesis test.

The Importance of Meteorite Collections to Sample Return Missions: Past, Present, and Future Considerations

Science.gov (United States)

Welzenbach, L. C.; McCoy, T. J.; Glavin, D. P.; Dworkin, J. P.; Abell, P. A.

2012-01-01

turn led to a new wave of Mars exploration that ultimately could lead to sample return focused on evidence for past or present life. This partnership between collections and missions will be increasingly important in the coming decades as we discover new questions to be addressed and identify targets for for both robotic and human exploration . Nowhere is this more true than in the ultimate search for the abiotic and biotic processes that produced life. Existing collections also provide the essential materials for developing and testing new analytical schemes to detect the rare markers of life and distinguish them from abiotic processes. Large collections of meteorites and the new types being identified within these collections, which come to us at a fraction of the cost of a sample return mission, will continue to shape the objectives of future missions and provide new ways of interpreting returned samples.

The importance of the sampling frequency in determining short-time-averaged irradiance and illuminance for rapidly changing cloud cover

International Nuclear Information System (INIS)

Delaunay, J.J.; Rommel, M.; Geisler, J.

1994-01-01

The sampling interval is an important parameter which must be chosen carefully, if measurements of the direct, global, and diffuse irradiance or illuminance are carried out to determine their averages over a given period. Using measurements from a day with rapidly moving clouds, we investigated the influence of the sampling interval on the uncertainly of the calculated 15-min averages. We conclude, for this averaging period, that the sampling interval should not exceed 60 s and 10 s for measurement of the diffuse and global components respectively, to reduce the influence of the sampling interval below 2%. For the direct component, even a 5 s sampling interval is too long to reach this influence level for days with extremely quickly changing insolation conditions. (author)

Fixed-Precision Sequential Sampling Plans for Estimating Alfalfa Caterpillar, Colias lesbia, Egg Density in Alfalfa, Medicago sativa, Fields in Córdoba, Argentina

Science.gov (United States)

Serra, Gerardo V.; Porta, Norma C. La; Avalos, Susana; Mazzuferi, Vilma

2013-01-01

The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies. PMID:23909840

A Hybrid Monte Carlo importance sampling of rare events in Turbulence and in Turbulent Models

Science.gov (United States)

Margazoglou, Georgios; Biferale, Luca; Grauer, Rainer; Jansen, Karl; Mesterhazy, David; Rosenow, Tillmann; Tripiccione, Raffaele

2017-11-01

Extreme and rare events is a challenging topic in the field of turbulence. Trying to investigate those instances through the use of traditional numerical tools turns to be a notorious task, as they fail to systematically sample the fluctuations around them. On the other hand, we propose that an importance sampling Monte Carlo method can selectively highlight extreme events in remote areas of the phase space and induce their occurrence. We present a brand new computational approach, based on the path integral formulation of stochastic dynamics, and employ an accelerated Hybrid Monte Carlo (HMC) algorithm for this purpose. Through the paradigm of stochastic one-dimensional Burgers' equation, subjected to a random noise that is white-in-time and power-law correlated in Fourier space, we will prove our concept and benchmark our results with standard CFD methods. Furthermore, we will present our first results of constrained sampling around saddle-point instanton configurations (optimal fluctuations). The research leading to these results has received funding from the EU Horizon 2020 research and innovation programme under Grant Agreement No. 642069, and from the EU Seventh Framework Programme (FP7/2007-2013) under ERC Grant Agreement No. 339032.

An introduction to Bartlett correction and bias reduction

CERN Document Server

Cordeiro, Gauss M

2014-01-01

This book presents a concise introduction to Bartlett and Bartlett-type corrections of statistical tests and bias correction of point estimators. The underlying idea behind both groups of corrections is to obtain higher accuracy in small samples. While the main focus is on corrections that can be analytically derived, the authors also present alternative strategies for improving estimators and tests based on bootstrap, a data resampling technique, and discuss concrete applications to several important statistical models.

The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings.

Science.gov (United States)

Lorca-Puls, Diego L; Gajardo-Vidal, Andrea; White, Jitrachote; Seghier, Mohamed L; Leff, Alexander P; Green, David W; Crinion, Jenny T; Ludersdorfer, Philipp; Hope, Thomas M H; Bowman, Howard; Price, Cathy J

2018-07-01

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Efficient Implementation of Filtering and Resampling Operations on Field Programmable Gate Arrays (FPGAs) for Software Defined Radio (SDR)

National Research Council Canada - National Science Library

Giannoulis, Georgios

2008-01-01

.... The data rate of the transmitted information is very important, since efficiency is a key requirement in real time implementations and cost increases considerably with the number of samples per second to be processed...

Sample size estimation and sampling techniques for selecting a representative sample

Directory of Open Access Journals (Sweden)

Aamir Omair

2014-01-01

Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

Prescribed burning in a Eucalyptus woodland suppresses fruiting of hypogeous fungi, an important food source for mammals.

Science.gov (United States)

Trappe, James M; Nicholls, A O; Claridge, Andrew W; Cork, Steven J

2006-11-01

Fruit bodies of hypogeous fungi are an important food source for many small mammals and are consumed by larger mammals as well. A controversial hypothesis that prescribed burning increases fruiting of certain hypogeous fungi based on observations in Tasmania was tested in the Australian Capital Territory to determine if it applied in a quite different habitat. Ten pairs of plots, burnt and nonburnt, were established at each of two sites prescribe-burnt in May 1999. When sampled in early July, after autumn rains had initiated the fungal fruiting season, species richness and numbers of fruit bodies on the burnt plots were extremely low: most plots produced none at all. Both species richness and fruit body numbers were simultaneously high on nonburnt plots. One of the sites was resampled a year after the initial sampling. At that time species richness and fruit body abundance were still significantly less on burnt plots than on nonburnt, but a strong trend towards fungal recovery on the burnt plots was evident. This was particularly so when numbers of fruit bodies of one species, the hypogeous agaric Dermocybe globuliformis, were removed from the analysis. This species strongly dominated the nonburnt plots but was absent from burnt plots in both years. The trend towards recovery of fruit body abundance in the burnt plots one year after the burn was much more pronounced with exclusion of the Dermocybe data. The Tasmanian-based hypothesis was based mostly on the fruiting of two fire-adapted species in the Mesophelliaceae. Neither species occurred on our plots. Accordingly, the results and conclusions of the Tasmanian study cannot be extrapolated to other habitats without extensive additional study. Implications for management of habitat for fungi and the animals that rely on the fungi as a food source are discussed.

PERFORMANCE COMPARISON OF SCENARIO-GENERATION METHODS APPLIED TO A STOCHASTIC OPTIMIZATION ASSET-LIABILITY MANAGEMENT MODEL

Directory of Open Access Journals (Sweden)

Alan Delgado de Oliveira

Full Text Available ABSTRACT In this paper, we provide an empirical discussion of the differences among some scenario tree-generation approaches for stochastic programming. We consider the classical Monte Carlo sampling and Moment matching methods. Moreover, we test the Resampled average approximation, which is an adaptation of Monte Carlo sampling and Monte Carlo with naive allocation strategy as the benchmark. We test the empirical effects of each approach on the stability of the problem objective function and initial portfolio allocation, using a multistage stochastic chance-constrained asset-liability management (ALM model as the application. The Moment matching and Resampled average approximation are more stable than the other two strategies.

A hybrid algorithm for reliability analysis combining Kriging and subset simulation importance sampling

International Nuclear Information System (INIS)

Tong, Cao; Sun, Zhili; Zhao, Qianli; Wang, Qibin; Wang, Shuang

2015-01-01

To solve the problem of large computation when failure probability with time-consuming numerical model is calculated, we propose an improved active learning reliability method called AK-SSIS based on AK-IS algorithm. First, an improved iterative stopping criterion in active learning is presented so that iterations decrease dramatically. Second, the proposed method introduces Subset simulation importance sampling (SSIS) into the active learning reliability calculation, and then a learning function suitable for SSIS is proposed. Finally, the efficiency of AK-SSIS is proved by two academic examples from the literature. The results show that AK-SSIS requires fewer calls to the performance function than AK-IS, and the failure probability obtained from AK-SSIS is very robust and accurate. Then this method is applied on a spur gear pair for tooth contact fatigue reliability analysis.

A hybrid algorithm for reliability analysis combining Kriging and subset simulation importance sampling

Energy Technology Data Exchange (ETDEWEB)

Tong, Cao; Sun, Zhili; Zhao, Qianli; Wang, Qibin [Northeastern University, Shenyang (China); Wang, Shuang [Jiangxi University of Science and Technology, Ganzhou (China)

2015-08-15

To solve the problem of large computation when failure probability with time-consuming numerical model is calculated, we propose an improved active learning reliability method called AK-SSIS based on AK-IS algorithm. First, an improved iterative stopping criterion in active learning is presented so that iterations decrease dramatically. Second, the proposed method introduces Subset simulation importance sampling (SSIS) into the active learning reliability calculation, and then a learning function suitable for SSIS is proposed. Finally, the efficiency of AK-SSIS is proved by two academic examples from the literature. The results show that AK-SSIS requires fewer calls to the performance function than AK-IS, and the failure probability obtained from AK-SSIS is very robust and accurate. Then this method is applied on a spur gear pair for tooth contact fatigue reliability analysis.

Baseline geochemical data for stream sediment and surface water samples from Panther Creek, the Middle Fork of the Salmon River, and the Main Salmon River from North Fork to Corn Creek, collected prior to the severe wildfires of 2000 in central Idaho

Science.gov (United States)

Eppinger, Robert G.; Briggs, Paul H.; Brown, Zoe Ann; Crock, James G.; Meier, Allen; Theodorakos, Peter M.; Wilson, Stephen A.

2001-01-01

In 1996, the U.S. Geological Survey conducted a reconnaissance baseline geochemical study in central Idaho. The purpose of the baseline study was to establish a 'geochemical snapshot' of the area, as a datum for monitoring future change in the geochemical landscape, whether natural or human-induced. This report presents the methology, analytical results, and sample descriptions for water, sediment, and heavy-mineral concentrate samples collected during this geochemical investigation. In the summer of 2000, the Clear Creek, Little Pistol, and Shellrock wildfires swept across much of the area that was sampled. Thus, these data represent a pre-fire baseline geochemical dataset. A 2001 post- fire study is planned and will involve re-sampling of the pre-fire baseline sites, to allow for pre- and post-fire comparison.

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

Science.gov (United States)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to

The importance of community building for establishing data management and curation practices for physical samples

Science.gov (United States)

Ramdeen, S.; Hangsterfer, A.; Stanley, V. L.

2017-12-01

There is growing enthusiasm for curation of physical samples in the Earth Science community (see sessions at AGU, GSA, ESIP). Multiple federally funded efforts aim to develop best practices for curation of physical samples; however, these efforts have not yet been consolidated. Harmonizing these concurrent efforts would enable the community as a whole to build the necessary tools and community standards to move forward together. Preliminary research indicate the various groups focused on this topic are working in isolation, and the development of standards needs to come from the broadest view of `community'. We will investigate the gaps between communities by collecting information about preservation policies and practices from curators, who can provide a diverse cross-section of the grand challenges to the overall community. We will look at existing reports and study results to identify example cases, then develop a survey to gather large scale data to reinforce or clarify the example cases. We will be targeting the various community groups which are working on similar issues, and use the survey to improve the visibility of developed best practices. Given that preservation and digital collection management for physical samples are both important and difficult at present (GMRWG, 2015; NRC, 2002), barriers to both need to be addressed in order to achieve open science goals for the entire community. To address these challenges, EarthCube's iSamples, a research coordination network established to advance discoverability, access, and curation of physical samples using cyberinfrastructure, has formed a working group to collect use cases to examine the breadth of earth scientists' work with physical samples. This research team includes curators of state survey and oceanographic geological collections, and a researcher from information science. In our presentation, we will share our research and the design of the proposed survey. Our goal is to engage the audience in a

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

Science.gov (United States)

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Parallel importance sampling in conditional linear Gaussian networks

DEFF Research Database (Denmark)

Salmerón, Antonio; Ramos-López, Darío; Borchani, Hanen

2015-01-01

In this paper we analyse the problem of probabilistic inference in CLG networks when evidence comes in streams. In such situations, fast and scalable algorithms, able to provide accurate responses in a short time are required. We consider the instantiation of variational inference and importance ...

Changeover Inference: Estimating the Relationship Between DT and OT Data

National Research Council Canada - National Science Library

Dippery, Kevin

1997-01-01

... which has undergone developmental testing. Using a re-sampling method called the Bootstrap, the sampling variance and standard error of the changeover factor are calculated, as are confidence intervals for the OT failure rate of a new system...

VOYAGER 1 SATURN POSITION RESAMPLED DATA 48.0 SECONDS

Data.gov (United States)

National Aeronautics and Space Administration — This data set includes Voyager 1 Saturn encounter position data that have been generated at a 48.0 second sample rate using the NAIF SPICE kernals. The data set is...

VOYAGER 2 SATURN POSITION RESAMPLED DATA 48.0 SECONDS

Data.gov (United States)

National Aeronautics and Space Administration — This data set includes Voyager 2 Saturn encounter position data that have been generated at a 48.0 second sample rate using the NAIF SPICE kernals. The data set is...

VOYAGER 1 JUPITER POSITION RESAMPLED DATA 48.0 SECONDS

Data.gov (United States)

National Aeronautics and Space Administration — This data set includes Voyager 1 Jupiter encounter position data that have been generated at a 48.0 second sample rate using the NAIF SPICE kernals. The data set is...

VOYAGER 2 JUPITER POSITION RESAMPLED DATA 48.0 SECONDS

Data.gov (United States)

National Aeronautics and Space Administration — This data set includes Voyager 2 Jupiter encounter position data that have been generated at a 48.0 second sample rate using the NAIF SPICE kernals. The data set is...

Adaptive particle filter for localization problem in service robotics

Directory of Open Access Journals (Sweden)

Heilig Alexander

2018-01-01

Full Text Available In this paper we present a statistical approach to the likelihood computation and adaptive resampling algorithm for particle filters using low cost ultrasonic sensors in the context of service robotics. This increases the efficiency of the particle filter in the Monte Carlo Localization problem by means of preventing sample impoverishment and ensuring it converges towards the most likely particle and simultaneously keeping less likely ones by systematic resampling. Proposed algorithms were developed in the ROS framework, simulation was done in Gazebo environment. Experiments using a differential drive mobile platform with 4 ultrasonic sensors in the office environment show that our approach provides strong improvement over particle filters with fixed sample sizes.

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

Science.gov (United States)

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks

International Nuclear Information System (INIS)

Wu, Ji; Zhang, Chenbin; Chen, Zonghai

2016-01-01

Highlights: • An online RUL estimation method for lithium-ion battery is proposed. • RUL is described by the difference among battery terminal voltage curves. • A feed forward neural network is employed for RUL estimation. • Importance sampling is utilized to select feed forward neural network inputs. - Abstract: An accurate battery remaining useful life (RUL) estimation can facilitate the design of a reliable battery system as well as the safety and reliability of actual operation. A reasonable definition and an effective prediction algorithm are indispensable for the achievement of an accurate RUL estimation result. In this paper, the analysis of battery terminal voltage curves under different cycle numbers during charge process is utilized for RUL definition. Moreover, the relationship between RUL and charge curve is simulated by feed forward neural network (FFNN) for its simplicity and effectiveness. Considering the nonlinearity of lithium-ion charge curve, importance sampling (IS) is employed for FFNN input selection. Based on these results, an online approach using FFNN and IS is presented to estimate lithium-ion battery RUL in this paper. Experiments and numerical comparisons are conducted to validate the proposed method. The results show that the FFNN with IS is an accurate estimation method for actual operation.

Do women's voices provide cues of the likelihood of ovulation? The importance of sampling regime.

Directory of Open Access Journals (Sweden)

Julia Fischer

Full Text Available The human voice provides a rich source of information about individual attributes such as body size, developmental stability and emotional state. Moreover, there is evidence that female voice characteristics change across the menstrual cycle. A previous study reported that women speak with higher fundamental frequency (F0 in the high-fertility compared to the low-fertility phase. To gain further insights into the mechanisms underlying this variation in perceived attractiveness and the relationship between vocal quality and the timing of ovulation, we combined hormone measurements and acoustic analyses, to characterize voice changes on a day-to-day basis throughout the menstrual cycle. Voice characteristics were measured from free speech as well as sustained vowels. In addition, we asked men to rate vocal attractiveness from selected samples. The free speech samples revealed marginally significant variation in F0 with an increase prior to and a distinct drop during ovulation. Overall variation throughout the cycle, however, precluded unequivocal identification of the period with the highest conception risk. The analysis of vowel samples revealed a significant increase in degree of unvoiceness and noise-to-harmonic ratio during menstruation, possibly related to an increase in tissue water content. Neither estrogen nor progestogen levels predicted the observed changes in acoustic characteristics. The perceptual experiments revealed a preference by males for voice samples recorded during the pre-ovulatory period compared to other periods in the cycle. While overall we confirm earlier findings in that women speak with a higher and more variable fundamental frequency just prior to ovulation, the present study highlights the importance of taking the full range of variation into account before drawing conclusions about the value of these cues for the detection of ovulation.

On the Sampling

OpenAIRE

Güleda Doğan

2017-01-01

This editorial is on statistical sampling, which is one of the most two important reasons for editorial rejection from our journal Turkish Librarianship. The stages of quantitative research, the stage in which we are sampling, the importance of sampling for a research, deciding on sample size and sampling methods are summarised briefly.

Variability in metagenomic samples from the Puget Sound: Relationship to temporal and anthropogenic impacts.

Directory of Open Access Journals (Sweden)

James C Wallace

Full Text Available Whole-metagenome sequencing (WMS has emerged as a powerful tool to assess potential public health risks in marine environments by measuring changes in microbial community structure and function in uncultured bacteria. In addition to monitoring public health risks such as antibiotic resistance determinants, it is essential to measure predictors of microbial variation in order to identify natural versus anthropogenic factors as well as to evaluate reproducibility of metagenomic measurements.This study expands our previous metagenomic characterization of Puget Sound by sampling new nearshore environments including the Duwamish River, an EPA superfund site, and the Hood Canal, an area characterized by highly variable oxygen levels. We also resampled a wastewater treatment plant, nearshore and open ocean sites introducing a longitudinal component measuring seasonal and locational variations and establishing metagenomics sampling reproducibility. Microbial composition from samples collected in the open sound were highly similar within the same season and location across different years, while nearshore samples revealed multi-fold seasonal variation in microbial composition and diversity. Comparisons with recently sequenced predominant marine bacterial genomes helped provide much greater species level taxonomic detail compared to our previous study. Antibiotic resistance determinants and pollution and detoxification indicators largely grouped by location showing minor seasonal differences. Metal resistance, oxidative stress and detoxification systems showed no increase in samples proximal to an EPA superfund site indicating a lack of ecosystem adaptation to anthropogenic impacts. Taxonomic analysis of common sewage influent families showed a surprising similarity between wastewater treatment plant and open sound samples suggesting a low-level but pervasive sewage influent signature in Puget Sound surface waters. Our study shows reproducibility of

Orthogonal projections and bootstrap resampling procedures in the study of infraspecific variation

Directory of Open Access Journals (Sweden)

Luiza Carla Duarte

1998-12-01

Full Text Available The effect of an increase in quantitative continuous characters resulting from indeterminate growth upon the analysis of population differentiation was investigated using, as an example, a set of continuous characters measured as distance variables in 10 populations of a rodent species. The data before and after correction for allometric size effects using orthogonal projections were analyzed with a parametric bootstrap resampling procedure applied to canonical variate analysis. The variance component of the distance measures attributable to indeterminate growth within the populations was found to be substantial, although the ordination of the populations was not affected, as evidenced by the relative and absolute positions of the centroids. The covariance pattern of the distance variables used to infer the nature of the morphological differences was strongly influenced by indeterminate growth. The uncorrected data produced a misleading picture of morphological differentiation by indicating that groups of populations differed in size. However, the data corrected for allometric effects clearly demonstrated that populations differed morphologically both in size and shape. These results are discussed in terms of the analysis of morphological differentiation among populations and the definition of infraspecific geographic units.A influência do aumento em caracteres quantitativos contínuos devido ao crescimento indeterminado sobre a análise de diferenciação entre populações foi investigado utilizando como exemplo um conjunto de dados de variáveis craniométricas em 10 populações de uma espécie de roedor. Dois conjuntos de dados, um não corrigido para o efeito alométrico do tamanho e um outro corrigido para o efeito alométrico do tamanho utilizando um método de projeção ortogonal, foram analisados por um procedimento "bootstrap" de reamostragem aplicado à análise de variáveis canônicas. O componente de variância devido ao

Simulative Investigation on Spectral Efficiency of Unipolar Codes based OCDMA System using Importance Sampling Technique

Science.gov (United States)

Farhat, A.; Menif, M.; Rezig, H.

2013-09-01

This paper analyses the spectral efficiency of Optical Code Division Multiple Access (OCDMA) system using Importance Sampling (IS) technique. We consider three configurations of OCDMA system namely Direct Sequence (DS), Spectral Amplitude Coding (SAC) and Fast Frequency Hopping (FFH) that exploits the Fiber Bragg Gratings (FBG) based encoder/decoder. We evaluate the spectral efficiency of the considered system by taking into consideration the effect of different families of unipolar codes for both coherent and incoherent sources. The results show that the spectral efficiency of OCDMA system with coherent source is higher than the incoherent case. We demonstrate also that DS-OCDMA outperforms both others in terms of spectral efficiency in all conditions.

Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels

KAUST Repository

Rached, Nadhir B.; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul

2015-01-01

The outage capacity (OC) is among the most important performance metrics of communication systems operating over fading channels. Of interest in the present paper is the evaluation of the OC at the output of the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC) receivers. In this case, it can be seen that this problem turns out to be that of computing the Cumulative Distribution Function (CDF) for the sum of independent random variables. Since finding a closedform expression for the CDF of the sum distribution is out of reach for a wide class of commonly used distributions, methods based on Monte Carlo (MC) simulations take pride of price. In order to allow for the estimation of the operating range of small outage probabilities, it is of paramount importance to develop fast and efficient estimation methods as naive Monte Carlo (MC) simulations would require high computational complexity. In this line, we propose in this work two unified, yet efficient, hazard rate twisting Importance Sampling (IS) based approaches that efficiently estimate the OC of MRC or EGC diversity techniques over generalized independent fading channels. The first estimator is shown to possess the asymptotic optimality criterion and applies for arbitrary fading models, whereas the second one achieves the well-desired bounded relative error property for the majority of the well-known fading variates. Moreover, the second estimator is shown to achieve the asymptotic optimality property under the particular Log-normal environment. Some selected simulation results are finally provided in order to illustrate the substantial computational gain achieved by the proposed IS schemes over naive MC simulations.

Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels

KAUST Repository

Rached, Nadhir B.

2015-11-13

The outage capacity (OC) is among the most important performance metrics of communication systems operating over fading channels. Of interest in the present paper is the evaluation of the OC at the output of the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC) receivers. In this case, it can be seen that this problem turns out to be that of computing the Cumulative Distribution Function (CDF) for the sum of independent random variables. Since finding a closedform expression for the CDF of the sum distribution is out of reach for a wide class of commonly used distributions, methods based on Monte Carlo (MC) simulations take pride of price. In order to allow for the estimation of the operating range of small outage probabilities, it is of paramount importance to develop fast and efficient estimation methods as naive Monte Carlo (MC) simulations would require high computational complexity. In this line, we propose in this work two unified, yet efficient, hazard rate twisting Importance Sampling (IS) based approaches that efficiently estimate the OC of MRC or EGC diversity techniques over generalized independent fading channels. The first estimator is shown to possess the asymptotic optimality criterion and applies for arbitrary fading models, whereas the second one achieves the well-desired bounded relative error property for the majority of the well-known fading variates. Moreover, the second estimator is shown to achieve the asymptotic optimality property under the particular Log-normal environment. Some selected simulation results are finally provided in order to illustrate the substantial computational gain achieved by the proposed IS schemes over naive MC simulations.

Bootstrap Determination of the Co-integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A.M.Robert

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we investigate...... the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically correctly sized and...

Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A. M. Robert

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio [PLR] co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying VAR model which obtain under the reduced rank null hypothesis. They propose methods based on an i.i.d. bootstrap re-sampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co-integrated VAR model with i.i.d. innovations. In this paper we investigate...... the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap re-sampling scheme, when time-varying behaviour is present in either the conditional or unconditional variance of the innovations. We show that the bootstrap PLR tests are asymptotically correctly sized and...

Support the Design of Improved IUE NEWSIPS High Dispersion Extraction Algorithms: Improved IUE High Dispersion Extraction Algorithms

Science.gov (United States)

Lawton, Pat

2004-01-01

The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.

Optimizing sampling design to deal with mist-net avoidance in Amazonian birds and bats.

Directory of Open Access Journals (Sweden)

João Tiago Marques

Full Text Available Mist netting is a widely used technique to sample bird and bat assemblages. However, captures often decline with time because animals learn and avoid the locations of nets. This avoidance or net shyness can substantially decrease sampling efficiency. We quantified the day-to-day decline in captures of Amazonian birds and bats with mist nets set at the same location for four consecutive days. We also evaluated how net avoidance influences the efficiency of surveys under different logistic scenarios using re-sampling techniques. Net avoidance caused substantial declines in bird and bat captures, although more accentuated in the latter. Most of the decline occurred between the first and second days of netting: 28% in birds and 47% in bats. Captures of commoner species were more affected. The numbers of species detected also declined. Moving nets daily to minimize the avoidance effect increased captures by 30% in birds and 70% in bats. However, moving the location of nets may cause a reduction in netting time and captures. When moving the nets caused the loss of one netting day it was no longer advantageous to move the nets frequently. In bird surveys that could even decrease the number of individuals captured and species detected. Net avoidance can greatly affect sampling efficiency but adjustments in survey design can minimize this. Whenever nets can be moved without losing netting time and the objective is to capture many individuals, they should be moved daily. If the main objective is to survey species present then nets should still be moved for bats, but not for birds. However, if relocating nets causes a significant loss of netting time, moving them to reduce effects of shyness will not improve sampling efficiency in either group. Overall, our findings can improve the design of mist netting sampling strategies in other tropical areas.

Use of Instrumental Neutron Activation Analysis for Determination of Some Trace Elements of Biological Importance in Different Jute(Corchorus Capsularis) Seed Samples

International Nuclear Information System (INIS)

Metwally, E.; Abd-El-Khalik, H.; El-Sweify, F.H.; El-Sweify, A.H.H.

2004-01-01

Instrumental neutron activation analysis technique was used to determine some trace elements in seeds of jute (corchorus capsularis). The seed samples were obtained from Agricultural Research Center (ARC), Giza, (EG). The analyzed seed samples were produced from cultivation of three different strains, namely: St. DC 1105, st. JRC 7447 and St. PADMA. These strains were imported from Bangladesh. The jute plant was cultivated in sandy soil in Ismailaya research station farm at may on two seasons 1999 and 2000. The plant was irrigated with water from Ismailaya canal. The study was carried out to compare the influence of applying different kinds of fertilizers of different rates, i.e. mineral fertilizer and biofertilizer, on the uptake of some biologically important trace elements and to determine their concentration in the analyzed jute seed samples. These elements were; Co,Cr,Fe,Zn and others eight elements were analyzed quantitatively

Unscented Kalman filtering in the additive noise case

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

The unscented Kalman filter(UKF) has four implementations in the additive noise case,according to whether the state is augmented with noise vectors and whether a new set of sigma points is redrawn from the predicted state(which is so-called resampling) for the observation prediction.This paper concerns the differences of performances for those implementations,such as accuracy,adaptability,computational complexity,etc.The conditionally equivalent relationships between the augmented and non-augmented unscented transforms(UTs) are proved for several sampling strategies that are commonly used.Then,we find that the augmented and non-augmented UKFs have the same filter results with the additive measurement noise,but only have the same state predictions with the additive process noise.Resampling is not believed to be necessary in some researches.However,we find out that resampling can be helpful for an adaptive Kalman gain.This will improve the convergence and accuracy of the filter when the large scale state modeling bias or unknown maneuvers occur.Finally,some universal designing principles for a practical UKF are given as follows:1) for the additive observation noise case,it’s better to use the non-augmented UKF;2) for the additive process noise case,when the small state modeling bias or maneuvers are involved,the non-resampling algorithms with state whether augmented or not are candidates for filters;3) the resampling and non-augmented algorithm is the only choice while the large state modeling bias or maneuvers are latent.

FACE Analysis as a Fast and Reliable Methodology to Monitor the Sulfation and Total Amount of Chondroitin Sulfate in Biological Samples of Clinical Importance

Directory of Open Access Journals (Sweden)

Evgenia Karousou

2014-06-01

Full Text Available Glycosaminoglycans (GAGs due to their hydrophilic character and high anionic charge densities play important roles in various (pathophysiological processes. The identification and quantification of GAGs in biological samples and tissues could be useful prognostic and diagnostic tools in pathological conditions. Despite the noteworthy progress in the development of sensitive and accurate methodologies for the determination of GAGs, there is a significant lack in methodologies regarding sample preparation and reliable fast analysis methods enabling the simultaneous analysis of several biological samples. In this report, developed protocols for the isolation of GAGs in biological samples were applied to analyze various sulfated chondroitin sulfate- and hyaluronan-derived disaccharides using fluorophore-assisted carbohydrate electrophoresis (FACE. Applications to biologic samples of clinical importance include blood serum, lens capsule tissue and urine. The sample preparation protocol followed by FACE analysis allows quantification with an optimal linearity over the concentration range 1.0–220.0 µg/mL, affording a limit of quantitation of 50 ng of disaccharides. Validation of FACE results was performed by capillary electrophoresis and high performance liquid chromatography techniques.

Exploring the importance of different items as reasons for leaving emergency medical services between fully compensated, partially compensated, and non-compensated/volunteer samples.

Science.gov (United States)

Blau, Gary; Chapman, Susan; Gibson, Gregory; Bentley, Melissa A

2011-01-01

The purpose of our study was to investigate the importance of different items as reasons for leaving the Emergency Medical Service (EMS) profession. An exit survey was returned by three distinct EMS samples: 127 full compensated, 45 partially compensated and 72 non-compensated/volunteer respondents, who rated the importance of 17 different items for affecting their decision to leave EMS. Unfortunately, there were a high percentage of "not applicable" responses for 10 items. We focused on those seven items that had a majority of useable responses across the three samples. Results showed that the desire for better pay and benefits was a more important reason for leaving EMS for the partially compensated versus fully compensated respondents. Perceived lack of advancement opportunity was a more important reason for leaving for the partially compensated and volunteer groups versus the fully compensated group. Study limitations are discussed and suggestions for future research offered.

The Importance of Contamination Knowledge in Curation - Insights into Mars Sample Return

Science.gov (United States)

Harrington, A. D.; Calaway, M. J.; Regberg, A. B.; Mitchell, J. L.; Fries, M. D.; Zeigler, R. A.; McCubbin, F. M.

2018-01-01

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (JSC), in Houston, TX (henceforth Curation Office) manages the curation of extraterrestrial samples returned by NASA missions and shared collections from international partners, preserving their integrity for future scientific study while providing the samples to the international community in a fair and unbiased way. The Curation Office also curates flight and non-flight reference materials and other materials from spacecraft assembly (e.g., lubricants, paints and gases) of sample return missions that would have the potential to cross-contaminate a present or future NASA astromaterials collection.

A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models

International Nuclear Information System (INIS)

Echard, B.; Gayton, N.; Lemaire, M.; Relun, N.

2013-01-01

Applying reliability methods to a complex structure is often delicate for two main reasons. First, such a structure is fortunately designed with codified rules leading to a large safety margin which means that failure is a small probability event. Such a probability level is difficult to assess efficiently. Second, the structure mechanical behaviour is modelled numerically in an attempt to reproduce the real response and numerical model tends to be more and more time-demanding as its complexity is increased to improve accuracy and to consider particular mechanical behaviour. As a consequence, performing a large number of model computations cannot be considered in order to assess the failure probability. To overcome these issues, this paper proposes an original and easily implementable method called AK-IS for active learning and Kriging-based Importance Sampling. This new method is based on the AK-MCS algorithm previously published by Echard et al. [AK-MCS: an active learning reliability method combining Kriging and Monte Carlo simulation. Structural Safety 2011;33(2):145–54]. It associates the Kriging metamodel and its advantageous stochastic property with the Importance Sampling method to assess small failure probabilities. It enables the correction or validation of the FORM approximation with only a very few mechanical model computations. The efficiency of the method is, first, proved on two academic applications. It is then conducted for assessing the reliability of a challenging aerospace case study submitted to fatigue.

Assessment of the effect of population and diary sampling methods on estimation of school-age children exposure to fine particles.

Science.gov (United States)

Che, W W; Frey, H Christopher; Lau, Alexis K H

2014-12-01

Population and diary sampling methods are employed in exposure models to sample simulated individuals and their daily activity on each simulation day. Different sampling methods may lead to variations in estimated human exposure. In this study, two population sampling methods (stratified-random and random-random) and three diary sampling methods (random resampling, diversity and autocorrelation, and Markov-chain cluster [MCC]) are evaluated. Their impacts on estimated children's exposure to ambient fine particulate matter (PM2.5 ) are quantified via case studies for children in Wake County, NC for July 2002. The estimated mean daily average exposure is 12.9 μg/m(3) for simulated children using the stratified population sampling method, and 12.2 μg/m(3) using the random sampling method. These minor differences are caused by the random sampling among ages within census tracts. Among the three diary sampling methods, there are differences in the estimated number of individuals with multiple days of exposures exceeding a benchmark of concern of 25 μg/m(3) due to differences in how multiday longitudinal diaries are estimated. The MCC method is relatively more conservative. In case studies evaluated here, the MCC method led to 10% higher estimation of the number of individuals with repeated exposures exceeding the benchmark. The comparisons help to identify and contrast the capabilities of each method and to offer insight regarding implications of method choice. Exposure simulation results are robust to the two population sampling methods evaluated, and are sensitive to the choice of method for simulating longitudinal diaries, particularly when analyzing results for specific microenvironments or for exposures exceeding a benchmark of concern. © 2014 Society for Risk Analysis.

Sequential determination of important ecotoxic radionuclides in nuclear waste samples

International Nuclear Information System (INIS)

Bilohuscin, J.

2016-01-01

In the dissertation thesis we focused on the development and optimization of a sequential determination method for radionuclides 93 Zr, 94 Nb, 99 Tc and 126 Sn, employing extraction chromatography sorbents TEVA (R) Resin and Anion Exchange Resin, supplied by Eichrom Industries. Prior to the attestation of sequential separation of these proposed radionuclides from radioactive waste samples, a unique sequential procedure of 90 Sr, 239 Pu, 241 Am separation from urine matrices was tried, using molecular recognition sorbents of AnaLig (R) series and extraction chromatography sorbent DGA (R) Resin. On these experiments, four various sorbents were continually used for separation, including PreFilter Resin sorbent, which removes interfering organic materials present in raw urine. After the acquisition of positive results of this sequential procedure followed experiments with a 126 Sn separation using TEVA (R) Resin and Anion Exchange Resin sorbents. Radiochemical recoveries obtained from samples of radioactive evaporate concentrates and sludge showed high efficiency of the separation, while values of 126 Sn were under the minimum detectable activities MDA. Activity of 126 Sn was determined after ingrowth of daughter nuclide 126m Sb on HPGe gamma detector, with minimal contamination of gamma interfering radionuclides with decontamination factors (D f ) higher then 1400 for 60 Co and 47000 for 137 Cs. Based on the acquired experiments and results of these separation procedures, a complex method of sequential separation of 93 Zr, 94 Nb, 99 Tc and 126 Sn was proposed, which included optimization steps similar to those used in previous parts of the dissertation work. Application of the sequential separation method for sorbents TEVA (R) Resin and Anion Exchange Resin on real samples of radioactive wastes provided satisfactory results and an economical, time sparing, efficient method. (author)

The importance and realization of values in relation to the subjective emotional well-being in the Slovenian and British sample

Directory of Open Access Journals (Sweden)

Jana Strniša

2007-07-01

Full Text Available In the study we examined the relationship between the importance and realization of values and subjective emotional well being of Slovenian and British subjects. The overall results were in concordance with telic and hedonistic theory of subjective emotional well being within both samples. Also the correlations between subjective emotional well being and fulfilled value orientation were in both samples substantially higher than the correlation between subjective emotional well being and value orientation itself. The finding of profound similarities in the relation between subjective emotional well being and the realization of general value orientation in Slovenian and British sample is interesting and deserves special attention and further research. The fulfillment of hedonic or dionisic values, respectively, was found to be the strongest predictor of subjective emotional well being of Slovenian and British subjects.

The effect of sampling rate and anti-aliasing filters on high-frequency response spectra

Science.gov (United States)

Boore, David M.; Goulet, Christine

2013-01-01

The most commonly used intensity measure in ground-motion prediction equations is the pseudo-absolute response spectral acceleration (PSA), for response periods from 0.01 to 10 s (or frequencies from 0.1 to 100 Hz). PSAs are often derived from recorded ground motions, and these motions are usually filtered to remove high and low frequencies before the PSAs are computed. In this article we are only concerned with the removal of high frequencies. In modern digital recordings, this filtering corresponds at least to an anti-aliasing filter applied before conversion to digital values. Additional high-cut filtering is sometimes applied both to digital and to analog records to reduce high-frequency noise. Potential errors on the short-period (high-frequency) response spectral values are expected if the true ground motion has significant energy at frequencies above that of the anti-aliasing filter. This is especially important for areas where the instrumental sample rate and the associated anti-aliasing filter corner frequency (above which significant energy in the time series is removed) are low relative to the frequencies contained in the true ground motions. A ground-motion simulation study was conducted to investigate these effects and to develop guidance for defining the usable bandwidth for high-frequency PSA. The primary conclusion is that if the ratio of the maximum Fourier acceleration spectrum (FAS) to the FAS at a frequency fsaa corresponding to the start of the anti-aliasing filter is more than about 10, then PSA for frequencies above fsaa should be little affected by the recording process, because the ground-motion frequencies that control the response spectra will be less than fsaa . A second topic of this article concerns the resampling of the digital acceleration time series to a higher sample rate often used in the computation of short-period PSA. We confirm previous findings that sinc-function interpolation is preferred to the standard practice of using

Efficient estimation of three-dimensional covariance and its application in the analysis of heterogeneous samples in cryo-electron microscopy.

Science.gov (United States)

Liao, Hstau Y; Hashem, Yaser; Frank, Joachim

2015-06-02

Single-particle cryogenic electron microscopy (cryo-EM) is a powerful tool for the study of macromolecular structures at high resolution. Classification allows multiple structural states to be extracted and reconstructed from the same sample. One classification approach is via the covariance matrix, which captures the correlation between every pair of voxels. Earlier approaches employ computing-intensive resampling and estimate only the eigenvectors of the matrix, which are then used in a separate fast classification step. We propose an iterative scheme to explicitly estimate the covariance matrix in its entirety. In our approach, the flexibility in choosing the solution domain allows us to examine a part of the molecule in greater detail. Three-dimensional covariance maps obtained in this way from experimental data (cryo-EM images of the eukaryotic pre-initiation complex) prove to be in excellent agreement with conclusions derived by using traditional approaches, revealing in addition the interdependencies of ligand bindings and structural changes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visualization of big SPH simulations via compressed octree grids

KAUST Repository

Reichl, Florian

2013-10-01

Interactive and high-quality visualization of spatially continuous 3D fields represented by scattered distributions of billions of particles is challenging. One common approach is to resample the quantities carried by the particles to a regular grid and to render the grid via volume ray-casting. In large-scale applications such as astrophysics, however, the required grid resolution can easily exceed 10K samples per spatial dimension, letting resampling approaches appear unfeasible. In this paper we demonstrate that even in these extreme cases such approaches perform surprisingly well, both in terms of memory requirement and rendering performance. We resample the particle data to a multiresolution multiblock grid, where the resolution of the blocks is dictated by the particle distribution. From this structure we build an octree grid, and we then compress each block in the hierarchy at no visual loss using wavelet-based compression. Since decompression can be performed on the GPU, it can be integrated effectively into GPU-based out-of-core volume ray-casting. We compare our approach to the perspective grid approach which resamples at run-time into a view-aligned grid. We demonstrate considerably faster rendering times at high quality, at only a moderate memory increase compared to the raw particle set. © 2013 IEEE.

Automatic bearing fault diagnosis of permanent magnet synchronous generators in wind turbines subjected to noise interference

Science.gov (United States)

Guo, Jun; Lu, Siliang; Zhai, Chao; He, Qingbo

2018-02-01

An automatic bearing fault diagnosis method is proposed for permanent magnet synchronous generators (PMSGs), which are widely installed in wind turbines subjected to low rotating speeds, speed fluctuations, and electrical device noise interferences. The mechanical rotating angle curve is first extracted from the phase current of a PMSG by sequentially applying a series of algorithms. The synchronous sampled vibration signal of the fault bearing is then resampled in the angular domain according to the obtained rotating phase information. Considering that the resampled vibration signal is still overwhelmed by heavy background noise, an adaptive stochastic resonance filter is applied to the resampled signal to enhance the fault indicator and facilitate bearing fault identification. Two types of fault bearings with different fault sizes in a PMSG test rig are subjected to experiments to test the effectiveness of the proposed method. The proposed method is fully automated and thus shows potential for convenient, highly efficient and in situ bearing fault diagnosis for wind turbines subjected to harsh environments.

Groundwater quality data in 15 GAMA study units: results from the 2006–10 Initial sampling and the 2009–13 resampling of wells, California GAMA Priority Basin Project

Science.gov (United States)

Kent, Robert

2015-08-31

The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). From May 2004 to March 2012, the GAMA-PBP collected samples from more than 2,300 wells in 35 study units across the State. Selected wells in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. This triennial (every 3 years) trend sampling of GAMA-PBP study units concluded in December 2013. Fifteen of the study units, initially sampled between January 2006 and June 2010 and sampled a second time between April 2009 and April 2013 to assess temporal trends, are the subject of this report.

Interpretation of stable isotope, denitrification, and groundwater age data for samples collected from Sandia National Laboratories /New Mexico (SNL/NM) Burn Site Groundwater Area of Concern

Energy Technology Data Exchange (ETDEWEB)

Madrid, V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Singleton, M. J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Visser, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Esser, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2016-06-02

This report combines and summarizes results for two groundwater-sampling events (October 2012 and October/November 2015) from the Sandia National Laboratories/New Mexico (SNL/NM) Burn Site Groundwater (BSG) Area of Concern (AOC) located in the Lurance Canyon Arroyo southeast of Albuquerque, NM in the Manzanita Mountains. The first phase of groundwater sampling occurred in October 2012 including samples from 19 wells at three separate sites that were analyzed by the Environmental Radiochemistry Laboratory at Lawrence Livermore National Laboratory as part of a nitrate Monitored Natural Attenuation (MNA) evaluation. The three sites (BSG, Technical Area-V, and Tijeras Arroyo) are shown on the regional hydrogeologic map and described in the Sandia Annual Groundwater Monitoring Report. The first phase of groundwater sampling included six monitoring wells at the Burn Site, eight monitoring wells at Technical Area-V, and five monitoring wells at Tijeras Arroyo. Each groundwater sample was analyzed using the two specialized analytical methods, age-dating and denitrification suites. In September 2015, a second phase of groundwater sampling took place at the Burn Site including 10 wells sampled and analyzed by the same two analytical suites. Five of the six wells sampled in 2012 were resampled in 2015. This report summarizes results from two sampling events in order to evaluate evidence for in situ denitrification, the average age of the groundwater, and the extent of recent recharge of the bedrock fracture system beneath the BSG AOC.

Interpretation of stable isotope, denitrification, and groundwater age data for samples collected from Sandia National Laboratories /New Mexico (SNL/NM) Burn Site Groundwater Area of Concern

International Nuclear Information System (INIS)

Madrid, V.; Singleton, M. J.; Visser, A.; Esser, B.

2016-01-01

This report combines and summarizes results for two groundwater-sampling events (October 2012 and October/November 2015) from the Sandia National Laboratories/New Mexico (SNL/NM) Burn Site Groundwater (BSG) Area of Concern (AOC) located in the Lurance Canyon Arroyo southeast of Albuquerque, NM in the Manzanita Mountains. The first phase of groundwater sampling occurred in October 2012 including samples from 19 wells at three separate sites that were analyzed by the Environmental Radiochemistry Laboratory at Lawrence Livermore National Laboratory as part of a nitrate Monitored Natural Attenuation (MNA) evaluation. The three sites (BSG, Technical Area-V, and Tijeras Arroyo) are shown on the regional hydrogeologic map and described in the Sandia Annual Groundwater Monitoring Report. The first phase of groundwater sampling included six monitoring wells at the Burn Site, eight monitoring wells at Technical Area-V, and five monitoring wells at Tijeras Arroyo. Each groundwater sample was analyzed using the two specialized analytical methods, age-dating and denitrification suites. In September 2015, a second phase of groundwater sampling took place at the Burn Site including 10 wells sampled and analyzed by the same two analytical suites. Five of the six wells sampled in 2012 were resampled in 2015. This report summarizes results from two sampling events in order to evaluate evidence for in situ denitrification, the average age of the groundwater, and the extent of recent recharge of the bedrock fracture system beneath the BSG AOC.

Measures of precision for dissimilarity-based multivariate analysis of ecological communities.

Science.gov (United States)

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

A methodological critique on using temperature-conditioned resampling for climate projections as in the paper of Gerstengarbe et al. (2013) winter storm- and summer thunderstorm-related loss events in Theoretical and Applied Climatology (TAC)

Science.gov (United States)

Wechsung, Frank; Wechsung, Maximilian

2016-11-01

The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale.

Importance of Sample Preparation for Molecular Diagnosis of Lyme Borreliosis from Urine

OpenAIRE

Bergmann, A. R.; Schmidt, B. L.; Derler, A.-M.; Aberer, E.

2002-01-01

Urine PCR has been used for the diagnosis of Borrelia burgdorferi infection in recent years but has been abandoned because of its low sensitivity and the irreproducibility of the results. Our study aimed to analyze technical details related to sample preparation and detection methods. Crucial for a successful urine PCR were (i) avoidance of the first morning urine sample; (ii) centrifugation at 36,000 × g; and (iii) the extraction method, with only DNAzol of the seven different extraction met...

Inferring the demographic history from DNA sequences: An importance sampling approach based on non-homogeneous processes.

Science.gov (United States)

Ait Kaci Azzou, S; Larribe, F; Froda, S

2016-10-01

In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.

Nonlinear Statistical Signal Processing: A Particle Filtering Approach

International Nuclear Information System (INIS)

Candy, J.

2007-01-01

A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations

HOW TO ESTIMATE THE AMOUNT OF IMPORTANT CHARACTERISTICS MISSING IN A CONSUMERS SAMPLE BY USING BAYESIAN ESTIMATORS

Directory of Open Access Journals (Sweden)

Sueli A. Mingoti

2001-06-01

Full Text Available Consumers surveys are conducted very often by many companies with the main objective of obtaining information about the opinions the consumers have about a specific prototype, product or service. In many situations the goal is to identify the characteristics that are considered important by the consumers when taking the decision of buying or using the products or services. When the survey is performed some characteristics that are present in the consumers population might not be reported by those consumers in the observed sample. Therefore, some important characteristics of the product according to the consumers opinions could be missing in the observed sample. The main objective of this paper is to show how the amount of characteristics missing in the observed sample could be easily estimated by using some Bayesian estimators proposed by Mingoti & Meeden (1992 and Mingoti (1999. An example of application related to an automobile survey is presented.Pesquisas de mercado são conduzidas freqüentemente com o propósito de obter informações sobre a opinião dos consumidores em relação a produtos já existentes no mercado, protótipos, ou determinados tipos de serviços prestados pela empresa. Em muitas situações deseja-se identificar as características que são consideradas importantes pelos consumidores no que se refere à tomada de decisão de compra do produto ou de opção pelo serviço prestado pela empresa. Como as pesquisas são feitas com amostras de consumidores do mercado potencial, algumas características consideradas importantes pela população podem não estar representadas nas amostras. O objetivo deste artigo é mostrar como a quantidade de características presentes na população e que não estão representadas nas amostras, pode ser facilmente estimada através de estimadores Bayesianos propostos por Mingoti & Meeden (1992 e Mingoti (1999. Como ilustração apresentamos um exemplo de uma pesquisa de mercado sobre um

Sampling

CERN Document Server

Thompson, Steven K

2012-01-01

Praise for the Second Edition "This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book." —Technometrics "Well-written . . . an excellent book on an important subject. Highly recommended." —Choice "An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treat

Importance Sampling Based Decision Trees for Security Assessment and the Corresponding Preventive Control Schemes: the Danish Case Study

DEFF Research Database (Denmark)

Liu, Leo; Rather, Zakir Hussain; Chen, Zhe

2013-01-01

Decision Trees (DT) based security assessment helps Power System Operators (PSO) by providing them with the most significant system attributes and guiding them in implementing the corresponding emergency control actions to prevent system insecurity and blackouts. DT is obtained offline from time...... and adopts a methodology of importance sampling to maximize the information contained in the database so as to increase the accuracy of DT. Further, this paper also studies the effectiveness of DT by implementing its corresponding preventive control schemes. These approaches are tested on the detailed model...

40 CFR 80.1348 - What gasoline sample retention requirements apply to refiners and importers?

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false What gasoline sample retention... PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Gasoline Benzene Sampling, Testing and Retention Requirements § 80.1348 What gasoline sample retention requirements...

Effect of the Target Motion Sampling Temperature Treatment Method on the Statistics and Performance

Science.gov (United States)

Viitanen, Tuomas; Leppänen, Jaakko

2014-06-01

Target Motion Sampling (TMS) is a stochastic on-the-fly temperature treatment technique that is being developed as a part of the Monte Carlo reactor physics code Serpent. The method provides for modeling of arbitrary temperatures in continuous-energy Monte Carlo tracking routines with only one set of cross sections stored in the computer memory. Previously, only the performance of the TMS method in terms of CPU time per transported neutron has been discussed. Since the effective cross sections are not calculated at any point of a transport simulation with TMS, reaction rate estimators must be scored using sampled cross sections, which is expected to increase the variances and, consequently, to decrease the figures-of-merit. This paper examines the effects of the TMS on the statistics and performance in practical calculations involving reaction rate estimation with collision estimators. Against all expectations it turned out that the usage of sampled response values has no practical effect on the performance of reaction rate estimators when using TMS with elevated basis cross section temperatures (EBT), i.e. the usual way. With 0 Kelvin cross sections a significant increase in the variances of capture rate estimators was observed right below the energy region of unresolved resonances, but at these energies the figures-of-merit could be increased using a simple resampling technique to decrease the variances of the responses. It was, however, noticed that the usage of the TMS method increases the statistical deviances of all estimators, including the flux estimator, by tens of percents in the vicinity of very strong resonances. This effect is actually not related to the usage of sampled responses, but is instead an inherent property of the TMS tracking method and concerns both EBT and 0 K calculations.

Projected large flood event sensitivity to projection selection and temporal downscaling methodology

Energy Technology Data Exchange (ETDEWEB)

Raff, D. [U.S. Dept. of the Interior, Bureau of Reclamation, Denver, Colorado (United States)

2008-07-01

Large flood events, that influence regulatory guidelines as well as safety of dams decisions, are likely to be affected by climate change. This talk will evaluate the use of climate projections downscaled and run through a rainfall - runoff model and its influence on large flood events. The climate spatial downscaling is performed statistically and a re-sampling and scaling methodology is used to temporally downscale from monthly to daily signals. The signals are run through a National Weather Service operational rainfall-runoff model to produce 6-hour flows. The flows will be evaluated for changes in large events at look-ahead horizons from 2011 - 2040, 2041 - 2070, and 2071 - 2099. The sensitivity of results will be evaluated with respect to projection selection criteria and re-sampling and scaling criteria for the Boise River in Idaho near Lucky Peak Dam. (author)

Projected large flood event sensitivity to projection selection and temporal downscaling methodology

International Nuclear Information System (INIS)

Raff, D.

2008-01-01

Large flood events, that influence regulatory guidelines as well as safety of dams decisions, are likely to be affected by climate change. This talk will evaluate the use of climate projections downscaled and run through a rainfall - runoff model and its influence on large flood events. The climate spatial downscaling is performed statistically and a re-sampling and scaling methodology is used to temporally downscale from monthly to daily signals. The signals are run through a National Weather Service operational rainfall-runoff model to produce 6-hour flows. The flows will be evaluated for changes in large events at look-ahead horizons from 2011 - 2040, 2041 - 2070, and 2071 - 2099. The sensitivity of results will be evaluated with respect to projection selection criteria and re-sampling and scaling criteria for the Boise River in Idaho near Lucky Peak Dam. (author)

High speed network sampling

OpenAIRE

Rindalsholt, Ole Arild

2005-01-01

Master i nettverks- og systemadministrasjon Classical Sampling methods play an important role in the current practice of Internet measurement. With today’s high speed networks, routers cannot manage to generate complete Netflow data for every packet. They have to perform restricted sampling. This thesis summarizes some of the most important sampling schemes and their applications before diving into an analysis on the effect of sampling Netflow records.

Importance sampling implemented in the code PRIZMA for deep penetration and detection problems in reactor physics

International Nuclear Information System (INIS)

Kandiev, Y.Z.; Zatsepin, O.V.

2013-01-01

At RFNC-VNIITF, the PRIZMA code which has been developed for more than 30 years, is used to model radiation transport by the Monte Carlo method. The code implements individual and coupled tracking of neutrons, photons, electrons, positrons and ions in one dimensional (1D), 2D or 3D geometry. Attendance estimators are used for tallying, i.e., the estimators whose scores are only nonzero from particles which cross a region or surface of interest. Importance sampling is used to make deep penetration and detection calculations more effective. However, its application to reactor analysis appeared peculiar and required further development. The paper reviews methods used for deep penetration and detection calculations by PRIZMA. It describes in what these calculations differ when applied to reactor analysis and how we compute approximated importance functions and parameters for biased distributions. Methods to control the statistical weight of particles are also discussed. A number of test and applied calculations which were done for the purpose of verification are provided. They are shown to agree either with asymptotic solutions if exist, or with results of analog calculations or predictions by other codes. The applied calculations include the estimation of ex-core detector response from neutron sources arranged in the core, and the estimation of in-core detector response. (authors)

Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

Science.gov (United States)

Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

2008-12-01

Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral

Building test data from real outbreaks for evaluating detection algorithms.

Science.gov (United States)

Texier, Gaetan; Jackson, Michael L; Siwe, Leonel; Meynard, Jean-Baptiste; Deparis, Xavier; Chaudet, Herve

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method-ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals.

Building test data from real outbreaks for evaluating detection algorithms.

Directory of Open Access Journals (Sweden)

Gaetan Texier

Full Text Available Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method-ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler. We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1 resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak

Grain Size and Parameter Recovery with TIMSS and the General Diagnostic Model

Science.gov (United States)

Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F.

2016-01-01

The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…

Comparison of concentrations of drugs between blood samples with and without fluoride additive-important findings for Δ9-tetrahydrocannabinol and amphetamine.

Science.gov (United States)

Wiedfeld, Christopher; Krueger, Julia; Skopp, Gisela; Musshoff, Frank

2018-02-17

Fluoride is a common stabilizing agent in forensic toxicology to avoid the frequent problem of degradation of drugs in blood samples especially described for cocaine. In cases only samples with addition of fluoride are available, it is a crucial question if also concentrations of common drugs other than cocaine (amphetamines, opiates and cannabinoids) are affected by fluoride. So far, there are only rare literature data available on discrepant results especially for Δ 9 -tetrahydrocannabinol (THC). In this study, comparative analysis of positive tested paired routine plasma/serum samples (n = 375), collected at the same time point (one device with and one without fluoride), was carried out with special focus on cannabinoids. Samples were measured with validated routine liquid chromatography-tandem mass spectrometry methods for THC, 11-hydroxy-THC (THC-OH), 11-nor-9-carboxy-THC (THC-COOH), cocaine, benzoylecgonine, ecgonine methyl ester, morphine, codeine, amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine, 3,4-methylenedioxyamphetamine, and 3,4-methylenedioxyethylamphetamine, and results were statistically evaluated. Beside the expected stabilization effect on cocaine and the consequently reduced concentration of ecgonine methyl ester in fluoride samples, benzoylecgonine was elevated compared to respective samples without fluoride. Most importantly, new findings were significantly reduced mean concentrations of THC (- 17%), THC-OH (- 17%), and THC-COOH (- 22%) in fluoride samples. Mean amphetamine concentration was significantly higher in samples with the additive (+ 6%). For the other amphetamine type of drugs as well as for morphine and codeine, no significant differences could be seen. Whenever specified thresholds have been set, such as in most European countries, the use of different blood sample systems may result in a motorist being differently charged or prosecuted. The findings will support forensic toxicologists at the

On the Importance of Accounting for Competing Risks in Pediatric Brain Cancer: II. Regression Modeling and Sample Size

International Nuclear Information System (INIS)

Tai, Bee-Choo; Grundy, Richard; Machin, David

2011-01-01

Purpose: To accurately model the cumulative need for radiotherapy in trials designed to delay or avoid irradiation among children with malignant brain tumor, it is crucial to account for competing events and evaluate how each contributes to the timing of irradiation. An appropriate choice of statistical model is also important for adequate determination of sample size. Methods and Materials: We describe the statistical modeling of competing events (A, radiotherapy after progression; B, no radiotherapy after progression; and C, elective radiotherapy) using proportional cause-specific and subdistribution hazard functions. The procedures of sample size estimation based on each method are outlined. These are illustrated by use of data comparing children with ependymoma and other malignant brain tumors. The results from these two approaches are compared. Results: The cause-specific hazard analysis showed a reduction in hazards among infants with ependymoma for all event types, including Event A (adjusted cause-specific hazard ratio, 0.76; 95% confidence interval, 0.45-1.28). Conversely, the subdistribution hazard analysis suggested an increase in hazard for Event A (adjusted subdistribution hazard ratio, 1.35; 95% confidence interval, 0.80-2.30), but the reduction in hazards for Events B and C remained. Analysis based on subdistribution hazard requires a larger sample size than the cause-specific hazard approach. Conclusions: Notable differences in effect estimates and anticipated sample size were observed between methods when the main event showed a beneficial effect whereas the competing events showed an adverse effect on the cumulative incidence. The subdistribution hazard is the most appropriate for modeling treatment when its effects on both the main and competing events are of interest.

Presence and Persistence of Viable, Clinically Relevant Legionella pneumophila Bacteria in Garden Soil in the Netherlands

Science.gov (United States)

van Heijnsbergen, E.; van Deursen, A.; Bouwknegt, M.; Bruin, J. P.; Schalk, J. A. C.

2016-01-01

ABSTRACT Garden soils were investigated as reservoirs and potential sources of pathogenic Legionella bacteria. Legionella bacteria were detected in 22 of 177 garden soil samples (12%) by amoebal coculture. Of these 22 Legionella-positive soil samples, seven contained Legionella pneumophila. Several other species were found, including the pathogenic Legionella longbeachae (4 gardens) and Legionella sainthelensi (9 gardens). The L. pneumophila isolates comprised 15 different sequence types (STs), and eight of these STs were previously isolated from patients according to the European Working Group for Legionella Infections (EWGLI) database. Six gardens that were found to be positive for L. pneumophila were resampled after several months, and in three gardens, L. pneumophila was again isolated. One of these gardens was resampled four times throughout the year and was found to be positive for L. pneumophila on all occasions. IMPORTANCE Tracking the source of infection for sporadic cases of Legionnaires' disease (LD) has proven to be hard. L. pneumophila ST47, the sequence type that is most frequently isolated from LD patients in the Netherlands, is rarely found in potential environmental sources. As L. pneumophila ST47 was previously isolated from a garden soil sample during an outbreak investigation, garden soils were investigated as reservoirs and potential sources of pathogenic Legionella bacteria. The detection of viable, clinically relevant Legionella strains indicates that garden soil is a potential source of Legionella bacteria, and future research should assess the public health implication of the presence of L. pneumophila in garden soil. PMID:27316958

The potential of Sentinel-2 spectral configuration to assess rangeland quality

CSIR Research Space (South Africa)

Ramoelo, Abel

2015-08-01

Full Text Available was measured using the analytical spectral device (ASD) in concert with leaf sample collections for leaf N chemical analysis. ASD reflectance data were resampled to the spectral bands of Sentinel-2 using published spectral response functions. Random forest (RF...

Using the Direct Sampling Multiple-Point Geostatistical Method for Filling Gaps in Landsat 7 ETM+ SLC-off Imagery

KAUST Repository

Yin, Gaohong

2016-05-01

Since the failure of the Scan Line Corrector (SLC) instrument on Landsat 7, observable gaps occur in the acquired Landsat 7 imagery, impacting the spatial continuity of observed imagery. Due to the highly geometric and radiometric accuracy provided by Landsat 7, a number of approaches have been proposed to fill the gaps. However, all proposed approaches have evident constraints for universal application. The main issues in gap-filling are an inability to describe the continuity features such as meandering streams or roads, or maintaining the shape of small objects when filling gaps in heterogeneous areas. The aim of the study is to validate the feasibility of using the Direct Sampling multiple-point geostatistical method, which has been shown to reconstruct complicated geological structures satisfactorily, to fill Landsat 7 gaps. The Direct Sampling method uses a conditional stochastic resampling of known locations within a target image to fill gaps and can generate multiple reconstructions for one simulation case. The Direct Sampling method was examined across a range of land cover types including deserts, sparse rural areas, dense farmlands, urban areas, braided rivers and coastal areas to demonstrate its capacity to recover gaps accurately for various land cover types. The prediction accuracy of the Direct Sampling method was also compared with other gap-filling approaches, which have been previously demonstrated to offer satisfactory results, under both homogeneous area and heterogeneous area situations. Studies have shown that the Direct Sampling method provides sufficiently accurate prediction results for a variety of land cover types from homogeneous areas to heterogeneous land cover types. Likewise, it exhibits superior performances when used to fill gaps in heterogeneous land cover types without input image or with an input image that is temporally far from the target image in comparison with other gap-filling approaches.

Reliability analysis of a gravity-based foundation for wind turbines

DEFF Research Database (Denmark)

Vahdatirad, Mohammad Javad; Griffiths, D. V.; Andersen, Lars Vabbersgaard

2014-01-01

its bearing capacity, is used to calibrate a code-based design procedure. A probabilistic finite element model is developed to analyze the bearing capacity of a surface footing on soil with spatially variable undrained strength. Monte Carlo simulation is combined with a re-sampling simulation...

Bias-Corrected Estimation of Noncentrality Parameters of Covariance Structure Models

Science.gov (United States)

Raykov, Tenko

2005-01-01

A bias-corrected estimator of noncentrality parameters of covariance structure models is discussed. The approach represents an application of the bootstrap methodology for purposes of bias correction, and utilizes the relation between average of resample conventional noncentrality parameter estimates and their sample counterpart. The…

Housing price forecastability: A factor analysis

DEFF Research Database (Denmark)

Bork, Lasse; Møller, Stig Vinther

of the model stays high at longer horizons. The estimated factors are strongly statistically signi…cant according to a bootstrap resampling method which takes into account that the factors are estimated regressors. The simple three-factor model also contains substantial out-of-sample predictive power...

A Big Data Approach for Situation-Aware estimation, correction and prediction of aerosol effects, based on MODIS Joint Atmosphere product (collection 6) time series data

Science.gov (United States)

Singh, A. K.; Toshniwal, D.

2017-12-01

The MODIS Joint Atmosphere product, MODATML2 and MYDATML2 L2/3 provided by LAADS DAAC (Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center) re-sampled from medium resolution MODIS Terra /Aqua Satellites data at 5km scale, contains Cloud Reflectance, Cloud Top Temperature, Water Vapor, Aerosol Optical Depth/Thickness, Humidity data. These re-sampled data, when used for deriving climatic effects of aerosols (particularly in case of cooling effect) still exposes limitations in presence of uncertainty measures in atmospheric artifacts such as aerosol, cloud, cirrus cloud etc. The effect of uncertainty measures in these artifacts imposes an important challenge for estimation of aerosol effects, adequately affecting precise regional weather modeling and predictions: Forecasting and recommendation applications developed largely depend on these short-term local conditions (e.g. City/Locality based recommendations to citizens/farmers based on local weather models). Our approach inculcates artificial intelligence technique for representing heterogeneous data(satellite data along with air quality data from local weather stations (i.e. in situ data)) to learn, correct and predict aerosol effects in the presence of cloud and other atmospheric artifacts, defusing Spatio-temporal correlations and regressions. The Big Data process pipeline consisting correlation and regression techniques developed on Apache Spark platform can easily scale for large data sets including many tiles (scenes) and over widened time-scale. Keywords: Climatic Effects of Aerosols, Situation-Aware, Big Data, Apache Spark, MODIS Terra /Aqua, Time Series

PCR diagnosis and characterization of Leishmania in local and imported clinical samples

NARCIS (Netherlands)

Schönian, Gabriele; Nasereddin, Abedelmajeed; Dinse, Nicole; Schweynoch, Carola; Schallig, Henk D. F. H.; Presber, Wolfgang; Jaffe, Charles L.

2003-01-01

Leishmaniasis diagnosis in regions where multiple species exist should identify each species directly in the clinical sample without parasite culturing. The sensitivity of two PCR approaches which amplify part of the ssu rRNA gene and the ribosomal internal transcribed spacer (ITS), respectively,

The Local Fractional Bootstrap

DEFF Research Database (Denmark)

Bennedsen, Mikkel; Hounyo, Ulrich; Lunde, Asger

We introduce a bootstrap procedure for high-frequency statistics of Brownian semistationary processes. More specifically, we focus on a hypothesis test on the roughness of sample paths of Brownian semistationary processes, which uses an estimator based on a ratio of realized power variations. Our...... new resampling method, the local fractional bootstrap, relies on simulating an auxiliary fractional Brownian motion that mimics the fine properties of high frequency differences of the Brownian semistationary process under the null hypothesis. We prove the first order validity of the bootstrap method...... and in simulations we observe that the bootstrap-based hypothesis test provides considerable finite-sample improvements over an existing test that is based on a central limit theorem. This is important when studying the roughness properties of time series data; we illustrate this by applying the bootstrap method...

The Importance of Sample Return in Establishing Chemical Evidence for Life on Mars or Other Solar System Bodies

Science.gov (United States)

Glavin, D. P.; Conrad, P.; Dworkin, J. P.; Eigenbrode, J.; Mahaffy, P. R.

2011-01-01

The search for evidence of life on Mars and elsewhere will continue to be one of the primary goals of NASA s robotic exploration program over the next decade. NASA and ESA are currently planning a series of robotic missions to Mars with the goal of understanding its climate, resources, and potential for harboring past or present life. One key goal will be the search for chemical biomarkers including complex organic compounds important in life on Earth. These include amino acids, the monomer building blocks of proteins and enzymes, nucleobases and sugars which form the backbone of DNA and RNA, and lipids, the structural components of cell membranes. Many of these organic compounds can also be formed abiotically as demonstrated by their prevalence in carbonaceous meteorites [1], though, their molecular characteristics may distinguish a biological source [2]. It is possible that in situ instruments may reveal such characteristics, however, return of the right sample (i.e. one with biosignatures or having a high probability of biosignatures) to Earth would allow for more intensive laboratory studies using a broad array of powerful instrumentation for bulk characterization, molecular detection, isotopic and enantiomeric compositions, and spatially resolved chemistry that may be required for confirmation of extant or extinct Martian life. Here we will discuss the current analytical capabilities and strategies for the detection of organics on the Mars Science Laboratory (MSL) using the Sample Analysis at Mars (SAM) instrument suite and how sample return missions from Mars and other targets of astrobiological interest will help advance our understanding of chemical biosignatures in the solar system.

Can The Pore Scale Geometry Explain Soil Sample Scale Hydrodynamic Properties?

Directory of Open Access Journals (Sweden)

Sarah Smet

2018-04-01

Full Text Available For decades, the development of new visualization techniques has brought incredible insights into our understanding of how soil structure affects soil function. X-ray microtomography is a technique often used by soil scientists but challenges remain with the implementation of the procedure, including how well the samples represent the uniqueness of the pore network and structure and the systemic compromise between sample size and resolution. We, therefore, chose to study soil samples from two perspectives: a macroscopic scale with hydrodynamic characterization and a microscopic scale with structural characterization through the use of X-ray microtomography (X-ray μCT at a voxel size of 21.53 μm3 (resampled at 433 μm3. The objective of this paper is to unravel the relationships between macroscopic soil properties and microscopic soil structure. The 24 samples came from an agricultural field (Cutanic Luvisol and the macroscopic hydrodynamic properties were determined using laboratory measurements of the saturated hydraulic conductivity (Ks, air permeability (ka, and retention curves (SWRC. The X-ray μCT images were segmented using a global method and multiple microscopic measurements were calculated. We used Bayesian statistics to report the credible correlation coefficients and linear regressions models between macro- and microscopic measurements. Due to the small voxel size, we observed unprecedented relationships, such as positive correlations between log(Ks and a μCT global connectivity indicator, the fractal dimension of the μCT images or the μCT degree of anisotropy. The air permeability measured at a water matric potential of −70 kPa was correlated to the average coordination number and the X-ray μCT porosity, but was best explained by the average pore volume of the smallest pores. Continuous SWRC were better predicted near saturation when the pore-size distributions calculated on the X-ray μCT images were used as model input. We

Approximate median regression for complex survey data with skewed response.

Science.gov (United States)

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Preprocessing the Nintendo Wii Board Signal to Derive More Accurate Descriptors of Statokinesigrams.

Science.gov (United States)

Audiffren, Julien; Contal, Emile

2016-08-01

During the past few years, the Nintendo Wii Balance Board (WBB) has been used in postural control research as an affordable but less reliable replacement for laboratory grade force platforms. However, the WBB suffers some limitations, such as a lower accuracy and an inconsistent sampling rate. In this study, we focus on the latter, namely the non uniform acquisition frequency. We show that this problem, combined with the poor signal to noise ratio of the WBB, can drastically decrease the quality of the obtained information if not handled properly. We propose a new resampling method, Sliding Window Average with Relevance Interval Interpolation (SWARII), specifically designed with the WBB in mind, for which we provide an open source implementation. We compare it with several existing methods commonly used in postural control, both on synthetic and experimental data. The results show that some methods, such as linear and piecewise constant interpolations should definitely be avoided, particularly when the resulting signal is differentiated, which is necessary to estimate speed, an important feature in postural control. Other methods, such as averaging on sliding windows or SWARII, perform significantly better on synthetic dataset, and produce results more similar to the laboratory-grade AMTI force plate (AFP) during experiments. Those methods should be preferred when resampling data collected from a WBB.

Soil sampling

International Nuclear Information System (INIS)

Fortunati, G.U.; Banfi, C.; Pasturenzi, M.

1994-01-01

This study attempts to survey the problems associated with techniques and strategies of soil sampling. Keeping in mind the well defined objectives of a sampling campaign, the aim was to highlight the most important aspect of representativeness of samples as a function of the available resources. Particular emphasis was given to the techniques and particularly to a description of the many types of samplers which are in use. The procedures and techniques employed during the investigations following the Seveso accident are described. (orig.)

Adaptive Annealed Importance Sampling for Multimodal Posterior Exploration and Model Selection with Application to Extrasolar Planet Detection

Science.gov (United States)

Liu, Bin

2014-07-01

We describe an algorithm that can adaptively provide mixture summaries of multimodal posterior distributions. The parameter space of the involved posteriors ranges in size from a few dimensions to dozens of dimensions. This work was motivated by an astrophysical problem called extrasolar planet (exoplanet) detection, wherein the computation of stochastic integrals that are required for Bayesian model comparison is challenging. The difficulty comes from the highly nonlinear models that lead to multimodal posterior distributions. We resort to importance sampling (IS) to estimate the integrals, and thus translate the problem to be how to find a parametric approximation of the posterior. To capture the multimodal structure in the posterior, we initialize a mixture proposal distribution and then tailor its parameters elaborately to make it resemble the posterior to the greatest extent possible. We use the effective sample size (ESS) calculated based on the IS draws to measure the degree of approximation. The bigger the ESS is, the better the proposal resembles the posterior. A difficulty within this tailoring operation lies in the adjustment of the number of mixing components in the mixture proposal. Brute force methods just preset it as a large constant, which leads to an increase in the required computational resources. We provide an iterative delete/merge/add process, which works in tandem with an expectation-maximization step to tailor such a number online. The efficiency of our proposed method is tested via both simulation studies and real exoplanet data analysis.

Molecular Biological Characterization of Air Samples: A Survey of Four Strategically Important Regions

National Research Council Canada - National Science Library

Francesconi, Stephen

2003-01-01

.... In support of this requirement, the Joint Program Office for Biological Defense initiated an aggressive program incorporating the development of air-sampling and agent detecting devices, coined...

Microfabricated Devices for Sample Extraction, Concentrations, and Related Sample Processing Technologies

Energy Technology Data Exchange (ETDEWEB)

Chen, Gang; Lin, Yuehe

2006-12-01

This is an invited book chapter. As with other analytical techniques, sample pretreatments, sample extraction, sample introduction, and related techniques are of extreme importance for micro-electro-mechanical systems (MEMS). Bio-MEMS devices and systems start with a sampling step. The biological sample then usually undergoes some kinds of sample preparation steps before the actual analysis. These steps may involve extracting the target sample from its matrix, removing interferences from the sample, derivatizing the sample to detectable species, or performing a sample preconcentration step. The integration of the components for sample pretreatment into microfluidic devices represents one of the remaining the bottle-neck towards achieving true miniaturized total analysis systems (?TAS). This chapter provides a thorough state-of-art of the developments in this field to date.

An assessment of particle filtering methods and nudging for climate state reconstructions

NARCIS (Netherlands)

S. Dubinkina (Svetlana); H. Goosse

2013-01-01

htmlabstractUsing the climate model of intermediate complexity LOVECLIM in an idealized framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle

Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

KAUST Repository

Liu, Bo

2015-11-11

We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

Effect of the Target Motion Sampling temperature treatment method on the statistics and performance

International Nuclear Information System (INIS)

Viitanen, Tuomas; Leppänen, Jaakko

2015-01-01

Highlights: • Use of the Target Motion Sampling (TMS) method with collision estimators is studied. • The expected values of the estimators agree with NJOY-based reference. • In most practical cases also the variances of the estimators are unaffected by TMS. • Transport calculation slow-down due to TMS dominates the impact on figures-of-merit. - Abstract: Target Motion Sampling (TMS) is a stochastic on-the-fly temperature treatment technique that is being developed as a part of the Monte Carlo reactor physics code Serpent. The method provides for modeling of arbitrary temperatures in continuous-energy Monte Carlo tracking routines with only one set of cross sections stored in the computer memory. Previously, only the performance of the TMS method in terms of CPU time per transported neutron has been discussed. Since the effective cross sections are not calculated at any point of a transport simulation with TMS, reaction rate estimators must be scored using sampled cross sections, which is expected to increase the variances and, consequently, to decrease the figures-of-merit. This paper examines the effects of the TMS on the statistics and performance in practical calculations involving reaction rate estimation with collision estimators. Against all expectations it turned out that the usage of sampled response values has no practical effect on the performance of reaction rate estimators when using TMS with elevated basis cross section temperatures (EBT), i.e. the usual way. With 0 Kelvin cross sections a significant increase in the variances of capture rate estimators was observed right below the energy region of unresolved resonances, but at these energies the figures-of-merit could be increased using a simple resampling technique to decrease the variances of the responses. It was, however, noticed that the usage of the TMS method increases the statistical deviances of all estimators, including the flux estimator, by tens of percents in the vicinity of very

Sample size methodology

CERN Document Server

Desu, M M

2012-01-01

One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropria

Bootstrap Determination of the Co-Integration Rank in Heteroskedastic VAR Models

DEFF Research Database (Denmark)

Cavaliere, G.; Rahbek, Anders; Taylor, A.M.R.

2014-01-01

In a recent paper Cavaliere et al. (2012) develop bootstrap implementations of the (pseudo-) likelihood ratio (PLR) co-integration rank test and associated sequential rank determination procedure of Johansen (1996). The bootstrap samples are constructed using the restricted parameter estimates...... of the underlying vector autoregressive (VAR) model which obtain under the reduced rank null hypothesis. They propose methods based on an independent and individual distributed (i.i.d.) bootstrap resampling scheme and establish the validity of their proposed bootstrap procedures in the context of a co......-integrated VAR model with i.i.d. innovations. In this paper we investigate the properties of their bootstrap procedures, together with analogous procedures based on a wild bootstrap resampling scheme, when time-varying behavior is present in either the conditional or unconditional variance of the innovations. We...

Sample preparation

International Nuclear Information System (INIS)

Anon.

1992-01-01

Sample preparation prior to HPLC analysis is certainly one of the most important steps to consider in trace or ultratrace analysis. For many years scientists have tried to simplify the sample preparation process. It is rarely possible to inject a neat liquid sample or a sample where preparation may not be any more complex than dissolution of the sample in a given solvent. The last process alone can remove insoluble materials, which is especially helpful with the samples in complex matrices if other interactions do not affect extraction. Here, it is very likely a large number of components will not dissolve and are, therefore, eliminated by a simple filtration process. In most cases, the process of sample preparation is not as simple as dissolution of the component interest. At times, enrichment is necessary, that is, the component of interest is present in very large volume or mass of material. It needs to be concentrated in some manner so a small volume of the concentrated or enriched sample can be injected into HPLC. 88 refs

Author Details

African Journals Online (AJOL)

Oyeyemi, GM. Vol 14, No 2 (2008) - Articles Comparison of bootstrap and jackknife methods of re-sampling in estimating population parameters. Abstract. ISSN: 1118-0579. AJOL African Journals Online. HOW TO USE AJOL... for Researchers · for Librarians · for Authors · FAQ's · More about AJOL · AJOL's Partners · Terms ...

Evolutionary change in Cepaea nemoralis shell colour over 43 years

NARCIS (Netherlands)

Ozgo, Malgorzata; Schilthuizen, Menno

We compared shell colour forms in the land snail Cepaea nemoralis at 16 sites in a 7 x 8 km section of the Province of Groningen, the Netherlands, between 1967 and 2010. To do so, we used stored samples in a natural history collection and resampled the exact collection localities. We found that

Perpendicular distance sampling: an alternative method for sampling downed coarse woody debris

Science.gov (United States)

Michael S. Williams; Jeffrey H. Gove

2003-01-01

Coarse woody debris (CWD) plays an important role in many forest ecosystem processes. In recent years, a number of new methods have been proposed to sample CWD. These methods select individual logs into the sample using some form of unequal probability sampling. One concern with most of these methods is the difficulty in estimating the volume of each log. A new method...

Sample size of the reference sample in a case-augmented study.

Science.gov (United States)

Ghosh, Palash; Dewanji, Anup

2017-05-01

The case-augmented study, in which a case sample is augmented with a reference (random) sample from the source population with only covariates information known, is becoming popular in different areas of applied science such as pharmacovigilance, ecology, and econometrics. In general, the case sample is available from some source (for example, hospital database, case registry, etc.); however, the reference sample is required to be drawn from the corresponding source population. The required minimum size of the reference sample is an important issue in this regard. In this work, we address the minimum sample size calculation and discuss related issues. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A method of language sampling

DEFF Research Database (Denmark)

Rijkhoff, Jan; Bakker, Dik; Hengeveld, Kees

1993-01-01

In recent years more attention is paid to the quality of language samples in typological work. Without an adequate sampling strategy, samples may suffer from various kinds of bias. In this article we propose a sampling method in which the genetic criterion is taken as the most important: samples...... to determine how many languages from each phylum should be selected, given any required sample size....

Development of SYVAC sampling techniques

International Nuclear Information System (INIS)

Prust, J.O.; Dalrymple, G.J.

1985-04-01

This report describes the requirements of a sampling scheme for use with the SYVAC radiological assessment model. The constraints on the number of samples that may be taken is considered. The conclusions from earlier studies using the deterministic generator sampling scheme are summarised. The method of Importance Sampling and a High Dose algorithm, which are designed to preferentially sample in the high dose region of the parameter space, are reviewed in the light of experience gained from earlier studies and the requirements of a site assessment and sensitivity analyses. In addition the use of an alternative numerical integration method for estimating risk is discussed. It is recommended that the method of Importance Sampling is developed and tested for use with SYVAC. An alternative numerical integration method is not recommended for investigation at this stage but should be the subject of future work. (author)

Evaluation of the microparticle enzyme immunoassay Abbott IMx Select Chlamydia and the importance of urethral site sampling to detect Chlamydia trachomatis in women.

OpenAIRE

Brokenshire, M K; Say, P J; van Vonno, A H; Wong, C

1997-01-01

OBJECTIVE: To evaluate the commercial microparticle enzyme immunoassay (MEIA), Abbott IMx Select Chlamydia, for the detection of Chlamydia trachomatis in women and to compare its performance with endocervical cell culture. Also, to determine whether sampling the urethral site is an important part of chlamydial diagnosis in women. SETTING: The Auckland, Manukau, and Waitakere Sexual Health Clinics, Auckland, New Zealand and the Department of Clinical Microbiology, Auckland Hospital, Auckland, ...

Daily river flow prediction based on Two-Phase Constructive Fuzzy Systems Modeling: A case of hydrological - meteorological measurements asymmetry

Science.gov (United States)

Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann

2018-03-01

Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.

STUDY ON THE CLASSIFICATION OF GAOFEN-3 POLARIMETRIC SAR IMAGES USING DEEP NEURAL NETWORK

Directory of Open Access Journals (Sweden)

J. Zhang

2018-04-01

Full Text Available Polarimetric Synthetic Aperture Radar（POLSAR） imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

Science.gov (United States)

Zhang, J.; Zhang, J.; Zhao, Z.

2018-04-01

Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

Long-Term Soil Chemistry Changes in Aggrading Forest Ecosystems

Science.gov (United States)

Jennifer D. Knoepp; Wayne T. Swank

1994-01-01

Assessing potential long-term forest productivity requires identification of the processes regulating chemical changes in forest soils. We resampled the litter layer and upper two mineral soil horizons, A and AB/BA, in two aggrading southern Appalachian watersheds 20 yr after an earlier sampling. Soils from a mixed-hardwood watershed exhibited a small but significant...

Statistical sampling strategies

International Nuclear Information System (INIS)

Andres, T.H.

1987-01-01

Systems assessment codes use mathematical models to simulate natural and engineered systems. Probabilistic systems assessment codes carry out multiple simulations to reveal the uncertainty in values of output variables due to uncertainty in the values of the model parameters. In this paper, methods are described for sampling sets of parameter values to be used in a probabilistic systems assessment code. Three Monte Carlo parameter selection methods are discussed: simple random sampling, Latin hypercube sampling, and sampling using two-level orthogonal arrays. Three post-selection transformations are also described: truncation, importance transformation, and discretization. Advantages and disadvantages of each method are summarized

Kolmogorov-Smirnov test for spatially correlated data

Science.gov (United States)

Olea, R.A.; Pawlowsky-Glahn, V.

2009-01-01

The Kolmogorov-Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov-Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size. ?? Springer-Verlag 2008.

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

Energy Technology Data Exchange (ETDEWEB)

Dolphin, Andrew E., E-mail: adolphin@raytheon.com [Raytheon Company, Tucson, AZ, 85734 (United States)

2013-09-20

The standard technique for measurement of random uncertainties of star formation histories (SFHs) is the bootstrap Monte Carlo, in which the color-magnitude diagram (CMD) is repeatedly resampled. The variation in SFHs measured from the resampled CMDs is assumed to represent the random uncertainty in the SFH measured from the original data. However, this technique systematically and significantly underestimates the uncertainties for times in which the measured star formation rate is low or zero, leading to overly (and incorrectly) high confidence in that measurement. This study proposes an alternative technique, the Markov Chain Monte Carlo (MCMC), which samples the probability distribution of the parameters used in the original solution to directly estimate confidence intervals. While the most commonly used MCMC algorithms are incapable of adequately sampling a probability distribution that can involve thousands of highly correlated dimensions, the Hybrid Monte Carlo algorithm is shown to be extremely effective and efficient for this particular task. Several implementation details, such as the handling of implicit priors created by parameterization of the SFH, are discussed in detail.

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

International Nuclear Information System (INIS)

Dolphin, Andrew E.

2013-01-01

The standard technique for measurement of random uncertainties of star formation histories (SFHs) is the bootstrap Monte Carlo, in which the color-magnitude diagram (CMD) is repeatedly resampled. The variation in SFHs measured from the resampled CMDs is assumed to represent the random uncertainty in the SFH measured from the original data. However, this technique systematically and significantly underestimates the uncertainties for times in which the measured star formation rate is low or zero, leading to overly (and incorrectly) high confidence in that measurement. This study proposes an alternative technique, the Markov Chain Monte Carlo (MCMC), which samples the probability distribution of the parameters used in the original solution to directly estimate confidence intervals. While the most commonly used MCMC algorithms are incapable of adequately sampling a probability distribution that can involve thousands of highly correlated dimensions, the Hybrid Monte Carlo algorithm is shown to be extremely effective and efficient for this particular task. Several implementation details, such as the handling of implicit priors created by parameterization of the SFH, are discussed in detail

Sampling and sample processing in pesticide residue analysis.

Science.gov (United States)

Lehotay, Steven J; Cook, Jo Marie

2015-05-13

Proper sampling and sample processing in pesticide residue analysis of food and soil have always been essential to obtain accurate results, but the subject is becoming a greater concern as approximately 100 mg test portions are being analyzed with automated high-throughput analytical methods by agrochemical industry and contract laboratories. As global food trade and the importance of monitoring increase, the food industry and regulatory laboratories are also considering miniaturized high-throughput methods. In conjunction with a summary of the symposium "Residues in Food and Feed - Going from Macro to Micro: The Future of Sample Processing in Residue Analytical Methods" held at the 13th IUPAC International Congress of Pesticide Chemistry, this is an opportune time to review sampling theory and sample processing for pesticide residue analysis. If collected samples and test portions do not adequately represent the actual lot from which they came and provide meaningful results, then all costs, time, and efforts involved in implementing programs using sophisticated analytical instruments and techniques are wasted and can actually yield misleading results. This paper is designed to briefly review the often-neglected but crucial topic of sample collection and processing and put the issue into perspective for the future of pesticide residue analysis. It also emphasizes that analysts should demonstrate the validity of their sample processing approaches for the analytes/matrices of interest and encourages further studies on sampling and sample mass reduction to produce a test portion.

Keeping quality of imported dried fish

OpenAIRE

Goonewardene, I.S.R.; Etoh, S.

1980-01-01

All imported salted, dried fish samples tested had a salt content below 30% and above 12% and hence met requirements of the proposed standard. Also samples without quality cut tested had a greater salt content than that with quality cut. This indicates that salt contributes to protecting dried fish and hence may be endorsed by sensory evaluation to a certain extent. Samples with quality cut had more moisture than that without quality cut. But all samples with and without quality cut had a moi...

Stable isotope probing reveals the importance of Comamonas and Pseudomonadaceae in RDX degradation in samples from a Navy detonation site.

Science.gov (United States)

Jayamani, Indumathy; Cupples, Alison M

2015-07-01

This study investigated the microorganisms involved in hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) degradation from a detonation area at a Navy base. Using Illumina sequencing, microbial communities were compared between the initial sample, samples following RDX degradation, and controls not amended with RDX to determine which phylotypes increased in abundance following RDX degradation. The effect of glucose on these communities was also examined. In addition, stable isotope probing (SIP) using labeled ((13)C3, (15)N3-ring) RDX was performed. Illumina sequencing revealed that several phylotypes were more abundant following RDX degradation compared to the initial soil and the no-RDX controls. For the glucose-amended samples, this trend was strong for an unclassified Pseudomonadaceae phylotype and for Comamonas. Without glucose, Acinetobacter exhibited the greatest increase following RDX degradation compared to the initial soil and no-RDX controls. Rhodococcus, a known RDX degrader, also increased in abundance following RDX degradation. For the SIP study, unclassified Pseudomonadaceae was the most abundant phylotype in the heavy fractions in both the presence and absence of glucose. In the glucose-amended heavy fractions, the 16S ribosomal RNA (rRNA) genes of Comamonas and Anaeromxyobacter were also present. Without glucose, the heavy fractions also contained the 16S rRNA genes of Azohydromonas and Rhodococcus. However, all four phylotypes were present at a much lower level compared to unclassified Pseudomonadaceae. Overall, these data indicate that unclassified Pseudomonadaceae was primarily responsible for label uptake in both treatments. This study indicates, for the first time, the importance of Comamonas for RDX removal.

Contrasting natural regeneration and tree planting in fourteen North American cities

Science.gov (United States)

David J. Nowak

2012-01-01

Field data from randomly located plots in 12 cities in the United States and Canada were used to estimate the proportion of the existing tree population that was planted or occurred via natural regeneration. In addition, two cities (Baltimore and Syracuse) were recently re-sampled to estimate the proportion of newly established trees that were planted. Results for the...

Methodology Series Module 5: Sampling Strategies.

Science.gov (United States)

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ' Sampling Method'. There are essentially two types of sampling methods: 1) probability sampling - based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling - based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term ' random sample' when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the ' generalizability' of these results. In such a scenario, the researcher may want to use ' purposive sampling' for the study.

Methodology series module 5: Sampling strategies

Directory of Open Access Journals (Sweden)

Maninder Singh Setia

2016-01-01

Full Text Available Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the 'Sampling Method'. There are essentially two types of sampling methods: 1 probability sampling – based on chance events (such as random numbers, flipping a coin etc.; and 2 non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term 'random sample' when the researcher has used convenience sample. The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the 'generalizability' of these results. In such a scenario, the researcher may want to use 'purposive sampling' for the study.

21 CFR 1.90 - Notice of sampling.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Notice of sampling. 1.90 Section 1.90 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL GENERAL ENFORCEMENT REGULATIONS Imports and Exports § 1.90 Notice of sampling. When a sample of an article offered for import has...

Co-integration Rank Testing under Conditional Heteroskedasticity

DEFF Research Database (Denmark)

Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

Machine learning methods as a tool to analyse incomplete or irregularly sampled radon time series data.

Science.gov (United States)

Janik, M; Bossew, P; Kurihara, O

2018-07-15

Machine learning is a class of statistical techniques which has proven to be a powerful tool for modelling the behaviour of complex systems, in which response quantities depend on assumed controls or predictors in a complicated way. In this paper, as our first purpose, we propose the application of machine learning to reconstruct incomplete or irregularly sampled data of time series indoor radon ( 222 Rn). The physical assumption underlying the modelling is that Rn concentration in the air is controlled by environmental variables such as air temperature and pressure. The algorithms "learn" from complete sections of multivariate series, derive a dependence model and apply it to sections where the controls are available, but not the response (Rn), and in this way complete the Rn series. Three machine learning techniques are applied in this study, namely random forest, its extension called the gradient boosting machine and deep learning. For a comparison, we apply the classical multiple regression in a generalized linear model version. Performance of the models is evaluated through different metrics. The performance of the gradient boosting machine is found to be superior to that of the other techniques. By applying learning machines, we show, as our second purpose, that missing data or periods of Rn series data can be reconstructed and resampled on a regular grid reasonably, if data of appropriate physical controls are available. The techniques also identify to which degree the assumed controls contribute to imputing missing Rn values. Our third purpose, though no less important from the viewpoint of physics, is identifying to which degree physical, in this case environmental variables, are relevant as Rn predictors, or in other words, which predictors explain most of the temporal variability of Rn. We show that variables which contribute most to the Rn series reconstruction, are temperature, relative humidity and day of the year. The first two are physical

Methodology Series Module 5: Sampling Strategies

Science.gov (United States)

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ‘ Sampling Method’. There are essentially two types of sampling methods: 1) probability sampling – based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term ‘ random sample’ when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the ‘ generalizability’ of these results. In such a scenario, the researcher may want to use ‘ purposive sampling’ for the study. PMID:27688438

Import-push or Export-pull?

DEFF Research Database (Denmark)

Jäkel, Ina Charlotte

2014-01-01

predictions regarding the export market and the role of product differentiation. Empirical results for a sample of Danish manufacturing industries confirm the import- "push" hypothesis as well as the export- "pull" hypothesis, but also reveal differences across industries. The selection effect of trade...... is mainly driven by the "import-push" if product differentiation is high, whereas it is driven by the "export-pull" if goods are homogeneous....

Import-push or Export-pull?

DEFF Research Database (Denmark)

Jäkel, Ina Charlotte

predictions regarding the export market and the role of product differentiation. Empirical results for a sample of Danish manufacturing industries confirm the import-"push" hypothesis as well as the export-"pull" hypothesis, but also reveal differences across industries. The selection effect of trade...... is mainly driven by the "import-push" if product differentiation is high, whereas it is driven by the "export-pull" if goods are homogeneous....

Sample representativeness verification of the FADN CZ farm business sample

Directory of Open Access Journals (Sweden)

Marie Prášilová

2011-01-01

Full Text Available Sample representativeness verification is one of the key stages of statistical work. After having joined the European Union the Czech Republic joined also the Farm Accountancy Data Network system of the Union. This is a sample of bodies and companies doing business in agriculture. Detailed production and economic data on the results of farming business are collected from that sample annually and results for the entire population of the country´s farms are then estimated and assessed. It is important hence, that the sample be representative. Representativeness is to be assessed as to the number of farms included in the survey and also as to the degree of accordance of the measures and indices as related to the population. The paper deals with the special statistical techniques and methods of the FADN CZ sample representativeness verification including the necessary sample size statement procedure. The Czech farm population data have been obtained from the Czech Statistical Office data bank.

The Importance of Pressure Sampling Frequency in Models for Determination of Critical Wave Loadingson Monolithic Structures

DEFF Research Database (Denmark)

Burcharth, Hans F.; Andersen, Thomas Lykke; Meinert, Palle

2008-01-01

This paper discusses the influence of wave load sampling frequency on calculated sliding distance in an overall stability analysis of a monolithic caisson. It is demonstrated by a specific example of caisson design that for this kind of analyses the sampling frequency in a small scale model could...... be as low as 100 Hz in model scale. However, for design of structure elements like the wave wall on the top of a caisson the wave load sampling frequency must be much higher, in the order of 1000 Hz in the model. Elastic-plastic deformations of foundation and structure were not included in the analysis....

On Using a Pilot Sample Variance for Sample Size Determination in the Detection of Differences between Two Means: Power Consideration

Science.gov (United States)

Shieh, Gwowen

2013-01-01

The a priori determination of a proper sample size necessary to achieve some specified power is an important problem encountered frequently in practical studies. To establish the needed sample size for a two-sample "t" test, researchers may conduct the power analysis by specifying scientifically important values as the underlying population means…

Principles of Proper Validation

DEFF Research Database (Denmark)

Esbensen, Kim; Geladi, Paul

2010-01-01

to suffer from the same deficiencies. The PPV are universal and can be applied to all situations in which the assessment of performance is desired: prediction-, classification-, time series forecasting-, modeling validation. The key element of PPV is the Theory of Sampling (TOS), which allow insight......) is critically necessary for the inclusion of the sampling errors incurred in all 'future' situations in which the validated model must perform. Logically, therefore, all one data set re-sampling approaches for validation, especially cross-validation and leverage-corrected validation, should be terminated...

"Best Practices in Using Large, Complex Samples: The Importance of Using Appropriate Weights and Design Effect Compensation"

Directory of Open Access Journals (Sweden)

Jason W. Osborne

2011-09-01

Full Text Available Large surveys often use probability sampling in order to obtain representative samples, and these data sets are valuable tools for researchers in all areas of science. Yet many researchers are not formally prepared to appropriately utilize these resources. Indeed, users of one popular dataset were generally found not to have modeled the analyses to take account of the complex sample (Johnson & Elliott, 1998 even when publishing in highly-regarded journals. It is well known that failure to appropriately model the complex sample can substantially bias the results of the analysis. Examples presented in this paper highlight the risk of error of inference and mis-estimation of parameters from failure to analyze these data sets appropriately.

Simple street tree sampling

Science.gov (United States)

David J. Nowak; Jeffrey T. Walton; James Baldwin; Jerry. Bond

2015-01-01

Information on street trees is critical for management of this important resource. Sampling of street tree populations provides an efficient means to obtain street tree population information. Long-term repeat measures of street tree samples supply additional information on street tree changes and can be used to report damages from catastrophic events. Analyses of...

Dendrochemical evidence for soil recovery from acidic deposition in forests of the northeastern U.S. with comparisons to the southeastern U.S. and Russia

Science.gov (United States)

Walter C. Shortle; Kevin T. Smith; Andrei G. Lapenis

2017-01-01

A soil resampling approach has detected an early stage of recovery in the cation chemistry of spruce forest soil due to reductions in acid deposition. That approach is limited by the lack of soil data and archived soil samples prior to major increases in acid deposition during the latter half of the 20th century. An alternative approach is the dendrochemical analysis...

Seeking Signs of Life on Mars: The Importance of Sedimentary Suites as Part of Mars Sample Return

Science.gov (United States)

iMOST Team; Mangold, N.; McLennan, S. M.; Czaja, A. D.; Ori, G. G.; Tosca, N. J.; Altieri, F.; Amelin, Y.; Ammannito, E.; Anand, M.; Beaty, D. W.; Benning, L. G.; Bishop, J. L.; Borg, L. E.; Boucher, D.; Brucato, J. R.; Busemann, H.; Campbell, K. A.; Carrier, B. L.; Debaille, V.; Des Marais, D. J.; Dixon, M.; Ehlmann, B. L.; Farmer, J. D.; Fernandez-Remolar, D. C.; Fogarty, J.; Glavin, D. P.; Goreva, Y. S.; Grady, M. M.; Hallis, L. J.; Harrington, A. D.; Hausrath, E. M.; Herd, C. D. K.; Horgan, B.; Humayun, M.; Kleine, T.; Kleinhenz, J.; Mackelprang, R.; Mayhew, L. E.; McCubbin, F. M.; McCoy, J. T.; McSween, H. Y.; Moser, D. E.; Moynier, F.; Mustard, J. F.; Niles, P. B.; Raulin, F.; Rettberg, P.; Rucker, M. A.; Schmitz, N.; Sefton-Nash, E.; Sephton, M. A.; Shaheen, R.; Shuster, D. L.; Siljestrom, S.; Smith, C. L.; Spry, J. A.; Steele, A.; Swindle, T. D.; ten Kate, I. L.; Usui, T.; Van Kranendonk, M. J.; Wadhwa, M.; Weiss, B. P.; Werner, S. C.; Westall, F.; Wheeler, R. M.; Zipfel, J.; Zorzano, M. P.

2018-04-01

Sedimentary, and especially lacustrine, depositional environments are high-priority geological/astrobiological settings for Mars Sample Return. We review the detailed investigations, measurements, and sample types required to evaluate such settings.

Rectal swab screening assays of public health importance in molecular diagnostics: Sample adequacy control.

Science.gov (United States)

Glisovic, Sanja; Eintracht, Shaun; Longtin, Yves; Oughton, Matthew; Brukner, Ivan

Rectal swabs are routinely used by public health authorities to screen for multi-drug resistant enteric bacteria including vancomycin-resistant enterococci (VRE) and carbapenem-resistant enterobacteriaceae (CRE). Screening sensitivity can be influenced by the quality of the swabbing, whether performed by the patient (self-swabbing) or a healthcare practitioner. One common exclusion criterion for rectal swabs is absence of "visible soiling" from fecal matter. In our institution, this criterion excludes almost 10% of rectal swabs received in the microbiology laboratory. Furthermore, over 30% of patients in whom rectal swabs are cancelled will not be re-screened within the next 48h, resulting in delays in removing infection prevention measures. We describe two quantitative polymerase chain reaction (qPCR)-based assays, human RNAse P and eubacterial 16S rDNA, which might serve as suitable controls for sampling adequacy. However, lower amounts of amplifiable human DNA make the 16s rDNA assay a better candidate for sample adequacy control. Copyright © 2017. Published by Elsevier Ltd.

Sampling procedure in a willow plantation for chemical elements important for biomass combustion quality

DEFF Research Database (Denmark)

Liu, Na; Nielsen, Henrik Kofoed; Jørgensen, Uffe

2015-01-01

clone ‘Tordis’, and to reveal the relationship between sampling position, shoot diameters, and distribution of elements. Five Tordis willow shoots were cut into 10–50 cm sections from base to top. The ash content and concentration of twelve elements (Al, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, P, Si, and Zn......Willow (Salix spp.) is expected to contribute significantly to the woody bioenergy system in the future, so more information on how to sample the quality of the willow biomass is needed. The objectives of this study were to investigate the spatial variation of elements within shoots of a willow......) in each section were determined. The results showed large spatial variation in the distribution of most elements along the length of the willow shoots. Concentrations of elements in 2-year old shoots of the willow clone Tordis were fairly stable within the range of 100–285 cm above ground and resembled...

Radioactive contamination in imported foods

International Nuclear Information System (INIS)

Kan, Kimiko; Maki, Toshio; Nagayama, Toshihiro; Hashimoto, Hideki; Kawai, Yuka; Kobayashi, Maki; Shioda, Hiroko; Nishima, Taichiro

1990-01-01

On April 26, 1986, explosion occurred in Chernobyl nuclear power station in USSR, and radioactivity contamination was brought about in almost all countries in the world. In European countries, crops were contaminated directly with radioactive fallout to high concentration. Also in Japan, after one week the radioactivity higher than usual was detected in environment, and also in vegetables, milk, tea leaves and others. Thereafter, in order to cope with the import of contaminated foods, inspection and watch system was strengthened by deciding the interim limit of radioactive concentration. However the cases of exceeding the interim limit were often reported. In order to remove the harmful foods due to radioactive contamination and to meet the fear of consumers, the authors measured the radioactive concentration in foods distributed in Tokyo and investigated the actual state of contamination. The samples were 920 imported foods. The experimental method, the preparation of samples, the method of analysis and the results are reported. The samples in which the radioactive concentration exceeding 50 Bq/kg was detected were 25 cases. The food having the high frequency of detection was flavors. (K.I.)

Uncertainty Assessment of Hydrological Frequency Analysis Using Bootstrap Method

Directory of Open Access Journals (Sweden)

Yi-Ming Hu

2013-01-01

Full Text Available The hydrological frequency analysis (HFA is the foundation for the hydraulic engineering design and water resources management. Hydrological extreme observations or samples are the basis for HFA; the representativeness of a sample series to the population distribution is extremely important for the estimation reliability of the hydrological design value or quantile. However, for most of hydrological extreme data obtained in practical application, the size of the samples is usually small, for example, in China about 40~50 years. Generally, samples with small size cannot completely display the statistical properties of the population distribution, thus leading to uncertainties in the estimation of hydrological design values. In this paper, a new method based on bootstrap is put forward to analyze the impact of sampling uncertainty on the design value. By bootstrap resampling technique, a large number of bootstrap samples are constructed from the original flood extreme observations; the corresponding design value or quantile is estimated for each bootstrap sample, so that the sampling distribution of design value is constructed; based on the sampling distribution, the uncertainty of quantile estimation can be quantified. Compared with the conventional approach, this method provides not only the point estimation of a design value but also quantitative evaluation on uncertainties of the estimation.

Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

Science.gov (United States)

Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

2015-06-01

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

Importance sampling techniques and treatment of electron transport in MCNP 4A

International Nuclear Information System (INIS)

Ueki, K.

1994-01-01

The continuous energy Monte Carlo code MCNP was developed by the Radiation Transport Group at Los Alamos National Laboratory and the MCNP 4A version is available, now. The MCNP 4A is able to do the coupled neutron-secondary gamma-ray-electron-bremsstrahlung calculation. The calculated results, such as energy spectra, tally fluctuation chart, and geometrical input data can be displayed by using a work station. The document of the MCNP 4A code has no description on the subroutines, except few ones of 'SOURCE', 'TALLYX'. However, when we want to improve the MCNP Monte Carlo sampling techniques to get more accuracy or efficiency results for some problems, some subroutines are required or needed to revised. Three subroutines have been revised and built in the MCNP 4A code. (author)

Efficient approach for reliability-based optimization based on weighted importance sampling approach

International Nuclear Information System (INIS)

Yuan, Xiukai; Lu, Zhenzhou

2014-01-01

An efficient methodology is presented to perform the reliability-based optimization (RBO). It is based on an efficient weighted approach for constructing an approximation of the failure probability as an explicit function of the design variables which is referred to as the ‘failure probability function (FPF)’. It expresses the FPF as a weighted sum of sample values obtained in the simulation-based reliability analysis. The required computational effort for decoupling in each iteration is just single reliability analysis. After the approximation of the FPF is established, the target RBO problem can be decoupled into a deterministic one. Meanwhile, the proposed weighted approach is combined with a decoupling approach and a sequential approximate optimization framework. Engineering examples are given to demonstrate the efficiency and accuracy of the presented methodology

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

International Nuclear Information System (INIS)

Hampton, Jerrad; Doostan, Alireza

2015-01-01

Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ 1 -minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

Science.gov (United States)

Hampton, Jerrad; Doostan, Alireza

2015-01-01

Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ1-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.

Methodology Series Module 5: Sampling Strategies

OpenAIRE

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ? Sampling Method?. There are essentially two types of sampling methods: 1) probability sampling ? based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling ? based on researcher's choice, population that accessible & available. Some of the non-probabilit...

Confidence limits for contribution plots in multivariate statistical process control using bootstrap estimates.

Science.gov (United States)

Babamoradi, Hamid; van den Berg, Frans; Rinnan, Åsmund

2016-02-18

In Multivariate Statistical Process Control, when a fault is expected or detected in the process, contribution plots are essential for operators and optimization engineers in identifying those process variables that were affected by or might be the cause of the fault. The traditional way of interpreting a contribution plot is to examine the largest contributing process variables as the most probable faulty ones. This might result in false readings purely due to the differences in natural variation, measurement uncertainties, etc. It is more reasonable to compare variable contributions for new process runs with historical results achieved under Normal Operating Conditions, where confidence limits for contribution plots estimated from training data are used to judge new production runs. Asymptotic methods cannot provide confidence limits for contribution plots, leaving re-sampling methods as the only option. We suggest bootstrap re-sampling to build confidence limits for all contribution plots in online PCA-based MSPC. The new strategy to estimate CLs is compared to the previously reported CLs for contribution plots. An industrial batch process dataset was used to illustrate the concepts. Copyright © 2016 Elsevier B.V. All rights reserved.

Power-line Interference Removal from ECG in Case of Power-line Frequency Variations

Directory of Open Access Journals (Sweden)

Todor Stoyanov

2008-10-01

Full Text Available The original version of the most successful approach for power-line (PL interference removal from ECG, called subtraction procedure, is based on linear segment detection in the signal and hardware synchronised analogue-to-digital conversion to cope with the PL frequency variations. However, this is not feasible for battery supplied devices and some computer-aided ECG systems. Recent improvements of the procedure apply software measurement of the frequency variations that allow a re-sampling of the contaminated signal with the rated PL frequency followed by interference removal and back re-sampling for restoration of the original time intervals. This study deals with a more accurate software frequency measurement and introduces a notch filtration as alternative to the procedure when no linear segments are encountered for long time, e.g. in cases of ventricular fibrillation or tachycardia. The result obtained with large PL frequency variations demonstrate very small errors, usually in the range of ± 20 μV for the subtraction procedure and ± 60 μV for the notch filtration, the last values strongly depending on the frequency contents of the QRS complexes.

Statistics and sampling in transuranic studies

International Nuclear Information System (INIS)

Eberhardt, L.L.; Gilbert, R.O.

1980-01-01

The existing data on transuranics in the environment exhibit a remarkably high variability from sample to sample (coefficients of variation of 100% or greater). This chapter stresses the necessity of adequate sample size and suggests various ways to increase sampling efficiency. Objectives in sampling are regarded as being of great importance in making decisions as to sampling methodology. Four different classes of sampling methods are described: (1) descriptive sampling, (2) sampling for spatial pattern, (3) analytical sampling, and (4) sampling for modeling. A number of research needs are identified in the various sampling categories along with several problems that appear to be common to two or more such areas

Importance of Using Multiple Sampling Methodologies for Estimating of Fish Community Composition in Offshore Wind Power Construction Areas of the Baltic Sea

Energy Technology Data Exchange (ETDEWEB)

Andersson, Mathias H.; Gullstroem, Martin; Oehman, Marcus C. (Dept. of Zoology, Stockholm Univ., Stockholm (Sweden)); Asplund, Maria E. (Dept. of Marine Ecology, Goeteborg Univ., Kristineberg Marine Research Station, Fiskebaeckskil (Sweden))

2007-12-15

In this study a visual SCUBA investigation was conducted in Utgrunden 2, an area where windmills had not yet been constructed, and where the bottom mainly consisted of mud or sand with no or a sparse number of algae or mussel beds. A wind farm at Utgrunden 2 would alter the local habitat from a predominantly sandy soft-bottom habitat to an area in which artificial reef structures that resemble hard-bottom habitats is introduced, i.e., the steel foundations and possibly boulders for scour protection. The fish community that will develop over time would be expected to change to resemble the assemblages observed at Utgrunden 1 and hence not visible using trawling and echosound sampling technique. As the goal of EIA is to assess changes, following human development visual techniques is recommended as a complement when examining the environmental effects of offshore windpower. Otherwise important ecological changes may go unnoticed. For a comprehensive understanding of the ecological effects of windfarm developments it is recommended that a combination of sampling methods is applied and that this should be defined before an investigation commences. Although it is well established in the scientific literature that different sampling methods will give different estimations of fish community composition, environmental impact assessments of offshore windpower have been incorrectly interpreted. In the interpretation of the results of such assessments it is common that the findings are extrapolated by stakeholders and media to include a larger extent of the fish populations than what was intended. Therefore, to fully understand how windpower influences fish the underwater visual census technique is here put forward as a necessary complement to more widescreening fish sampling methods (e.g., gill nets, echo-sounds, trawling)

The Lunar Sample Compendium

Science.gov (United States)

Meyer, Charles

2009-01-01

The Lunar Sample Compendium is a succinct summary of the data obtained from 40 years of study of Apollo and Luna samples of the Moon. Basic petrographic, chemical and age information is compiled, sample-by-sample, in the form of an advanced catalog in order to provide a basic description of each sample. The LSC can be found online using Google. The initial allocation of lunar samples was done sparingly, because it was realized that scientific techniques would improve over the years and new questions would be formulated. The LSC is important because it enables scientists to select samples within the context of the work that has already been done and facilitates better review of proposed allocations. It also provides back up material for public displays, captures information found only in abstracts, grey literature and curatorial databases and serves as a ready access to the now-vast scientific literature.

Comparison of parametric and bootstrap method in bioequivalence test.

Science.gov (United States)

Ahn, Byung-Jin; Yim, Dong-Seok

2009-10-01

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled datasets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

Probability Maps for the Visualization of Assimilation Ensemble Flow Data

KAUST Repository

Hollt, Thomas; Hadwiger, Markus; Knio, Omar; Hoteit, Ibrahim

2015-01-01

resampling, every member can follow up on any of the members before resampling. Tracking behavior over time, such as all possible paths of a particle in an ensemble vector field, becomes very difficult, as the number of combinations rises exponentially

Contributions to sampling statistics

CERN Document Server

Conti, Pier; Ranalli, Maria

2014-01-01

This book contains a selection of the papers presented at the ITACOSM 2013 Conference, held in Milan in June 2013. ITACOSM is the bi-annual meeting of the Survey Sampling Group S2G of the Italian Statistical Society, intended as an international  forum of scientific discussion on the developments of theory and application of survey sampling methodologies and applications in human and natural sciences. The book gathers research papers carefully selected from both invited and contributed sessions of the conference. The whole book appears to be a relevant contribution to various key aspects of sampling methodology and techniques; it deals with some hot topics in sampling theory, such as calibration, quantile-regression and multiple frame surveys, and with innovative methodologies in important topics of both sampling theory and applications. Contributions cut across current sampling methodologies such as interval estimation for complex samples, randomized responses, bootstrap, weighting, modeling, imputati...

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

Science.gov (United States)

Biro, Peter A

2013-02-01

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

New data from Oposisi : implications for Early Papuan pottery phase

International Nuclear Information System (INIS)

Allen, J.; Summerhayes, G.; Mandui, H.; Leavesley, M.

2011-01-01

An apparent colonisation of the Papuan south coast by pottery-making villagers about 2000 years ago let in the 1970s to the development of a regional sequence of first millenium AD decorated pottery styles now known as Early Papuan pottery (EPP). Important in defining this style horizon is the Yule Island site of Oposisi first excavated by Ron Vanderwal in 1969. As part of an on-going re-appraisal of pottery production along this coast by two of us, we took advantage of an opportunity to re-sample the site in 2007. A paper proposing a much earlier starting date for EPP based on dates for sherds in Torres Strait meant that we could also take advantage of this visit to acquire further dating samples. A coherent set of seven new AMS dates strongly supports the Oposisi sequence beginning at c. 2000 BP. Beyond this our sample produced much more obsidian, imported from Fergusson Island 600 km to the east, than had previously been recorded for the site. This attests to stronger and more continuous eastern links than had been previously supposed. Lastly the paper reviews EPP in the light of recent pottery finds that suggest pre-EPP pottery will occur on the south Papuan coast. (author). 21 refs., 8 figs., 8 tabs.

A method of language sampling

DEFF Research Database (Denmark)

Rijkhoff, Jan; Bakker, Dik; Hengeveld, Kees

1993-01-01

In recent years more attention is paid to the quality of language samples in typological work. Without an adequate sampling strategy, samples may suffer from various kinds of bias. In this article we propose a sampling method in which the genetic criterion is taken as the most important: samples...... created with this method will reflect optimally the diversity of the languages of the world. On the basis of the internal structure of each genetic language tree a measure is computed that reflects the linguistic diversity in the language families represented by these trees. This measure is used...... to determine how many languages from each phylum should be selected, given any required sample size....

Sample preparation guidelines for two-dimensional electrophoresis.

Science.gov (United States)

Posch, Anton

2014-12-01

Sample preparation is one of the key technologies for successful two-dimensional electrophoresis (2DE). Due to the great diversity of protein sample types and sources, no single sample preparation method works with all proteins; for any sample the optimum procedure must be determined empirically. This review is meant to provide a broad overview of the most important principles in sample preparation in order to avoid a multitude of possible pitfalls. Sample preparation protocols from the expert in the field were screened and evaluated. On the basis of these protocols and my own comprehensive practical experience important guidelines are given in this review. The presented guidelines will facilitate straightforward protocol development for researchers new to gel-based proteomics. In addition the available choices are rationalized in order to successfully prepare a protein sample for 2DE separations. The strategies described here are not limited to 2DE and can also be applied to other protein separation techniques.

Adaptive sampling method in deep-penetration particle transport problem

International Nuclear Information System (INIS)

Wang Ruihong; Ji Zhicheng; Pei Lucheng

2012-01-01

Deep-penetration problem has been one of the difficult problems in shielding calculation with Monte Carlo method for several decades. In this paper, a kind of particle transport random walking system under the emission point as a sampling station is built. Then, an adaptive sampling scheme is derived for better solution with the achieved information. The main advantage of the adaptive scheme is to choose the most suitable sampling number from the emission point station to obtain the minimum value of the total cost in the process of the random walk. Further, the related importance sampling method is introduced. Its main principle is to define the importance function due to the particle state and to ensure the sampling number of the emission particle is proportional to the importance function. The numerical results show that the adaptive scheme under the emission point as a station could overcome the difficulty of underestimation of the result in some degree, and the adaptive importance sampling method gets satisfied results as well. (authors)

Microfluidic devices for sample clean-up and screening of biological samples

NARCIS (Netherlands)

Tetala, K.K.R.

2009-01-01

Analytical chemistry plays an important role in the separation and identification of analytes from raw samples (e.g. plant extracts, blood), but the whole analytical process is tedious, difficult to automate and time consuming. To overcome these drawbacks, the concept of μTAS (miniaturized total

Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

Energy Technology Data Exchange (ETDEWEB)

Hosntalab, Mohammad [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Aghaeizadeh Zoroofi, Reza [University of Tehran, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, Tehran (Iran); Abbaspour Tehrani-Fard, Ali [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Sharif University of Technology, Department of Electrical Engineering, Tehran (Iran); Shirani, Gholamreza [Faculty of Dentistry Medical Science of Tehran University, Oral and Maxillofacial Surgery Department, Tehran (Iran)

2008-09-15

Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. (orig.)

Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set

International Nuclear Information System (INIS)

Hosntalab, Mohammad; Aghaeizadeh Zoroofi, Reza; Abbaspour Tehrani-Fard, Ali; Shirani, Gholamreza

2008-01-01

Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. (orig.)

Combined effects of hydrographic structure and iron and copper availability on the phytoplankton growth in Terra Nova Bay Polynya (Ross Sea, Antarctica)

Science.gov (United States)

Rivaro, Paola; Luisa Abelmoschi, Maria; Grotti, Marco; Ianni, Carmela; Magi, Emanuele; Margiotta, Francesca; Massolo, Serena; Saggiomo, Vincenzo

2012-04-01

Surface water (CLIMA) Project of the Programma Nazionale di Ricerca in Antartide activities. Dissolved oxygen, nutrients, phytoplankton pigments and concentration and complexation of dissolved trace metals were determined. Experimental data were elaborated by Principal Component Analysis (PCA). As a result of solar heating and freshwater inputs from melting sea-ice, the water column was strongly stratified with an Upper Mixed Layer 4-16 m deep. The integrated Chl a in the layer 0-100 m ranged from 60 mg m-2 to 235 mg m-2, with a mean value of 138 mg m-2. The pigment analysis showed that diatoms dominated the phytoplankton assemblage. Major nutrients were generally high, with the lowest concentration at the surface and they were never fully depleted. The Si:N drawdown ratio was close to the expected value of 1 for Fe-replete diatoms. We evaluated both the total and the labile dissolved fraction of Fe and Cu. The labile fraction was operationally defined by employing the chelating resin Chelex-100, which retains free and loosely bound trace metal species. The total dissolved Fe ranged from 0.48 to 3.02 nM, while the total dissolved Cu from 3.68 to 6.84 nM. The dissolved labile Fe ranged from below the detection limit (0.15 nM) to 1.22 nM, and the dissolved labile Cu from 0.31 to 1.59 nM, respectively. The labile fractions measured at 20 m were significantly lower than values in 40-100 m samples. As two stations were re-sampled 5 days later, we evaluated the short-term variability of the physical and biogeochemical properties. In particular, in a re-sampled station at 20 m, the total dissolved Fe increased and the total dissolved Cu decreased, while their labile fraction was relatively steady. As a result of the increase in total Fe, the percentage of the labile Fe decreased. An increase of the Si:N, Si:P and Si:FUCO ratios was measured also in the re-sampled station. On this basis, we speculated that a switch from a Fe-replete to a Fe-deplete condition was occurring.

Comparison of sample preparation methods for the determination of essential and toxic elements in important indigenous medicinal plant Aloe barbadensis

International Nuclear Information System (INIS)

Sahito, S.R.; Kazi, T.G.; Kazi, G.H.; Jakhrani, M.A.; Wattoo, M.H.S.

2002-01-01

The role of elements particularly traces elements in health and disease is now well established. In this paper we investigate the presence of various elements in very important herb Aloe barbadensis, it is commonly used in different ailments especially of elementary tract. We used four extraction methods for the determination of total elements in Aloe barbadensis. The procedure, which is found to be more efficient and decompose the biological material, is nitric acid and 30% hydrogen peroxide as compared to other method. The sample of plants was collected from surrounding of Hyderabad; Sindh University and vouches specimens were prepared following the standard herbarium techniques. Fifteen essential, trace and toxic elements such as Zn, Cr, K, Mg, Ca, Na, Fe, Pb, Al, Ba, Mn, Co, Ni and Cd were determined in plant and in its decoction. Using Flame Atomic Absorption Spectrophotometer Hitachi Model 180-50. It is noted that, level of essential elements was found high as compare to the level of toxic elements. (author)

Assessment of radionuclides in imported foodstuffs in Iran

International Nuclear Information System (INIS)

Hosseini, T.; Fathivand, A. A.; Barati, H.; Karimi, M.

2006-01-01

Knowledge of radioactivity levels in human diet is of particular concern for the estimation of possible radiological hazards to human health. However, very few surveys of radioactivity in food have been conducted in Iran; therefore the baseline values of the natural radionuclides concentration (4 0K , 2 26R a and 2 32T h), and man made radionuclide, 1 37C s, were determined in twenty six samples of imported foodstuff in Iran. Materials and Methods: Twenty six samples of different kinds of imported foodstuff were selected for analysis. These samples, after pretreatment and washing (if necessary), were measured by a low level gamma spectrometry system. Results: All samples were found to contain detectable 4 0K content in range 6.4 to 778.4 Bq.kg -1 fresh weights (f w). 1 37C s, 2 26R a and 2 32T h were detectable in most of the samples. The maximum concentration of 4 0K , 2 26R a and 2 32T h were found in tea sample, equal to 778.4±23.4, 2.9±0.1 and 5.4±0.2 Bq.kg -1 (f w), respectively, where as for 1 37C s it was 3.2±0.1 Bq.kg -1 (f w) in milk powder. Conclusion: The concentrations of 4 0K and 1 37C s in different imported foodstuff are comparable with those from the other countries yet 2 32T h concentration is higher than the reported values. Also, 2 26R a results appear to be higher than the reported values in some cases

UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

Directory of Open Access Journals (Sweden)

A. Kianisarkaleh

2015-12-01

Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

16 CFR 1500.266 - Notice of sampling.

Science.gov (United States)

2010-01-01

... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Notice of sampling. 1500.266 Section 1500.266 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT... Notice of sampling. When a sample of a hazardous substance offered for import has been requested by the...

Sampling Methods in Cardiovascular Nursing Research: An Overview.

Science.gov (United States)

Kandola, Damanpreet; Banner, Davina; O'Keefe-McCarthy, Sheila; Jassal, Debbie

2014-01-01

Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. The selection of specific participant samples is an important part of the research design and process. The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. There are two main categories of sampling methods: probability and non-probability. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Each approach offers distinct advantages and disadvantages and must be considered critically. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research.

Time and Power Optimizations in FPGA-Based Architectures for Polyphase Channelizers

DEFF Research Database (Denmark)

Awan, Mehmood-Ur-Rehman; Harris, Fred; Koch, Peter

2012-01-01

This paper presents the time and power optimization considerations for Field Programmable Gate Array (FPGA) based architectures for a polyphase filter bank channelizer with an embedded square root shaping filter in its polyphase engine. This configuration performs two different re-sampling tasks......% slice register resources of a Xilinx Virtex-5 FPGA, operating at 400 and 480 MHz, and consuming 1.9 and 2.6 Watts of dynamic power, respectively....

Sample design effects in landscape genetics

Science.gov (United States)

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach

DEFF Research Database (Denmark)

Christensen, Kim; Hounyo, Ulrich; Podolskij, Mark

-frequency data. We document the importance of jump-robustness, when measuring heteroscedasticity in practice. We also find that a large fraction of variation in intraday volatility is accounted for by seasonality. This suggests that, once we control for jumps and deate asset returns by a non-parametric estimate...

Statistical aspects of food safety sampling

NARCIS (Netherlands)

Jongenburger, I.; Besten, den H.M.W.; Zwietering, M.H.

2015-01-01

In food safety management, sampling is an important tool for verifying control. Sampling by nature is a stochastic process. However, uncertainty regarding results is made even greater by the uneven distribution of microorganisms in a batch of food. This article reviews statistical aspects of

Hydrogen peroxide: importance and determination

OpenAIRE

Mattos, Ivanildo Luiz de; Shiraishi, Karina Antonelli; Braz, Alexandre Delphini; Fernandes, João Roberto

2003-01-01

A brief discussion about the hydrogen peroxide importance and its determination is presented. It was emphasized some consideration of the H2O2 as reagent (separated or combined), uses and methods of analysis (techniques, detection limits, linear response intervals, sensor specifications). Moreover, it was presented several applications, such as in environmental, pharmaceutical, medicine and food samples.

CHOMIK -Sampling Device of Penetrating Type for Russian Phobos Sample Return Mission

Science.gov (United States)

Seweryn, Karol; Grygorczuk, Jerzy; Rickmann, Hans; Morawski, Marek; Aleksashkin, Sergey; Banaszkiewicz, Marek; Drogosz, Michal; Gurgurewicz, Joanna; Kozlov, Oleg E.; Krolikowska-Soltan, Malgorzata; Sutugin, Sergiej E.; Wawrzaszek, Roman; Wisniewski, Lukasz; Zakharov, Alexander

Measurements of physical properties of planetary bodies allow to determine many important parameters for scientists working in different fields of research. For example effective heat conductivity of the regolith can help with better understanding of processes occurring in the body interior. Chemical and mineralogical composition gives us a chance to better understand the origin and evolution of the moons. In principle such parameters of the planetary bodies can be determined based on three different measurement techniques: (i) in situ measurements (ii) measurements of the samples in laboratory conditions at the Earth and (iii) remote sensing measurements. Scientific missions which allow us to perform all type of measurements, give us a chance for not only parameters determination but also cross calibration of the instruments. Russian Phobos Sample Return (PhSR) mission is one of few which allows for all type of such measurements. The spacecraft will be equipped with remote sensing instruments like: spectrometers, long wave radar and dust counter, instruments for in-situ measurements -gas-chromatograph, seismometer, thermodetector and others and also robotic arm and sampling device. PhSR mission will be launched in November 2011 on board of a launch vehicle Zenit. About a year later (11 months) the vehicle will reach the Martian orbit. It is anticipated that it will land on Phobos in the beginning of 2013. A take off back will take place a month later and the re-entry module containing a capsule that will hold the soil sample enclosed in a container will be on its way back to Earth. The 11 kg re-entry capsule with the container will land in Kazakhstan in mid-2014. A unique geological penetrator CHOMIK dedicated for the Phobos Sample Return space mis-sion will be designed and manufactured at the Space Mechatronics and Robotics Laboratory, Space Research Centre Polish Academy of Sciences (SRC PAS) in Warsaw. Functionally CHOMIK is based on the well known MUPUS

Developing Students' Reasoning about Samples and Sampling Variability as a Path to Expert Statistical Thinking

Science.gov (United States)

Garfield, Joan; Le, Laura; Zieffler, Andrew; Ben-Zvi, Dani

2015-01-01

This paper describes the importance of developing students' reasoning about samples and sampling variability as a foundation for statistical thinking. Research on expert-novice thinking as well as statistical thinking is reviewed and compared. A case is made that statistical thinking is a type of expert thinking, and as such, research…

Representativeness of two sampling procedures for an internet intervention targeting cancer-related distress: a comparison of convenience and registry samples.

Science.gov (United States)

Owen, Jason E; Bantum, Erin O'Carroll; Criswell, Kevin; Bazzo, Julie; Gorlick, Amanda; Stanton, Annette L

2014-08-01

Internet interventions often rely on convenience sampling, yet convenience samples may differ in important ways from systematic recruitment approaches. The purpose of this study was to evaluate potential demographic, medical, and psychosocial differences between Internet-recruited and registry-recruited cancer survivors in an Internet-based intervention. Participants were recruited from a cancer registry (n = 80) and via broad Internet outreach efforts (n = 160). Participants completed a set of self-report questionnaires, and both samples were compared to a population-based sample of cancer survivors (n = 5,150). The Internet sample was younger, better educated, more likely to be female, had longer time since diagnosis, and had more advanced stage of disease (p's sample was over-represented by men and those with prostate or other cancer types (p's sample also exhibited lower quality of life and social support and greater mood disturbance (p's convenience and systematic samples differ has important implications for external validity and potential for dissemination of Internet-based interventions.

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

Energy Technology Data Exchange (ETDEWEB)

Shine, E. P.; Poirier, M. R.

2013-10-29

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

International Nuclear Information System (INIS)

Shine, E. P.; Poirier, M. R.

2013-01-01

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and data interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and

German radionuclide exports and imports 1990

International Nuclear Information System (INIS)

Anon.

1991-01-01

The statistics compiled by the German Federal Office for Trade and Industry (Bundesamt fuer Wirtschaft) for the Federal Ministry for the Environment, Conservation of Nature, and Reactor Protection of imports and exports of radionuclides, irradiation samples and sealed emitters above 1850 GBq show a slight decline by 11.8%, on the basis of activity, in imports and a somewhat higher rise by 21.6% in exports in 1990. Imports returned to the level of 1988 after having experienced an extraordinary rise in 1989. Exports were slightly better than in the previous year, but still considerably below the average of the past five years. (orig.) [de

Quality Control Samples for the Radiological Determination of Tritium in Urine Samples

International Nuclear Information System (INIS)

Ost'pezuk, P.; Froning, M.; Laumen, S.; Richert, I.; Hill, P.

2004-01-01

The radioactive decay product of tritium is a low energy beta that cannot penetrate the outer dead layer of human skin. Therefore , the main hazard associated with tritium is internal exposure. In addition, due to the relatively long half life and short biological half life, tritium must be ingested in large amounts to pose a significant health risk. On the other hand, the internal exposure should be kept as low as practical. For incorporation monitoring of professional radiation workers the quality control is of utmost importance. In the Research Centre Juelich GmbH (FZJ) a considerable fraction of monitoring by excretion analysis relates to the isotope Tritium. Usually an aliquot of an urine sample is mixed with a liquid scintillator and measured in a liquid scintillation counter. Quality control samples in the form of three kind of internal reference samples (blank, reference samples with low activity and reference sample with elevated activity) were prepared from a mixed, Tritium (free) urine samples. 1 ml of these samples were pipetted into a liquid scintillation vial. In the part of theses vials a known amounts of Tritium were added. All these samples were stored at 20 degrees. Based on long term use of all these reference samples it was possible to construct appropriate control charts with the upper and lower alarm limits. Daily use of these reference samples decrease significantly the risk for false results in original urine with no significant increase of the determination time. (Author) 2 refs

Importance of sampling design and analysis in animal population studies: a comment on Sergio et al

Science.gov (United States)

Kery, M.; Royle, J. Andrew; Schmid, Hans

2008-01-01

1. The use of predators as indicators and umbrellas in conservation has been criticized. In the Trentino region, Sergio et al. (2006; hereafter SEA) counted almost twice as many bird species in quadrats located in raptor territories than in controls. However, SEA detected astonishingly few species. We used contemporary Swiss Breeding Bird Survey data from an adjacent region and a novel statistical model that corrects for overlooked species to estimate the expected number of bird species per quadrat in that region. 2. There are two anomalies in SEA which render their results ambiguous. First, SEA detected on average only 6.8 species, whereas a value of 32 might be expected. Hence, they probably overlooked almost 80% of all species. Secondly, the precision of their mean species counts was greater in two-thirds of cases than in the unlikely case that all quadrats harboured exactly the same number of equally detectable species. This suggests that they detected consistently only a biased, unrepresentative subset of species. 3. Conceptually, expected species counts are the product of true species number and species detectability p. Plenty of factors may affect p, including date, hour, observer, previous knowledge of a site and mobbing behaviour of passerines in the presence of predators. Such differences in p between raptor and control quadrats could have easily created the observed effects. Without a method that corrects for such biases, or without quantitative evidence that species detectability was indeed similar between raptor and control quadrats, the meaning of SEA's counts is hard to evaluate. Therefore, the evidence presented by SEA in favour of raptors as indicator species for enhanced levels of biodiversity remains inconclusive. 4. Synthesis and application. Ecologists should pay greater attention to sampling design and analysis in animal population estimation. Species richness estimation means sampling a community. Samples should be representative for the

Development and application of group importance measures

International Nuclear Information System (INIS)

Haskin, F.E.; Huang, Min; Sasser, M.K.; Stack, D.W.

1992-01-01

As part of a complete Level I probabilistic safety analysis of the K Production Reactor, three traditional importance measures-risk reduction, partial derivative, and variance reduction-have been extended to permit analyses of the relative importance of groups of basic and initiating events. None of the group importance measures require Monte Carlo sampling for their quantification. The group importance measures are quantified for the overall fuel damage equation and for dominant accident sequences using the following event groups: initiating events, electrical failures, instrumentation failures, common-cause failures, human errors, and nonrecovery events. Additional analyses are presented using other event groups. Collectively, these applications indicate both the utility and the versatility of the group importance measures

Concentrations of radiocesium in foods imported from Russia (1996-1998)

International Nuclear Information System (INIS)

Sugiyama, Hideo; Terada, Hiroshi; Izumo, Yoshiro; Miyata, Masahiro; Watanabe, Yoshinori; Tsuchiya, Tetsu; Endo, Taigo; Yoshida, Akio; Maeda, Kenji

2000-01-01

The concentrations of radiocesium, 137 Cs and 134 Cs, were determined in foods imported from Russia between 1996 and 1998. A total of 143 samples, including cod roe (47 samples), crab (44), fish, including flatfish and halibut (18), ground fish meat (11), and shrimp (8), were collected in quarantine stations throughout Japan and measured with a high-purity Ge semiconductor detector and spectrometer. The concentrations of both 137 Cs and 134 Cs were determined in 115 of the samples, but only 137 Cs was measured in the other 28 samples. 137 Cs was detected in 24 samples, and the mean concentration was 0.06 Bq/kg in the raw samples and 36.7 Bq/kg in the dry samples. Japanese tsubugai shellfish had the highest concentration (0.50 Bq/kg) among the non-dried foods. Radiocesium was most frequently detected in cod roe (15 raw samples, 0.06 - 0.14 Bq/kg), followed by fish and shellfish, including ground fish meat (7 samples), dried bracken (1 sample), and dried kabanoanatake (a species of mushrooms) (1 sample). The radiocesium concentration in kabanoanatake was the highest in this survey. The concentrations of 134 Cs in all samples was below the limit of detection. The concentrations of radiocesium in foods imported from Russia did not change between 1996 and 1998, and they appeared to be low, the same as in food distributed in Japanese markets. The annual effective dose equivalents in adults were estimated based on the assumption that all of the imported food from Russia was consumed by Japanese people. It was assumed that the amount of intake of each food was 0.5% and that the 137 Cs dose conversion factor was 1.4 x 10 - 5 mSv/Bq. The intake of 134 Cs was assumed to be zero. The results of the estimations were an annual effective dose equivalent of 0.28 x 10-3 μSv for fish/shellfish, of 2.8 x 10-3 μSv for dried bracken, and of 11.9 x 10-3 μSv for dried kabanoanatake. These results overestimated actual intake, and these annual effective dose equivalents appeared to be

Growth of a Functionally Important Lexicon.

Science.gov (United States)

Zechmeister, Eugene B.; And Others

1995-01-01

Uses a dictionary-sampling method and multiple-choice testing of word knowledge to estimate the lexicon size of junior-high students, college students, and older adults. Suggests that there may yet be a role for direct instruction in affecting lexicon size of functionally important words. (SR)

Improving the quality of extracting dynamics from interspike intervals via a resampling approach

Science.gov (United States)

Pavlova, O. N.; Pavlov, A. N.

2018-04-01

We address the problem of improving the quality of characterizing chaotic dynamics based on point processes produced by different types of neuron models. Despite the presence of embedding theorems for non-uniformly sampled dynamical systems, the case of short data analysis requires additional attention because the selection of algorithmic parameters may have an essential influence on estimated measures. We consider how the preliminary processing of interspike intervals (ISIs) can increase the precision of computing the largest Lyapunov exponent (LE). We report general features of characterizing chaotic dynamics from point processes and show that independently of the selected mechanism for spike generation, the performed preprocessing reduces computation errors when dealing with a limited amount of data.

Analysis of the research sample collections of Uppsala biobank.

Science.gov (United States)

Engelmark, Malin T; Beskow, Anna H

2014-10-01

Uppsala Biobank is the joint and only biobank organization of the two principals, Uppsala University and Uppsala University Hospital. Biobanks are required to have updated registries on sample collection composition and management in order to fulfill legal regulations. We report here the results from the first comprehensive and overall analysis of the 131 research sample collections organized in the biobank. The results show that the median of the number of samples in the collections was 700 and that the number of samples varied from less than 500 to over one million. Blood samples, such as whole blood, serum, and plasma, were included in the vast majority, 84.0%, of the research sample collections. Also, as much as 95.5% of the newly collected samples within healthcare included blood samples, which further supports the concept that blood samples have fundamental importance for medical research. Tissue samples were also commonly used and occurred in 39.7% of the research sample collections, often combined with other types of samples. In total, 96.9% of the 131 sample collections included samples collected for healthcare, showing the importance of healthcare as a research infrastructure. Of the collections that had accessed existing samples from healthcare, as much as 96.3% included tissue samples from the Department of Pathology, which shows the importance of pathology samples as a resource for medical research. Analysis of different research areas shows that the most common of known public health diseases are covered. Collections that had generated the most publications, up to over 300, contained a large number of samples collected systematically and repeatedly over many years. More knowledge about existing biobank materials, together with public registries on sample collections, will support research collaborations, improve transparency, and bring us closer to the goals of biobanks, which is to save and prolong human lives and improve health and quality of life.

Fluctuation Flooding Method (FFM) for accelerating conformational transitions of proteins

Science.gov (United States)

Harada, Ryuhei; Takano, Yu; Shigeta, Yasuteru

2014-03-01

A powerful conformational sampling method for accelerating structural transitions of proteins, "Fluctuation Flooding Method (FFM)," is proposed. In FFM, cycles of the following steps enhance the transitions: (i) extractions of largely fluctuating snapshots along anisotropic modes obtained from trajectories of multiple independent molecular dynamics (MD) simulations and (ii) conformational re-sampling of the snapshots via re-generations of initial velocities when re-starting MD simulations. In an application to bacteriophage T4 lysozyme, FFM successfully accelerated the open-closed transition with the 6 ns simulation starting solely from the open state, although the 1-μs canonical MD simulation failed to sample such a rare event.

Combining Electrochemical Sensors with Miniaturized Sample Preparation for Rapid Detection in Clinical Samples

Science.gov (United States)

Bunyakul, Natinan; Baeumner, Antje J.

2015-01-01

Clinical analyses benefit world-wide from rapid and reliable diagnostics tests. New tests are sought with greatest demand not only for new analytes, but also to reduce costs, complexity and lengthy analysis times of current techniques. Among the myriad of possibilities available today to develop new test systems, amperometric biosensors are prominent players—best represented by the ubiquitous amperometric-based glucose sensors. Electrochemical approaches in general require little and often enough only simple hardware components, are rugged and yet provide low limits of detection. They thus offer many of the desirable attributes for point-of-care/point-of-need tests. This review focuses on investigating the important integration of sample preparation with (primarily electrochemical) biosensors. Sample clean up requirements, miniaturized sample preparation strategies, and their potential integration with sensors will be discussed, focusing on clinical sample analyses. PMID:25558994

Frequency Analysis Using Bootstrap Method and SIR Algorithm for Prevention of Natural Disasters

Science.gov (United States)

Kim, T.; Kim, Y. S.

2017-12-01

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results show that probabilistic daily snowfall depth by frequency analysis is decreased at most stations, and most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics. Acknowledgment.This research was supported by a grant(MPSS-NH-2015-79) from Disaster Prediction and Mitigation Technology Development Program funded by Korean Ministry of Public Safety and Security(MPSS).

Sequential Monte Carlo with Highly Informative Observations

OpenAIRE

Del Moral, Pierre; Murray, Lawrence M.

2014-01-01

We propose sequential Monte Carlo (SMC) methods for sampling the posterior distribution of state-space models under highly informative observation regimes, a situation in which standard SMC methods can perform poorly. A special case is simulating bridges between given initial and final values. The basic idea is to introduce a schedule of intermediate weighting and resampling times between observation times, which guide particles towards the final state. This can always be done for continuous-...

Comparison of C-arm computed tomography and on-site quick cortisol assay for adrenal venous sampling: A retrospective study of 178 patients

Energy Technology Data Exchange (ETDEWEB)

Chang, Chin-Chen; Lee, Bo-Ching; Chang, Yeun-Chung; Liu, Kao-Lang [National Taiwan University Hospital and National Taiwan University College of Medicine, Department of Medical Imaging, Taipei (China); Wu, Vin-Cent [National Taiwan University Hospital and National Taiwan University College of Medicine, Department of Internal Medicine, Taipei (China); Huang, Kuo-How [National Taiwan University Hospital and National Taiwan University College of Medicine, Department of Urology, Taipei (China); Collaboration: on behalf of the TAIPAI Study Group

2017-12-15

To compare the performance of on-site quick cortisol assay (QCA) and C-arm computed tomography (CT) assistance on adrenal venous sampling (AVS) without adrenocorticotropic hormone stimulation. The institutional review board at our hospital approved this retrospective study, which included 178 consecutive patients with primary aldosteronism. During AVS, we used C-arm CT to confirm right adrenal cannulation between May 2012 and June 2015 (n = 100) and QCA for bilateral adrenal cannulation between July 2015 and September 2016 (n = 78). Successful AVS required a selectivity index (cortisol{sub adrenal} {sub vein}/cortisol{sub peripheral}) of ≥ 2.0 bilaterally. The overall success rate of C-arm CT-assisted AVS was 87%, which increased to 97.4% under QCA (P =.013). The procedure time (C-arm CT, 49.5 ± 21.3 min; QCA, 37.5 ± 15.6 min; P <.001) and radiation dose (C-arm CT, 673.9 ± 613.8 mGy; QCA, 346.4 ± 387.8 mGy; P <.001) were also improved. The resampling rate was 16% and 21.8% for C-arm CT and QCA, respectively. The initial success rate of the performing radiologist remained stable during the study period (C-arm CT 75%; QCA, 82.1%, P =.259). QCA might be superior to C-arm CT for improving the performance of AVS. (orig.)

Urine sample preparation for proteomic analysis.

Science.gov (United States)

Olszowy, Pawel; Buszewski, Boguslaw

2014-10-01

Sample preparation for both environmental and more importantly biological matrices is a bottleneck of all kinds of analytical processes. In the case of proteomic analysis this element is even more important due to the amount of cross-reactions that should be taken into consideration. The incorporation of new post-translational modifications, protein hydrolysis, or even its degradation is possible as side effects of proteins sample processing. If protocols are evaluated appropriately, then identification of such proteins does not bring difficulties. However, if structural changes are provided without sufficient attention then protein sequence coverage will be reduced or even identification of such proteins could be impossible. This review summarizes obstacles and achievements in protein sample preparation of urine for proteome analysis using different tools for mass spectrometry analysis. The main aim is to present comprehensively the idea of urine application as a valuable matrix. This article is dedicated to sample preparation and application of urine mainly in novel cancer biomarkers discovery. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An improved sampling method of complex network

Science.gov (United States)

Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

2014-12-01

Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

Sampling, feasibility, and priors in Bayesian estimation

OpenAIRE

Chorin, Alexandre J.; Lu, Fei; Miller, Robert N.; Morzfeld, Matthias; Tu, Xuemin

2015-01-01

Importance sampling algorithms are discussed in detail, with an emphasis on implicit sampling, and applied to data assimilation via particle filters. Implicit sampling makes it possible to use the data to find high-probability samples at relatively low cost, making the assimilation more efficient. A new analysis of the feasibility of data assimilation is presented, showing in detail why feasibility depends on the Frobenius norm of the covariance matrix of the noise and not on the number of va...

Big Data, Small Sample.

Science.gov (United States)

Gerlovina, Inna; van der Laan, Mark J; Hubbard, Alan

2017-05-20

Multiple comparisons and small sample size, common characteristics of many types of "Big Data" including those that are produced by genomic studies, present specific challenges that affect reliability of inference. Use of multiple testing procedures necessitates calculation of very small tail probabilities of a test statistic distribution. Results based on large deviation theory provide a formal condition that is necessary to guarantee error rate control given practical sample sizes, linking the number of tests and the sample size; this condition, however, is rarely satisfied. Using methods that are based on Edgeworth expansions (relying especially on the work of Peter Hall), we explore the impact of departures of sampling distributions from typical assumptions on actual error rates. Our investigation illustrates how far the actual error rates can be from the declared nominal levels, suggesting potentially wide-spread problems with error rate control, specifically excessive false positives. This is an important factor that contributes to "reproducibility crisis". We also review some other commonly used methods (such as permutation and methods based on finite sampling inequalities) in their application to multiple testing/small sample data. We point out that Edgeworth expansions, providing higher order approximations to the sampling distribution, offer a promising direction for data analysis that could improve reliability of studies relying on large numbers of comparisons with modest sample sizes.

Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices

International Nuclear Information System (INIS)

Thieke, Christian; Nill, Simeon; Oelfke, Uwe; Bortfeld, Thomas

2002-01-01

In inverse planning for intensity-modulated radiotherapy, the dose calculation is a crucial element limiting both the maximum achievable plan quality and the speed of the optimization process. One way to integrate accurate dose calculation algorithms into inverse planning is to precalculate the dose contribution of each beam element to each voxel for unit fluence. These precalculated values are stored in a big dose calculation matrix. Then the dose calculation during the iterative optimization process consists merely of matrix look-up and multiplication with the actual fluence values. However, because the dose calculation matrix can become very large, this ansatz requires a lot of computer memory and is still very time consuming, making it not practical for clinical routine without further modifications. In this work we present a new method to significantly reduce the number of entries in the dose calculation matrix. The method utilizes the fact that a photon pencil beam has a rapid radial dose falloff, and has very small dose values for the most part. In this low-dose part of the pencil beam, the dose contribution to a voxel is only integrated into the dose calculation matrix with a certain probability. Normalization with the reciprocal of this probability preserves the total energy, even though many matrix elements are omitted. Three probability distributions were tested to find the most accurate one for a given memory size. The sampling method is compared with the use of a fully filled matrix and with the well-known method of just cutting off the pencil beam at a certain lateral distance. A clinical example of a head and neck case is presented. It turns out that a sampled dose calculation matrix with only 1/3 of the entries of the fully filled matrix does not sacrifice the quality of the resulting plans, whereby the cutoff method results in a suboptimal treatment plan

Stereo reconstruction from multiperspective panoramas.

Science.gov (United States)

Li, Yin; Shum, Heung-Yeung; Tang, Chi-Keung; Szeliski, Richard

2004-01-01

A new approach to computing a panoramic (360 degrees) depth map is presented in this paper. Our approach uses a large collection of images taken by a camera whose motion has been constrained to planar concentric circles. We resample regular perspective images to produce a set of multiperspective panoramas and then compute depth maps directly from these resampled panoramas. Our panoramas sample uniformly in three dimensions: rotation angle, inverse radial distance, and vertical elevation. The use of multiperspective panoramas eliminates the limited overlap present in the original input images and, thus, problems as in conventional multibaseline stereo can be avoided. Our approach differs from stereo matching of single-perspective panoramic images taken from different locations, where the epipolar constraints are sine curves. For our multiperspective panoramas, the epipolar geometry, to the first order approximation, consists of horizontal lines. Therefore, any traditional stereo algorithm can be applied to multiperspective panoramas with little modification. In this paper, we describe two reconstruction algorithms. The first is a cylinder sweep algorithm that uses a small number of resampled multiperspective panoramas to obtain dense 3D reconstruction. The second algorithm, in contrast, uses a large number of multiperspective panoramas and takes advantage of the approximate horizontal epipolar geometry inherent in multiperspective panoramas. It comprises a novel and efficient 1D multibaseline matching technique, followed by tensor voting to extract the depth surface. Experiments show that our algorithms are capable of producing comparable high quality depth maps which can be used for applications such as view interpolation.

The importance of drug checking outside the context of nightlife in Slovenia.

Science.gov (United States)

Sande, Matej; Šabić, Simona

2018-01-12

The main purpose of the research was to evaluate the implementation of the drug checking service in Slovenia and to obtain the opinion of users included in harm reduction programmes for high-risk drug users and of drug users in nightlife settings on drug checking, the reasons for drug checking, and their attitude towards adulterants in the drugs that they use. The two final unrepresentative research samples included 102 respondents from harm reduction programmes and 554 respondents from the online sample. The questionnaire was designed based on analysis of the interviews conducted with professionals from the programmes, who took part in the drug checking project, and based on previous research on drug use in nightlife. The main findings related to users' opinions on the drug checking service are that users from both samples perceive drug checking as a contribution to risk reduction and that they find providing information for them about the harmful adulterants and substances that they use very important. In addition, users from both samples considered accessibility of the drug checking service as very important and would be in favour of brief counselling at the collection of the drug sample. One of the salient differences between samples was that nightlife drug users found it more important to recognise substances in the drugs that they use. Drug users from two different samples attach a relatively high importance to the drug checking service, and they consider it to be a contribution to risk reduction. As well as drug users in nightlife settings, high-risk drug users also perceive the drug checking service to be important, which is relevant in the phase of planning drug checking services outside the context of nightlife and for the act of incorporating these services into contemporary harm reduction policy.

An object-oriented framework for medical image registration, fusion, and visualization.

Science.gov (United States)

Zhu, Yang-Ming; Cochoff, Steven M

2006-06-01

An object-oriented framework for image registration, fusion, and visualization was developed based on the classic model-view-controller paradigm. The framework employs many design patterns to facilitate legacy code reuse, manage software complexity, and enhance the maintainability and portability of the framework. Three sample applications built a-top of this framework are illustrated to show the effectiveness of this framework: the first one is for volume image grouping and re-sampling, the second one is for 2D registration and fusion, and the last one is for visualization of single images as well as registered volume images.

Analysis of IFR samples at ANL-E

International Nuclear Information System (INIS)

Bowers, D.L.; Sabau, C.S.

1993-01-01

The Analytical Chemistry Laboratory analyzes a variety of samples submitted by the different research groups within IFR. This talk describes the analytical work on samples generated by the Plutonium Electrorefiner, Large Scale Electrorefiner and Waste Treatment Studies. The majority of these samples contain Transuranics and necessitate facilities that safely contain these radioisotopes. Details such as: sample receiving, dissolution techniques, chemical separations, Instrumentation used, reporting of results are discussed. The Importance of Interactions between customer and analytical personnel Is also demonstrated

Research-Grade 3D Virtual Astromaterials Samples: Novel Visualization of NASA's Apollo Lunar Samples and Antarctic Meteorite Samples to Benefit Curation, Research, and Education

Science.gov (United States)

Blumenfeld, E. H.; Evans, C. A.; Oshel, E. R.; Liddle, D. A.; Beaulieu, K. R.; Zeigler, R. A.; Righter, K.; Hanna, R. D.; Ketcham, R. A.

2017-01-01

NASA's vast and growing collections of astromaterials are both scientifically and culturally significant, requiring unique preservation strategies that need to be recurrently updated to contemporary technological capabilities and increasing accessibility demands. New technologies have made it possible to advance documentation and visualization practices that can enhance conservation and curation protocols for NASA's Astromaterials Collections. Our interdisciplinary team has developed a method to create 3D Virtual Astromaterials Samples (VAS) of the existing collections of Apollo Lunar Samples and Antarctic Meteorites. Research-grade 3D VAS will virtually put these samples in the hands of researchers and educators worldwide, increasing accessibility and visibility of these significant collections. With new sample return missions on the horizon, it is of primary importance to develop advanced curation standards for documentation and visualization methodologies.

Data-driven importance distributions for articulated tracking

DEFF Research Database (Denmark)

Hauberg, Søren; Pedersen, Kim Steenstrup

2011-01-01

We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In order to keep the algorithms efficient, we represent human poses in terms of spatial joint positions. To ensure constant bone le...... filter, where they improve both accuracy and efficiency of the tracker. In fact, they triple the effective number of samples compared to the most commonly used importance distribution at little extra computational cost....

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

Science.gov (United States)

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

DETERMINING EFFICIENCY OF INVESTMENT BANKS AFTERFINANCIALCRISISBY BOOTSTRAPDATA ENVELOPMENTANALYSIS (BDEA :A CASE OF TURKEY

Directory of Open Access Journals (Sweden)

Funda H. Sezgin

2012-01-01

Full Text Available Data Envelopment Analysis (DEA is a mathematical programming formulationbased technique that provides an efficient frontier to suggest an estimate of therelative efficiency of each decision making unit (DMU in a problem set. DEA isdeveloped around the concept of evaluating the efficiency of a decision alternativebased on its performance of creating outputs in means of input consumption.Besides its advantages,criticisms about the potential bias of efficiency estimatesof DEA has been arised. One criticism about DEA is on the sampling variation ofthe estimated frontier which may affect the accuracy of results. The bootstrapmethod is a statistical resampling method used to perform inference complexproblems. The basic idea of the bootstrap method is to approximate the samplingdistributions of the estimator by using the empirical distribution of resampledestimates obtained from a Monte Carlo resampling. DEA estimators introducedan approach based on “bootstrap techniques” to correct and estimate the bias ofthe DEA efficiency indicators.The purpose of this study is to measure theefficiency of small amount ofinvestment banksin Turkeyafter thefinancialcrisis in 2010with theBootstrapDEA(BDEA.

Sampling Transition Pathways in Highly Correlated Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Chandler, David

2004-10-20

This research grant supported my group's efforts to apply and extend the method of transition path sampling that we invented during the late 1990s. This methodology is based upon a statistical mechanics of trajectory space. Traditional statistical mechanics focuses on state space, and with it, one can use Monte Carlo methods to facilitate importance sampling of states. With our formulation of a statistical mechanics of trajectory space, we have succeeded at creating algorithms by which importance sampling can be done for dynamical processes. In particular, we are able to study rare but important events without prior knowledge of transition states or mechanisms. In perhaps the most impressive application of transition path sampling, my group combined forces with Michele Parrinello and his coworkers to unravel the dynamics of auto ionization of water [5]. This dynamics is the fundamental kinetic step of pH. Other applications concern nature of dynamics far from equilibrium [1, 7], nucleation processes [2], cluster isomerization, melting and dissociation [3, 6], and molecular motors [10]. Research groups throughout the world are adopting transition path sampling. In part this has been the result of our efforts to provide pedagogical presentations of the technique [4, 8, 9], as well as providing new procedures for interpreting trajectories of complex systems [11].

Measurement of neutron activation in concrete samples

International Nuclear Information System (INIS)

Zagar, T.; Ravnik, M.

2000-01-01

The results of activation studies of ordinary and barytes concrete samples relevant for research reactor decommissioning are given. Five important long-lived radioactive isotopes ( 54 Mn, 60 Co, 65 Zn, 133 Ba, and 152 Eu) were identified from the gamma-ray spectra measured in the irradiated concrete samples. Activation of these samples was also calculated using ORIGEN2 code. Comparison of calculated and measured results is given. (author)

Handling missing data in ranked set sampling

CERN Document Server

Bouza-Herrera, Carlos N

2013-01-01

The existence of missing observations is a very important aspect to be considered in the application of survey sampling, for example. In human populations they may be caused by a refusal of some interviewees to give the true value for the variable of interest. Traditionally, simple random sampling is used to select samples. Most statistical models are supported by the use of samples selected by means of this design. In recent decades, an alternative design has started being used, which, in many cases, shows an improvement in terms of accuracy compared with traditional sampling. It is called R

Drone inflight mixing of biochemical samples.

Science.gov (United States)

Katariya, Mayur; Chung, Dwayne Chung Kim; Minife, Tristan; Gupta, Harshit; Zahidi, Alifa Afiah Ahmad; Liew, Oi Wah; Ng, Tuck Wah

2018-03-15

Autonomous systems for sample transport to the laboratory for analysis can be improved in terms of timeliness, cost and error mitigation in the pre-analytical testing phase. Drones have been reported for outdoor sample transport but incorporating devices on them to attain homogenous mixing of reagents during flight to enhance sample processing timeliness is limited by payload issues. It is shown here that flipping maneuvers conducted with quadcopters are able to facilitate complete and gentle mixing. This capability incorporated during automated sample transport serves to address an important factor contributing to pre-analytical variability which ultimately impacts on test result reliability. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of the orthodontic treatment need in a paediatric sample from Southern Italy and its importance among paediatricians for improving oral health in pediatric dentistry

Science.gov (United States)

Ierardo, Gaetano; Corridore, Denise; Di Carlo, Gabriele; Di Giorgio, Gianni; Leonardi, Emanuele; Campus, Guglielmo-Giuseppe; Vozza, Iole; Polimeni, Antonella; Bossù, Maurizio

2017-01-01

Background Data from epidemiological studies investigating the prevalence and severity of malocclusions in children are of great relevance to public health programs aimed at orthodontic prevention. Previous epidemiological studies focused mainly on the adolescence age group and reported a prevalence of malocclusion with a high variability, going from 32% to 93%. Aim of our study was to assess the need for orthodontic treatment in a paediatric sample from Southern Italy in order to improve awareness among paediatricians about oral health preventive strategies in pediatric dentistry. Material and Methods The study used the IOTN-DHC index to evaluate the need for orthodontic treatment for several malocclusions (overjet, reverse overjet, overbite, openbite, crossbite) in a sample of 579 children in the 2-9 years age range. Results The most frequently altered occlusal parameter was the overbite (prevalence: 24.5%), while the occlusal anomaly that most frequently presented a need for orthodontic treatment was the crossbite (8.8%). The overall prevalence of need for orthodontic treatment was of 19.3%, while 49% of the sample showed one or more altered occlusal parameters. No statistically significant difference was found between males and females. Conclusions Results from this study support the idea that the establishment of a malocclusion is a gradual process starting at an early age. Effective orthodontic prevention programs should therefore include preschool children being aware paediatricians of the importance of early first dental visit. Key words:Orthodontic treatment, malocclusion, oral health, pediatric dentistry. PMID:28936290

21 CFR 1005.10 - Notice of sampling.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Notice of sampling. 1005.10 Section 1005.10 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) RADIOLOGICAL HEALTH IMPORTATION OF ELECTRONIC PRODUCTS Inspection and Testing § 1005.10 Notice of sampling...

'Intelligent' approach to radioimmunoassay sample counting employing a microprocessor controlled sample counter

International Nuclear Information System (INIS)

Ekins, R.P.; Sufi, S.; Malan, P.G.

1977-01-01

The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore particularly imperitive that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. The majority of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be releted to the counting errors for that sample. It is the objective of this presentation to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5-10 fold to be made. (orig.) [de

Chapter 12. Sampling and analytical methods

International Nuclear Information System (INIS)

Busenberg, E.; Plummer, L.N.; Cook, P.G.; Solomon, D.K.; Han, L.F.; Groening, M.; Oster, H.

2006-01-01

When water samples are taken for the analysis of CFCs, regardless of the sampling method used, contamination of samples by contact with atmospheric air (with its 'high' CFC concentrations) is a major concern. This is because groundwaters usually have lower CFC concentrations than those waters which have been exposed to the modern air. Some groundwaters might not contain CFCs and, therefore, are most sensitive to trace contamination by atmospheric air. Thus, extreme precautions are needed to obtain uncontaminated samples when groundwaters, particularly those with older ages, are sampled. It is recommended at the start of any CFC investigation that samples from a CFC-free source be collected and analysed, as a check upon the sampling equipment and methodology. The CFC-free source might be a deep monitoring well or, alternatively, CFC-free water could be carefully prepared in the laboratory. It is especially important that all tubing, pumps and connection that will be used in the sampling campaign be checked in this manner

Feature Extraction for Structural Dynamics Model Validation

Energy Technology Data Exchange (ETDEWEB)

Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield

2016-01-13

As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

Relationships between the Definition of the Hyperplane Width to the Fidelity of Principal Component Loading Patterns.

Science.gov (United States)

Richman, Michael B.; Gong, Xiaofeng

1999-06-01

When applying eigenanalysis, one decision analysts make is the determination of what magnitude an eigenvector coefficient (e.g., principal component (PC) loading) must achieve to be considered as physically important. Such coefficients can be displayed on maps or in a time series or tables to gain a fuller understanding of a large array of multivariate data. Previously, such a decision on what value of loading designates a useful signal (hereafter called the loading `cutoff') for each eigenvector has been purely subjective. The importance of selecting such a cutoff is apparent since those loading elements in the range of zero to the cutoff are ignored in the interpretation and naming of PCs since only the absolute values of loadings greater than the cutoff are physically analyzed. This research sets out to objectify the problem of best identifying the cutoff by application of matching between known correlation/covariance structures and their corresponding eigenpatterns, as this cutoff point (known as the hyperplane width) is varied.A Monte Carlo framework is used to resample at five sample sizes. Fourteen different hyperplane cutoff widths are tested, bootstrap resampled 50 times to obtain stable results. The key findings are that the location of an optimal hyperplane cutoff width (one which maximized the information content match between the eigenvector and the parent dispersion matrix from which it was derived) is a well-behaved unimodal function. On an individual eigenvector, this enables the unique determination of a hyperplane cutoff value to be used to separate those loadings that best reflect the relationships from those that do not. The effects of sample size on the matching accuracy are dramatic as the values for all solutions (i.e., unrotated, rotated) rose steadily from 25 through 250 observations and then weakly thereafter. The specific matching coefficients are useful to assess the penalties incurred when one analyzes eigenvector coefficients of a

Radionuclide content of local and imported cements used in Egypt

International Nuclear Information System (INIS)

Mahmoud, K R

2007-01-01

The activity concentrations of natural and artificial gamma-ray emitting radionuclides in local and imported cement have been investigated during the period from 2000 to 2003 using a 50% HPGe γ-spectroscopy system. The total numbers of local and imported samples were 29 and 8, respectively. The results showed a low activity concentration of 137 Cs in both the local and imported samples. The only exception was found in one imported Portland cement (2.8 ± 0.2 Bq kg -1 ) and one local blast furnace slag cement (1.9 ± 0.3 Bq kg -1 ). The average activity concentrations of 226 Ra, 232 Th and 40 K in local cement were 33 ± 17, 14 ± 2.4 and 45 ± 26 Bq kg -1 , respectively, whereas those in imported cement were 27 ± 7, 8 ± 7 and 134 ± 22 Bq kg -1 , respectively. The results showed that blast furnace slag cement contains the highest level of natural radioactivity, whereas white cement contains the lowest levels. The measured activity concentrations of the detected radionuclides were compared with other measurements carried out in Egypt and elsewhere. Radium-equivalent activities were also calculated to assess the radiation hazards arising from using such material in the construction of dwellings. Generally, the radium-equivalents of the analysed samples were smaller than the guideline limit of 370 Bq kg -1

CAN'T MISS--conquer any number task by making important statistics simple. Part 2. Probability, populations, samples, and normal distributions.

Science.gov (United States)

Hansen, John P

2003-01-01

Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 2, describes probability, populations, and samples. The uses of descriptive and inferential statistics are outlined. The article also discusses the properties and probability of normal distributions, including the standard normal distribution.

Effect of sample matrix composition on INAA sample weights, measurement precisions, limits of detection, and optimum conditions

International Nuclear Information System (INIS)

Guinn, V.P.; Nakazawa, L.; Leslie, J.

1984-01-01

The instrumental neutron activation analysis (INAA) Advance Prediction Computer Program (APCP) is extremely useful in guiding one to optimum subsequent experimental analyses of samples of all types of matrices. By taking into account the contributions to the cumulative Compton-continuum levels from all significant induced gamma-emitting radionuclides, it provides good INAA advance estimates of detectable photopeaks, measurement precisions, concentration lower limits of detection (LOD's) and optimum irradiation/decay/counting conditions - as well as of the very important maximum allowable sample size for each set of conditions calculated. The usefulness and importance of the four output parameters cited in the title are discussed using the INAA APCP outputs for NBS SRM-1632 Coal as the example

Importance Sampling, Large Deviations, and Differential Games

Science.gov (United States)

2002-01-01

National Science Foundation (NSF- DMS-0072004, NSF-ECS-9979250) and the Army Research Office (DAAD19-00-1-0549, DAAD19-02-1-0425). �Research of this author...supported in part by the National Science Foundation (NSF- DMS-0103669). Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting...Process. Appl., 20:213�229, 1985. [2] S. Asmussen. Risk theory in a Markovian environment. Scand. Acturial J., pages 69�100, 1989. [3] S. Asmussen, R

TSCA Chemical Data Reporting Fact Sheet: Imported Articles

Science.gov (United States)

This fact sheet provides guidance and sample reporting scenarios on the reporting exemption for the import of a chemical substance as part of an article, for purposes of the Chemical Data Reporting (CDR) rule.

VizieR Online Data Catalog: SL2S galaxy-scale sample of lens candidates (Gavazzi+, 2014)

Science.gov (United States)

Gavazzi, R.; Marshall, P. J.; Treu, T.; Sonnenfeld, A.

2017-06-01

The CFHTLS5 is a major photometric survey of more than 450 nights over 5 yr (started on 2003 June 1) using the MegaCam wide-field imager, which covers ~1 deg2 on the sky, with a pixel size of 0.186". The CFHTLS has two components aimed at extragalactic studies: a Deep component consisting of four pencil-beam fields of 1 deg2 and a wide component consisting of four mosaics covering 150 deg2 in total. Both surveys are imaged through five broadband filters. The data are pre-reduced at CFHT with the Elixir pipeline (http://www.cfht.hawaii.edu/Instruments/Elixir/), which removes the instrumental artifacts in individual exposures. The CFHTLS images are then astrometrically calibrated, photometrically inter-calibrated, resampled and stacked by the Terapix group at the Institut d'Astrophysique de Paris, and finally archived at the Canadian Astronomy Data Centre. (2 data files).

Searching for the majority: algorithms of voluntary control.

Directory of Open Access Journals (Sweden)

Jin Fan

Full Text Available Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5 and content (ratio of left and right pointing arrows within a set of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search. The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.

Partnership for Edge Physics (EPSI), University of Texas Final Report

International Nuclear Information System (INIS)

Moser, Robert; Carey, Varis; Michoski, Craig; Faghihi, Danial

2017-01-01

Simulations of tokamak plasmas require a number of inputs whose values are uncertain. The effects of these input uncertainties on the reliability of model predictions is of great importance when validating predictions by comparison to experimental observations, and when using the predictions for design and operation of devices. However, high fidelity simulation of tokamak plasmas, particular those aimed at characterization of the edge plasma physics, are computationally expensive, so lower cost surrogates are required to enable practical uncertainty estimates. Two surrogate modeling techniques have been explored in the context of tokamak plasma simulations using the XGC family of plasma simulation codes. The first is a response surface surrogate, and the second is an augmented surrogate relying on scenario extrapolation. In addition, to reduce the costs of the XGC simulations, a particle resampling algorithm was developed, which allows marker particle distributions to be adjusted to maintain optimal importance sampling. This means that the total number of particles in and therefore the cost of a simulation can be reduced while maintaining the same accuracy.

Partnership for Edge Physics (EPSI), University of Texas Final Report

Energy Technology Data Exchange (ETDEWEB)

Moser, Robert [Univ. of Texas, Austin, TX (United States); Carey, Varis [Univ. of Texas, Austin, TX (United States); Michoski, Craig [Univ. of Texas, Austin, TX (United States); Faghihi, Danial [Univ. of Texas, Austin, TX (United States)

2017-11-03

Simulations of tokamak plasmas require a number of inputs whose values are uncertain. The effects of these input uncertainties on the reliability of model predictions is of great importance when validating predictions by comparison to experimental observations, and when using the predictions for design and operation of devices. However, high fidelity simulation of tokamak plasmas, particular those aimed at characterization of the edge plasma physics, are computationally expensive, so lower cost surrogates are required to enable practical uncertainty estimates. Two surrogate modeling techniques have been explored in the context of tokamak plasma simulations using the XGC family of plasma simulation codes. The first is a response surface surrogate, and the second is an augmented surrogate relying on scenario extrapolation. In addition, to reduce the costs of the XGC simulations, a particle resampling algorithm was developed, which allows marker particle distributions to be adjusted to maintain optimal importance sampling. This means that the total number of particles in and therefore the cost of a simulation can be reduced while maintaining the same accuracy.

Verification of imported food upon import for radiation processing: Dried herbs, including herbs used in food supplements, and spices by PSL and TL

International Nuclear Information System (INIS)

Boniglia, C.; Aureli, P.; Bortolin, E.; Onori, S.

2009-01-01

The Italian National Institute of Health in 2005-2006 performed an analytical survey of import on dried spices and herbs, including herbs used in food supplements, to investigate the entry in Italy of irradiated, and not correctly labelled, raw materials. In this survey, 52 samples, including nine herbal extracts, were collected. The method of photo-stimulated luminescence (PSL) was applied to all samples and only samples screened positive or intermediate with PSL were analysed by using the thermo-luminescence (TL) method. Out of the 12 samples screened positive or intermediate with PSL, the TL method confirmed irradiation of five samples (10% of the total assayed samples). One out of these five samples was a herbal supplement whereas three were herbal extracts that are known to be used as ingredients of herbal supplements, and another one was a spice.

Verification of imported food upon import for radiation processing: Dried herbs, including herbs used in food supplements, and spices by PSL and TL

Energy Technology Data Exchange (ETDEWEB)

Boniglia, C. [Department of Veterinary Public Health and Food Safety, Istituto Superiore di Sanita, Rome (Italy)], E-mail: concetta.boniglia@iss.it; Aureli, P. [Department of Veterinary Public Health and Food Safety, Istituto Superiore di Sanita, Rome (Italy); Bortolin, E.; Onori, S. [Department of Technology and Health, Istituto Superiore di Sanita, Rome (Italy)

2009-07-15

The Italian National Institute of Health in 2005-2006 performed an analytical survey of import on dried spices and herbs, including herbs used in food supplements, to investigate the entry in Italy of irradiated, and not correctly labelled, raw materials. In this survey, 52 samples, including nine herbal extracts, were collected. The method of photo-stimulated luminescence (PSL) was applied to all samples and only samples screened positive or intermediate with PSL were analysed by using the thermo-luminescence (TL) method. Out of the 12 samples screened positive or intermediate with PSL, the TL method confirmed irradiation of five samples (10% of the total assayed samples). One out of these five samples was a herbal supplement whereas three were herbal extracts that are known to be used as ingredients of herbal supplements, and another one was a spice.

1986 imports and exports of radionuclides

International Nuclear Information System (INIS)

Anon.

1987-01-01

The statistics compiled by the German Federal Office for Industry (Bundesamt fuer Wirtschaft), on behalf of the Federal Ministry for the Environment, Protection of Nature, and Reactor Safety, of the imports and exports of radionuclides, irradiation samples, and sealed emitters of more than 1850 GBq show an enormous increase by 152.7% of imports (on the basis of activity) and a decline by 19.5% of exports. In the category of imports, some 98% of the total activity were made up of the H-3, Co-60, Mo-99, and Ir-192 nuclides. In the category of sealed emitters, the imports of Co-60 have trebled. In the exports category, more than 95% of the total activity were made up of the H-3, Mo-99, and Ir-192 nuclides. In the category of sealed emitters, exports of Cs-137 experienced a fourfold increase over the level of the previous year. (orig.) [de

Network Sampling with Memory: A proposal for more efficient sampling from social networks

Science.gov (United States)

Mouw, Ted; Verdery, Ashton M.

2013-01-01

Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

Gaussian Process Interpolation for Uncertainty Estimation in Image Registration

Science.gov (United States)

Wachinger, Christian; Golland, Polina; Reuter, Martin; Wells, William

2014-01-01

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods. PMID:25333127

Control charts for location based on different sampling schemes

NARCIS (Netherlands)

Mehmood, R.; Riaz, M.; Does, R.J.M.M.

2013-01-01

Control charts are the most important statistical process control tool for monitoring variations in a process. A number of articles are available in the literature for the X̄ control chart based on simple random sampling, ranked set sampling, median-ranked set sampling (MRSS), extreme-ranked set

Importance of participation rate in sampling of data in population based studies, with special reference to bone mass in Sweden.

OpenAIRE

Düppe, H; Gärdsell, P; Hanson, B S; Johnell, O; Nilsson, B E

1996-01-01

OBJECTIVE: To study the effects of participation rate in sampling on "normative" bone mass data. DESIGN: This was a comparison between two randomly selected samples from the same population. The participation rates in the two samples were 61.9% and 83.6%. Measurements were made of bone mass at different skeletal sites and of muscle strength, as well as an assessment of physical activity. SETTING: Malmö, Sweden. SUBJECTS: There were 230 subjects (117 men, 113 women), aged 21 to 42 years. RESUL...

Sample size determination in clinical trials with multiple endpoints

CERN Document Server

Sozu, Takashi; Hamasaki, Toshimitsu; Evans, Scott R

2015-01-01

This book integrates recent methodological developments for calculating the sample size and power in trials with more than one endpoint considered as multiple primary or co-primary, offering an important reference work for statisticians working in this area. The determination of sample size and the evaluation of power are fundamental and critical elements in the design of clinical trials. If the sample size is too small, important effects may go unnoticed; if the sample size is too large, it represents a waste of resources and unethically puts more participants at risk than necessary. Recently many clinical trials have been designed with more than one endpoint considered as multiple primary or co-primary, creating a need for new approaches to the design and analysis of these clinical trials. The book focuses on the evaluation of power and sample size determination when comparing the effects of two interventions in superiority clinical trials with multiple endpoints. Methods for sample size calculation in clin...

Advanced pressure tube sampling tools

International Nuclear Information System (INIS)

Wittich, K.C.; King, J.M.

2002-01-01

Deuterium concentration is an important parameter that must be assessed to evaluate the Fitness for service of CANDU pressure tubes. In-reactor pressure tube sampling allows accurate deuterium concentration assessment to be made without the expenses associated with fuel channel removal. This technology, which AECL has developed over the past fifteen years, has become the standard method for deuterium concentration assessment. AECL is developing a multi-head tool that would reduce in-reactor handling overhead by allowing one tool to sequentially sample at all four axial pressure tube locations before removal from the reactor. Four sets of independent cutting heads, like those on the existing sampling tools, facilitate this incorporating proven technology demonstrated in over 1400 in-reactor samples taken to date. The multi-head tool is delivered by AECL's Advanced Delivery Machine or other similar delivery machines. Further, AECL has developed an automated sample handling system that receives and processes the tool once out of the reactor. This system retrieves samples from the tool, dries, weighs and places them in labelled vials which are then directed into shielded shipping flasks. The multi-head wet sampling tool and the automated sample handling system are based on proven technology and offer continued savings and dose reduction to utilities in a competitive electricity market. (author)

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models.

Science.gov (United States)

Blutke, Andreas; Wanke, Rüdiger

2018-03-06

In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of genetically modified pig models, and the often-limited number of available animals of these models, establishment of (biobank) collections of adequately processed tissue samples suited for a broad spectrum of subsequent analyses methods, including analyses not specified at the time point of sampling, represent meaningful approaches to take full advantage of the translational value of the model. With respect to the peculiarities of porcine anatomy, comprehensive guidelines have recently been established for standardized generation of representative, high-quality samples from different porcine organs and tissues. These guidelines are essential prerequisites for the reproducibility of results and their comparability between different studies and investigators. The recording of basic data, such as organ weights and volumes, the determination of the sampling locations and of the numbers of tissue samples to be generated, as well as their orientation, size, processing and trimming directions, are relevant factors determining the generalizability and usability of the specimen for molecular, qualitative, and quantitative morphological analyses. Here, an illustrative, practical, step-by-step demonstration of the most important techniques for generation of representative, multi-purpose biobank specimen from porcine tissues is presented. The methods described here include determination of organ/tissue volumes and densities, the application of a volume-weighted systematic random sampling procedure for parenchymal organs by point-counting, determination of the extent of tissue shrinkage related to histological embedding of samples, and generation of randomly oriented samples for quantitative stereological analyses, such as isotropic uniform random (IUR) sections generated by the "Orientator" and "Isector" methods, and vertical

The effect of biotope-specific sampling for aquatic ...

African Journals Online (AJOL)

The effect of biotope-specific sampling for aquatic macroinvertebrates on ... riffle), depth, and quality (deposition of silt on stones), were important at habitat scale. ... Geological type, which affects overall water chemistry, was important in the ...

A recursive Monte Carlo method for estimating importance functions in deep penetration problems

International Nuclear Information System (INIS)

Goldstein, M.

1980-04-01

A pratical recursive Monte Carlo method for estimating the importance function distribution, aimed at importance sampling for the solution of deep penetration problems in three-dimensional systems, was developed. The efficiency of the recursive method was investigated for sample problems including one- and two-dimensional, monoenergetic and and multigroup problems, as well as for a practical deep-penetration problem with streaming. The results of the recursive Monte Carlo calculations agree fairly well with Ssub(n) results. It is concluded that the recursive Monte Carlo method promises to become a universal method for estimating the importance function distribution for the solution of deep-penetration problems, in all kinds of systems: for many systems the recursive method is likely to be more efficient than previously existing methods; for three-dimensional systems it is the first method that can estimate the importance function with the accuracy required for an efficient solution based on importance sampling of neutron deep-penetration problems in those systems

Attenuation of species abundance distributions by sampling

Science.gov (United States)

Shimadzu, Hideyasu; Darnell, Ross

2015-01-01

Quantifying biodiversity aspects such as species presence/ absence, richness and abundance is an important challenge to answer scientific and resource management questions. In practice, biodiversity can only be assessed from biological material taken by surveys, a difficult task given limited time and resources. A type of random sampling, or often called sub-sampling, is a commonly used technique to reduce the amount of time and effort for investigating large quantities of biological samples. However, it is not immediately clear how (sub-)sampling affects the estimate of biodiversity aspects from a quantitative perspective. This paper specifies the effect of (sub-)sampling as attenuation of the species abundance distribution (SAD), and articulates how the sampling bias is induced to the SAD by random sampling. The framework presented also reveals some confusion in previous theoretical studies. PMID:26064626

[Progress in sample preparation and analytical methods for trace polar small molecules in complex samples].

Science.gov (United States)

Zhang, Qianchun; Luo, Xialin; Li, Gongke; Xiao, Xiaohua

2015-09-01

Small polar molecules such as nucleosides, amines, amino acids are important analytes in biological, food, environmental, and other fields. It is necessary to develop efficient sample preparation and sensitive analytical methods for rapid analysis of these polar small molecules in complex matrices. Some typical materials in sample preparation, including silica, polymer, carbon, boric acid and so on, are introduced in this paper. Meanwhile, the applications and developments of analytical methods of polar small molecules, such as reversed-phase liquid chromatography, hydrophilic interaction chromatography, etc., are also reviewed.

Efficient Unbiased Rendering using Enlightened Local Path Sampling

DEFF Research Database (Denmark)

Kristensen, Anders Wang

measurements, which are the solution to the adjoint light transport problem. The second is a representation of the distribution of radiance and importance in the scene. We also derive a new method of particle sampling, which is advantageous compared to existing methods. Together we call the resulting algorithm....... The downside to using these algorithms is that they can be slow to converge. Due to the nature of Monte Carlo methods, the results are random variables subject to variance. This manifests itself as noise in the images, which can only be reduced by generating more samples. The reason these methods are slow...... is because of a lack of eeffective methods of importance sampling. Most global illumination algorithms are based on local path sampling, which is essentially a recipe for constructing random walks. Using this procedure paths are built based on information given explicitly as part of scene description...

Evaluation of common methods for sampling invertebrate pollinator assemblages: net sampling out-perform pan traps.

Science.gov (United States)

Popic, Tony J; Davila, Yvonne C; Wardle, Glenda M

2013-01-01

Methods for sampling ecological assemblages strive to be efficient, repeatable, and representative. Unknowingly, common methods may be limited in terms of revealing species function and so of less value for comparative studies. The global decline in pollination services has stimulated surveys of flower-visiting invertebrates, using pan traps and net sampling. We explore the relative merits of these two methods in terms of species discovery, quantifying abundance, function, and composition, and responses of species to changing floral resources. Using a spatially-nested design we sampled across a 5000 km(2) area of arid grasslands, including 432 hours of net sampling and 1296 pan trap-days, between June 2010 and July 2011. Net sampling yielded 22% more species and 30% higher abundance than pan traps, and better reflected the spatio-temporal variation of floral resources. Species composition differed significantly between methods; from 436 total species, 25% were sampled by both methods, 50% only by nets, and the remaining 25% only by pans. Apart from being less comprehensive, if pan traps do not sample flower-visitors, the link to pollination is questionable. By contrast, net sampling functionally linked species to pollination through behavioural observations of flower-visitation interaction frequency. Netted specimens are also necessary for evidence of pollen transport. Benefits of net-based sampling outweighed minor differences in overall sampling effort. As pan traps and net sampling methods are not equivalent for sampling invertebrate-flower interactions, we recommend net sampling of invertebrate pollinator assemblages, especially if datasets are intended to document declines in pollination and guide measures to retain this important ecosystem service.