Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants

PubMed Central

Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

2016-01-01

The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants. PMID:27304876

Evaluation of the Environmental DNA Method for Estimating Distribution and Biomass of Submerged Aquatic Plants.

PubMed

Matsuhashi, Saeko; Doi, Hideyuki; Fujiwara, Ayaka; Watanabe, Sonoko; Minamoto, Toshifumi

2016-01-01

The environmental DNA (eDNA) method has increasingly been recognized as a powerful tool for monitoring aquatic animal species; however, its application for monitoring aquatic plants is limited. To evaluate eDNA analysis for estimating the distribution of aquatic plants, we compared its estimated distributions with eDNA analysis, visual observation, and past distribution records for the submerged species Hydrilla verticillata. Moreover, we conducted aquarium experiments using H. verticillata and Egeria densa and analyzed the relationships between eDNA concentrations and plant biomass to investigate the potential for biomass estimation. The occurrences estimated by eDNA analysis closely corresponded to past distribution records, and eDNA detections were more frequent than visual observations, indicating that the method is potentially more sensitive. The results of the aquarium experiments showed a positive relationship between plant biomass and eDNA concentration; however, the relationship was not always significant. The eDNA concentration peaked within three days of the start of the experiment in most cases, suggesting that plants do not release constant amounts of DNA. These results showed that eDNA analysis can be used for distribution surveys, and has the potential to estimate the biomass of aquatic plants.

Performance analysis of a brushless dc motor due to magnetization distribution in a continuous ring magnet

NASA Astrophysics Data System (ADS)

Hur, Jin; Jung, In-Soung; Sung, Ha-Gyeong; Park, Soon-Sup

2003-05-01

This paper represents the force performance of a brushless dc motor with a continuous ring-type permanent magnet (PM), considering its magnetization patterns: trapezoidal, trapezoidal with dead zone, and unbalanced trapezoidal magnetization with dead zone. The radial force density in PM motor causes vibration, because vibration is induced the traveling force from the rotating PM acting on the stator. Magnetization distribution of the PM as well as the shape of the teeth determines the distribution of force density. In particular, the distribution has a three-dimensional (3-D) pattern because of overhang, that is, it is not uniform in axial direction. Thus, the analysis of radial force density required dynamic analysis considering the 3-D shape of the teeth and overhang. The results show that the force density as a source of vibration varies considerably depending on the overhang and magnetization distribution patterns. In addition, the validity of the developed method, coupled 3-D equivalent magnetic circuit network method, with driving circuit and motion equation, is confirmed by comparison of conventional method using 3D finite element method.

An investigation on the intra-sample distribution of cotton color by using image analysis

USDA-ARS?s Scientific Manuscript database

The colorimeter principle is widely used to measure cotton color. This method provides the sample’s color grade; but the result does not include information about the color distribution and any variation within the sample. We conducted an investigation that used image analysis method to study the ...

Cooling of Gas Turbines. 6; Computed Temperature Distribution Through Cross Section of Water-Cooled Turbine Blade

NASA Technical Reports Server (NTRS)

Livingood, John N. B.; Sams, Eldon W.

1947-01-01

A theoretical analysis of the cross-sectional temperature distribution of a water-cooled turbine blade was made using the relaxation method to solve the differential equation derived from the analysis. The analysis was applied to specific turbine blade and the studies icluded investigations of the accuracy of simple methods to determine the temperature distribution along the mean line of the rear part of the blade, of the possible effect of varying the perimetric distribution of the hot gas-to -metal heat transfer coefficient, and of the effect of changing the thermal conductivity of the blade metal for a constant cross sectional area blade with two quarter inch diameter coolant passages.

Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).

PubMed

Kwon, Deukwoo; Reis, Isildinha M

2015-08-12

When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.

Mixture distributions of wind speed in the UAE

NASA Astrophysics Data System (ADS)

Shin, J.; Ouarda, T.; Lee, T. S.

2013-12-01

Wind speed probability distribution is commonly used to estimate potential wind energy. The 2-parameter Weibull distribution has been most widely used to characterize the distribution of wind speed. However, it is unable to properly model wind speed regimes when wind speed distribution presents bimodal and kurtotic shapes. Several studies have concluded that the Weibull distribution should not be used for frequency analysis of wind speed without investigation of wind speed distribution. Due to these mixture distributional characteristics of wind speed data, the application of mixture distributions should be further investigated in the frequency analysis of wind speed. A number of studies have investigated the potential wind energy in different parts of the Arabian Peninsula. Mixture distributional characteristics of wind speed were detected from some of these studies. Nevertheless, mixture distributions have not been employed for wind speed modeling in the Arabian Peninsula. In order to improve our understanding of wind energy potential in Arabian Peninsula, mixture distributions should be tested for the frequency analysis of wind speed. The aim of the current study is to assess the suitability of mixture distributions for the frequency analysis of wind speed in the UAE. Hourly mean wind speed data at 10-m height from 7 stations were used in the current study. The Weibull and Kappa distributions were employed as representatives of the conventional non-mixture distributions. 10 mixture distributions are used and constructed by mixing four probability distributions such as Normal, Gamma, Weibull and Extreme value type-one (EV-1) distributions. Three parameter estimation methods such as Expectation Maximization algorithm, Least Squares method and Meta-Heuristic Maximum Likelihood (MHML) method were employed to estimate the parameters of the mixture distributions. In order to compare the goodness-of-fit of tested distributions and parameter estimation methods for sample wind data, the adjusted coefficient of determination, Bayesian Information Criterion (BIC) and Chi-squared statistics were computed. Results indicate that MHML presents the best performance of parameter estimation for the used mixture distributions. In most of the employed 7 stations, mixture distributions give the best fit. When the wind speed regime shows mixture distributional characteristics, most of these regimes present the kurtotic statistical characteristic. Particularly, applications of mixture distributions for these stations show a significant improvement in explaining the whole wind speed regime. In addition, the Weibull-Weibull mixture distribution presents the best fit for the wind speed data in the UAE.

Influence of the Redundant Verification and the Non-Redundant Verification on the Hydraulic Tomography

NASA Astrophysics Data System (ADS)

Wei, T. B.; Chen, Y. L.; Lin, H. R.; Huang, S. Y.; Yeh, T. C. J.; Wen, J. C.

2016-12-01

In the groundwater study, it estimated the heterogeneous spatial distribution of hydraulic Properties, there were many scholars use to hydraulic tomography (HT) from field site pumping tests to estimate inverse of heterogeneous spatial distribution of hydraulic Properties, to prove the most of most field site aquifer was heterogeneous hydrogeological parameters spatial distribution field. Many scholars had proposed a method of hydraulic tomography to estimate heterogeneous spatial distribution of hydraulic Properties of aquifer, the Huang et al. [2011] was used the non-redundant verification analysis of pumping wells changed, observation wells fixed on the inverse and the forward, to reflect the feasibility of the heterogeneous spatial distribution of hydraulic Properties of field site aquifer of the non-redundant verification analysis on steady-state model.From post literature, finding only in steady state, non-redundant verification analysis of pumping well changed location and observation wells fixed location for inverse and forward. But the studies had not yet pumping wells fixed or changed location, and observation wells fixed location for redundant verification or observation wells change location for non-redundant verification of the various combinations may to explore of influences of hydraulic tomography method. In this study, it carried out redundant verification method and non-redundant verification method for forward to influences of hydraulic tomography method in transient. And it discuss above mentioned in NYUST campus sites the actual case, to prove the effectiveness of hydraulic tomography methods, and confirmed the feasibility on inverse and forward analysis from analysis results.Keywords: Hydraulic Tomography, Redundant Verification, Heterogeneous, Inverse, Forward

Computational Analysis of the Caenorhabditis elegans Germline to Study the Distribution of Nuclei, Proteins, and the Cytoskeleton.

PubMed

Gopal, Sandeep; Pocock, Roger

2018-04-19

The Caenorhabditis elegans (C. elegans) germline is used to study several biologically important processes including stem cell development, apoptosis, and chromosome dynamics. While the germline is an excellent model, the analysis is often two dimensional due to the time and labor required for three-dimensional analysis. Major readouts in such studies are the number/position of nuclei and protein distribution within the germline. Here, we present a method to perform automated analysis of the germline using confocal microscopy and computational approaches to determine the number and position of nuclei in each region of the germline. Our method also analyzes germline protein distribution that enables the three-dimensional examination of protein expression in different genetic backgrounds. Further, our study shows variations in cytoskeletal architecture in distinct regions of the germline that may accommodate specific spatial developmental requirements. Finally, our method enables automated counting of the sperm in the spermatheca of each germline. Taken together, our method enables rapid and reproducible phenotypic analysis of the C. elegans germline.

Characterizing property distributions of polymeric nanogels by size-exclusion chromatography.

PubMed

Mourey, Thomas H; Leon, Jeffrey W; Bennett, James R; Bryan, Trevor G; Slater, Lisa A; Balke, Stephen T

2007-03-30

Nanogels are highly branched, swellable polymer structures with average diameters between 1 and 100nm. Size-exclusion chromatography (SEC) fractionates materials in this size range, and it is commonly used to measure nanogel molar mass distributions. For many nanogel applications, it may be more important to calculate the particle size distribution from the SEC data than it is to calculate the molar mass distribution. Other useful nanogel property distributions include particle shape, area, and volume, as well as polymer volume fraction per particle. All can be obtained from multi-detector SEC data with proper calibration and data analysis methods. This work develops the basic equations for calculating several of these differential and cumulative property distributions and applies them to SEC data from the analysis of polymeric nanogels. The methods are analogous to those used to calculate the more familiar SEC molar mass distributions. Calibration methods and characteristics of the distributions are discussed, and the effects of detector noise and mismatched concentration and molar mass sensitive detector signals are examined.

Quantitative characterization of the spatial distribution of particles in materials: Application to materials processing

NASA Technical Reports Server (NTRS)

Parse, Joseph B.; Wert, J. A.

1991-01-01

Inhomogeneities in the spatial distribution of second phase particles in engineering materials are known to affect certain mechanical properties. Progress in this area has been hampered by the lack of a convenient method for quantitative description of the spatial distribution of the second phase. This study intends to develop a broadly applicable method for the quantitative analysis and description of the spatial distribution of second phase particles. The method was designed to operate on a desktop computer. The Dirichlet tessellation technique (geometrical method for dividing an area containing an array of points into a set of polygons uniquely associated with the individual particles) was selected as the basis of an analysis technique implemented on a PC. This technique is being applied to the production of Al sheet by PM processing methods; vacuum hot pressing, forging, and rolling. The effect of varying hot working parameters on the spatial distribution of aluminum oxide particles in consolidated sheet is being studied. Changes in distributions of properties such as through-thickness near-neighbor distance correlate with hot-working reduction.

The border-to-border distribution method for analysis of cytoplasmic particles and organelles.

PubMed

Yacovone, Shalane K; Ornelles, David A; Lyles, Douglas S

2016-02-01

Comparing the distribution of cytoplasmic particles and organelles between different experimental conditions can be challenging due to the heterogeneous nature of cell morphologies. The border-to-border distribution method was created to enable the quantitative analysis of fluorescently labeled cytoplasmic particles and organelles of multiple cells from images obtained by confocal microscopy. The method consists of four steps: (1) imaging of fluorescently labeled cells, (2) division of the image of the cytoplasm into radial segments, (3) selection of segments of interest, and (4) population analysis of fluorescence intensities at the pixel level either as a function of distance along the selected radial segments or as a function of angle around an annulus. The method was validated using the well-characterized effect of brefeldin A (BFA) on the distribution of the vesicular stomatitis virus G protein, in which intensely labeled Golgi membranes are redistributed within the cytoplasm. Surprisingly, in untreated cells, the distribution of fluorescence in Golgi membrane-containing radial segments was similar to the distribution of fluorescence in other G protein-containing segments, indicating that the presence of Golgi membranes did not shift the distribution of G protein towards the nucleus compared to the distribution of G protein in other regions of the cell. Treatment with BFA caused only a slight shift in the distribution of the brightest G protein-containing segments which had a distribution similar to that in untreated cells. Instead, the major effect of BFA was to alter the annular distribution of G protein in the perinuclear region.

Stress analysis of ribbon parachutes

NASA Technical Reports Server (NTRS)

Reynolds, D. T.; Mullins, W. M.

1975-01-01

An analytical method has been developed for determining the internal load distribution for ribbon parachutes subjected to known riser and aerodynamic forces. Finite elements with non-linear elastic properties represent the parachute structure. This method is an extension of the analysis previously developed by the authors and implemented in the digital computer program CANO. The present analysis accounts for the effect of vertical ribbons in the solution for canopy shape and stress distribution. Parametric results are presented which relate the canopy stress distribution to such factors as vertical ribbon strength, number of gores, and gore shape in a ribbon parachute.

Analysis of temperature rise for piezoelectric transformer using finite-element method.

PubMed

Joo, Hyun-Woo; Lee, Chang-Hwan; Rho, Jong-Seok; Jung, Hyun-Kyo

2006-08-01

Analysis of heat problem and temperature field of a piezoelectric transformer, operated at steady-state conditions, is described. The resonance frequency of the transformer is calculated from impedance and electrical gain analysis using a finite-element method. Mechanical displacement and electric potential of the transformer at the calculated resonance frequency are used to calculate the loss distribution of the transformer. Temperature distribution using discretized heat transfer equation is calculated from the obtained losses of the transformer. Properties of the piezoelectric material, dependent on the temperature field, are measured to recalculate the losses, temperature distribution, and new resonance characteristics of the transformer. Iterative method is adopted to recalculate the losses and resonance frequency due to the changes of the material constants from temperature increase. Computed temperature distributions and new resonance characteristics of the transformer at steady-state temperature are verified by comparison with experimental results.

Comparative analysis of ferroelectric domain statistics via nonlinear diffraction in random nonlinear materials.

PubMed

Wang, B; Switowski, K; Cojocaru, C; Roppo, V; Sheng, Y; Scalora, M; Kisielewski, J; Pawlak, D; Vilaseca, R; Akhouayri, H; Krolikowski, W; Trull, J

2018-01-22

We present an indirect, non-destructive optical method for domain statistic characterization in disordered nonlinear crystals having homogeneous refractive index and spatially random distribution of ferroelectric domains. This method relies on the analysis of the wave-dependent spatial distribution of the second harmonic, in the plane perpendicular to the optical axis in combination with numerical simulations. We apply this technique to the characterization of two different media, Calcium Barium Niobate and Strontium Barium Niobate, with drastically different statistical distributions of ferroelectric domains.

Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis

PubMed Central

Turner, Rebecca M; Jackson, Dan; Wei, Yinghui; Thompson, Simon G; Higgins, Julian P T

2015-01-01

Numerous meta-analyses in healthcare research combine results from only a small number of studies, for which the variance representing between-study heterogeneity is estimated imprecisely. A Bayesian approach to estimation allows external evidence on the expected magnitude of heterogeneity to be incorporated. The aim of this paper is to provide tools that improve the accessibility of Bayesian meta-analysis. We present two methods for implementing Bayesian meta-analysis, using numerical integration and importance sampling techniques. Based on 14 886 binary outcome meta-analyses in the Cochrane Database of Systematic Reviews, we derive a novel set of predictive distributions for the degree of heterogeneity expected in 80 settings depending on the outcomes assessed and comparisons made. These can be used as prior distributions for heterogeneity in future meta-analyses. The two methods are implemented in R, for which code is provided. Both methods produce equivalent results to standard but more complex Markov chain Monte Carlo approaches. The priors are derived as log-normal distributions for the between-study variance, applicable to meta-analyses of binary outcomes on the log odds-ratio scale. The methods are applied to two example meta-analyses, incorporating the relevant predictive distributions as prior distributions for between-study heterogeneity. We have provided resources to facilitate Bayesian meta-analysis, in a form accessible to applied researchers, which allow relevant prior information on the degree of heterogeneity to be incorporated. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:25475839

Methods for Determining Particle Size Distributions from Nuclear Detonations.

DTIC Science & Technology

1987-03-01

Debris . . . 30 IV. Summary of Sample Preparation Method . . . . 35 V. Set Parameters for PCS ... ........... 39 VI. Analysis by Vendors...54 XV. Results From Brookhaven Analysis Using The Method of Cumulants ... ........... . 54 XVI. Results From Brookhaven Analysis of Sample...R-3 Using Histogram Method ......... .55 XVII. Results From Brookhaven Analysis of Sample R-8 Using Histogram Method ........... 56 XVIII.TEM Particle

Lognormal Approximations of Fault Tree Uncertainty Distributions.

PubMed

El-Shanawany, Ashraf Ben; Ardron, Keith H; Walker, Simon P

2018-01-26

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks's method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models. © 2018 Society for Risk Analysis.

Power in Bayesian Mediation Analysis for Small Sample Research

PubMed Central

Miočević, Milica; MacKinnon, David P.; Levy, Roy

2018-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results. PMID:29662296

Power in Bayesian Mediation Analysis for Small Sample Research.

PubMed

Miočević, Milica; MacKinnon, David P; Levy, Roy

2017-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results.

Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

PubMed Central

Lee, Eun Gyung; Kim, Seung Won; Feigley, Charles E.; Harper, Martin

2015-01-01

This study introduces two semi-quantitative methods, Structured Subjective Assessment (SSA) and Control of Substances Hazardous to Health (COSHH) Essentials, in conjunction with two-dimensional Monte Carlo simulations for determining prior probabilities. Prior distribution using expert judgment was included for comparison. Practical applications of the proposed methods were demonstrated using personal exposure measurements of isoamyl acetate in an electronics manufacturing facility and of isopropanol in a printing shop. Applicability of these methods in real workplaces was discussed based on the advantages and disadvantages of each method. Although these methods could not be completely independent of expert judgments, this study demonstrated a methodological improvement in the estimation of the prior distribution for the Bayesian decision analysis tool. The proposed methods provide a logical basis for the decision process by considering determinants of worker exposure. PMID:23252451

Robust Mediation Analysis Based on Median Regression

PubMed Central

Yuan, Ying; MacKinnon, David P.

2014-01-01

Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925

Powerlaw: a Python package for analysis of heavy-tailed distributions.

PubMed

Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

2014-01-01

Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible.

Representing distributed cognition in complex systems: how a submarine returns to periscope depth.

PubMed

Stanton, Neville A

2014-01-01

This paper presents the Event Analysis of Systemic Teamwork (EAST) method as a means of modelling distributed cognition in systems. The method comprises three network models (i.e. task, social and information) and their combination. This method was applied to the interactions between the sound room and control room in a submarine, following the activities of returning the submarine to periscope depth. This paper demonstrates three main developments in EAST. First, building the network models directly, without reference to the intervening methods. Second, the application of analysis metrics to all three networks. Third, the combination of the aforementioned networks in different ways to gain a broader understanding of the distributed cognition. Analyses have shown that EAST can be used to gain both qualitative and quantitative insights into distributed cognition. Future research should focus on the analyses of network resilience and modelling alternative versions of a system.

About normal distribution on SO(3) group in texture analysis

NASA Astrophysics Data System (ADS)

Savyolova, T. I.; Filatov, S. V.

2017-12-01

This article studies and compares different normal distributions (NDs) on SO(3) group, which are used in texture analysis. Those NDs are: Fisher normal distribution (FND), Bunge normal distribution (BND), central normal distribution (CND) and wrapped normal distribution (WND). All of the previously mentioned NDs are central functions on SO(3) group. CND is a subcase for normal CLT-motivated distributions on SO(3) (CLT here is Parthasarathy’s central limit theorem). WND is motivated by CLT in R 3 and mapped to SO(3) group. A Monte Carlo method for modeling normally distributed values was studied for both CND and WND. All of the NDs mentioned above are used for modeling different components of crystallites orientation distribution function in texture analysis.

Approximations to the distribution of a test statistic in covariance structure analysis: A comprehensive study.

PubMed

Wu, Hao

2018-05-01

In structural equation modelling (SEM), a robust adjustment to the test statistic or to its reference distribution is needed when its null distribution deviates from a χ 2 distribution, which usually arises when data do not follow a multivariate normal distribution. Unfortunately, existing studies on this issue typically focus on only a few methods and neglect the majority of alternative methods in statistics. Existing simulation studies typically consider only non-normal distributions of data that either satisfy asymptotic robustness or lead to an asymptotic scaled χ 2 distribution. In this work we conduct a comprehensive study that involves both typical methods in SEM and less well-known methods from the statistics literature. We also propose the use of several novel non-normal data distributions that are qualitatively different from the non-normal distributions widely used in existing studies. We found that several under-studied methods give the best performance under specific conditions, but the Satorra-Bentler method remains the most viable method for most situations. © 2017 The British Psychological Society.

Noise deconvolution based on the L1-metric and decomposition of discrete distributions of postsynaptic responses.

PubMed

Astrelin, A V; Sokolov, M V; Behnisch, T; Reymann, K G; Voronin, L L

1997-04-25

A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.

Application of the variational-asymptotical method to composite plates

NASA Technical Reports Server (NTRS)

Hodges, Dewey H.; Lee, Bok W.; Atilgan, Ali R.

1992-01-01

A method is developed for the 3D analysis of laminated plate deformation which is an extension of a variational-asymptotical method by Atilgan and Hodges (1991). Both methods are based on the treatment of plate deformation by splitting the 3D analysis into linear through-the-thickness analysis and 2D plate analysis. Whereas the first technique tackles transverse shear deformation in the second asymptotical approximation, the present method simplifies its treatment and restricts it to the first approximation. Both analytical techniques are applied to the linear cylindrical bending problem, and the strain and stress distributions are derived and compared with those of the exact solution. The present theory provides more accurate results than those of the classical laminated-plate theory for the transverse displacement of 2-, 3-, and 4-layer cross-ply laminated plates. The method can give reliable estimates of the in-plane strain and displacement distributions.

Entropy Methods For Univariate Distributions in Decision Analysis

NASA Astrophysics Data System (ADS)

Abbas, Ali E.

2003-03-01

One of the most important steps in decision analysis practice is the elicitation of the decision-maker's belief about an uncertainty of interest in the form of a representative probability distribution. However, the probability elicitation process is a task that involves many cognitive and motivational biases. Alternatively, the decision-maker may provide other information about the distribution of interest, such as its moments, and the maximum entropy method can be used to obtain a full distribution subject to the given moment constraints. In practice however, decision makers cannot readily provide moments for the distribution, and are much more comfortable providing information about the fractiles of the distribution of interest or bounds on its cumulative probabilities. In this paper we present a graphical method to determine the maximum entropy distribution between upper and lower probability bounds and provide an interpretation for the shape of the maximum entropy distribution subject to fractile constraints, (FMED). We also discuss the problems with the FMED in that it is discontinuous and flat over each fractile interval. We present a heuristic approximation to a distribution if in addition to its fractiles, we also know it is continuous and work through full examples to illustrate the approach.

Fractal analysis of the dark matter and gas distributions in the Mare-Nostrum universe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaite, José, E-mail: jose.gaite@upm.es

2010-03-01

We develop a method of multifractal analysis of N-body cosmological simulations that improves on the customary counts-in-cells method by taking special care of the effects of discreteness and large scale homogeneity. The analysis of the Mare-Nostrum simulation with our method provides strong evidence of self-similar multifractal distributions of dark matter and gas, with a halo mass function that is of Press-Schechter type but has a power-law exponent -2, as corresponds to a multifractal. Furthermore, our analysis shows that the dark matter and gas distributions are indistinguishable as multifractals. To determine if there is any gas biasing, we calculate the cross-correlationmore » coefficient, with negative but inconclusive results. Hence, we develop an effective Bayesian analysis connected with information theory, which clearly demonstrates that the gas is biased in a long range of scales, up to the scale of homogeneity. However, entropic measures related to the Bayesian analysis show that this gas bias is small (in a precise sense) and is such that the fractal singularities of both distributions coincide and are identical. We conclude that this common multifractal cosmic web structure is determined by the dynamics and is independent of the initial conditions.« less

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

Distribution of localized states from fine analysis of electron spin resonance spectra of organic semiconductors: Physical meaning and methodology

NASA Astrophysics Data System (ADS)

Mishchenko, Andrey S.; Matsui, Hiroyuki; Hasegawa, Tatsuo

2012-02-01

We develop an analytical method for the processing of electron spin resonance (ESR) spectra. The goal is to obtain the distributions of trapped carriers over both their degree of localization and their binding energy in semiconductor crystals or films composed of regularly aligned organic molecules [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.104.056602 104, 056602 (2010)]. Our method has two steps. We first carry out a fine analysis of the shape of the ESR spectra due to the trapped carriers; this reveals the distribution of the trap density of the states over the degree of localization. This analysis is based on the reasonable assumption that the linewidth of the trapped carriers is predetermined by their degree of localization because of the hyperfine mechanism. We then transform the distribution over the degree of localization into a distribution over the binding energies. The transformation uses the relationships between the binding energies and the localization parameters of the trapped carriers. The particular relation for the system under study is obtained by the Holstein model for trapped polarons using a diagrammatic Monte Carlo analysis. We illustrate the application of the method to pentacene organic thin-film transistors.

Application of the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

A Monte Carlo experiment was conducted to investigate the performance of bootstrap methods in normal theory maximum likelihood factor analysis when the distributional assumption was satisfied or unsatisfied. Problems arising with the use of bootstrap methods are highlighted. (SLD)

Preliminary evaluation of diabatic heating distribution from FGGE level 3b analysis data

NASA Technical Reports Server (NTRS)

Kasahara, A.; Mizzi, A. P.

1985-01-01

A method is presented for calculating the global distribution of diabatic heating rate. Preliminary results of global heating rate evaluated from the European center for Medium Range Weather Forecasts Level IIIb analysis data is also presented.

Particle size analysis of amalgam powder and handpiece generated specimens.

PubMed

Drummond, J L; Hathorn, R M; Cailas, M D; Karuhn, R

2001-07-01

The increasing interest in the elimination of amalgam particles from the dental waste (DW) stream, requires efficient devices to remove these particles. The major objective of this project was to perform a comparative evaluation of five basic methods of particle size analysis in terms of the instrument's ability to quantify the size distribution of the various components within the DW stream. The analytical techniques chosen were image analysis via scanning electron microscopy, standard wire mesh sieves, X-ray sedigraphy, laser diffraction, and electrozone analysis. The DW particle stream components were represented by amalgam powders and handpiece/diamond bur generated specimens of enamel; dentin, whole tooth, and condensed amalgam. Each analytical method quantified the examined DW particle stream components. However, X-ray sedigraphy, electrozone, and laser diffraction particle analyses provided similar results for determining particle distributions of DW samples. These three methods were able to more clearly quantify the properties of the examined powder and condensed amalgam samples. Furthermore, these methods indicated that a significant fraction of the DW stream contains particles less than 20 microm. The findings of this study indicated that the electrozone method is likely to be the most effective technique for quantifying the particle size distribution in the DW particle stream. This method required a relative small volume of sample, was not affected by density, shape factors or optical properties, and measured a sufficient number of particles to provide a reliable representation of the particle size distribution curve.

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

EMD-WVD time-frequency distribution for analysis of multi-component signals

NASA Astrophysics Data System (ADS)

Chai, Yunzi; Zhang, Xudong

2016-10-01

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components - Intrinsic Mode Function (IMF) - by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

Classic maximum entropy recovery of the average joint distribution of apparent FRET efficiency and fluorescence photons for single-molecule burst measurements.

PubMed

DeVore, Matthew S; Gull, Stephen F; Johnson, Carey K

2012-04-05

We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions.

Component Analysis of Remanent Magnetization Curves: A Revisit with a New Model Distribution

NASA Astrophysics Data System (ADS)

Zhao, X.; Suganuma, Y.; Fujii, M.

2017-12-01

Geological samples often consist of several magnetic components that have distinct origins. As the magnetic components are often indicative of their underlying geological and environmental processes, it is therefore desirable to identify individual components to extract associated information. This component analysis can be achieved using the so-called unmixing method, which fits a mixture model of certain end-member model distribution to the measured remanent magnetization curve. In earlier studies, the lognormal, skew generalized Gaussian and skewed Gaussian distributions have been used as the end-member model distribution in previous studies, which are performed on the gradient curve of remanent magnetization curves. However, gradient curves are sensitive to measurement noise as the differentiation of the measured curve amplifies noise, which could deteriorate the component analysis. Though either smoothing or filtering can be applied to reduce the noise before differentiation, their effect on biasing component analysis is vaguely addressed. In this study, we investigated a new model function that can be directly applied to the remanent magnetization curves and therefore avoid the differentiation. The new model function can provide more flexible shape than the lognormal distribution, which is a merit for modeling the coercivity distribution of complex magnetic component. We applied the unmixing method both to model and measured data, and compared the results with those obtained using other model distributions to better understand their interchangeability, applicability and limitation. The analyses on model data suggest that unmixing methods are inherently sensitive to noise, especially when the number of component is over two. It is, therefore, recommended to verify the reliability of component analysis by running multiple analyses with synthetic noise. Marine sediments and seafloor rocks are analyzed with the new model distribution. Given the same component number, the new model distribution can provide closer fits than the lognormal distribution evidenced by reduced residuals. Moreover, the new unmixing protocol is automated so that the users are freed from the labor of providing initial guesses for the parameters, which is also helpful to improve the subjectivity of component analysis.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Radar Imaging Using The Wigner-Ville Distribution

NASA Astrophysics Data System (ADS)

Boashash, Boualem; Kenny, Owen P.; Whitehouse, Harper J.

1989-12-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. This paper first discusses the radar equation in terms of the time-frequency representation of the signal received from a radar system. It then presents a method of tomographic reconstruction for time-frequency images to estimate the scattering function of the aircraft. An optical archi-tecture is then discussed for the real-time implementation of the analysis method based on the WVD.

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

NASA Astrophysics Data System (ADS)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

PubMed

Tian, Guo-Liang; Li, Hui-Qiong

2017-08-01

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins. The second objective is to provide a new framework for analyzing incomplete contingency tables based on the derived joint sampling distribution of the observed counts by developing a Fisher scoring algorithm to calculate maximum likelihood estimates of parameters of interest, the bootstrap confidence interval methods, and the bootstrap testing hypothesis methods. We compare the differences between the valid sampling distribution and the sampling distribution under the independency assumption. Simulation studies showed that average/expected confidence-interval widths of parameters based on the sampling distribution under the independency assumption are shorter than those based on the new sampling distribution, yielding unrealistic results. A real data set is analyzed to illustrate the application of the new sampling distribution for incomplete contingency tables and the analysis results again confirm the conclusions obtained from the simulation studies.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components

NASA Technical Reports Server (NTRS)

Cruse, T. A.

1987-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Probabilistic Structural Analysis Methods for select space propulsion system structural components (PSAM)

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Burnside, O. H.; Wu, Y.-T.; Polch, E. Z.; Dias, J. B.

1988-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Visual Aggregate Analysis of Eligibility Features of Clinical Trials

PubMed Central

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-01-01

Objective To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Methods Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. Results We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions “hypertension” and “Type 2 diabetes”, respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. Conclusions We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. PMID:25615940

Bilinear Time-frequency Analysis for Lamb Wave Signal Detected by Electromagnetic Acoustic Transducer

NASA Astrophysics Data System (ADS)

Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu

2018-03-01

Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.

Statistical analysis of secondary particle distributions in relativistic nucleus-nucleus collisions

NASA Technical Reports Server (NTRS)

Mcguire, Stephen C.

1987-01-01

The use is described of several statistical techniques to characterize structure in the angular distributions of secondary particles from nucleus-nucleus collisions in the energy range 24 to 61 GeV/nucleon. The objective of this work was to determine whether there are correlations between emitted particle intensity and angle that may be used to support the existence of the quark gluon plasma. The techniques include chi-square null hypothesis tests, the method of discrete Fourier transform analysis, and fluctuation analysis. We have also used the method of composite unit vectors to test for azimuthal asymmetry in a data set of 63 JACEE-3 events. Each method is presented in a manner that provides the reader with some practical detail regarding its application. Of those events with relatively high statistics, Fe approaches 0 at 55 GeV/nucleon was found to possess an azimuthal distribution with a highly non-random structure. No evidence of non-statistical fluctuations was found in the pseudo-rapidity distributions of the events studied. It is seen that the most effective application of these methods relies upon the availability of many events or single events that possess very high multiplicities.

Electron density and electron temperature measurement in a bi-Maxwellian electron distribution using a derivative method of Langmuir probes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Ikjin; Chung, ChinWook; Youn Moon, Se

2013-08-15

In plasma diagnostics with a single Langmuir probe, the electron temperature T{sub e} is usually obtained from the slope of the logarithm of the electron current or from the electron energy probability functions of current (I)-voltage (V) curve. Recently, Chen [F. F. Chen, Phys. Plasmas 8, 3029 (2001)] suggested a derivative analysis method to obtain T{sub e} by the ratio between the probe current and the derivative of the probe current at a plasma potential where the ion current becomes zero. Based on this method, electron temperatures and electron densities were measured and compared with those from the electron energymore » distribution function (EEDF) measurement in Maxwellian and bi-Maxwellian electron distribution conditions. In a bi-Maxwellian electron distribution, we found the electron temperature T{sub e} obtained from the method is always lower than the effective temperatures T{sub eff} derived from EEDFs. The theoretical analysis for this is presented.« less

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging

NASA Astrophysics Data System (ADS)

Wu, Zhisheng; Tao, Ou; Cheng, Wei; Yu, Lu; Shi, Xinyuan; Qiao, Yanjiang

2012-02-01

This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Integral finite element analysis of turntable bearing with flexible rings

NASA Astrophysics Data System (ADS)

Deng, Biao; Liu, Yunfei; Guo, Yuan; Tang, Shengjin; Su, Wenbin; Lei, Zhufeng; Wang, Pengcheng

2018-03-01

This paper suggests a method to calculate the internal load distribution and contact stress of the thrust angular contact ball turntable bearing by FEA. The influence of the stiffness of the bearing structure and the plastic deformation of contact area on the internal load distribution and contact stress of the bearing is considered. In this method, the load-deformation relationship of the rolling elements is determined by the finite element contact analysis of a single rolling element and the raceway. Based on this, the nonlinear contact between the rolling elements and the inner and outer ring raceways is same as a nonlinear compression spring and bearing integral finite element analysis model including support structure was established. The effects of structural deformation and plastic deformation on the built-in stress distribution of slewing bearing are investigated on basis of comparing the consequences of load distribution, inner and outer ring stress, contact stress and other finite element analysis results with the traditional bearing theory, which has guiding function for improving the design of slewing bearing.

A Holarctic Biogeographical Analysis of the Collembola (Arthropoda, Hexapoda) Unravels Recent Post-Glacial Colonization Patterns

PubMed Central

Ávila-Jiménez, María Luisa; Coulson, Stephen James

2011-01-01

We aimed to describe the main Arctic biogeographical patterns of the Collembola, and analyze historical factors and current climatic regimes determining Arctic collembolan species distribution. Furthermore, we aimed to identify possible dispersal routes, colonization sources and glacial refugia for Arctic collembola. We implemented a Gaussian Mixture Clustering method on species distribution ranges and applied a distance- based parametric bootstrap test on presence-absence collembolan species distribution data. Additionally, multivariate analysis was performed considering species distributions, biodiversity, cluster distribution and environmental factors (temperature and precipitation). No clear relation was found between current climatic regimes and species distribution in the Arctic. Gaussian Mixture Clustering found common elements within Siberian areas, Atlantic areas, the Canadian Arctic, a mid-Siberian cluster and specific Beringian elements, following the same pattern previously described, using a variety of molecular methods, for Arctic plants. Species distribution hence indicate the influence of recent glacial history, as LGM glacial refugia (mid-Siberia, and Beringia) and major dispersal routes to high Arctic island groups can be identified. Endemic species are found in the high Arctic, but no specific biogeographical pattern can be clearly identified as a sign of high Arctic glacial refugia. Ocean currents patterns are suggested as being an important factor shaping the distribution of Arctic Collembola, which is consistent with Antarctic studies in collembolan biogeography. The clear relations between cluster distribution and geographical areas considering their recent glacial history, lack of relationship of species distribution with current climatic regimes, and consistency with previously described Arctic patterns in a series of organisms inferred using a variety of methods, suggest that historical phenomena shaping contemporary collembolan distribution can be inferred through biogeographical analysis. PMID:26467728

The Effect on Non-Normal Distributions on the Integrated Moving Average Model of Time-Series Analysis.

ERIC Educational Resources Information Center

Doerann-George, Judith

The Integrated Moving Average (IMA) model of time series, and the analysis of intervention effects based on it, assume random shocks which are normally distributed. To determine the robustness of the analysis to violations of this assumption, empirical sampling methods were employed. Samples were generated from three populations; normal,…

Quantifying the pattern of beta/A4 amyloid protein distribution in Alzheimer's disease by image analysis.

PubMed

Bruce, C V; Clinton, J; Gentleman, S M; Roberts, G W; Royston, M C

1992-04-01

We have undertaken a study of the distribution of the beta/A4 amyloid deposited in the cerebral cortex in Alzheimer's disease. Previous studies which have examined the differential distribution of amyloid in the cortex in order to determine the laminar pattern of cortical pathology have not proved to be conclusive. We have developed an alternative method for the solution of this problem. It involves the immunostaining of sections followed by computer-enhanced image analysis. A mathematical model is then used to describe both the amount and the pattern of amyloid across the cortex. This method is both accurate and reliable and also removes many of the problems concerning inter and intra-rater variability in measurement. This method will provide the basis for further quantitative studies on the differential distribution of amyloid in Alzheimer's disease and other cases of dementia where cerebral amyloidosis occurs.

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Broadband Time-Frequency Analysis Using a Multicomputer

DTIC Science & Technology

2004-09-30

FFT 512 pt Waterfall WVD display 8© 2004 Mercury Computer Systems, Inc. Smoothed Pseudo Wigner - Ville Distribution One of many interference reduction...The Wigner - Ville distribution , the scalogram, and the discrete Gabor transform are among the most well-known of these methods. Due to specific...based upon FFT Accumulation Method • Continuous Wavelet Transform (Scalogram) • Discrete Wigner - Ville Distribution with a selected set of interference

Superstatistics analysis of the ion current distribution function: Met3PbCl influence study.

PubMed

Miśkiewicz, Janusz; Trela, Zenon; Przestalski, Stanisław; Karcz, Waldemar

2010-09-01

A novel analysis of ion current time series is proposed. It is shown that higher (second, third and fourth) statistical moments of the ion current probability distribution function (PDF) can yield new information about ion channel properties. The method is illustrated on a two-state model where the PDF of the compound states are given by normal distributions. The proposed method was applied to the analysis of the SV cation channels of vacuolar membrane of Beta vulgaris and the influence of trimethyllead chloride (Met(3)PbCl) on the ion current probability distribution. Ion currents were measured by patch-clamp technique. It was shown that Met(3)PbCl influences the variance of the open-state ion current but does not alter the PDF of the closed-state ion current. Incorporation of higher statistical moments into the standard investigation of ion channel properties is proposed.

Diagnostics of Robust Growth Curve Modeling Using Student's "t" Distribution

ERIC Educational Resources Information Center

Tong, Xin; Zhang, Zhiyong

2012-01-01

Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE PAGES

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

2017-01-16

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

Classic Maximum Entropy Recovery of the Average Joint Distribution of Apparent FRET Efficiency and Fluorescence Photons for Single-molecule Burst Measurements

PubMed Central

DeVore, Matthew S.; Gull, Stephen F.; Johnson, Carey K.

2012-01-01

We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions. PMID:22338694

XRD measurement of mean thickness, thickness distribution and strain for illite and illite-smectite crystallites by the Bertaut-Warren-Averbach technique

USGS Publications Warehouse

Drits, Victor A.; Eberl, Dennis D.; Środoń, Jan

1998-01-01

A modified version of the Bertaut-Warren-Averbach (BWA) technique (Bertaut 1949, 1950; Warren and Averbach 1950) has been developed to measure coherent scattering domain (CSD) sizes and strains in minerals by analysis of X-ray diffraction (XRD) data. This method is used to measure CSD thickness distributions for calculated and experimental XRD patterns of illites and illite-smectites (I-S). The method almost exactly recovers CSD thickness distributions for calculated illite XRD patterns. Natural I-S samples contain swelling layers that lead to nonperiodic structures in the c* direction and to XRD peaks that are broadened and made asymmetric by mixed layering. Therefore, these peaks cannot be analyzed by the BWA method. These difficulties are overcome by K-saturation and heating prior to X-ray analysis in order to form 10-Å periodic structures. BWA analysis yields the thickness distribution of mixed-layer crystals (coherently diffracting stacks of fundamental illite particles). For most I-S samples, CSD thickness distributions can be approximated by lognormal functions. Mixed-layer crystal mean thickness and expandability then can be used to calculate fundamental illite particle mean thickness. Analyses of the dehydrated, K-saturated samples indicate that basal XRD reflections are broadened by symmetrical strain that may be related to local variations in smectite interlayers caused by dehydration, and that the standard deviation of the strain increases regularly with expandability. The 001 and 002 reflections are affected only slightly by this strain and therefore are suited for CSD thickness analysis. Mean mixed-layer crystal thicknesses for dehydrated I-S measured by the BWA method are very close to those measured by an integral peak width method.

REPRESENTATIVE SAMPLING AND ANALYSIS OF HETEROGENEOUS SOILS

EPA Science Inventory

Standard sampling and analysis methods for hazardous substances in contaminated soils currently are available and routinely employed. Standard methods inherently assume a homogeneous soil matrix and contaminant distribution; therefore only small sample quantities typically are p...

DataHub knowledge based assistance for science visualization and analysis using large distributed databases

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Collins, Donald J.; Doyle, Richard J.; Jacobson, Allan S.

1991-01-01

Viewgraphs on DataHub knowledge based assistance for science visualization and analysis using large distributed databases. Topics covered include: DataHub functional architecture; data representation; logical access methods; preliminary software architecture; LinkWinds; data knowledge issues; expert systems; and data management.

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

Optical granulometric analysis of sedimentary deposits by color segmentation-based software: OPTGRAN-CS

NASA Astrophysics Data System (ADS)

Chávez, G. Moreno; Sarocchi, D.; Santana, E. Arce; Borselli, L.

2015-12-01

The study of grain size distribution is fundamental for understanding sedimentological environments. Through these analyses, clast erosion, transport and deposition processes can be interpreted and modeled. However, grain size distribution analysis can be difficult in some outcrops due to the number and complexity of the arrangement of clasts and matrix and their physical size. Despite various technological advances, it is almost impossible to get the full grain size distribution (blocks to sand grain size) with a single method or instrument of analysis. For this reason development in this area continues to be fundamental. In recent years, various methods of particle size analysis by automatic image processing have been developed, due to their potential advantages with respect to classical ones; speed and final detailed content of information (virtually for each analyzed particle). In this framework, we have developed a novel algorithm and software for grain size distribution analysis, based on color image segmentation using an entropy-controlled quadratic Markov measure field algorithm and the Rosiwal method for counting intersections between clast and linear transects in the images. We test the novel algorithm in different sedimentary deposit types from 14 varieties of sedimentological environments. The results of the new algorithm were compared with grain counts performed manually by the same Rosiwal methods applied by experts. The new algorithm has the same accuracy as a classical manual count process, but the application of this innovative methodology is much easier and dramatically less time-consuming. The final productivity of the new software for analysis of clasts deposits after recording field outcrop images can be increased significantly.

[An EMD based time-frequency distribution and its application in EEG analysis].

PubMed

Li, Xiaobing; Chu, Meng; Qiu, Tianshuang; Bao, Haiping

2007-10-01

Hilbert-Huang transform (HHT) is a new time-frequency analytic method to analyze the nonlinear and the non-stationary signals. The key step of this method is the empirical mode decomposition (EMD), with which any complicated signal can be decomposed into a finite and small number of intrinsic mode functions (IMF). In this paper, a new EMD based method for suppressing the cross-term of Wigner-Ville distribution (WVD) is developed and is applied to analyze the epileptic EEG signals. The simulation data and analysis results show that the new method suppresses the cross-term of the WVD effectively with an excellent resolution.

Visual aggregate analysis of eligibility features of clinical trials.

PubMed

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-04-01

To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions "hypertension" and "Type 2 diabetes", respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Competing risk models in reliability systems, an exponential distribution model with Bayesian analysis approach

NASA Astrophysics Data System (ADS)

Iskandar, I.

2018-03-01

The exponential distribution is the most widely used reliability analysis. This distribution is very suitable for representing the lengths of life of many cases and is available in a simple statistical form. The characteristic of this distribution is a constant hazard rate. The exponential distribution is the lower rank of the Weibull distributions. In this paper our effort is to introduce the basic notions that constitute an exponential competing risks model in reliability analysis using Bayesian analysis approach and presenting their analytic methods. The cases are limited to the models with independent causes of failure. A non-informative prior distribution is used in our analysis. This model describes the likelihood function and follows with the description of the posterior function and the estimations of the point, interval, hazard function, and reliability. The net probability of failure if only one specific risk is present, crude probability of failure due to a specific risk in the presence of other causes, and partial crude probabilities are also included.

Poisson-Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain.

PubMed

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-03-29

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson-Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson-Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods.

Poisson–Gaussian Noise Analysis and Estimation for Low-Dose X-ray Images in the NSCT Domain

PubMed Central

Lee, Sangyoon; Lee, Min Seok; Kang, Moon Gi

2018-01-01

The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson–Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson–Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods. PMID:29596335

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

USDA-ARS?s Scientific Manuscript database

This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

Static analysis of rectifier cabinet for nuclear power generating stations based on finite element method

NASA Astrophysics Data System (ADS)

Yin, Qiang; Chen, Tian-jin; Li, Wei-yang; Xiong, Ze-cheng; Ma, Rui

2017-09-01

In order to obtain the deformation map and equivalent stress distribution of rectifier cabinet for nuclear power generating stations, the quality distribution of structure and electrical are described, the tensile bond strengths of the rings are checked, and the finite element model of cabinet is set up by ANSYS. The transport conditions of the hoisting state and fork loading state are analyzed. The deformation map and equivalent stress distribution are obtained. The attentive problems are put forward. It is a reference for analysis method and the obtained results for the transport of rectifier cabinet for nuclear power generating stations.

Results of the Verification of the Statistical Distribution Model of Microseismicity Emission Characteristics

NASA Astrophysics Data System (ADS)

Cianciara, Aleksander

2016-09-01

The paper presents the results of research aimed at verifying the hypothesis that the Weibull distribution is an appropriate statistical distribution model of microseismicity emission characteristics, namely: energy of phenomena and inter-event time. It is understood that the emission under consideration is induced by the natural rock mass fracturing. Because the recorded emission contain noise, therefore, it is subjected to an appropriate filtering. The study has been conducted using the method of statistical verification of null hypothesis that the Weibull distribution fits the empirical cumulative distribution function. As the model describing the cumulative distribution function is given in an analytical form, its verification may be performed using the Kolmogorov-Smirnov goodness-of-fit test. Interpretations by means of probabilistic methods require specifying the correct model describing the statistical distribution of data. Because in these methods measurement data are not used directly, but their statistical distributions, e.g., in the method based on the hazard analysis, or in that that uses maximum value statistics.

Reliable and More Powerful Methods for Power Analysis in Structural Equation Modeling

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun

2017-01-01

The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…

The equivalence of Darmois-Israel and distributional method for thin shells in general relativity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mansouri, R.; Khorrami, M.

1996-11-01

A distributional method to solve the Einstein{close_quote}s field equations for thin shells is formulated. The familiar field equations and jump conditions of Darmois-Israel formalism are derived. A careful analysis of the Bianchi identities shows that, for cases under consideration, they make sense as distributions and lead to jump conditions of Darmois-Israel formalism. {copyright} {ital 1996 American Institute of Physics.}

Reliability analysis of structural ceramic components using a three-parameter Weibull distribution

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Powers, Lynn M.; Starlinger, Alois

1992-01-01

Described here are nonlinear regression estimators for the three-Weibull distribution. Issues relating to the bias and invariance associated with these estimators are examined numerically using Monte Carlo simulation methods. The estimators were used to extract parameters from sintered silicon nitride failure data. A reliability analysis was performed on a turbopump blade utilizing the three-parameter Weibull distribution and the estimates from the sintered silicon nitride data.

Probability Density Functions of Observed Rainfall in Montana

NASA Technical Reports Server (NTRS)

Larsen, Scott D.; Johnson, L. Ronald; Smith, Paul L.

1995-01-01

The question of whether a rain rate probability density function (PDF) can vary uniformly between precipitation events is examined. Image analysis on large samples of radar echoes is possible because of advances in technology. The data provided by such an analysis easily allow development of radar reflectivity factors (and by extension rain rate) distribution. Finding a PDF becomes a matter of finding a function that describes the curve approximating the resulting distributions. Ideally, one PDF would exist for all cases; or many PDF's that have the same functional form with only systematic variations in parameters (such as size or shape) exist. Satisfying either of theses cases will, validate the theoretical basis of the Area Time Integral (ATI). Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89 percent of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit. Using the method of moments and Elderton's curve selection criteria, the Pearson Type 1 equation was identified as a potential fit for 89% of the observed distributions. Further analysis indicates that the Type 1 curve does approximate the shape of the distributions but quantitatively does not produce a great fit.

Self spectrum window method in wigner-ville distribution.

PubMed

Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun

2005-01-01

Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.

Inverse analysis of non-uniform temperature distributions using multispectral pyrometry

NASA Astrophysics Data System (ADS)

Fu, Tairan; Duan, Minghao; Tian, Jibin; Shi, Congling

2016-05-01

Optical diagnostics can be used to obtain sub-pixel temperature information in remote sensing. A multispectral pyrometry method was developed using multiple spectral radiation intensities to deduce the temperature area distribution in the measurement region. The method transforms a spot multispectral pyrometer with a fixed field of view into a pyrometer with enhanced spatial resolution that can give sub-pixel temperature information from a "one pixel" measurement region. A temperature area fraction function was defined to represent the spatial temperature distribution in the measurement region. The method is illustrated by simulations of a multispectral pyrometer with a spectral range of 8.0-13.0 μm measuring a non-isothermal region with a temperature range of 500-800 K in the spot pyrometer field of view. The inverse algorithm for the sub-pixel temperature distribution (temperature area fractions) in the "one pixel" verifies this multispectral pyrometry method. The results show that an improved Levenberg-Marquardt algorithm is effective for this ill-posed inverse problem with relative errors in the temperature area fractions of (-3%, 3%) for most of the temperatures. The analysis provides a valuable reference for the use of spot multispectral pyrometers for sub-pixel temperature distributions in remote sensing measurements.

Two dimensional distribution measurement of electric current generated in a polymer electrolyte fuel cell using 49 NMR surface coils.

PubMed

Ogawa, Kuniyasu; Sasaki, Tatsuyoshi; Yoneda, Shigeki; Tsujinaka, Kumiko; Asai, Ritsuko

2018-05-17

In order to increase the current density generated in a PEFC (polymer electrolyte fuel cell), a method for measuring the spatial distribution of both the current and the water content of the MEA (membrane electrode assembly) is necessary. Based on the frequency shifts of NMR (nuclear magnetic resonance) signals acquired from the water contained in the MEA using 49 NMR coils in a 7 × 7 arrangement inserted in the PEFC, a method for measuring the two-dimensional spatial distribution of electric current generated in a unit cell with a power generation area of 140 mm × 160 mm was devised. We also developed an inverse analysis method to determine the two-dimensional electric current distribution that can be applied to actual PEFC connections. Two analytical techniques, namely coarse graining of segments and stepwise search, were used to shorten the calculation time required for inverse analysis of the electric current map. Using this method and techniques, spatial distributions of electric current and water content in the MEA were obtained when the PEFC generated electric power at 100 A. Copyright © 2018 Elsevier Inc. All rights reserved.

Redshift data and statistical inference

NASA Technical Reports Server (NTRS)

Newman, William I.; Haynes, Martha P.; Terzian, Yervant

1994-01-01

Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

NASA Technical Reports Server (NTRS)

Deepak, A.; Fluellen, A.

1978-01-01

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Elemental Analysis in Biological Matrices Using ICP-MS.

PubMed

Hansen, Matthew N; Clogston, Jeffrey D

2018-01-01

The increasing exploration of metallic nanoparticles for use as cancer therapeutic agents necessitates a sensitive technique to track the clearance and distribution of the material once introduced into a living system. Inductively coupled plasma mass spectrometry (ICP-MS) provides a sensitive and selective tool for tracking the distribution of metal components from these nanotherapeutics. This chapter presents a standardized method for processing biological matrices, ensuring complete homogenization of tissues, and outlines the preparation of appropriate standards and controls. The method described herein utilized gold nanoparticle-treated samples; however, the method can easily be applied to the analysis of other metals.

Heat analysis of thermal overload relays using 3-D finite element method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawase, Yoshihiro; Ichihashi, Takayuki; Ito, Shokichi

1999-05-01

In designing a thermal overload relay, it is necessary to analyze thermal characteristics of several trial models. Up to now, this has been done by measuring the temperatures on a number of positions in the trial models. This experimental method is undoubtedly expensive. In this paper, the temperature distribution of a thermal overload relay is obtained by using 3-D finite element analysis taking into account the current distribution in current-carrying conductors. It is shown that the 3-D analysis is capable of evaluating a new design of thermal overload relays.

Avalanche statistics from data with low time resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

LeBlanc, Michael; Nawano, Aya; Wright, Wendelin J.

Extracting avalanche distributions from experimental microplasticity data can be hampered by limited time resolution. We compute the effects of low time resolution on avalanche size distributions and give quantitative criteria for diagnosing and circumventing problems associated with low time resolution. We show that traditional analysis of data obtained at low acquisition rates can lead to avalanche size distributions with incorrect power-law exponents or no power-law scaling at all. Furthermore, we demonstrate that it can lead to apparent data collapses with incorrect power-law and cutoff exponents. We propose new methods to analyze low-resolution stress-time series that can recover the size distributionmore » of the underlying avalanches even when the resolution is so low that naive analysis methods give incorrect results. We test these methods on both downsampled simulation data from a simple model and downsampled bulk metallic glass compression data and find that the methods recover the correct critical exponents.« less

Avalanche statistics from data with low time resolution

DOE PAGES

LeBlanc, Michael; Nawano, Aya; Wright, Wendelin J.; ...

2016-11-22

Extracting avalanche distributions from experimental microplasticity data can be hampered by limited time resolution. We compute the effects of low time resolution on avalanche size distributions and give quantitative criteria for diagnosing and circumventing problems associated with low time resolution. We show that traditional analysis of data obtained at low acquisition rates can lead to avalanche size distributions with incorrect power-law exponents or no power-law scaling at all. Furthermore, we demonstrate that it can lead to apparent data collapses with incorrect power-law and cutoff exponents. We propose new methods to analyze low-resolution stress-time series that can recover the size distributionmore » of the underlying avalanches even when the resolution is so low that naive analysis methods give incorrect results. We test these methods on both downsampled simulation data from a simple model and downsampled bulk metallic glass compression data and find that the methods recover the correct critical exponents.« less

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

PubMed

Andersen, Mikkel Meyer; Eriksen, Poul Svante; Morling, Niels

2014-07-01

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Statistical analysis of water-quality data containing multiple detection limits II: S-language software for nonparametric distribution modeling and hypothesis testing

USGS Publications Warehouse

Lee, L.; Helsel, D.

2007-01-01

Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.

Interfacing Computer-Assisted Drafting and Design with the Building Loads Analysis and System Thermodynamics (BLAST) Program

DTIC Science & Technology

1992-10-01

Manual CI APPENDIX D: Drawing Navigator Field Test D1 DISTRIBUTION Accesion For NTIS CRA&I OTIC TAB Unannouncea JustiteCdtOn By Distribution I "".i•I...methods replace manual methods, the automation will handle the data for the designer, thus reducing error and increasing throughput. However, the two...actively move data from one automation tool (CADD) to the other (the analysis program). This intervention involves a manual rekeying of data already in

Automatic Data Distribution for CFD Applications on Structured Grids

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Yan, Jerry

2000-01-01

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAFT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAFT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Automatic Data Distribution for CFD Applications on Structured Grids

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Yan, Jerry

1999-01-01

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Ultrasound shear wave simulation based on nonlinear wave propagation and Wigner-Ville Distribution analysis

NASA Astrophysics Data System (ADS)

Bidari, Pooya Sobhe; Alirezaie, Javad; Tavakkoli, Jahan

2017-03-01

This paper presents a method for modeling and simulation of shear wave generation from a nonlinear Acoustic Radiation Force Impulse (ARFI) that is considered as a distributed force applied at the focal region of a HIFU transducer radiating in nonlinear regime. The shear wave propagation is simulated by solving the Navier's equation from the distributed nonlinear ARFI as the source of the shear wave. Then, the Wigner-Ville Distribution (WVD) as a time-frequency analysis method is used to detect the shear wave at different local points in the region of interest. The WVD results in an estimation of the shear wave time of arrival, its mean frequency and local attenuation which can be utilized to estimate medium's shear modulus and shear viscosity using the Voigt model.

Modeling error distributions of growth curve models through Bayesian methods.

PubMed

Zhang, Zhiyong

2016-06-01

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is proposed to flexibly model normal and non-normal data through the explicit specification of the error distributions. A simulation study shows when the distribution of the error is correctly specified, one can avoid the loss in the efficiency of standard error estimates. A real example on the analysis of mathematical ability growth data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 is used to show the application of the proposed methods. Instructions and code on how to conduct growth curve analysis with both normal and non-normal error distributions using the the MCMC procedure of SAS are provided.

Numerical analysis of the unintegrated double gluon distribution

NASA Astrophysics Data System (ADS)

Elias, Edgar; Golec-Biernat, Krzysztof; Staśto, Anna M.

2018-01-01

We present detailed numerical analysis of the unintegrated double gluon distribution which includes the dependence on the transverse momenta of partons. The unintegrated double gluon distribution was obtained following the Kimber-Martin-Ryskin method as a convolution of the perturbative gluon splitting function with the collinear integrated double gluon distribution and the Sudakov form factors. We analyze the dependence on the transverse momenta, longitudinal momentum fractions and hard scales. We find that the unintegrated gluon distribution factorizes into a product of two single unintegrated gluon distributions in the region of small values of x, provided the splitting contribution is included and the momentum sum rule is satisfied.

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.

2003-01-01

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

Decision Process to Identify Lessons for Transition to a Distributed (or Blended) Learning Instructional Format

DTIC Science & Technology

2009-09-01

instructional format. Using a mixed- method coding and analysis approach, the sample of POIs were categorized, coded, statistically analyzed, and a... Method SECURITY CLASSIFICATION OF 19. LIMITATION OF 20. NUMBER 21. RESPONSIBLE PERSON 16. REPORT Unclassified 17. ABSTRACT...transition to a distributed (or blended) learning format. Procedure: A mixed- methods approach, combining qualitative coding procedures with basic

Lipid Vesicle Shape Analysis from Populations Using Light Video Microscopy and Computer Vision

PubMed Central

Zupanc, Jernej; Drašler, Barbara; Boljte, Sabina; Kralj-Iglič, Veronika; Iglič, Aleš; Erdogmus, Deniz; Drobne, Damjana

2014-01-01

We present a method for giant lipid vesicle shape analysis that combines manually guided large-scale video microscopy and computer vision algorithms to enable analyzing vesicle populations. The method retains the benefits of light microscopy and enables non-destructive analysis of vesicles from suspensions containing up to several thousands of lipid vesicles (1–50 µm in diameter). For each sample, image analysis was employed to extract data on vesicle quantity and size distributions of their projected diameters and isoperimetric quotients (measure of contour roundness). This process enables a comparison of samples from the same population over time, or the comparison of a treated population to a control. Although vesicles in suspensions are heterogeneous in sizes and shapes and have distinctively non-homogeneous distribution throughout the suspension, this method allows for the capture and analysis of repeatable vesicle samples that are representative of the population inspected. PMID:25426933

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

Multivariate pattern analysis of fMRI data reveals deficits in distributed representations in schizophrenia

PubMed Central

Yoon, Jong H.; Tamir, Diana; Minzenberg, Michael J.; Ragland, J. Daniel; Ursu, Stefan; Carter, Cameron S.

2009-01-01

Background Multivariate pattern analysis is an alternative method of analyzing fMRI data, which is capable of decoding distributed neural representations. We applied this method to test the hypothesis of the impairment in distributed representations in schizophrenia. We also compared the results of this method with traditional GLM-based univariate analysis. Methods 19 schizophrenia and 15 control subjects viewed two runs of stimuli--exemplars of faces, scenes, objects, and scrambled images. To verify engagement with stimuli, subjects completed a 1-back matching task. A multi-voxel pattern classifier was trained to identify category-specific activity patterns on one run of fMRI data. Classification testing was conducted on the remaining run. Correlation of voxel-wise activity across runs evaluated variance over time in activity patterns. Results Patients performed the task less accurately. This group difference was reflected in the pattern analysis results with diminished classification accuracy in patients compared to controls, 59% and 72% respectively. In contrast, there was no group difference in GLM-based univariate measures. In both groups, classification accuracy was significantly correlated with behavioral measures. Both groups showed highly significant correlation between inter-run correlations and classification accuracy. Conclusions Distributed representations of visual objects are impaired in schizophrenia. This impairment is correlated with diminished task performance, suggesting that decreased integrity of cortical activity patterns is reflected in impaired behavior. Comparisons with univariate results suggest greater sensitivity of pattern analysis in detecting group differences in neural activity and reduced likelihood of non-specific factors driving these results. PMID:18822407

A method for reduction of cogging torque in brushless DC motor considering the distribution of magnetization by 3DEMCN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hur, J.; Hyun, D.S.; Hong, J.P.

1998-09-01

The method of reducing cogging torque and improving average torque has been studied by changing the dead zone angle of trapezoidal magnetization distribution of ring type rotor magnet in brushless DC motor (BLDCM). Because BLDCM has 3-D shape of overhang, 3-D analysis should be used for exact computation of its magnetic field. 3-D equivalent magnetic circuit network method (3-D EMCN) which can analyze an accurate 3-D magnetic field has been introduced. The analysis results of cogging torque using 3-D EMCN are compared with ones of 3-D finite element method (3-D FEM) and experimental data.

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

NASA Technical Reports Server (NTRS)

Chao, Luen-Yuan; Shetty, Dinesh K.

1992-01-01

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Dynamic Pressure Distribution due to Horizontal Acceleration in Spherical LNG Tank with Cylindrical Central Part

NASA Astrophysics Data System (ADS)

Ko, Dae-Eun; Shin, Sang-Hoon

2017-11-01

Spherical LNG tanks having many advantages such as structural safety are used as a cargo containment system of LNG carriers. However, it is practically difficult to fabricate perfectly spherical tanks of different sizes in the yard. The most effective method of manufacturing LNG tanks of various capacities is to insert a cylindrical part at the center of existing spherical tanks. While a simplified high-precision analysis method for the initial design of the spherical tanks has been developed for both static and dynamic loads, in the case of spherical tanks with a cylindrical central part, the analysis method available only considers static loads. The purpose of the present study is to derive the dynamic pressure distribution due to horizontal acceleration, which is essential for developing an analysis method that considers dynamic loads as well.

Comparisons of non-Gaussian statistical models in DNA methylation analysis.

PubMed

Ma, Zhanyu; Teschendorff, Andrew E; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-06-16

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance.

Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

PubMed Central

Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-01-01

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687

Analysis of crackling noise using the maximum-likelihood method: Power-law mixing and exponential damping.

PubMed

Salje, Ekhard K H; Planes, Antoni; Vives, Eduard

2017-10-01

Crackling noise can be initiated by competing or coexisting mechanisms. These mechanisms can combine to generate an approximate scale invariant distribution that contains two or more contributions. The overall distribution function can be analyzed, to a good approximation, using maximum-likelihood methods and assuming that it follows a power law although with nonuniversal exponents depending on a varying lower cutoff. We propose that such distributions are rather common and originate from a simple superposition of crackling noise distributions or exponential damping.

Distribution of Localized States from Fine Analysis of Electron Spin Resonance Spectra in Organic Transistors

NASA Astrophysics Data System (ADS)

Matsui, Hiroyuki; Mishchenko, Andrei S.; Hasegawa, Tatsuo

2010-02-01

We developed a novel method for obtaining the distribution of trapped carriers over their degree of localization in organic transistors, based on the fine analysis of electron spin resonance spectra at low enough temperatures where all carriers are localized. To apply the method to pentacene thin-film transistors, we proved through continuous wave saturation experiments that all carriers are localized at below 50 K. We analyzed the spectra at 20 K and found that the major groups of traps comprise localized states having wave functions spanning around 1.5 and 5 molecules and a continuous distribution of states with spatial extent in the range between 6 and 20 molecules.

Distribution of localized states from fine analysis of electron spin resonance spectra in organic transistors.

PubMed

Matsui, Hiroyuki; Mishchenko, Andrei S; Hasegawa, Tatsuo

2010-02-05

We developed a novel method for obtaining the distribution of trapped carriers over their degree of localization in organic transistors, based on the fine analysis of electron spin resonance spectra at low enough temperatures where all carriers are localized. To apply the method to pentacene thin-film transistors, we proved through continuous wave saturation experiments that all carriers are localized at below 50 K. We analyzed the spectra at 20 K and found that the major groups of traps comprise localized states having wave functions spanning around 1.5 and 5 molecules and a continuous distribution of states with spatial extent in the range between 6 and 20 molecules.

A Posteriori Error Analysis and Uncertainty Quantification for Adaptive Multiscale Operator Decomposition Methods for Multiphysics Problems

DTIC Science & Technology

2014-04-01

Barrier methods for critical exponent problems in geometric analysis and mathematical physics, J. Erway and M. Holst, Submitted for publication ...TR-14-33 A Posteriori Error Analysis and Uncertainty Quantification for Adaptive Multiscale Operator Decomposition Methods for Multiphysics...Problems Approved for public release, distribution is unlimited. April 2014 HDTRA1-09-1-0036 Donald Estep and Michael

Local and Widely Distributed EEG Activity in Schizophrenia With Prevalence of Negative Symptoms.

PubMed

Grin-Yatsenko, Vera A; Ponomarev, Valery A; Pronina, Marina V; Poliakov, Yury I; Plotnikova, Irina V; Kropotov, Juri D

2017-09-01

We evaluated EEG frequency abnormalities in resting state (eyes closed and eyes open) EEG in a group of chronic schizophrenia patients as compared with healthy subjects. The study included 3 methods of analysis of deviation of EEG characteristics: genuine EEG, current source density (CSD), and group independent component (gIC). All 3 methods have shown that the EEG in schizophrenia patients is characterized by enhanced low-frequency (delta and theta) and high-frequency (beta) activity in comparison with the control group. However, the spatial pattern of differences was dependent on the type of method used. Comparative analysis has shown that increased EEG power in schizophrenia patients apparently concerns both widely spatially distributed components and local components of signal. Furthermore, the observed differences in the delta and theta range can be described mainly by the local components, and those in the beta range mostly by spatially widely distributed ones. The possible nature of the widely distributed activity is discussed.

Verification of echo amplitude envelope analysis method in skin tissues for quantitative follow-up of healing ulcers

NASA Astrophysics Data System (ADS)

Omura, Masaaki; Yoshida, Kenji; Akita, Shinsuke; Yamaguchi, Tadashi

2018-07-01

We aim to develop an ultrasonic tissue characterization method for the follow-up of healing ulcers by diagnosing collagen fibers properties. In this paper, we demonstrated a computer simulation with simulation phantoms reflecting irregularly distributed collagen fibers to evaluate the relationship between physical properties, such as number density and periodicity, and the estimated characteristics of the echo amplitude envelope using the homodyned-K distribution. Moreover, the consistency between echo signal characteristics and the structures of ex vivo human tissues was verified from the measured data of normal skin and nonhealed ulcers. In the simulation study, speckle or coherent signal characteristics are identified as periodically or uniformly distributed collagen fibers with high number density and high periodicity. This result shows the effectiveness of the analysis using the homodyned-K distribution for tissues with complicated structures. Normal skin analysis results are characterized as including speckle or low-coherence signal components, and a nonhealed ulcer is different from normal skin with respect to the physical properties of collagen fibers.

Application of Monte Carlo techniques to transient thermal modeling of cavity radiometers having diffuse-specular surfaces

NASA Technical Reports Server (NTRS)

Mahan, J. R.; Eskin, L. D.

1981-01-01

A viable alternative to the net exchange method of radiative analysis which is equally applicable to diffuse and diffuse-specular enclosures is presented. It is particularly more advantageous to use than the net exchange method in the case of a transient thermal analysis involving conduction and storage of energy as well as radiative exchange. A new quantity, called the distribution factor is defined which replaces the angle factor and the configuration factor. Once obtained, the array of distribution factors for an ensemble of surface elements which define an enclosure permits the instantaneous net radiative heat fluxes to all of the surfaces to be computed directly in terms of the known surface temperatures at that instant. The formulation of the thermal model is described, as is the determination of distribution factors by application of a Monte Carlo analysis. The results show that when fewer than 10,000 packets are emitted, an unsatisfactory approximation for the distribution factors is obtained, but that 10,000 packets is sufficient.

Leveraging AMI data for distribution system model calibration and situational awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Leveraging AMI data for distribution system model calibration and situational awareness

DOE PAGES

Peppanen, Jouni; Reno, Matthew J.; Thakkar, Mohini; ...

2015-01-15

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation andmore » regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.« less

Spatial analysis of cities using Renyi entropy and fractal parameters

NASA Astrophysics Data System (ADS)

Chen, Yanguang; Feng, Jian

2017-12-01

The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.

Evaluation of methods for the extraction of DNA from drinking water distribution system biofilms.

PubMed

Hwang, Chiachi; Ling, Fangqiong; Andersen, Gary L; LeChevallier, Mark W; Liu, Wen-Tso

2012-01-01

While drinking water biofilms have been characterized in various drinking water distribution systems (DWDS), little is known about the impact of different DNA extraction methods on the subsequent analysis of microbial communities in drinking water biofilms. Since different DNA extraction methods have been shown to affect the outcome of microbial community analysis in other environments, it is necessary to select a DNA extraction method prior to the application of molecular tools to characterize the complex microbial ecology of the DWDS. This study compared the quantity and quality of DNA yields from selected DWDS bacteria with different cell wall properties using five widely used DNA extraction methods. These were further selected and evaluated for their efficiency and reproducibility of DNA extraction from DWDS samples. Terminal restriction fragment length analysis and the 454 pyrosequencing technique were used to interpret the differences in microbial community structure and composition, respectively, from extracted DNA. Such assessments serve as a concrete step towards the determination of an optimal DNA extraction method for drinking water biofilms, which can then provide a reliable comparison of the meta-analysis results obtained in different laboratories.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

Martina, R; Kay, R; van Maanen, R; Ridder, A

2015-01-01

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.

Operation Guiding Light-Scientific Program and Field Plan. The Pilot Field Experiment for NORDA Project Chemical Dynamics in Ocean Frontal Areas

DTIC Science & Technology

1985-03-01

distribution. Samples of suspended partici’lates will also be collected for later image and elemental analysis . 25 Method of analysis for particle...will be flow injection analysis . This method will allow rapid, continuous analysis of seawater nutrients. Measurements will be made at one minute...5 m intervals) as well as from the underway pumping system. Method of pigment analysis for porphyrin and carotenoid pigments will be separation by

Damage diagnosis algorithm using a sequential change point detection method with an unknown distribution for damage

NASA Astrophysics Data System (ADS)

Noh, Hae Young; Rajagopal, Ram; Kiremidjian, Anne S.

2012-04-01

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method for the cases where the post-damage feature distribution is unknown a priori. This algorithm extracts features from structural vibration data using time-series analysis and then declares damage using the change point detection method. The change point detection method asymptotically minimizes detection delay for a given false alarm rate. The conventional method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori. Therefore, our algorithm estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using multiple sets of simulated data and a set of experimental data collected from a four-story steel special moment-resisting frame. Our algorithm was able to estimate the post-damage distribution consistently and resulted in detection delays only a few seconds longer than the delays from the conventional method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.

Binocular optical axis parallelism detection precision analysis based on Monte Carlo method

NASA Astrophysics Data System (ADS)

Ying, Jiaju; Liu, Bingqi

2018-02-01

According to the working principle of the binocular photoelectric instrument optical axis parallelism digital calibration instrument, and in view of all components of the instrument, the various factors affect the system precision is analyzed, and then precision analysis model is established. Based on the error distribution, Monte Carlo method is used to analyze the relationship between the comprehensive error and the change of the center coordinate of the circle target image. The method can further guide the error distribution, optimize control the factors which have greater influence on the comprehensive error, and improve the measurement accuracy of the optical axis parallelism digital calibration instrument.

Analysis of an ultrasonically rotating droplet by moving particle semi-implicit and distributed point source method in a rotational coordinate

NASA Astrophysics Data System (ADS)

Wada, Yuji; Yuge, Kohei; Tanaka, Hiroki; Nakamura, Kentaro

2017-07-01

Numerical analysis on the rotation of an ultrasonically levitated droplet in centrifugal coordinate is discussed. A droplet levitated in an acoustic chamber is simulated using the distributed point source method and the moving particle semi-implicit method. Centrifugal coordinate is adopted to avoid the Laplacian differential error, which causes numerical divergence or inaccuracy in the global coordinate calculation. Consequently, the duration of calculation stability has increased 30 times longer than that in a the previous paper. Moreover, the droplet radius versus rotational acceleration characteristics show a similar trend to the theoretical and experimental values in the literature.

Spatially Resolved Chemical Imaging for Biosignature Analysis: Terrestrial and Extraterrestrial Examples

NASA Astrophysics Data System (ADS)

Bhartia, R.; Wanger, G.; Orphan, V. J.; Fries, M.; Rowe, A. R.; Nealson, K. H.; Abbey, W. J.; DeFlores, L. P.; Beegle, L. W.

2014-12-01

Detection of in situ biosignatures on terrestrial and planetary missions is becoming increasingly more important. Missions that target the Earth's deep biosphere, Mars, moons of Jupiter (including Europa), moons of Saturn (Titan and Enceladus), and small bodies such as asteroids or comets require methods that enable detection of materials for both in-situ analysis that preserve context and as a means to select high priority sample for return to Earth. In situ instrumentation for biosignature detection spans a wide range of analytical and spectroscopic methods that capitalize on amino acid distribution, chirality, lipid composition, isotopic fractionation, or textures that persist in the environment. Many of the existing analytical instruments are bulk analysis methods and while highly sensitive, these require sample acquisition and sample processing. However, by combining with triaging spectroscopic methods, biosignatures can be targeted on a surface and preserve spatial context (including mineralogy, textures, and organic distribution). To provide spatially correlated chemical analysis at multiple spatial scales (meters to microns) we have employed a dual spectroscopic approach that capitalizes on high sensitivity deep UV native fluorescence detection and high specificity deep UV Raman analysis.. Recently selected as a payload on the Mars 2020 mission, SHERLOC incorporates these optical methods for potential biosignatures detection on Mars. We present data from both Earth analogs that operate as our only examples known biosignatures and meteorite samples that provide an example of abiotic organic formation, and demonstrate how provenance effects the spatial distribution and composition of organics.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

A study of the application of power-spectral methods of generalized harmonic analysis to gust loads on airplanes

NASA Technical Reports Server (NTRS)

Press, Harry; Mazelsky, Bernard

1954-01-01

The applicability of some results from the theory of generalized harmonic analysis (or power-spectral analysis) to the analysis of gust loads on airplanes in continuous rough air is examined. The general relations for linear systems between power spectrums of a random input disturbance and an output response are used to relate the spectrum of airplane load in rough air to the spectrum of atmospheric gust velocity. The power spectrum of loads is shown to provide a measure of the load intensity in terms of the standard deviation (root mean square) of the load distribution for an airplane in flight through continuous rough air. For the case of a load output having a normal distribution, which appears from experimental evidence to apply to homogeneous rough air, the standard deviation is shown to describe the probability distribution of loads or the proportion of total time that the load has given values. Thus, for airplane in flight through homogeneous rough air, the probability distribution of loads may be determined from a power-spectral analysis. In order to illustrate the application of power-spectral analysis to gust-load analysis and to obtain an insight into the relations between loads and airplane gust-response characteristics, two selected series of calculations are presented. The results indicate that both methods of analysis yield results that are consistent to a first approximation.

Comparing the index-flood and multiple-regression methods using L-moments

NASA Astrophysics Data System (ADS)

Malekinezhad, H.; Nachtnebel, H. P.; Klik, A.

In arid and semi-arid regions, the length of records is usually too short to ensure reliable quantile estimates. Comparing index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main influencing variables on flood magnitude. Ward’s cluster and L-moments approaches were applied to several sites in the Namak-Lake basin in central Iran to delineate homogeneous regions based on site characteristics. Homogeneity test was done using L-moments-based measures. Several distributions were fitted to the regional flood data and index-flood and multiple-regression methods as two regional flood frequency methods were compared. The results of factor analysis showed that length of main waterway, compactness coefficient, mean annual precipitation, and mean annual temperature were the main variables affecting flood magnitude. The study area was divided into three regions based on the Ward’s method of clustering approach. The homogeneity test based on L-moments showed that all three regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of three homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, GEV distribution was identified as the most robust distribution among five candidate distributions for all the proposed sub-regions of the study area, and in general, it was concluded that the generalised extreme value distribution was the best-fit distribution for every three regions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals. Therefore, this method should be adopted as regional flood frequency method for the study area and the Namak-Lake basin in central Iran. To estimate floods of various return periods for gauged catchments in the study area, the mean annual peak flood of the catchments may be multiplied by corresponding values of the growth factors, and computed using the GEV distribution.

Probabilistic Analysis of a Composite Crew Module

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Krishnamurthy, Thiagarajan

2011-01-01

An approach for conducting reliability-based analysis (RBA) of a Composite Crew Module (CCM) is presented. The goal is to identify and quantify the benefits of probabilistic design methods for the CCM and future space vehicles. The coarse finite element model from a previous NASA Engineering and Safety Center (NESC) project is used as the baseline deterministic analysis model to evaluate the performance of the CCM using a strength-based failure index. The first step in the probabilistic analysis process is the determination of the uncertainty distributions for key parameters in the model. Analytical data from water landing simulations are used to develop an uncertainty distribution, but such data were unavailable for other load cases. The uncertainty distributions for the other load scale factors and the strength allowables are generated based on assumed coefficients of variation. Probability of first-ply failure is estimated using three methods: the first order reliability method (FORM), Monte Carlo simulation, and conditional sampling. Results for the three methods were consistent. The reliability is shown to be driven by first ply failure in one region of the CCM at the high altitude abort load set. The final predicted probability of failure is on the order of 10-11 due to the conservative nature of the factors of safety on the deterministic loads.

Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources

NASA Astrophysics Data System (ADS)

Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi

2017-01-01

Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.

Distribution Grid Integration Costs Under High PV Penetrations Workshop |

Science.gov Websites

grids. These distribution grid integration costs are one component of a complete cost-benefit analysis . Engaging stakeholders to coalesce around transparent and mutually acceptable frameworks for cost-benefit -voltage only). In particular, there was be a focus on methods most appropriate for cost-benefit analysis

An Evaluation of Normal versus Lognormal Distribution in Data Description and Empirical Analysis

ERIC Educational Resources Information Center

Diwakar, Rekha

2017-01-01

Many existing methods of statistical inference and analysis rely heavily on the assumption that the data are normally distributed. However, the normality assumption is not fulfilled when dealing with data which does not contain negative values or are otherwise skewed--a common occurrence in diverse disciplines such as finance, economics, political…

An Analysis of Variance Approach for the Estimation of Response Time Distributions in Tests

ERIC Educational Resources Information Center

Attali, Yigal

2010-01-01

Generalizability theory and analysis of variance methods are employed, together with the concept of objective time pressure, to estimate response time distributions and the degree of time pressure in timed tests. By estimating response time variance components due to person, item, and their interaction, and fixed effects due to item types and…

A New Approach in Time-Frequency Analysis with Applications to Experimental High Range Resolution Radar Data

DTIC Science & Technology

2003-11-01

Distributions In contrast to the linear time-frequency transforms such as the short-time Fourier transform, the Wigner - Ville distribution ( WVD ) is...23 9 Results of nine TFDs: (a) Wigner - Ville distribution , (b) Born-Jordan distribution , (c) Choi-Williams distribution , (d) bilinear TFD...are applied in the Wigner - Ville class of time-frequency transforms and the reassignment methods, which are applied to any time-frequency distribution

Grid-based Continual Analysis of Molecular Interior for Drug Discovery, QSAR and QSPR.

PubMed

Potemkin, Andrey V; Grishina, Maria A; Potemkin, Vladimir A

2017-01-01

In 1979, R.D.Cramer and M.Milne made a first realization of 3D comparison of molecules by aligning them in space and by mapping their molecular fields to a 3D grid. Further, this approach was developed as the DYLOMMS (Dynamic Lattice- Oriented Molecular Modelling System) approach. In 1984, H.Wold and S.Wold proposed the use of partial least squares (PLS) analysis, instead of principal component analysis, to correlate the field values with biological activities. Then, in 1988, the method which was called CoMFA (Comparative Molecular Field Analysis) was introduced and the appropriate software became commercially available. Since 1988, a lot of 3D QSAR methods, algorithms and their modifications are introduced for solving of virtual drug discovery problems (e.g., CoMSIA, CoMMA, HINT, HASL, GOLPE, GRID, PARM, Raptor, BiS, CiS, ConGO,). All the methods can be divided into two groups (classes):1. Methods studying the exterior of molecules; 2) Methods studying the interior of molecules. A series of grid-based computational technologies for Continual Molecular Interior analysis (CoMIn) are invented in the current paper. The grid-based analysis is fulfilled by means of a lattice construction analogously to many other grid-based methods. The further continual elucidation of molecular structure is performed in various ways. (i) In terms of intermolecular interactions potentials. This can be represented as a superposition of Coulomb, Van der Waals interactions and hydrogen bonds. All the potentials are well known continual functions and their values can be determined in all lattice points for a molecule. (ii) In the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum free-orbital approach AlteQ is proposed. All the functions can be calculated using a quantum approach at a sufficient level of theory and their values can be determined in all lattice points for a molecule. Then, the molecules of a dataset can be superimposed in the lattice for the maximal coincidence (or minimal deviations) of the potentials (i) or the quantum functions (ii). The methods and criteria of the superimposition are discussed. After that a functional relationship between biological activity or property and characteristics of potentials (i) or functions (ii) is created. The methods of the quantitative relationship construction are discussed. New approaches for rational virtual drug design based on the intermolecular potentials and quantum functions are invented. All the invented methods are realized at www.chemosophia.com web page. Therefore, a set of 3D QSAR approaches for continual molecular interior study giving a lot of opportunities for virtual drug discovery, virtual screening and ligand-based drug design are invented. The continual elucidation of molecular structure is performed in the terms of intermolecular interactions potentials and in the terms of quantum functions such as electron density distribution, Laplacian and Hamiltonian of electron density distribution, potential energy distribution, the highest occupied and the lowest unoccupied molecular orbitals distribution and their superposition. To reduce time of calculations using quantum methods based on the first principles, an original quantum free-orbital approach AlteQ is proposed. The methods of the quantitative relationship construction are discussed. New approaches for rational virtual drug design based on the intermolecular potentials and quantum functions are invented. All the invented methods are realized at www.chemosophia.com web page. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Gear Fatigue Crack Diagnosis by Vibration Analysis Using Embedded Modeling

DTIC Science & Technology

2001-04-05

gave references on Wigner - Ville Distribution ( WVD ) and some statistical based methods including FM4, NA4 and NB4. There are limitations for vibration...Embedded Modeling DISTRIBUTION : Approved for public release, distribution unlimited This paper is part of the following report: TITLE: New Frontiers in

Univariate and Bivariate Loglinear Models for Discrete Test Score Distributions.

ERIC Educational Resources Information Center

Holland, Paul W.; Thayer, Dorothy T.

2000-01-01

Applied the theory of exponential families of distributions to the problem of fitting the univariate histograms and discrete bivariate frequency distributions that often arise in the analysis of test scores. Considers efficient computation of the maximum likelihood estimates of the parameters using Newton's Method and computationally efficient…

Applying Multivariate Discrete Distributions to Genetically Informative Count Data.

PubMed

Kirkpatrick, Robert M; Neale, Michael C

2016-03-01

We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.

Three-beam interferogram analysis method for surface flatness testing of glass plates and wedges

NASA Astrophysics Data System (ADS)

Sunderland, Zofia; Patorski, Krzysztof

2015-09-01

When testing transparent plates with high quality flat surfaces and a small angle between them the three-beam interference phenomenon is observed. Since the reference beam and the object beams reflected from both the front and back surface of a sample are detected, the recorded intensity distribution may be regarded as a sum of three fringe patterns. Images of that type cannot be succesfully analyzed with standard interferogram analysis methods. They contain, however, useful information on the tested plate surface flatness and its optical thickness variations. Several methods were elaborated to decode the plate parameters. Our technique represents a competitive solution which allows for retrieval of phase components of the three-beam interferogram. It requires recording two images: a three-beam interferogram and the two-beam one with the reference beam blocked. Mutually subtracting these images leads to the intensity distribution which, under some assumptions, provides access to the two component fringe sets which encode surfaces flatness. At various stages of processing we take advantage of nonlinear operations as well as single-frame interferogram analysis methods. Two-dimensional continuous wavelet transform (2D CWT) is used to separate a particular fringe family from the overall interferogram intensity distribution as well as to estimate the phase distribution from a pattern. We distinguish two processing paths depending on the relative density of fringe sets which is connected with geometry of a sample and optical setup. The proposed method is tested on simulated data.

A novel method for correcting scanline-observational bias of discontinuity orientation

PubMed Central

Huang, Lei; Tang, Huiming; Tan, Qinwen; Wang, Dingjian; Wang, Liangqing; Ez Eldin, Mutasim A. M.; Li, Changdong; Wu, Qiong

2016-01-01

Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inherent distribution (in three-dimensional space) are derived using probability theory and calculus under the independence hypothesis of dip direction and dip angle. Based on these solutions, a novel method for obtaining the inherent distribution (also for correcting the bias) is proposed, an approach which includes two procedures: 1) Correcting the cumulative probabilities of orientation according to the solutions, and 2) Determining the distribution of the corrected orientations using approximation methods such as the one-sample Kolmogorov-Smirnov test. The inherent distribution corrected by the proposed method can be used for discrete fracture network (DFN) modelling, which is applied to such areas as rockmass stability evaluation, rockmass permeability analysis, rockmass quality calculation and other related fields. To maximize the correction capacity of the proposed method, the observed sample size is suggested through effectiveness tests for different distribution types, dispersions and sample sizes. The performance of the proposed method and the comparison of its correction capacity with existing methods are illustrated with two case studies. PMID:26961249

On the Analysis of Output Information of S-tree Method

NASA Astrophysics Data System (ADS)

Bekaryan, Karen M.; Melkonyan, Anahit A.

2007-08-01

On of the most popular and effective method of analysis of hierarchical structure of N-body gravitating systems is method of S-tree diagrams. Apart from many interesting peculiarities, the method, unfortunately, is not free from some disadvantages, among which most important is an extremely complexity of analysis of output information. To solve this problem a number of methods are suggested. From our point of view, most effective approach is an application of all these methods simultaneousely. This allows to obtaine more complete and objective «picture» concerning a final distribution.

Quantitative phase analysis and microstructure characterization of magnetite nanocrystals obtained by microwave assisted non-hydrolytic sol–gel synthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sciancalepore, Corrado, E-mail: corrado.sciancalepore@unimore.it; Bondioli, Federica; INSTM Consortium, Via G. Giusti 9, 51121 Firenze

2015-02-15

An innovative preparation procedure, based on microwave assisted non-hydrolytic sol–gel synthesis, to obtain spherical magnetite nanoparticles was reported together with a detailed quantitative phase analysis and microstructure characterization of the synthetic products. The nanoparticle growth was analyzed as a function of the synthesis time and was described in terms of crystallization degree employing the Rietveld method on the magnetic nanostructured system for the determination of the amorphous content using hematite as internal standard. Product crystallinity increases as the microwave thermal treatment is increased and reaches very high percentages for synthesis times longer than 1 h. Microstructural evolution of nanocrystals wasmore » followed by the integral breadth methods to obtain information on the crystallite size-strain distribution. The results of diffraction line profile analysis were compared with nanoparticle grain distribution estimated by dimensional analysis of the transmission electron microscopy (TEM) images. A variation both in the average grain size and in the distribution of the coherently diffraction domains is evidenced, allowing to suppose a relationship between the two quantities. The traditional integral breadth methods have proven to be valid for a rapid assessment of the diffraction line broadening effects in the above-mentioned nanostructured systems and the basic assumption for the correct use of these methods are discussed as well. - Highlights: • Fe{sub 3}O{sub 4} nanocrystals were obtained by MW-assisted non-hydrolytic sol–gel synthesis. • Quantitative phase analysis revealed that crystallinity up to 95% was reached. • The strategy of Rietveld refinements was discussed in details. • Dimensional analysis showed nanoparticles ranging from 4 to 8 nm. • Results of integral breadth methods were compared with microscopic analysis.« less

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Componential distribution analysis of food using near infrared ray image

NASA Astrophysics Data System (ADS)

Yamauchi, Hiroki; Kato, Kunihito; Yamamoto, Kazuhiko; Ogawa, Noriko; Ohba, Kimie

2008-11-01

The components of the food related to the "deliciousness" are usually evaluated by componential analysis. The component content and type of components in the food are determined by this analysis. However, componential analysis is not able to analyze measurements in detail, and the measurement is time consuming. We propose a method to measure the two-dimensional distribution of the component in food using a near infrared ray (IR) image. The advantage of our method is to be able to visualize the invisible components. Many components in food have characteristics such as absorption and reflection of light in the IR range. The component content is measured using subtraction between two wavelengths of near IR light. In this paper, we describe a method to measure the component of food using near IR image processing, and we show an application to visualize the saccharose in the pumpkin.

Analytical Methods for Interconnection | Distributed Generation

Science.gov Websites

; ANALYSIS Program Lead Kristen.Ardani@nrel.gov 303-384-4641 Accurately and quickly defining the effects of designed to accommodate voltage rises, bi-directional power flows, and other effects caused by distributed

Regional probability distribution of the annual reference evapotranspiration and its effective parameters in Iran

NASA Astrophysics Data System (ADS)

Khanmohammadi, Neda; Rezaie, Hossein; Montaseri, Majid; Behmanesh, Javad

2017-10-01

The reference evapotranspiration (ET0) plays an important role in water management plans in arid or semi-arid countries such as Iran. For this reason, the regional analysis of this parameter is important. But, ET0 process is affected by several meteorological parameters such as wind speed, solar radiation, temperature and relative humidity. Therefore, the effect of distribution type of effective meteorological variables on ET0 distribution was analyzed. For this purpose, the regional probability distribution of the annual ET0 and its effective parameters were selected. Used data in this research was recorded data at 30 synoptic stations of Iran during 1960-2014. Using the probability plot correlation coefficient (PPCC) test and the L-moment method, five common distributions were compared and the best distribution was selected. The results of PPCC test and L-moment diagram indicated that the Pearson type III distribution was the best probability distribution for fitting annual ET0 and its four effective parameters. The results of RMSE showed that the ability of the PPCC test and L-moment method for regional analysis of reference evapotranspiration and its effective parameters was similar. The results also showed that the distribution type of the parameters which affected ET0 values can affect the distribution of reference evapotranspiration.

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

An Empirical Analysis of the Cascade Secret Key Reconciliation Protocol for Quantum Key Distribution

DTIC Science & Technology

2011-09-01

performance with the parity checks within each pass increasing and as a result, the processing time is expected to increase as well. A conclusion is drawn... timely manner has driven efforts to develop new key distribution methods. The most promising method is Quantum Key Distribution (QKD) and is...thank the QKD Project Team for all of the insight and support they provided in such a short time period. Thanks are especially in order for my

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

The weighted function method: A handy tool for flood frequency analysis or just a curiosity?

NASA Astrophysics Data System (ADS)

Bogdanowicz, Ewa; Kochanek, Krzysztof; Strupczewski, Witold G.

2018-04-01

The idea of the Weighted Function (WF) method for estimation of Pearson type 3 (Pe3) distribution introduced by Ma in 1984 has been revised and successfully applied for shifted inverse Gaussian (IGa3) distribution. Also the conditions of WF applicability to a shifted distribution have been formulated. The accuracy of WF flood quantiles for both Pe3 and IGa3 distributions was assessed by Monte Caro simulations under the true and false distribution assumption versus the maximum likelihood (MLM), moment (MOM) and L-moments (LMM) methods. Three datasets of annual peak flows of Polish catchments serve the case studies to compare the results of the WF, MOM, MLM and LMM performance for the real flood data. For the hundred-year flood the WF method revealed the explicit superiority only over the MLM surpassing the MOM and especially LMM both for the true and false distributional assumption with respect to relative bias and relative mean root square error values. Generally, the WF method performs well and for hydrological sample size and constitutes good alternative for the estimation of the flood upper quantiles.

A New Method for Non-destructive Measurement of Biomass, Growth Rates, Vertical Biomass Distribution and Dry Matter Content Based on Digital Image Analysis

PubMed Central

Tackenberg, Oliver

2007-01-01

Background and Aims Biomass is an important trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive. Thus, they do not allow the development of individual plants to be followed and they require many individuals to be cultivated for repeated measurements. Non-destructive methods do not have these limitations. Here, a non-destructive method based on digital image analysis is presented, addressing not only above-ground fresh biomass (FBM) and oven-dried biomass (DBM), but also vertical biomass distribution as well as dry matter content (DMC) and growth rates. Methods Scaled digital images of the plants silhouettes were taken for 582 individuals of 27 grass species (Poaceae). Above-ground biomass and DMC were measured using destructive methods. With image analysis software Zeiss KS 300, the projected area and the proportion of greenish pixels were calculated, and generalized linear models (GLMs) were developed with destructively measured parameters as dependent variables and parameters derived from image analysis as independent variables. A bootstrap analysis was performed to assess the number of individuals required for re-calibration of the models. Key Results The results of the developed models showed no systematic errors compared with traditionally measured values and explained most of their variance (R2 ≥ 0·85 for all models). The presented models can be directly applied to herbaceous grasses without further calibration. Applying the models to other growth forms might require a re-calibration which can be based on only 10–20 individuals for FBM or DMC and on 40–50 individuals for DBM. Conclusions The methods presented are time and cost effective compared with traditional methods, especially if development or growth rates are to be measured repeatedly. Hence, they offer an alternative way of determining biomass, especially as they are non-destructive and address not only FBM and DBM, but also vertical biomass distribution and DMC. PMID:17353204

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

NASA Astrophysics Data System (ADS)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

SU-F-T-192: Study of Robustness Analysis Method of Multiple Field Optimized IMPT Plans for Head & Neck Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Y; Wang, X; Li, H

Purpose: Proton therapy is more sensitive to uncertainties than photon treatments due to protons’ finite range depending on the tissue density. Worst case scenario (WCS) method originally proposed by Lomax has been adopted in our institute for robustness analysis of IMPT plans. This work demonstrates that WCS method is sufficient enough to take into account of the uncertainties which could be encountered during daily clinical treatment. Methods: A fast and approximate dose calculation method is developed to calculate the dose for the IMPT plan under different setup and range uncertainties. Effects of two factors, inversed square factor and range uncertainty,more » are explored. WCS robustness analysis method was evaluated using this fast dose calculation method. The worst-case dose distribution was generated by shifting isocenter by 3 mm along x,y and z directions and modifying stopping power ratios by ±3.5%. 1000 randomly perturbed cases in proton range and x, yz directions were created and the corresponding dose distributions were calculated using this approximated method. DVH and dosimetric indexes of all 1000 perturbed cases were calculated and compared with the result using worst case scenario method. Results: The distributions of dosimetric indexes of 1000 perturbed cases were generated and compared with the results using worst case scenario. For D95 of CTVs, at least 97% of 1000 perturbed cases show higher values than the one of worst case scenario. For D5 of CTVs, at least 98% of perturbed cases have lower values than worst case scenario. Conclusion: By extensively calculating the dose distributions under random uncertainties, WCS method was verified to be reliable in evaluating the robustness level of MFO IMPT plans of H&N patients. The extensively sampling approach using fast approximated method could be used in evaluating the effects of different factors on the robustness level of IMPT plans in the future.« less

Understanding poisson regression.

PubMed

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

[Environmental Hazards Assessment Program annual report, June 1992--June 1993]. Use of diatom distributions to monitor environmental health

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levine, R.H.

1993-12-01

A variety of approaches has been used in the past to assess the environmental impact of anthropogenic contaminants. One reliable index for aquatic environments is the analysis of diatom species distribution; the focus in this case being on the Savannah River. The completed objectives of this study were: (A) the development and use of procedures for measuring diatom distribution in the water column and (B) the development and evaluation of sediment sampling methods for retrospective analysis.

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Two dimensional Fourier transform methods for fringe pattern analysis

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.; Bhat, G.

An overview of the use of FFTs for fringe pattern analysis is presented, with emphasis on fringe patterns containing displacement information. The techniques are illustrated via analysis of the displacement and strain distributions in the direction perpendicular to the loading, in a disk under diametral compression. The experimental strain distribution is compared to the theoretical, and the agreement is found to be excellent in regions where the elasticity solution models well the actual problem.

Potential energy distribution (PED) analysis of DFT calculated IR spectra of the most stable Li, Na, and Cu(I) diformate molecules

NASA Astrophysics Data System (ADS)

Jamróz, M. H.; Dobrowolski, J. Cz.

2001-05-01

For the most stable Li, Na, and Cu(I) diformates we present the vibrational spectra, supported by potential energy distribution (PED) analysis, and the interaction energies between formic acid and metal formate by the DFT (B3PW91) method. PED analysis of the theoretical spectra forms the basis for the elucidation of the future matrix isolation IR spectra.

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Dynamic Analysis of Large In-Space Deployable Membrane Antennas

NASA Technical Reports Server (NTRS)

Fang, Houfei; Yang, Bingen; Ding, Hongli; Hah, John; Quijano, Ubaldo; Huang, John

2006-01-01

This paper presents a vibration analysis of an eight-meter diameter membrane reflectarray antenna, which is composed of a thin membrane and a deployable frame. This analysis process has two main steps. In the first step, a two-variable-parameter (2-VP) membrane model is developed to determine the in-plane stress distribution of the membrane due to pre-tensioning, which eventually yields the differential stiffness of the membrane. In the second step, the obtained differential stiffness is incorporated in a dynamic equation governing the transverse vibration of the membrane-frame assembly. This dynamic equation is then solved by a semi-analytical method, called the Distributed Transfer Function Method (DTFM), which produces the natural frequencies and mode shapes of the antenna. The combination of the 2-VP model and the DTFM provides an accurate prediction of the in-plane stress distribution and modes of vibration for the antenna.

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Application of Image Analysis for Characterization of Spatial Arrangements of Features in Microstructure

NASA Technical Reports Server (NTRS)

Louis, Pascal; Gokhale, Arun M.

1995-01-01

A number of microstructural processes are sensitive to the spatial arrangements of features in microstructure. However, very little attention has been given in the past to the experimental measurements of the descriptors of microstructural distance distributions due to the lack of practically feasible methods. We present a digital image analysis procedure to estimate the micro-structural distance distributions. The application of the technique is demonstrated via estimation of K function, radial distribution function, and nearest-neighbor distribution function of hollow spherical carbon particulates in a polymer matrix composite, observed in a metallographic section.

The particle size distribution, density, and specific surface area of welding fumes from SMAW and GMAW mild and stainless steel consumables.

PubMed

Hewett, P

1995-02-01

Particle size distributions were measured for fumes from mild steel (MS) and stainless steel (SS); shielded metal arc welding (SMAW) and gas metal arc welding (GMAW) consumables. Up to six samples of each type of fume were collected in a test chamber using a micro-orifice uniform deposit (cascade) impactor. Bulk samples were collected for bulk fume density and specific surface area analysis. Additional impactor samples were collected using polycarbonate substrates and analyzed for elemental content. The parameters of the underlying mass distributions were estimated using a nonlinear least squares analysis method that fits a smooth curve to the mass fraction distribution histograms of all samples for each type of fume. The mass distributions for all four consumables were unimodal and well described by a lognormal distribution; with the exception of the GMAW-MS and GMAW-SS comparison, they were statistically different. The estimated mass distribution geometric means for the SMAW-MS and SMAW-SS consumables were 0.59 and 0.46 micron aerodynamic equivalent diameter (AED), respectively, and 0.25 micron AED for both the GMAW-MS and GMAW-SS consumables. The bulk fume densities and specific surface areas were similar for the SMAW-MS and SMAW-SS consumables and for the GMAW-MS and GMAW-SS consumables, but differed between SMAW and GMAW. The distribution of metals was similar to the mass distributions. Particle size distributions and physical properties of the fumes were considerably different when categorized by welding method. Within each welding method there was little difference between MS and SS fumes.

Using independent component analysis for electrical impedance tomography

NASA Astrophysics Data System (ADS)

Yan, Peimin; Mo, Yulong

2004-05-01

Independent component analysis (ICA) is a way to resolve signals into independent components based on the statistical characteristics of the signals. It is a method for factoring probability densities of measured signals into a set of densities that are as statistically independent as possible under the assumptions of a linear model. Electrical impedance tomography (EIT) is used to detect variations of the electric conductivity of the human body. Because there are variations of the conductivity distributions inside the body, EIT presents multi-channel data. In order to get all information contained in different location of tissue it is necessary to image the individual conductivity distribution. In this paper we consider to apply ICA to EIT on the signal subspace (individual conductivity distribution). Using ICA the signal subspace will then be decomposed into statistically independent components. The individual conductivity distribution can be reconstructed by the sensitivity theorem in this paper. Compute simulations show that the full information contained in the multi-conductivity distribution will be obtained by this method.

Numerical analysis for distributed-order differential equations

NASA Astrophysics Data System (ADS)

Diethelm, Kai; Ford, Neville J.

2009-03-01

In this paper we present and analyse a numerical method for the solution of a distributed-order differential equation of the general form where m is a positive real number and where the derivative is taken to be a fractional derivative of Caputo type of order r. We give a convergence theory for our method and conclude with some numerical examples.

Robustness of fit indices to outliers and leverage observations in structural equation modeling.

PubMed

Yuan, Ke-Hai; Zhong, Xiaoling

2013-06-01

Normal-distribution-based maximum likelihood (NML) is the most widely used method in structural equation modeling (SEM), although practical data tend to be nonnormally distributed. The effect of nonnormally distributed data or data contamination on the normal-distribution-based likelihood ratio (LR) statistic is well understood due to many analytical and empirical studies. In SEM, fit indices are used as widely as the LR statistic. In addition to NML, robust procedures have been developed for more efficient and less biased parameter estimates with practical data. This article studies the effect of outliers and leverage observations on fit indices following NML and two robust methods. Analysis and empirical results indicate that good leverage observations following NML and one of the robust methods lead most fit indices to give more support to the substantive model. While outliers tend to make a good model superficially bad according to many fit indices following NML, they have little effect on those following the two robust procedures. Implications of the results to data analysis are discussed, and recommendations are provided regarding the use of estimation methods and interpretation of fit indices. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Use of Bayesian Inference in Crystallographic Structure Refinement via Full Diffraction Profile Analysis

PubMed Central

Fancher, Chris M.; Han, Zhen; Levin, Igor; Page, Katharine; Reich, Brian J.; Smith, Ralph C.; Wilson, Alyson G.; Jones, Jacob L.

2016-01-01

A Bayesian inference method for refining crystallographic structures is presented. The distribution of model parameters is stochastically sampled using Markov chain Monte Carlo. Posterior probability distributions are constructed for all model parameters to properly quantify uncertainty by appropriately modeling the heteroskedasticity and correlation of the error structure. The proposed method is demonstrated by analyzing a National Institute of Standards and Technology silicon standard reference material. The results obtained by Bayesian inference are compared with those determined by Rietveld refinement. Posterior probability distributions of model parameters provide both estimates and uncertainties. The new method better estimates the true uncertainties in the model as compared to the Rietveld method. PMID:27550221

Alpha-spectrometry and fractal analysis of surface micro-images for characterisation of porous materials used in manufacture of targets for laser plasma experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aushev, A A; Barinov, S P; Vasin, M G

2015-06-30

We present the results of employing the alpha-spectrometry method to determine the characteristics of porous materials used in targets for laser plasma experiments. It is shown that the energy spectrum of alpha-particles, after their passage through porous samples, allows one to determine the distribution of their path length in the foam skeleton. We describe the procedure of deriving such a distribution, excluding both the distribution broadening due to statistical nature of the alpha-particle interaction with an atomic structure (straggling) and hardware effects. The fractal analysis of micro-images is applied to the same porous surface samples that have been studied bymore » alpha-spectrometry. The fractal dimension and size distribution of the number of the foam skeleton grains are obtained. Using the data obtained, a distribution of the total foam skeleton thickness along a chosen direction is constructed. It roughly coincides with the path length distribution of alpha-particles within a range of larger path lengths. It is concluded that the combined use of the alpha-spectrometry method and fractal analysis of images will make it possible to determine the size distribution of foam skeleton grains (or pores). The results can be used as initial data in theoretical studies on propagation of the laser and X-ray radiation in specific porous samples. (laser plasma)« less

Analysis and prediction of operating vehicle load effects on Highway bridges under the weight charge policy

NASA Astrophysics Data System (ADS)

Huang, Haiyun; Zhang, Junping; Li, Yonghe

2018-05-01

Under the weight charge policy, the weigh in motion data at a toll station on the Jing-Zhu Expressway were collected. The statistic analysis of vehicle load data was carried out. For calculating the operating vehicle load effects on bridges, by Monte Carlo method used to generate random traffic flow and influence line loading method, the maximum bending moment effect of simple supported beams were obtained. The extreme value I distribution and normal distribution were used to simulate the distribution of the maximum bending moment effect. By the extrapolation of Rice formula and the extreme value I distribution, the predicted values of the maximum load effects were obtained. By comparing with vehicle load effect according to current specification, some references were provided for the management of the operating vehicles and the revision of the bridge specifications.

Improved first-order uncertainty method for water-quality modeling

USGS Publications Warehouse

Melching, C.S.; Anmangandla, S.

1992-01-01

Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.

The determination of density and molecular weight distributions of lipoproteins by sedimentation equilibrium.

PubMed

Jeffrey, P D; Nichol, L W; Smith, G D

1975-01-25

A method is presented by which an experimental record of total concentration as a function of radial distance, obtained in a sedimentation equilibrium experiment conducted with a noninteracting mixture in the absence of a density gradient, may be analyzed to obtain the unimodal distributions of molecular weight and of partial molar volume when these vary concomitantly and continuously. Particular attention is given to the caracterization of classes of lipoproteins exhibiting Gaussian distributions of these quantities, although the analysis is applicable to other types of unimodal distribution. Equations are also formulated permitting the definition of the corresponding distributions of partial specific volume and of density. The analysis procedure is based on a method (employing Laplace transforms) developed previously, but differs from it in that it avoids the necessity of differentiating experimental results, which introduces error. The method offers certain advantages over other procedures used to characterize and compare lipoprotein samples (exhibiting unimodal distributions) with regard to the duration of the experiment, economy of the sample, and, particularly, the ability to define in principle all of the relevant distributions from one sedimentation equilibrium experiment and an external measurement of the weight average partial specific volume. These points and the steps in the analysis procedure are illustrated with experimental results obtained in the sedimentation equilibrium of a sample of human serum low density lipoprotein. The experimental parameters (such as solution density, column height, and angular velocity) used in the conduction of these experiments were selected on the basis of computer-simulated examples, which are also presented. These provide a guide for other workers interested in characterizing lipoproteins of this class.

Large Area Stress Distribution in Crystalline Materials Calculated from Lattice Deformation Identified by Electron Backscatter Diffraction

NASA Astrophysics Data System (ADS)

Shao, Yongliang; Zhang, Lei; Hao, Xiaopeng; Wu, Yongzhong; Dai, Yuanbin; Tian, Yuan; Huo, Qin

2014-08-01

We report a method to obtain the stress of crystalline materials directly from lattice deformation by Hooke's law. The lattice deformation was calculated using the crystallographic orientations obtained from electron backscatter diffraction (EBSD) technology. The stress distribution over a large area was obtained efficiently and accurately using this method. Wurtzite structure gallium nitride (GaN) crystal was used as the example of a hexagonal crystal system. With this method, the stress distribution of a GaN crystal was obtained. Raman spectroscopy was used to verify the stress distribution. The cause of the stress distribution found in the GaN crystal was discussed from theoretical analysis and EBSD data. Other properties related to lattice deformation, such as piezoelectricity, can also be analyzed by this novel approach based on EBSD data.

Large area stress distribution in crystalline materials calculated from lattice deformation identified by electron backscatter diffraction.

PubMed

Shao, Yongliang; Zhang, Lei; Hao, Xiaopeng; Wu, Yongzhong; Dai, Yuanbin; Tian, Yuan; Huo, Qin

2014-08-05

We report a method to obtain the stress of crystalline materials directly from lattice deformation by Hooke's law. The lattice deformation was calculated using the crystallographic orientations obtained from electron backscatter diffraction (EBSD) technology. The stress distribution over a large area was obtained efficiently and accurately using this method. Wurtzite structure gallium nitride (GaN) crystal was used as the example of a hexagonal crystal system. With this method, the stress distribution of a GaN crystal was obtained. Raman spectroscopy was used to verify the stress distribution. The cause of the stress distribution found in the GaN crystal was discussed from theoretical analysis and EBSD data. Other properties related to lattice deformation, such as piezoelectricity, can also be analyzed by this novel approach based on EBSD data.

Large Area Stress Distribution in Crystalline Materials Calculated from Lattice Deformation Identified by Electron Backscatter Diffraction

PubMed Central

Shao, Yongliang; Zhang, Lei; Hao, Xiaopeng; Wu, Yongzhong; Dai, Yuanbin; Tian, Yuan; Huo, Qin

2014-01-01

We report a method to obtain the stress of crystalline materials directly from lattice deformation by Hooke's law. The lattice deformation was calculated using the crystallographic orientations obtained from electron backscatter diffraction (EBSD) technology. The stress distribution over a large area was obtained efficiently and accurately using this method. Wurtzite structure gallium nitride (GaN) crystal was used as the example of a hexagonal crystal system. With this method, the stress distribution of a GaN crystal was obtained. Raman spectroscopy was used to verify the stress distribution. The cause of the stress distribution found in the GaN crystal was discussed from theoretical analysis and EBSD data. Other properties related to lattice deformation, such as piezoelectricity, can also be analyzed by this novel approach based on EBSD data. PMID:25091314

A survey of kernel-type estimators for copula and their applications

NASA Astrophysics Data System (ADS)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

New statistical analysis of the horizontal phase velocity distribution of gravity waves observed by airglow imaging

NASA Astrophysics Data System (ADS)

Matsuda, Takashi S.; Nakamura, Takuji; Ejiri, Mitsumu K.; Tsutsumi, Masaki; Shiokawa, Kazuo

2014-08-01

We have developed a new analysis method for obtaining the power spectrum in the horizontal phase velocity domain from airglow intensity image data to study atmospheric gravity waves. This method can deal with extensive amounts of imaging data obtained on different years and at various observation sites without bias caused by different event extraction criteria for the person processing the data. The new method was applied to sodium airglow data obtained in 2011 at Syowa Station (69°S, 40°E), Antarctica. The results were compared with those obtained from a conventional event analysis in which the phase fronts were traced manually in order to estimate horizontal characteristics, such as wavelengths, phase velocities, and wave periods. The horizontal phase velocity of each wave event in the airglow images corresponded closely to a peak in the spectrum. The statistical results of spectral analysis showed an eastward offset of the horizontal phase velocity distribution. This could be interpreted as the existence of wave sources around the stratospheric eastward jet. Similar zonal anisotropy was also seen in the horizontal phase velocity distribution of the gravity waves by the event analysis. Both methods produce similar statistical results about directionality of atmospheric gravity waves. Galactic contamination of the spectrum was examined by calculating the apparent velocity of the stars and found to be limited for phase speeds lower than 30 m/s. In conclusion, our new method is suitable for deriving the horizontal phase velocity characteristics of atmospheric gravity waves from an extensive amount of imaging data.

Self-Organizing Maps and Parton Distribution Functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

K. Holcomb, Simonetta Liuti, D. Z. Perry

2011-05-01

We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly useful for an anaysis directed at extracting generalized parton distributions from data. We show quantitative results of our initial analysis of the parton distribution functions from inclusive deep inelastic scattering.

Study on the influence of X-ray tube spectral distribution on the analysis of bulk samples and thin films: Fundamental parameters method and theoretical coefficient algorithms

NASA Astrophysics Data System (ADS)

Sitko, Rafał

2008-11-01

Knowledge of X-ray tube spectral distribution is necessary in theoretical methods of matrix correction, i.e. in both fundamental parameter (FP) methods and theoretical influence coefficient algorithms. Thus, the influence of X-ray tube distribution on the accuracy of the analysis of thin films and bulk samples is presented. The calculations are performed using experimental X-ray tube spectra taken from the literature and theoretical X-ray tube spectra evaluated by three different algorithms proposed by Pella et al. (X-Ray Spectrom. 14 (1985) 125-135), Ebel (X-Ray Spectrom. 28 (1999) 255-266), and Finkelshtein and Pavlova (X-Ray Spectrom. 28 (1999) 27-32). In this study, Fe-Cr-Ni system is selected as an example and the calculations are performed for X-ray tubes commonly applied in X-ray fluorescence analysis (XRF), i.e., Cr, Mo, Rh and W. The influence of X-ray tube spectra on FP analysis is evaluated when quantification is performed using various types of calibration samples. FP analysis of bulk samples is performed using pure-element bulk standards and multielement bulk standards similar to the analyzed material, whereas for FP analysis of thin films, the bulk and thin pure-element standards are used. For the evaluation of the influence of X-ray tube spectra on XRF analysis performed by theoretical influence coefficient methods, two algorithms for bulk samples are selected, i.e. Claisse-Quintin (Can. Spectrosc. 12 (1967) 129-134) and COLA algorithms (G.R. Lachance, Paper Presented at the International Conference on Industrial Inorganic Elemental Analysis, Metz, France, June 3, 1981) and two algorithms (constant and linear coefficients) for thin films recently proposed by Sitko (X-Ray Spectrom. 37 (2008) 265-272).

Evaluation of Methods for the Extraction of DNA from Drinking Water Distribution System Biofilms

PubMed Central

Hwang, Chiachi; Ling, Fangqiong; Andersen, Gary L.; LeChevallier, Mark W.; Liu, Wen-Tso

2012-01-01

While drinking water biofilms have been characterized in various drinking water distribution systems (DWDS), little is known about the impact of different DNA extraction methods on the subsequent analysis of microbial communities in drinking water biofilms. Since different DNA extraction methods have been shown to affect the outcome of microbial community analysis in other environments, it is necessary to select a DNA extraction method prior to the application of molecular tools to characterize the complex microbial ecology of the DWDS. This study compared the quantity and quality of DNA yields from selected DWDS bacteria with different cell wall properties using five widely used DNA extraction methods. These were further selected and evaluated for their efficiency and reproducibility of DNA extraction from DWDS samples. Terminal restriction fragment length analysis and the 454 pyrosequencing technique were used to interpret the differences in microbial community structure and composition, respectively, from extracted DNA. Such assessments serve as a concrete step towards the determination of an optimal DNA extraction method for drinking water biofilms, which can then provide a reliable comparison of the meta-analysis results obtained in different laboratories. PMID:22075624

Review of probabilistic analysis of dynamic response of systems with random parameters

NASA Technical Reports Server (NTRS)

Kozin, F.; Klosner, J. M.

1989-01-01

The various methods that have been studied in the past to allow probabilistic analysis of dynamic response for systems with random parameters are reviewed. Dynamic response may have been obtained deterministically if the variations about the nominal values were small; however, for space structures which require precise pointing, the variations about the nominal values of the structural details and of the environmental conditions are too large to be considered as negligible. These uncertainties are accounted for in terms of probability distributions about their nominal values. The quantities of concern for describing the response of the structure includes displacements, velocities, and the distributions of natural frequencies. The exact statistical characterization of the response would yield joint probability distributions for the response variables. Since the random quantities will appear as coefficients, determining the exact distributions will be difficult at best. Thus, certain approximations will have to be made. A number of techniques that are available are discussed, even in the nonlinear case. The methods that are described were: (1) Liouville's equation; (2) perturbation methods; (3) mean square approximate systems; and (4) nonlinear systems with approximation by linear systems.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Low speed airfoil design and analysis

NASA Technical Reports Server (NTRS)

Eppler, R.; Somers, D. M.

1979-01-01

A low speed airfoil design and analysis program was developed which contains several unique features. In the design mode, the velocity distribution is not specified for one but many different angles of attack. Several iteration options are included which allow the trailing edge angle to be specified while other parameters are iterated. For airfoil analysis, a panel method is available which uses third-order panels having parabolic vorticity distributions. The flow condition is satisfied at the end points of the panels. Both sharp and blunt trailing edges can be analyzed. The integral boundary layer method with its laminar separation bubble analog, empirical transition criterion, and precise turbulent boundary layer equations compares very favorably with other methods, both integral and finite difference. Comparisons with experiment for several airfoils over a very wide Reynolds number range are discussed. Applications to high lift airfoil design are also demonstrated.

Measurement of carbon distribution in nuclear fuel pin cladding specimens by means of a secondary ion mass spectrometer

NASA Astrophysics Data System (ADS)

Bart, Gerhard; Aerne, Ernst Tino; Burri, Martin; Zwicky, Hans-Urs

1986-11-01

Cladding carburization during irradiation of advanced mixed uranium plutonium carbide fast breeder reactor fuel is possibly a life limiting fuel pin factor. The quantitative assessment of such clad carbon embrittlement is difficult to perform by electron microprobe analysis because of sample surface contamination, and due to the very low energy of the carbon K α X-ray transition. The work presented here describes a method developed at the Swiss Federal Institute for Reactor Research (EIR) to use shielded secondary ion mass spectrometry (SIMS) as an accurate tool to determine radial distribution profiles of carbon in radioactive stainless steel fuel pin cladding. Compared with nuclear microprobe analysis (NMA) [1], which is also an accurate method for carbon analysis, the SIMS method distinguishes itself by its versatility for simultaneous determination of additional impurities.

An analysis of thermal stress and gas bending effects on vibrations of compressor rotor stages. [blade torsional rigidity

NASA Technical Reports Server (NTRS)

Chen, L.-T.; Dugundji, J.

1979-01-01

A preliminary study conducted by Kerrebrock et al. (1976) has shown that the torsional rigidity of untwisted thin blades of a transonic compressor can be reduced significantly by transient thermal stresses. The aerodynamic loads have various effects on blade vibration. One effect is that gas bending loads may result in a bending-torsion coupling which may change the characteristics of the torsion and bending vibration of the blade. For a general study of transient-temperature distribution within a rotor stage, a finite-element heat-conduction analysis was developed. The blade and shroud are divided into annular elements. With a temperature distribution obtained from the heat-conduction analysis and a prescribed gas bending load distribution along the blade span, the static deformation and moment distributions of the blade can be solved iteratively using the finite-element method. The reduction of the torsional rigidity of pretwisted blades caused by the thermal stress effect is then computed. The dynamic behavior of the blade is studied by a modified Galerkin's method.

A feasibility study of altered spatial distribution of losses induced by eddy currents in body composition analysis

PubMed Central

2010-01-01

Background Tomographic imaging has revealed that the body mass index does not give a reliable state of overall fitness. However, high measurement costs make the tomographic imaging unsuitable for large scale studies or repeated individual use. This paper reports an experimental investigation of a new electromagnetic method and its feasibility for assessing body composition. The method is called body electrical loss analysis (BELA). Methods The BELA method uses a high-Q parallel resonant circuit to produce a time-varying magnetic field. The Q of the resonator changes when the sample is placed in its coil. This is caused by induced eddy currents in the sample. The new idea in the BELA method is the altered spatial distribution of the electrical losses generated by these currents. The distribution of losses is varied using different excitation frequencies. The feasibility of the method was tested using simplified phantoms. Two of these phantoms were rough estimations of human torso. One had fat in the middle of its volume and saline solution in the outer shell volume. The other had reversed conductivity distributions. The phantoms were placed in the resonator and the change in the losses was measured. Five different excitation frequencies from 100 kHz to 200 kHz were used. Results The rate of loss as a function of frequency was observed to be approximately three times larger for a phantom with fat in the middle of its volume than for one with fat in its outer shell volume. Conclusions At higher frequencies the major signal contribution can be shifted toward outer shell volume. This enables probing the conductivity distribution of the subject by weighting outer structural components. The authors expect that the loss changing rate over frequency can be a potential index for body composition analysis. PMID:21047441

Integral-moment analysis of the BATSE gamma-ray burst intensity distribution

NASA Technical Reports Server (NTRS)

Horack, John M.; Emslie, A. Gordon

1994-01-01

We have applied the technique of integral-moment analysis to the intensity distribution of the first 260 gamma-ray bursts observed by the Burst and Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory. This technique provides direct measurement of properties such as the mean, variance, and skewness of the convolved luminosity-number density distribution, as well as associated uncertainties. Using this method, one obtains insight into the nature of the source distributions unavailable through computation of traditional single parameters such as V/V(sub max)). If the luminosity function of the gamma-ray bursts is strongly peaked, giving bursts only a narrow range of luminosities, these results are then direct probes of the radial distribution of sources, regardless of whether the bursts are a local phenomenon, are distributed in a galactic halo, or are at cosmological distances. Accordingly, an integral-moment analysis of the intensity distribution of the gamma-ray bursts provides for the most complete analytic description of the source distribution available from the data, and offers the most comprehensive test of the compatibility of a given hypothesized distribution with observation.

The Particle Distribution in Liquid Metal with Ceramic Particles Mould Filling Process

NASA Astrophysics Data System (ADS)

Dong, Qi; Xing, Shu-ming

2017-09-01

Adding ceramic particles in the plate hammer is an effective method to increase the wear resistance of the hammer. The liquid phase method is based on the “with the flow of mixed liquid forging composite preparation of ZTA ceramic particle reinforced high chromium cast iron hammer. Preparation method for this system is using CFD simulation analysis the particles distribution of flow mixing and filling process. Taking the 30% volume fraction of ZTA ceramic composite of high chromium cast iron hammer as example, by changing the speed of liquid metal viscosity to control and make reasonable predictions of particles distribution before solidification.

Disease clusters, exact distributions of maxima, and P-values.

PubMed

Grimson, R C

1993-10-01

This paper presents combinatorial (exact) methods that are useful in the analysis of disease cluster data obtained from small environments, such as buildings and neighbourhoods. Maxwell-Boltzmann and Fermi-Dirac occupancy models are compared in terms of appropriateness of representation of disease incidence patterns (space and/or time) in these environments. The methods are illustrated by a statistical analysis of the incidence pattern of bone fractures in a setting wherein fracture clustering was alleged to be occurring. One of the methodological results derived in this paper is the exact distribution of the maximum cell frequency in occupancy models.

Retrieval of spheroid particle size distribution from spectral extinction data in the independent mode using PCA approach

NASA Astrophysics Data System (ADS)

Tang, Hong; Lin, Jian-Zhong

2013-01-01

An improved anomalous diffraction approximation (ADA) method is presented for calculating the extinction efficiency of spheroids firstly. In this approach, the extinction efficiency of spheroid particles can be calculated with good accuracy and high efficiency in a wider size range by combining the Latimer method and the ADA theory, and this method can present a more general expression for calculating the extinction efficiency of spheroid particles with various complex refractive indices and aspect ratios. Meanwhile, the visible spectral extinction with varied spheroid particle size distributions and complex refractive indices is surveyed. Furthermore, a selection principle about the spectral extinction data is developed based on PCA (principle component analysis) of first derivative spectral extinction. By calculating the contribution rate of first derivative spectral extinction, the spectral extinction with more significant features can be selected as the input data, and those with less features is removed from the inversion data. In addition, we propose an improved Tikhonov iteration method to retrieve the spheroid particle size distributions in the independent mode. Simulation experiments indicate that the spheroid particle size distributions obtained with the proposed method coincide fairly well with the given distributions, and this inversion method provides a simple, reliable and efficient method to retrieve the spheroid particle size distributions from the spectral extinction data.

Technical note: An inverse method to relate organic carbon reactivity to isotope composition from serial oxidation

NASA Astrophysics Data System (ADS)

Hemingway, Jordon D.; Rothman, Daniel H.; Rosengard, Sarah Z.; Galy, Valier V.

2017-11-01

Serial oxidation coupled with stable carbon and radiocarbon analysis of sequentially evolved CO2 is a promising method to characterize the relationship between organic carbon (OC) chemical composition, source, and residence time in the environment. However, observed decay profiles depend on experimental conditions and oxidation pathway. It is therefore necessary to properly assess serial oxidation kinetics before utilizing decay profiles as a measure of OC reactivity. We present a regularized inverse method to estimate the distribution of OC activation energy (E), a proxy for bond strength, using serial oxidation. Here, we apply this method to ramped temperature pyrolysis or oxidation (RPO) analysis but note that this approach is broadly applicable to any serial oxidation technique. RPO analysis directly compares thermal reactivity to isotope composition by determining the E range for OC decaying within each temperature interval over which CO2 is collected. By analyzing a decarbonated test sample at multiple masses and oven ramp rates, we show that OC decay during RPO analysis follows a superposition of parallel first-order kinetics and that resulting E distributions are independent of experimental conditions. We therefore propose the E distribution as a novel proxy to describe OC thermal reactivity and suggest that E vs. isotope relationships can provide new insight into the compositional controls on OC source and residence time.

A Comparative Study of Distribution System Parameter Estimation Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup

2016-07-17

In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less

Application of a frequency distribution method for determining instars of the beet armyworm (Lepidoptera: Noctuidae) from widths of cast head capsules

Treesearch

Y. Chen; S. J. Seybold

2013-01-01

Instar determination of field-collected insect larvae has generally been based on the analysis of head capsule width frequency distributions or bivariate plotting, but few studies have tested the validity of such methods. We used head capsules from exuviae of known instars of the beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae),...

Empirical evidence about inconsistency among studies in a pair-wise meta-analysis.

PubMed

Rhodes, Kirsty M; Turner, Rebecca M; Higgins, Julian P T

2016-12-01

This paper investigates how inconsistency (as measured by the I 2 statistic) among studies in a meta-analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta-analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta-analyses were obtained, which can inform priors for between-study variance. Inconsistency estimates were highest on average for binary outcome meta-analyses of risk differences and continuous outcome meta-analyses. For a planned binary outcome meta-analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta-analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta-analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta-analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

PubMed

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

Multiscale Modeling for the Analysis for Grain-Scale Fracture Within Aluminum Microstructures

NASA Technical Reports Server (NTRS)

Glaessgen, Edward H.; Phillips, Dawn R.; Yamakov, Vesselin; Saether, Erik

2005-01-01

Multiscale modeling methods for the analysis of metallic microstructures are discussed. Both molecular dynamics and the finite element method are used to analyze crack propagation and stress distribution in a nanoscale aluminum bicrystal model subjected to hydrostatic loading. Quantitative similarity is observed between the results from the two very different analysis methods. A bilinear traction-displacement relationship that may be embedded into cohesive zone finite elements is extracted from the nanoscale molecular dynamics results.

Physics and Computational Methods for X-ray Scatter Estimation and Correction in Cone-Beam Computed Tomography

NASA Astrophysics Data System (ADS)

Bootsma, Gregory J.

X-ray scatter in cone-beam computed tomography (CBCT) is known to reduce image quality by introducing image artifacts, reducing contrast, and limiting computed tomography (CT) number accuracy. The extent of the effect of x-ray scatter on CBCT image quality is determined by the shape and magnitude of the scatter distribution in the projections. A method to allay the effects of scatter is imperative to enable application of CBCT to solve a wider domain of clinical problems. The work contained herein proposes such a method. A characterization of the scatter distribution through the use of a validated Monte Carlo (MC) model is carried out. The effects of imaging parameters and compensators on the scatter distribution are investigated. The spectral frequency components of the scatter distribution in CBCT projection sets are analyzed using Fourier analysis and found to reside predominately in the low frequency domain. The exact frequency extents of the scatter distribution are explored for different imaging configurations and patient geometries. Based on the Fourier analysis it is hypothesized the scatter distribution can be represented by a finite sum of sine and cosine functions. The fitting of MC scatter distribution estimates enables the reduction of the MC computation time by diminishing the number of photon tracks required by over three orders of magnitude. The fitting method is incorporated into a novel scatter correction method using an algorithm that simultaneously combines multiple MC scatter simulations. Running concurrent MC simulations while simultaneously fitting the results allows for the physical accuracy and flexibility of MC methods to be maintained while enhancing the overall efficiency. CBCT projection set scatter estimates, using the algorithm, are computed on the order of 1--2 minutes instead of hours or days. Resulting scatter corrected reconstructions show a reduction in artifacts and improvement in tissue contrast and voxel value accuracy.

Thermal stress analysis for a wood composite blade. [wind turbines

NASA Technical Reports Server (NTRS)

Fu, K. C.; Harb, A.

1984-01-01

Heat conduction throughout the blade and the distribution of thermal stresses caused by the temperature distribution were determined for a laminated wood wind turbine blade in both the horizontal and vertical positions. Results show that blade cracking is not due to thermal stresses induced by insulation. A method and practical example of thermal stress analysis for an engineering body of orthotropic materials is presented.

Lognormal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of α-Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2010-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log-normal (LN) distribution function (J Nucl Med. 2006;47:1049–1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data. Methods The measured distributions of α-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained log-normal. Conclusion The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:18483086

Moderation analysis with missing data in the predictors.

PubMed

Zhang, Qian; Wang, Lijuan

2017-12-01

The most widely used statistical model for conducting moderation analysis is the moderated multiple regression (MMR) model. In MMR modeling, missing data could pose a challenge, mainly because the interaction term is a product of two or more variables and thus is a nonlinear function of the involved variables. In this study, we consider a simple MMR model, where the effect of the focal predictor X on the outcome Y is moderated by a moderator U. The primary interest is to find ways of estimating and testing the moderation effect with the existence of missing data in X. We mainly focus on cases when X is missing completely at random (MCAR) and missing at random (MAR). Three methods are compared: (a) Normal-distribution-based maximum likelihood estimation (NML); (b) Normal-distribution-based multiple imputation (NMI); and (c) Bayesian estimation (BE). Via simulations, we found that NML and NMI could lead to biased estimates of moderation effects under MAR missingness mechanism. The BE method outperformed NMI and NML for MMR modeling with missing data in the focal predictor, missingness depending on the moderator and/or auxiliary variables, and correctly specified distributions for the focal predictor. In addition, more robust BE methods are needed in terms of the distribution mis-specification problem of the focal predictor. An empirical example was used to illustrate the applications of the methods with a simple sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Ultra-thin carbon-fiber paper fabrication and carbon-fiber distribution homogeneity evaluation method

NASA Astrophysics Data System (ADS)

Zhang, L. F.; Chen, D. Y.; Wang, Q.; Li, H.; Zhao, Z. G.

2018-01-01

A preparation technology of ultra-thin Carbon-fiber paper is reported. Carbon fiber distribution homogeneity has a great influence on the properties of ultra-thin Carbon-fiber paper. In this paper, a self-developed homogeneity analysis system is introduced to assist users to evaluate the distribution homogeneity of Carbon fiber among two or more two-value images of carbon-fiber paper. A relative-uniformity factor W/H is introduced. The experimental results show that the smaller the W/H factor, the higher uniformity of the distribution of Carbon fiber is. The new uniformity-evaluation method provides a practical and reliable tool for analyzing homogeneity of materials.

Single atom catalysts on amorphous supports: A quenched disorder perspective

NASA Astrophysics Data System (ADS)

Peters, Baron; Scott, Susannah L.

2015-03-01

Phenomenological models that invoke catalyst sites with different adsorption constants and rate constants are well-established, but computational and experimental methods are just beginning to provide atomically resolved details about amorphous surfaces and their active sites. This letter develops a statistical transformation from the quenched disorder distribution of site structures to the distribution of activation energies for sites on amorphous supports. We show that the overall kinetics are highly sensitive to the precise nature of the low energy tail in the activation energy distribution. Our analysis motivates further development of systematic methods to identify and understand the most reactive members of the active site distribution.

Analysis of corner cracks at hole by a 3-D weight function method with stresses from finite element method

NASA Technical Reports Server (NTRS)

Zhao, W.; Newman, J. C., Jr.; Sutton, M. A.; Wu, X. R.; Shivakumar, K. N.

1995-01-01

Stress intensity factors for quarter-elliptical corner cracks emanating from a circular hole are determined using a 3-D weight function method combined with a 3-D finite element method. The 3-D finite element method is used to analyze uncracked configuration and provide stress distribution in the region where crack is to occur. Using this stress distribution as input, the 3-D weight function method is used to determine stress intensity factors. Three different loading conditions, i.e. remote tension, remote bending and wedge loading, are considered for a wide range in geometrical parameters. The significance in using 3-D uncracked stress distribution and the difference between single and double corner cracks are studied. Typical crack opening displacements are also provided. Comparisons are made with solutions available in the literature.

Research on the Rural Express Alliance based on ANP improved profit Allocation

NASA Astrophysics Data System (ADS)

Zhuang, Yufeng; Zhang, Bin

2018-01-01

Online shopping platform in rural distribution difficulties, leading to rural online shopping market and logistics market development is slow. At present, China Post and other private courier companies are not possible to do. So we need to build distribution alliances. Reasonable profit allocation mechanism is the key to the stable development of this distribution alliance. So we proposed the Shapley Value Method and the ANP Improved Model to allocate profits. Finally, the rationality of the method is proved by numerical analysis before and after using the corrected Shapley Value.

Analysis of Digital Communication Signals and Extraction of Parameters.

DTIC Science & Technology

1994-12-01

Fast Fourier Transform (FFT). The correlation methods utilize modified time-frequency distributions , where one of these is based on the Wigner - Ville ... Distribution ( WVD ). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNRs).

Metagenomic Analysis of Water Distribution System Bacterial Communities

EPA Science Inventory

The microbial quality of drinking water is assessed using culture-based methods that are highly selective and that tend to underestimate the densities and diversity of microbial populations inhabiting distribution systems. In order to better understand the effect of different dis...

The solution of the optimization problem of small energy complexes using linear programming methods

NASA Astrophysics Data System (ADS)

Ivanin, O. A.; Director, L. B.

2016-11-01

Linear programming methods were used for solving the optimization problem of schemes and operation modes of distributed generation energy complexes. Applicability conditions of simplex method, applied to energy complexes, including installations of renewable energy (solar, wind), diesel-generators and energy storage, considered. The analysis of decomposition algorithms for various schemes of energy complexes was made. The results of optimization calculations for energy complexes, operated autonomously and as a part of distribution grid, are presented.

Comprehensive evaluation of impacts of distributed generation integration in distribution network

NASA Astrophysics Data System (ADS)

Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu

2018-04-01

All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.

Exact posterior computation in non-conjugate Gaussian location-scale parameters models

NASA Astrophysics Data System (ADS)

Andrade, J. A. A.; Rathie, P. N.

2017-12-01

In Bayesian analysis the class of conjugate models allows to obtain exact posterior distributions, however this class quite restrictive in the sense that it involves only a few distributions. In fact, most of the practical applications involves non-conjugate models, thus approximate methods, such as the MCMC algorithms, are required. Although these methods can deal with quite complex structures, some practical problems can make their applications quite time demanding, for example, when we use heavy-tailed distributions, convergence may be difficult, also the Metropolis-Hastings algorithm can become very slow, in addition to the extra work inevitably required on choosing efficient candidate generator distributions. In this work, we draw attention to the special functions as a tools for Bayesian computation, we propose an alternative method for obtaining the posterior distribution in Gaussian non-conjugate models in an exact form. We use complex integration methods based on the H-function in order to obtain the posterior distribution and some of its posterior quantities in an explicit computable form. Two examples are provided in order to illustrate the theory.

Concentration Regimes of Biopolymers Xanthan, Tara, and Clairana, Comparing Dynamic Light Scattering and Distribution of Relaxation Time

PubMed Central

Oliveira, Patrícia D.; Michel, Ricardo C.; McBride, Alan J. A.; Moreira, Angelita S.; Lomba, Rosana F. T.; Vendruscolo, Claire T.

2013-01-01

The aim of this work was to evaluate the utilization of analysis of the distribution of relaxation time (DRT) using a dynamic light back-scattering technique as alternative method for the determination of the concentration regimes in aqueous solutions of biopolymers (xanthan, clairana and tara gums) by an analysis of the overlap (c*) and aggregation (c**) concentrations. The diffusion coefficients were obtained over a range of concentrations for each biopolymer using two methods. The first method analysed the behaviour of the diffusion coefficient as a function of the concentration of the gum solution. This method is based on the analysis of the diffusion coefficient versus the concentration curve. Using the slope of the curves, it was possible to determine the c* and c** for xanthan and tara gum. However, it was not possible to determine the concentration regimes for clairana using this method. The second method was based on an analysis of the DRTs, which showed different numbers of relaxation modes. It was observed that the concentrations at which the number of modes changed corresponded to the c* and c**. Thus, the DRT technique provided an alternative method for the determination of the critical concentrations of biopolymers. PMID:23671627

Non-Gaussian Distributions Affect Identification of Expression Patterns, Functional Annotation, and Prospective Classification in Human Cancer Genomes

PubMed Central

Marko, Nicholas F.; Weil, Robert J.

2012-01-01

Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

NASA Astrophysics Data System (ADS)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

3. Evaluation of unstable lands for interagency watershed analysis

Treesearch

Leslie M. Reid; Robert R. Ziemer; Mark E. Smith; Colin Close

1994-01-01

Abstract - Although methods for evaluating landslide rates and distributions are well developed, much less attention has been paid to evaluating the biological and physical role of landsliding. New directions in land management on Federal lands of the Pacific Northwest now require such evaluations for designing Riparian Reserves. Traditional analysis methods are no...

An Evaluation of Four Methods of Numerical Analysis for Two-Dimensional Airfoil Flows. Revision.

DTIC Science & Technology

1985-07-06

distribution as determined by the Eppler and Chang potential codes for the four airfoil geometries is shown in Figures 3-6. Here, 2 n-- Cp (P-Po)/.5pUo where...SPD- 1037-01. 2) Eppler , R., and D.M. Somers. A Computer Program for the Design and Analysis of Low Speed Airfoils . NASA Technical Memorandum 80210. 3...OF NUMERICAL n ANALYSIS FORI TWO-DIMENSIONAL AIRFOIL FLOWS Roger Burke APPROVED FOR PUBLIC RELEASE: DISTRIBUTION UNLIMITED DAVID TAYLOR NAVAL SHIP R

An adequacy-constrained integrated planning method for effective accommodation of DG and electric vehicles in smart distribution systems

NASA Astrophysics Data System (ADS)

Tan, Zhukui; Xie, Baiming; Zhao, Yuanliang; Dou, Jinyue; Yan, Tong; Liu, Bin; Zeng, Ming

2018-06-01

This paper presents a new integrated planning framework for effective accommodating electric vehicles in smart distribution systems (SDS). The proposed method incorporates various investment options available for the utility collectively, including distributed generation (DG), capacitors and network reinforcement. Using a back-propagation algorithm combined with cost-benefit analysis, the optimal network upgrade plan, allocation and sizing of the selected components are determined, with the purpose of minimizing the total system capital and operating costs of DG and EV accommodation. Furthermore, a new iterative reliability test method is proposed. It can check the optimization results by subsequently simulating the reliability level of the planning scheme, and modify the generation reserve margin to guarantee acceptable adequacy levels for each year of the planning horizon. Numerical results based on a 32-bus distribution system verify the effectiveness of the proposed method.

A Simple Method for Estimating Informative Node Age Priors for the Fossil Calibration of Molecular Divergence Time Analyses

PubMed Central

Nowak, Michael D.; Smith, Andrew B.; Simpson, Carl; Zwickl, Derrick J.

2013-01-01

Molecular divergence time analyses often rely on the age of fossil lineages to calibrate node age estimates. Most divergence time analyses are now performed in a Bayesian framework, where fossil calibrations are incorporated as parametric prior probabilities on node ages. It is widely accepted that an ideal parameterization of such node age prior probabilities should be based on a comprehensive analysis of the fossil record of the clade of interest, but there is currently no generally applicable approach for calculating such informative priors. We provide here a simple and easily implemented method that employs fossil data to estimate the likely amount of missing history prior to the oldest fossil occurrence of a clade, which can be used to fit an informative parametric prior probability distribution on a node age. Specifically, our method uses the extant diversity and the stratigraphic distribution of fossil lineages confidently assigned to a clade to fit a branching model of lineage diversification. Conditioning this on a simple model of fossil preservation, we estimate the likely amount of missing history prior to the oldest fossil occurrence of a clade. The likelihood surface of missing history can then be translated into a parametric prior probability distribution on the age of the clade of interest. We show that the method performs well with simulated fossil distribution data, but that the likelihood surface of missing history can at times be too complex for the distribution-fitting algorithm employed by our software tool. An empirical example of the application of our method is performed to estimate echinoid node ages. A simulation-based sensitivity analysis using the echinoid data set shows that node age prior distributions estimated under poor preservation rates are significantly less informative than those estimated under high preservation rates. PMID:23755303

Distributed bearing fault diagnosis based on vibration analysis

NASA Astrophysics Data System (ADS)

Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

2016-01-01

Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

An analysis of the symmetry issue in the ℓ-distribution method of gas radiation in non-uniform gaseous media

NASA Astrophysics Data System (ADS)

André, Frédéric

2017-03-01

The recently proposed ℓ-distribution/ICE (Iterative Copula Evaluation) method of gas radiation suffers from symmetry issues when applied in highly non-isothermal and non-homogeneous gaseous media. This problem is studied in a detailed theoretical way. The objective of the present paper is: 1/to provide a mathematical analysis of this problem of symmetry and, 2/to suggest a decisive factor, defined in terms of the ratio between the narrow band Planck and Rosseland mean absorption coefficients, to handle this issue. Comparisons of model predictions with reference LBL calculations show that the proposed criterion improves the accuracy of the intuitive ICE method for applications in highly non-uniform gases at high temperatures.

Analysis of digital communication signals and extraction of parameters

NASA Astrophysics Data System (ADS)

Al-Jowder, Anwar

1994-12-01

The signal classification performance of four types of electronics support measure (ESM) communications detection systems is compared from the standpoint of the unintended receiver (interceptor). Typical digital communication signals considered include binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and on-off keying (OOK). The analysis emphasizes the use of available signal processing software. Detection methods compared include broadband energy detection, FFT-based narrowband energy detection, and two correlation methods which employ the fast Fourier transform (FFT). The correlation methods utilize modified time-frequency distributions, where one of these is based on the Wigner-Ville distribution (WVD). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNR's).

Computational methods for analyzing the transmission characteristics of a beta particle magnetic analysis system

NASA Technical Reports Server (NTRS)

Singh, J. J.

1979-01-01

Computational methods were developed to study the trajectories of beta particles (positrons) through a magnetic analysis system as a function of the spatial distribution of the radionuclides in the beta source, size and shape of the source collimator, and the strength of the analyzer magnetic field. On the basis of these methods, the particle flux, their energy spectrum, and source-to-target transit times have been calculated for Na-22 positrons as a function of the analyzer magnetic field and the size and location of the target. These data are in studies requiring parallel beams of positrons of uniform energy such as measurement of the moisture distribution in composite materials. Computer programs for obtaining various trajectories are included.

GIS-based poverty and population distribution analysis in China

NASA Astrophysics Data System (ADS)

Cui, Jing; Wang, Yingjie; Yan, Hong

2009-07-01

Geographically, poverty status is not only related with social-economic factors but also strongly affected by geographical environment. In the paper, GIS-based poverty and population distribution analysis method is introduced for revealing their regional differences. More than 100000 poor villages and 592 national key poor counties are chosen for the analysis. The results show that poverty distribution tends to concentrate in most of west China and mountainous rural areas of mid China. Furthermore, the fifth census data are overlaid to those poor areas in order to gain its internal diversity of social-economic characteristics. By overlaying poverty related social-economic parameters, such as sex ratio, illiteracy, education level, percentage of ethnic minorities, family composition, finding shows that poverty distribution is strongly correlated with high illiteracy rate, high percentage minorities, and larger family member.

The detection methods of dynamic objects

NASA Astrophysics Data System (ADS)

Knyazev, N. L.; Denisova, L. A.

2018-01-01

The article deals with the application of cluster analysis methods for solving the task of aircraft detection on the basis of distribution of navigation parameters selection into groups (clusters). The modified method of cluster analysis for search and detection of objects and then iterative combining in clusters with the subsequent count of their quantity for increase in accuracy of the aircraft detection have been suggested. The course of the method operation and the features of implementation have been considered. In the conclusion the noted efficiency of the offered method for exact cluster analysis for finding targets has been shown.

Performance analysis of the node shell on a container door based on ANSYS

NASA Astrophysics Data System (ADS)

Li, Qingzhou; Zhou, Yi; Hu, Changqing; Cheng, Jiamin; Zeng, Xiaochen

2018-01-01

The structure of thenode shell on a container door was designed and analyzed in this study. The model of the shell was developed with ANSYS. The grids of the model were divided based on the Hex dominant method, and the stress distribution and the temperature distribution of the shell were calculated based on FEA (Finite Element Analysis) method. The analysis results indicated thatthe location of the concave upward side has the highest stress which also lower than the strength limit of the material. The temperature of the magnet installation location was highest, therefore the glue for fixing the magnet must has high temperature resistance. The results provide the basis for the further optimization of the shell.

Particle sizing of pharmaceutical aerosols via direct imaging of particle settling velocities.

PubMed

Fishler, Rami; Verhoeven, Frank; de Kruijf, Wilbur; Sznitman, Josué

2018-02-15

We present a novel method for characterizing in near real-time the aerodynamic particle size distributions from pharmaceutical inhalers. The proposed method is based on direct imaging of airborne particles followed by a particle-by-particle measurement of settling velocities using image analysis and particle tracking algorithms. Due to the simplicity of the principle of operation, this method has the potential of circumventing potential biases of current real-time particle analyzers (e.g. Time of Flight analysis), while offering a cost effective solution. The simple device can also be constructed in laboratory settings from off-the-shelf materials for research purposes. To demonstrate the feasibility and robustness of the measurement technique, we have conducted benchmark experiments whereby aerodynamic particle size distributions are obtained from several commercially-available dry powder inhalers (DPIs). Our measurements yield size distributions (i.e. MMAD and GSD) that are closely in line with those obtained from Time of Flight analysis and cascade impactors suggesting that our imaging-based method may embody an attractive methodology for rapid inhaler testing and characterization. In a final step, we discuss some of the ongoing limitations of the current prototype and conceivable routes for improving the technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Audio feature extraction using probability distribution function

NASA Astrophysics Data System (ADS)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Uncertainty Analysis Based on Sparse Grid Collocation and Quasi-Monte Carlo Sampling with Application in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Zhang, G.; Lu, D.; Ye, M.; Gunzburger, M.

2011-12-01

Markov Chain Monte Carlo (MCMC) methods have been widely used in many fields of uncertainty analysis to estimate the posterior distributions of parameters and credible intervals of predictions in the Bayesian framework. However, in practice, MCMC may be computationally unaffordable due to slow convergence and the excessive number of forward model executions required, especially when the forward model is expensive to compute. Both disadvantages arise from the curse of dimensionality, i.e., the posterior distribution is usually a multivariate function of parameters. Recently, sparse grid method has been demonstrated to be an effective technique for coping with high-dimensional interpolation or integration problems. Thus, in order to accelerate the forward model and avoid the slow convergence of MCMC, we propose a new method for uncertainty analysis based on sparse grid interpolation and quasi-Monte Carlo sampling. First, we construct a polynomial approximation of the forward model in the parameter space by using the sparse grid interpolation. This approximation then defines an accurate surrogate posterior distribution that can be evaluated repeatedly at minimal computational cost. Second, instead of using MCMC, a quasi-Monte Carlo method is applied to draw samples in the parameter space. Then, the desired probability density function of each prediction is approximated by accumulating the posterior density values of all the samples according to the prediction values. Our method has the following advantages: (1) the polynomial approximation of the forward model on the sparse grid provides a very efficient evaluation of the surrogate posterior distribution; (2) the quasi-Monte Carlo method retains the same accuracy in approximating the PDF of predictions but avoids all disadvantages of MCMC. The proposed method is applied to a controlled numerical experiment of groundwater flow modeling. The results show that our method attains the same accuracy much more efficiently than traditional MCMC.

Calculated spanwise lift distributions, influence functions, and influence coefficients for unswept wings in subsonic flow

NASA Technical Reports Server (NTRS)

Diederich, Franklin W; Zlotnick, Martin

1955-01-01

Spanwise lift distributions have been calculated for nineteen unswept wings with various aspect ratios and taper ratios and with a variety of angle-of-attack or twist distributions, including flap and aileron deflections, by means of the Weissinger method with eight control points on the semispan. Also calculated were aerodynamic influence coefficients which pertain to a certain definite set of stations along the span, and several methods are presented for calculating aerodynamic influence functions and coefficients for stations other than those stipulated. The information presented in this report can be used in the analysis of untwisted wings or wings with known twist distributions, as well as in aeroelastic calculations involving initially unknown twist distributions.

WebDISCO: a web service for distributed cox model learning without patient-level data sharing.

PubMed

Lu, Chia-Lun; Wang, Shuang; Ji, Zhanglong; Wu, Yuan; Xiong, Li; Jiang, Xiaoqian; Ohno-Machado, Lucila

2015-11-01

The Cox proportional hazards model is a widely used method for analyzing survival data. To achieve sufficient statistical power in a survival analysis, it usually requires a large amount of data. Data sharing across institutions could be a potential workaround for providing this added power. The authors develop a web service for distributed Cox model learning (WebDISCO), which focuses on the proof-of-concept and algorithm development for federated survival analysis. The sensitive patient-level data can be processed locally and only the less-sensitive intermediate statistics are exchanged to build a global Cox model. Mathematical derivation shows that the proposed distributed algorithm is identical to the centralized Cox model. The authors evaluated the proposed framework at the University of California, San Diego (UCSD), Emory, and Duke. The experimental results show that both distributed and centralized models result in near-identical model coefficients with differences in the range [Formula: see text] to [Formula: see text]. The results confirm the mathematical derivation and show that the implementation of the distributed model can achieve the same results as the centralized implementation. The proposed method serves as a proof of concept, in which a publicly available dataset was used to evaluate the performance. The authors do not intend to suggest that this method can resolve policy and engineering issues related to the federated use of institutional data, but they should serve as evidence of the technical feasibility of the proposed approach.Conclusions WebDISCO (Web-based Distributed Cox Regression Model; https://webdisco.ucsd-dbmi.org:8443/cox/) provides a proof-of-concept web service that implements a distributed algorithm to conduct distributed survival analysis without sharing patient level data. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

PubMed Central

Huang, Lawrence; Helmke, Brian P.

2011-01-01

Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 µm of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization. PMID:21643526

An Improved Time-Frequency Analysis Method in Interference Detection for GNSS Receivers

PubMed Central

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-01-01

In this paper, an improved joint time-frequency (TF) analysis method based on a reassigned smoothed pseudo Wigner–Ville distribution (RSPWVD) has been proposed in interference detection for Global Navigation Satellite System (GNSS) receivers. In the RSPWVD, the two-dimensional low-pass filtering smoothing function is introduced to eliminate the cross-terms present in the quadratic TF distribution, and at the same time, the reassignment method is adopted to improve the TF concentration properties of the auto-terms of the signal components. This proposed interference detection method is evaluated by experiments on GPS L1 signals in the disturbing scenarios compared to the state-of-the-art interference detection approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-terms problem and also preserves good TF localization properties, which has been proven to be effective and valid to enhance the interference detection performance of the GNSS receivers, particularly in the jamming environments. PMID:25905704

Dynamic analysis of ultrasonically levitated droplet with moving particle semi-implicit and distributed point source method

NASA Astrophysics Data System (ADS)

Wada, Yuji; Yuge, Kohei; Nakamura, Ryohei; Tanaka, Hiroki; Nakamura, Kentaro

2015-07-01

Numerical analysis of an ultrasonically levitated droplet with a free surface boundary is discussed. The droplet is known to change its shape from sphere to spheroid when it is suspended in a standing wave owing to the acoustic radiation force. However, few studies on numerical simulation have been reported in association with this phenomenon including fluid dynamics inside the droplet. In this paper, coupled analysis using the distributed point source method (DPSM) and the moving particle semi-implicit (MPS) method, both of which do not require grids or meshes to handle the moving boundary with ease, is suggested. A droplet levitated in a plane standing wave field between a piston-vibrating ultrasonic transducer and a reflector is simulated with the DPSM-MPS coupled method. The dynamic change in the spheroidal shape of the droplet is successfully reproduced numerically, and the gravitational center and the change in the spheroidal aspect ratio are discussed and compared with the previous literature.

The fundamental parameter method applied to X-ray fluorescence analysis with synchrotron radiation

NASA Astrophysics Data System (ADS)

Pantenburg, F. J.; Beier, T.; Hennrich, F.; Mommsen, H.

1992-05-01

Quantitative X-ray fluorescence analysis applying the fundamental parameter method is usually restricted to monochromatic excitation sources. It is shown here, that such analyses can be performed as well with a white synchrotron radiation spectrum. To determine absolute elemental concentration values it is necessary to know the spectral distribution of this spectrum. A newly designed and tested experimental setup, which uses the synchrotron radiation emitted from electrons in a bending magnet of ELSA (electron stretcher accelerator of the university of Bonn) is presented. The determination of the exciting spectrum, described by the given electron beam parameters, is limited due to uncertainties in the vertical electron beam size and divergence. We describe a method which allows us to determine the relative and absolute spectral distributions needed for accurate analysis. First test measurements of different alloys and standards of known composition demonstrate that it is possible to determine exact concentration values in bulk and trace element analysis.

Methodology to model the energy and greenhouse gas emissions of electronic software distributions.

PubMed

Williams, Daniel R; Tang, Yinshan

2012-01-17

A new electronic software distribution (ESD) life cycle analysis (LCA) methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative, physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO(2)e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO(2)e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

Nonlinear Trimodal Regression Analysis of Radiodensitometric Distributions to Quantify Sarcopenic and Sequelae Muscle Degeneration

PubMed Central

Árnadóttir, Í.; Gíslason, M. K.; Carraro, U.

2016-01-01

Muscle degeneration has been consistently identified as an independent risk factor for high mortality in both aging populations and individuals suffering from neuromuscular pathology or injury. While there is much extant literature on its quantification and correlation to comorbidities, a quantitative gold standard for analyses in this regard remains undefined. Herein, we hypothesize that rigorously quantifying entire radiodensitometric distributions elicits more muscle quality information than average values reported in extant methods. This study reports the development and utility of a nonlinear trimodal regression analysis method utilized on radiodensitometric distributions of upper leg muscles from CT scans of a healthy young adult, a healthy elderly subject, and a spinal cord injury patient. The method was then employed with a THA cohort to assess pre- and postsurgical differences in their healthy and operative legs. Results from the initial representative models elicited high degrees of correlation to HU distributions, and regression parameters highlighted physiologically evident differences between subjects. Furthermore, results from the THA cohort echoed physiological justification and indicated significant improvements in muscle quality in both legs following surgery. Altogether, these results highlight the utility of novel parameters from entire HU distributions that could provide insight into the optimal quantification of muscle degeneration. PMID:28115982

Dictionaries and distributions: Combining expert knowledge and large scale textual data content analysis : Distributed dictionary representation.

PubMed

Garten, Justin; Hoover, Joe; Johnson, Kate M; Boghrati, Reihane; Iskiwitch, Carol; Dehghani, Morteza

2018-02-01

Theory-driven text analysis has made extensive use of psychological concept dictionaries, leading to a wide range of important results. These dictionaries have generally been applied through word count methods which have proven to be both simple and effective. In this paper, we introduce Distributed Dictionary Representations (DDR), a method that applies psychological dictionaries using semantic similarity rather than word counts. This allows for the measurement of the similarity between dictionaries and spans of text ranging from complete documents to individual words. We show how DDR enables dictionary authors to place greater emphasis on construct validity without sacrificing linguistic coverage. We further demonstrate the benefits of DDR on two real-world tasks and finally conduct an extensive study of the interaction between dictionary size and task performance. These studies allow us to examine how DDR and word count methods complement one another as tools for applying concept dictionaries and where each is best applied. Finally, we provide references to tools and resources to make this method both available and accessible to a broad psychological audience.

Geospatial methods and data analysis for assessing distribution of grazing livestock

USDA-ARS?s Scientific Manuscript database

Free-ranging livestock research must begin with a well conceived problem statement and employ appropriate data acquisition tools and analytical techniques to accomplish the research objective. These requirements are especially critical in addressing animal distribution. Tools and statistics used t...

MNE software for processing MEG and EEG data

PubMed Central

Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.

2013-01-01

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808

A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance Structure Models to Block-Toeplitz Matrices Representing Single-Subject Multivariate Time-Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

1998-01-01

Pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation methods for estimating dynamic factor model parameters within a covariance structure framework were compared through a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates, but only ADF gives standard errors and chi-square…

Estimate of uncertainties in polarized parton distributions

NASA Astrophysics Data System (ADS)

Miyama, M.; Goto, Y.; Hirai, M.; Kobayashi, H.; Kumano, S.; Morii, T.; Saito, N.; Shibata, T.-A.; Yamanishi, T.

2001-10-01

From \\chi^2 analysis of polarized deep inelastic scattering data, we determined polarized parton distribution functions (Y. Goto et al. (AAC), Phys. Rev. D 62, 34017 (2000).). In order to clarify the reliability of the obtained distributions, we should estimate uncertainties of the distributions. In this talk, we discuss the pol-PDF uncertainties by using a Hessian method. A Hessian matrix H_ij is given by second derivatives of the \\chi^2, and the error matrix \\varepsilon_ij is defined as the inverse matrix of H_ij. Using the error matrix, we calculate the error of a function F by (δ F)^2 = sum_i,j fracpartial Fpartial ai \\varepsilon_ij fracpartial Fpartial aj , where a_i,j are the parameters in the \\chi^2 analysis. Using this method, we show the uncertainties of the pol-PDF, structure functions g_1, and spin asymmetries A_1. Furthermore, we show a role of future experiments such as the RHIC-Spin. An important purpose of planned experiments in the near future is to determine the polarized gluon distribution function Δ g (x) in detail. We reanalyze the pol-PDF uncertainties including the gluon fake data which are expected to be given by the upcoming experiments. From this analysis, we discuss how much the uncertainties of Δ g (x) can be improved by such measurements.

A computer program for the design and analysis of low-speed airfoils

NASA Technical Reports Server (NTRS)

Eppler, R.; Somers, D. M.

1980-01-01

A conformal mapping method for the design of airfoils with prescribed velocity distribution characteristics, a panel method for the analysis of the potential flow about given airfoils, and a boundary layer method have been combined. With this combined method, airfoils with prescribed boundary layer characteristics can be designed and airfoils with prescribed shapes can be analyzed. All three methods are described briefly. The program and its input options are described. A complete listing is given as an appendix.

Valuing vaccines using value of statistical life measures.

PubMed

Laxminarayan, Ramanan; Jamison, Dean T; Krupnick, Alan J; Norheim, Ole F

2014-09-03

Vaccines are effective tools to improve human health, but resources to pursue all vaccine-related investments are lacking. Benefit-cost and cost-effectiveness analysis are the two major methodological approaches used to assess the impact, efficiency, and distributional consequences of disease interventions, including those related to vaccinations. Childhood vaccinations can have important non-health consequences for productivity and economic well-being through multiple channels, including school attendance, physical growth, and cognitive ability. Benefit-cost analysis would capture such non-health benefits; cost-effectiveness analysis does not. Standard cost-effectiveness analysis may grossly underestimate the benefits of vaccines. A specific willingness-to-pay measure is based on the notion of the value of a statistical life (VSL), derived from trade-offs people are willing to make between fatality risk and wealth. Such methods have been used widely in the environmental and health literature to capture the broader economic benefits of improving health, but reservations remain about their acceptability. These reservations remain mainly because the methods may reflect ability to pay, and hence be discriminatory against the poor. However, willingness-to-pay methods can be made sensitive to income distribution by using appropriate income-sensitive distributional weights. Here, we describe the pros and cons of these methods and how they compare against standard cost-effectiveness analysis using pure health metrics, such as quality-adjusted life years (QALYs) and disability-adjusted life years (DALYs), in the context of vaccine priorities. We conclude that if appropriately used, willingness-to-pay methods will not discriminate against the poor, and they can capture important non-health benefits such as financial risk protection, productivity gains, and economic wellbeing. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis on Voltage Profile of Distribution Network with Distributed Generation

NASA Astrophysics Data System (ADS)

Shao, Hua; Shi, Yujie; Yuan, Jianpu; An, Jiakun; Yang, Jianhua

2018-02-01

Penetration of distributed generation has some impacts on a distribution network in load flow, voltage profile, reliability, power loss and so on. After the impacts and the typical structures of the grid-connected distributed generation are analyzed, the back/forward sweep method of the load flow calculation of the distribution network is modelled including distributed generation. The voltage profiles of the distribution network affected by the installation location and the capacity of distributed generation are thoroughly investigated and simulated. The impacts on the voltage profiles are summarized and some suggestions to the installation location and the capacity of distributed generation are given correspondingly.

Fluctuation-Enhanced Sensing for Biological Agent Detection and Identification

DTIC Science & Technology

2009-01-01

method for bacterium detection published earlier; sensing and evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise...REPORT TYPE 3. DATES COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE Fluctuation-Enhanced Sensing for Biological Agent Detection and...evaluating the odors of microbes ; and spectral and amplitude distribution analysis of noise in light scattering to identify spores based on their

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Zhiqiang; Department of Materials Science and Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706; Geng, Dalong

A simple and effective decoupled finite element analysis method was developed for simulating both the piezoelectric and flexoelectric effects of zinc oxide (ZnO) and barium titanate (BTO) nanowires (NWs). The piezoelectric potential distribution on a ZnO NW was calculated under three deformation conditions (cantilever, three-point, and four-point bending) and compared to the conventional fully coupled method. The discrepancies of the electric potential maximums from these two methods were found very small, validating the accuracy and effectiveness of the decoupled method. Both ZnO and BTO NWs yielded very similar potential distributions. Comparing the potential distributions induced by the piezoelectric and flexoelectricmore » effects, we identified that the middle segment of a four-point bending NW beam is the ideal place for measuring the flexoelectric coefficient, because the uniform parallel plate capacitor-like potential distribution in this region is exclusively induced by the flexoelectric effect. This decoupled method could provide a valuable guideline for experimental measurements of the piezoelectric effects and flexoelectric effects in the nanometer scale.« less

Determination of the proton-to-helium ratio in cosmic rays at ultra-high energies from the tail of the Xmax distribution

NASA Astrophysics Data System (ADS)

Yushkov, A.; Risse, M.; Werner, M.; Krieg, J.

2016-12-01

We present a method to determine the proton-to-helium ratio in cosmic rays at ultra-high energies. It makes use of the exponential slope, Λ, of the tail of the Xmax distribution measured by an air shower experiment. The method is quite robust with respect to uncertainties from modeling hadronic interactions and to systematic errors on Xmax and energy, and to the possible presence of primary nuclei heavier than helium. Obtaining the proton-to-helium ratio with air shower experiments would be a remarkable achievement. To quantify the applicability of a particular mass-sensitive variable for mass composition analysis despite hadronic uncertainties we introduce as a metric the 'analysis indicator' and find an improved performance of the Λ method compared to other variables currently used in the literature. The fraction of events in the tail of the Xmax distribution can provide additional information on the presence of nuclei heavier than helium in the primary beam.

Extended method of moments for deterministic analysis of stochastic multistable neurodynamical systems

NASA Astrophysics Data System (ADS)

Deco, Gustavo; Martí, Daniel

2007-03-01

The analysis of transitions in stochastic neurodynamical systems is essential to understand the computational principles that underlie those perceptual and cognitive processes involving multistable phenomena, like decision making and bistable perception. To investigate the role of noise in a multistable neurodynamical system described by coupled differential equations, one usually considers numerical simulations, which are time consuming because of the need for sufficiently many trials to capture the statistics of the influence of the fluctuations on that system. An alternative analytical approach involves the derivation of deterministic differential equations for the moments of the distribution of the activity of the neuronal populations. However, the application of the method of moments is restricted by the assumption that the distribution of the state variables of the system takes on a unimodal Gaussian shape. We extend in this paper the classical moments method to the case of bimodal distribution of the state variables, such that a reduced system of deterministic coupled differential equations can be derived for the desired regime of multistability.

Advanced statistical methods for improved data analysis of NASA astrophysics missions

NASA Technical Reports Server (NTRS)

Feigelson, Eric D.

1992-01-01

The investigators under this grant studied ways to improve the statistical analysis of astronomical data. They looked at existing techniques, the development of new techniques, and the production and distribution of specialized software to the astronomical community. Abstracts of nine papers that were produced are included, as well as brief descriptions of four software packages. The articles that are abstracted discuss analytical and Monte Carlo comparisons of six different linear least squares fits, a (second) paper on linear regression in astronomy, two reviews of public domain software for the astronomer, subsample and half-sample methods for estimating sampling distributions, a nonparametric estimation of survival functions under dependent competing risks, censoring in astronomical data due to nondetections, an astronomy survival analysis computer package called ASURV, and improving the statistical methodology of astronomical data analysis.

Gene Level Meta-Analysis of Quantitative Traits by Functional Linear Models.

PubMed

Fan, Ruzong; Wang, Yifan; Boehnke, Michael; Chen, Wei; Li, Yun; Ren, Haobo; Lobach, Iryna; Xiong, Momiao

2015-08-01

Meta-analysis of genetic data must account for differences among studies including study designs, markers genotyped, and covariates. The effects of genetic variants may differ from population to population, i.e., heterogeneity. Thus, meta-analysis of combining data of multiple studies is difficult. Novel statistical methods for meta-analysis are needed. In this article, functional linear models are developed for meta-analyses that connect genetic data to quantitative traits, adjusting for covariates. The models can be used to analyze rare variants, common variants, or a combination of the two. Both likelihood-ratio test (LRT) and F-distributed statistics are introduced to test association between quantitative traits and multiple variants in one genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed tests. The proposed LRT and F-distributed statistics control the type I error very well and have higher power than the existing methods of the meta-analysis sequence kernel association test (MetaSKAT). We analyze four blood lipid levels in data from a meta-analysis of eight European studies. The proposed methods detect more significant associations than MetaSKAT and the P-values of the proposed LRT and F-distributed statistics are usually much smaller than those of MetaSKAT. The functional linear models and related test statistics can be useful in whole-genome and whole-exome association studies. Copyright © 2015 by the Genetics Society of America.

An agarose gel electrophoretic method for analysis of hyaluronan molecular weight distribution.

PubMed

Lee, H G; Cowman, M K

1994-06-01

An electrophoretic method is described for determining the molecular weight distribution of hyaluronan (HA). The method involves separation of HA by electrophoresis on a 0.5% agarose gel, followed by detection of HA using the cationic dye Stains-All (3,3'-dimethyl-9-methyl-4,5,4'5'-dibenzothiacarbocyanine). The recommended sample load is 7 micrograms. Calibration of the method with HA standards of known molecular weight has established a linear relationship between electrophoretic mobility and the logarithm of the weight-average molecular weight over the range of approximately 0.2-6 x 10(6). The separated HA pattern may also be visualized after electrotransfer of HA from the agarose gel to a nylon membrane. The membrane may be stained with the dye alcian blue. Alternatively, specific detection of HA from impure samples can be achieved by probing the nylon membrane with biotin-labeled HA-binding protein and subsequent interaction with a streptavidin-linked gold reagent and silver staining for amplification. The electrophoretic method was used to analyze HA in two different liquid connective tissues. Normal human knee joint synovial fluid showed a narrow HA molecular weight distribution, with a peak at 6-7 x 10(6). Owl monkey vitreous HA also showed a narrow molecular weight distribution, with a peak at 5-6 x 10(6). These results agree well with available published data and indicate the applicability of the method to the analysis of impure HA samples which may be available in limited amounts.

Bivariate drought frequency analysis using the copula method

NASA Astrophysics Data System (ADS)

Mirabbasi, Rasoul; Fakheri-Fard, Ahmad; Dinpashoh, Yagob

2012-04-01

Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.

Inter-cohort growth for three tropical resources: tilapia, octopus and lobster.

PubMed

Velázquez-Abunader, Iván; Gómez-Muñoz, Victor Manuel; Salas, Silvia; Ruiz-Velazco, Javier M J

2015-09-01

Growth parameters are an important component for the stock assessment of exploited aquatic species. However, it is often difficult to apply direct methods to estimate growth and to analyse the differences between males and females, particularly in tropical areas. The objective of this study was to analyse the inter-cohort growth of three tropical resources and discuss the possible fisheries management implications. A simple method was used to compare individual growth curves obtained from length frequency distribution analysis, illustrated by case studies of three tropical species from different aquatic environments: tilapia (Oreochromis aureus), red octopus (Octopus maya) and the Caribbean spiny lobster (Panulirus argus). The analysis undertaken compared the size distribution of males and females of a given cohort through modal progression analysis. The technique used proved to be useful for highlighting the differences in growth between females and males of a specific cohort. The potential effect of extrinsic and intrinsic factors on the organism's development as reflected in the size distribution of the cohorts is discussed.

Multifractal characteristics of multiparticle production in heavy-ion collisions at SPS energies

NASA Astrophysics Data System (ADS)

Khan, Shaista; Ahmad, Shakeel

Entropy, dimensions and other multifractal characteristics of multiplicity distributions of relativistic charged hadrons produced in ion-ion collisions at SPS energies are investigated. The analysis of the experimental data is carried out in terms of phase space bin-size dependence of multiplicity distributions following the Takagi’s approach. Yet another method is also followed to study the multifractality which, is not related to the bin-width and (or) the detector resolution, rather involves multiplicity distribution of charged particles in full phase space in terms of information entropy and its generalization, Rényi’s order-q information entropy. The findings reveal the presence of multifractal structure — a remarkable property of the fluctuations. Nearly constant values of multifractal specific heat “c” estimated by the two different methods of analysis followed indicate that the parameter “c” may be used as a universal characteristic of the particle production in high energy collisions. The results obtained from the analysis of the experimental data agree well with the predictions of Monte Carlo model AMPT.

Novel microbiological and spatial statistical methods to improve strength of epidemiological evidence in a community-wide waterborne outbreak.

PubMed

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9-16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak.

Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies.

PubMed

Fornasaro, Stefano; Vicario, Annalisa; De Leo, Luigina; Bonifacio, Alois; Not, Tarcisio; Sergo, Valter

2018-05-14

Raman hyperspectral imaging is an emerging practice in biological and biomedical research for label free analysis of tissues and cells. Using this method, both spatial distribution and spectral information of analyzed samples can be obtained. The current study reports the first Raman microspectroscopic characterisation of colon tissues from patients with Coeliac Disease (CD). The aim was to assess if Raman imaging coupled with hyperspectral multivariate image analysis is capable of detecting the alterations in the biochemical composition of intestinal tissues associated with CD. The analytical approach was based on a multi-step methodology: duodenal biopsies from healthy and coeliac patients were measured and processed with Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). Based on the distribution maps and the pure spectra of the image constituents obtained from MCR-ALS, interesting biochemical differences between healthy and coeliac patients has been derived. Noticeably, a reduced distribution of complex lipids in the pericryptic space, and a different distribution and abundance of proteins rich in beta-sheet structures was found in CD patients. The output of the MCR-ALS analysis was then used as a starting point for two clustering algorithms (k-means clustering and hierarchical clustering methods). Both methods converged with similar results providing precise segmentation over multiple Raman images of studied tissues.

Progress Toward Efficient Laminar Flow Analysis and Design

NASA Technical Reports Server (NTRS)

Campbell, Richard L.; Campbell, Matthew L.; Streit, Thomas

2011-01-01

A multi-fidelity system of computer codes for the analysis and design of vehicles having extensive areas of laminar flow is under development at the NASA Langley Research Center. The overall approach consists of the loose coupling of a flow solver, a transition prediction method and a design module using shell scripts, along with interface modules to prepare the input for each method. This approach allows the user to select the flow solver and transition prediction module, as well as run mode for each code, based on the fidelity most compatible with the problem and available resources. The design module can be any method that designs to a specified target pressure distribution. In addition to the interface modules, two new components have been developed: 1) an efficient, empirical transition prediction module (MATTC) that provides n-factor growth distributions without requiring boundary layer information; and 2) an automated target pressure generation code (ATPG) that develops a target pressure distribution that meets a variety of flow and geometry constraints. The ATPG code also includes empirical estimates of several drag components to allow the optimization of the target pressure distribution. The current system has been developed for the design of subsonic and transonic airfoils and wings, but may be extendable to other speed ranges and components. Several analysis and design examples are included to demonstrate the current capabilities of the system.

q-Gaussian distributions and multiplicative stochastic processes for analysis of multiple financial time series

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2010-12-01

This study considers q-Gaussian distributions and stochastic differential equations with both multiplicative and additive noises. In the M-dimensional case a q-Gaussian distribution can be theoretically derived as a stationary probability distribution of the multiplicative stochastic differential equation with both mutually independent multiplicative and additive noises. By using the proposed stochastic differential equation a method to evaluate a default probability under a given risk buffer is proposed.

Uncertainty of Polarized Parton Distributions

NASA Astrophysics Data System (ADS)

Hirai, M.; Goto, Y.; Horaguchi, T.; Kobayashi, H.; Kumano, S.; Miyama, M.; Saito, N.; Shibata, T.-A.

Polarized parton distribution functions are determined by a χ2 analysis of polarized deep inelastic experimental data. In this paper, uncertainty of obtained distribution functions is investigated by a Hessian method. We find that the uncertainty of the polarized gluon distribution is fairly large. Then, we estimate the gluon uncertainty by including the fake data which are generated from prompt photon process at RHIC. We observed that the uncertainty could be reduced with these data.

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

NanoSIMS analysis of Bacillus spores for forensics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, P K; Davisson, M L; Velsko, S P

2010-02-23

The threat associated with the potential use of radiological, nuclear, chemical and biological materials in terrorist acts has resulted in new fields of forensic science requiring the application of state-of-the-science analytical techniques. Since the anthrax letter attacks in the United States in the fall of 2001, there has been increased interest in physical and chemical characterization of bacterial spores. While molecular methods are powerful tools for identifying genetic differences, other methods may be able to differentiate genetically identical samples based on physical and chemical properties, as well as provide complimentary information, such as methods of production and approximate date ofmore » production. Microanalysis has the potential to contribute significantly to microbial forensics. Bacillus spores are highly structured, consisting of a core, cortex, coat, and in some species, an exosporium. This structure provides a template for constraining elemental abundance differences at the nanometer scale. The primary controls on the distribution of major elements in spores are likely structural and physiological. For example, P and Ca are known to be abundant in the spore core because that is where P-rich nucleic acids and Cadipicolinic acid are located, respectively. Trace elements are known to bind to the spore coat but the controls on these elements are less well understood. Elemental distributions and abundances may be directly related to spore production, purification and stabilization methodologies, which are of particular interest for forensic investigation. To this end, we are developing a high-resolution secondary ion mass spectrometry method using a Cameca NanoSIMS 50 to study the distribution and abundance of trace elements in bacterial spores. In this presentation we will review and compare methods for preparing and analyzing samples, as well as review results on the distribution and abundance of elements in bacterial spores. We use NanoSIMS to directly image samples as well as depth profile samples. The directly imaged samples are sectioned to present a flat surface for analysis. We use focused ion beam (FIB) milling to top-cut individual spores to create flat surfaces for NanoSIMS analysis. Depth profiling can be used on whole spores, which are consumed in the process of analysis. The two methods generate comparable results, with the expected distribution of P and Ca. Ca-compatible elements, such as Mg and Mn, are found to follow the distribution of Ca. The distribution of other elements will be discussed. We envision the first application of this methodology will be to sample matching for trace samples. Towards this end, we are generating a baseline data set for samples produced by multiple laboratories. Preliminary results suggest that this method provides significant probative value for identifying samples produced by the same method in the same laboratory, as well as coming from the same initial production run. The results of this study will be presented.« less

Pulsed Laser Ablation-Induced Green Synthesis of TiO2 Nanoparticles and Application of Novel Small Angle X-Ray Scattering Technique for Nanoparticle Size and Size Distribution Analysis.

PubMed

Singh, Amandeep; Vihinen, Jorma; Frankberg, Erkka; Hyvärinen, Leo; Honkanen, Mari; Levänen, Erkki

2016-12-01

This paper aims to introduce small angle X-ray scattering (SAXS) as a promising technique for measuring size and size distribution of TiO 2 nanoparticles. In this manuscript, pulsed laser ablation in liquids (PLAL) has been demonstrated as a quick and simple technique for synthesizing TiO 2 nanoparticles directly into deionized water as a suspension from titanium targets. Spherical TiO 2 nanoparticles with diameters in the range 4-35 nm were observed with transmission electron microscopy (TEM). X-ray diffraction (XRD) showed highly crystalline nanoparticles that comprised of two main photoactive phases of TiO 2 : anatase and rutile. However, presence of minor amounts of brookite was also reported. The traditional methods for nanoparticle size and size distribution analysis such as electron microscopy-based methods are time-consuming. In this study, we have proposed and validated SAXS as a promising method for characterization of laser-ablated TiO 2 nanoparticles for their size and size distribution by comparing SAXS- and TEM-measured nanoparticle size and size distribution. SAXS- and TEM-measured size distributions closely followed each other for each sample, and size distributions in both showed maxima at the same nanoparticle size. The SAXS-measured nanoparticle diameters were slightly larger than the respective diameters measured by TEM. This was because SAXS measures an agglomerate consisting of several particles as one big particle which slightly increased the mean diameter. TEM- and SAXS-measured mean diameters when plotted together showed similar trend in the variation in the size as the laser power was changed which along with extremely similar size distributions for TEM and SAXS validated the application of SAXS for size distribution measurement of the synthesized TiO 2 nanoparticles.

Frequency Analysis Using Bootstrap Method and SIR Algorithm for Prevention of Natural Disasters

NASA Astrophysics Data System (ADS)

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).

Interactions and reversal-field memory in complex magnetic nanowire arrays

NASA Astrophysics Data System (ADS)

Rotaru, Aurelian; Lim, Jin-Hee; Lenormand, Denny; Diaconu, Andrei; Wiley, John. B.; Postolache, Petronel; Stancu, Alexandru; Spinu, Leonard

2011-10-01

Interactions and magnetization reversal of Ni nanowire arrays have been investigated by the first-order reversal curve (FORC) method. Several series of samples with controlled spatial distribution were considered including simple wires of different lengths and diameters (70 and 110 nm) and complex wires with a single modulated diameter along their length. Subtle features of magnetic interactions are revealed through a quantitative analysis of the local interaction field profile distributions obtained from the FORC method. In addition, the FORC analysis indicates that the nanowire systems with a mean diameter of 70 nm appear to be organized in symmetric clusters indicative of a reversal-field memory effect.

Photometric geodesy of main-belt asteroids. IV - An updated analysis of lightcurves for poles, periods, and shapes

NASA Technical Reports Server (NTRS)

Drummond, J. D.; Weidenschilling, S. J.; Chapman, C. R.; Davis, D. R.

1991-01-01

The Drummond et al. (1988) analysis of main-belt asteroids is presently extended, using three independent methods to derive poles, periods, phase functions, and triaxial ellipsoid shapes from lightcurve maxima and minima. This group of 26 asteroids is also reinvestigated with a view to the distributions of triaxial shapes and obliquity distributions. Poles weakly tend to avoid asteroid orbital planes; a rough-smooth dichotomization appears to be justified by the persistence of two solar phase angle-amplitude relations. Seven of the objects may be Jacobi ellipsoids if axial ratios are slightly exaggerated by a systematic effect of the analytical method employed.

Characterization of x-ray framing cameras for the National Ignition Facility using single photon pulse height analysis.

PubMed

Holder, J P; Benedetti, L R; Bradley, D K

2016-11-01

Single hit pulse height analysis is applied to National Ignition Facility x-ray framing cameras to quantify gain and gain variation in a single micro-channel plate-based instrument. This method allows the separation of gain from detectability in these photon-detecting devices. While pulse heights measured by standard-DC calibration methods follow the expected exponential distribution at the limit of a compound-Poisson process, gain-gated pulse heights follow a more complex distribution that may be approximated as a weighted sum of a few exponentials. We can reproduce this behavior with a simple statistical-sampling model.

The Use of Multidimensional Image-Based Analysis to Accurately Monitor Cell Growth in 3D Bioreactor Culture

PubMed Central

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells. PMID:22028809

The use of multidimensional image-based analysis to accurately monitor cell growth in 3D bioreactor culture.

PubMed

Baradez, Marc-Olivier; Marshall, Damian

2011-01-01

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells.

Characterization of the Failure Site Distribution in MIM Devices Using Zoomed Wavelet Analysis

NASA Astrophysics Data System (ADS)

Muñoz-Gorriz, J.; Monaghan, S.; Cherkaoui, K.; Suñé, J.; Hurley, P. K.; Miranda, E.

2018-05-01

The angular wavelet analysis is applied to the study of the spatial distribution of breakdown (BD) spots in Pt/HfO2/Pt capacitors with square and circular areas. The method is originally developed for rectangular areas, so a zoomed approach needs to be considered when the observation window does not coincide with the device area. The BD spots appear as a consequence of the application of electrical stress to the device. The stress generates defects within the dielectric film, a process that ends with the formation of a percolation path between the electrodes and the melting of the top metal layer because of the high release of energy. The BD spots have lateral sizes ranging from 1 μm to 3 μm and they appear as a point pattern that can be studied using spatial statistics methods. In this paper, we report the application of the angular wavelet method as a complementary tool for the analysis of the distribution of failure sites in large-area metal-insulator-metal (MIM) devices. The differences between considering a continuous or a discrete wavelet and the role played by the number of BD spots are also investigated.

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

PubMed

Zhu, Qiaohao; Carriere, K C

2016-01-01

Publication bias can significantly limit the validity of meta-analysis when trying to draw conclusion about a research question from independent studies. Most research on detection and correction for publication bias in meta-analysis focus mainly on funnel plot-based methodologies or selection models. In this paper, we formulate publication bias as a truncated distribution problem, and propose new parametric solutions. We develop methodologies of estimating the underlying overall effect size and the severity of publication bias. We distinguish the two major situations, in which publication bias may be induced by: (1) small effect size or (2) large p-value. We consider both fixed and random effects models, and derive estimators for the overall mean and the truncation proportion. These estimators will be obtained using maximum likelihood estimation and method of moments under fixed- and random-effects models, respectively. We carried out extensive simulation studies to evaluate the performance of our methodology, and to compare with the non-parametric Trim and Fill method based on funnel plot. We find that our methods based on truncated normal distribution perform consistently well, both in detecting and correcting publication bias under various situations.

Methods and apparatuses for information analysis on shared and distributed computing systems

DOEpatents

Bohn, Shawn J [Richland, WA; Krishnan, Manoj Kumar [Richland, WA; Cowley, Wendy E [Richland, WA; Nieplocha, Jarek [Richland, WA

2011-02-22

Apparatuses and computer-implemented methods for analyzing, on shared and distributed computing systems, information comprising one or more documents are disclosed according to some aspects. In one embodiment, information analysis can comprise distributing one or more distinct sets of documents among each of a plurality of processes, wherein each process performs operations on a distinct set of documents substantially in parallel with other processes. Operations by each process can further comprise computing term statistics for terms contained in each distinct set of documents, thereby generating a local set of term statistics for each distinct set of documents. Still further, operations by each process can comprise contributing the local sets of term statistics to a global set of term statistics, and participating in generating a major term set from an assigned portion of a global vocabulary.

Principal Component Analysis for Normal-Distribution-Valued Symbolic Data.

PubMed

Wang, Huiwen; Chen, Meiling; Shi, Xiaojun; Li, Nan

2016-02-01

This paper puts forward a new approach to principal component analysis (PCA) for normal-distribution-valued symbolic data, which has a vast potential of applications in the economic and management field. We derive a full set of numerical characteristics and variance-covariance structure for such data, which forms the foundation for our analytical PCA approach. Our approach is able to use all of the variance information in the original data than the prevailing representative-type approach in the literature which only uses centers, vertices, etc. The paper also provides an accurate approach to constructing the observations in a PC space based on the linear additivity property of normal distribution. The effectiveness of the proposed method is illustrated by simulated numerical experiments. At last, our method is applied to explain the puzzle of risk-return tradeoff in China's stock market.

Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.

PubMed

Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin

2007-07-01

Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.

Condition Assessment of Drinking Water Transmission and Distribution Systems

EPA Science Inventory

Condition assessment of water transmission and distribution mains is the collection of data and information through direct and/or indirect methods, followed by analysis of the data and information, to make a determination of the current and/or future structural, water quality, an...

Asymptotic confidence intervals for the Pearson correlation via skewness and kurtosis.

PubMed

Bishara, Anthony J; Li, Jiexiang; Nash, Thomas

2018-02-01

When bivariate normality is violated, the default confidence interval of the Pearson correlation can be inaccurate. Two new methods were developed based on the asymptotic sampling distribution of Fisher's z' under the general case where bivariate normality need not be assumed. In Monte Carlo simulations, the most successful of these methods relied on the (Vale & Maurelli, 1983, Psychometrika, 48, 465) family to approximate a distribution via the marginal skewness and kurtosis of the sample data. In Simulation 1, this method provided more accurate confidence intervals of the correlation in non-normal data, at least as compared to no adjustment of the Fisher z' interval, or to adjustment via the sample joint moments. In Simulation 2, this approximate distribution method performed favourably relative to common non-parametric bootstrap methods, but its performance was mixed relative to an observed imposed bootstrap and two other robust methods (PM1 and HC4). No method was completely satisfactory. An advantage of the approximate distribution method, though, is that it can be implemented even without access to raw data if sample skewness and kurtosis are reported, making the method particularly useful for meta-analysis. Supporting information includes R code. © 2017 The British Psychological Society.

Thermal analysis of disc brakes using finite element method

NASA Astrophysics Data System (ADS)

Jaenudin, Jamari, J.; Tauviqirrahman, M.

2017-01-01

Disc brakes are components of a vehicle that serve to slow or stop the rotation of the wheel. This paper discusses the phenomenon of heat distribution on the brake disc during braking. Heat distribution on the brake disc is caused by kinetic energy changing into mechanical energy. Energy changes occur during the braking process due to friction between the surface of the disc and a disc pad. The temperature resulting from this friction rises high. This thermal analysis on brake discs is aimed to evaluate the performance of an electric car in the braking process. The aim of this study is to analyze the thermal behavior of the brake discs using the Finite Element Method (FEM) through examining the heat distribution on the brake disc using 3-D modeling. Results obtained from the FEM reflect the effects of high heat due to the friction between the disc pad with the disc rotor. Results of the simulation study are used to identify the effect of the heat distribution that occurred during the braking process.

Principal Effects of Axial Load on Moment-Distribution Analysis of Rigid Structures

NASA Technical Reports Server (NTRS)

James, Benjamin Wylie

1935-01-01

This thesis presents the method of moment distribution modified to include the effect of axial load upon the bending moments. This modification makes it possible to analyze accurately complex structures, such as rigid fuselage trusses, that heretofore had to be analyzed by approximate formulas and empirical rules. The method is simple enough to be practicable even for complex structures, and it gives a means of analysis for continuous beams that is simpler than the extended three-moment equation now in common use. When the effect of axial load is included, it is found that the basic principles of moment distribution remain unchanged, the only difference being that the factors used, instead of being constants for a given member, become functions of the axial load. Formulas have been developed for these factors, and curves plotted so that their applications requires no more work than moment distribution without axial load. Simple problems have been included to illustrate the use of the curves.

Particle size distributions and the vertical distribution of suspended matter in the upwelling region off Oregon

NASA Technical Reports Server (NTRS)

Kitchen, J. C.

1977-01-01

Various methods of presenting and mathematically describing particle size distribution are explained and evaluated. The hyperbolic distribution is found to be the most practical but the more complex characteristic vector analysis is the most sensitive to changes in the shape of the particle size distributions. A method for determining onshore-offshore flow patterns from the distribution of particulates was presented. A numerical model of the vertical structure of two size classes of particles was developed. The results show a close similarity to the observed distributions but overestimate the particle concentration by forty percent. This was attributed to ignoring grazing by zooplankton. Sensivity analyses showed the size preference was most responsive to the maximum specific growth rates and nutrient half saturation constants. The verical structure was highly dependent on the eddy diffusivity followed closely by the growth terms.

Stress and reliability analyses of multilayered composite cylinder under thermal and mechanical loads

NASA Astrophysics Data System (ADS)

Wang, Xiaohua

The coupling resulting from the mutual influence of material thermal and mechanical parameters is examined in the thermal stress analysis of a multilayered isotropic composite cylinder subjected to sudden axisymmetric external and internal temperature. The method of complex frequency response functions together with the Fourier transform technique is utilized. Because the coupling parameters for some composite materials, such as carbon-carbon, are very small, the effect of coupling is neglected in the orthotropic thermal stress analysis. The stress distributions in multilayered orthotropic cylinders subjected to sudden axisymmetric temperature loading combined with dynamic pressure as well as asymmetric temperature loading are also obtained. The method of Fourier series together with the Laplace transform is utilized in solving the heat conduction equation and thermal stress analysis. For brittle materials, like carbon-carbon composites, the strength variability is represented by two or three parameter Weibull distributions. The 'weakest link' principle which takes into account both the carbon-carbon composite cylinders. The complex frequency response analysis is performed on a multilayered orthotropic cylinder under asymmetrical thermal load. Both deterministic and random thermal stress and reliability analyses can be based on the results of this frequency response analysis. The stress and displacement distributions and reliability of rocket motors under static or dynamic line loads are analyzed by an elasticity approach. Rocket motors are modeled as long hollow multilayered cylinders with an air core, a thick isotropic propellant inner layer and a thin orthotropic kevlar-epoxy case. The case is treated as a single orthotropic layer or a ten layered orthotropic structure. Five material properties and the load are treated as random variable with normal distributions when the reliability of the rocket motor is analyzed by the first-order, second-moment method (FOSM).

A Note on Procrustean Rotation in Exploratory Factor Analysis: A Computer Intensive Approach to Goodness-of-Fit Evaluation.

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…

Method and apparatus for enhanced sequencing of complex molecules using surface-induced dissociation in conjunction with mass spectrometric analysis

DOEpatents

Laskin, Julia [Richland, WA; Futrell, Jean H [Richland, WA

2008-04-29

The invention relates to a method and apparatus for enhanced sequencing of complex molecules using surface-induced dissociation (SID) in conjunction with mass spectrometric analysis. Results demonstrate formation of a wide distribution of structure-specific fragments having wide sequence coverage useful for sequencing and identifying the complex molecules.

Thermal decomposition in thermal desorption instruments: importance of thermogram measurements for analysis of secondary organic aerosol

NASA Astrophysics Data System (ADS)

Stark, H.; Yatavelli, R. L. N.; Thompson, S.; Kang, H.; Krechmer, J. E.; Kimmel, J.; Palm, B. B.; Hu, W.; Hayes, P.; Day, D. A.; Campuzano Jost, P.; Ye, P.; Canagaratna, M. R.; Jayne, J. T.; Worsnop, D. R.; Jimenez, J. L.

2017-12-01

Understanding the chemical composition of secondary organic aerosol (SOA) is crucial for explaining sources and fate of this important aerosol class in tropospheric chemistry. Further, determining SOA volatility is key in predicting its atmospheric lifetime and fate, due to partitioning from and to the gas phase. We present three analysis approaches to determine SOA volatility distributions from two field campaigns in areas with strong biogenic emissions, a Ponderosa pine forest in Colorado, USA, from the BEACHON-RoMBAS campaign, and a mixed forest in Alabama, USA, from the SOAS campaign. We used a high-resolution-time-of-flight chemical ionization mass spectrometer (CIMS) for both campaigns, equipped with a micro-orifice volatilization impactor (MOVI) inlet for BEACHON and a filter inlet for gases and aerosols (FIGAERO) for SOAS. These inlets allow near simultaneous analysis of particle and gas-phase species by the CIMS. While gas-phase species are directly measured without heating, particles undergo thermal desorption prior to analysis. Volatility distributions can be estimated in three ways: (1) analysis of the thermograms (signal vs. temperature); (2) via partitioning theory using the gas- and particle-phase measurements; (3) from measured chemical formulas via a group contribution model. Comparison of the SOA volatility distributions from the three methods shows large discrepancies for both campaigns. Results from the thermogram method are the most consistent of the methods when compared with independent AMS-thermal denuder measurements. The volatility distributions estimated from partitioning measurements are very narrow, likely due to signal-to-noise limits in the measurements. The discrepancy between the formula and the thermogram methods indicates large-scale thermal decomposition of the SOA species. We will also show results of citric acid thermal decomposition, where, in addition to the mass spectra, measurements of CO, CO2 and H2O were made, showing thermal decomposition of up to 65% of the citric acid molecules.

Partial Discharge Monitoring on Metal-Enclosed Switchgear with Distributed Non-Contact Sensors.

PubMed

Zhang, Chongxing; Dong, Ming; Ren, Ming; Huang, Wenguang; Zhou, Jierui; Gao, Xuze; Albarracín, Ricardo

2018-02-11

Metal-enclosed switchgear, which are widely used in the distribution of electrical energy, play an important role in power distribution networks. Their safe operation is directly related to the reliability of power system as well as the power quality on the consumer side. Partial discharge detection is an effective way to identify potential faults and can be utilized for insulation diagnosis of metal-enclosed switchgear. The transient earth voltage method, an effective non-intrusive method, has substantial engineering application value for estimating the insulation condition of switchgear. However, the practical application effectiveness of TEV detection is not satisfactory because of the lack of a TEV detection application method, i.e., a method with sufficient technical cognition and analysis. This paper proposes an innovative online PD detection system and a corresponding application strategy based on an intelligent feedback distributed TEV wireless sensor network, consisting of sensing, communication, and diagnosis layers. In the proposed system, the TEV signal or status data are wirelessly transmitted to the terminal following low-energy signal preprocessing and acquisition by TEV sensors. Then, a central server analyzes the correlation of the uploaded data and gives a fault warning level according to the quantity, trend, parallel analysis, and phase resolved partial discharge pattern recognition. In this way, a TEV detection system and strategy with distributed acquisition, unitized fault warning, and centralized diagnosis is realized. The proposed system has positive significance for reducing the fault rate of medium voltage switchgear and improving its operation and maintenance level.

Using Micro-Synchrophasor Data for Advanced Distribution Grid Planning and Operations Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, Emma; Kiliccote, Sila; McParland, Charles

2014-07-01

This report reviews the potential for distribution-grid phase-angle data that will be available from new micro-synchrophasors (µPMUs) to be utilized in existing distribution-grid planning and operations analysis. This data could augment the current diagnostic capabilities of grid analysis software, used in both planning and operations for applications such as fault location, and provide data for more accurate modeling of the distribution system. µPMUs are new distribution-grid sensors that will advance measurement and diagnostic capabilities and provide improved visibility of the distribution grid, enabling analysis of the grid’s increasingly complex loads that include features such as large volumes of distributed generation.more » Large volumes of DG leads to concerns on continued reliable operation of the grid, due to changing power flow characteristics and active generation, with its own protection and control capabilities. Using µPMU data on change in voltage phase angle between two points in conjunction with new and existing distribution-grid planning and operational tools is expected to enable model validation, state estimation, fault location, and renewable resource/load characterization. Our findings include: data measurement is outstripping the processing capabilities of planning and operational tools; not every tool can visualize a voltage phase-angle measurement to the degree of accuracy measured by advanced sensors, and the degree of accuracy in measurement required for the distribution grid is not defined; solving methods cannot handle the high volumes of data generated by modern sensors, so new models and solving methods (such as graph trace analysis) are needed; standardization of sensor-data communications platforms in planning and applications tools would allow integration of different vendors’ sensors and advanced measurement devices. In addition, data from advanced sources such as µPMUs could be used to validate models to improve/ensure accuracy, providing information on normally estimated values such as underground conductor impedance, and characterization of complex loads. Although the input of high-fidelity data to existing tools will be challenging, µPMU data on phase angle (as well as other data from advanced sensors) will be useful for basic operational decisions that are based on a trend of changing data.« less

A case study of liquefaction risk analysis based on the thickness and depth of the liquefaction layer using CPT and electric resistivity data in the Hinode area, Itako City, Ibaraki Prefecture, Japan

NASA Astrophysics Data System (ADS)

Jinguuji, Motoharu; Toprak, Selcuk

2017-12-01

The Hinode area of Itako City in Ibaraki Prefecture, Japan, suffered some of the most severe liquefaction damage of any areas in the Great Eastern Japan Earthquake in 2011. This liquefaction damage has been investigated by Itako City, as well as by universities and research institutes in Japan. The National Institute of Advanced Industrial Science and Technology (AIST) has carried out numerous investigations along the Tone River, and in particular, intensive surveys were done in the Hinode area. We have conducted a risk analysis based on the thickness and depth of the liquefaction layer measured using cone penetration testing (CPT) data and electric resistivity data obtained in the Hinode area. The distribution of the risk estimated from CPT at 143 points, and that obtained from analysis of the resistivity survey data, agreed with the distribution of actual damage. We also carried out conventional risk analyses method using the liquefaction resistance factor (FL) and liquefaction potential index (PL) methods with CPT data. The results show high PL values over the entire area, but their distribution did not agree well with actual damage in some parts of the study area. Because the analysis of the thickness and depth of the liquefaction layer, using geophysical prospecting methods, can cover a widespread area, this method will be very useful in investigating liquefaction risk, especially for gas and water pipelines.

Fast Determination of Distribution-Connected PV Impacts Using a Variable Time-Step Quasi-Static Time-Series Approach: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mather, Barry

The increasing deployment of distribution-connected photovoltaic (DPV) systems requires utilities to complete complex interconnection studies. Relatively simple interconnection study methods worked well for low penetrations of photovoltaic systems, but more complicated quasi-static time-series (QSTS) analysis is required to make better interconnection decisions as DPV penetration levels increase. Tools and methods must be developed to support this. This paper presents a variable-time-step solver for QSTS analysis that significantly shortens the computational time and effort to complete a detailed analysis of the operation of a distribution circuit with many DPV systems. Specifically, it demonstrates that the proposed variable-time-step solver can reduce themore » required computational time by as much as 84% without introducing any important errors to metrics, such as the highest and lowest voltage occurring on the feeder, number of voltage regulator tap operations, and total amount of losses realized in the distribution circuit during a 1-yr period. Further improvement in computational speed is possible with the introduction of only modest errors in these metrics, such as a 91 percent reduction with less than 5 percent error when predicting voltage regulator operations.« less

Improved Test Planning and Analysis Through the Use of Advanced Statistical Methods

NASA Technical Reports Server (NTRS)

Green, Lawrence L.; Maxwell, Katherine A.; Glass, David E.; Vaughn, Wallace L.; Barger, Weston; Cook, Mylan

2016-01-01

The goal of this work is, through computational simulations, to provide statistically-based evidence to convince the testing community that a distributed testing approach is superior to a clustered testing approach for most situations. For clustered testing, numerous, repeated test points are acquired at a limited number of test conditions. For distributed testing, only one or a few test points are requested at many different conditions. The statistical techniques of Analysis of Variance (ANOVA), Design of Experiments (DOE) and Response Surface Methods (RSM) are applied to enable distributed test planning, data analysis and test augmentation. The D-Optimal class of DOE is used to plan an optimally efficient single- and multi-factor test. The resulting simulated test data are analyzed via ANOVA and a parametric model is constructed using RSM. Finally, ANOVA can be used to plan a second round of testing to augment the existing data set with new data points. The use of these techniques is demonstrated through several illustrative examples. To date, many thousands of comparisons have been performed and the results strongly support the conclusion that the distributed testing approach outperforms the clustered testing approach.

Inversion Analysis of Postseismic Deformation in Poroelastic Material Using Finite Element Method

NASA Astrophysics Data System (ADS)

Kawamoto, S.; Ito, T.; Hirahara, K.

2005-12-01

Following a large earthquake, postseismic deformations in the focal source region have been observed by several geodetic measurements. To explain the postseismic deformations, researchers have proposed some physical mechanisms known as afterslip, viscoelastic relaxation and poroelastic rebound. There are a number of studies about postseismic deformations but for poroelastic rebound. So, we calculated the postseismic deformations caused by afterslip and poroelastic rebound using modified FEM code _eCAMBIOT3D_f originally developed by Geotech. Lab. Gunma University, Japan (2003). The postseismic deformations caused by both afterslip and poroelastic rebound are characteristically different from those caused only by afterslip. This suggests that the slip distributions on the fault estimated from geodetic measurements also change. Because of this, we developed the inversion method that accounts for both afterslip and poroelastic rebound using FEM to estimate the difference of slip distributions on the fault quantitatively. The inversion analysis takes following steps. First, we calculate the coseismic and postseismic response functions on each fault segment induced by the unit slip. Where postseismic response function indicate the poroelastic rebound. Next, we make the observation equations at each time step using the response functions and estimate the spatiotemporal distribution of slip on the fault. In solving this inverse problem, we assume the slip distributions on the fault are smooth in space and time except for rapid change (coseismic change). Because the hyperparameters that control the smoothness of spatial and temporal distributions of slip are needed, we determine the best hyperparameters using ABIC. In this presentation, we introduce the example of analysis results using this method.

Statistical methods of fracture characterization using acoustic borehole televiewer log interpretation

NASA Astrophysics Data System (ADS)

Massiot, Cécile; Townend, John; Nicol, Andrew; McNamara, David D.

2017-08-01

Acoustic borehole televiewer (BHTV) logs provide measurements of fracture attributes (orientations, thickness, and spacing) at depth. Orientation, censoring, and truncation sampling biases similar to those described for one-dimensional outcrop scanlines, and other logging or drilling artifacts specific to BHTV logs, can affect the interpretation of fracture attributes from BHTV logs. K-means, fuzzy K-means, and agglomerative clustering methods provide transparent means of separating fracture groups on the basis of their orientation. Fracture spacing is calculated for each of these fracture sets. Maximum likelihood estimation using truncated distributions permits the fitting of several probability distributions to the fracture attribute data sets within truncation limits, which can then be extrapolated over the entire range where they naturally occur. Akaike Information Criterion (AIC) and Schwartz Bayesian Criterion (SBC) statistical information criteria rank the distributions by how well they fit the data. We demonstrate these attribute analysis methods with a data set derived from three BHTV logs acquired from the high-temperature Rotokawa geothermal field, New Zealand. Varying BHTV log quality reduces the number of input data points, but careful selection of the quality levels where fractures are deemed fully sampled increases the reliability of the analysis. Spacing data analysis comprising up to 300 data points and spanning three orders of magnitude can be approximated similarly well (similar AIC rankings) with several distributions. Several clustering configurations and probability distributions can often characterize the data at similar levels of statistical criteria. Thus, several scenarios should be considered when using BHTV log data to constrain numerical fracture models.

Identification of potential rockfall source areas at a regional scale using a DEM-based geomorphometric analysis

NASA Astrophysics Data System (ADS)

Loye, A.; Jaboyedoff, M.; Pedrazzini, A.

2009-10-01

The availability of high resolution Digital Elevation Models (DEM) at a regional scale enables the analysis of topography with high levels of detail. Hence, a DEM-based geomorphometric approach becomes more accurate for detecting potential rockfall sources. Potential rockfall source areas are identified according to the slope angle distribution deduced from high resolution DEM crossed with other information extracted from geological and topographic maps in GIS format. The slope angle distribution can be decomposed in several Gaussian distributions that can be considered as characteristic of morphological units: rock cliffs, steep slopes, footslopes and plains. A terrain is considered as potential rockfall sources when their slope angles lie over an angle threshold, which is defined where the Gaussian distribution of the morphological unit "Rock cliffs" become dominant over the one of "Steep slopes". In addition to this analysis, the cliff outcrops indicated by the topographic maps were added. They contain however "flat areas", so that only the slope angles values above the mode of the Gaussian distribution of the morphological unit "Steep slopes" were considered. An application of this method is presented over the entire Canton of Vaud (3200 km2), Switzerland. The results were compared with rockfall sources observed on the field and orthophotos analysis in order to validate the method. Finally, the influence of the cell size of the DEM is inspected by applying the methodology over six different DEM resolutions.

A Numerical Method for Calculating the Wave Drag of a Configuration from the Second Derivative of the Area Distribution of a Series of Equivalent Bodies of Revolution

NASA Technical Reports Server (NTRS)

Levy, Lionel L., Jr.; Yoshikawa, Kenneth K.

1959-01-01

A method based on linearized and slender-body theories, which is easily adapted to electronic-machine computing equipment, is developed for calculating the zero-lift wave drag of single- and multiple-component configurations from a knowledge of the second derivative of the area distribution of a series of equivalent bodies of revolution. The accuracy and computational time required of the method to calculate zero-lift wave drag is evaluated relative to another numerical method which employs the Tchebichef form of harmonic analysis of the area distribution of a series of equivalent bodies of revolution. The results of the evaluation indicate that the total zero-lift wave drag of a multiple-component configuration can generally be calculated most accurately as the sum of the zero-lift wave drag of each component alone plus the zero-lift interference wave drag between all pairs of components. The accuracy and computational time required of both methods to calculate total zero-lift wave drag at supersonic Mach numbers is comparable for airplane-type configurations. For systems of bodies of revolution both methods yield similar results with comparable accuracy; however, the present method only requires up to 60 percent of the computing time required of the harmonic-analysis method for two bodies of revolution and less time for a larger number of bodies.

Energy-Based Wavelet De-Noising of Hydrologic Time Series

PubMed Central

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

A comparative study on the stress distribution around dental implants in three arch form models for replacing six implants using finite element analysis.

PubMed

Zarei, Maryam; Jahangirnezhad, Mahmoud; Yousefimanesh, Hojatollah; Robati, Maryam; Robati, Hossein

2018-01-01

Dental implant is a method to replacement of missing teeth. It is important for replacing the missed anterior teeth. In vitro method is a safe method for evaluation of stress distribution. Finite element analysis as an in vitro method evaluated stress distribution around replacement of six maxillary anterior teeth implants in three models of maxillary arch. In this in vitro study, using ABAQUS software (Simulia Corporation, Vélizy-Villacoublay, France), implant simulation was performed for reconstruction of six maxillary anterior teeth in three models. Two implants were placed on both sides of the canine tooth region (A model); two implants on both sides of the canine tooth region and another on one side of the central incisor region (B model); and two implants on both sides of the canine tooth region and two implants in the central incisor area (C model). All implants evaluated in three arch forms (tapered, ovoid, and square). Data were analyzed by finite analysis software. Von Mises stress by increasing of implant number was reduced. In a comparison of A model in each maxillary arch, the stress created in the cortical and cancellous bones in the square arch was less than ovoid and tapered arches. The stress created in implants and cortical and cancellous bones in C model was less than A and B models. The C model (four-implant) reduced the stress distribution in cortical and cancellous bones, but this pattern must be evaluated according to arch form and cost benefit of patients.

Stress analysis of circular semimonocoque cylinders with cutouts

NASA Technical Reports Server (NTRS)

Mccomb, Harvey G , Jr

1955-01-01

A method is presented for analyzing the stresses about cutouts in circular semimonocoque cylinders with flexible rings. The method involves the use of so-called perturbation stress distributions which are superposed on the stress distribution that would exist in the structure with no cutout in such a way as to give the effects of a cutout. The method can be used for any loading case for which the structure without the cutout can be analyzed and is sufficiently versatile to account for stringer and shear reinforcement about the cutout.

Pilot Scale Application of a Method for the Analysis of Perfluorinated Compounds in Surface Soils

EPA Science Inventory

A growing number of studies now indicate that perfluorinated compounds (PFCs) are globally distributed in the environment. Their widespread distribution and presence in remote locations has led to questions about the importance of atmospheric and oceanic transport. Describing the...

General methodology: Costing, budgeting, and techniques for benefit-cost and cost-effectiveness analysis

NASA Technical Reports Server (NTRS)

Stretchberry, D. M.; Hein, G. F.

1972-01-01

The general concepts of costing, budgeting, and benefit-cost ratio and cost-effectiveness analysis are discussed. The three common methods of costing are presented. Budgeting distributions are discussed. The use of discounting procedures is outlined. The benefit-cost ratio and cost-effectiveness analysis is defined and their current application to NASA planning is pointed out. Specific practices and techniques are discussed, and actual costing and budgeting procedures are outlined. The recommended method of calculating benefit-cost ratios is described. A standardized method of cost-effectiveness analysis and long-range planning are also discussed.

Analysis and Modeling of Complex Geomorphic Systems: Technique Development, Data Collection, and Application to Rangeland Terrain

DTIC Science & Technology

2008-10-01

attempts to measure the long-term distribution of stor- age time have relied unrealistic assumptions, but two recent studies suggest a new approach. As...sediment 10 age . Everitt (1968) mapped the age distribution of cottonwoods along a 34 km stretch of the Little Missouri River in North Dakota...Dietrich et al. (1982) applied Erikssons (1971) method to estimate the residence time distribution from Everitts age distribution. Somewhat mysteriously

On the robustness of a Bayes estimate. [in reliability theory

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

This paper examines the robustness of a Bayes estimator with respect to the assigned prior distribution. A Bayesian analysis for a stochastic scale parameter of a Weibull failure model is summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity analysis is carried out by the Monte Carlo method in which, although an inverted gamma is the assigned prior, realizations are generated using distribution functions of varying shape. For several distributional forms and even for some fixed values of the parameter, simulated mean squared errors of Bayes and minimum variance unbiased estimators are determined and compared. Results indicate that the Bayes estimator remains squared-error superior and appears to be largely robust to the form of the assigned prior distribution.

Systems analysis of the space shuttle. [communication systems, computer systems, and power distribution

NASA Technical Reports Server (NTRS)

Schilling, D. L.; Oh, S. J.; Thau, F.

1975-01-01

Developments in communications systems, computer systems, and power distribution systems for the space shuttle are described. The use of high speed delta modulation for bit rate compression in the transmission of television signals is discussed. Simultaneous Multiprocessor Organization, an approach to computer organization, is presented. Methods of computer simulation and automatic malfunction detection for the shuttle power distribution system are also described.

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Interindividual registration and dose mapping for voxelwise population analysis of rectal toxicity in prostate cancer radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dréan, Gaël; Acosta, Oscar, E-mail: Oscar.Acosta@univ-rennes1.fr; Simon, Antoine

2016-06-15

Purpose: Recent studies revealed a trend toward voxelwise population analysis in order to understand the local dose/toxicity relationships in prostate cancer radiotherapy. Such approaches require, however, an accurate interindividual mapping of the anatomies and 3D dose distributions toward a common coordinate system. This step is challenging due to the high interindividual variability. In this paper, the authors propose a method designed for interindividual nonrigid registration of the rectum and dose mapping for population analysis. Methods: The method is based on the computation of a normalized structural description of the rectum using a Laplacian-based model. This description takes advantage of themore » tubular structure of the rectum and its centerline to be embedded in a nonrigid registration-based scheme. The performances of the method were evaluated on 30 individuals treated for prostate cancer in a leave-one-out cross validation. Results: Performance was measured using classical metrics (Dice score and Hausdorff distance), along with new metrics devised to better assess dose mapping in relation with structural deformation (dose-organ overlap). Considering these scores, the proposed method outperforms intensity-based and distance maps-based registration methods. Conclusions: The proposed method allows for accurately mapping interindividual 3D dose distributions toward a single anatomical template, opening the way for further voxelwise statistical analysis.« less

Method for Estimating the Charge Density Distribution on a Dielectric Surface.

PubMed

Nakashima, Takuya; Suhara, Hiroyuki; Murata, Hidekazu; Shimoyama, Hiroshi

2017-06-01

High-quality color output from digital photocopiers and laser printers is in strong demand, motivating attempts to achieve fine dot reproducibility and stability. The resolution of a digital photocopier depends on the charge density distribution on the organic photoconductor surface; however, directly measuring the charge density distribution is impossible. In this study, we propose a new electron optical instrument that can rapidly measure the electrostatic latent image on an organic photoconductor surface, which is a dielectric surface, as well as a novel method to quantitatively estimate the charge density distribution on a dielectric surface by combining experimental data obtained from the apparatus via a computer simulation. In the computer simulation, an improved three-dimensional boundary charge density method (BCM) is used for electric field analysis in the vicinity of the dielectric material with a charge density distribution. This method enables us to estimate the profile and quantity of the charge density distribution on a dielectric surface with a resolution of the order of microns. Furthermore, the surface potential on the dielectric surface can be immediately calculated using the obtained charge density. This method enables the relation between the charge pattern on the organic photoconductor surface and toner particle behavior to be studied; an understanding regarding the same may lead to the development of a new generation of higher resolution photocopiers.

NEAT: an efficient network enrichment analysis test.

PubMed

Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

2016-09-05

Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat ).

Effects of cleft type, facemask anchorage method, and alveolar bone graft on maxillary protraction: a three-dimensional finite element analysis.

PubMed

Yang, Il-Hyung; Chang, Young-Il; Kim, Tae-Woo; Ahn, Sug-Joon; Lim, Won-Hee; Lee, Nam-Ki; Baek, Seung-Hak

2012-03-01

To investigate biomechanical effects of cleft type (unilateral/bilateral cleft lip and palate), facemask anchorage method (tooth-borne and miniplate anchorage), and alveolar bone graft on maxillary protraction. Three-dimensional finite element analysis with application of orthopedic force (30° downward and forward to the occlusal plane, 500 g per side). Computed tomography data from a 13.5-year-old girl with maxillary hypoplasia. Eight three-dimensional finite element models were fabricated according to cleft type, facemask anchorage method, and alveolar bone graft. Initial stress distribution and displacement after force application were analyzed. Unilateral cleft lip and palate showed an asymmetric pattern in stress distribution and displacement before alveolar bone graft and demonstrated a symmetric pattern after alveolar bone graft. However, bilateral cleft lip and palate showed symmetric patterns in stress distribution and displacement before and after alveolar bone graft. In both cleft types, the graft extended the stress distribution area laterally beyond the infraorbital foramen. For both unilateral and bilateral cleft lip and palate, a facemask with a tooth-borne anchorage showed a dentoalveolar effect with prominent stress distribution and displacement on the upper canine point. In contrast, a facemask with miniplate anchorage exhibited an orthopedic effect with more favorable stress distribution and displacement on the middle maxilla point. In addition, the facemask with a miniplate anchorage showed a larger stress distribution area and sutural stress values than did the facemask with a tooth-borne anchorage. The pterygopalatine and zygomatico-maxillary sutures showed the largest sutural stress values with a facemask with a miniplate anchorage and after alveolar bone grafting, respectively. In this three-dimensional finite element analysis, it would be more advantageous to perform maxillary protraction using a facemask with a miniplate anchorage than a facemask with a tooth-borne anchorage and after alveolar bone graft rather than before alveolar bone graft, regardless of cleft type.

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

NASA Astrophysics Data System (ADS)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

Development of indirect EFBEM for radiating noise analysis including underwater problems

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Wung; Hong, Suk-Yoon; Song, Jee-Hun

2013-09-01

For the analysis of radiating noise problems in medium-to-high frequency ranges, the Energy Flow Boundary Element Method (EFBEM) was developed. EFBEM is the analysis technique that applies the Boundary Element Method (BEM) to Energy Flow Analysis (EFA). The fundamental solutions representing spherical wave property for radiating noise problems in open field and considering the free surface effect in underwater are developed. Also the directivity factor is developed to express wave's directivity patterns in medium-to-high frequency ranges. Indirect EFBEM by using fundamental solutions and fictitious source was applied to open field and underwater noise problems successfully. Through numerical applications, the acoustic energy density distributions due to vibration of a simple plate model and a sphere model were compared with those of commercial code, and the comparison showed good agreement in the level and pattern of the energy density distributions.

Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches.

PubMed

Zounemat-Kermani, Mohammad; Ramezani-Charmahineh, Abdollah; Adamowski, Jan; Kisi, Ozgur

2018-06-13

Chlorination, the basic treatment utilized for drinking water sources, is widely used for water disinfection and pathogen elimination in water distribution networks. Thereafter, the proper prediction of chlorine consumption is of great importance in water distribution network performance. In this respect, data mining techniques-which have the ability to discover the relationship between dependent variable(s) and independent variables-can be considered as alternative approaches in comparison to conventional methods (e.g., numerical methods). This study examines the applicability of three key methods, based on the data mining approach, for predicting chlorine levels in four water distribution networks. ANNs (artificial neural networks, including the multi-layer perceptron neural network, MLPNN, and radial basis function neural network, RBFNN), SVM (support vector machine), and CART (classification and regression tree) methods were used to estimate the concentration of residual chlorine in distribution networks for three villages in Kerman Province, Iran. Produced water (flow), chlorine consumption, and residual chlorine were collected daily for 3 years. An assessment of the studied models using several statistical criteria (NSC, RMSE, R 2 , and SEP) indicated that, in general, MLPNN has the greatest capability for predicting chlorine levels followed by CART, SVM, and RBF-ANN. Weaker performance of the data-driven methods in the water distribution networks, in some cases, could be attributed to improper chlorination management rather than the methods' capability.

[Abdomen specific bioelectrical impedance analysis (BIA) methods for evaluation of abdominal fat distribution].

PubMed

Ida, Midori; Hirata, Masakazu; Hosoda, Kiminori; Nakao, Kazuwa

2013-02-01

Two novel bioelectrical impedance analysis (BIA) methods have been developed recently for evaluation of intra-abdominal fat accumulation. Both methods use electrodes that are placed on abdominal wall and allow evaluation of intra-abdominal fat area (IAFA) easily without radiation exposure. Of these, "abdominal BIA" method measures impedance distribution along abdominal anterior-posterior axis, and IAFA by BIA method(BIA-IAFA) is calculated from waist circumference and the voltage occurring at the flank. Dual BIA method measures impedance of trunk and body surface at the abdominal level and calculates BIA-IAFA from transverse and antero-posterior diameters of the abdomen and the impedance of trunk and abdominal surface. BIA-IAFA by these two BIA methods correlated well with IAFA measured by abdominal CT (CT-IAFA) with correlatipn coefficient of 0.88 (n = 91, p < 0.0001) for the former, and 0.861 (n = 469, p < 0.01) for the latter. These new BIA methods are useful for evaluating abdominal adiposity in clinical study and routine clinical practice of metabolic syndrome and obesity.

Development, verification, and application of a simplified method to estimate total-streambed scour at bridge sites in Illinois

USGS Publications Warehouse

Holmes, Robert R.; Dunn, Chad J.

1996-01-01

A simplified method to estimate total-streambed scour was developed for application to bridges in the State of Illinois. Scour envelope curves, developed as empirical relations between calculated total scour and bridge-site chracteristics for 213 State highway bridges in Illinois, are used in the method to estimate the 500-year flood scour. These 213 bridges, geographically distributed throughout Illinois, had been previously evaluated for streambed scour with the application of conventional hydraulic and scour-analysis methods recommended by the Federal Highway Administration. The bridge characteristics necessary for application of the simplified bridge scour-analysis method can be obtained from an office review of bridge plans, examination of topographic maps, and reconnaissance-level site inspection. The estimates computed with the simplified method generally resulted in a larger value of 500-year flood total-streambed scour than with the more detailed conventional method. The simplified method was successfully verified with a separate data set of 106 State highway bridges, which are geographically distributed throughout Illinois, and 15 county highway bridges.

Nuclear risk analysis of the Ulysses mission

NASA Astrophysics Data System (ADS)

Bartram, Bart W.; Vaughan, Frank R.; Englehart, Richard W., Dr.

1991-01-01

The use of a radioisotope thermoelectric generator fueled with plutonium-238 dioxide on the Space Shuttle-launched Ulysses mission implies some level of risk due to potential accidents. This paper describes the method used to quantify risks in the Ulysses mission Final Safety Analysis Report prepared for the U.S. Department of Energy. The starting point for the analysis described herein is following input of source term probability distributions from the General Electric Company. A Monte Carlo technique is used to develop probability distributions of radiological consequences for a range of accident scenarios thoughout the mission. Factors affecting radiological consequences are identified, the probability distribution of the effect of each factor determined, and the functional relationship among all the factors established. The probability distributions of all the factor effects are then combined using a Monte Carlo technique. The results of the analysis are presented in terms of complementary cumulative distribution functions (CCDF) by mission sub-phase, phase, and the overall mission. The CCDFs show the total probability that consequences (calculated health effects) would be equal to or greater than a given value.

Subsonic panel method for designing wing surfaces from pressure distribution

NASA Technical Reports Server (NTRS)

Bristow, D. R.; Hawk, J. D.

1983-01-01

An iterative method has been developed for designing wing section contours corresponding to a prescribed subcritical distribution of pressure. The calculations are initialized by using a surface panel method to analyze a baseline wing or wing-fuselage configuration. A first-order expansion to the baseline panel method equations is then used to calculate a matrix containing the partial derivative of potential at each control point with respect to each unknown geometry parameter. In every iteration cycle, the matrix is used both to calculate the geometry perturbation and to analyze the perturbed geometry. The distribution of potential on the perturbed geometry is established by simple linear extrapolation from the baseline solution. The extrapolated potential is converted to pressure by Bernoulli's equation. Not only is the accuracy of the approach good for very large perturbations, but the computing cost of each complete iteration cycle is substantially less than one analysis solution by a conventional panel method.

Prestressing force monitoring method for a box girder through distributed long-gauge FBG sensors

NASA Astrophysics Data System (ADS)

Chen, Shi-Zhi; Wu, Gang; Xing, Tuo; Feng, De-Cheng

2018-01-01

Monitoring prestressing forces is essential for prestressed concrete box girder bridges. However, the current monitoring methods used for prestressing force were not applicable for a box girder neither because of the sensor’s setup being constrained or shear lag effect not being properly considered. Through combining with the previous analysis model of shear lag effect in the box girder, this paper proposed an indirect monitoring method for on-site determination of prestressing force in a concrete box girder utilizing the distributed long-gauge fiber Bragg grating sensor. The performance of this method was initially verified using numerical simulation for three different distribution forms of prestressing tendons. Then, an experiment involving two concrete box girders was conducted to study the feasibility of this method under different prestressing levels preliminarily. The results of both numerical simulation and lab experiment validated this method’s practicability in a box girder.

pyCTQW: A continuous-time quantum walk simulator on distributed memory computers

NASA Astrophysics Data System (ADS)

Izaac, Josh A.; Wang, Jingbo B.

2015-01-01

In the general field of quantum information and computation, quantum walks are playing an increasingly important role in constructing physical models and quantum algorithms. We have recently developed a distributed memory software package pyCTQW, with an object-oriented Python interface, that allows efficient simulation of large multi-particle CTQW (continuous-time quantum walk)-based systems. In this paper, we present an introduction to the Python and Fortran interfaces of pyCTQW, discuss various numerical methods of calculating the matrix exponential, and demonstrate the performance behavior of pyCTQW on a distributed memory cluster. In particular, the Chebyshev and Krylov-subspace methods for calculating the quantum walk propagation are provided, as well as methods for visualization and data analysis.

Three Strategies for the Critical Use of Statistical Methods in Psychological Research

ERIC Educational Resources Information Center

Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando

2017-01-01

We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…

Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Random Data

ERIC Educational Resources Information Center

Dinno, Alexis

2009-01-01

Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…

Characterization of winemaking yeast by cell number-size distribution analysis through flow field-flow fractionation with multi-wavelength turbidimetric detection.

PubMed

Zattoni, Andrea; Melucci, Dora; Reschiglian, Pierluigi; Sanz, Ramsés; Puignou, Lluís; Galceran, Maria Teresa

2004-10-29

Yeasts are widely used in several areas of food industry, e.g. baking, beer brewing, and wine production. Interest in new analytical methods for quality control and characterization of yeast cells is thus increasing. The biophysical properties of yeast cells, among which cell size, are related to yeast cell capabilities to produce primary and secondary metabolites during the fermentation process. Biophysical properties of winemaking yeast strains can be screened by field-flow fractionation (FFF). In this work we present the use of flow FFF (FlFFF) with turbidimetric multi-wavelength detection for the number-size distribution analysis of different commercial winemaking yeast varieties. The use of a diode-array detector allows to apply to dispersed samples like yeast cells the recently developed method for number-size (or mass-size) analysis in flow-assisted separation techniques. Results for six commercial winemaking yeast strains are compared with data obtained by a standard method for cell sizing (Coulter counter). The method here proposed gives, at short analysis time, accurate information on the number of cells of a given size, and information on the total number of cells.

Direct magnetic field estimation based on echo planar raw data.

PubMed

Testud, Frederik; Splitthoff, Daniel Nicolas; Speck, Oliver; Hennig, Jürgen; Zaitsev, Maxim

2010-07-01

Gradient recalled echo echo planar imaging is widely used in functional magnetic resonance imaging. The fast data acquisition is, however, very sensitive to field inhomogeneities which manifest themselves as artifacts in the images. Typically used correction methods have the common deficit that the data for the correction are acquired only once at the beginning of the experiment, assuming the field inhomogeneity distribution B(0) does not change over the course of the experiment. In this paper, methods to extract the magnetic field distribution from the acquired k-space data or from the reconstructed phase image of a gradient echo planar sequence are compared and extended. A common derivation for the presented approaches provides a solid theoretical basis, enables a fair comparison and demonstrates the equivalence of the k-space and the image phase based approaches. The image phase analysis is extended here to calculate the local gradient in the readout direction and improvements are introduced to the echo shift analysis, referred to here as "k-space filtering analysis." The described methods are compared to experimentally acquired B(0) maps in phantoms and in vivo. The k-space filtering analysis presented in this work demonstrated to be the most sensitive method to detect field inhomogeneities.

The Use of Propensity Scores in Mediation Analysis

ERIC Educational Resources Information Center

Jo, Booil; Stuart, Elizabeth A.; MacKinnon, David P.; Vinokur, Amiram D.

2011-01-01

Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid…

Research on intelligent power distribution system for spacecraft

NASA Astrophysics Data System (ADS)

Xia, Xiaodong; Wu, Jianju

2017-10-01

The power distribution system (PDS) mainly realizes the power distribution and management of the electrical load of the whole spacecraft, which is directly related to the success or failure of the mission, and hence is an important part of the spacecraft. In order to improve the reliability and intelligent degree of the PDS, and considering the function and composition of spacecraft power distribution system, this paper systematically expounds the design principle and method of the intelligent power distribution system based on SSPC, and provides the analysis and verification of the test data additionally.

Multiple Method Analysis of TiO2 Nanoparticle Uptake in Rice (Oryza sativa L.) Plants.

PubMed

Deng, Yingqing; Petersen, Elijah J; Challis, Katie E; Rabb, Savelas A; Holbrook, R David; Ranville, James F; Nelson, Bryant C; Xing, Baoshan

2017-09-19

Understanding the translocation of nanoparticles (NPs) into plants is challenging because qualitative and quantitative methods are still being developed and the comparability of results among different methods is unclear. In this study, uptake of titanium dioxide NPs and larger bulk particles (BPs) in rice plant (Oryza sativa L.) tissues was evaluated using three orthogonal techniques: electron microscopy, single-particle inductively coupled plasma mass spectroscopy (spICP-MS) with two different plant digestion approaches, and total elemental analysis using ICP optical emission spectroscopy. In agreement with electron microscopy results, total elemental analysis of plants exposed to TiO 2 NPs and BPs at 5 and 50 mg/L concentrations revealed that TiO 2 NPs penetrated into the plant root and resulted in Ti accumulation in above ground tissues at a higher level compared to BPs. spICP-MS analyses revealed that the size distributions of internalized particles differed between the NPs and BPs with the NPs showing a distribution with smaller particles. Acid digestion resulted in higher particle numbers and the detection of a broader range of particle sizes than the enzymatic digestion approach, highlighting the need for development of robust plant digestion procedures for NP analysis. Overall, there was agreement among the three techniques regarding NP and BP penetration into rice plant roots and spICP-MS showed its unique contribution to provide size distribution information.

Comparative Study of Wing Lift Distribution Analysis for High Altitude Long Endurance (HALE) Unmaned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Silitonga, Faber Y.; Agoes Moelyadi, M.

2018-04-01

The development of High Altitude Long Endurance (HALE) Unmanned Aerial Vehicle (UAV) has been emerged for both civil and military purposes. Its ability of operating in high altitude with long endurance is important in supporting maritime applications.Preliminary analysis of HALE UAV lift distribution of the wing presented to give decisive consideration for its early development. Ensuring that the generated lift is enough to compensate its own weight. Therotical approach using Pradtl’s non-linear lifting line theory will be compared with modern numerical approach using Computational Fluid Dynamics (CFD). Results of wing lift distribution calculated from both methods will be compared to study the reliability of it. HALE UAV ITB has high aspect ratio wing and will be analyze at cruise flight condition. The result indicates difference between Non-linear Lifting Line and CFD method.

Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

NASA Astrophysics Data System (ADS)

Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

2017-08-01

In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

Robustness of S1 statistic with Hodges-Lehmann for skewed distributions

NASA Astrophysics Data System (ADS)

Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping

2016-10-01

Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.

Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling.

PubMed

Schuck, P

2000-03-01

A new method for the size-distribution analysis of polymers by sedimentation velocity analytical ultracentrifugation is described. It exploits the ability of Lamm equation modeling to discriminate between the spreading of the sedimentation boundary arising from sample heterogeneity and from diffusion. Finite element solutions of the Lamm equation for a large number of discrete noninteracting species are combined with maximum entropy regularization to represent a continuous size-distribution. As in the program CONTIN, the parameter governing the regularization constraint is adjusted by variance analysis to a predefined confidence level. Estimates of the partial specific volume and the frictional ratio of the macromolecules are used to calculate the diffusion coefficients, resulting in relatively high-resolution sedimentation coefficient distributions c(s) or molar mass distributions c(M). It can be applied to interference optical data that exhibit systematic noise components, and it does not require solution or solvent plateaus to be established. More details on the size-distribution can be obtained than from van Holde-Weischet analysis. The sensitivity to the values of the regularization parameter and to the shape parameters is explored with the help of simulated sedimentation data of discrete and continuous model size distributions, and by applications to experimental data of continuous and discrete protein mixtures.

Empirical evidence about inconsistency among studies in a pair‐wise meta‐analysis

PubMed Central

Turner, Rebecca M.; Higgins, Julian P. T.

2015-01-01

This paper investigates how inconsistency (as measured by the I2 statistic) among studies in a meta‐analysis may differ, according to the type of outcome data and effect measure. We used hierarchical models to analyse data from 3873 binary, 5132 continuous and 880 mixed outcome meta‐analyses within the Cochrane Database of Systematic Reviews. Predictive distributions for inconsistency expected in future meta‐analyses were obtained, which can inform priors for between‐study variance. Inconsistency estimates were highest on average for binary outcome meta‐analyses of risk differences and continuous outcome meta‐analyses. For a planned binary outcome meta‐analysis in a general research setting, the predictive distribution for inconsistency among log odds ratios had median 22% and 95% CI: 12% to 39%. For a continuous outcome meta‐analysis, the predictive distribution for inconsistency among standardized mean differences had median 40% and 95% CI: 15% to 73%. Levels of inconsistency were similar for binary data measured by log odds ratios and log relative risks. Fitted distributions for inconsistency expected in continuous outcome meta‐analyses using mean differences were almost identical to those using standardized mean differences. The empirical evidence on inconsistency gives guidance on which outcome measures are most likely to be consistent in particular circumstances and facilitates Bayesian meta‐analysis with an informative prior for heterogeneity. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. PMID:26679486

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

PubMed

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force.

Discrimination of particulate matter emission sources using stochastic methods

NASA Astrophysics Data System (ADS)

Szczurek, Andrzej; Maciejewska, Monika; Wyłomańska, Agnieszka; Sikora, Grzegorz; Balcerek, Michał; Teuerle, Marek

2016-12-01

Particulate matter (PM) is one of the criteria pollutants which has been determined as harmful to public health and the environment. For this reason the ability to recognize its emission sources is very important. There are a number of measurement methods which allow to characterize PM in terms of concentration, particles size distribution, and chemical composition. All these information are useful to establish a link between the dust found in the air, its emission sources and influence on human as well as the environment. However, the methods are typically quite sophisticated and not applicable outside laboratories. In this work, we considered PM emission source discrimination method which is based on continuous measurements of PM concentration with a relatively cheap instrument and stochastic analysis of the obtained data. The stochastic analysis is focused on the temporal variation of PM concentration and it involves two steps: (1) recognition of the category of distribution for the data i.e. stable or the domain of attraction of stable distribution and (2) finding best matching distribution out of Gaussian, stable and normal-inverse Gaussian (NIG). We examined six PM emission sources. They were associated with material processing in industrial environment, namely machining and welding aluminum, forged carbon steel and plastic with various tools. As shown by the obtained results, PM emission sources may be distinguished based on statistical distribution of PM concentration variations. Major factor responsible for the differences detectable with our method was the type of material processing and the tool applied. In case different materials were processed by the same tool the distinction of emission sources was difficult. For successful discrimination it was crucial to consider size-segregated mass fraction concentrations. In our opinion the presented approach is very promising. It deserves further study and development.

Ridit Analysis for Cooper-Harper and Other Ordinal Ratings for Sparse Data - A Distance-based Approach

DTIC Science & Technology

2016-09-01

is to fit empirical Beta distributions to observed data, and then to use a randomization approach to make inferences on the difference between...a Ridit analysis on the often sparse data sets in many Flying Qualities applicationsi. The method of this paper is to fit empirical Beta ...One such measure is the discrete- probability-distribution version of the (squared) ‘Hellinger Distance’ (Yang & Le Cam , 2000) 2(, ) = 1

Airborne agent concentration analysis

DOEpatents

Gelbard, Fred

2004-02-03

A method and system for inferring airborne contaminant concentrations in rooms without contaminant sensors, based on data collected by contaminant sensors in other rooms of a building, using known airflow interconnectivity data. The method solves a least squares problem that minimizes the difference between measured and predicted contaminant sensor concentrations with respect to an unknown contaminant release time. Solutions are constrained to providing non-negative initial contaminant concentrations in all rooms. The method can be used to identify a near-optimal distribution of sensors within the building, when then number of available sensors is less than the total number of rooms. This is achieved by having a system-sensor matrix that is non-singular, and by selecting that distribution which yields the lowest condition number of all the distributions considered. The method can predict one or more contaminant initial release points from the collected data.

Pedestrian simulation and distribution in urban space based on visibility analysis and agent simulation

NASA Astrophysics Data System (ADS)

Ying, Shen; Li, Lin; Gao, Yurong

2009-10-01

Spatial visibility analysis is the important direction of pedestrian behaviors because our visual conception in space is the straight method to get environment information and navigate your actions. Based on the agent modeling and up-tobottom method, the paper develop the framework about the analysis of the pedestrian flow depended on visibility. We use viewshed in visibility analysis and impose the parameters on agent simulation to direct their motion in urban space. We analyze the pedestrian behaviors in micro-scale and macro-scale of urban open space. The individual agent use visual affordance to determine his direction of motion in micro-scale urban street on district. And we compare the distribution of pedestrian flow with configuration in macro-scale urban environment, and mine the relationship between the pedestrian flow and distribution of urban facilities and urban function. The paper first computes the visibility situations at the vantage point in urban open space, such as street network, quantify the visibility parameters. The multiple agents use visibility parameters to decide their direction of motion, and finally pedestrian flow reach to a stable state in urban environment through the simulation of multiple agent system. The paper compare the morphology of visibility parameters and pedestrian distribution with urban function and facilities layout to confirm the consistence between them, which can be used to make decision support in urban design.

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

Dynamic strain distribution of FRP plate under blast loading

NASA Astrophysics Data System (ADS)

Saburi, T.; Yoshida, M.; Kubota, S.

2017-02-01

The dynamic strain distribution of a fiber re-enforced plastic (FRP) plate under blast loading was investigated using a Digital Image Correlation (DIC) image analysis method. The testing FRP plates were mounted in parallel to each other on a steel frame. 50 g of composition C4 explosive was used as a blast loading source and set in the center of the FRP plates. The dynamic behavior of the FRP plate under blast loading were observed by two high-speed video cameras. The set of two high-speed video image sequences were used to analyze the FRP three-dimensional strain distribution by means of DIC method. A point strain profile extracted from the analyzed strain distribution data was compared with a directly observed strain profile using a strain gauge and it was shown that the strain profile under the blast loading by DIC method is quantitatively accurate.

Power Distribution Analysis For Electrical Usage In Province Area Using Olap (Online Analytical Processing)

NASA Astrophysics Data System (ADS)

Samsinar, Riza; Suseno, Jatmiko Endro; Widodo, Catur Edi

2018-02-01

The distribution network is the closest power grid to the customer Electric service providers such as PT. PLN. The dispatching center of power grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. Specific methods for online analytics information systems resulting from data warehouse processing with OLAP are chart and query reporting. The information in the form of chart reporting consists of the load distribution chart based on the repetition of time, distribution chart on the area, the substation region chart and the electric load usage chart. The results of the OLAP process show the development of electric load distribution, as well as the analysis of information on the load of electric power consumption and become an alternative in presenting information related to peak load.

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A method for the assessment of specific energy distribution in a model tumor system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noska, M.A.

1996-12-31

Due to the short range of alpha particles in tissue, the calculation of dose from internally deposited alpha emitters requires a detailed analysis of the microscopic distribution of the radionuclide in order to determine the spatial distribution of energy emission events and, from this, the spatial distribution of dose. In the present study, the authors used quantitative autoradiography (QAR) to assess the microdistribution of a radiolabeled monoclonal antibody (MAb) fragment in human glioma xenografts in mice.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Theuws, P.G.A.; Beijerinck, H.C.W.; Schram, D.C.

Velocity analysis of the molecular beam is done with a time-of-flight method. The measured velocity distribution of the fast neutral atoms is described by the sum of two Maxwell-Boltzmann distributions with temperatures on the order of 0.25 and 1 eV, respectively. This bimodal distribution is attributed to an overpopulation of the high-energy tail of the ion velocity distribution. The measured intensities of the fast neutrals vary between 5 x 10/sup 14/ and 7 x 10/sup 15/ (molecules s/sup -1/ sr/sup -1/).

A New Reassigned Spectrogram Method in Interference Detection for GNSS Receivers.

PubMed

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-09-02

Interference detection is very important for Global Navigation Satellite System (GNSS) receivers. Current work on interference detection in GNSS receivers has mainly focused on time-frequency (TF) analysis techniques, such as spectrogram and Wigner-Ville distribution (WVD), where the spectrogram approach presents the TF resolution trade-off problem, since the analysis window is used, and the WVD method suffers from the very serious cross-term problem, due to its quadratic TF distribution nature. In order to solve the cross-term problem and to preserve good TF resolution in the TF plane at the same time, in this paper, a new TF distribution by using a reassigned spectrogram has been proposed in interference detection for GNSS receivers. This proposed reassigned spectrogram method efficiently combines the elimination of the cross-term provided by the spectrogram itself according to its inherent nature and the improvement of the TF aggregation property achieved by the reassignment method. Moreover, a notch filter has been adopted in interference mitigation for GNSS receivers, where receiver operating characteristics (ROCs) are used as metrics for the characterization of interference mitigation performance. The proposed interference detection method by using a reassigned spectrogram is evaluated by experiments on GPS L1 signals in the disturbing scenarios in comparison to the state-of-the-art TF analysis approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-term problem and also keeps good TF localization properties, which has been proven to be valid and effective to enhance the interference Sensors 2015, 15 22168 detection performance; in addition, the adoption of the notch filter in interference mitigation has shown a significant acquisition performance improvement in terms of ROC curves for GNSS receivers in jamming environments.

A New Reassigned Spectrogram Method in Interference Detection for GNSS Receivers

PubMed Central

Sun, Kewen; Jin, Tian; Yang, Dongkai

2015-01-01

Interference detection is very important for Global Navigation Satellite System (GNSS) receivers. Current work on interference detection in GNSS receivers has mainly focused on time-frequency (TF) analysis techniques, such as spectrogram and Wigner–Ville distribution (WVD), where the spectrogram approach presents the TF resolution trade-off problem, since the analysis window is used, and the WVD method suffers from the very serious cross-term problem, due to its quadratic TF distribution nature. In order to solve the cross-term problem and to preserve good TF resolution in the TF plane at the same time, in this paper, a new TF distribution by using a reassigned spectrogram has been proposed in interference detection for GNSS receivers. This proposed reassigned spectrogram method efficiently combines the elimination of the cross-term provided by the spectrogram itself according to its inherent nature and the improvement of the TF aggregation property achieved by the reassignment method. Moreover, a notch filter has been adopted in interference mitigation for GNSS receivers, where receiver operating characteristics (ROCs) are used as metrics for the characterization of interference mitigation performance. The proposed interference detection method by using a reassigned spectrogram is evaluated by experiments on GPS L1 signals in the disturbing scenarios in comparison to the state-of-the-art TF analysis approaches. The analysis results show that the proposed interference detection technique effectively overcomes the cross-term problem and also keeps good TF localization properties, which has been proven to be valid and effective to enhance the interference detection performance; in addition, the adoption of the notch filter in interference mitigation has shown a significant acquisition performance improvement in terms of ROC curves for GNSS receivers in jamming environments. PMID:26364637

Novel Microbiological and Spatial Statistical Methods to Improve Strength of Epidemiological Evidence in a Community-Wide Waterborne Outbreak

PubMed Central

Jalava, Katri; Rintala, Hanna; Ollgren, Jukka; Maunula, Leena; Gomez-Alvarez, Vicente; Revez, Joana; Palander, Marja; Antikainen, Jenni; Kauppinen, Ari; Räsänen, Pia; Siponen, Sallamaari; Nyholm, Outi; Kyyhkynen, Aino; Hakkarainen, Sirpa; Merentie, Juhani; Pärnänen, Martti; Loginov, Raisa; Ryu, Hodon; Kuusi, Markku; Siitonen, Anja; Miettinen, Ilkka; Santo Domingo, Jorge W.; Hänninen, Marja-Liisa; Pitkänen, Tarja

2014-01-01

Failures in the drinking water distribution system cause gastrointestinal outbreaks with multiple pathogens. A water distribution pipe breakage caused a community-wide waterborne outbreak in Vuorela, Finland, July 2012. We investigated this outbreak with advanced epidemiological and microbiological methods. A total of 473/2931 inhabitants (16%) responded to a web-based questionnaire. Water and patient samples were subjected to analysis of multiple microbial targets, molecular typing and microbial community analysis. Spatial analysis on the water distribution network was done and we applied a spatial logistic regression model. The course of the illness was mild. Drinking untreated tap water from the defined outbreak area was significantly associated with illness (RR 5.6, 95% CI 1.9–16.4) increasing in a dose response manner. The closer a person lived to the water distribution breakage point, the higher the risk of becoming ill. Sapovirus, enterovirus, single Campylobacter jejuni and EHEC O157:H7 findings as well as virulence genes for EPEC, EAEC and EHEC pathogroups were detected by molecular or culture methods from the faecal samples of the patients. EPEC, EAEC and EHEC virulence genes and faecal indicator bacteria were also detected in water samples. Microbial community sequencing of contaminated tap water revealed abundance of Arcobacter species. The polyphasic approach improved the understanding of the source of the infections, and aided to define the extent and magnitude of this outbreak. PMID:25147923

Influential input classification in probabilistic multimedia models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maddalena, Randy L.; McKone, Thomas E.; Hsieh, Dennis P.H.

1999-05-01

Monte Carlo analysis is a statistical simulation method that is often used to assess and quantify the outcome variance in complex environmental fate and effects models. Total outcome variance of these models is a function of (1) the uncertainty and/or variability associated with each model input and (2) the sensitivity of the model outcome to changes in the inputs. To propagate variance through a model using Monte Carlo techniques, each variable must be assigned a probability distribution. The validity of these distributions directly influences the accuracy and reliability of the model outcome. To efficiently allocate resources for constructing distributions onemore » should first identify the most influential set of variables in the model. Although existing sensitivity and uncertainty analysis methods can provide a relative ranking of the importance of model inputs, they fail to identify the minimum set of stochastic inputs necessary to sufficiently characterize the outcome variance. In this paper, we describe and demonstrate a novel sensitivity/uncertainty analysis method for assessing the importance of each variable in a multimedia environmental fate model. Our analyses show that for a given scenario, a relatively small number of input variables influence the central tendency of the model and an even smaller set determines the shape of the outcome distribution. For each input, the level of influence depends on the scenario under consideration. This information is useful for developing site specific models and improving our understanding of the processes that have the greatest influence on the variance in outcomes from multimedia models.« less

Kinetic analysis of single molecule FRET transitions without trajectories

NASA Astrophysics Data System (ADS)

Schrangl, Lukas; Göhring, Janett; Schütz, Gerhard J.

2018-03-01

Single molecule Förster resonance energy transfer (smFRET) is a popular tool to study biological systems that undergo topological transitions on the nanometer scale. smFRET experiments typically require recording of long smFRET trajectories and subsequent statistical analysis to extract parameters such as the states' lifetimes. Alternatively, analysis of probability distributions exploits the shapes of smFRET distributions at well chosen exposure times and hence works without the acquisition of time traces. Here, we describe a variant that utilizes statistical tests to compare experimental datasets with Monte Carlo simulations. For a given model, parameters are varied to cover the full realistic parameter space. As output, the method yields p-values which quantify the likelihood for each parameter setting to be consistent with the experimental data. The method provides suitable results even if the actual lifetimes differ by an order of magnitude. We also demonstrated the robustness of the method to inaccurately determine input parameters. As proof of concept, the new method was applied to the determination of transition rate constants for Holliday junctions.

Quantile Functions, Convergence in Quantile, and Extreme Value Distribution Theory.

DTIC Science & Technology

1980-11-01

Gnanadesikan (1968). Quantile functions are advocated by Parzen (1979) as providing an approach to probability-based data analysis. Quantile functions are... Gnanadesikan , R. (1968). Probability Plotting Methods for the Analysis of Data, Biomtrika, 55, 1-17.

A bayesian approach to classification criteria for spectacled eiders

USGS Publications Warehouse

Taylor, B.L.; Wade, P.R.; Stehn, R.A.; Cochrane, J.F.

1996-01-01

To facilitate decisions to classify species according to risk of extinction, we used Bayesian methods to analyze trend data for the Spectacled Eider, an arctic sea duck. Trend data from three independent surveys of the Yukon-Kuskokwim Delta were analyzed individually and in combination to yield posterior distributions for population growth rates. We used classification criteria developed by the recovery team for Spectacled Eiders that seek to equalize errors of under- or overprotecting the species. We conducted both a Bayesian decision analysis and a frequentist (classical statistical inference) decision analysis. Bayesian decision analyses are computationally easier, yield basically the same results, and yield results that are easier to explain to nonscientists. With the exception of the aerial survey analysis of the 10 most recent years, both Bayesian and frequentist methods indicated that an endangered classification is warranted. The discrepancy between surveys warrants further research. Although the trend data are abundance indices, we used a preliminary estimate of absolute abundance to demonstrate how to calculate extinction distributions using the joint probability distributions for population growth rate and variance in growth rate generated by the Bayesian analysis. Recent apparent increases in abundance highlight the need for models that apply to declining and then recovering species.

Nuclear morphology for the detection of alterations in bronchial cells from lung cancer: an attempt to improve sensitivity and specificity.

PubMed

Fafin-Lefevre, Mélanie; Morlais, Fabrice; Guittet, Lydia; Clin, Bénédicte; Launoy, Guy; Galateau-Sallé, Françoise; Plancoulaine, Benoît; Herlin, Paulette; Letourneux, Marc

2011-08-01

To identify which morphologic or densitometric parameters are modified in cell nuclei from bronchopulmonary cancer based on 18 parameters involving shape, intensity, chromatin, texture, and DNA content and develop a bronchopulmonary cancer screening method relying on analysis of sputum sample cell nuclei. A total of 25 sputum samples from controls and 22 bronchial aspiration samples from patients presenting with bronchopulmonary cancer who were professionally exposed to cancer were used. After Feulgen staining, 18 morphologic and DNA content parameters were measured on cell nuclei, via image cytom- etry. A method was developed for analyzing distribution quantiles, compared with simply interpreting mean values, to characterize morphologic modifications in cell nuclei. Distribution analysis of parameters enabled us to distinguish 13 of 18 parameters that demonstrated significant differences between controls and cancer cases. These parameters, used alone, enabled us to distinguish two population types, with both sensitivity and specificity > 70%. Three parameters offered 100% sensitivity and specificity. When mean values offered high sensitivity and specificity, comparable or higher sensitivity and specificity values were observed for at least one of the corresponding quantiles. Analysis of modification in morphologic parameters via distribution analysis proved promising for screening bronchopulmonary cancer from sputum.

Distributed collaborative response surface method for mechanical dynamic assembly reliability design

NASA Astrophysics Data System (ADS)

Bai, Guangchen; Fei, Chengwei

2013-11-01

Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40˜4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.

Wavelet analysis of birefringence images of myocardium tissue

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Yu.; Ushenko, Yu. O.; Kushnerik, L.; Soltys, I. V.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Linearized radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements

NASA Astrophysics Data System (ADS)

Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego

2018-07-01

In this paper, we describe several linearized radiative transfer models which can be used for the retrieval of cloud parameters from EPIC (Earth Polychromatic Imaging Camera) measurements. The approaches under examination are (1) the linearized forward approach, represented in this paper by the linearized discrete ordinate and matrix operator methods with matrix exponential, and (2) the forward-adjoint approach based on the discrete ordinate method with matrix exponential. To enhance the performance of the radiative transfer computations, the correlated k-distribution method and the Principal Component Analysis (PCA) technique are used. We provide a compact description of the proposed methods, as well as a numerical analysis of their accuracy and efficiency when simulating EPIC measurements in the oxygen A-band channel at 764 nm. We found that the computation time of the forward-adjoint approach using the correlated k-distribution method in conjunction with PCA is approximately 13 s for simultaneously computing the derivatives with respect to cloud optical thickness and cloud top height.

Error correction and diversity analysis of population mixtures determined by NGS

PubMed Central

Burroughs, Nigel J.; Evans, David J.; Ryabov, Eugene V.

2014-01-01

The impetus for this work was the need to analyse nucleotide diversity in a viral mix taken from honeybees. The paper has two findings. First, a method for correction of next generation sequencing error in the distribution of nucleotides at a site is developed. Second, a package of methods for assessment of nucleotide diversity is assembled. The error correction method is statistically based and works at the level of the nucleotide distribution rather than the level of individual nucleotides. The method relies on an error model and a sample of known viral genotypes that is used for model calibration. A compendium of existing and new diversity analysis tools is also presented, allowing hypotheses about diversity and mean diversity to be tested and associated confidence intervals to be calculated. The methods are illustrated using honeybee viral samples. Software in both Excel and Matlab and a guide are available at http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/, the Warwick University Systems Biology Centre software download site. PMID:25405074

On sample size of the kruskal-wallis test with application to a mouse peritoneal cavity study.

PubMed

Fan, Chunpeng; Zhang, Donghui; Zhang, Cun-Hui

2011-03-01

As the nonparametric generalization of the one-way analysis of variance model, the Kruskal-Wallis test applies when the goal is to test the difference between multiple samples and the underlying population distributions are nonnormal or unknown. Although the Kruskal-Wallis test has been widely used for data analysis, power and sample size methods for this test have been investigated to a much lesser extent. This article proposes new power and sample size calculation methods for the Kruskal-Wallis test based on the pilot study in either a completely nonparametric model or a semiparametric location model. No assumption is made on the shape of the underlying population distributions. Simulation results show that, in terms of sample size calculation for the Kruskal-Wallis test, the proposed methods are more reliable and preferable to some more traditional methods. A mouse peritoneal cavity study is used to demonstrate the application of the methods. © 2010, The International Biometric Society.

Toward a quantitative account of pitch distribution in spontaneous narrative: Method and validation

PubMed Central

Matteson, Samuel E.; Streit Olness, Gloria; Caplow, Nancy J.

2013-01-01

Pitch is well-known both to animate human discourse and to convey meaning in communication. The study of the statistical population distributions of pitch in discourse will undoubtedly benefit from methodological improvements. The current investigation examines a method that parameterizes pitch in discourse as musical pitch interval H measured in units of cents and that disaggregates the sequence of peak word-pitches using tools employed in time-series analysis and digital signal processing. The investigators test the proposed methodology by its application to distributions in pitch interval of the peak word-pitch (collectively called the discourse gamut) that occur in simulated and actual spontaneous emotive narratives obtained from 17 middle-aged African-American adults. The analysis, in rigorous tests, not only faithfully reproduced simulated distributions imbedded in realistic time series that drift and include pitch breaks, but the protocol also reveals that the empirical distributions exhibit a common hidden structure when normalized to a slowly varying mode (called the gamut root) of their respective probability density functions. Quantitative differences between narratives reveal the speakers' relative propensity for the use of pitch levels corresponding to elevated degrees of a discourse gamut (the “e-la”) superimposed upon a continuum that conforms systematically to an asymmetric Laplace distribution. PMID:23654400

Pilot Scale Application of a Method for the Analysis of ...

EPA Pesticide Factsheets

A growing number of studies now indicate that perfluorinated compounds (PFCs) are globally distributed in the environment. Their widespread distribution and presence in remote locations has led to questions about the importance of atmospheric and oceanic transport. Describing their distribution in surface soils is also an essential but neglected element in developing a comprehensive understanding of their occurrence in the environment. Soils are the critical link between global atmospheric and hydrologic processes where both local and distant contaminants can accumulate and be released into aquatic and terrestrial communities. Because PFC concentrations in soils will influence ground and surface water, wildlife, and crops, methods to accurately measure PFCs in soil are clearly needed. To help answer this need, we developed a method for the analysis of nine perfluorinated carboxylic acids and four perfluorinated sulfonic acids in soil. Samples from six nations (n = 10 per nation) were analyzed by LC-MS/MS to demonstrate the method performance parameters and to make preliminary observations about the occurrence of the PFCs in soils in different parts of the world. The resulting method shows acceptable performance characteristics for the target compounds in most soils while documenting the widespread occurrence of PFCs in surface soils The National Exposure Research Laboratory′s (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in

Keeping an eye on the ring: COMS plaque loading optimization for improved dose conformity and homogeneity.

PubMed

Gagne, Nolan L; Cutright, Daniel R; Rivard, Mark J

2012-09-01

To improve tumor dose conformity and homogeneity for COMS plaque brachytherapy by investigating the dosimetric effects of varying component source ring radionuclides and source strengths. The MCNP5 Monte Carlo (MC) radiation transport code was used to simulate plaque heterogeneity-corrected dose distributions for individually-activated source rings of 14, 16 and 18 mm diameter COMS plaques, populated with (103)Pd, (125)I and (131)Cs sources. Ellipsoidal tumors were contoured for each plaque size and MATLAB programming was developed to generate tumor dose distributions for all possible ring weighting and radionuclide permutations for a given plaque size and source strength resolution, assuming a 75 Gy apical prescription dose. These dose distributions were analyzed for conformity and homogeneity and compared to reference dose distributions from uniformly-loaded (125)I plaques. The most conformal and homogeneous dose distributions were reproduced within a reference eye environment to assess organ-at-risk (OAR) doses in the Pinnacle(3) treatment planning system (TPS). The gamma-index analysis method was used to quantitatively compare MC and TPS-generated dose distributions. Concentrating > 97% of the total source strength in a single or pair of central (103)Pd seeds produced the most conformal dose distributions, with tumor basal doses a factor of 2-3 higher and OAR doses a factor of 2-3 lower than those of corresponding uniformly-loaded (125)I plaques. Concentrating 82-86% of the total source strength in peripherally-loaded (131)Cs seeds produced the most homogeneous dose distributions, with tumor basal doses 17-25% lower and OAR doses typically 20% higher than those of corresponding uniformly-loaded (125)I plaques. Gamma-index analysis found > 99% agreement between MC and TPS dose distributions. A method was developed to select intra-plaque ring radionuclide compositions and source strengths to deliver more conformal and homogeneous tumor dose distributions than uniformly-loaded (125)I plaques. This method may support coordinated investigations of an appropriate clinical target for eye plaque brachytherapy.

Signal Processing Applications Of Wigner-Ville Analysis

NASA Astrophysics Data System (ADS)

Whitehouse, H. J.; Boashash, B.

1986-04-01

The Wigner-Ville distribution (WVD), a form of time-frequency analysis, is shown to be useful in the analysis of a variety of non-stationary signals both deterministic and stochastic. The properties of the WVD are reviewed and alternative methods of calculating the WVD are discussed. Applications are presented.

Analytical method for predicting the pressure distribution about a nacelle at transonic speeds

NASA Technical Reports Server (NTRS)

Keith, J. S.; Ferguson, D. R.; Merkle, C. L.; Heck, P. H.; Lahti, D. J.

1973-01-01

The formulation and development of a computer analysis for the calculation of streamlines and pressure distributions around two-dimensional (planar and axisymmetric) isolated nacelles at transonic speeds are described. The computerized flow field analysis is designed to predict the transonic flow around long and short high-bypass-ratio fan duct nacelles with inlet flows and with exhaust flows having appropriate aerothermodynamic properties. The flow field boundaries are located as far upstream and downstream as necessary to obtain minimum disturbances at the boundary. The far-field lateral flow field boundary is analytically defined to exactly represent free-flight conditions or solid wind tunnel wall effects. The inviscid solution technique is based on a Streamtube Curvature Analysis. The computer program utilizes an automatic grid refinement procedure and solves the flow field equations with a matrix relaxation technique. The boundary layer displacement effects and the onset of turbulent separation are included, based on the compressible turbulent boundary layer solution method of Stratford and Beavers and on the turbulent separation prediction method of Stratford.

Visual accumulation tube for size analysis of sands

USGS Publications Warehouse

Colby, B.C.; Christensen, R.P.

1956-01-01

The visual-accumulation-tube method was developed primarily for making size analyses of the sand fractions of suspended-sediment and bed-material samples. Because the fundamental property governing the motion of a sediment particle in a fluid is believed to be its fall velocity. the analysis is designed to determine the fall-velocity-frequency distribution of the individual particles of the sample. The analysis is based on a stratified sedimentation system in which the sample is introduced at the top of a transparent settling tube containing distilled water. The procedure involves the direct visual tracing of the height of sediment accumulation in a contracted section at the bottom of the tube. A pen records the height on a moving chart. The method is simple and fast, provides a continuous and permanent record, gives highly reproducible results, and accurately determines the fall-velocity characteristics of the sample. The apparatus, procedure, results, and accuracy of the visual-accumulation-tube method for determining the sedimentation-size distribution of sands are presented in this paper.

Assessment of uncertainties of the models used in thermal-hydraulic computer codes

NASA Astrophysics Data System (ADS)

Gricay, A. S.; Migrov, Yu. A.

2015-09-01

The article deals with matters concerned with the problem of determining the statistical characteristics of variable parameters (the variation range and distribution law) in analyzing the uncertainty and sensitivity of calculation results to uncertainty in input data. A comparative analysis of modern approaches to uncertainty in input data is presented. The need to develop an alternative method for estimating the uncertainty of model parameters used in thermal-hydraulic computer codes, in particular, in the closing correlations of the loop thermal hydraulics block, is shown. Such a method shall feature the minimal degree of subjectivism and must be based on objective quantitative assessment criteria. The method includes three sequential stages: selecting experimental data satisfying the specified criteria, identifying the key closing correlation using a sensitivity analysis, and carrying out case calculations followed by statistical processing of the results. By using the method, one can estimate the uncertainty range of a variable parameter and establish its distribution law in the above-mentioned range provided that the experimental information is sufficiently representative. Practical application of the method is demonstrated taking as an example the problem of estimating the uncertainty of a parameter appearing in the model describing transition to post-burnout heat transfer that is used in the thermal-hydraulic computer code KORSAR. The performed study revealed the need to narrow the previously established uncertainty range of this parameter and to replace the uniform distribution law in the above-mentioned range by the Gaussian distribution law. The proposed method can be applied to different thermal-hydraulic computer codes. In some cases, application of the method can make it possible to achieve a smaller degree of conservatism in the expert estimates of uncertainties pertinent to the model parameters used in computer codes.

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

NASA Astrophysics Data System (ADS)

Di Mauro, M.; Manconi, S.; Zechlin, H.-S.; Ajello, M.; Charles, E.; Donato, F.

2018-04-01

The Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (| b| > 20^\\circ ), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10‑12 ph cm‑2 s‑1. With this method, we detect a flux break at (3.5 ± 0.4) × 10‑11 ph cm‑2 s‑1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ∼10‑11 ph cm‑2 s‑1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.

Application of short-data methods on extreme surge levels

NASA Astrophysics Data System (ADS)

Feng, X.

2014-12-01

Tropical cyclone-induced storm surges are among the most destructive natural hazards that impact the United States. Unfortunately for academic research, the available time series for extreme surge analysis are very short. The limited data introduces uncertainty and affects the accuracy of statistical analyses of extreme surge levels. This study deals with techniques applicable to data sets less than 20 years, including simulation modelling and methods based on the parameters of the parent distribution. The verified water levels from water gauges spread along the Southwest and Southeast Florida Coast, as well as the Florida Keys, are used in this study. Methods to calculate extreme storm surges are described and reviewed, including 'classical' methods based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD), and approaches designed specifically to deal with short data sets. Incorporating global-warming influence, the statistical analysis reveals enhanced extreme surge magnitudes and frequencies during warm years, while reduced levels of extreme surge activity are observed in the same study domain during cold years. Furthermore, a non-stationary GEV distribution is applied to predict the extreme surge levels with warming sea surface temperatures. The non-stationary GEV distribution indicates that with 1 Celsius degree warming in sea surface temperature from the baseline climate, the 100-year return surge level in Southwest and Southeast Florida will increase by up to 40 centimeters. The considered statistical approaches for extreme surge estimation based on short data sets will be valuable to coastal stakeholders, including urban planners, emergency managers, and the hurricane and storm surge forecasting and warning system.

Analysis of the Long Period Terms of Local and Global Data of UT1-AT

NASA Astrophysics Data System (ADS)

Stavinschi, Magdalena; Souchay, Jean; Donea, Alina-Catalina

In our analysis of UTO and UTI, the long period terms 18.6y, 13.9y, 12.5y, 11.1y, 9.2y have been emphasized. To be sure that the results are trustworthy, different methods (Scargle for data unevenly distributed,the classical least square method and Fourier analysis) have been used for the data recorded as well at the Bucharest Observatory and the data of IERS.

The uncertainty of nitrous oxide emissions from grazed grasslands: A New Zealand case study

NASA Astrophysics Data System (ADS)

Kelliher, Francis M.; Henderson, Harold V.; Cox, Neil R.

2017-01-01

Agricultural soils emit nitrous oxide (N2O), a greenhouse gas and the primary source of nitrogen oxides which deplete stratospheric ozone. Agriculture has been estimated to be the largest anthropogenic N2O source. In New Zealand (NZ), pastoral agriculture uses half the land area. To estimate the annual N2O emissions from NZ's agricultural soils, the nitrogen (N) inputs have been determined and multiplied by an emission factor (EF), the mass fraction of N inputs emitted as N2Osbnd N. To estimate the associated uncertainty, we developed an analytical method. For comparison, another estimate was determined by Monte Carlo numerical simulation. For both methods, expert judgement was used to estimate the N input uncertainty. The EF uncertainty was estimated by meta-analysis of the results from 185 NZ field trials. For the analytical method, assuming a normal distribution and independence of the terms used to calculate the emissions (correlation = 0), the estimated 95% confidence limit was ±57%. When there was a normal distribution and an estimated correlation of 0.4 between N input and EF, the latter inferred from experimental data involving six NZ soils, the analytical method estimated a 95% confidence limit of ±61%. The EF data from 185 NZ field trials had a logarithmic normal distribution. For the Monte Carlo method, assuming a logarithmic normal distribution for EF, a normal distribution for the other terms and independence of all terms, the estimated 95% confidence limits were -32% and +88% or ±60% on average. When there were the same distribution assumptions and a correlation of 0.4 between N input and EF, the Monte Carlo method estimated 95% confidence limits were -34% and +94% or ±64% on average. For the analytical and Monte Carlo methods, EF uncertainty accounted for 95% and 83% of the emissions uncertainty when the correlation between N input and EF was 0 and 0.4, respectively. As the first uncertainty analysis of an agricultural soils N2O emissions inventory using "country-specific" field trials to estimate EF uncertainty, this can be a potentially informative case study for the international scientific community.

Blade design and analysis using a modified Euler solver

NASA Technical Reports Server (NTRS)

Leonard, O.; Vandenbraembussche, R. A.

1991-01-01

An iterative method for blade design based on Euler solver and described in an earlier paper is used to design compressor and turbine blades providing shock free transonic flows. The method shows a rapid convergence, and indicates how much the flow is sensitive to small modifications of the blade geometry, that the classical iterative use of analysis methods might not be able to define. The relationship between the required Mach number distribution and the resulting geometry is discussed. Examples show how geometrical constraints imposed upon the blade shape can be respected by using free geometrical parameters or by relaxing the required Mach number distribution. The same code is used both for the design of the required geometry and for the off-design calculations. Examples illustrate the difficulty of designing blade shapes with optimal performance also outside of the design point.

Determination of the Shear Stress Distribution in a Laminate from the Applied Shear Resultant--A Simplified Shear Solution

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Yarrington, Phillip W.

2007-01-01

The simplified shear solution method is presented for approximating the through-thickness shear stress distribution within a composite laminate based on laminated beam theory. The method does not consider the solution of a particular boundary value problem, rather it requires only knowledge of the global shear loading, geometry, and material properties of the laminate or panel. It is thus analogous to lamination theory in that ply level stresses can be efficiently determined from global load resultants (as determined, for instance, by finite element analysis) at a given location in a structure and used to evaluate the margin of safety on a ply by ply basis. The simplified shear solution stress distribution is zero at free surfaces, continuous at ply boundaries, and integrates to the applied shear load. Comparisons to existing theories are made for a variety of laminates, and design examples are provided illustrating the use of the method for determining through-thickness shear stress margins in several types of composite panels and in the context of a finite element structural analysis.

Quantum Monte Carlo analysis of a charge ordered insulating antiferromagnet: The Ti 4O 7 Magneli phase

DOE PAGES

Benali, Anouar; Shulenburger, Luke; Krogel, Jaron T.; ...

2016-06-07

The Magneli phase Ti 4O 7 is an important transition metal oxide with a wide range of applications because of its interplay between charge, spin, and lattice degrees of freedom. At low temperatures, it has non-trivial magnetic states very close in energy, driven by electronic exchange and correlation interactions. We have examined three low- lying states, one ferromagnetic and two antiferromagnetic, and calculated their energies as well as Ti spin moment distributions using highly accurate Quantum Monte Carlo methods. We compare our results to those obtained from density functional theory- based methods that include approximate corrections for exchange and correlation.more » Our results confirm the nature of the states and their ordering in energy, as compared with density-functional theory methods. However, the energy differences and spin distributions differ. Here, a detailed analysis suggests that non-local exchange-correlation functionals, in addition to other approximations such as LDA+U to account for correlations, are needed to simultaneously obtain better estimates for spin moments, distributions, energy differences and energy gaps.« less

Novel Method for Incorporating Model Uncertainties into Gravitational Wave Parameter Estimates

NASA Astrophysics Data System (ADS)

Moore, Christopher J.; Gair, Jonathan R.

2014-12-01

Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications, these models are incomplete, which both reduces the prospects of detection and leads to a systematic error in the parameter estimates. In the analysis of data from gravitational wave detectors, for example, accurate waveform templates can be computed using numerical methods, but the prohibitive cost of these simulations means this can only be done for a small handful of parameters. In this Letter, a novel method to fold model uncertainties into data analysis is proposed; the waveform uncertainty is analytically marginalized over using with a prior distribution constructed by using Gaussian process regression to interpolate the waveform difference from a small training set of accurate templates. The method is well motivated, easy to implement, and no more computationally expensive than standard techniques. The new method is shown to perform extremely well when applied to a toy problem. While we use the application to gravitational wave data analysis to motivate and illustrate the technique, it can be applied in any context where model uncertainties exist.

Sobol's sensitivity analysis for a fuel cell stack assembly model with the aid of structure-selection techniques

NASA Astrophysics Data System (ADS)

Zhang, Wei; Cho, Chongdu; Piao, Changhao; Choi, Hojoon

2016-01-01

This paper presents a novel method for identifying the main parameters affecting the stress distribution of the components used in assembly modeling of proton exchange membrane fuel cell (PEMFC) stack. This method is a combination of an approximation model and Sobol's method, which allows a fast global sensitivity analysis for a set of uncertain parameters using only a limited number of calculations. Seven major parameters, i.e., Young's modulus of the end plate and the membrane electrode assembly (MEA), the contact stiffness between the MEA and bipolar plate (BPP), the X and Y positions of the bolts, the pressure of each bolt, and the thickness of the end plate, are investigated regarding their effect on four metrics, i.e., the maximum stresses of the MEA, BPP, and end plate, and the stress distribution percentage of the MEA. The analysis reveals the individual effects of each parameter and its interactions with the other parameters. The results show that the X position of a bolt has a major influence on the maximum stresses of the BPP and end plate, whereas the thickness of the end plate has the strongest effect on both the maximum stress and the stress distribution percentage of the MEA.

[Analysis of visible extinction spectrum of particle system and selection of optimal wavelength].

PubMed

Sun, Xiao-gang; Tang, Hong; Yuan, Gui-bin

2008-09-01

In the total light scattering particle sizing technique, the extinction spectrum of particle system contains some information about the particle size and refractive index. The visible extinction spectra of the common monomodal and biomodal R-R particle size distribution were computed, and the variation in the visible extinction spectrum with the particle size and refractive index was analyzed. The corresponding wavelengths were selected as the measurement wavelengths at which the second order differential extinction spectrum was discontinuous. Furthermore, the minimum and the maximum wavelengths in the visible region were also selected as the measurement wavelengths. The genetic algorithm was used as the inversion method under the dependent model The computer simulation and experiments illustrate that it is feasible to make an analysis of the extinction spectrum and use this selection method of the optimal wavelength in the total light scattering particle sizing. The rough contour of the particle size distribution can be determined after the analysis of visible extinction spectrum, so the search range of the particle size parameter is reduced in the optimal algorithm, and then a more accurate inversion result can be obtained using the selection method. The inversion results of monomodal and biomodal distribution are all still satisfactory when 1% stochastic noise is put in the transmission extinction measurement values.

Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

USGS Publications Warehouse

Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

2010-01-01

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.

Uncovering a Latent Multinomial: Analysis of Mark-Recapture Data with Misidentification

USGS Publications Warehouse

Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

2009-01-01

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.

Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis

PubMed Central

Dziak, John J.; Bray, Bethany C.; Zhang, Jieting; Zhang, Minqiang; Lanza, Stephanie T.

2016-01-01

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt’s (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators. PMID:28630602

A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Lall, Upmanu; Troy, Tara; Devineni, Naresh

2016-10-01

We estimate local and regional Generalized Extreme Value (GEV) distribution parameters for flood frequency analysis in a multilevel, hierarchical Bayesian framework, to explicitly model and reduce uncertainties. As prior information for the model, we assume that the GEV location and scale parameters for each site come from independent log-normal distributions, whose mean parameter scales with the drainage area. From empirical and theoretical arguments, the shape parameter for each site is shrunk towards a common mean. Non-informative prior distributions are assumed for the hyperparameters and the MCMC method is used to sample from the joint posterior distribution. The model is tested using annual maximum series from 20 streamflow gauges located in an 83,000 km2 flood prone basin in Southeast Brazil. The results show a significant reduction of uncertainty estimates of flood quantile estimates over the traditional GEV model, particularly for sites with shorter records. For return periods within the range of the data (around 50 years), the Bayesian credible intervals for the flood quantiles tend to be narrower than the classical confidence limits based on the delta method. As the return period increases beyond the range of the data, the confidence limits from the delta method become unreliable and the Bayesian credible intervals provide a way to estimate satisfactory confidence bands for the flood quantiles considering parameter uncertainties and regional information. In order to evaluate the applicability of the proposed hierarchical Bayesian model for regional flood frequency analysis, we estimate flood quantiles for three randomly chosen out-of-sample sites and compare with classical estimates using the index flood method. The posterior distributions of the scaling law coefficients are used to define the predictive distributions of the GEV location and scale parameters for the out-of-sample sites given only their drainage areas and the posterior distribution of the average shape parameter is taken as the regional predictive distribution for this parameter. While the index flood method does not provide a straightforward way to consider the uncertainties in the index flood and in the regional parameters, the results obtained here show that the proposed Bayesian method is able to produce adequate credible intervals for flood quantiles that are in accordance with empirical estimates.

Analysis of shear test method for composite laminates

NASA Technical Reports Server (NTRS)

Bergner, H. W., Jr.; Davis, J. G., Jr.; Herakovich, C. T.

1977-01-01

An elastic plane stress finite element analysis of the stress distributions in four flat test specimens for in-plane shear response of composite materials subjected to mechanical or thermal loads is presented. The shear test specimens investigated include: slotted coupon, cross beam, losipescu, and rail shear. Results are presented in the form of normalized shear contour plots for all three in-plane stess components. It is shown that the cross beam, losipescu, and rail shear specimens have stress distributions which are more than adequate for determining linear shear behavior of composite materials. Laminate properties, core effects, and fixture configurations are among the factors which were found to influence the stress distributions.

Global stabilization analysis of inertial memristive recurrent neural networks with discrete and distributed delays.

PubMed

Wang, Leimin; Zeng, Zhigang; Ge, Ming-Feng; Hu, Junhao

2018-05-02

This paper deals with the stabilization problem of memristive recurrent neural networks with inertial items, discrete delays, bounded and unbounded distributed delays. First, for inertial memristive recurrent neural networks (IMRNNs) with second-order derivatives of states, an appropriate variable substitution method is invoked to transfer IMRNNs into a first-order differential form. Then, based on nonsmooth analysis theory, several algebraic criteria are established for the global stabilizability of IMRNNs under proposed feedback control, where the cases with both bounded and unbounded distributed delays are successfully addressed. Finally, the theoretical results are illustrated via the numerical simulations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Control of the Low-energy X-rays by Using MCNP5 and Numerical Analysis for a New Concept Intra-oral X-ray Imaging System

NASA Astrophysics Data System (ADS)

Huh, Jangyong; Ji, Yunseo; Lee, Rena

2018-05-01

An X-ray control algorithm to modulate the X-ray intensity distribution over the FOV (field of view) has been developed by using numerical analysis and MCNP5, a particle transport simulation code on the basis of the Monte Carlo method. X-rays, which are widely used in medical diagnostic imaging, should be controlled in order to maximize the performance of the X-ray imaging system. However, transporting X-rays, like a liquid or a gas is conveyed through a physical form such as pipes, is not possible. In the present study, an X-ray control algorithm and technique to uniformize the Xray intensity projected on the image sensor were developed using a flattening filter and a collimator in order to alleviate the anisotropy of the distribution of X-rays due to intrinsic features of the X-ray generator. The proposed method, which is combined with MCNP5 modeling and numerical analysis, aimed to optimize a flattening filter and a collimator for a uniform distribution of X-rays. Their size and shape were estimated from the method. The simulation and the experimental results both showed that the method yielded an intensity distribution over an X-ray field of 6×4 cm2 at SID (source to image-receptor distance) of 5 cm with a uniformity of more than 90% when the flattening filter and the collimator were mounted on the system. The proposed algorithm and technique are not only confined to flattening filter development but can also be applied for other X-ray related research and development efforts.

Time is Money

NASA Astrophysics Data System (ADS)

Ausloos, Marcel; Vandewalle, Nicolas; Ivanova, Kristinka

Specialized topics on financial data analysis from a numerical and physical point of view are discussed when pertaining to the analysis of coherent and random sequences in financial fluctuations within (i) the extended detrended fluctuation analysis method, (ii) multi-affine analysis technique, (iii) mobile average intersection rules and distributions, (iv) sandpile avalanches models for crash prediction, (v) the (m,k)-Zipf method and (vi) the i-variability diagram technique for sorting out short range correlations. The most baffling result that needs further thought from mathematicians and physicists is recalled: the crossing of two mobile averages is an original method for measuring the "signal" roughness exponent, but why it is so is not understood up to now.

A method of using cluster analysis to study statistical dependence in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Mesh-matrix analysis method for electromagnetic launchers

NASA Technical Reports Server (NTRS)

Elliott, David G.

1989-01-01

The mesh-matrix method is a procedure for calculating the current distribution in the conductors of electromagnetic launchers with coil or flat-plate geometry. Once the current distribution is known the launcher performance can be calculated. The method divides the conductors into parallel current paths, or meshes, and finds the current in each mesh by matrix inversion. The author presents procedures for writing equations for the current and voltage relations for a few meshes to serve as a pattern for writing the computer code. An available subroutine package provides routines for field and flux coefficients and equation solution.

Methods and apparatus for analysis of chromatographic migration patterns

DOEpatents

Stockham, Thomas G.; Ives, Jeffrey T.

1993-01-01

A method and apparatus for sharpening signal peaks in a signal representing the distribution of biological or chemical components of a mixture separated by a chromatographic technique such as, but not limited to, electrophoresis. A key step in the method is the use of a blind deconvolution technique, presently embodied as homomorphic filtering, to reduce the contribution of a blurring function to the signal encoding the peaks of the distribution. The invention further includes steps and apparatus directed to determination of a nucleotide sequence from a set of four such signals representing DNA sequence data derived by electrophoretic means.

Signal acquisition and scale calibration for beam power density distribution of electron beam welding

NASA Astrophysics Data System (ADS)

Peng, Yong; Li, Hongqiang; Shen, Chunlong; Guo, Shun; Zhou, Qi; Wang, Kehong

2017-06-01

The power density distribution of electron beam welding (EBW) is a key factor to reflect the beam quality. The beam quality test system was designed for the actual beam power density distribution of high-voltage EBW. After the analysis of characteristics and phase relationship between the deflection control signal and the acquisition signal, the Post-Trigger mode was proposed for the signal acquisition meanwhile the same external clock source was shared by the control signal and the sampling clock. The power density distribution of beam cross-section was reconstructed using one-dimensional signal that was processed by median filtering, twice signal segmentation and spatial scale calibration. The diameter of beam cross-section was defined by amplitude method and integral method respectively. The measured diameter of integral definition is bigger than that of amplitude definition, but for the ideal distribution the former is smaller than the latter. The measured distribution without symmetrical shape is not concentrated compared to Gaussian distribution.

Defining and Enabling Resiliency of Electric Distribution Systems With Multiple Microgrids

DOE PAGES

Chanda, Sayonsom; Srivastava, Anurag K.

2016-05-02

This paper presents a method for quantifying and enabling the resiliency of a power distribution system (PDS) using analytical hierarchical process and percolation theory. Using this metric, quantitative analysis can be done to analyze the impact of possible control decisions to pro-actively enable the resilient operation of distribution system with multiple microgrids and other resources. Developed resiliency metric can also be used in short term distribution system planning. The benefits of being able to quantify resiliency can help distribution system planning engineers and operators to justify control actions, compare different reconfiguration algorithms, develop proactive control actions to avert power systemmore » outage due to impending catastrophic weather situations or other adverse events. Validation of the proposed method is done using modified CERTS microgrids and a modified industrial distribution system. Furthermore, simulation results show topological and composite metric considering power system characteristics to quantify the resiliency of a distribution system with the proposed methodology, and improvements in resiliency using two-stage reconfiguration algorithm and multiple microgrids.« less

Implementation Recommendations for MOSAIC: A Workflow Architecture for Analytic Enrichment. Analysis and Recommendations for the Implementation of a Cohesive Method for Orchestrating Analytics in a Distributed Model

DTIC Science & Technology

2011-02-01

Process Architecture Technology Analysis: Executive .............................................. 15 UIMA as Executive...44 A.4: Flow Code in UIMA ......................................................................................................... 46... UIMA ................................................................................................................................ 57 E.2

Consistent maximum entropy representations of pipe flow networks

NASA Astrophysics Data System (ADS)

Waldrip, Steven H.; Niven, Robert K.; Abel, Markus; Schlegel, Michael

2017-06-01

The maximum entropy method is used to predict flows on water distribution networks. This analysis extends the water distribution network formulation of Waldrip et al. (2016) Journal of Hydraulic Engineering (ASCE), by the use of a continuous relative entropy defined on a reduced parameter set. This reduction in the parameters that the entropy is defined over ensures consistency between different representations of the same network. The performance of the proposed reduced parameter method is demonstrated with a one-loop network case study.

Confidence Intervals for True Scores Using the Skew-Normal Distribution

ERIC Educational Resources Information Center

Garcia-Perez, Miguel A.

2010-01-01

A recent comparative analysis of alternative interval estimation approaches and procedures has shown that confidence intervals (CIs) for true raw scores determined with the Score method--which uses the normal approximation to the binomial distribution--have actual coverage probabilities that are closest to their nominal level. It has also recently…

An Analysis of Fifth-Grade Students' Performance When Solving Selected Open Distributive Sentences. Technical Report No. 397.

ERIC Educational Resources Information Center

Hobbs, Charles Eugene

The author investigates elementary school students' performance when solving selected open distributive sentences in relation to three factors (Open Sentence Type, Context, Number Size) and identifies and classifies solution methods attempted by students and students' errors in performance. Eighty fifth-grade students participated in the…

A computational method for estimating the dosimetric effect of intra-fraction motion on step-and-shoot IMRT and compensator plans

NASA Astrophysics Data System (ADS)

Waghorn, Ben J.; Shah, Amish P.; Ngwa, Wilfred; Meeks, Sanford L.; Moore, Joseph A.; Siebers, Jeffrey V.; Langen, Katja M.

2010-07-01

Intra-fraction organ motion during intensity-modulated radiation therapy (IMRT) treatment can cause differences between the planned and the delivered dose distribution. To investigate the extent of these dosimetric changes, a computational model was developed and validated. The computational method allows for calculation of the rigid motion perturbed three-dimensional dose distribution in the CT volume and therefore a dose volume histogram-based assessment of the dosimetric impact of intra-fraction motion on a rigidly moving body. The method was developed and validated for both step-and-shoot IMRT and solid compensator IMRT treatment plans. For each segment (or beam), fluence maps were exported from the treatment planning system. Fluence maps were shifted according to the target position deduced from a motion track. These shifted, motion-encoded fluence maps were then re-imported into the treatment planning system and were used to calculate the motion-encoded dose distribution. To validate the accuracy of the motion-encoded dose distribution the treatment plan was delivered to a moving cylindrical phantom using a programmed four-dimensional motion phantom. Extended dose response (EDR-2) film was used to measure a planar dose distribution for comparison with the calculated motion-encoded distribution using a gamma index analysis (3% dose difference, 3 mm distance-to-agreement). A series of motion tracks incorporating both inter-beam step-function shifts and continuous sinusoidal motion were tested. The method was shown to accurately predict the film's dose distribution for all of the tested motion tracks, both for the step-and-shoot IMRT and compensator plans. The average gamma analysis pass rate for the measured dose distribution with respect to the calculated motion-encoded distribution was 98.3 ± 0.7%. For static delivery the average film-to-calculation pass rate was 98.7 ± 0.2%. In summary, a computational technique has been developed to calculate the dosimetric effect of intra-fraction motion. This technique has the potential to evaluate a given plan's sensitivity to anticipated organ motion. With knowledge of the organ's motion it can also be used as a tool to assess the impact of measured intra-fraction motion after dose delivery.

A Wireless Sensor Network approach for distributed in-line chemical analysis of water.

PubMed

Capella, J V; Bonastre, A; Ors, R; Peris, M

2010-03-15

In this work we propose the implementation of a distributed system based on a Wireless Sensor Network for the control of a chemical analysis system for fresh water. This implementation is presented by describing the nodes that form the distributed system, the communication system by wireless networks, control strategies, and so on. Nitrate, ammonium, and chloride are measured in-line using appropriate ion selective electrodes (ISEs), the results obtained being compared with those provided by the corresponding reference methods. Recovery analyses with ISEs and standard methods, study of interferences, and evaluation of major sensor features have also been carried out. The communication among the nodes that form the distributed system is implemented by means of the utilization of proprietary wireless networks, and secondary data transmission services (GSM or GPRS) provided by a mobile telephone operator. The information is processed, integrated and stored in a control center. These data can be retrieved--through the Internet--so as to know the real-time system status and its evolution. Copyright (c) 2009 Elsevier B.V. All rights reserved.

Predicting location-specific extreme coastal floods in the future climate by introducing a probabilistic method to calculate maximum elevation of the continuous water mass caused by a combination of water level variations and wind waves

NASA Astrophysics Data System (ADS)

Leijala, Ulpu; Björkqvist, Jan-Victor; Johansson, Milla M.; Pellikka, Havu

2017-04-01

Future coastal management continuously strives for more location-exact and precise methods to investigate possible extreme sea level events and to face flooding hazards in the most appropriate way. Evaluating future flooding risks by understanding the behaviour of the joint effect of sea level variations and wind waves is one of the means to make more comprehensive flooding hazard analysis, and may at first seem like a straightforward task to solve. Nevertheless, challenges and limitations such as availability of time series of the sea level and wave height components, the quality of data, significant locational variability of coastal wave height, as well as assumptions to be made depending on the study location, make the task more complicated. In this study, we present a statistical method for combining location-specific probability distributions of water level variations (including local sea level observations and global mean sea level rise) and wave run-up (based on wave buoy measurements). The goal of our method is to obtain a more accurate way to account for the waves when making flooding hazard analysis on the coast compared to the approach of adding a separate fixed wave action height on top of sea level -based flood risk estimates. As a result of our new method, we gain maximum elevation heights with different return periods of the continuous water mass caused by a combination of both phenomena, "the green water". We also introduce a sensitivity analysis to evaluate the properties and functioning of our method. The sensitivity test is based on using theoretical wave distributions representing different alternatives of wave behaviour in relation to sea level variations. As these wave distributions are merged with the sea level distribution, we get information on how the different wave height conditions and shape of the wave height distribution influence the joint results. Our method presented here can be used as an advanced tool to minimize over- and underestimation of the combined effect of sea level variations and wind waves, and to help coastal infrastructure planning and support smooth and safe operation of coastal cities in a changing climate.

Sample size determination for mediation analysis of longitudinal data.

PubMed

Pan, Haitao; Liu, Suyu; Miao, Danmin; Yuan, Ying

2018-03-27

Sample size planning for longitudinal data is crucial when designing mediation studies because sufficient statistical power is not only required in grant applications and peer-reviewed publications, but is essential to reliable research results. However, sample size determination is not straightforward for mediation analysis of longitudinal design. To facilitate planning the sample size for longitudinal mediation studies with a multilevel mediation model, this article provides the sample size required to achieve 80% power by simulations under various sizes of the mediation effect, within-subject correlations and numbers of repeated measures. The sample size calculation is based on three commonly used mediation tests: Sobel's method, distribution of product method and the bootstrap method. Among the three methods of testing the mediation effects, Sobel's method required the largest sample size to achieve 80% power. Bootstrapping and the distribution of the product method performed similarly and were more powerful than Sobel's method, as reflected by the relatively smaller sample sizes. For all three methods, the sample size required to achieve 80% power depended on the value of the ICC (i.e., within-subject correlation). A larger value of ICC typically required a larger sample size to achieve 80% power. Simulation results also illustrated the advantage of the longitudinal study design. The sample size tables for most encountered scenarios in practice have also been published for convenient use. Extensive simulations study showed that the distribution of the product method and bootstrapping method have superior performance to the Sobel's method, but the product method was recommended to use in practice in terms of less computation time load compared to the bootstrapping method. A R package has been developed for the product method of sample size determination in mediation longitudinal study design.

Analysis on IGBT and Diode Failures in Distribution Electronic Power Transformers

NASA Astrophysics Data System (ADS)

Wang, Si-cong; Sang, Zi-xia; Yan, Jiong; Du, Zhi; Huang, Jia-qi; Chen, Zhu

2018-02-01

Fault characteristics of power electronic components are of great importance for a power electronic device, and are of extraordinary importance for those applied in power system. The topology structures and control method of Distribution Electronic Power Transformer (D-EPT) are introduced, and an exploration on fault types and fault characteristics for the IGBT and diode failures is presented. The analysis and simulation of different fault types for the fault characteristics lead to the D-EPT fault location scheme.

Predicting the probability of slip in gait: methodology and distribution study.

PubMed

Gragg, Jared; Yang, James

2016-01-01

The likelihood of a slip is related to the available and required friction for a certain activity, here gait. Classical slip and fall analysis presumed that a walking surface was safe if the difference between the mean available and required friction coefficients exceeded a certain threshold. Previous research was dedicated to reformulating the classical slip and fall theory to include the stochastic variation of the available and required friction when predicting the probability of slip in gait. However, when predicting the probability of a slip, previous researchers have either ignored the variation in the required friction or assumed the available and required friction to be normally distributed. Also, there are no published results that actually give the probability of slip for various combinations of required and available frictions. This study proposes a modification to the equation for predicting the probability of slip, reducing the previous equation from a double-integral to a more convenient single-integral form. Also, a simple numerical integration technique is provided to predict the probability of slip in gait: the trapezoidal method. The effect of the random variable distributions on the probability of slip is also studied. It is shown that both the required and available friction distributions cannot automatically be assumed as being normally distributed. The proposed methods allow for any combination of distributions for the available and required friction, and numerical results are compared to analytical solutions for an error analysis. The trapezoidal method is shown to be highly accurate and efficient. The probability of slip is also shown to be sensitive to the input distributions of the required and available friction. Lastly, a critical value for the probability of slip is proposed based on the number of steps taken by an average person in a single day.

An empirical analysis of the distribution of the duration of overshoots in a stationary gaussian stochastic process

NASA Technical Reports Server (NTRS)

Parrish, R. S.; Carter, M. C.

1974-01-01

This analysis utilizes computer simulation and statistical estimation. Realizations of stationary gaussian stochastic processes with selected autocorrelation functions are computer simulated. Analysis of the simulated data revealed that the mean and the variance of a process were functionally dependent upon the autocorrelation parameter and crossing level. Using predicted values for the mean and standard deviation, by the method of moments, the distribution parameters was estimated. Thus, given the autocorrelation parameter, crossing level, mean, and standard deviation of a process, the probability of exceeding the crossing level for a particular length of time was calculated.

S-curve networks and an approximate method for estimating degree distributions of complex networks

NASA Astrophysics Data System (ADS)

Guo, Jin-Li

2010-12-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

A Study to Investigate the Sleeping Comfort of Mattress using Finite Element Method

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Kamijo, Masayoshi; Shimizu, Yoshio

Sleep is an essential physiological activity for human beings and many studies have so far investigated sleeping comfort of mattresses. The appropriate measurement of stress distribution within the human body would provide valuable information to us. For the appropriate measurement to estimate stress distribution within the human body, numerical analysis is considered one of the most desirable techniques, and Finite Element Method (FEM), which is widely accepted as a useful numerical technique, was utilized in this study. Since human body dimensions have individual differences, however, it is presumed that the way of the internal stress distribution also changes due to the differences and that the mattress preference varies among different body forms. Thus, we developed three human FEM models reproducing the body forms of three types of male subjects, and investigated the sleeping comfort of mattress based on the relationship between FEM analysis findings and sensory testing results. In comparison with the results of both FEM analysis and sensory testing in the neck region, we found, the sensory testing results corresponded to the FEM analysis findings, and it was possible to estimate subjects' preferences of mattress and comfort in the neck region using the FEM analysis. In this study, we believe, the FEM analysis managed to quantify the subjects' preferences for mattress and to prove itself that it is the valuable tools to examine the sleeping comfort of mattress.

Performance analysis of mineral mapping method to delineate mineralization zones under tropical region

NASA Astrophysics Data System (ADS)

Wakila, M. H.; Saepuloh, A.; Heriawan, M. N.; Susanto, A.

2016-09-01

Geothermal explorations and productions are currently being intensively conducted at certain areas in Indonesia such as Wayang Windu Geothermal Field (WWGF) in West Java, Indonesia. The WWGF is located at wide area covering about 40 km2. An accurate method to map the distribution of heterogeneity minerals is necessary for wide areas such as WWGF. Mineral mapping is an important method in geothermal explorations to determine the distribution of minerals which indicate the surface manifestations of geothermal system. This study is aimed to determine the most precise and accurate methods for minerals mapping at geothermal field. Field measurements were performed to assess the accuracy of three proposed methods: 1) Minimum Noise Fraction (MNF), utilizing the linear transformation method to eliminate the correlation among the spectra bands and to reduce the noise in the data, 2) Pixel Purity Index (PPI), a designed method to find the most extreme spectrum pixels and their characteristics due to end-members mixing, 3) Spectral Angle Mapper (SAM), an image classification technique by measuring the spectral similarity between an unknown object with spectral reference in n- dimension. The output of those methods were mineral distribution occurrence. The performance of each mapping method was analyzed based on the ground truth data. Among the three proposed method, the SAM classification method is the most appropriate and accurate for mineral mapping related to spatial distribution of alteration minerals.

CDF-XL: computing cumulative distribution functions of reaction time data in Excel.

PubMed

Houghton, George; Grange, James A

2011-12-01

In experimental psychology, central tendencies of reaction time (RT) distributions are used to compare different experimental conditions. This emphasis on the central tendency ignores additional information that may be derived from the RT distribution itself. One method for analysing RT distributions is to construct cumulative distribution frequency plots (CDFs; Ratcliff, Psychological Bulletin 86:446-461, 1979). However, this method is difficult to implement in widely available software, severely restricting its use. In this report, we present an Excel-based program, CDF-XL, for constructing and analysing CDFs, with the aim of making such techniques more readily accessible to researchers, including students (CDF-XL can be downloaded free of charge from the Psychonomic Society's online archive). CDF-XL functions as an Excel workbook and starts from the raw experimental data, organised into three columns (Subject, Condition, and RT) on an Input Data worksheet (a point-and-click utility is provided for achieving this format from a broader data set). No further preprocessing or sorting of the data is required. With one click of a button, CDF-XL will generate two forms of cumulative analysis: (1) "standard" CDFs, based on percentiles of participant RT distributions (by condition), and (2) a related analysis employing the participant means of rank-ordered RT bins. Both analyses involve partitioning the data in similar ways, but the first uses a "median"-type measure at the participant level, while the latter uses the mean. The results are presented in three formats: (i) by participants, suitable for entry into further statistical analysis; (ii) grand means by condition; and (iii) completed CDF plots in Excel charts.

Review of Vibration-Based Helicopters Health and Usage Monitoring Methods

DTIC Science & Technology

2001-04-05

FM4, NA4, NA4*, NB4 and NB48* (Polyshchuk et al., 1998). The Wigner - Ville distribution ( WVD ) is a joint time-frequency signal analysis. The WVD is one...signal processing methodologies that are of relevance to vibration based damage detection (e.g., Wavelet Transform and Wigner - Ville distribution ) will be...operation cost, reduce maintenance flights, and increase flight safety. Key Words: HUMS; Wavelet Transform; Wigner - Ville distribution ; O&S; Machinery

Influence of the distribution of PWO crystal radiation hardness on electromagnetic calorimeter performance

NASA Astrophysics Data System (ADS)

Drobychev, Gleb Yu.; Borisevich, Andrei E.; Korjik, Mikhail V.; Lecoq, Paul; Moroz, Valeri I.; Peigneux, Jean-Pierre

2002-06-01

The distribution of about 5000 mass-produced PWO crystals by their light yield and radiation hardness is analysed. The correlation between results of radiation hardness measurements at low and saturating dose rates is refined. A method for the evaluation of the energy resolution of the electromagnetic calorimeter accounting for a distribution of individual PWO crystal characteristics is proposed. A preliminary analysis of the PWO crystal recovery kinetics is also performed.

A New Method for Automated Identification and Morphometry of Myelinated Fibers Through Light Microscopy Image Analysis.

PubMed

Novas, Romulo Bourget; Fazan, Valeria Paula Sassoli; Felipe, Joaquim Cezar

2016-02-01

Nerve morphometry is known to produce relevant information for the evaluation of several phenomena, such as nerve repair, regeneration, implant, transplant, aging, and different human neuropathies. Manual morphometry is laborious, tedious, time consuming, and subject to many sources of error. Therefore, in this paper, we propose a new method for the automated morphometry of myelinated fibers in cross-section light microscopy images. Images from the recurrent laryngeal nerve of adult rats and the vestibulocochlear nerve of adult guinea pigs were used herein. The proposed pipeline for fiber segmentation is based on the techniques of competitive clustering and concavity analysis. The evaluation of the proposed method for segmentation of images was done by comparing the automatic segmentation with the manual segmentation. To further evaluate the proposed method considering morphometric features extracted from the segmented images, the distributions of these features were tested for statistical significant difference. The method achieved a high overall sensitivity and very low false-positive rates per image. We detect no statistical difference between the distribution of the features extracted from the manual and the pipeline segmentations. The method presented a good overall performance, showing widespread potential in experimental and clinical settings allowing large-scale image analysis and, thus, leading to more reliable results.

A moment-convergence method for stochastic analysis of biochemical reaction networks.

PubMed

Zhang, Jiajun; Nie, Qing; Zhou, Tianshou

2016-05-21

Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

PubMed Central

Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

An approximate methods approach to probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.

A Multi-Variate Fit to the Chemical Composition of the Cosmic-Ray Spectrum

NASA Astrophysics Data System (ADS)

Eisch, Jonathan

Since the discovery of cosmic rays over a century ago, evidence of their origins has remained elusive. Deflected by galactic magnetic fields, the only direct evidence of their origin and propagation remain encoded in their energy distribution and chemical composition. Current models of galactic cosmic rays predict variations of the energy distribution of individual elements in an energy region around 3x1015 eV known as the knee. This work presents a method to measure the energy distribution of individual elemental groups in the knee region and its application to a year of data from the IceCube detector. The method uses cosmic rays detected by both IceTop, the surface-array component, and the deep-ice component of IceCube during the 2009-2010 operation of the IC-59 detector. IceTop is used to measure the energy and the relative likelihood of the mass composition using the signal from the cosmic-ray induced extensive air shower reaching the surface. IceCube, 1.5 km below the surface, measures the energy of the high-energy bundle of muons created in the very first interactions after the cosmic ray enters the atmosphere. These event distributions are fit by a constrained model derived from detailed simulations of cosmic rays representing five chemical elements. The results of this analysis are evaluated in terms of the theoretical uncertainties in cosmic-ray interactions and seasonal variations in the atmosphere. The improvements in high-energy cosmic ray hadronic-interaction models informed by this analysis, combined with increased data from subsequent operation of the IceCube detector, could provide crucial limits on the origin of cosmic rays and their propagation through the galaxy. In the course of developing this method, a number of analysis and statistical techniques were developed to deal with the difficulties inherent in this type of measurement. These include a composition-sensitive air shower reconstruction technique, a method to model simulated event distributions with limited statistics, and a method to optimize and estimate the error on a regularized fit.

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

An Approach to the Constrained Design of Natural Laminar Flow Airfoils

NASA Technical Reports Server (NTRS)

Green, Bradford E.

1997-01-01

A design method has been developed by which an airfoil with a substantial amount of natural laminar flow can be designed, while maintaining other aerodynamic and geometric constraints. After obtaining the initial airfoil's pressure distribution at the design lift coefficient using an Euler solver coupled with an integral turbulent boundary layer method, the calculations from a laminar boundary layer solver are used by a stability analysis code to obtain estimates of the transition location (using N-Factors) for the starting airfoil. A new design method then calculates a target pressure distribution that will increase the laminar flow toward the desired amount. An airfoil design method is then iteratively used to design an airfoil that possesses that target pressure distribution. The new airfoil's boundary layer stability characteristics are determined, and this iterative process continues until an airfoil is designed that meets the laminar flow requirement and as many of the other constraints as possible.

An approach to the constrained design of natural laminar flow airfoils

NASA Technical Reports Server (NTRS)

Green, Bradford Earl

1995-01-01

A design method has been developed by which an airfoil with a substantial amount of natural laminar flow can be designed, while maintaining other aerodynamic and geometric constraints. After obtaining the initial airfoil's pressure distribution at the design lift coefficient using an Euler solver coupled with an integml turbulent boundary layer method, the calculations from a laminar boundary layer solver are used by a stability analysis code to obtain estimates of the transition location (using N-Factors) for the starting airfoil. A new design method then calculates a target pressure distribution that will increase the larninar flow toward the desired amounl An airfoil design method is then iteratively used to design an airfoil that possesses that target pressure distribution. The new airfoil's boundary layer stability characteristics are determined, and this iterative process continues until an airfoil is designed that meets the laminar flow requirement and as many of the other constraints as possible.

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Neutron-stimulated gamma ray analysis of soil

USDA-ARS?s Scientific Manuscript database

The chapter will discuss methods to use gamma rays to measure elements in soil. In regard to land management, there is a need to develop a non-destructive, non-contact, in-situ method of determining soil elements distributed in a soil volume or on soil surface. A unique method having all of above ...

Study of multilayered SiGe semiconductor structures by X-ray diffractometry, grazing-incidence X-ray reflectometry, and secondary-ion mass spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yunin, P. A., E-mail: yunin@ipmras.ru; Drozdov, Yu. N.; Drozdov, M. N.

2013-12-15

In this publication, we report the results of studying a multilayerd nonperiodic SiGe/Si structure by the methods of X-ray diffractometry, grazing-angle X-ray reflectometry, and secondary-ion mass spectrometry (SIMS). Special attention is paid to the processing of the component distribution profile using the SIMS method and to consideration of the most significant experimental distortions introduced by this method. A method for processing the measured composition distribution profile with subsequent consideration of the influence of matrix effects, variation in the etching rate, and remnants of ion sputtering is suggested. The results of such processing are compared with a structure model obtained uponmore » combined analysis of X-ray diffractometry and grazing-angle reflectometry data. Good agreement between the results is established. It is shown that the combined use of independent techniques makes it possible to improve the methods of secondary-ion mass spectrometry and grazing-incidence reflectometry as applied to an analysis of multilayered heteroepitaxial structures (to increase the accuracy and informativity of these methods)« less

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

PubMed

Sitek, Arkadiusz; Li, Quanzheng; El Fakhri, Georges; Alpert, Nathaniel M

2016-10-01

Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Uncertainty in determining extreme precipitation thresholds

NASA Astrophysics Data System (ADS)

Liu, Bingjun; Chen, Junfan; Chen, Xiaohong; Lian, Yanqing; Wu, Lili

2013-10-01

Extreme precipitation events are rare and occur mostly on a relatively small and local scale, which makes it difficult to set the thresholds for extreme precipitations in a large basin. Based on the long term daily precipitation data from 62 observation stations in the Pearl River Basin, this study has assessed the applicability of the non-parametric, parametric, and the detrended fluctuation analysis (DFA) methods in determining extreme precipitation threshold (EPT) and the certainty to EPTs from each method. Analyses from this study show the non-parametric absolute critical value method is easy to use, but unable to reflect the difference of spatial rainfall distribution. The non-parametric percentile method can account for the spatial distribution feature of precipitation, but the problem with this method is that the threshold value is sensitive to the size of rainfall data series and is subjected to the selection of a percentile thus make it difficult to determine reasonable threshold values for a large basin. The parametric method can provide the most apt description of extreme precipitations by fitting extreme precipitation distributions with probability distribution functions; however, selections of probability distribution functions, the goodness-of-fit tests, and the size of the rainfall data series can greatly affect the fitting accuracy. In contrast to the non-parametric and the parametric methods which are unable to provide information for EPTs with certainty, the DFA method although involving complicated computational processes has proven to be the most appropriate method that is able to provide a unique set of EPTs for a large basin with uneven spatio-temporal precipitation distribution. The consistency between the spatial distribution of DFA-based thresholds with the annual average precipitation, the coefficient of variation (CV), and the coefficient of skewness (CS) for the daily precipitation further proves that EPTs determined by the DFA method are more reasonable and applicable for the Pearl River Basin.

Application of a transonic potential flow code to the static aeroelastic analysis of three-dimensional wings

NASA Technical Reports Server (NTRS)

Whitlow, W., Jr.; Bennett, R. M.

1982-01-01

Since the aerodynamic theory is nonlinear, the method requires the coupling of two iterative processes - an aerodynamic analysis and a structural analysis. A full potential analysis code, FLO22, is combined with a linear structural analysis to yield aerodynamic load distributions on and deflections of elastic wings. This method was used to analyze an aeroelastically-scaled wind tunnel model of a proposed executive-jet transport wing and an aeroelastic research wing. The results are compared with the corresponding rigid-wing analyses, and some effects of elasticity on the aerodynamic loading are noted.

Log Normal Distribution of Cellular Uptake of Radioactivity: Statistical Analysis of Alpha Particle Track Autoradiography

PubMed Central

Neti, Prasad V.S.V.; Howell, Roger W.

2008-01-01

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a log normal distribution function (J Nucl Med 47, 6 (2006) 1049-1058) with the aid of an autoradiographic approach. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analyses of these data. Methods The measured distributions of alpha particle tracks per cell were subjected to statistical tests with Poisson (P), log normal (LN), and Poisson – log normal (P – LN) models. Results The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL 210Po-citrate. When cells were exposed to 67 kBq/mL, the P – LN distribution function gave a better fit, however, the underlying activity distribution remained log normal. Conclusions The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution. PMID:16741316

Strain Modal Analysis of Small and Light Pipes Using Distributed Fibre Bragg Grating Sensors

PubMed Central

Huang, Jun; Zhou, Zude; Zhang, Lin; Chen, Juntao; Ji, Chunqian; Pham, Duc Truong

2016-01-01

Vibration fatigue failure is a critical problem of hydraulic pipes under severe working conditions. Strain modal testing of small and light pipes is a good option for dynamic characteristic evaluation, structural health monitoring and damage identification. Unique features such as small size, light weight, and high multiplexing capability enable Fibre Bragg Grating (FBG) sensors to measure structural dynamic responses where sensor size and placement are critical. In this paper, experimental strain modal analysis of pipes using distributed FBG sensors ispresented. Strain modal analysis and parameter identification methods are introduced. Experimental strain modal testing and finite element analysis for a cantilever pipe have been carried out. The analysis results indicate that the natural frequencies and strain mode shapes of the tested pipe acquired by FBG sensors are in good agreement with the results obtained by a reference accelerometer and simulation outputs. The strain modal parameters of a hydraulic pipe were obtained by the proposed strain modal testing method. FBG sensors have been shown to be useful in the experimental strain modal analysis of small and light pipes in mechanical, aeronautic and aerospace applications. PMID:27681728

Statistical deprojection of galaxy pairs

NASA Astrophysics Data System (ADS)

Nottale, Laurent; Chamaraux, Pierre

2018-06-01

Aims: The purpose of the present paper is to provide methods of statistical analysis of the physical properties of galaxy pairs. We perform this study to apply it later to catalogs of isolated pairs of galaxies, especially two new catalogs we recently constructed that contain ≈1000 and ≈13 000 pairs, respectively. We are particularly interested by the dynamics of those pairs, including the determination of their masses. Methods: We could not compute the dynamical parameters directly since the necessary data are incomplete. Indeed, we only have at our disposal one component of the intervelocity between the members, namely along the line of sight, and two components of their interdistance, i.e., the projection on the sky-plane. Moreover, we know only one point of each galaxy orbit. Hence we need statistical methods to find the probability distribution of 3D interdistances and 3D intervelocities from their projections; we designed those methods under the term deprojection. Results: We proceed in two steps to determine and use the deprojection methods. First we derive the probability distributions expected for the various relevant projected quantities, namely intervelocity vz, interdistance rp, their ratio, and the product rp v_z^2, which is involved in mass determination. In a second step, we propose various methods of deprojection of those parameters based on the previous analysis. We start from a histogram of the projected data and we apply inversion formulae to obtain the deprojected distributions; lastly, we test the methods by numerical simulations, which also allow us to determine the uncertainties involved.

Effect of geometrical parameters on pressure distributions of impulse manufacturing technologies

NASA Astrophysics Data System (ADS)

Brune, Ryan Carl

Impulse manufacturing techniques constitute a growing field of methods that utilize high-intensity pressure events to conduct useful mechanical operations. As interest in applying this technology continues to grow, greater understanding must be achieved with respect to output pressure events in both magnitude and distribution. In order to address this need, a novel pressure measurement has been developed called the Profile Indentation Pressure Evaluation (PIPE) method that systematically analyzes indentation patterns created with impulse events. Correlation with quasi-static test data and use of software-assisted analysis techniques allows for colorized pressure maps to be generated for both electromagnetic and vaporizing foil actuator (VFA) impulse forming events. Development of this technique aided introduction of a design method for electromagnetic path actuator systems, where key geometrical variables are considered using a newly developed analysis method, which is called the Path Actuator Proximal Array (PAPA) pressure model. This model considers key current distribution and proximity effects and interprets generated pressure by considering the adjacent conductor surfaces as proximal arrays of individual conductors. According to PIPE output pressure analysis, the PAPA model provides a reliable prediction of generated pressure for path actuator systems as local geometry is changed. Associated mechanical calculations allow for pressure requirements to be calculated for shearing, flanging, and hemming operations, providing a design process for such cases. Additionally, geometry effect is investigated through a formability enhancement study using VFA metalworking techniques. A conical die assembly is utilized with both VFA high velocity and traditional quasi-static test methods on varied Hasek-type sample geometries to elicit strain states consistent with different locations on a forming limit diagram. Digital image correlation techniques are utilized to measure major and minor strains for each sample type to compare limit strain results. Overall testing indicated decreased formability at high velocity for 304 DDQ stainless steel and increased formability at high velocity for 3003-H14 aluminum. Microstructural and fractographic analysis helped dissect and analyze the observed differences in these cases. Overall, these studies comprehensively explore the effects of geometrical parameters on magnitude and distribution of impulse manufacturing generated pressure, establishing key guidelines and models for continued development and implementation in commercial applications.

Morphological analysis of red blood cells by polychromatic interference microscopy of thin films

NASA Astrophysics Data System (ADS)

Dyachenko, A. A.; Malinova, L. I.; Ryabukho, V. P.

2016-11-01

Red blood cells (RBC) distribution width (RDW) is a promising hematological parameter with broadapplications in clinical practice; in various studies RDWhas been shown to be associated with increased risk of heart failure (HF) in general population. It predicts mortality and other major adverse events in HF patients. In this report new method of RDWmeasurement is presented. It's based on interference color analysis of red blood cells in blood smear and further measurement of its optical thickness. Descriptive statistics of the of the RBC optical thickness distribution in a blood smear were used for RDW estimation in every studied sample. Proposed method is considered to be avoiding type II errors and minimizing the variability of measured RDW.

Distributional Cost-Effectiveness Analysis

PubMed Central

Asaria, Miqdad; Griffin, Susan; Cookson, Richard

2015-01-01

Distributional cost-effectiveness analysis (DCEA) is a framework for incorporating health inequality concerns into the economic evaluation of health sector interventions. In this tutorial, we describe the technical details of how to conduct DCEA, using an illustrative example comparing alternative ways of implementing the National Health Service (NHS) Bowel Cancer Screening Programme (BCSP). The 2 key stages in DCEA are 1) modeling social distributions of health associated with different interventions, and 2) evaluating social distributions of health with respect to the dual objectives of improving total population health and reducing unfair health inequality. As well as describing the technical methods used, we also identify the data requirements and the social value judgments that have to be made. Finally, we demonstrate the use of sensitivity analyses to explore the impacts of alternative modeling assumptions and social value judgments. PMID:25908564

Statistical Deconvolution for Superresolution Fluorescence Microscopy

PubMed Central

Mukamel, Eran A.; Babcock, Hazen; Zhuang, Xiaowei

2012-01-01

Superresolution microscopy techniques based on the sequential activation of fluorophores can achieve image resolution of ∼10 nm but require a sparse distribution of simultaneously activated fluorophores in the field of view. Image analysis procedures for this approach typically discard data from crowded molecules with overlapping images, wasting valuable image information that is only partly degraded by overlap. A data analysis method that exploits all available fluorescence data, regardless of overlap, could increase the number of molecules processed per frame and thereby accelerate superresolution imaging speed, enabling the study of fast, dynamic biological processes. Here, we present a computational method, referred to as deconvolution-STORM (deconSTORM), which uses iterative image deconvolution in place of single- or multiemitter localization to estimate the sample. DeconSTORM approximates the maximum likelihood sample estimate under a realistic statistical model of fluorescence microscopy movies comprising numerous frames. The model incorporates Poisson-distributed photon-detection noise, the sparse spatial distribution of activated fluorophores, and temporal correlations between consecutive movie frames arising from intermittent fluorophore activation. We first quantitatively validated this approach with simulated fluorescence data and showed that deconSTORM accurately estimates superresolution images even at high densities of activated fluorophores where analysis by single- or multiemitter localization methods fails. We then applied the method to experimental data of cellular structures and demonstrated that deconSTORM enables an approximately fivefold or greater increase in imaging speed by allowing a higher density of activated fluorophores/frame. PMID:22677393

Mathematical models and methods of assisting state subsidy distribution at the regional level

NASA Astrophysics Data System (ADS)

Bondarenko, Yu V.; Azarnova, T. V.; Kashirina, I. L.; Goroshko, I. V.

2018-03-01

One of the most common forms of state support in the world is subsidization. By providing direct financial support to businesses, local authorities get an opportunity to set certain performance targets. Successful achievement of such targets depends not only on the amount of the budgetary allocations, but also on the distribution mechanisms adopted by the regional authorities. Analysis of the existing mechanisms of subsidies distribution in Russian regions shows that in most cases the choice of subsidy calculation formula and its parameters depends on the experts’ subjective opinion. The authors offer a new approach to assisting subsidy distribution at the regional level, which is based on mathematical models and methods, allowing to evaluate the influence of subsidy distribution on the region’s social and economic development. The results of calculations were discussed with the regional administration representatives who confirmed their significance for decision-making in the sphere of state control.

Gis-Based Spatial Statistical Analysis of College Graduates Employment

NASA Astrophysics Data System (ADS)

Tang, R.

2012-07-01

It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

Application of Powder Diffraction Methods to the Analysis of Short- and Long-Range Atomic Order in Nanocrystalline Diamond and SiC: The Concept of the Apparent Lattice Parameter (alp)

NASA Technical Reports Server (NTRS)

Palosz, B.; Grzanka, E.; Gierlotka, S.; Stelmakh, S.; Pielaszek, R.; Bismayer, U.; Weber, H.-P.; Palosz, W.

2003-01-01

Two methods of the analysis of powder diffraction patterns of diamond and SiC nanocrystals are presented: (a) examination of changes of the lattice parameters with diffraction vector Q ('apparent lattice parameter', alp) which refers to Bragg scattering, and (b), examination of changes of inter-atomic distances based on the analysis of the atomic Pair Distribution Function, PDF. Application of these methods was studied based on the theoretical diffraction patterns computed for models of nanocrystals having (i) a perfect crystal lattice, and (ii), a core-shell structure, i.e. constituting a two-phase system. The models are defined by the lattice parameter of the grain core, thickness of the surface shell, and the magnitude and distribution of the strain field in the shell. X-ray and neutron experimental diffraction data of nanocrystalline SiC and diamond powders of the grain diameter from 4 nm up to micrometers were used. The effects of the internal pressure and strain at the grain surface on the structure are discussed based on the experimentally determined dependence of the alp values on the Q-vector, and changes of the interatomic distances with the grain size determined experimentally by the atomic Pair Distribution Function (PDF) analysis. The experimental results lend a strong support to the concept of a two-phase, core and the surface shell structure of nanocrystalline diamond and SiC.

Confounding adjustment in comparative effectiveness research conducted within distributed research networks.

PubMed

Toh, Sengwee; Gagne, Joshua J; Rassen, Jeremy A; Fireman, Bruce H; Kulldorff, Martin; Brown, Jeffrey S

2013-08-01

A distributed research network (DRN) of electronic health care databases, in which data reside behind the firewall of each data partner, can support a wide range of comparative effectiveness research (CER) activities. An essential component of a fully functional DRN is the capability to perform robust statistical analyses to produce valid, actionable evidence without compromising patient privacy, data security, or proprietary interests. We describe the strengths and limitations of different confounding adjustment approaches that can be considered in observational CER studies conducted within DRNs, and the theoretical and practical issues to consider when selecting among them in various study settings. Several methods can be used to adjust for multiple confounders simultaneously, either as individual covariates or as confounder summary scores (eg, propensity scores and disease risk scores), including: (1) centralized analysis of patient-level data, (2) case-centered logistic regression of risk set data, (3) stratified or matched analysis of aggregated data, (4) distributed regression analysis, and (5) meta-analysis of site-specific effect estimates. These methods require different granularities of information be shared across sites and afford investigators different levels of analytic flexibility. DRNs are growing in use and sharing of highly detailed patient-level information is not always feasible in DRNs. Methods that incorporate confounder summary scores allow investigators to adjust for a large number of confounding factors without the need to transfer potentially identifiable information in DRNs. They have the potential to let investigators perform many analyses traditionally conducted through a centralized dataset with detailed patient-level information.

EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data.

PubMed

Wijetunge, Chalini D; Saeed, Isaam; Boughton, Berin A; Spraggins, Jeffrey M; Caprioli, Richard M; Bacic, Antony; Roessner, Ute; Halgamuge, Saman K

2015-10-01

Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in 'omics' data acquisition generates detailed information about the spatial distribution of molecules in a given biological sample. Various data processing methods have been developed for exploring the resultant high volume data. However, most of these methods process data in the spectral domain and do not make the most of the important spatial information available through this technology. Therefore, we propose a novel streamlined data analysis pipeline specifically developed for MALDI-IMS data utilizing significant spatial information for identifying hidden significant molecular distribution patterns in these complex datasets. The proposed unsupervised algorithm uses Sliding Window Normalization (SWN) and a new spatial distribution based peak picking method developed based on Gray level Co-Occurrence (GCO) matrices followed by clustering of biomolecules. We also use gist descriptors and an improved version of GCO matrices to extract features from molecular images and minimum medoid distance to automatically estimate the number of possible groups. We evaluated our algorithm using a new MALDI-IMS metabolomics dataset of a plant (Eucalypt) leaf. The algorithm revealed hidden significant molecular distribution patterns in the dataset, which the current Component Analysis and Segmentation Map based approaches failed to extract. We further demonstrate the performance of our peak picking method over other traditional approaches by using a publicly available MALDI-IMS proteomics dataset of a rat brain. Although SWN did not show any significant improvement as compared with using no normalization, the visual assessment showed an improvement as compared to using the median normalization. The source code and sample data are freely available at http://exims.sourceforge.net/. awgcdw@student.unimelb.edu.au or chalini_w@live.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Uniform Sampling Table Method and its Applications II--Evaluating the Uniform Sampling by Experiment.

PubMed

Chen, Yibin; Chen, Jiaxi; Chen, Xuan; Wang, Min; Wang, Wei

2015-01-01

A new method of uniform sampling is evaluated in this paper. The items and indexes were adopted to evaluate the rationality of the uniform sampling. The evaluation items included convenience of operation, uniformity of sampling site distribution, and accuracy and precision of measured results. The evaluation indexes included operational complexity, occupation rate of sampling site in a row and column, relative accuracy of pill weight, and relative deviation of pill weight. They were obtained from three kinds of drugs with different shape and size by four kinds of sampling methods. Gray correlation analysis was adopted to make the comprehensive evaluation by comparing it with the standard method. The experimental results showed that the convenience of uniform sampling method was 1 (100%), odds ratio of occupation rate in a row and column was infinity, relative accuracy was 99.50-99.89%, reproducibility RSD was 0.45-0.89%, and weighted incidence degree exceeded the standard method. Hence, the uniform sampling method was easy to operate, and the selected samples were distributed uniformly. The experimental results demonstrated that the uniform sampling method has good accuracy and reproducibility, which can be put into use in drugs analysis.

A random effects meta-analysis model with Box-Cox transformation.

PubMed

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The random effects meta-analysis with the Box-Cox transformation may be an important tool for examining robustness of traditional meta-analysis results against skewness on the observed treatment effect estimates. Further critical evaluation of the method is needed.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

PubMed

Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Resolution-Enhanced Harmonic and Interharmonic Measurement for Power Quality Analysis in Cyber-Physical Energy System.

PubMed

Liu, Yanchi; Wang, Xue; Liu, Youda; Cui, Sujin

2016-06-27

Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system.

Resolution-Enhanced Harmonic and Interharmonic Measurement for Power Quality Analysis in Cyber-Physical Energy System

PubMed Central

Liu, Yanchi; Wang, Xue; Liu, Youda; Cui, Sujin

2016-01-01

Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system. PMID:27355946

A Disciplined Architectural Approach to Scaling Data Analysis for Massive, Scientific Data

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Braverman, A. J.; Cinquini, L.; Turmon, M.; Lee, H.; Law, E.

2014-12-01

Data collections across remote sensing and ground-based instruments in astronomy, Earth science, and planetary science are outpacing scientists' ability to analyze them. Furthermore, the distribution, structure, and heterogeneity of the measurements themselves pose challenges that limit the scalability of data analysis using traditional approaches. Methods for developing science data processing pipelines, distribution of scientific datasets, and performing analysis will require innovative approaches that integrate cyber-infrastructure, algorithms, and data into more systematic approaches that can more efficiently compute and reduce data, particularly distributed data. This requires the integration of computer science, machine learning, statistics and domain expertise to identify scalable architectures for data analysis. The size of data returned from Earth Science observing satellites and the magnitude of data from climate model output, is predicted to grow into the tens of petabytes challenging current data analysis paradigms. This same kind of growth is present in astronomy and planetary science data. One of the major challenges in data science and related disciplines defining new approaches to scaling systems and analysis in order to increase scientific productivity and yield. Specific needs include: 1) identification of optimized system architectures for analyzing massive, distributed data sets; 2) algorithms for systematic analysis of massive data sets in distributed environments; and 3) the development of software infrastructures that are capable of performing massive, distributed data analysis across a comprehensive data science framework. NASA/JPL has begun an initiative in data science to address these challenges. Our goal is to evaluate how scientific productivity can be improved through optimized architectural topologies that identify how to deploy and manage the access, distribution, computation, and reduction of massive, distributed data, while managing the uncertainties of scientific conclusions derived from such capabilities. This talk will provide an overview of JPL's efforts in developing a comprehensive architectural approach to data science.

Studying aerosol light scattering based on aspect ratio distribution observed by fluorescence microscope.

PubMed

Li, Li; Zheng, Xu; Li, Zhengqiang; Li, Zhanhua; Dubovik, Oleg; Chen, Xingfeng; Wendisch, Manfred

2017-08-07

Particle shape is crucial to the properties of light scattered by atmospheric aerosol particles. A method of fluorescence microscopy direct observation was introduced to determine the aspect ratio distribution of aerosol particles. The result is comparable with that of the electron microscopic analysis. The measured aspect ratio distribution has been successfully applied in modeling light scattering and further in simulation of polarization measurements of the sun/sky radiometer. These efforts are expected to improve shape retrieval from skylight polarization by using directly measured aspect ratio distribution.

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Optimal Output of Distributed Generation Based On Complex Power Increment

NASA Astrophysics Data System (ADS)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Prediction of the Electromagnetic Field Distribution in a Typical Aircraft Using the Statistical Energy Analysis

NASA Astrophysics Data System (ADS)

Kovalevsky, Louis; Langley, Robin S.; Caro, Stephane

2016-05-01

Due to the high cost of experimental EMI measurements significant attention has been focused on numerical simulation. Classical methods such as Method of Moment or Finite Difference Time Domain are not well suited for this type of problem, as they require a fine discretisation of space and failed to take into account uncertainties. In this paper, the authors show that the Statistical Energy Analysis is well suited for this type of application. The SEA is a statistical approach employed to solve high frequency problems of electromagnetically reverberant cavities at a reduced computational cost. The key aspects of this approach are (i) to consider an ensemble of system that share the same gross parameter, and (ii) to avoid solving Maxwell's equations inside the cavity, using the power balance principle. The output is an estimate of the field magnitude distribution in each cavity. The method is applied on a typical aircraft structure.

Analysis of possible designs of processing units with radial plasma flows

NASA Astrophysics Data System (ADS)

Kolesnik, V. V.; Zaitsev, S. V.; Vashilin, V. S.; Limarenko, M. V.; Prochorenkov, D. S.

2018-03-01

Analysis of plasma-ion methods of obtaining thin-film coatings shows that their development goes along the path of the increasing use of sputter deposition processes, which allow one to obtain multicomponent coatings with varying percentage of particular components. One of the methods that allow one to form multicomponent coatings with virtually any composition of elementary components is the method of coating deposition using quasi-magnetron sputtering systems [1]. This requires the creation of an axial magnetic field of a defined configuration with the flux density within the range of 0.01-0.1 T [2]. In order to compare and analyze various configurations of processing unit magnetic systems, it is necessary to obtain the following dependencies: the dependency of magnetic core section on the input power to inductors, the distribution of magnetic induction within the equatorial plane in the corresponding sections, the distribution of the magnetic induction value in the area of cathode target location.

Study and Application on Cloud Covered Rate for Agroclimatical Distribution Using In Guangxi Based on Modis Data

NASA Astrophysics Data System (ADS)

Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua

Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.

Phenytoin crystal growth rates in the presence of phosphate and chloride ions

NASA Astrophysics Data System (ADS)

Zipp, G. L.; Rodríguez-Hornedo, N.

1992-09-01

Phenytoin crystal growth kinetics have been measured as a function of supersaturation in pH 2.2 phosphoric acid and pH 2.2 hydrochloric acid solutions. Two different methods were used for the kinetic analysis. The first involved a zone-sensing device which provided an analysis of the distribution of crystals in a batch crystallizer. Crystal growth rates were calculated from the increase in the size of the distribution with time. In the second method, growth rates were evaluated from the change in size with time of individual crystals observed under an inverted microscope. The results from each method compare favorably. The use of both techniques provides an excellent opportunity to exploit the strengths of each: an average growth rate from a population of crystals from batch crystallization and insight into the effect of growth on the morphology of the crystals from the individual crystal measurements.

Analysis methods and recent advances in nonlinear pharmacokinetics from in vitro through in loci to in vivo.

PubMed

Yamaoka, Kiyoshi; Takakura, Yoshinobu

2004-12-01

An attempt has been made to review the nonlinearities in the disposition in vitro, in situ, in loci and in vivo mainly from a theoretical point of view. Parallel Michaelis-Menten and linear (first-order) eliminations are often observed in the cellular uptake, metabolism and efflux of drugs. The well-stirred and parallel-tube models are mainly adopted under steady-state conditions in perfusion experiments, whereas distribution, tank-in-series and dispersion models are often used under nonsteady-state conditions with a pulse input. The analysis of the nonlinear local disposition in loci is reviewed from two points of view, namely an indirect method involving physiologically based pharmacokinetics (PBPK) and a direct (two or three samplings) method using live animals. The nonlinear global pharmacokinetics in vivo is reviewed with regard to absorption, elimination (metabolism and excretion) and distribution.

MAPPING THE GALAXY COLOR–REDSHIFT RELATION: OPTIMAL PHOTOMETRIC REDSHIFT CALIBRATION STRATEGIES FOR COSMOLOGY SURVEYS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masters, Daniel; Steinhardt, Charles; Faisst, Andreas

2015-11-01

Calibrating the photometric redshifts of ≳10{sup 9} galaxies for upcoming weak lensing cosmology experiments is a major challenge for the astrophysics community. The path to obtaining the required spectroscopic redshifts for training and calibration is daunting, given the anticipated depths of the surveys and the difficulty in obtaining secure redshifts for some faint galaxy populations. Here we present an analysis of the problem based on the self-organizing map, a method of mapping the distribution of data in a high-dimensional space and projecting it onto a lower-dimensional representation. We apply this method to existing photometric data from the COSMOS survey selectedmore » to approximate the anticipated Euclid weak lensing sample, enabling us to robustly map the empirical distribution of galaxies in the multidimensional color space defined by the expected Euclid filters. Mapping this multicolor distribution lets us determine where—in galaxy color space—redshifts from current spectroscopic surveys exist and where they are systematically missing. Crucially, the method lets us determine whether a spectroscopic training sample is representative of the full photometric space occupied by the galaxies in a survey. We explore optimal sampling techniques and estimate the additional spectroscopy needed to map out the color–redshift relation, finding that sampling the galaxy distribution in color space in a systematic way can efficiently meet the calibration requirements. While the analysis presented here focuses on the Euclid survey, similar analysis can be applied to other surveys facing the same calibration challenge, such as DES, LSST, and WFIRST.« less

COMPARISON OF LARGE RIVER SAMPLING METHOD USING DIATOM METRICS

EPA Science Inventory

We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...

COMPARISON OF LARGE RIVER SAMPLING METHODS ON ALGAL METRICS

EPA Science Inventory

We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...

Aerodynamic design of turbomachinery blading in three-dimensional flow - An application to radial inflow turbines

NASA Technical Reports Server (NTRS)

Yang, Y. L.; Tan, C. S.; Hawthorne, W. R.

1992-01-01

A computational method, based on a theory for turbomachinery blading design in three-dimensional inviscid flow, is applied to a parametric design study of a radial inflow turbine wheel. As the method requires the specification of swirl distribution, a technique for its smooth generation within the blade region is proposed. Excellent agreements have been obtained between the computed results from this design method and those from direct Euler computations, demonstrating the correspondence and consistency between the two. The computed results indicate the sensitivity of the pressure distribution to a lean in the stacking axis and a minor alteration in the hub/shroud profiles. Analysis based on Navier-Stokes solver shows no breakdown of flow within the designed blade passage and agreement with that from design calculation; thus the flow in the designed turbine rotor closely approximates that of an inviscid one. These calculations illustrate the use of a design method coupled to an analysis tool for establishing guidelines and criteria for designing turbomachinery blading.

Multifractality of stock markets based on cumulative distribution function and multiscale multifractal analysis

NASA Astrophysics Data System (ADS)

Lin, Aijing; Shang, Pengjian

2016-04-01

Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.

Is Earnings Uncertainty Relevant for Educational Choice? An Empirical Analysis for China

ERIC Educational Resources Information Center

Hartog, Joop; Ding, Xiaohao; Liao, Juan

2014-01-01

We use the method of Dominitz and Manski [1996. Eliciting student expectations of the return to schooling. "Journal of Human Resources" 31, no. 1: 1-26] to solicit anticipated wage distributions for continuing to a master degree or going to work after completing the bachelor degree. The means of the distributions have an effect on…

The planetary distribution of heat sources and sinks during FGGE

NASA Technical Reports Server (NTRS)

Johnson, D. R.; Wei, M. Y.

1985-01-01

Heating distributions from analysis of the National Meteorological Center and European Center for Medium Range Weather Forecasts data sets; methods used and problems involved in the inference of diabatic heating; the relationship between differential heating and energy transport; and recommendations on the inference of heat soruces and heat sinks for the planetary show are discussed.

Efficient and robust method for simultaneous reconstruction of the temperature distribution and radiative properties in absorbing, emitting, and scattering media

NASA Astrophysics Data System (ADS)

Niu, Chun-Yang; Qi, Hong; Huang, Xing; Ruan, Li-Ming; Tan, He-Ping

2016-11-01

A rapid computational method called generalized sourced multi-flux method (GSMFM) was developed to simulate outgoing radiative intensities in arbitrary directions at the boundary surfaces of absorbing, emitting, and scattering media which were served as input for the inverse analysis. A hybrid least-square QR decomposition-stochastic particle swarm optimization (LSQR-SPSO) algorithm based on the forward GSMFM solution was developed to simultaneously reconstruct multi-dimensional temperature distribution and absorption and scattering coefficients of the cylindrical participating media. The retrieval results for axisymmetric temperature distribution and non-axisymmetric temperature distribution indicated that the temperature distribution and scattering and absorption coefficients could be retrieved accurately using the LSQR-SPSO algorithm even with noisy data. Moreover, the influences of extinction coefficient and scattering albedo on the accuracy of the estimation were investigated, and the results suggested that the reconstruction accuracy decreased with the increase of extinction coefficient and the scattering albedo. Finally, a non-contact measurement platform of flame temperature field based on the light field imaging was set up to validate the reconstruction model experimentally.

Deterministic analysis of extrinsic and intrinsic noise in an epidemiological model.

PubMed

Bayati, Basil S

2016-05-01

We couple a stochastic collocation method with an analytical expansion of the canonical epidemiological master equation to analyze the effects of both extrinsic and intrinsic noise. It is shown that depending on the distribution of the extrinsic noise, the master equation yields quantitatively different results compared to using the expectation of the distribution for the stochastic parameter. This difference is incident to the nonlinear terms in the master equation, and we show that the deviation away from the expectation of the extrinsic noise scales nonlinearly with the variance of the distribution. The method presented here converges linearly with respect to the number of particles in the system and exponentially with respect to the order of the polynomials used in the stochastic collocation calculation. This makes the method presented here more accurate than standard Monte Carlo methods, which suffer from slow, nonmonotonic convergence. In epidemiological terms, the results show that extrinsic fluctuations should be taken into account since they effect the speed of disease breakouts and that the gamma distribution should be used to model the basic reproductive number.

A Nonlinear Framework of Delayed Particle Smoothing Method for Vehicle Localization under Non-Gaussian Environment.

PubMed

Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-05-13

In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student's t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Generalisation of the identity method for determination of high-order moments of multiplicity distributions with a software implementation

NASA Astrophysics Data System (ADS)

Maćkowiak-Pawłowska, Maja; Przybyła, Piotr

2018-05-01

The incomplete particle identification limits the experimentally-available phase space region for identified particle analysis. This problem affects ongoing fluctuation and correlation studies including the search for the critical point of strongly interacting matter performed on SPS and RHIC accelerators. In this paper we provide a procedure to obtain nth order moments of the multiplicity distribution using the identity method, generalising previously published solutions for n=2 and n=3. Moreover, we present an open source software implementation of this computation, called Idhim, that allows one to obtain the true moments of identified particle multiplicity distributions from the measured ones provided the response function of the detector is known.

Comparative analysis through probability distributions of a data set

NASA Astrophysics Data System (ADS)

Cristea, Gabriel; Constantinescu, Dan Mihai

2018-02-01

In practice, probability distributions are applied in such diverse fields as risk analysis, reliability engineering, chemical engineering, hydrology, image processing, physics, market research, business and economic research, customer support, medicine, sociology, demography etc. This article highlights important aspects of fitting probability distributions to data and applying the analysis results to make informed decisions. There are a number of statistical methods available which can help us to select the best fitting model. Some of the graphs display both input data and fitted distributions at the same time, as probability density and cumulative distribution. The goodness of fit tests can be used to determine whether a certain distribution is a good fit. The main used idea is to measure the "distance" between the data and the tested distribution, and compare that distance to some threshold values. Calculating the goodness of fit statistics also enables us to order the fitted distributions accordingly to how good they fit to data. This particular feature is very helpful for comparing the fitted models. The paper presents a comparison of most commonly used goodness of fit tests as: Kolmogorov-Smirnov, Anderson-Darling, and Chi-Squared. A large set of data is analyzed and conclusions are drawn by visualizing the data, comparing multiple fitted distributions and selecting the best model. These graphs should be viewed as an addition to the goodness of fit tests.

Strain, curvature, and twist measurements in digital holographic interferometry using pseudo-Wigner-Ville distribution based method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rajshekhar, G.; Gorthi, Sai Siva; Rastogi, Pramod

2009-09-15

Measurement of strain, curvature, and twist of a deformed object play an important role in deformation analysis. Strain depends on the first order displacement derivative, whereas curvature and twist are determined by second order displacement derivatives. This paper proposes a pseudo-Wigner-Ville distribution based method for measurement of strain, curvature, and twist in digital holographic interferometry where the object deformation or displacement is encoded as interference phase. In the proposed method, the phase derivative is estimated by peak detection of pseudo-Wigner-Ville distribution evaluated along each row/column of the reconstructed interference field. A complex exponential signal with unit amplitude and the phasemore » derivative estimate as the argument is then generated and the pseudo-Wigner-Ville distribution along each row/column of this signal is evaluated. The curvature is estimated by using peak tracking strategy for the new distribution. For estimation of twist, the pseudo-Wigner-Ville distribution is evaluated along each column/row (i.e., in alternate direction with respect to the previous one) for the generated complex exponential signal and the corresponding peak detection gives the twist estimate.« less

A novel method for the investigation of liquid/liquid distribution coefficients and interface permeabilities applied to the water-octanol-drug system.

PubMed

Stein, Paul C; di Cagno, Massimiliano; Bauer-Brandl, Annette

2011-09-01

In this work a new, accurate and convenient technique for the measurement of distribution coefficients and membrane permeabilities based on nuclear magnetic resonance (NMR) is described. This method is a novel implementation of localized NMR spectroscopy and enables the simultaneous analysis of the drug content in the octanol and in the water phase without separation. For validation of the method, the distribution coefficients at pH = 7.4 of four active pharmaceutical ingredients (APIs), namely ibuprofen, ketoprofen, nadolol, and paracetamol (acetaminophen), were determined using a classical approach. These results were compared to the NMR experiments which are described in this work. For all substances, the respective distribution coefficients found with the two techniques coincided very well. Furthermore, the NMR experiments make it possible to follow the distribution of the drug between the phases as a function of position and time. Our results show that the technique, which is available on any modern NMR spectrometer, is well suited to the measurement of distribution coefficients. The experiments present also new insight into the dynamics of the water-octanol interface itself and permit measurement of the interface permeability.

Spatial accessibility of the population to urban health centres in Kermanshah, Islamic Republic of Iran: a geographic information systems analysis.

PubMed

Reshadat, S; Saedi, S; Zangeneh, A; Ghasemi, S R; Gilan, N R; Karbasi, A; Bavandpoor, E

2015-09-08

Geographic information systems (GIS) analysis has not been widely used in underdeveloped countries to ensure that vulnerable populations have accessibility to primary health-care services. This study applied GIS methods to analyse the spatial accessibility to urban primary-care centres of the population in Kermanshah city, Islamic Republic of Iran, by age and sex groups. In a descriptive-analytical study over 3 time periods, network analysis, mean centre and standard distance methods were applied using ArcGIS 9.3. The analysis was based on a standard radius of 750 m distance from health centres, walking speed of 1 m/s and desired access time to health centres of 12.5 mins. The proportion of the population with inadequate geographical access to health centres rose from 47.3% in 1997 to 58.4% in 2012. The mean centre and standard distance mapping showed that the spatial distribution of health centres in Kermanshah needed to be adjusted to changes in population distribution.

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

DOE PAGES

Di Mauro, M.; Manconi, S.; Zechlin, H. -S.; ...

2018-03-29

Here, the Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (more » $$|b| \\gt 20^\\circ $$), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10 –12 ph cm –2 s –1. With this method, we detect a flux break at (3.5 ± 0.4) × 10 –11 ph cm –2 s –1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ~10 –11 ph cm –2 s –1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.« less

Deriving the Contribution of Blazars to the Fermi-LAT Extragalactic γ-ray Background at E > 10 GeV with Efficiency Corrections and Photon Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Mauro, M.; Manconi, S.; Zechlin, H. -S.

Here, the Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. Building upon the 3FHL results, we investigate the flux distribution of sources at high Galactic latitudes (more » $$|b| \\gt 20^\\circ $$), which are mostly blazars. We use two complementary techniques: (1) a source-detection efficiency correction method and (2) an analysis of pixel photon count statistics with the one-point probability distribution function (1pPDF). With the first method, using realistic Monte Carlo simulations of the γ-ray sky, we calculate the efficiency of the LAT to detect point sources. This enables us to find the intrinsic source-count distribution at photon fluxes down to 7.5 × 10 –12 ph cm –2 s –1. With this method, we detect a flux break at (3.5 ± 0.4) × 10 –11 ph cm –2 s –1 with a significance of at least 5.4σ. The power-law indexes of the source-count distribution above and below the break are 2.09 ± 0.04 and 1.07 ± 0.27, respectively. This result is confirmed with the 1pPDF method, which has a sensitivity reach of ~10 –11 ph cm –2 s –1. Integrating the derived source-count distribution above the sensitivity of our analysis, we find that (42 ± 8)% of the extragalactic γ-ray background originates from blazars.« less

Analysis to Inform CA Grid Integration Rules for PV: Final Report on Inverter Settings for Transmission and Distribution System Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Jeff; Rylander, Matthew; Boemer, Jens

The fourth solicitation of the California Solar Initiative (CSI) Research, Development, Demonstration and Deployment (RD&D) Program established by the California Public Utilities Commission (CPUC) supported the Electric Power Research Institute (EPRI), National Renewable Energy Laboratory (NREL), and Sandia National Laboratories (SNL) with data provided from Pacific Gas and Electric (PG&E), Southern California Edison (SCE), and San Diego Gas and Electric (SDG&E) conducted research to determine optimal default settings for distributed energy resource advanced inverter controls. The inverter functions studied are aligned with those developed by the California Smart Inverter Working Group (SIWG) and those being considered by the IEEE 1547more » Working Group. The advanced inverter controls examined to improve the distribution system response included power factor, volt-var, and volt-watt. The advanced inverter controls examined to improve the transmission system response included frequency and voltage ride-through as well as Dynamic Voltage Support. This CSI RD&D project accomplished the task of developing methods to derive distribution focused advanced inverter control settings, selecting a diverse set of feeders to evaluate the methods through detailed analysis, and evaluating the effectiveness of each method developed. Inverter settings focused on the transmission system performance were also evaluated and verified. Based on the findings of this work, the suggested advanced inverter settings and methods to determine settings can be used to improve the accommodation of distributed energy resources (PV specifically). The voltage impact from PV can be mitigated using power factor, volt-var, or volt-watt control, while the bulk system impact can be improved with frequency/voltage ride-through.« less

A distribution method for analysing the baseline of pulsatile endocrine signals as exemplified by 24-hour growth hormone profiles.

PubMed

Matthews, D R; Hindmarsh, P C; Pringle, P J; Brook, C G

1991-09-01

To develop a method for quantifying the distribution of concentrations present in hormone profiles, which would allow an observer-unbiased estimate of the time concentration attribute and to make an assessment of the baseline. The log-transformed concentrations (regardless of their temporal attribute) are sorted and allocated to class intervals. The number of observations in each interval are then determined and expressed as a percentage of the total number of samples drawn in the study period. The data may be displayed as a frequency distribution or as a cumulative distribution. Cumulative distributions may be plotted as sigmoidal ogives or can be transformed into discrete probabilities (linear probits), which are then linear, and amenable to regression analysis. Probability analysis gives estimates of the mean (the value below which 50% of the observed concentrations lie, which we term 'OC50'). 'Baseline' can be defined in terms of percentage occupancy--the 'Observed Concentration for 5%' (which we term 'OC5') which is the threshold at or below which the hormone concentrations are measured 5% of the time. We report the use of applying this method to 24-hour growth hormone (GH) profiles from 63 children, 26 adults and one giant. We demonstrate that GH effects (growth or gigantism) in these groups are more related to the baseline OC5 concentration than peak concentration (OC5 +/- 95% confidence limits: adults 0.05 +/- 0.04, peak-height-velocity pubertal 0.39 +/- 0.22, giant 8.9 mU/l). Pulsatile hormone profiles can be analysed using this method in order to assess baseline and other concentration domains.

Observed oil and gas field size distributions: A consequence of the discovery process and prices of oil and gas

USGS Publications Warehouse

Drew, L.J.; Attanasi, E.D.; Schuenemeyer, J.H.

1988-01-01

If observed oil and gas field size distributions are obtained by random samplings, the fitted distributions should approximate that of the parent population of oil and gas fields. However, empirical evidence strongly suggests that larger fields tend to be discovered earlier in the discovery process than they would be by random sampling. Economic factors also can limit the number of small fields that are developed and reported. This paper examines observed size distributions in state and federal waters of offshore Texas. Results of the analysis demonstrate how the shape of the observable size distributions change with significant hydrocarbon price changes. Comparison of state and federal observed size distributions in the offshore area shows how production cost differences also affect the shape of the observed size distribution. Methods for modifying the discovery rate estimation procedures when economic factors significantly affect the discovery sequence are presented. A primary conclusion of the analysis is that, because hydrocarbon price changes can significantly affect the observed discovery size distribution, one should not be confident about inferring the form and specific parameters of the parent field size distribution from the observed distributions. ?? 1988 International Association for Mathematical Geology.

Volcanoes Distribution in Linear Segmentation of Mariana Arc

NASA Astrophysics Data System (ADS)

Andikagumi, H.; Macpherson, C.; McCaffrey, K. J. W.

2016-12-01

A new method has been developed to describe better volcanoes distribution pattern within Mariana Arc. A previous study assumed the distribution of volcanoes in the Mariana Arc is described by a small circle distribution which reflects the melting processes in a curved subduction zone. The small circle fit to this dataset used in the study, comprised 12 -mainly subaerial- volcanoes from Smithsonian Institute Global Volcanism Program, was reassessed by us to have a root-mean-square misfit of 2.5 km. The same method applied to a more complete dataset from Baker et al. (2008), consisting 37 subaerial and submarine volcanoes, resulted in an 8.4 km misfit. However, using the Hough Transform method on the larger dataset, lower misfits of great circle segments were achieved (3.1 and 3.0 km) for two possible segments combination. The results indicate that the distribution of volcanoes in the Mariana Arc is better described by a great circle pattern, instead of small circle. Variogram and cross-variogram analysis on volcano spacing and volume shows that there is spatial correlation between volcanoes between 420 and 500 km which corresponds to the maximum segmentation lengths from Hough Transform (320 km). Further analysis of volcano spacing by the coefficient of variation (Cv), shows a tendency toward not-random distribution as the Cv values are closer to zero than one. These distributions are inferred to be associated with the development of normal faults at the back arc as their Cv values also tend towards zero. To analyse whether volcano spacing is random or not, Cv values were simulated using a Monte Carlo method with random input. Only the southernmost segment has allowed us to reject the null hypothesis that volcanoes are randomly spaced at 95% confidence level by 0.007 estimated probability. This result shows infrequent regularity in volcano spacing by chance so that controlling factor in lithospheric scale should be analysed with different approach (not from random number generator). Sunda Arc which has been studied to have en enchelon segmentation and larger number of volcanoes will be further studied to understand particular upper plate influence in volcanoes distribution.

Analysis of multi lobe journal bearings with surface roughness using finite difference method

NASA Astrophysics Data System (ADS)

PhaniRaja Kumar, K.; Bhaskar, SUdaya; Manzoor Hussain, M.

2018-04-01

Multi lobe journal bearings are used for high operating speeds and high loads in machines. In this paper symmetrical multi lobe journal bearings are analyzed to find out the effect of surface roughnessduring non linear loading. Using the fourth order RungeKutta method, time transient analysis was performed to calculate and plot the journal centre trajectories. Flow factor method is used to evaluate the roughness and the finite difference method (FDM) is used to predict the pressure distribution over the bearing surface. The Transient analysis is done on the multi lobe journal bearings for threedifferent surface roughness orientations. Longitudinal surface roughness is more effective when compared with isotopic and traverse surface roughness.

Bose-Einstein distribution of money in a free-market economy. II

NASA Astrophysics Data System (ADS)

Kürten, K. E.; Kusmartsev, F. V.

2011-01-01

We argue about the application of methods of statistical mechanics to free economy (Kusmartsev F. V., Phys. Lett. A, 375 (2011) 966) and find that the most general distribution of money or income in a free-market economy has a general Bose-Einstein distribution form. Therewith the market is described by three parameters: temperature, chemical potential and the space dimensionality. Numerical simulations and a detailed analysis of a generic model confirm this finding.

Multiscale power analysis for heart rate variability

NASA Astrophysics Data System (ADS)

Zeng, Peng; Liu, Hongxing; Ni, Huangjing; Zhou, Jing; Xia, Lan; Ning, Xinbao

2015-06-01

We first introduce multiscale power (MSP) method to assess the power distribution of physiological signals on multiple time scales. Simulation on synthetic data and experiments on heart rate variability (HRV) are tested to support the approach. Results show that both physical and psychological changes influence power distribution significantly. A quantitative parameter, termed power difference (PD), is introduced to evaluate the degree of power distribution alteration. We find that dynamical correlation of HRV will be destroyed completely when PD>0.7.

Velocity distributions on two-dimensional wing-duct inlets by conformal mapping

NASA Technical Reports Server (NTRS)

Perl, W; Moses, H E

1948-01-01

The conformal-mapping method of the Cartesian mapping function is applied to the determination of the velocity distribution on arbitrary two-dimensional duct-inlet shapes such as are used in wing installations. An idealized form of the actual wing-duct inlet is analyzed. The effects of leading edge stagger, inlet-velocity ratio, and section lift coefficients on the velocity distribution are included in the analysis. Numerical examples are given and, in part, compared with experimental data.

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

Distributed support vector machine in master-slave mode.

PubMed

Chen, Qingguo; Cao, Feilong

2018-05-01

It is well known that the support vector machine (SVM) is an effective learning algorithm. The alternating direction method of multipliers (ADMM) algorithm has emerged as a powerful technique for solving distributed optimisation models. This paper proposes a distributed SVM algorithm in a master-slave mode (MS-DSVM), which integrates a distributed SVM and ADMM acting in a master-slave configuration where the master node and slave nodes are connected, meaning the results can be broadcasted. The distributed SVM is regarded as a regularised optimisation problem and modelled as a series of convex optimisation sub-problems that are solved by ADMM. Additionally, the over-relaxation technique is utilised to accelerate the convergence rate of the proposed MS-DSVM. Our theoretical analysis demonstrates that the proposed MS-DSVM has linear convergence, meaning it possesses the fastest convergence rate among existing standard distributed ADMM algorithms. Numerical examples demonstrate that the convergence and accuracy of the proposed MS-DSVM are superior to those of existing methods under the ADMM framework. Copyright © 2018 Elsevier Ltd. All rights reserved.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Time series behaviour of the number of Air Asia passengers: A distributional approach

NASA Astrophysics Data System (ADS)

Asrah, Norhaidah Mohd; Djauhari, Maman Abdurachman

2013-09-01

The common practice to time series analysis is by fitting a model and then further analysis is conducted on the residuals. However, if we know the distributional behavior of time series, the analyses in model identification, parameter estimation, and model checking are more straightforward. In this paper, we show that the number of Air Asia passengers can be represented as a geometric Brownian motion process. Therefore, instead of using the standard approach in model fitting, we use an appropriate transformation to come up with a stationary, normally distributed and even independent time series. An example in forecasting the number of Air Asia passengers will be given to illustrate the advantages of the method.

Numerical Uncertainty Analysis for Computational Fluid Dynamics using Student T Distribution -- Application of CFD Uncertainty Analysis Compared to Exact Analytical Solution

NASA Technical Reports Server (NTRS)

Groves, Curtis E.; Ilie, marcel; Shallhorn, Paul A.

2014-01-01

Computational Fluid Dynamics (CFD) is the standard numerical tool used by Fluid Dynamists to estimate solutions to many problems in academia, government, and industry. CFD is known to have errors and uncertainties and there is no universally adopted method to estimate such quantities. This paper describes an approach to estimate CFD uncertainties strictly numerically using inputs and the Student-T distribution. The approach is compared to an exact analytical solution of fully developed, laminar flow between infinite, stationary plates. It is shown that treating all CFD input parameters as oscillatory uncertainty terms coupled with the Student-T distribution can encompass the exact solution.

Large scale intercomparison of aerosol trace element analysis by different analytical methods

NASA Astrophysics Data System (ADS)

Bombelka, E.; Richter, F.-W.; Ries, H.; Wätjen, U.

1984-04-01

The general agreement of PIXE analysis with other methods (INAA, XRF, AAS, OES-ICP, and PhAA) is very good based on the analysis of filter pieces taken from 250 aerosol samples. It is better than 5% for Pb and Zn, better than 10% for V, Cr, and Mn, indicating that the accuracy of PIXE analysis can be within 10%. For elements such as Cd and Sb, difficult to analyze by PIXE because of their low mass content in the sample, the agreement is given mainly by the reproducibility of the method (20% to 30%). Similar agreement is found for sulfur, after taking account of the depth distribution of the aerosol in the filter.

Mixed-Fidelity Approach for Design of Low-Boom Supersonic Aircraft

NASA Technical Reports Server (NTRS)

Li, Wu; Shields, Elwood; Geiselhart, Karl

2011-01-01

This paper documents a mixed-fidelity approach for the design of low-boom supersonic aircraft with a focus on fuselage shaping.A low-boom configuration that is based on low-fidelity analysis is used as the baseline. The fuselage shape is modified iteratively to obtain a configuration with an equivalent-area distribution derived from computational fluid dynamics analysis that attempts to match a predetermined low-boom target area distribution and also yields a low-boom ground signature. The ground signature of the final configuration is calculated by using a state-of-the-art computational-fluid-dynamics-based boom analysis method that generates accurate midfield pressure distributions for propagation to the ground with ray tracing. The ground signature that is propagated from a midfield pressure distribution has a shaped ramp front, which is similar to the ground signature that is propagated from the computational fluid dynamics equivalent-area distribution. This result supports the validity of low-boom supersonic configuration design by matching a low-boom equivalent-area target, which is easier to accomplish than matching a low-boom midfield pressure target.

Finite Element Analysis of the Endodontically-treated Maxillary Premolars restored with Composite Resin along with Glass Fiber Insertion in Various Positions.

PubMed

Navimipour, Elmira Jafari; Firouzmandi, Maryam; Mirhashemi, Fatemeh Sadat

2015-04-01

This study evaluated the effect of three methods of glass fiber insertion on stress distribution pattern and cusp movement of the root-filled maxillary premolars using finite element method (FEM) analysis. A three-dimensional (3 D) FEM model of a sound upper premolar tooth and four models of root-filled upper premolars with mesiocclusodistal (MOD) cavities were molded and restored with: (1) Composite resin only (NF); (2) Composite resin along with a ribbon of glass fiber placed in the occlusal third (OF); (3) Composite resin along with a ribbon of glass fiber placed circumferentially in the cervical third (CF), and (4) Composite resin along with occlusal and circumferential fibers (OCF). A static vertical load was applied to calculate the stress distributions. Structural analysis program by Solidworks were used for FEM analysis. Von-Mises stress values and cusp movements induced by occlusal loading were evaluated. Maximum Von-Mises stress of enamel occurred in sound tooth, followed by NF, CF, OF and OCF. Maximum Von-Mises stress of dentin occurred in sound tooth, followed by OF, OCF, CF and NF. Stress distribution patterns of OF and OCF were similar. Maximum overall stress values were concentrated in NF. Although stress distribution patterns of NF and CF were found as similar, CF showed lower stress values. Palatal cusp movement was more than buccal cusp in all of the models. The results of our study indicated that while the circumferential fiber had little effect on overall stress concentration, it provided a more favorable stress distribution pattern in cervical region. The occlusal fiber reduced the average stress in the entire structure but did not reduce cuspal movement. Incorporating glass fiber in composite restorations may alter the stress state within the structure depending on fiber position.

[Using infrared thermal asymmetry analysis for objective assessment of the lesion of facial nerve function].

PubMed

Liu, Xu-long; Hong, Wen-xue; Song, Jia-lin; Wu, Zhen-ying

2012-03-01

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some lesions of facial nerve function are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to capture the alteration of the infrared thermal distribution. This paper presents a new method of analysis of the thermal asymmetry named effective thermal area ratio, which is a product of two variables. The first variable is mean temperature difference between the specific facial region and its contralateral region. The second variable is a ratio, which is equal to the area of the abnormal region divided by the total area. Using this new method, we performed a controlled trial to assess the facial nerve function of the healthy subjects and the patients with Bell's palsy respectively. The results show: that the mean specificity and sensitivity of this method are 0.90 and 0.87 respectively, improved by 7% and 26% compared with conventional methods. Spearman correlation coefficient between effective thermal area ratio and the degree of facial nerve function is an average of 0.664. Hence, concerning the diagnosis and assessment of facial nerve function, infrared thermography is a powerful tool; while the effective ther mal area ratio is an efficient clinical indicator.

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

USGS Publications Warehouse

Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

PubMed

Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P

2014-01-01

Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.

Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems

NASA Technical Reports Server (NTRS)

Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.

2005-01-01

The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.

Consequences of Decontamination Procedures in Forensic Hair Analysis Using Metal-Assisted Secondary Ion Mass Spectrometry Analysis.

PubMed

Cuypers, Eva; Flinders, Bryn; Boone, Carolien M; Bosman, Ingrid J; Lusthof, Klaas J; Van Asten, Arian C; Tytgat, Jan; Heeren, Ron M A

2016-03-15

Today, hair testing is considered to be the standard method for the detection of chronic drug abuse. Nevertheless, the differentiation between systemic exposure and external contamination remains a major challenge in the forensic interpretation of hair analysis. Nowadays, it is still impossible to directly show the difference between external contamination and use-related incorporation. Although the effects of washing procedures on the distribution of (incorporated) drugs in hair remain unknown, these decontamination procedures prior to hair analysis are considered to be indispensable in order to exclude external contamination. However, insights into the effect of decontamination protocols on levels and distribution of drugs incorporated in hair are essential to draw the correct forensic conclusions from hair analysis; we studied the consequences of these procedures on the spatial distribution of cocaine in hair using imaging mass spectrometry. Additionally, using metal-assisted secondary ion mass spectrometry, we are the first to directly show the difference between cocaine-contaminated and user hair without any prior washing procedure.

Comparison of time-frequency distribution techniques for analysis of spinal somatosensory evoked potential.

PubMed

Hu, Y; Luk, K D; Lu, W W; Holmes, A; Leong, J C

2001-05-01

Spinal somatosensory evoked potential (SSEP) has been employed to monitor the integrity of the spinal cord during surgery. To detect both temporal and spectral changes in SSEP waveforms, an investigation of the application of time-frequency analysis (TFA) techniques was conducted. SSEP signals from 30 scoliosis patients were analysed using different techniques; short time Fourier transform (STFT), Wigner-Ville distribution (WVD), Choi-Williams distribution (CWD), cone-shaped distribution (CSD) and adaptive spectrogram (ADS). The time-frequency distributions (TFD) computed using these methods were assessed and compared with each other. WVD, ADS, CSD and CWD showed better resolution than STFT. Comparing normalised peak widths, CSD showed the sharpest peak width (0.13+/-0.1) in the frequency dimension, and a mean peak width of 0.70+/-0.12 in the time dimension. Both WVD and CWD produced cross-term interference, distorting the TFA distribution, but this was not seen with CSD and ADS. CSD appeared to give a lower mean peak power bias (10.3%+/-6.2%) than ADS (41.8%+/-19.6%). Application of the CSD algorithm showed both good resolution and accurate spectrograms, and is therefore recommended as the most appropriate TFA technique for the analysis of SSEP signals.