A new parametric method of estimating the joint probability density
NASA Astrophysics Data System (ADS)
Alghalith, Moawia
2017-04-01
We present simple parametric methods that overcome major limitations of the literature on joint/marginal density estimation. In doing so, we do not assume any form of marginal or joint distribution. Furthermore, using our method, a multivariate density can be easily estimated if we know only one of the marginal densities. We apply our methods to financial data.
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
NASA Technical Reports Server (NTRS)
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
Simplified Computation for Nonparametric Windows Method of Probability Density Function Estimation.
Joshi, Niranjan; Kadir, Timor; Brady, Michael
2011-08-01
Recently, Kadir and Brady proposed a method for estimating probability density functions (PDFs) for digital signals which they call the Nonparametric (NP) Windows method. The method involves constructing a continuous space representation of the discrete space and sampled signal by using a suitable interpolation method. NP Windows requires only a small number of observed signal samples to estimate the PDF and is completely data driven. In this short paper, we first develop analytical formulae to obtain the NP Windows PDF estimates for 1D, 2D, and 3D signals, for different interpolation methods. We then show that the original procedure to calculate the PDF estimate can be significantly simplified and made computationally more efficient by a judicious choice of the frame of reference. We have also outlined specific algorithmic details of the procedures enabling quick implementation. Our reformulation of the original concept has directly demonstrated a close link between the NP Windows method and the Kernel Density Estimator.
Nonparametric maximum likelihood estimation of probability densities by penalty function methods
NASA Technical Reports Server (NTRS)
Demontricher, G. F.; Tapia, R. A.; Thompson, J. R.
1974-01-01
When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.
NASA Astrophysics Data System (ADS)
Cavuoti, S.; Amaro, V.; Brescia, M.; Vellucci, C.; Tortora, C.; Longo, G.
2017-02-01
A variety of fundamental astrophysical science topics require the determination of very accurate photometric redshifts (photo-z). A wide plethora of methods have been developed, based either on template models fitting or on empirical explorations of the photometric parameter space. Machine-learning-based techniques are not explicitly dependent on the physical priors and able to produce accurate photo-z estimations within the photometric ranges derived from the spectroscopic training set. These estimates, however, are not easy to characterize in terms of a photo-z probability density function (PDF), due to the fact that the analytical relation mapping the photometric parameters on to the redshift space is virtually unknown. We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method designed to provide a reliable PDF of the error distribution for empirical techniques. The method is implemented as a modular workflow, whose internal engine for photo-z estimation makes use of the MLPQNA neural network (Multi Layer Perceptron with Quasi Newton learning rule), with the possibility to easily replace the specific machine-learning model chosen to predict photo-z. We present a summary of results on SDSS-DR9 galaxy data, used also to perform a direct comparison with PDFs obtained by the LE PHARE spectral energy distribution template fitting. We show that METAPHOR is capable to estimate the precision and reliability of photometric redshifts obtained with three different self-adaptive techniques, i.e. MLPQNA, Random Forest and the standard K-Nearest Neighbors models.
NASA Astrophysics Data System (ADS)
Lussana, C.
2013-04-01
The presented work focuses on the investigation of gridded daily minimum (TN) and maximum (TX) temperature probability density functions (PDFs) with the intent of both characterising a region and detecting extreme values. The empirical PDFs estimation procedure has been realised using the most recent years of gridded temperature analysis fields available at ARPA Lombardia, in Northern Italy. The spatial interpolation is based on an implementation of Optimal Interpolation using observations from a dense surface network of automated weather stations. An effort has been made to identify both the time period and the spatial areas with a stable data density otherwise the elaboration could be influenced by the unsettled station distribution. The PDF used in this study is based on the Gaussian distribution, nevertheless it is designed to have an asymmetrical (skewed) shape in order to enable distinction between warming and cooling events. Once properly defined the occurrence of extreme events, it is possible to straightforwardly deliver to the users the information on a local-scale in a concise way, such as: TX extremely cold/hot or TN extremely cold/hot.
Estimation of probability densities using scale-free field theories.
Kinney, Justin B
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Estimation of probability densities using scale-free field theories
NASA Astrophysics Data System (ADS)
Kinney, Justin B.
2014-07-01
The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way using methods from statistical field theory. Here I describe results that allow this field-theoretic approach to be rapidly and deterministically computed in low dimensions, making it practical for use in day-to-day data analysis. Importantly, this approach does not impose a privileged length scale for smoothness of the inferred probability density, but rather learns a natural length scale from the data due to the tradeoff between goodness of fit and an Occam factor. Open source software implementing this method in one and two dimensions is provided.
Online Reinforcement Learning Using a Probability Density Estimation.
Agostini, Alejandro; Celaya, Enric
2017-01-01
Function approximation in online, incremental, reinforcement learning needs to deal with two fundamental problems: biased sampling and nonstationarity. In this kind of task, biased sampling occurs because samples are obtained from specific trajectories dictated by the dynamics of the environment and are usually concentrated in particular convergence regions, which in the long term tend to dominate the approximation in the less sampled regions. The nonstationarity comes from the recursive nature of the estimations typical of temporal difference methods. This nonstationarity has a local profile, varying not only along the learning process but also along different regions of the state space. We propose to deal with these problems using an estimation of the probability density of samples represented with a gaussian mixture model. To deal with the nonstationarity problem, we use the common approach of introducing a forgetting factor in the updating formula. However, instead of using the same forgetting factor for the whole domain, we make it dependent on the local density of samples, which we use to estimate the nonstationarity of the function at any given input point. To address the biased sampling problem, the forgetting factor applied to each mixture component is modulated according to the new information provided in the updating, rather than forgetting depending only on time, thus avoiding undesired distortions of the approximation in less sampled regions.
Conditional Probability Density Functions Arising in Bearing Estimation
1994-05-01
and a better known performance measure: the Cramer-Rao bound . 14. SUMECT TEm IL5 NUlMN OF PAMES Probability Density Function, bearing angle estimation...results obtained using the calculated density functions and a better known performance measure: the Cramer-Rao bound . The major results obtained are as...48 15. Sampling Inteval , Propagation Delay, and Covariance Singularities ....... 52 viii List of Figures (continued
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
NASA Astrophysics Data System (ADS)
Livingston, Richard A.; Jin, Shuang
2005-05-01
Bridges and other civil structures can exhibit nonlinear and/or chaotic behavior under ambient traffic or wind loadings. The probability density function (pdf) of the observed structural responses thus plays an important role for long-term structural health monitoring, LRFR and fatigue life analysis. However, the actual pdf of such structural response data often has a very complicated shape due to its fractal nature. Various conventional methods to approximate it can often lead to biased estimates. This paper presents recent research progress at the Turner-Fairbank Highway Research Center of the FHWA in applying a novel probabilistic scaling scheme for enhanced maximum entropy evaluation to find the most unbiased pdf. The maximum entropy method is applied with a fractal interpolation formulation based on contraction mappings through an iterated function system (IFS). Based on a fractal dimension determined from the entire response data set by an algorithm involving the information dimension, a characteristic uncertainty parameter, called the probabilistic scaling factor, can be introduced. This allows significantly enhanced maximum entropy evaluation through the added inferences about the fine scale fluctuations in the response data. Case studies using the dynamic response data sets collected from a real world bridge (Commodore Barry Bridge, PA) and from the simulation of a classical nonlinear chaotic system (the Lorenz system) are presented in this paper. The results illustrate the advantages of the probabilistic scaling method over conventional approaches for finding the unbiased pdf especially in the critical tail region that contains the larger structural responses.
Nonparametric probability density estimation by optimization theoretic techniques
NASA Technical Reports Server (NTRS)
Scott, D. W.
1976-01-01
Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.
Numerical methods for high-dimensional probability density function equations
NASA Astrophysics Data System (ADS)
Cho, H.; Venturi, D.; Karniadakis, G. E.
2016-01-01
In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker-Planck and Dostupov-Pugachev equations), random wave theory (Malakhov-Saichev equations) and coarse-grained stochastic systems (Mori-Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov-Born-Green-Kirkwood-Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.
Numerical methods for high-dimensional probability density function equations
Cho, H.; Venturi, D.; Karniadakis, G.E.
2016-01-15
In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker–Planck and Dostupov–Pugachev equations), random wave theory (Malakhov–Saichev equations) and coarse-grained stochastic systems (Mori–Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov–Born–Green–Kirkwood–Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Höft, J.; ...
2015-01-06
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Hoft, Jan; Weber, J. K.; Raut, E.; Larson, Vincent E.; Wang, Minghuai; Rasch, Philip J.
2015-01-06
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection.These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.
Parameterizing deep convection using the assumed probability density function method
Storer, R. L.; Griffin, B. M.; Höft, J.; ...
2014-06-11
Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing ismore » weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.« less
A Non-Parametric Probability Density Estimator and Some Applications.
1984-05-01
but she always made them easier. My children, Alison and Adam, did not always make °’ things easier but did keep my efforts in perspective. I love...Since one goal of this research is to develop a " handi - off" estimator, these choices will either be made a priori 24
Rajwade, Ajit; Banerjee, Arunava; Rangarajan, Anand
2009-03-01
We present a new, geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels, and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint densities of image pairs. We demonstrate the application of our method to affine registration between two or more images using information theoretic measures such as mutual information. We show cases where our method outperforms existing methods such as simple histograms, histograms with partial volume interpolation, Parzen windows, etc. under fine intensity quantization for affine image registration under significant image noise. Furthermore, we demonstrate results on simultaneous registration of multiple images, as well as for pairs of volume datasets, and show some theoretical properties of our density estimator. Our approach requires the selection of only an image interpolant. The method neither requires any kind of kernel functions (as in Parzen windows) which are unrelated to the structure of the image in itself, nor does it rely on any form of sampling for density estimation.
Rajwade, Ajit; Banerjee, Arunava; Rangarajan, Anand
2010-01-01
We present a new geometric approach for determining the probability density of the intensity values in an image. We drop the notion of an image as a set of discrete pixels and assume a piecewise-continuous representation. The probability density can then be regarded as being proportional to the area between two nearby isocontours of the image surface. Our paper extends this idea to joint densities of image pairs. We demonstrate the application of our method to affine registration between two or more images using information-theoretic measures such as mutual information. We show cases where our method outperforms existing methods such as simple histograms, histograms with partial volume interpolation, Parzen windows, etc., under fine intensity quantization for affine image registration under significant image noise. Furthermore, we demonstrate results on simultaneous registration of multiple images, as well as for pairs of volume data sets, and show some theoretical properties of our density estimator. Our approach requires the selection of only an image interpolant. The method neither requires any kind of kernel functions (as in Parzen windows), which are unrelated to the structure of the image in itself, nor does it rely on any form of sampling for density estimation. PMID:19147876
SAR amplitude probability density function estimation based on a generalized Gaussian model.
Moser, Gabriele; Zerubia, Josiane; Serpico, Sebastiano B
2006-06-01
In the context of remotely sensed data analysis, an important problem is the development of accurate models for the statistics of the pixel intensities. Focusing on synthetic aperture radar (SAR) data, this modeling process turns out to be a crucial task, for instance, for classification or for denoising purposes. In this paper, an innovative parametric estimation methodology for SAR amplitude data is proposed that adopts a generalized Gaussian (GG) model for the complex SAR backscattered signal. A closed-form expression for the corresponding amplitude probability density function (PDF) is derived and a specific parameter estimation algorithm is developed in order to deal with the proposed model. Specifically, the recently proposed "method-of-log-cumulants" (MoLC) is applied, which stems from the adoption of the Mellin transform (instead of the usual Fourier transform) in the computation of characteristic functions and from the corresponding generalization of the concepts of moment and cumulant. For the developed GG-based amplitude model, the resulting MoLC estimates turn out to be numerically feasible and are also analytically proved to be consistent. The proposed parametric approach was validated by using several real ERS-1, XSAR, E-SAR, and NASA/JPL airborne SAR images, and the experimental results prove that the method models the amplitude PDF better than several previously proposed parametric models for backscattering phenomena.
Dictionary-based probability density function estimation for high-resolution SAR data
NASA Astrophysics Data System (ADS)
Krylov, Vladimir; Moser, Gabriele; Serpico, Sebastiano B.; Zerubia, Josiane
2009-02-01
In the context of remotely sensed data analysis, a crucial problem is represented by the need to develop accurate models for the statistics of pixel intensities. In this work, we develop a parametric finite mixture model for the statistics of pixel intensities in high resolution synthetic aperture radar (SAR) images. This method is an extension of previously existing method for lower resolution images. The method integrates the stochastic expectation maximization (SEM) scheme and the method of log-cumulants (MoLC) with an automatic technique to select, for each mixture component, an optimal parametric model taken from a predefined dictionary of parametric probability density functions (pdf). The proposed dictionary consists of eight state-of-the-art SAR-specific pdfs: Nakagami, log-normal, generalized Gaussian Rayleigh, Heavy-tailed Rayleigh, Weibull, K-root, Fisher and generalized Gamma. The designed scheme is endowed with the novel initialization procedure and the algorithm to automatically estimate the optimal number of mixture components. The experimental results with a set of several high resolution COSMO-SkyMed images demonstrate the high accuracy of the designed algorithm, both from the viewpoint of a visual comparison of the histograms, and from the viewpoint of quantitive accuracy measures such as correlation coefficient (above 99,5%). The method proves to be effective on all the considered images, remaining accurate for multimodal and highly heterogeneous scenes.
Unification of field theory and maximum entropy methods for learning probability densities.
Kinney, Justin B
2015-09-01
The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.
A Tomographic Method for the Reconstruction of Local Probability Density Functions
NASA Technical Reports Server (NTRS)
Sivathanu, Y. R.; Gore, J. P.
1993-01-01
A method of obtaining the probability density function (PDF) of local properties from path integrated measurements is described. The approach uses a discrete probability function (DPF) method to infer the PDF of the local extinction coefficient from measurements of the PDFs of the path integrated transmittance. The local PDFs obtained using the method are compared with those obtained from direct intrusive measurements in propylene/air and ethylene/air diffusion flames. The results of this comparison are good.
Fast and accurate probability density estimation in large high dimensional astronomical datasets
NASA Astrophysics Data System (ADS)
Gupta, Pramod; Connolly, Andrew J.; Gardner, Jeffrey P.
2015-01-01
Astronomical surveys will generate measurements of hundreds of attributes (e.g. color, size, shape) on hundreds of millions of sources. Analyzing these large, high dimensional data sets will require efficient algorithms for data analysis. An example of this is probability density estimation that is at the heart of many classification problems such as the separation of stars and quasars based on their colors. Popular density estimation techniques use binning or kernel density estimation. Kernel density estimation has a small memory footprint but often requires large computational resources. Binning has small computational requirements but usually binning is implemented with multi-dimensional arrays which leads to memory requirements which scale exponentially with the number of dimensions. Hence both techniques do not scale well to large data sets in high dimensions. We present an alternative approach of binning implemented with hash tables (BASH tables). This approach uses the sparseness of data in the high dimensional space to ensure that the memory requirements are small. However hashing requires some extra computation so a priori it is not clear if the reduction in memory requirements will lead to increased computational requirements. Through an implementation of BASH tables in C++ we show that the additional computational requirements of hashing are negligible. Hence this approach has small memory and computational requirements. We apply our density estimation technique to photometric selection of quasars using non-parametric Bayesian classification and show that the accuracy of the classification is same as the accuracy of earlier approaches. Since the BASH table approach is one to three orders of magnitude faster than the earlier approaches it may be useful in various other applications of density estimation in astrostatistics.
Rius, Jordi
2006-09-01
The maximum-likelihood method is applied to direct methods to derive a more general probability density function of the triple-phase sums which is capable of predicting negative values. This study also proves that maximization of the origin-free modulus sum function S yields, within the limitations imposed by the assumed approximations, the maximum-likelihood estimates of the phases. It thus represents the formal theoretical justification of the S function that was initially derived from Patterson-function arguments [Rius (1993). Acta Cryst. A49, 406-409].
NASA Astrophysics Data System (ADS)
Liu, Jie; Sun, Xingsheng; Li, Kun; Jiang, Chao; Han, Xu
2015-11-01
Aiming at structures containing random parameters with multi-peak probability density functions (PDFs) or great variable coefficients, an analytical method of probability density function discretization and approximation (PDFDA) is proposed for dynamic load identification. Dynamic loads are expressed as the functions of time and random parameters in time domain and the forward model is established through the discretized convolution integral of loads and the corresponding unit-pulse response functions. The PDF of each random parameter is discretized into several subintervals and in each subinterval the original PDF curve is approximated via uniform distribution PDF with equal probability value. Then the joint distribution model is built and hence the equivalent deterministic equations are solved to identify unknown loads. Inverse analysis is operated separately at each variable in the joint distribution model through regularization because of noise-contaminated measured responses. In order to assess the accuracy of identified results, PDF curves and statistical properties of loads are achieved based on the specially assumed distributions of identified loads. Numerical simulations demonstrate the efficiency and superiority of the presented method.
A Monte Carlo method for the PDF (Probability Density Functions) equations of turbulent flow
NASA Astrophysics Data System (ADS)
Pope, S. B.
1980-02-01
The transport equations of joint probability density functions (pdfs) in turbulent flows are simulated using a Monte Carlo method because finite difference solutions of the equations are impracticable, mainly due to the large dimensionality of the pdfs. Attention is focused on equation for the joint pdf of chemical and thermodynamic properties in turbulent reactive flows. It is shown that the Monte Carlo method provides a true simulation of this equation and that the amount of computation required increases only linearly with the number of properties considered. Consequently, the method can be used to solve the pdf equation for turbulent flows involving many chemical species and complex reaction kinetics. Monte Carlo calculations of the pdf of temperature in a turbulent mixing layer are reported. These calculations are in good agreement with the measurements of Batt (1977).
Zhang Yumin; Lum, Kai-Yew; Wang Qingguo
2009-03-05
In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.
A probability density function method for detecting atrial fibrillation using R-R intervals.
Hong-Wei, Lu; Ying, Sun; Min, Lin; Pi-Ding, Li; Zheng, Zheng
2009-01-01
A probability density function (PDF) method is proposed for investigating the structure of the reconstructed attractor of R-R intervals. By constructing the PDF of distance between two points in the reconstructed phase space of R-R intervals of normal sinus rhythm (NSR) and atrial fibrillation (AF), it is found that the distributions of PDF of NSR and AF R-R intervals have significant differences. By taking advantage of their differences, a characteristic parameter k(n), which represents the sum of n points slope in filtered PDF curve, is put forward to detect both 400 segments of NSR and AF R-R intervals from the MIT-BIH Atrial Fibrillation database. Parameters such as number of R-R intervals, number of embedding dimensions and slope are optimized for the best detection performance. Results demonstrate that the new algorithm has a fast response speed with R-R intervals as short as 40, and shows a sensitivity of 0.978, and a specificity of 0.990 in the best detecting performance.
Bakosi, Jozsef; Ristorcelli, Raymond J
2010-01-01
Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.
Spline Histogram Method for Reconstruction of Probability Density Functions of Clusters of Galaxies
NASA Astrophysics Data System (ADS)
Docenko, Dmitrijs; Berzins, Karlis
We describe the spline histogram algorithm which is useful for visualization of the probability density function setting up a statistical hypothesis for a test. The spline histogram is constructed from discrete data measurements using tensioned cubic spline interpolation of the cumulative distribution function which is then differentiated and smoothed using the Savitzky-Golay filter. The optimal width of the filter is determined by minimization of the Integrated Square Error function. The current distribution of the TCSplin algorithm written in f77 with IDL and Gnuplot visualization scripts is available from www.virac.lv/en/soft.html.
NASA Astrophysics Data System (ADS)
Papadopoulos, Vissarion; Kalogeris, Ioannis
2016-05-01
The present paper proposes a Galerkin finite element projection scheme for the solution of the partial differential equations (pde's) involved in the probability density evolution method, for the linear and nonlinear static analysis of stochastic systems. According to the principle of preservation of probability, the probability density evolution of a stochastic system is expressed by its corresponding Fokker-Planck (FP) stochastic partial differential equation. Direct integration of the FP equation is feasible only for simple systems with a small number of degrees of freedom, due to analytical and/or numerical intractability. However, rewriting the FP equation conditioned to the random event description, a generalized density evolution equation (GDEE) can be obtained, which can be reduced to a one dimensional pde. Two Galerkin finite element method schemes are proposed for the numerical solution of the resulting pde's, namely a time-marching discontinuous Galerkin scheme and the StreamlineUpwind/Petrov Galerkin (SUPG) scheme. In addition, a reformulation of the classical GDEE is proposed, which implements the principle of probability preservation in space instead of time, making this approach suitable for the stochastic analysis of finite element systems. The advantages of the FE Galerkin methods and in particular the SUPG over finite difference schemes, like the modified Lax-Wendroff, which is the most frequently used method for the solution of the GDEE, are illustrated with numerical examples and explored further.
NASA Technical Reports Server (NTRS)
Tretter, S. A.
1977-01-01
A report is given to supplement the progress report of June 17, 1977. In that progress report gamma, lognormal, and Rayleigh probability density functions were fitted to the times between lightning flashes in the storms of 9/12/75, 8/26/75, and 7/13/76 by the maximum likelihood method. The goodness of fit is checked by the Kolmogoroff-Smirnoff test. Plots of the estimated densities along with normalized histograms are included to provide a visual check on the goodness of fit. The lognormal densities are the most peaked and have the highest tails. This results in the best fit to the normalized histogram in most cases. The Rayleigh densities have too broad and rounded peaks to give good fits. In addition, they have the lowest tails. The gamma densities fall inbetween and give the best fit in a few cases.
Caliandro, G.A.; Torres, D.F.; Rea, N. E-mail: dtorres@aliga.ieec.uab.es
2013-07-01
Here, we present a new method to evaluate the expectation value of the power spectrum of a time series. A statistical approach is adopted to define the method. After its demonstration, it is validated showing that it leads to the known properties of the power spectrum when the time series contains a periodic signal. The approach is also validated in general with numerical simulations. The method puts into evidence the importance that is played by the probability density function of the phases associated to each time stamp for a given frequency, and how this distribution can be perturbed by the uncertainties of the parameters in the pulsar ephemeris. We applied this method to solve the power spectrum in the case the first derivative of the pulsar frequency is unknown and not negligible. We also undertook the study of the most general case of a blind search, in which both the frequency and its first derivative are uncertain. We found the analytical solutions of the above cases invoking the sum of Fresnel's integrals squared.
Sato, Tatsuhiko; Furusawa, Yoshiya
2012-10-01
Estimation of the survival fractions of cells irradiated with various particles over a wide linear energy transfer (LET) range is of great importance in the treatment planning of charged-particle therapy. Two computational models were developed for estimating survival fractions based on the concept of the microdosimetric kinetic model. They were designated as the double-stochastic microdosimetric kinetic and stochastic microdosimetric kinetic models. The former model takes into account the stochastic natures of both domain and cell nucleus specific energies, whereas the latter model represents the stochastic nature of domain specific energy by its approximated mean value and variance to reduce the computational time. The probability densities of the domain and cell nucleus specific energies are the fundamental quantities for expressing survival fractions in these models. These densities are calculated using the microdosimetric and LET-estimator functions implemented in the Particle and Heavy Ion Transport code System (PHITS) in combination with the convolution or database method. Both the double-stochastic microdosimetric kinetic and stochastic microdosimetric kinetic models can reproduce the measured survival fractions for high-LET and high-dose irradiations, whereas a previously proposed microdosimetric kinetic model predicts lower values for these fractions, mainly due to intrinsic ignorance of the stochastic nature of cell nucleus specific energies in the calculation. The models we developed should contribute to a better understanding of the mechanism of cell inactivation, as well as improve the accuracy of treatment planning of charged-particle therapy.
Kim, Sangdan; Han, Suhee
2010-01-01
Most related literature regarding designing urban non-point-source management systems assumes that precipitation event-depths follow the 1-parameter exponential probability density function to reduce the mathematical complexity of the derivation process. However, the method of expressing the rainfall is the most important factor for analyzing stormwater; thus, a better mathematical expression, which represents the probability distribution of rainfall depths, is suggested in this study. Also, the rainfall-runoff calculation procedure required for deriving a stormwater-capture curve is altered by the U.S. Natural Resources Conservation Service (Washington, D.C.) (NRCS) runoff curve number method to consider the nonlinearity of the rainfall-runoff relation and, at the same time, obtain a more verifiable and representative curve for design when applying it to urban drainage areas with complicated land-use characteristics, such as occurs in Korea. The result of developing the stormwater-capture curve from the rainfall data in Busan, Korea, confirms that the methodology suggested in this study provides a better solution than the pre-existing one.
NASA Astrophysics Data System (ADS)
Kwasniok, Frank
2013-11-01
A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.
Kwasniok, Frank
2013-11-01
A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.
Trajectory versus probability density entropy.
Bologna, M; Grigolini, P; Karagiorgis, M; Rosa, A
2001-07-01
We show that the widely accepted conviction that a connection can be established between the probability density entropy and the Kolmogorov-Sinai (KS) entropy is questionable. We adopt the definition of density entropy as a functional of a distribution density whose time evolution is determined by a transport equation, conceived as the only prescription to use for the calculation. Although the transport equation is built up for the purpose of affording a picture equivalent to that stemming from trajectory dynamics, no direct use of trajectory time evolution is allowed, once the transport equation is defined. With this definition in mind we prove that the detection of a time regime of increase of the density entropy with a rate identical to the KS entropy is possible only in a limited number of cases. The proposals made by some authors to establish a connection between the two entropies in general, violate our definition of density entropy and imply the concept of trajectory, which is foreign to that of density entropy.
Modulation Based on Probability Density Functions
NASA Technical Reports Server (NTRS)
Williams, Glenn L.
2009-01-01
A proposed method of modulating a sinusoidal carrier signal to convey digital information involves the use of histograms representing probability density functions (PDFs) that characterize samples of the signal waveform. The method is based partly on the observation that when a waveform is sampled (whether by analog or digital means) over a time interval at least as long as one half cycle of the waveform, the samples can be sorted by frequency of occurrence, thereby constructing a histogram representing a PDF of the waveform during that time interval.
Durrieu, G; Ciffroy, P; Garnier, J-M
2006-11-01
The objective of the study was to provide global probability density functions (PDFs) representing the uncertainty of distribution coefficients (Kds) in freshwater for radioisotopes of Co, Cs, Sr and I. A comprehensive database containing Kd values referenced in 61 articles was first built and quality scores were affected to each data point according to various criteria (e.g. presentation of data, contact times, pH, solid-to-liquid ratio, expert judgement). A weighted bootstrapping procedure was then set up in order to build PDFs, in such a way that more importance is given to the most relevant data points (i.e. those corresponding to typical natural environments). However, it was also assessed that the relevance and the robustness of the PDFs determined by our procedure depended on the number of Kd values in the database. Owing to the large database, conditional PDFs were also proposed, for site studies where some parametric information is known (e.g. pH, contact time between radionuclides and particles, solid-to-liquid ratio). Such conditional PDFs reduce the uncertainty on the Kd values. These global and conditional PDFs are useful for end-users of dose models because the uncertainty and sensitivity of Kd values are taking into account.
NASA Astrophysics Data System (ADS)
Kim, Jeonglae; Pope, Stephen B.
2014-05-01
A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational efficiency of combined dimension reduction and tabulation of chemistry. The computational condition matches the Volvo rig experiments. For the reactive simulation, the Lagrangian Large-Eddy Simulation/Probability Density Function (LES/PDF) formulation is used. A novel two-way coupling approach between LES and PDF is applied to obtain resolved density to reduce its statistical fluctuations. Composition mixing is evaluated by the modified Interaction-by-Exchange with the Mean (IEM) model. A baseline case uses In Situ Adaptive Tabulation (ISAT) to calculate chemical reactions efficiently. Its results demonstrate good agreement with the experimental measurements in turbulence statistics, temperature, and minor species mass fractions. For dimension reduction, 11 and 16 represented species are chosen and a variant of Rate Controlled Constrained Equilibrium (RCCE) is applied in conjunction with ISAT to each case. All the quantities in the comparison are indistinguishable from the baseline results using ISAT only. The combined use of RCCE/ISAT reduces the computational time for chemical reaction by more than 50%. However, for the current turbulent premixed flame, chemical reaction takes only a minor portion of the overall computational cost, in contrast to non-premixed flame simulations using LES/PDF, presumably due to the restricted manifold of purely premixed flame in the composition space. Instead, composition mixing is the major contributor to cost reduction since the mean-drift term, which is computationally expensive, is computed for the reduced representation. Overall, a reduction of more than 15% in the computational cost is obtained.
NASA Astrophysics Data System (ADS)
Maslennikova, Yu. S.; Nugmanov, I. S.
2016-08-01
The problem of probability density function estimation for a random process is one of the most common in practice. There are several methods to solve this problem. Presented laboratory work uses methods of the mathematical statistics to detect patterns in the realization of random process. On the basis of ergodic theory, we construct algorithm for estimating univariate probability density distribution function for a random process. Correlational analysis of realizations is applied to estimate the necessary size of the sample and the time of observation. Hypothesis testing for two probability distributions (normal and Cauchy) is used on the experimental data, using χ2 criterion. To facilitate understanding and clarity of the problem solved, we use ELVIS II platform and LabVIEW software package that allows us to make the necessary calculations, display results of the experiment and, most importantly, to control the experiment. At the same time students are introduced to a LabVIEW software package and its capabilities.
Velocity analysis with local event slopes related probability density function
NASA Astrophysics Data System (ADS)
Zhang, Peng; Lu, Wenkai; Zhang, Yingqiang
2015-12-01
Macro velocity model plays a key role in seismic imaging and inversion. The performance of traditional velocity analysis methods is degraded by multiples and amplitude-versus-offset (AVO) anomalies. Local event slopes, containing the subsurface velocity information, have been widely used to accomplish common time-domain seismic processing, imaging and velocity estimation. In this paper, we propose a method for velocity analysis with probability density function (PDF) related to local event slopes. We first estimate local event slopes with phase information in the Fourier domain. An adaptive filter is applied to improve the performance of slopes estimator in the low signal-to-noise ratio (SNR) situation. Second, the PDF is approximated with the histogram function, which is related to attributes derived from local event slopes. As a graphical representation of the data distribution, the histogram function can be computed efficiently. By locating the ray path of the first arrival on the semblance image with straight-ray segments assumption, automatic velocity picking is carried out to establish velocity model. Unlike local event slopes based velocity estimation strategies such as averaging filters and image warping, the proposed method does not make the assumption that the errors of mapped velocity values are symmetrically distributed or that the variation of amplitude along the offset is slight. Extension of the method to prestack time-domain migration velocity estimation is also given. With synthetic and field examples, we demonstrate that our method can achieve high resolution, even in the presence of multiples, strong amplitude variations and polarity reversals.
Probability density functions in turbulent channel flow
NASA Technical Reports Server (NTRS)
Dinavahi, Surya P. G.
1992-01-01
The probability density functions (pdf's) of the fluctuating velocity components, as well as their first and second derivatives, are calculated using data from the direct numerical simulations (DNS) of fully developed turbulent channel flow. It is observed that, beyond the buffer region, the pdf of each of these quantities is independent of the distance from the channel wall. It is further observed that, beyond the buffer region, the pdf's for all the first derivatives collapse onto a single universal curve and those of the second derivatives also collapse onto another universal curve, irrespective of the distance from the wall. The kinetic-energy dissipation rate exhibits log normal behavior.
Carrier Modulation Via Waveform Probability Density Function
NASA Technical Reports Server (NTRS)
Williams, Glenn L.
2006-01-01
Beyond the classic modes of carrier modulation by varying amplitude (AM), phase (PM), or frequency (FM), we extend the modulation domain of an analog carrier signal to include a class of general modulations which are distinguished by their probability density function histogram. Separate waveform states are easily created by varying the pdf of the transmitted waveform. Individual waveform states are assignable as proxies for digital one's or zero's. At the receiver, these states are easily detected by accumulating sampled waveform statistics and performing periodic pattern matching, correlation, or statistical filtering. No fundamental physical laws are broken in the detection process. We show how a typical modulation scheme would work in the digital domain and suggest how to build an analog version. We propose that clever variations of the modulating waveform (and thus the histogram) can provide simple steganographic encoding.
Carrier Modulation Via Waveform Probability Density Function
NASA Technical Reports Server (NTRS)
Williams, Glenn L.
2004-01-01
Beyond the classic modes of carrier modulation by varying amplitude (AM), phase (PM), or frequency (FM), we extend the modulation domain of an analog carrier signal to include a class of general modulations which are distinguished by their probability density function histogram. Separate waveform states are easily created by varying the pdf of the transmitted waveform. Individual waveform states are assignable as proxies for digital ONEs or ZEROs. At the receiver, these states are easily detected by accumulating sampled waveform statistics and performing periodic pattern matching, correlation, or statistical filtering. No fundamental natural laws are broken in the detection process. We show how a typical modulation scheme would work in the digital domain and suggest how to build an analog version. We propose that clever variations of the modulating waveform (and thus the histogram) can provide simple steganographic encoding.
Downlink Probability Density Functions for EOS-McMurdo Sound
NASA Technical Reports Server (NTRS)
Christopher, P.; Jackson, A. H.
1996-01-01
The visibility times and communication link dynamics for the Earth Observations Satellite (EOS)-McMurdo Sound direct downlinks have been studied. The 16 day EOS periodicity may be shown with the Goddard Trajectory Determination System (GTDS) and the entire 16 day period should be simulated for representative link statistics. We desire many attributes of the downlink, however, and a faster orbital determination method is desirable. We use the method of osculating elements for speed and accuracy in simulating the EOS orbit. The accuracy of the method of osculating elements is demonstrated by closely reproducing the observed 16 day Landsat periodicity. An autocorrelation function method is used to show the correlation spike at 16 days. The entire 16 day record of passes over McMurdo Sound is then used to generate statistics for innage time, outage time, elevation angle, antenna angle rates, and propagation loss. The levation angle probability density function is compared with 1967 analytic approximation which has been used for medium to high altitude satellites. One practical result of this comparison is seen to be the rare occurrence of zenith passes. The new result is functionally different than the earlier result, with a heavy emphasis on low elevation angles. EOS is one of a large class of sun synchronous satellites which may be downlinked to McMurdo Sound. We examine delay statistics for an entire group of sun synchronous satellites ranging from 400 km to 1000 km altitude. Outage probability density function results are presented three dimensionally.
Protein single-model quality assessment by feature-based probability density functions.
Cao, Renzhi; Cheng, Jianlin
2016-04-04
Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.
Probability Density Function Analysis of Turbulent Condensation Using GPU Hardware
NASA Astrophysics Data System (ADS)
Keedy, Ryan; Riley, James; Aliseda, Alberto
2014-11-01
Growth of liquid droplets by condensation is an important phenomenon in many environmental and industrial applications. In a homogenous, supersaturated environment, condensation will tend to narrow the diameter distribution of a poly-disperse collection of droplets. However, free shear turbulence can broaden the diameter distribution due to intermittency in the mixing and by subjecting droplets to non-Gaussian supersaturation statistics. In order to understand the condensation behavior of water droplets in a turbulent flow, it is necessary to understand the dispersion of the droplets and transported scalars. We describe a hybrid approach for predicting droplet growth and dispersion in a turbulent mixing layer and compare our computational predictions to experimental data. The approach utilizes a finite-volume code to calculate the fluid velocity field and a particle-mesh Monte Carlo method to track the locations and thermodynamics of the large number of stochastic particles throughout the domain required to resolve the Probability Density Function of the water vapor and droplets. The particle tracking algorithm is designed to take advantage of the computational power of a large number of GPU cores, with significant speed-up when compared against a baseline CPU configuration.
NASA Astrophysics Data System (ADS)
Vasta, M.; Di Paola, M.
In this paper an approximate explicit probability density function for the analysis of external oscillations of a linear and geometric nonlinear simply supported beam driven by random pulses is proposed. The adopted impulsive loading model is the Poisson White Noise , that is a process having Dirac's delta occurrences with random intensity distributed in time according to Poisson's law. The response probability density function can be obtained solving the related Kolmogorov-Feller (KF) integro-differential equation. An approximated solution, using path integral method, is derived transforming the KF equation to a first order partial differential equation. The method of characteristic is then applied to obtain an explicit solution. Different levels of approximation, depending on the physical assumption on the transition probability density function, are found and the solution for the response density is obtained as series expansion using convolution integrals.
Representation of Probability Density Functions from Orbit Determination using the Particle Filter
NASA Technical Reports Server (NTRS)
Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell
2012-01-01
Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.
Exact probability-density function for phase-measurement interferometry
NASA Astrophysics Data System (ADS)
Ho, Keang-Po; Kahn, Joseph M.
1995-09-01
Conventional analyses of the accuracy of phase-measurement interferometry derive a figure of merit that is either a variance or a signal-to-noise ratio. We derive the probability-density function of the phase-measurement output, so that the measurement confidence interval can be determined. We include both laser phase noise and additive Gaussian noise, and we consider both unmodulated interferometers and those employing phase or frequency modulation. For both unmodulated and modulated interferometers the confidence interval can be obtained by numerical integration of the probability-density function. For the modulated interferometer we derive a series summation for the confidence interval. For both unmodulated and modulated interferometers we derive approximate analytical expressions for the confidence interval, which we show to be extremely accurate at high signal-to-noise ratios.
Probability Density Function at the 3D Anderson Transition
NASA Astrophysics Data System (ADS)
Rodriguez, Alberto; Vasquez, Louella J.; Roemer, Rudolf
2009-03-01
The probability density function (PDF) for the wavefunction amplitudes is studied at the metal-insulator transition of the 3D Anderson model, for very large systems up to L^3=240^3. The implications of the multifractal nature of the state upon the PDF are presented in detail. A formal expression between the PDF and the singularity spectrum f(α) is given. The PDF can be easily used to carry out a numerical multifractal analysis and it appears as a valid alternative to the more usual approach based on the scaling law of the general inverse participation rations.
Representation of layer-counted proxy records as probability densities on error-free time axes
NASA Astrophysics Data System (ADS)
Boers, Niklas; Goswami, Bedartha; Ghil, Michael
2016-04-01
Time series derived from paleoclimatic proxy records exhibit substantial dating uncertainties in addition to the measurement errors of the proxy values. For radiometrically dated proxy archives, Goswami et al. [1] have recently introduced a framework rooted in Bayesian statistics that successfully propagates the dating uncertainties from the time axis to the proxy axis. The resulting proxy record consists of a sequence of probability densities over the proxy values, conditioned on prescribed age values. One of the major benefits of this approach is that the proxy record is represented on an accurate, error-free time axis. Such unambiguous dating is crucial, for instance, in comparing different proxy records. This approach, however, is not directly applicable to proxy records with layer-counted chronologies, as for example ice cores, which are typically dated by counting quasi-annually deposited ice layers. Hence the nature of the chronological uncertainty in such records is fundamentally different from that in radiometrically dated ones. Here, we introduce a modification of the Goswami et al. [1] approach that is specifically designed for layer-counted proxy records, instead of radiometrically dated ones. We apply our method to isotope ratios and dust concentrations in the NGRIP core, using a published 60,000-year chronology [2]. It is shown that the further one goes into the past, the more the layer-counting errors accumulate and lead to growing uncertainties in the probability density sequence for the proxy values that results from the proposed approach. For the older parts of the record, these uncertainties affect more and more a statistically sound estimation of proxy values. This difficulty implies that great care has to be exercised when comparing and in particular aligning specific events among different layer-counted proxy records. On the other hand, when attempting to derive stochastic dynamical models from the proxy records, one is only interested in the
Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; ...
2016-02-02
Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power datamore » are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.« less
Gomez-Lazaro, Emilio; Bueso, Maria C.; Kessler, Mathieu; Martin-Martinez, Sergio; Zhang, Jie; Hodge, Bri -Mathias; Molina-Garcia, Angel
2016-02-02
Here, the Weibull probability distribution has been widely applied to characterize wind speeds for wind energy resources. Wind power generation modeling is different, however, due in particular to power curve limitations, wind turbine control methods, and transmission system operation requirements. These differences are even greater for aggregated wind power generation in power systems with high wind penetration. Consequently, models based on one-Weibull component can provide poor characterizations for aggregated wind power generation. With this aim, the present paper focuses on discussing Weibull mixtures to characterize the probability density function (PDF) for aggregated wind power generation. PDFs of wind power data are firstly classified attending to hourly and seasonal patterns. The selection of the number of components in the mixture is analyzed through two well-known different criteria: the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Finally, the optimal number of Weibull components for maximum likelihood is explored for the defined patterns, including the estimated weight, scale, and shape parameters. Results show that multi-Weibull models are more suitable to characterize aggregated wind power data due to the impact of distributed generation, variety of wind speed values and wind power curtailment.
Analytical Formulation of the Single-visit Completeness Joint Probability Density Function
NASA Astrophysics Data System (ADS)
Garrett, Daniel; Savransky, Dmitry
2016-09-01
We derive an exact formulation of the multivariate integral representing the single-visit obscurational and photometric completeness joint probability density function for arbitrary distributions for planetary parameters. We present a derivation of the region of nonzero values of this function, which extends previous work, and discuss the time and computational complexity costs and benefits of the method. We present a working implementation and demonstrate excellent agreement between this approach and Monte Carlo simulation results.
NASA Astrophysics Data System (ADS)
Mori, Shohei; Hirata, Shinnosuke; Yamaguchi, Tadashi; Hachiya, Hiroyuki
To develop a quantitative diagnostic method for liver fibrosis using an ultrasound B-mode image, a probability imaging method of tissue characteristics based on a multi-Rayleigh model, which expresses a probability density function of echo signals from liver fibrosis, has been proposed. In this paper, an effect of non-speckle echo signals on tissue characteristics estimated from the multi-Rayleigh model was evaluated. Non-speckle signals were determined and removed using the modeling error of the multi-Rayleigh model. The correct tissue characteristics of fibrotic tissue could be estimated with the removal of non-speckle signals.
NASA Astrophysics Data System (ADS)
Boslough, M.
2011-12-01
Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based
Probability density distribution of velocity differences at high Reynolds numbers
NASA Technical Reports Server (NTRS)
Praskovsky, Alexander A.
1993-01-01
Recent understanding of fine-scale turbulence structure in high Reynolds number flows is mostly based on Kolmogorov's original and revised models. The main finding of these models is that intrinsic characteristics of fine-scale fluctuations are universal ones at high Reynolds numbers, i.e., the functional behavior of any small-scale parameter is the same in all flows if the Reynolds number is high enough. The only large-scale quantity that directly affects small-scale fluctuations is the energy flux through a cascade. In dynamical equilibrium between large- and small-scale motions, this flux is equal to the mean rate of energy dissipation epsilon. The pdd of velocity difference is a very important characteristic for both the basic understanding of fully developed turbulence and engineering problems. Hence, it is important to test the findings: (1) the functional behavior of the tails of the probability density distribution (pdd) represented by P(delta(u)) is proportional to exp(-b(r) absolute value of delta(u)/sigma(sub delta(u))) and (2) the logarithmic decrement b(r) scales as b(r) is proportional to r(sup 0.15) when separation r lies in the inertial subrange in high Reynolds number laboratory shear flows.
Spectral Discrete Probability Density Function of Measured Wind Turbine Noise in the Far Field
Ashtiani, Payam; Denison, Adelaide
2015-01-01
Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources. PMID:25905097
Spectral discrete probability density function of measured wind turbine noise in the far field.
Ashtiani, Payam; Denison, Adelaide
2015-01-01
Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources.
Boundary conditions for probability density function transport equations in fluid mechanics.
Valiño, Luis; Hierro, Juan
2003-04-01
The behavior of the probability density function (PDF) transport equation at the limits of the probability space is studied from the point of view of fluid mechanics. Different boundary conditions are considered depending on the nature of the variable considered (velocity, scalar, and position). A study of the implications of entrance and exit conditions is performed, showing that a new term should be added to the PDF transport equation to preserve normalization in some nonstationary processes. In practice, this term is taken into account naturally in particle methods. Finally, the existence of discontinuities at the limits is also investigated.
Impact of sampling volume on the probability density function of steady state concentration
NASA Astrophysics Data System (ADS)
Schwede, Ronnie L.; Cirpka, Olaf A.; Nowak, Wolfgang; Neuweiler, Insa
2008-12-01
In recent years, statistical theory has been used to compute the ensemble mean and variance of solute concentration in aquifer formations with second-order stationary velocity fields. The merit of accurately estimating the mean and variance of concentration, however, remains unclear without knowing the shape of the probability density function (pdf). In a setup where a conservative solute is continuously injected into a domain, the concentration is bounded between zero and the concentration value in the injected solution. At small travel distances close to the fringe of the plume, an observation point may fall into the plume or outside, so that the statistical concentration distribution clusters at the two limiting values. Obviously, this results in non-Gaussian pdf's of concentration. With increasing travel distance, the lateral plume boundaries are smoothed, resulting in increased probability of intermediate concentrations. Likewise, averaging the concentration in a larger sampling volume, as typically done in field measurements, leads to higher probabilities of intermediate concentrations. We present semianalytical results of concentration pdf's for measurements with point-like or larger support volumes based on stochastic theory applied to stationary media. To this end, we employ a reversed auxiliary transport problem, in which we use analytical expressions for first and second central spatial lateral moments with an assumed Gaussian pdf for the uncertainty of the first lateral moment and Gauss-like shapes in individual cross sections. The resulting concentration pdf can be reasonably fitted by beta distributions. The results are compared to Monte Carlo simulations of flow and steady state transport in 3-D heterogeneous domains. In both methods the shape of the concentration pdf changes with distance to the contaminant source: Near the source, the distribution is multimodal, whereas it becomes a unimodal beta distribution far away from the contaminant source
NASA Astrophysics Data System (ADS)
Lei, Youming; Zheng, Fan
2016-12-01
Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.
Lei, Youming; Zheng, Fan
2016-12-01
Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.
Nonparametric Estimation by the Method of Sieves.
1983-07-01
high speed memory to which Accomando has added a board with 64k 16-bit words. The programs will reconstruct a 60x60 phantom in about fifteen or twenty...1971. 8. Budingere T. F.. Gullberg. G. T., and Huesman. R. H., Emission computed tomography, chapter 5 in J&&" Reconstrution f= Prjeins; Im&lementation...section reconstrution . Phys. Med. Biol. 22. 511-521& 1977. 60 29. Kronmal, R. and Tarter. M., The estimation of probability densities and cumulatives by
NASA Astrophysics Data System (ADS)
Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru
2015-10-01
An integrated method of a proper orthogonal decomposition based reduced-order model (ROM) and data assimilation is proposed for the real-time prediction of an unsteady flow field. In this paper, a particle filter (PF) and an ensemble Kalman filter (EnKF) are compared for data assimilation and the difference in the predicted flow fields is evaluated focusing on the probability density function (PDF) of the model variables. The proposed method is demonstrated using identical twin experiments of an unsteady flow field around a circular cylinder at the Reynolds number of 1000. The PF and EnKF are employed to estimate temporal coefficients of the ROM based on the observed velocity components in the wake of the circular cylinder. The prediction accuracy of ROM-PF is significantly better than that of ROM-EnKF due to the flexibility of PF for representing a PDF compared to EnKF. Furthermore, the proposed method reproduces the unsteady flow field several orders faster than the reference numerical simulation based on the Navier-Stokes equations.
NASA Astrophysics Data System (ADS)
Rebola, João L.; Cartaxo, Adolfo V. T.
The influence of the concatenation of arbitrary optical multiplexers/demultiplexers (MUX/DEMUXs) on the probability density function (PDF) of the output current of a transparent optical network is assessed. All PDF results obtained analytically are compared with estimates from Monte Carlo simulation and an excellent agreement is achieved. The non-Gaussian behavior of the PDFs, previously reported by other authors for square-law detectors, is significantly enhanced with the number of nodes increase due to the noise accumulation along the cascade of MUX/DEMUXs. The increase of the MUX/DEMUXs bandwidth and detuning also enhances the PDFs non-Gaussian behavior. The PDF shape variation with the detuning depends strongly on the number of nodes. Explanations for the Gaussian approximation (GA) accuracy on the assessment of the performance of a concatenation of optical MUX/DEMUXs are also provided. For infinite extinction ratio and tuned MUX/DEMUXs, the GA error probabilities are, in general, pessimistic, due to the inaccurate estimation of the error probability for both bits. For low extinction ratio, the GA is very accurate due to a balance between the error probabilities estimated for the bits "1" and "0." With the detuning increase, the GA estimates can become optimistic.
Particle number and probability density functional theory and A-representability.
Pan, Xiao-Yin; Sahni, Viraht
2010-04-28
In Hohenberg-Kohn density functional theory, the energy E is expressed as a unique functional of the ground state density rho(r): E = E[rho] with the internal energy component F(HK)[rho] being universal. Knowledge of the functional F(HK)[rho] by itself, however, is insufficient to obtain the energy: the particle number N is primary. By emphasizing this primacy, the energy E is written as a nonuniversal functional of N and probability density p(r): E = E[N,p]. The set of functions p(r) satisfies the constraints of normalization to unity and non-negativity, exists for each N; N = 1, ..., infinity, and defines the probability density or p-space. A particle number N and probability density p(r) functional theory is constructed. Two examples for which the exact energy functionals E[N,p] are known are provided. The concept of A-representability is introduced, by which it is meant the set of functions Psi(p) that leads to probability densities p(r) obtained as the quantum-mechanical expectation of the probability density operator, and which satisfies the above constraints. We show that the set of functions p(r) of p-space is equivalent to the A-representable probability density set. We also show via the Harriman and Gilbert constructions that the A-representable and N-representable probability density p(r) sets are equivalent.
NASA Astrophysics Data System (ADS)
Angraini, Lily Maysari; Suparmi, Variani, Viska Inda
2010-12-01
SUSY quantum mechanics can be applied to solve Schrodinger equation for high dimensional system that can be reduced into one dimensional system and represented in lowering and raising operators. Lowering and raising operators can be obtained using relationship between original Hamiltonian equation and the (super) potential equation. In this paper SUSY quantum mechanics is used as a method to obtain the wave function and the energy level of the Modified Poschl Teller potential. The graph of wave function equation and probability density is simulated by using Delphi 7.0 programming language. Finally, the expectation value of quantum mechanics operator could be calculated analytically using integral form or probability density graph resulted by the programming.
Angraini, Lily Maysari; Suparmi,; Variani, Viska Inda
2010-12-23
SUSY quantum mechanics can be applied to solve Schrodinger equation for high dimensional system that can be reduced into one dimensional system and represented in lowering and raising operators. Lowering and raising operators can be obtained using relationship between original Hamiltonian equation and the (super) potential equation. In this paper SUSY quantum mechanics is used as a method to obtain the wave function and the energy level of the Modified Poschl Teller potential. The graph of wave function equation and probability density is simulated by using Delphi 7.0 programming language. Finally, the expectation value of quantum mechanics operator could be calculated analytically using integral form or probability density graph resulted by the programming.
Approximation to the Probability Density at the Output of a Photmultiplier Tube
NASA Technical Reports Server (NTRS)
Stokey, R. J.; Lee, P. J.
1983-01-01
The probability density of the integrated output of a photomultiplier tube (PMT) is approximated by the Gaussian, Rayleigh, and Gamma probability densities. The accuracy of the approximations depends on the signal energy alpha: the Gamma distribution is accurate for all alpha, the Raleigh distribution is accurate for small alpha (approximate or less than 1 photon) and the Gaussian distribution is accurate for large alpha (approximate or greater than 10 photons).
NASA Astrophysics Data System (ADS)
Lu, C.; Liu, Y.; Niu, S.; Vogelmann, A. M.
2012-12-01
In situ aircraft cumulus observations from the RACORO field campaign are used to estimate entrainment rate for individual clouds using a recently developed mixing fraction approach. The entrainment rate is computed based on the observed state of the cloud core and the state of the air that is laterally mixed into the cloud at its edge. The computed entrainment rate decreases when the air is entrained from increasing distance from the cloud core edge; this is because the air farther away from cloud edge is drier than the neighboring air that is within the humid shells around cumulus clouds. Probability density functions of entrainment rate are well fitted by lognormal distributions at different heights above cloud base for different dry air sources (i.e., different source distances from the cloud core edge). Such lognormal distribution functions are appropriate for inclusion into future entrainment rate parameterization in large scale models. To the authors' knowledge, this is the first time that probability density functions of entrainment rate have been obtained in shallow cumulus clouds based on in situ observations. The reason for the wide spread of entrainment rate is that the observed clouds are affected by entrainment mixing processes to different extents, which is verified by the relationships between the entrainment rate and cloud microphysics/dynamics. The entrainment rate is negatively correlated with liquid water content and cloud droplet number concentration due to the dilution and evaporation in entrainment mixing processes. The entrainment rate is positively correlated with relative dispersion (i.e., ratio of standard deviation to mean value) of liquid water content and droplet size distributions, consistent with the theoretical expectation that entrainment mixing processes are responsible for microphysics fluctuations and spectral broadening. The entrainment rate is negatively correlated with vertical velocity and dissipation rate because entrainment
Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei
2016-01-01
Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851
NASA Astrophysics Data System (ADS)
Bakosi, J.; Franzese, P.; Boybeyi, Z.
2007-11-01
Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbin's [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. Single-point velocity and concentration statistics are compared to direct numerical simulation and experimental data at Reτ=1080 based on the friction velocity and the channel half width. The joint model accurately reproduces a wide variety of conditional and unconditional statistics in both physical and composition space.
Development and evaluation of probability density functions for a set of human exposure factors
Maddalena, R.L.; McKone, T.E.; Bodnar, A.; Jacobson, J.
1999-06-01
The purpose of this report is to describe efforts carried out during 1998 and 1999 at the Lawrence Berkeley National Laboratory to assist the U.S. EPA in developing and ranking the robustness of a set of default probability distributions for exposure assessment factors. Among the current needs of the exposure-assessment community is the need to provide data for linking exposure, dose, and health information in ways that improve environmental surveillance, improve predictive models, and enhance risk assessment and risk management (NAS, 1994). The U.S. Environmental Protection Agency (EPA) Office of Emergency and Remedial Response (OERR) plays a lead role in developing national guidance and planning future activities that support the EPA Superfund Program. OERR is in the process of updating its 1989 Risk Assessment Guidance for Superfund (RAGS) as part of the EPA Superfund reform activities. Volume III of RAGS, when completed in 1999 will provide guidance for conducting probabilistic risk assessments. This revised document will contain technical information including probability density functions (PDFs) and methods used to develop and evaluate these PDFs. The PDFs provided in this EPA document are limited to those relating to exposure factors.
Probability density functions of the average and difference intensities of Friedel opposites.
Shmueli, U; Flack, H D
2010-11-01
Trigonometric series for the average (A) and difference (D) intensities of Friedel opposites were carefully rederived and were normalized to minimize their dependence on sin(theta)/lambda. Probability density functions (hereafter p.d.f.s) of these series were then derived by the Fourier method [Shmueli, Weiss, Kiefer & Wilson (1984). Acta Cryst. A40, 651-660] and their expressions, which admit any chemical composition of the unit-cell contents, were obtained for the space group P1. Histograms of A and D were then calculated for an assumed random-structure model and for 3135 Friedel pairs of a published solved crystal structure, and were compared with the p.d.f.s after the latter were scaled up to the histograms. Good agreement was obtained for the random-structure model and a qualitative one for the published solved structure. The results indicate that the residual discrepancy is mainly due to the presumed statistical independence of the p.d.f.'s characteristic function on the contributions of the interatomic vectors.
Probability density function of a puff dispersing from the wall of a turbulent channel
NASA Astrophysics Data System (ADS)
Nguyen, Quoc; Papavassiliou, Dimitrios
2015-11-01
Study of dispersion of passive contaminants in turbulence has proved to be helpful in understanding fundamental heat and mass transfer phenomena. Many simulation and experimental works have been carried out to locate and track motions of scalar markers in a flow. One method is to combine Direct Numerical Simulation (DNS) and Lagrangian Scalar Tracking (LST) to record locations of markers. While this has proved to be useful, high computational cost remains a concern. In this study, we develop a model that could reproduce results obtained by DNS and LST for turbulent flow. Puffs of markers with different Schmidt numbers were released into a flow field at a frictional Reynolds number of 150. The point of release was at the channel wall, so that both diffusion and convection contribute to the puff dispersion pattern, defining different stages of dispersion. Based on outputs from DNS and LST, we seek the most suitable and feasible probability density function (PDF) that represents distribution of markers in the flow field. The PDF would play a significant role in predicting heat and mass transfer in wall turbulence, and would prove to be helpful where DNS and LST are not always available.
NASA Technical Reports Server (NTRS)
Smith, N. S. A.; Frolov, S. M.; Bowman, C. T.
1996-01-01
Two types of mixing sub-models are evaluated in connection with a joint-scalar probability density function method for turbulent nonpremixed combustion. Model calculations are made and compared to simulation results for homogeneously distributed methane-air reaction zones mixing and reacting in decaying turbulence within a two-dimensional enclosed domain. The comparison is arranged to ensure that both the simulation and model calculations a) make use of exactly the same chemical mechanism, b) do not involve non-unity Lewis number transport of species, and c) are free from radiation loss. The modified Curl mixing sub-model was found to provide superior predictive accuracy over the simple relaxation-to-mean submodel in the case studied. Accuracy to within 10-20% was found for global means of major species and temperature; however, nitric oxide prediction accuracy was lower and highly dependent on the choice of mixing sub-model. Both mixing submodels were found to produce non-physical mixing behavior for mixture fractions removed from the immediate reaction zone. A suggestion for a further modified Curl mixing sub-model is made in connection with earlier work done in the field.
Error Estimates for Mixed Methods.
1979-03-01
This paper presents abstract error estimates for mixed methods for the approximate solution of elliptic boundary value problems. These estimates are...then applied to obtain quasi-optimal error estimates in the usual Sobolev norms for four examples: three mixed methods for the biharmonic problem and a mixed method for 2nd order elliptic problems. (Author)
Fading probability density function of free-space optical communication channels with pointing error
NASA Astrophysics Data System (ADS)
Zhao, Zhijun; Liao, Rui
2011-06-01
The turbulent atmosphere causes wavefront distortion, beam wander, and beam broadening of a laser beam. These effects result in average power loss and instantaneous power fading at the receiver aperture and thus degrade performance of a free-space optical (FSO) communication system. In addition to the atmospheric turbulence, a FSO communication system may also suffer from laser beam pointing error. The pointing error causes excessive power loss and power fading. This paper proposes and studies an analytical method for calculating the FSO channel fading probability density function (pdf) induced by both atmospheric turbulence and pointing error. This method is based on the fast-tracked laser beam fading profile and the joint effects of beam wander and pointing error. In order to evaluate the proposed analytical method, large-scale numerical wave-optics simulations are conducted. Three types of pointing errors are studied , namely, the Gaussian random pointing error, the residual tracking error, and the sinusoidal sway pointing error. The FSO system employs a collimated Gaussian laser beam propagating along a horizontal path. The propagation distances range from 0.25 miles to 2.5 miles. The refractive index structure parameter is chosen to be Cn2 = 5×10-15m-2/3 and Cn2 = 5×10-13m-2/3. The studied cases cover from weak to strong fluctuations. The fading pdf curves of channels with pointing error calculated using the analytical method match accurately the corresponding pdf curves obtained directly from large-scale wave-optics simulations. They also give accurate average bit-error-rate (BER) curves and outage probabilities. Both the lognormal and the best-fit gamma-gamma fading pdf curves deviate from those of corresponding simulation curves, and they produce overoptimistic average BER curves and outage probabilities.
Generation of time histories with a specified auto spectral density and probability density function
Smallwood, D.O.
1996-08-01
It is recognized that some dynamic and noise environments are characterized by time histories which are not Gaussian. An example is high intensity acoustic noise. Another example is some transportation vibration. A better simulation of these environments can be generated if a zero mean non-Gaussian time history can be reproduced with a specified auto (or power) spectral density (ASD or PSD) and a specified probability density function (pdf). After the required time history is synthesized, the waveform can be used for simulation purposes. For example, modem waveform reproduction techniques can be used to reproduce the waveform on electrodynamic or electrohydraulic shakers. Or the waveforms can be used in digital simulations. A method is presented for the generation of realizations of zero mean non-Gaussian random time histories with a specified ASD, and pdf. First a Gaussian time history with the specified auto (or power) spectral density (ASD) is generated. A monotonic nonlinear function relating the Gaussian waveform to the desired realization is then established based on the Cumulative Distribution Function (CDF) of the desired waveform and the known CDF of a Gaussian waveform. The established function is used to transform the Gaussian waveform to a realization of the desired waveform. Since the transformation preserves the zero-crossings and peaks of the original Gaussian waveform, and does not introduce any substantial discontinuities, the ASD is not substantially changed. Several methods are available to generate a realization of a Gaussian distributed waveform with a known ASD. The method of Smallwood and Paez (1993) is an example. However, the generation of random noise with a specified ASD but with a non-Gaussian distribution is less well known.
Dynamic Graphics in Excel for Teaching Statistics: Understanding the Probability Density Function
ERIC Educational Resources Information Center
Coll-Serrano, Vicente; Blasco-Blasco, Olga; Alvarez-Jareno, Jose A.
2011-01-01
In this article, we show a dynamic graphic in Excel that is used to introduce an important concept in our subject, Statistics I: the probability density function. This interactive graphic seeks to facilitate conceptual understanding of the main aspects analysed by the learners.
Kernel density estimator methods for Monte Carlo radiation transport
NASA Astrophysics Data System (ADS)
Banerjee, Kaushik
In this dissertation, the Kernel Density Estimator (KDE), a nonparametric probability density estimator, is studied and used to represent global Monte Carlo (MC) tallies. KDE is also employed to remove the singularities from two important Monte Carlo tallies, namely point detector and surface crossing flux tallies. Finally, KDE is also applied to accelerate the Monte Carlo fission source iteration for criticality problems. In the conventional MC calculation histograms are used to represent global tallies which divide the phase space into multiple bins. Partitioning the phase space into bins can add significant overhead to the MC simulation and the histogram provides only a first order approximation to the underlying distribution. The KDE method is attractive because it can estimate MC tallies in any location within the required domain without any particular bin structure. Post-processing of the KDE tallies is sufficient to extract detailed, higher order tally information for an arbitrary grid. The quantitative and numerical convergence properties of KDE tallies are also investigated and they are shown to be superior to conventional histograms as well as the functional expansion tally developed by Griesheimer. Monte Carlo point detector and surface crossing flux tallies are two widely used tallies but they suffer from an unbounded variance. As a result, the central limit theorem can not be used for these tallies to estimate confidence intervals. By construction, KDE tallies can be directly used to estimate flux at a point but the variance of this point estimate does not converge as 1/N, which is not unexpected for a point quantity. However, an improved approach is to modify both point detector and surface crossing flux tallies directly by using KDE within a variance reduction approach by taking advantage of the fact that KDE estimates the underlying probability density function. This methodology is demonstrated by several numerical examples and demonstrates that
NASA Astrophysics Data System (ADS)
Coclite, A.; Pascazio, G.; De Palma, P.; Cutrone, L.
2016-07-01
Flamelet-Progress-Variable (FPV) combustion models allow the evaluation of all thermochemical quantities in a reacting flow by computing only the mixture fraction Z and a progress variable C. When using such a method to predict turbulent combustion in conjunction with a turbulence model, a probability density function (PDF) is required to evaluate statistical averages (e. g., Favre averages) of chemical quantities. The choice of the PDF is a compromise between computational costs and accuracy level. The aim of this paper is to investigate the influence of the PDF choice and its modeling aspects to predict turbulent combustion. Three different models are considered: the standard one, based on the choice of a β-distribution for Z and a Dirac-distribution for C; a model employing a β-distribution for both Z and C; and the third model obtained using a β-distribution for Z and the statistically most likely distribution (SMLD) for C. The standard model, although widely used, does not take into account the interaction between turbulence and chemical kinetics as well as the dependence of the progress variable not only on its mean but also on its variance. The SMLD approach establishes a systematic framework to incorporate informations from an arbitrary number of moments, thus providing an improvement over conventionally employed presumed PDF closure models. The rational behind the choice of the three PDFs is described in some details and the prediction capability of the corresponding models is tested vs. well-known test cases, namely, the Sandia flames, and H2-air supersonic combustion.
NASA Technical Reports Server (NTRS)
Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor)
2012-01-01
This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices.
Derivation of an eigenvalue probability density function relating to the Poincaré disk
NASA Astrophysics Data System (ADS)
Forrester, Peter J.; Krishnapur, Manjunath
2009-09-01
A result of Zyczkowski and Sommers (2000 J. Phys. A: Math. Gen. 33 2045-57) gives the eigenvalue probability density function for the top N × N sub-block of a Haar distributed matrix from U(N + n). In the case n >= N, we rederive this result, starting from knowledge of the distribution of the sub-blocks, introducing the Schur decomposition and integrating over all variables except the eigenvalues. The integration is done by identifying a recursive structure which reduces the dimension. This approach is inspired by an analogous approach which has been recently applied to determine the eigenvalue probability density function for random matrices A-1B, where A and B are random matrices with entries standard complex normals. We relate the eigenvalue distribution of the sub-blocks to a many-body quantum state, and to the one-component plasma, on the pseudosphere.
NASA Astrophysics Data System (ADS)
Majumdar, Arun K.; Luna, Carlos E.; Idell, Paul S.
2007-09-01
A new method of reconstructing and predicting an unknown probability density function (PDF) characterizing the statistics of intensity fluctuations of optical beams propagating through atmospheric turbulence is presented in this paper. The method is based on a series expansion of generalized Laguerre polynomials ; the expansion coefficients are expressed in terms of the higher-order intensity moments of intensity statistics. This method generates the PDF from the data moments without any prior knowledge of specific statistics and converges smoothly. The utility of reconstructed PDF relevant to free-space laser communication in terms of calculating the average bit error rate and probability of fading is pointed out. Simulated numerical results are compared with some known non-Gaussian test PDFs: Log-Normal, Rice-Nakagami and Gamma-Gamma distributions and show excellent agreement obtained by the method developed. The accuracy of the reconstructed PDF is also evaluated.
A Projection and Density Estimation Method for Knowledge Discovery
Stanski, Adam; Hellwich, Olaf
2012-01-01
A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features. PMID:23049675
PDV Uncertainty Estimation & Methods Comparison
Machorro, E.
2011-11-01
Several methods are presented for estimating the rapidly changing instantaneous frequency of a time varying signal that is contaminated by measurement noise. Useful a posteriori error estimates for several methods are verified numerically through Monte Carlo simulation. However, given the sampling rates of modern digitizers, sub-nanosecond variations in velocity are shown to be reliably measurable in most (but not all) cases. Results support the hypothesis that in many PDV regimes of interest, sub-nanosecond resolution can be achieved.
NASA Astrophysics Data System (ADS)
Zhao, Zhijun; Liao, Rui
2011-03-01
Free-space optical (FSO) communication systems suffer from average power loss and instantaneous power fading due to the atmospheric turbulence. The channel fading probability density function (pdf) is of critical importance for FSO communication system design and evaluation. The performance and reliability of FSO communication systems can be greatly enhanced if fast-tacking devices are employed at the transmitter in order to compensate laser beam wander at the receiver aperture. The fast-tracking method is especially effective when communication distance is long. This paper studies the fading probability density functions of both fast-tracked and untracked FSO communication channels. Large-scale wave-optics simulations are conducted for both tracked and untracked lasers. In the simulations, the Kolmogorov spectrum is adopted, and it is assumed that the outer scale is infinitely large and the inner scale is negligibly small. The fading pdfs of both fast-tracked and untracked FSO channels are obtained from the simulations. Results show that the fast-tracked channel fading can be accurately modeled as gamma-distributed if receiver aperture size is smaller than the coherence radius. An analytical method is given for calculating the untracked fading pdfs of both point-like and finite-size receiver apertures from the fast-tracked fading pdf. For point-like apertures, the analytical method gives pdfs close to the well-known gamma-gamma pdfs if off-axis effects are omitted in the formulation. When off-axis effects are taken into consideration, the untracked pdfs obtained using the analytical method fit the simulation pdfs better than gamma-gamma distributions for point-like apertures, and closely fit the simulation pdfs for finite-size apertures where gamma-gamma pdfs deviate from those of the simulations significantly.
Carr, Thomas W
2017-02-01
In an SIRS compartment model for a disease we consider the effect of different probability distributions for remaining immune. We show that to first approximation the first three moments of the corresponding probability densities are sufficient to well describe oscillatory solutions corresponding to recurrent epidemics. Specifically, increasing the fraction who lose immunity, increasing the mean immunity time, and decreasing the heterogeneity of the population all favor the onset of epidemics and increase their severity. We consider six different distributions, some symmetric about their mean and some asymmetric, and show that by tuning their parameters such that they have equivalent moments that they all exhibit equivalent dynamical behavior.
Eulerian Mapping Closure Approach for Probability Density Function of Concentration in Shear Flows
NASA Technical Reports Server (NTRS)
He, Guowei; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
The Eulerian mapping closure approach is developed for uncertainty propagation in computational fluid mechanics. The approach is used to study the Probability Density Function (PDF) for the concentration of species advected by a random shear flow. An analytical argument shows that fluctuation of the concentration field at one point in space is non-Gaussian and exhibits stretched exponential form. An Eulerian mapping approach provides an appropriate approximation to both convection and diffusion terms and leads to a closed mapping equation. The results obtained describe the evolution of the initial Gaussian field, which is in agreement with direct numerical simulations.
NASA Astrophysics Data System (ADS)
Akhmediev, N.; Soto-Crespo, J. M.; Devine, N.
2016-08-01
Turbulence in integrable systems exhibits a noticeable scientific advantage: it can be expressed in terms of the nonlinear modes of these systems. Whether the majority of the excitations in the system are breathers or solitons defines the properties of the turbulent state. In the two extreme cases we can call such states "breather turbulence" or "soliton turbulence." The number of rogue waves, the probability density functions of the chaotic wave fields, and their physical spectra are all specific for each of these two situations. Understanding these extreme cases also helps in studies of mixed turbulent states when the wave field contains both solitons and breathers, thus revealing intermediate characteristics.
Akhmediev, N; Soto-Crespo, J M; Devine, N
2016-08-01
Turbulence in integrable systems exhibits a noticeable scientific advantage: it can be expressed in terms of the nonlinear modes of these systems. Whether the majority of the excitations in the system are breathers or solitons defines the properties of the turbulent state. In the two extreme cases we can call such states "breather turbulence" or "soliton turbulence." The number of rogue waves, the probability density functions of the chaotic wave fields, and their physical spectra are all specific for each of these two situations. Understanding these extreme cases also helps in studies of mixed turbulent states when the wave field contains both solitons and breathers, thus revealing intermediate characteristics.
NASA Astrophysics Data System (ADS)
Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo
2016-07-01
Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.
NASA Astrophysics Data System (ADS)
Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo
2017-02-01
Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.
Parameter estimation of social forces in pedestrian dynamics models via a probabilistic method.
Corbetta, Alessandro; Muntean, Adrian; Vafayi, Kiamars
2015-04-01
Focusing on a specific crowd dynamics situation, including real life experiments and measurements, our paper targets a twofold aim: (1) we present a Bayesian probabilistic method to estimate the value and the uncertainty (in the form of a probability density function) of parameters in crowd dynamic models from the experimental data; and (2) we introduce a fitness measure for the models to classify a couple of model structures (forces) according to their fitness to the experimental data, preparing the stage for a more general model-selection and validation strategy inspired by probabilistic data analysis. Finally, we review the essential aspects of our experimental setup and measurement technique.
NASA Astrophysics Data System (ADS)
Wacławczyk, M.; Grebenev, V. N.; Oberlack, M.
2017-04-01
The problem of turbulence statistics described by the Lundgren–Monin–Novikov (LMN) hierarchy of integro-differential equations is studied in terms of its group properties. For this we perform a Lie group analysis of a truncated LMN chain which presents the first two equations in an infinite set of integro-differential equations for the multi-point probability density functions (pdf’s) of velocity. A complete set of point transformations is derived for the one-point pdf’s and the independent variables: sample space of velocity, space and time. For this purpose we use a direct method based on the canonical Lie–Bäcklund operator. Due to the one-way coupling of correlation equations, the present results are complete in the sense that no additional symmetries exist for the first leading equation, even if the full infinite hierarchy is considered.
NASA Astrophysics Data System (ADS)
Anderson, Johan; Johansson, Jonas
2016-12-01
An analytical derivation of the probability density function (PDF) tail describing the strongly correlated interface growth governed by the nonlinear Kardar-Parisi-Zhang equation is provided. The PDF tail exactly coincides with a Tracy-Widom distribution i.e. a PDF tail proportional to \\exp ≤ft(-cw23/2\\right) , where w 2 is the the width of the interface. The PDF tail is computed by the instanton method in the strongly non-linear regime within the Martin-Siggia-Rose framework using a careful treatment of the non-linear interactions. In addition, the effect of spatial dimensions on the PDF tail scaling is discussed. This gives a novel approach to understand the rightmost PDF tail of the interface width distribution and the analysis suggests that there is no upper critical dimension.
Ensemble Averaged Probability Density Function (APDF) for Compressible Turbulent Reacting Flows
NASA Technical Reports Server (NTRS)
Shih, Tsan-Hsing; Liu, Nan-Suey
2012-01-01
In this paper, we present a concept of the averaged probability density function (APDF) for studying compressible turbulent reacting flows. The APDF is defined as an ensemble average of the fine grained probability density function (FG-PDF) with a mass density weighting. It can be used to exactly deduce the mass density weighted, ensemble averaged turbulent mean variables. The transport equation for APDF can be derived in two ways. One is the traditional way that starts from the transport equation of FG-PDF, in which the compressible Navier- Stokes equations are embedded. The resulting transport equation of APDF is then in a traditional form that contains conditional means of all terms from the right hand side of the Navier-Stokes equations except for the chemical reaction term. These conditional means are new unknown quantities that need to be modeled. Another way of deriving the transport equation of APDF is to start directly from the ensemble averaged Navier-Stokes equations. The resulting transport equation of APDF derived from this approach appears in a closed form without any need for additional modeling. The methodology of ensemble averaging presented in this paper can be extended to other averaging procedures: for example, the Reynolds time averaging for statistically steady flow and the Reynolds spatial averaging for statistically homogeneous flow. It can also be extended to a time or spatial filtering procedure to construct the filtered density function (FDF) for the large eddy simulation (LES) of compressible turbulent reacting flows.
Probability density of the empirical wavelet coefficients of a noisy chaos
NASA Astrophysics Data System (ADS)
Garcin, Matthieu; Guégan, Dominique
2014-05-01
We are interested in the random empirical wavelet coefficients of a noisy signal when this signal is a unidimensional or multidimensional chaos. More precisely we provide an expression of the conditional probability density of such coefficients, given a discrete observation grid. The noise is assumed to be described by a symmetric alpha-stable random variable. If the noise is a dynamic noise, then we present the exact expression of the probability density of each wavelet coefficient of the noisy signal. If we face a measurement noise, then the noise has a non-linear influence and we propose two approximations. The first one relies on a Taylor expansion whereas the second one, relying on an Edgeworth expansion, improves the first general Taylor approximation if the cumulants of the noise are defined. We give some illustrations of these theoretical results for the logistic map, the tent map and a multidimensional chaos, the Hénon map, disrupted by a Gaussian or a Cauchy noise.
Weatherbee, Andrew; Sugita, Mitsuro; Bizheva, Kostadinka; Popov, Ivan; Vitkin, Alex
2016-06-15
The distribution of backscattered intensities as described by the probability density function (PDF) of tissue-scattered light contains information that may be useful for tissue assessment and diagnosis, including characterization of its pathology. In this Letter, we examine the PDF description of the light scattering statistics in a well characterized tissue-like particulate medium using optical coherence tomography (OCT). It is shown that for low scatterer density, the governing statistics depart considerably from a Gaussian description and follow the K distribution for both OCT amplitude and intensity. The PDF formalism is shown to be independent of the scatterer flow conditions; this is expected from theory, and suggests robustness and motion independence of the OCT amplitude (and OCT intensity) PDF metrics in the context of potential biomedical applications.
Methods for Cloud Cover Estimation
NASA Technical Reports Server (NTRS)
Glackin, D. L.; Huning, J. R.; Smith, J. H.; Logan, T. L.
1984-01-01
Several methods for cloud cover estimation are described relevant to assessing the performance of a ground-based network of solar observatories. The methods rely on ground and satellite data sources and provide meteorological or climatological information. One means of acquiring long-term observations of solar oscillations is the establishment of a ground-based network of solar observatories. Criteria for station site selection are: gross cloudiness, accurate transparency information, and seeing. Alternative methods for computing this duty cycle are discussed. The cycle, or alternatively a time history of solar visibility from the network, can then be input to a model to determine the effect of duty cycle on derived solar seismology parameters. Cloudiness from space is studied to examine various means by which the duty cycle might be computed. Cloudiness, and to some extent transparency, can potentially be estimated from satellite data.
NASA Astrophysics Data System (ADS)
Hadjiagapiou, Ioannis A.
2014-03-01
The magnetic systems with disorder form an important class of systems, which are under intensive studies, since they reflect real systems. Such a class of systems is the spin glass one, which combines randomness and frustration. The Sherrington-Kirkpatrick Ising spin glass with random couplings in the presence of a random magnetic field is investigated in detail within the framework of the replica method. The two random variables (exchange integral interaction and random magnetic field) are drawn from a joint Gaussian probability density function characterized by a correlation coefficient ρ. The thermodynamic properties and phase diagrams are studied with respect to the natural parameters of both random components of the system contained in the probability density. The de Almeida-Thouless line is explored as a function of temperature, ρ and other system parameters. The entropy for zero temperature as well as for non zero temperatures is partly negative or positive, acquiring positive branches as h0 increases.
Translating CFC-based piston ages into probability density functions of ground-water age in karst
Long, A.J.; Putnam, L.D.
2006-01-01
Temporal age distributions are equivalent to probability density functions (PDFs) of transit time. The type and shape of a PDF provides important information related to ground-water mixing at the well or spring and the complex nature of flow networks in karst aquifers. Chlorofluorocarbon (CFC) concentrations measured for samples from 12 locations in the karstic Madison aquifer were used to evaluate the suitability of various PDF types for this aquifer. Parameters of PDFs could not be estimated within acceptable confidence intervals for any of the individual sites. Therefore, metrics derived from CFC-based apparent ages were used to evaluate results of PDF modeling in a more general approach. The ranges of these metrics were established as criteria against which families of PDFs could be evaluated for their applicability to different parts of the aquifer. Seven PDF types, including five unimodal and two bimodal models, were evaluated. Model results indicate that unimodal models may be applicable to areas close to conduits that have younger piston (i.e., apparent) ages and that bimodal models probably are applicable to areas farther from conduits that have older piston ages. The two components of a bimodal PDF are interpreted as representing conduit and diffuse flow, and transit times of as much as two decades may separate these PDF components. Areas near conduits may be dominated by conduit flow, whereas areas farther from conduits having bimodal distributions probably have good hydraulic connection to both diffuse and conduit flow. ?? 2006 Elsevier B.V. All rights reserved.
Multi-Detection Events, Probability Density Functions, and Reduced Location Area
Eslinger, Paul W.; Schrom, Brian T.
2016-03-01
Abstract Several efforts have been made in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) community to assess the benefits of combining detections of radionuclides to improve the location estimates available from atmospheric transport modeling (ATM) backtrack calculations. We present a Bayesian estimation approach rather than a simple dilution field of regard approach to allow xenon detections and non-detections to be combined mathematically. This system represents one possible probabilistic approach to radionuclide event formation. Application of this method to a recent interesting radionuclide event shows a substantial reduction in the location uncertainty of that event.
Korotkova, Olga; Avramov-Zamurovic, Svetlana; Malek-Madani, Reza; Nelson, Charles
2011-10-10
A number of field experiments measuring the fluctuating intensity of a laser beam propagating along horizontal paths in the maritime environment is performed over sub-kilometer distances at the United States Naval Academy. Both above the ground and over the water links are explored. Two different detection schemes, one photographing the beam on a white board, and the other capturing the beam directly using a ccd sensor, gave consistent results. The probability density function (pdf) of the fluctuating intensity is reconstructed with the help of two theoretical models: the Gamma-Gamma and the Gamma-Laguerre, and compared with the intensity's histograms. It is found that the on-ground experimental results are in good agreement with theoretical predictions. The results obtained above the water paths lead to appreciable discrepancies, especially in the case of the Gamma-Gamma model. These discrepancies are attributed to the presence of the various scatterers along the path of the beam, such as water droplets, aerosols and other airborne particles. Our paper's main contribution is providing a methodology for computing the pdf function of the laser beam intensity in the maritime environment using field measurements.
On the evolution of the density probability density function in strongly self-gravitating systems
Girichidis, Philipp; Konstandin, Lukas; Klessen, Ralf S.; Whitworth, Anthony P.
2014-02-01
The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple approximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse results in a power-law tail on the high-density side of the PDF. The slope quickly asymptotes to the functional form P{sub V} (ρ)∝ρ{sup –1.54} for the (volume-weighted) PDF and P{sub M} (ρ)∝ρ{sup –0.54} for the corresponding mass-weighted distribution. From the simple approximation of the PDF we derive analytic descriptions for mass accretion, finding that dynamically quiet systems with narrow density PDFs lead to retarded star formation and low star formation rates (SFRs). Conversely, strong turbulent motions that broaden the PDF accelerate the collapse causing a bursting mode of star formation. Finally, we compare our theoretical work with observations. The measured SFRs are consistent with our model during the early phases of the collapse. Comparison of observed column density PDFs with those derived from our model suggests that observed star-forming cores are roughly in free-fall.
On the Evolution of the Density Probability Density Function in Strongly Self-gravitating Systems
NASA Astrophysics Data System (ADS)
Girichidis, Philipp; Konstandin, Lukas; Whitworth, Anthony P.; Klessen, Ralf S.
2014-02-01
The time evolution of the probability density function (PDF) of the mass density is formulated and solved for systems in free-fall using a simple approximate function for the collapse of a sphere. We demonstrate that a pressure-free collapse results in a power-law tail on the high-density side of the PDF. The slope quickly asymptotes to the functional form PV (ρ)vpropρ-1.54 for the (volume-weighted) PDF and PM (ρ)vpropρ-0.54 for the corresponding mass-weighted distribution. From the simple approximation of the PDF we derive analytic descriptions for mass accretion, finding that dynamically quiet systems with narrow density PDFs lead to retarded star formation and low star formation rates (SFRs). Conversely, strong turbulent motions that broaden the PDF accelerate the collapse causing a bursting mode of star formation. Finally, we compare our theoretical work with observations. The measured SFRs are consistent with our model during the early phases of the collapse. Comparison of observed column density PDFs with those derived from our model suggests that observed star-forming cores are roughly in free-fall.
Probability density function model equation for particle charging in a homogeneous dusty plasma.
Pandya, R V; Mashayek, F
2001-09-01
In this paper, we use the direct interaction approximation (DIA) to obtain an approximate integrodifferential equation for the probability density function (PDF) of charge (q) on dust particles in homogeneous dusty plasma. The DIA is used to solve the closure problem which appears in the PDF equation due to the interactions between the phase space density of plasma particles and the phase space density of dust particles. The equation simplifies to a differential form under the condition when the fluctuations in phase space density for plasma particles change very rapidly in time and is correlated for very short times. The result is a Fokker-Planck type equation with extra terms having third and fourth order differentials in q, which account for the discrete nature of distribution of plasma particles and the interaction between fluctuations. Approximate macroscopic equations for the time evolution of the average charge and the higher order moments of the fluctuations in charge on the dust particles are obtained from the differential PDF equation. These equations are computed, in the case of a Maxwellian plasma, to show the effect of density fluctuations of plasma particles on the statistics of dust charge.
Probability density functions of the stream flow discharge in linearized diffusion wave models
NASA Astrophysics Data System (ADS)
Chang, Ching-Min; Yeh, Hund-Der
2016-12-01
This article considers stream flow discharge moving through channels subject to the lateral inflow and described by a linearized diffusion wave equation. The variability of lateral inflow is manifested by random fluctuations in time, which is the only source of uncertainty as to flow discharge quantification. The stochastic nature of stream flow discharge is described by the probability density function (PDF) obtained using the theory of distributions. The PDF of the stream flow discharge depends on the hydraulic properties of the stream flow, such as the wave celerity and hydraulic diffusivity as well as the temporal correlation scale of the lateral inflow rate fluctuations. The focus in this analysis is placed on the influence of the temporal correlation scale and the wave celerity coefficient on the PDF of the flow discharge. The analysis demonstrates that a larger temporal correlation scale causes an increase of PDF of the lateral inflow rate and, in turn, the PDF of the flow discharge which is also affected positively by the wave celerity coefficient.
Ovchinnikov, Mikhail; Lim, Kyo-Sun Sunny; Larson, Vincent E.; Wong, May; Thayer-Calder, Katherine; Ghan, Steven J.
2016-11-05
Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.
Vertical overlap of probability density functions of cloud and precipitation hydrometeors
NASA Astrophysics Data System (ADS)
Ovchinnikov, Mikhail; Lim, Kyo-Sun Sunny; Larson, Vincent E.; Wong, May; Thayer-Calder, Katherine; Ghan, Steven J.
2016-11-01
Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of clouds and precipitation. When subcolumns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and cloud scheme called the Cloud Layers Unified by Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continental and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in cloud-resolving model (CRM) simulations of the same cases that explicitly predict the 3-D structure of cloud and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor types, as well as between PDFs of mass and number mixing ratios for each species—a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve cloud and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling cloud liquid and ice. These results suggest that to improve the overlap treatment in the subcolumn generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.
The probability density function in molecular gas in the G333 and Vela C molecular clouds
NASA Astrophysics Data System (ADS)
Cunningham, Maria
2015-08-01
The probability density function (PDF) is a simple analytical tool for determining the hierarchical spatial structure of molecular clouds. It has been used frequently in recent years with dust continuum emission, such as that from the Herschel space telescope and ALMA. These dust column density PDFs universally show a log-normal distribution in low column density gas, characteristic of unbound turbulent gas, and a power-law tail at high column densities, indicating the presence of gravitationally bound gas. We have recently conducted a PDF analysis of the molecular gas in the G333 and Vela C giant molecular cloud complexes, using transitions of CO, HCN, HNC, HCO+ and N2H+.The results show that CO and its isotopologues trace mostly the log-normal part of the PDF, while HCN and HCO+ trace both a log-normal part and a power law part to the distribution. On the other hand, HNC and N2H+ mostly trace only the power law tail. The difference between the PDFs of HCN and HNC is surprising, as is the similarity between HNC and the N2H+ PDFs. The most likely explanation for the similar distributions of HNC and N2H+ is that N2H+ is known to be enhanced in cool gas below 20K, where CO is depleted, while the reaction that forms HNC or HCN favours the former at similar low temperatures. The lack of evidence for a power law tail in 13CO and C18O, in conjunction for the results for the N2H+ PDF suggest that depletion of CO in the dense cores of these molecular clouds is significant. In conclusion, the PDF has proved to be a surprisingly useful tool for investigating not only the spatial distribution of molecular gas, but also the wide scale chemistry of molecular clouds.
NASA Astrophysics Data System (ADS)
Mysina, N. Yu; Maksimova, L. A.; Gorbatenko, B. B.; Ryabukho, V. P.
2015-10-01
Investigated are statistical properties of the phase difference of oscillations in speckle-fields at two points in the far-field diffraction region, with different shapes of the scatterer aperture. Statistical and spatial nonuniformity of the probability density function of the field phase difference is established. Numerical experiments show that, for the speckle-fields with an oscillating alternating-sign transverse correlation function, a significant nonuniformity of the probability density function of the phase difference in the correlation region of the field complex amplitude, with the most probable values 0 and p, is observed. A natural statistical interference experiment using Young diagrams has confirmed the results of numerical experiments.
Nonparametric estimation of plant density by the distance method
Patil, S.A.; Burnham, K.P.; Kovner, J.L.
1979-01-01
A relation between the plant density and the probability density function of the nearest neighbor distance (squared) from a random point is established under fairly broad conditions. Based upon this relationship, a nonparametric estimator for the plant density is developed and presented in terms of order statistics. Consistency and asymptotic normality of the estimator are discussed. An interval estimator for the density is obtained. The modifications of this estimator and its variance are given when the distribution is truncated. Simulation results are presented for regular, random and aggregated populations to illustrate the nonparametric estimator and its variance. A numerical example from field data is given. Merits and deficiencies of the estimator are discussed with regard to its robustness and variance.
NASA Technical Reports Server (NTRS)
Raju, M. S.
1998-01-01
The success of any solution methodology used in the study of gas-turbine combustor flows depends a great deal on how well it can model the various complex and rate controlling processes associated with the spray's turbulent transport, mixing, chemical kinetics, evaporation, and spreading rates, as well as convective and radiative heat transfer and other phenomena. The phenomena to be modeled, which are controlled by these processes, often strongly interact with each other at different times and locations. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. The influence of turbulence in a diffusion flame manifests itself in several forms, ranging from the so-called wrinkled, or stretched, flamelets regime to the distributed combustion regime, depending upon how turbulence interacts with various flame scales. Conventional turbulence models have difficulty treating highly nonlinear reaction rates. A solution procedure based on the composition joint probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices (such as extinction, blowoff limits, and emissions predictions) because it can account for nonlinear chemical reaction rates without making approximations. In an attempt to advance the state-of-the-art in multidimensional numerical methods, we at the NASA Lewis Research Center extended our previous work on the PDF method to unstructured grids, parallel computing, and sprays. EUPDF, which was developed by M.S. Raju of Nyma, Inc., was designed to be massively parallel and could easily be coupled with any existing gas-phase and/or spray solvers. EUPDF can use an unstructured mesh with mixed triangular, quadrilateral, and/or tetrahedral elements. The application of the PDF method showed favorable results when applied to several supersonic
Kinetic and dynamic probability-density-function descriptions of disperse turbulent two-phase flows.
Minier, Jean-Pierre; Profeta, Christophe
2015-11-01
This article analyzes the status of two classical one-particle probability density function (PDF) descriptions of the dynamics of discrete particles dispersed in turbulent flows. The first PDF formulation considers only the process made up by particle position and velocity Z(p)=(x(p),U(p)) and is represented by its PDF p(t; y(p),V(p)) which is the solution of a kinetic PDF equation obtained through a flux closure based on the Furutsu-Novikov theorem. The second PDF formulation includes fluid variables into the particle state vector, for example, the fluid velocity seen by particles Z(p)=(x(p),U(p),U(s)), and, consequently, handles an extended PDF p(t; y(p),V(p),V(s)) which is the solution of a dynamic PDF equation. For high-Reynolds-number fluid flows, a typical formulation of the latter category relies on a Langevin model for the trajectories of the fluid seen or, conversely, on a Fokker-Planck equation for the extended PDF. In the present work, a new derivation of the kinetic PDF equation is worked out and new physical expressions of the dispersion tensors entering the kinetic PDF equation are obtained by starting from the extended PDF and integrating over the fluid seen. This demonstrates that, under the same assumption of a Gaussian colored noise and irrespective of the specific stochastic model chosen for the fluid seen, the kinetic PDF description is the marginal of a dynamic PDF one. However, a detailed analysis reveals that kinetic PDF models of particle dynamics in turbulent flows described by statistical correlations constitute incomplete stand-alone PDF descriptions and, moreover, that present kinetic-PDF equations are mathematically ill posed. This is shown to be the consequence of the non-Markovian characteristic of the stochastic process retained to describe the system and the use of an external colored noise. Furthermore, developments bring out that well-posed PDF descriptions are essentially due to a proper choice of the variables selected to
Jian, Y; Yao, R; Mulnix, T; Jin, X; Carson, R E
2015-01-07
Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7 mm to 1.9 mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.
Nonlinear Regression Methods for Estimation
2005-09-01
accuracy when the geometric dilution of precision ( GDOP ) causes collinearity, which in turn brings about poor position estimates. The main goal is...measurements are needed to wash-out the 168 measurement noise. Furthermore, the measurement arrangement’s geometry ( GDOP ) strongly impacts the achievable...Newton algorithm, 61 geometric dilution of precision, see GDOP initial parameter estimate, 91 iterative least squares, see ILS Kalman filtering, 10
NASA Astrophysics Data System (ADS)
Pedretti, Daniele; Fernàndez-Garcia, Daniel
2013-09-01
Particle tracking methods to simulate solute transport deal with the issue of having to reconstruct smooth concentrations from a limited number of particles. This is an error-prone process that typically leads to large fluctuations in the determined late-time behavior of breakthrough curves (BTCs). Kernel density estimators (KDE) can be used to automatically reconstruct smooth BTCs from a small number of particles. The kernel approach incorporates the uncertainty associated with subsampling a large population by equipping each particle with a probability density function. Two broad classes of KDE methods can be distinguished depending on the parametrization of this function: global and adaptive methods. This paper shows that each method is likely to estimate a specific portion of the BTCs. Although global methods offer a valid approach to estimate early-time behavior and peak of BTCs, they exhibit important fluctuations at the tails where fewer particles exist. In contrast, locally adaptive methods improve tail estimation while oversmoothing both early-time and peak concentrations. Therefore a new method is proposed combining the strength of both KDE approaches. The proposed approach is universal and only needs one parameter (α) which slightly depends on the shape of the BTCs. Results show that, for the tested cases, heavily-tailed BTCs are properly reconstructed with α ≈ 0.5 .
Mysina, N Yu; Maksimova, L A; Ryabukho, V P; Gorbatenko, B B
2015-10-31
Investigated are statistical properties of the phase difference of oscillations in speckle-fields at two points in the far-field diffraction region, with different shapes of the scatterer aperture. Statistical and spatial nonuniformity of the probability density function of the field phase difference is established. Numerical experiments show that, for the speckle-fields with an oscillating alternating-sign transverse correlation function, a significant nonuniformity of the probability density function of the phase difference in the correlation region of the field complex amplitude, with the most probable values 0 and p, is observed. A natural statistical interference experiment using Young diagrams has confirmed the results of numerical experiments. (laser applications and other topics in quantum electronics)
Radiance and atmosphere propagation-based method for the target range estimation
NASA Astrophysics Data System (ADS)
Cho, Hoonkyung; Chun, Joohwan
2012-06-01
Target range estimation is traditionally based on radar and active sonar systems in modern combat system. However, the performance of such active sensor devices is degraded tremendously by jamming signal from the enemy. This paper proposes a simple range estimation method between the target and the sensor. Passive IR sensors measures infrared (IR) light radiance radiating from objects in dierent wavelength and this method shows robustness against electromagnetic jamming. The measured target radiance of each wavelength at the IR sensor depends on the emissive properties of target material and is attenuated by various factors, in particular the distance between the sensor and the target and atmosphere environment. MODTRAN is a tool that models atmospheric propagation of electromagnetic radiation. Based on the result from MODTRAN and measured radiance, the target range is estimated. To statistically analyze the performance of proposed method, we use maximum likelihood estimation (MLE) and evaluate the Cramer-Rao Lower Bound (CRLB) via the probability density function of measured radiance. And we also compare CRLB and the variance of and ML estimation using Monte-Carlo.
NASA Technical Reports Server (NTRS)
1995-01-01
The success of any solution methodology for studying gas-turbine combustor flows depends a great deal on how well it can model various complex, rate-controlling processes associated with turbulent transport, mixing, chemical kinetics, evaporation and spreading rates of the spray, convective and radiative heat transfer, and other phenomena. These phenomena often strongly interact with each other at disparate time and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and evaporation in many practical combustion devices. Turbulence manifests its influence in a diffusion flame in several forms depending on how turbulence interacts with various flame scales. These forms range from the so-called wrinkled, or stretched, flamelets regime, to the distributed combustion regime. Conventional turbulence closure models have difficulty in treating highly nonlinear reaction rates. A solution procedure based on the joint composition probability density function (PDF) approach holds the promise of modeling various important combustion phenomena relevant to practical combustion devices such as extinction, blowoff limits, and emissions predictions because it can handle the nonlinear chemical reaction rates without any approximation. In this approach, mean and turbulence gas-phase velocity fields are determined from a standard turbulence model; the joint composition field of species and enthalpy are determined from the solution of a modeled PDF transport equation; and a Lagrangian-based dilute spray model is used for the liquid-phase representation with appropriate consideration of the exchanges of mass, momentum, and energy between the two phases. The PDF transport equation is solved by a Monte Carlo method, and existing state-of-the-art numerical representations are used to solve the mean gasphase velocity and turbulence fields together with the liquid-phase equations. The joint composition PDF
Yao, Rutao; Ramachandra, Ranjith M.; Mahajan, Neeraj; Rathod, Vinay; Gunasekar, Noel; Panse, Ashish; Ma, Tianyu; Jian, Yiqiang; Yan, Jianhua; Carson, Richard E.
2012-01-01
To achieve optimal PET image reconstruction through better system modeling, we developed a system matrix that is based on the probability density function for each line of response (LOR-PDF). The LOR-PDFs are grouped by LOR-to-detector incident angles to form a highly compact system matrix. The system matrix was implemented in the MOLAR list mode reconstruction algorithm for a small animal PET scanner. The impact of LOR-PDF on reconstructed image quality was assessed qualitatively as well as quantitatively in terms of contrast recovery coefficient (CRC) and coefficient of variance (COV), and its performance was compared with a fixed Gaussian (iso-Gaussian) line spread function. The LOR-PDFs of 3 coincidence signal emitting sources, 1) ideal positron emitter that emits perfect back-to-back γ rays (γγ) in air; 2) fluorine-18 (18F) nuclide in water; and 3) oxygen-15 (15O) nuclide in water, were derived, and assessed with simulated and experimental phantom data. The derived LOR-PDFs showed anisotropic and asymmetric characteristics dependent on LOR-detector angle, coincidence emitting source, and the medium, consistent with common PET physical principles. The comparison of the iso-Gaussian function and LOR-PDF showed that: 1) without positron range and acolinearity effects, the LOR-PDF achieved better or similar trade-offs of contrast recovery and noise for objects of 4-mm radius or larger, and this advantage extended to smaller objects (e.g. 2-mm radius sphere, 0.6-mm radius hot-rods) at higher iteration numbers; and 2) with positron range and acolinearity effects, the iso-Gaussian achieved similar or better resolution recovery depending on the significance of positron range effect. We conclude that the 3-D LOR-PDF approach is an effective method to generate an accurate and compact system matrix. However, when used directly in expectation-maximization based list-mode iterative reconstruction algorithms such as MOLAR, its superiority is not clear. For this
NASA Astrophysics Data System (ADS)
Ballestra, Luca Vincenzo; Pacelli, Graziella; Radi, Davide
2016-12-01
We propose a numerical method to compute the first-passage probability density function in a time-changed Brownian model. In particular, we derive an integral representation of such a density function in which the integrand functions must be obtained solving a system of Volterra equations of the first kind. In addition, we develop an ad-hoc numerical procedure to regularize and solve this system of integral equations. The proposed method is tested on three application problems of interest in mathematical finance, namely the calculation of the survival probability of an indebted firm, the pricing of a single-knock-out put option and the pricing of a double-knock-out put option. The results obtained reveal that the novel approach is extremely accurate and fast, and performs significantly better than the finite difference method.
Probability density function selection based on the characteristics of wind speed data
NASA Astrophysics Data System (ADS)
Yürüşen, N. Y.; Melero, Julio J.
2016-09-01
The probabilistic approach has an important place in the wind energy research field as it provides cheap and fast initial information for experts with the help of simulations and estimations. Wind energy experts have been using the Weibull distribution for wind speed data for many years. Nevertheless, there exist cases, where the Weibull distribution is inappropriate with data presenting bimodal or multimodal behaviour which are unfit in high, null and low winds that can cause serious energy estimation errors. This paper presents a procedure for dealing with wind speed data taking into account non-Weibull distributions or data treatment when needed. The procedure detects deviations from the unimodal (Weibull) distribution and proposes other possible distributions to be used. The deviations of the used distributions regarding real data are addressed with the Root Mean Square Error (RMSE) and the annual energy production (AEP).
An at-site flood estimation method in the context of nonstationarity I. A simulation study
NASA Astrophysics Data System (ADS)
Gado, Tamer A.; Nguyen, Van-Thanh-Van
2016-04-01
The stationarity of annual flood peak records is the traditional assumption of flood frequency analysis. In some cases, however, as a result of land-use and/or climate change, this assumption is no longer valid. Therefore, new statistical models are needed to capture dynamically the change of probability density functions over time, in order to obtain reliable flood estimation. In this study, an innovative method for nonstationary flood frequency analysis was presented. Here, the new method is based on detrending the flood series and applying the L-moments along with the GEV distribution to the transformed "stationary" series (hereafter, this is called the LM-NS). The LM-NS method was assessed through a comparative study with the maximum likelihood (ML) method for the nonstationary GEV model, as well as with the stationary (S) GEV model. The comparative study, based on Monte Carlo simulations, was carried out for three nonstationary GEV models: a linear dependence of the mean on time (GEV1), a quadratic dependence of the mean on time (GEV2), and linear dependence in both the mean and log standard deviation on time (GEV11). The simulation results indicated that the LM-NS method performs better than the ML method for most of the cases studied, whereas the stationary method provides the least accurate results. An additional advantage of the LM-NS method is to avoid the numerical problems (e.g., convergence problems) that may occur with the ML method when estimating parameters for small data samples.
Methods of Estimating Strategic Intentions
1982-05-01
of events, coding categories. A V 2. Weighting Data: polIcy capturIng, Bayesian methods, correlation and variance analysis. 3. Characterizing Data...memory aids, fuzzy sets, factor analysis. 4. Assessing Covariations: actuarial models, backcasting . bootstrapping. 5. Cause and Effect Assessment...causae search, causal analysis, search trees, stepping analysts, hypothesis, regression analysis. 6. Predictions: Backcast !ng, boot strapping, decision
Probability density functions for the variable solar wind near the solar cycle minimum
NASA Astrophysics Data System (ADS)
Vörös, Z.; Leitner, M.; Narita, Y.; Consolini, G.; Kovács, P.; Tóth, A.; Lichtenberger, J.
2015-08-01
Unconditional and conditional statistics are used for studying the histograms of magnetic field multiscale fluctuations in the solar wind near the solar cycle minimum in 2008. The unconditional statistics involves the magnetic data during the whole year in 2008. The conditional statistics involves the magnetic field time series split into concatenated subsets of data according to a threshold in dynamic pressure. The threshold separates fast-stream leading edge compressional and trailing edge uncompressional fluctuations. The histograms obtained from these data sets are associated with both multiscale (B) and small-scale (δB) magnetic fluctuations, the latter corresponding to time-delayed differences. It is shown here that, by keeping flexibility but avoiding the unnecessary redundancy in modeling, the histograms can be effectively described by a limited set of theoretical probability distribution functions (PDFs), such as the normal, lognormal, kappa, and log-kappa functions. In a statistical sense the model PDFs correspond to additive and multiplicative processes exhibiting correlations. It is demonstrated here that the skewed small-scale histograms inherent in turbulent cascades are better described by the skewed log-kappa than by the symmetric kappa model. Nevertheless, the observed skewness is rather small, resulting in potential difficulties of estimation of the third-order moments. This paper also investigates the dependence of the statistical convergence of PDF model parameters, goodness of fit, and skewness on the data sample size. It is shown that the minimum lengths of data intervals required for the robust estimation of parameters is scale, process, and model dependent.
NASA Astrophysics Data System (ADS)
Yoshimura, Shinji; Terasaka, Kenichiro; Tanaka, Eiki; Aramaki, Mitsutoshi; Tanaka, Masayoshi Y.
An intermittent behavior of local electron flux in a laboratory ECR plasma is statistically analyzed by means of probability density functions (PDFs). The PDF constructed from a time series of the floating potential signal on a Langmuir probe has a fat tail in the negative value side, which reflects the intermittency of the local electron flux. The PDF of the waiting time, which is defined by the time interval between two successive events, is found to exhibit an exponential distribution, suggesting that the phenomenon is characterized by a stationary Poisson process. The underlying Poisson process is also confirmed by the number of events in given time intervals that is Poisson distributed.
Cardozo, David Lopes; Holdsworth, Peter C W
2016-04-27
The magnetization probability density in d = 2 and 3 dimensional Ising models in slab geometry of volume [Formula: see text] is computed through Monte-Carlo simulation at the critical temperature and zero magnetic field. The finite-size scaling of this distribution and its dependence on the system aspect-ratio [Formula: see text]and boundary conditions are discussed. In the limiting case [Formula: see text] of a macroscopically large slab ([Formula: see text]) the distribution is found to scale as a Gaussian function for all tested system sizes and boundary conditions.
NASA Technical Reports Server (NTRS)
Nitsche, Ludwig C.; Nitsche, Johannes M.; Brenner, Howard
1988-01-01
The sedimentation and diffusion of a nonneutrally buoyant Brownian particle in vertical fluid-filled cylinder of finite length which is instantaneously inverted at regular intervals are investigated analytically. A one-dimensional convective-diffusive equation is derived to describe the temporal and spatial evolution of the probability density; a periodicity condition is formulated; the applicability of Fredholm theory is established; and the parameter-space regions are determined within which the existence and uniqueness of solutions are guaranteed. Numerical results for sample problems are presented graphically and briefly characterized.
NASA Astrophysics Data System (ADS)
Lopes Cardozo, David; Holdsworth, Peter C. W.
2016-04-01
The magnetization probability density in d = 2 and 3 dimensional Ising models in slab geometry of volume L\\paralleld-1× {{L}\\bot} is computed through Monte-Carlo simulation at the critical temperature and zero magnetic field. The finite-size scaling of this distribution and its dependence on the system aspect-ratio ρ =\\frac{{{L}\\bot}}{{{L}\\parallel}} and boundary conditions are discussed. In the limiting case ρ \\to 0 of a macroscopically large slab ({{L}\\parallel}\\gg {{L}\\bot} ) the distribution is found to scale as a Gaussian function for all tested system sizes and boundary conditions.
Multivariate Density Estimation and Remote Sensing
NASA Technical Reports Server (NTRS)
Scott, D. W.
1983-01-01
Current efforts to develop methods and computer algorithms to effectively represent multivariate data commonly encountered in remote sensing applications are described. While this may involve scatter diagrams, multivariate representations of nonparametric probability density estimates are emphasized. The density function provides a useful graphical tool for looking at data and a useful theoretical tool for classification. This approach is called a thunderstorm data analysis.
Probability Density Function for Waves Propagating in a Straight Rough Wall Tunnel
Pao, H
2004-01-28
The radio channel places fundamental limitations on the performance of wireless communication systems in tunnels and caves. The transmission path between the transmitter and receiver can vary from a simple direct line of sight to one that is severely obstructed by rough walls and corners. Unlike wired channels that are stationary and predictable, radio channels can be extremely random and difficult to analyze. In fact, modeling the radio channel has historically been one of the more challenging parts of any radio system design; this is often done using statistical methods. The mechanisms behind electromagnetic wave propagation are diverse, but can generally be attributed to reflection, diffraction, and scattering. Because of the multiple reflections from rough walls, the electromagnetic waves travel along different paths of varying lengths. The interactions between these waves cause multipath fading at any location, and the strengths of the waves decrease as the distance between the transmitter and receiver increases. As a consequence of the central limit theorem, the received signals are approximately Gaussian random process. This means that the field propagating in a cave or tunnel is typically a complex-valued Gaussian random process.
NASA Technical Reports Server (NTRS)
Simon, M.; Mileant, A.
1986-01-01
The steady-state behavior of a particular type of digital phase-locked loop (DPLL) with an integrate-and-dump circuit following the phase detector is characterized in terms of the probability density function (pdf) of the phase error in the loop. Although the loop is entirely digital from an implementation standpoint, it operates at two extremely different sampling rates. In particular, the combination of a phase detector and an integrate-and-dump circuit operates at a very high rate whereas the loop update rate is very slow by comparison. Because of this dichotomy, the loop can be analyzed by hybrid analog/digital (s/z domain) techniques. The loop is modeled in such a general fashion that previous analyses of the Real-Time Combiner (RTC), Subcarrier Demodulator Assembly (SDA), and Symbol Synchronization Assembly (SSA) fall out as special cases.
NASA Astrophysics Data System (ADS)
Wang, Haifeng; Popov, Pavel; Hiremath, Varun; Lantz, Steven; Viswanathan, Sharadha; Pope, Stephen
2010-11-01
A large-eddy simulation (LES)/probability density function (PDF) code is developed and applied to the study of local extinction and re-ignition in Sandia Flame E. The modified Curl mixing model is used to account for the sub-filter scalar mixing; the ARM1 mechanism is used for the chemical reaction; and the in- situ adaptive tabulation (ISAT) algorithm is used to accelerate the chemistry calculations. Calculations are performed on different grids to study the resolution requirement for this flame. Then, with sufficient grid resolution, full-scale LES/PDF calculations are performed to study the flame characteristics and the turbulence-chemistry interactions. Sensitivity to the mixing frequency model is explored in order to understand the behavior of sub-filter scalar mixing in the context of LES. The simulation results are compared to the experimental data to demonstrate the capability of the code. Comparison is also made to previous RANS/PDF simulations.
Nonparametric estimation of population density for line transect sampling using FOURIER series
Crain, B.R.; Burnham, K.P.; Anderson, D.R.; Lake, J.L.
1979-01-01
A nonparametric, robust density estimation method is explored for the analysis of right-angle distances from a transect line to the objects sighted. The method is based on the FOURIER series expansion of a probability density function over an interval. With only mild assumptions, a general population density estimator of wide applicability is obtained.
Standard methods for spectral estimation and prewhitening
Stearns, S.D.
1986-07-01
A standard FFT periodogram-averaging method for power spectral estimation is described in detail, with examples that the reader can use to verify his own software. The parameters that must be specified in order to repeat a given spectral estimate are listed. A standard technique for prewhitening is also described, again with repeatable examples and a summary of the parameters that must be specified.
Shankar Subramaniam
2009-04-01
This final project report summarizes progress made towards the objectives described in the proposal entitled “Developing New Mathematical Models for Multiphase Flows Based on a Fundamental Probability Density Function Approach”. Substantial progress has been made in theory, modeling and numerical simulation of turbulent multiphase flows. The consistent mathematical framework based on probability density functions is described. New models are proposed for turbulent particle-laden flows and sprays.
Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.
2016-01-01
Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
Source estimation methods for atmospheric dispersion
NASA Astrophysics Data System (ADS)
Shankar Rao, K.
Both forward and backward transport modeling methods are being developed for characterization of sources in atmospheric releases of toxic agents. Forward modeling methods, which describe the atmospheric transport from sources to receptors, use forward-running transport and dispersion models or computational fluid dynamics models which are run many times, and the resulting dispersion field is compared to observations from multiple sensors. Forward modeling methods include Bayesian updating and inference schemes using stochastic Monte Carlo or Markov Chain Monte Carlo sampling techniques. Backward or inverse modeling methods use only one model run in the reverse direction from the receptors to estimate the upwind sources. Inverse modeling methods include adjoint and tangent linear models, Kalman filters, and variational data assimilation, among others. This survey paper discusses these source estimation methods and lists the key references. The need for assessing uncertainties in the characterization of sources using atmospheric transport and dispersion models is emphasized.
Tveito, Aslak; Lines, Glenn T; Edwards, Andrew G; McCulloch, Andrew
2016-07-01
Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature.
A simple method to estimate interwell autocorrelation
Pizarro, J.O.S.; Lake, L.W.
1997-08-01
The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.
Wall, Clifton; Boersma, Bendiks Jan; Moin, Parviz
2000-10-01
The assumed beta distribution model for the subgrid-scale probability density function (PDF) of the mixture fraction in large eddy simulation of nonpremixed, turbulent combustion is tested, a priori, for a reacting jet having significant heat release (density ratio of 5). The assumed beta distribution is tested as a model for both the subgrid-scale PDF and the subgrid-scale Favre PDF of the mixture fraction. The beta model is successful in approximating both types of PDF but is slightly more accurate in approximating the normal (non-Favre) PDF. To estimate the subgrid-scale variance of mixture fraction, which is required by the beta model, both a scale similarity model and a dynamic model are used. Predictions using the dynamic model are found to be more accurate. The beta model is used to predict the filtered value of a function chosen to resemble the reaction rate. When no model is used, errors in the predicted value are of the same order as the actual value. The beta model is found to reduce this error by about a factor of two, providing a significant improvement. (c) 2000 American Institute of Physics.
Cost estimating methods for advanced space systems
NASA Technical Reports Server (NTRS)
Cyr, Kelley
1988-01-01
The development of parametric cost estimating methods for advanced space systems in the conceptual design phase is discussed. The process of identifying variables which drive cost and the relationship between weight and cost are discussed. A theoretical model of cost is developed and tested using a historical data base of research and development projects.
Karatsuba's method for estimating Kloosterman sums
NASA Astrophysics Data System (ADS)
Korolev, M. A.
2016-08-01
Using Karatsuba's method, we obtain estimates for Kloosterman sums modulo a prime, in which the number of terms is less than an arbitrarily small fixed power of the modulus. These bounds refine similar results obtained earlier by Bourgain and Garaev. Bibliography: 16 titles.
A statistical method to estimate outflow volume in case of levee breach due to overtopping
NASA Astrophysics Data System (ADS)
Brandimarte, Luigia; Martina, Mario; Dottori, Francesco; Mazzoleni, Maurizio
2015-04-01
The aim of this study is to propose a statistical method to assess the outflowing water volume through a levee breach, due to overtopping, in case of three different types of grass cover quality. The first step in the proposed methodology is the definition of the reliability function, a the relation between loading and resistance conditions on the levee system, in case of overtopping. Secondly, the fragility curve, which relates the probability of failure with loading condition over the levee system, is estimated having defined the stochastic variables in the reliability function. Thus, different fragility curves are assessed in case of different scenarios of grass cover quality. Then, a levee breach model is implemented and combined with a 1D hydrodynamic model in order to assess the outflow hydrograph given the water level in the main channel and stochastic values of the breach width. Finally, the water volume is estimated as a combination of the probability density function of the breach width and levee failure. The case study is located in the in 98km-braided reach of Po River, Italy, between the cross-sections of Cremona and Borgoforte. The analysis showed how different counter measures, different grass cover quality in this case, can reduce the probability of failure of the levee system. In particular, for a given values of breach width good levee cover qualities can significantly reduce the outflowing water volume, compared to bad cover qualities, inducing a consequent lower flood risk within the flood-prone area.
Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method
NASA Astrophysics Data System (ADS)
Pei-Jui, Wu; Hwa-Lung, Yu
2016-04-01
The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .
A Flexible Method of Estimating Luminosity Functions
NASA Astrophysics Data System (ADS)
Kelly, Brandon C.; Fan, Xiaohui; Vestergaard, Marianne
2008-08-01
We describe a Bayesian approach to estimating luminosity functions. We derive the likelihood function and posterior probability distribution for the luminosity function, given the observed data, and we compare the Bayesian approach with maximum likelihood by simulating sources from a Schechter function. For our simulations confidence intervals derived from bootstrapping the maximum likelihood estimate can be too narrow, while confidence intervals derived from the Bayesian approach are valid. We develop our statistical approach for a flexible model where the luminosity function is modeled as a mixture of Gaussian functions. Statistical inference is performed using Markov chain Monte Carlo (MCMC) methods, and we describe a Metropolis-Hastings algorithm to perform the MCMC. The MCMC simulates random draws from the probability distribution of the luminosity function parameters, given the data, and we use a simulated data set to show how these random draws may be used to estimate the probability distribution for the luminosity function. In addition, we show how the MCMC output may be used to estimate the probability distribution of any quantities derived from the luminosity function, such as the peak in the space density of quasars. The Bayesian method we develop has the advantage that it is able to place accurate constraints on the luminosity function even beyond the survey detection limits, and that it provides a natural way of estimating the probability distribution of any quantities derived from the luminosity function, including those that rely on information beyond the survey detection limits.
NASA Astrophysics Data System (ADS)
Sato, Katsushi
2016-08-01
The friction coefficient controls the brittle strength of the Earth's crust for deformation recorded by faults. This study proposes a computerized method to determine the friction coefficient of meso-scale faults. The method is based on the analysis of orientation distribution of faults, and the principal stress axes and the stress ratio calculated by a stress tensor inversion technique. The method assumes that faults are activated according to the cohesionless Coulomb's failure criterion, where the fluctuations of fluid pressure and the magnitude of differential stress are assumed to induce faulting. In this case, the orientation distribution of fault planes is described by a probability density function that is visualized as linear contours on a Mohr diagram. The parametric optimization of the function for an observed fault population yields the friction coefficient. A test using an artificial fault-slip dataset successfully determines the internal friction angle (the arctangent of the friction coefficient) with its confidence interval of several degrees estimated by the bootstrap resampling technique. An application to natural faults cutting a Pleistocene forearc basin fill yields a friction coefficient around 0.7 which is experimentally predicted by the Byerlee's law.
Cost estimating methods for advanced space systems
NASA Technical Reports Server (NTRS)
Cyr, Kelley
1988-01-01
Parametric cost estimating methods for space systems in the conceptual design phase are developed. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance, and time. The relationship between weight and cost is examined in detail. A theoretical model of cost is developed and tested statistically against a historical data base of major research and development programs. It is concluded that the technique presented is sound, but that it must be refined in order to produce acceptable cost estimates.
Implicit solvent methods for free energy estimation
Decherchi, Sergio; Masetti, Matteo; Vyalov, Ivan; Rocchia, Walter
2014-01-01
Solvation is a fundamental contribution in many biological processes and especially in molecular binding. Its estimation can be performed by means of several computational approaches. The aim of this review is to give an overview of existing theories and methods to estimate solvent effects giving a specific focus on the category of implicit solvent models and their use in Molecular Dynamics. In many of these models, the solvent is considered as a continuum homogenous medium, while the solute can be represented at the atomic detail and at different levels of theory. Despite their degree of approximation, implicit methods are still widely employed due to their trade-off between accuracy and efficiency. Their derivation is rooted in the statistical mechanics and integral equations disciplines, some of the related details being provided here. Finally, methods that combine implicit solvent models and molecular dynamics simulation, are briefly described. PMID:25193298
Chowdhury, Shakhawat
2013-05-01
The evaluation of the status of a municipal drinking water treatment plant (WTP) is important. The evaluation depends on several factors, including, human health risks from disinfection by-products (R), disinfection performance (D), and cost (C) of water production and distribution. The Dempster-Shafer theory (DST) of evidence can combine the individual status with respect to R, D, and C to generate a new indicator, from which the overall status of a WTP can be evaluated. In the DST, the ranges of different factors affecting the overall status are divided into several segments. The basic probability assignments (BPA) for each segment of these factors are provided by multiple experts, which are then combined to obtain the overall status. In assigning the BPA, the experts use their individual judgments, which can impart subjective biases in the overall evaluation. In this research, an approach has been introduced to avoid the assignment of subjective BPA. The factors contributing to the overall status were characterized using the probability density functions (PDF). The cumulative probabilities for different segments of these factors were determined from the cumulative density function, which were then assigned as the BPA for these factors. A case study is presented to demonstrate the application of PDF in DST to evaluate a WTP, leading to the selection of the required level of upgradation for the WTP.
NASA Astrophysics Data System (ADS)
Cao, Hong-Jun; Zhang, Hui-Qiang; Lin, Wen-Yi
2012-05-01
Four kinds of presumed probability-density-function (PDF) models for non-premixed turbulent combustion are evaluated in flames with various stoichiometric mixture fractions by using large eddy simulation (LES). The LES code is validated by the experimental data of a classical turbulent jet flame (Sandia flame D). The mean and rms temperatures obtained by the presumed PDF models are compared with the LES results. The β-function model achieves a good prediction for different flames. The predicted rms temperature by using the double-δ function model is very small and unphysical in the vicinity of the maximum mean temperature. The clip-Gaussian model and the multi-δ function model make a worse prediction of the extremely fuel-rich or fuel-lean side due to the clip at the boundary of the mixture fraction space. The results also show that the overall prediction performance of presumed PDF models is better at mediate stoichiometric mixture fractions than that at very small or very large ones.
NASA Technical Reports Server (NTRS)
Nemeth, Noel
2013-01-01
Models that predict the failure probability of monolithic glass and ceramic components under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" failure models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This report develops a formulation to describe the probability density distribution of the orientation of critical strength-controlling flaws that results from an applied load. This distribution is a function of the multiaxial stress state, the shear sensitivity of the flaws, the Weibull modulus, and the strength anisotropy. Examples are provided showing the predicted response on the unit sphere for various stress states for isotropic and transversely isotropic (anisotropic) materials--including the most probable orientation of critical flaws for offset uniaxial loads with strength anisotropy. The author anticipates that this information could be used to determine anisotropic stiffness degradation or anisotropic damage evolution for individual brittle (or quasi-brittle) composite material constituents within finite element or micromechanics-based software
Clustering method for estimating principal diffusion directions
Nazem-Zadeh, Mohammad-Reza; Jafari-Khouzani, Kourosh; Davoodi-Bojd, Esmaeil; Jiang, Quan; Soltanian-Zadeh, Hamid
2012-01-01
Diffusion tensor magnetic resonance imaging (DTMRI) is a non-invasive tool for the investigation of white matter structure within the brain. However, the traditional tensor model is unable to characterize anisotropies of orders higher than two in heterogeneous areas containing more than one fiber population. To resolve this issue, high angular resolution diffusion imaging (HARDI) with a large number of diffusion encoding gradients is used along with reconstruction methods such as Q-ball. Using HARDI data, the fiber orientation distribution function (ODF) on the unit sphere is calculated and used to extract the principal diffusion directions (PDDs). Fast and accurate estimation of PDDs is a prerequisite for tracking algorithms that deal with fiber crossings. In this paper, the PDDs are defined as the directions around which the ODF data is concentrated. Estimates of the PDDs based on this definition are less sensitive to noise in comparison with the previous approaches. A clustering approach to estimate the PDDs is proposed which is an extension of fuzzy c-means clustering developed for orientation of points on a sphere. MDL (Minimum description length) principle is proposed to estimate the number of PDDs. Using both simulated and real diffusion data, the proposed method has been evaluated and compared with some previous protocols. Experimental results show that the proposed clustering algorithm is more accurate, more resistant to noise, and faster than some of techniques currently being utilized. PMID:21642005
Child survivorship estimation: methods and data analysis.
Feeney, G
1991-01-01
"The past 20 years have seen extensive elaboration, refinement, and application of the original Brass method for estimating infant and child mortality from child survivorship data. This experience has confirmed the overall usefulness of the methods beyond question, but it has also shown that...estimates must be analyzed in relation to other relevant information before useful conclusions about the level and trend of mortality can be drawn.... This article aims to illustrate the importance of data analysis through a series of examples, including data for the Eastern Malaysian state of Sarawak, Mexico, Thailand, and Indonesia. Specific maneuvers include plotting completed parity distributions and 'time-plotting' mean numbers of children ever born from successive censuses. A substantive conclusion of general interest is that data for older women are not so widely defective as generally supposed."
A method for estimating soil moisture availability
NASA Technical Reports Server (NTRS)
Carlson, T. N.
1985-01-01
A method for estimating values of soil moisture based on measurements of infrared surface temperature is discussed. A central element in the method is a boundary layer model. Although it has been shown that soil moistures determined by this method using satellite measurements do correspond in a coarse fashion to the antecedent precipitation, the accuracy and exact physical interpretation (with respect to ground water amounts) are not well known. This area of ignorance, which currently impedes the practical application of the method to problems in hydrology, meteorology and agriculture, is largely due to the absence of corresponding surface measurements. Preliminary field measurements made over France have led to the development of a promising vegetation formulation (Taconet et al., 1985), which has been incorporated in the model. It is necessary, however, to test the vegetation component, and the entire method, over a wide variety of surface conditions and crop canopies.
Bisetti, Fabrizio; Chen, J.-Y.; Hawkes, Evatt R.; Chen, Jacqueline H.
2008-12-15
Homogeneous charge compression ignition (HCCI) engine technology promises to reduce NO{sub x} and soot emissions while achieving high thermal efficiency. Temperature and mixture stratification are regarded as effective means of controlling the start of combustion and reducing the abrupt pressure rise at high loads. Probability density function methods are currently being pursued as a viable approach to modeling the effects of turbulent mixing and mixture stratification on HCCI ignition. In this paper we present an assessment of the merits of three widely used mixing models in reproducing the moments of reactive scalars during the ignition of a lean hydrogen/air mixture ({phi}=0.1, p=41atm, and T=1070 K) under increasing temperature stratification and subject to decaying turbulence. The results from the solution of the evolution equation for a spatially homogeneous joint PDF of the reactive scalars are compared with available direct numerical simulation (DNS) data [E.R. Hawkes, R. Sankaran, P.P. Pebay, J.H. Chen, Combust. Flame 145 (1-2) (2006) 145-159]. The mixing models are found able to quantitatively reproduce the time history of the heat release rate, first and second moments of temperature, and hydroxyl radical mass fraction from the DNS results. Most importantly, the dependence of the heat release rate on the extent of the initial temperature stratification in the charge is also well captured. (author)
Comparative yield estimation via shock hydrodynamic methods
Attia, A.V.; Moran, B.; Glenn, L.A.
1991-06-01
Shock TOA (CORRTEX) from recent underground nuclear explosions in saturated tuff were used to estimate yield via the simulated explosion-scaling method. The sensitivity of the derived yield to uncertainties in the measured shock Hugoniot, release adiabats, and gas porosity is the main focus of this paper. In this method for determining yield, we assume a point-source explosion in an infinite homogeneous material. The rock is formulated using laboratory experiments on core samples, taken prior to the explosion. Results show that increasing gas porosity from 0% to 2% causes a 15% increase in yield per ms/kt{sup 1/3}. 6 refs., 4 figs.
Cost estimating methods for advanced space systems
NASA Technical Reports Server (NTRS)
Cyr, Kelley
1994-01-01
NASA is responsible for developing much of the nation's future space technology. Cost estimates for new programs are required early in the planning process so that decisions can be made accurately. Because of the long lead times required to develop space hardware, the cost estimates are frequently required 10 to 15 years before the program delivers hardware. The system design in conceptual phases of a program is usually only vaguely defined and the technology used is so often state-of-the-art or beyond. These factors combine to make cost estimating for conceptual programs very challenging. This paper describes an effort to develop parametric cost estimating methods for space systems in the conceptual design phase. The approach is to identify variables that drive cost such as weight, quantity, development culture, design inheritance and time. The nature of the relationships between the driver variables and cost will be discussed. In particular, the relationship between weight and cost will be examined in detail. A theoretical model of cost will be developed and tested statistically against a historical database of major research and development projects.
NASA Technical Reports Server (NTRS)
Garber, Donald P.
1993-01-01
A probability density function for the variability of ensemble averaged spectral estimates from helicopter acoustic signals in Gaussian background noise was evaluated. Numerical methods for calculating the density function and for determining confidence limits were explored. Density functions were predicted for both synthesized and experimental data and compared with observed spectral estimate variability.
Tsai, Keng-Chang; Jian, Jhih-Wei; Yang, Ei-Wen; Hsu, Po-Chiang; Peng, Hung-Pin; Chen, Ching-Tai; Chen, Jun-Bo; Chang, Jeng-Yih; Hsu, Wen-Lian; Yang, An-Suei
2012-01-01
Non-covalent protein-carbohydrate interactions mediate molecular targeting in many biological processes. Prediction of non-covalent carbohydrate binding sites on protein surfaces not only provides insights into the functions of the query proteins; information on key carbohydrate-binding residues could suggest site-directed mutagenesis experiments, design therapeutics targeting carbohydrate-binding proteins, and provide guidance in engineering protein-carbohydrate interactions. In this work, we show that non-covalent carbohydrate binding sites on protein surfaces can be predicted with relatively high accuracy when the query protein structures are known. The prediction capabilities were based on a novel encoding scheme of the three-dimensional probability density maps describing the distributions of 36 non-covalent interacting atom types around protein surfaces. One machine learning model was trained for each of the 30 protein atom types. The machine learning algorithms predicted tentative carbohydrate binding sites on query proteins by recognizing the characteristic interacting atom distribution patterns specific for carbohydrate binding sites from known protein structures. The prediction results for all protein atom types were integrated into surface patches as tentative carbohydrate binding sites based on normalized prediction confidence level. The prediction capabilities of the predictors were benchmarked by a 10-fold cross validation on 497 non-redundant proteins with known carbohydrate binding sites. The predictors were further tested on an independent test set with 108 proteins. The residue-based Matthews correlation coefficient (MCC) for the independent test was 0.45, with prediction precision and sensitivity (or recall) of 0.45 and 0.49 respectively. In addition, 111 unbound carbohydrate-binding protein structures for which the structures were determined in the absence of the carbohydrate ligands were predicted with the trained predictors. The overall
ERIC Educational Resources Information Center
Riggs, Peter J.
2013-01-01
Students often wrestle unsuccessfully with the task of correctly calculating momentum probability densities and have difficulty in understanding their interpretation. In the case of a particle in an "infinite" potential well, its momentum can take values that are not just those corresponding to the particle's quantised energies but…
Demographic estimation methods for plants with dormancy
Kery, M.; Gregg, K.B.
2004-01-01
Demographic studies in plants appear simple because unlike animals, plants do not run away. Plant individuals can be marked with, e.g., plastic tags, but often the coordinates of an individual may be sufficient to identify it. Vascular plants in temperate latitudes have a pronounced seasonal life–cycle, so most plant demographers survey their study plots once a year often during or shortly after flowering. Life–states are pervasive in plants, hence the results of a demographic study for an individual can be summarized in a familiar encounter history, such as 0VFVVF000. A zero means that an individual was not seen in a year and a letter denotes its state for years when it was seen aboveground. V and F here stand for vegetative and flowering states, respectively. Probabilities of survival and state transitions can then be obtained by mere counting.Problems arise when there is an unobservable dormant state, i.e., when plants may stay belowground for one or more growing seasons. Encounter histories such as 0VF00F000 may then occur where the meaning of zeroes becomes ambiguous. A zero can either mean a dead or a dormant plant. Various ad hoc methods in wide use among plant ecologists have made strong assumptions about when a zero should be equated to a dormant individual. These methods have never been compared among each other. In our talk and in Kéry et al. (submitted), we show that these ad hoc estimators provide spurious estimates of survival and should not be used.In contrast, if detection probabilities for aboveground plants are known or can be estimated, capturerecapture (CR) models can be used to estimate probabilities of survival and state–transitions and the fraction of the population that is dormant. We have used this approach in two studies of terrestrial orchids, Cleistes bifaria (Kéry et al., submitted) and Cypripedium reginae(Kéry & Gregg, submitted) in West Virginia, U.S.A. For Cleistes, our data comprised one population with a total of 620
NASA Astrophysics Data System (ADS)
Koutmos, P.; Marazioti, P.
2001-04-01
The effects of finite-rate chemistry, such as partial extinctions and re-ignitions, are investigated in turbulent non-pre-mixed reacting flows stabilized in the wake of an axisymmetric bluff-body burner. A two-dimensional large-eddy simulation procedure is employed that uses a partial equilibrium/two-scalar reactedness mixture fraction probability density function (PDF) combustion sub-model, which is applied at the sub-grid scale (SGS) level. An anisotropic sub-grid eddy-viscosity and two equations for the SGS turbulence kinetic and scalar energies complete the SGS closure model. The scalar covariances required in the joint PDF formulation are obtained from an extended scale-similarity assumption between the resolved and the sub-grid fluctuations. Extinction due to strong turbulence/chemistry interactions is recognized with the help of a critical, locally variable, turbulent Damkohler number criterion, while transient localized extinctions and re-ignitions are treated with a Lagrangian transport equation for a reactedness progress variable. Comparisons with available experimental data suggested that the formulated approach was capable of identifying the effects of large-scale vortex structure activity, which were inherent in the reacting wake and dominant in the counterpart isothermal flows that otherwise would have been obscured if a standard time-averaged procedure had been used. Additionally, the post-extinction and re-ignition behaviour and its time-varying interaction with the large-scale structure dynamics were more appropriately addressed within the context of the present time-dependent method. Copyright
Efficient resampling methods for nonsmooth estimating functions
ZENG, DONGLIN
2009-01-01
Summary We propose a simple and general resampling strategy to estimate variances for parameter estimators derived from nonsmooth estimating functions. This approach applies to a wide variety of semiparametric and nonparametric problems in biostatistics. It does not require solving estimating equations and is thus much faster than the existing resampling procedures. Its usefulness is illustrated with heteroscedastic quantile regression and censored data rank regression. Numerical results based on simulated and real data are provided. PMID:17925303
NASA Astrophysics Data System (ADS)
Zengmei, L.; Guanghua, Q.; Zishen, C.
2015-05-01
The direct benefit of a waterlogging control project is reflected by the reduction or avoidance of waterlogging loss. Before and after the construction of a waterlogging control project, the disaster-inducing environment in the waterlogging-prone zone is generally different. In addition, the category, quantity and spatial distribution of the disaster-bearing bodies are also changed more or less. Therefore, under the changing environment, the direct benefit of a waterlogging control project should be the reduction of waterlogging losses compared to conditions with no control project. Moreover, the waterlogging losses with or without the project should be the mathematical expectations of the waterlogging losses when rainstorms of all frequencies meet various water levels in the drainage-accepting zone. So an estimation model of the direct benefit of waterlogging control is proposed. Firstly, on the basis of a Copula function, the joint distribution of the rainstorms and the water levels are established, so as to obtain their joint probability density function. Secondly, according to the two-dimensional joint probability density distribution, the dimensional domain of integration is determined, which is then divided into small domains so as to calculate the probability for each of the small domains and the difference between the average waterlogging loss with and without a waterlogging control project, called the regional benefit of waterlogging control project, under the condition that rainstorms in the waterlogging-prone zone meet the water level in the drainage-accepting zone. Finally, it calculates the weighted mean of the project benefit of all small domains, with probability as the weight, and gets the benefit of the waterlogging control project. Taking the estimation of benefit of a waterlogging control project in Yangshan County, Guangdong Province, as an example, the paper briefly explains the procedures in waterlogging control project benefit estimation. The
Bayesian methods for parameter estimation in effective field theories
Schindler, M.R. Phillips, D.R.
2009-03-15
We demonstrate and explicate Bayesian methods for fitting the parameters that encode the impact of short-distance physics on observables in effective field theories (EFTs). We use Bayes' theorem together with the principle of maximum entropy to account for the prior information that these parameters should be natural, i.e., O(1) in appropriate units. Marginalization can then be employed to integrate the resulting probability density function (pdf) over the EFT parameters that are not of specific interest in the fit. We also explore marginalization over the order of the EFT calculation, M, and over the variable, R, that encodes the inherent ambiguity in the notion that these parameters are O(1). This results in a very general formula for the pdf of the EFT parameters of interest given a data set, D. We use this formula and the simpler 'augmented {chi}{sup 2}' in a toy problem for which we generate pseudo-data. These Bayesian methods, when used in combination with the 'naturalness prior', facilitate reliable extractions of EFT parameters in cases where {chi}{sup 2} methods are ambiguous at best. We also examine the problem of extracting the nucleon mass in the chiral limit, M{sub 0}, and the nucleon sigma term, from pseudo-data on the nucleon mass as a function of the pion mass. We find that Bayesian techniques can provide reliable information on M{sub 0}, even if some of the data points used for the extraction lie outside the region of applicability of the EFT.
Online Direct Density-Ratio Estimation Applied to Inlier-Based Outlier Detection.
du Plessis, Marthinus Christoffel; Shiino, Hiroaki; Sugiyama, Masashi
2015-09-01
Many machine learning problems, such as nonstationarity adaptation, outlier detection, dimensionality reduction, and conditional density estimation, can be effectively solved by using the ratio of probability densities. Since the naive two-step procedure of first estimating the probability densities and then taking their ratio performs poorly, methods to directly estimate the density ratio from two sets of samples without density estimation have been extensively studied recently. However, these methods are batch algorithms that use the whole data set to estimate the density ratio, and they are inefficient in the online setup, where training samples are provided sequentially and solutions are updated incrementally without storing previous samples. In this letter, we propose two online density-ratio estimators based on the adaptive regularization of weight vectors. Through experiments on inlier-based outlier detection, we demonstrate the usefulness of the proposed methods.
NASA Astrophysics Data System (ADS)
Ruggles, Adam J.
2015-11-01
This paper presents improved statistical insight regarding the self-similar scalar mixing process of atmospheric hydrogen jets and the downstream region of under-expanded hydrogen jets. Quantitative planar laser Rayleigh scattering imaging is used to probe both jets. The self-similarity of statistical moments up to the sixth order (beyond the literature established second order) is documented in both cases. This is achieved using a novel self-similar normalization method that facilitated a degree of statistical convergence that is typically limited to continuous, point-based measurements. This demonstrates that image-based measurements of a limited number of samples can be used for self-similar scalar mixing studies. Both jets exhibit the same radial trends of these moments demonstrating that advanced atmospheric self-similarity can be applied in the analysis of under-expanded jets. Self-similar histograms away from the centerline are shown to be the combination of two distributions. The first is attributed to turbulent mixing. The second, a symmetric Poisson-type distribution centered on zero mass fraction, progressively becomes the dominant and eventually sole distribution at the edge of the jet. This distribution is attributed to shot noise-affected pure air measurements, rather than a diffusive superlayer at the jet boundary. This conclusion is reached after a rigorous measurement uncertainty analysis and inspection of pure air data collected with each hydrogen data set. A threshold based upon the measurement noise analysis is used to separate the turbulent and pure air data, and thusly estimate intermittency. Beta-distributions (four parameters) are used to accurately represent the turbulent distribution moments. This combination of measured intermittency and four-parameter beta-distributions constitutes a new, simple approach to model scalar mixing. Comparisons between global moments from the data and moments calculated using the proposed model show excellent
Comparisons of Four Methods for Estimating a Dynamic Factor Model
ERIC Educational Resources Information Center
Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.
2008-01-01
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…
Statistical methods of estimating mining costs
Long, K.R.
2011-01-01
Until it was defunded in 1995, the U.S. Bureau of Mines maintained a Cost Estimating System (CES) for prefeasibility-type economic evaluations of mineral deposits and estimating costs at producing and non-producing mines. This system had a significant role in mineral resource assessments to estimate costs of developing and operating known mineral deposits and predicted undiscovered deposits. For legal reasons, the U.S. Geological Survey cannot update and maintain CES. Instead, statistical tools are under development to estimate mining costs from basic properties of mineral deposits such as tonnage, grade, mineralogy, depth, strip ratio, distance from infrastructure, rock strength, and work index. The first step was to reestimate "Taylor's Rule" which relates operating rate to available ore tonnage. The second step was to estimate statistical models of capital and operating costs for open pit porphyry copper mines with flotation concentrators. For a sample of 27 proposed porphyry copper projects, capital costs can be estimated from three variables: mineral processing rate, strip ratio, and distance from nearest railroad before mine construction began. Of all the variables tested, operating costs were found to be significantly correlated only with strip ratio.
A Study of Variance Estimation Methods. Working Paper Series.
ERIC Educational Resources Information Center
Zhang, Fan; Weng, Stanley; Salvucci, Sameena; Hu, Ming-xiu
This working paper contains reports of five studies of variance estimation methods. The first, An Empirical Study of Poststratified Estimator, by Fan Zhang uses data from the National Household Education Survey to illustrate use of poststratified estimation. The second paper, BRR Variance Estimation Using BPLX Hadamard Procedure, by Stanley Weng…
alphaPDE: A new multivariate technique for parameter estimation
Knuteson, B.; Miettinen, H.; Holmstrom, L.
2002-06-01
We present alphaPDE, a new multivariate analysis technique for parameter estimation. The method is based on a direct construction of joint probability densities of known variables and the parameters to be estimated. We show how posterior densities and best-value estimates are then obtained for the parameters of interest by a straightforward manipulation of these densities. The method is essentially non-parametric and allows for an intuitive graphical interpretation. We illustrate the method by outlining how it can be used to estimate the mass of the top quark, and we explain how the method is applied to an ensemble of events containing background.
Nutrient Estimation Using Subsurface Sensing Methods
Technology Transfer Automated Retrieval System (TEKTRAN)
This report investigates the use of precision management techniques for measuring soil conductivity on feedlot surfaces to estimate nutrient value for crop production. An electromagnetic induction soil conductivity meter was used to collect apparent soil electrical conductivity (ECa) from feedlot p...
Evaluating Methods for Estimating Program Effects
ERIC Educational Resources Information Center
Reichardt, Charles S.
2011-01-01
I define a treatment effect in terms of a comparison of outcomes and provide a typology of all possible comparisons that can be used to estimate treatment effects, including comparisons that are relatively unknown in both the literature and practice. I then assess the relative merit, worth, and value of all possible comparisons based on the…
New High Throughput Methods to Estimate Chemical ...
EPA has made many recent advances in high throughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing and screening chemicals. A recent report by the National Research Council of the National Academies, Exposure Science in the 21st Century: A Vision and a Strategy (NRC 2012) laid out a number of applications in chemical evaluation of both toxicity and risk in critical need of quantitative exposure predictions, including screening and prioritization of chemicals for targeted toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability. Despite these significant needs, for the majority of chemicals (e.g. non-pesticide environmental compounds) there are no or limited estimates of exposure. For example, exposure estimates exist for only 7% of the ToxCast Phase II chemical list. In addition, the data required for generating exposure estimates for large numbers of chemicals is severely lacking (Egeghy et al. 2012). This SAP reviewed the use of EPA's ExpoCast model to rapidly estimate potential chemical exposures for prioritization and screening purposes. The focus was on bounded chemical exposure values for people and the environment for the Endocrine Disruptor Screening Program (EDSP) Universe of Chemicals. In addition to exposure, the SAP
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2010-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.
Estimation Methods for One-Parameter Testlet Models
ERIC Educational Resources Information Center
Jiao, Hong; Wang, Shudong; He, Wei
2013-01-01
This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…
Estimation of vegetation cover at subpixel resolution using LANDSAT data
NASA Technical Reports Server (NTRS)
Jasinski, Michael F.; Eagleson, Peter S.
1986-01-01
The present report summarizes the various approaches relevant to estimating canopy cover at subpixel resolution. The approaches are based on physical models of radiative transfer in non-homogeneous canopies and on empirical methods. The effects of vegetation shadows and topography are examined. Simple versions of the model are tested, using the Taos, New Mexico Study Area database. Emphasis has been placed on using relatively simple models requiring only one or two bands. Although most methods require some degree of ground truth, a two-band method is investigated whereby the percent cover can be estimated without ground truth by examining the limits of the data space. Future work is proposed which will incorporate additional surface parameters into the canopy cover algorithm, such as topography, leaf area, or shadows. The method involves deriving a probability density function for the percent canopy cover based on the joint probability density function of the observed radiances.
Quantum Estimation Methods for Quantum Illumination
NASA Astrophysics Data System (ADS)
Sanz, M.; Las Heras, U.; García-Ripoll, J. J.; Solano, E.; Di Candia, R.
2017-02-01
Quantum illumination consists in shining quantum light on a target region immersed in a bright thermal bath with the aim of detecting the presence of a possible low-reflective object. If the signal is entangled with the receiver, then a suitable choice of the measurement offers a gain with respect to the optimal classical protocol employing coherent states. Here, we tackle this detection problem by using quantum estimation techniques to measure the reflectivity parameter of the object, showing an enhancement in the signal-to-noise ratio up to 3 dB with respect to the classical case when implementing only local measurements. Our approach employs the quantum Fisher information to provide an upper bound for the error probability, supplies the concrete estimator saturating the bound, and extends the quantum illumination protocol to non-Gaussian states. As an example, we show how Schrödinger's cat states may be used for quantum illumination.
Quantum Estimation Methods for Quantum Illumination.
Sanz, M; Las Heras, U; García-Ripoll, J J; Solano, E; Di Candia, R
2017-02-17
Quantum illumination consists in shining quantum light on a target region immersed in a bright thermal bath with the aim of detecting the presence of a possible low-reflective object. If the signal is entangled with the receiver, then a suitable choice of the measurement offers a gain with respect to the optimal classical protocol employing coherent states. Here, we tackle this detection problem by using quantum estimation techniques to measure the reflectivity parameter of the object, showing an enhancement in the signal-to-noise ratio up to 3 dB with respect to the classical case when implementing only local measurements. Our approach employs the quantum Fisher information to provide an upper bound for the error probability, supplies the concrete estimator saturating the bound, and extends the quantum illumination protocol to non-Gaussian states. As an example, we show how Schrödinger's cat states may be used for quantum illumination.
Development of advanced acreage estimation methods
NASA Technical Reports Server (NTRS)
Guseman, L. F., Jr. (Principal Investigator)
1980-01-01
The use of the AMOEBA clustering/classification algorithm was investigated as a basis for both a color display generation technique and maximum likelihood proportion estimation procedure. An approach to analyzing large data reduction systems was formulated and an exploratory empirical study of spatial correlation in LANDSAT data was also carried out. Topics addressed include: (1) development of multiimage color images; (2) spectral spatial classification algorithm development; (3) spatial correlation studies; and (4) evaluation of data systems.
An investigation of new methods for estimating parameter sensitivities
NASA Technical Reports Server (NTRS)
Beltracchi, Todd J.; Gabriele, Gary A.
1989-01-01
The method proposed for estimating sensitivity derivatives is based on the Recursive Quadratic Programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This method is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RQP algorithm. Initial testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity.
NASA Technical Reports Server (NTRS)
Tapia, R. A.; Vanrooy, D. L.
1976-01-01
A quasi-Newton method is presented for minimizing a nonlinear function while constraining the variables to be nonnegative and sum to one. The nonnegativity constraints were eliminated by working with the squares of the variables and the resulting problem was solved using Tapia's general theory of quasi-Newton methods for constrained optimization. A user's guide for a computer program implementing this algorithm is provided.
[Weighted estimation methods for multistage sampling survey data].
Hou, Xiao-Yan; Wei, Yong-Yue; Chen, Feng
2009-06-01
Multistage sampling techniques are widely applied in the cross-sectional study of epidemiology, while methods based on independent assumption are still used to analyze such complex survey data. This paper aims to introduce the application of weighted estimation methods for the complex survey data. A brief overview of basic theory is described, and then a practical analysis is illustrated to apply to the weighted estimation algorithm in a stratified two-stage clustered sampling data. For multistage sampling survey data, weighted estimation method can be used to obtain unbiased point estimation and more reasonable variance estimation, and so make proper statistical inference by correcting the clustering, stratification and unequal probability effects.
A Joint Analytic Method for Estimating Aquitard Hydraulic Parameters.
Zhuang, Chao; Zhou, Zhifang; Illman, Walter A
2017-01-10
The vertical hydraulic conductivity (Kv ), elastic (Sske ), and inelastic (Sskv ) skeletal specific storage of aquitards are three of the most critical parameters in land subsidence investigations. Two new analytic methods are proposed to estimate the three parameters. The first analytic method is based on a new concept of delay time ratio for estimating Kv and Sske of an aquitard subject to long-term stable, cyclic hydraulic head changes at boundaries. The second analytic method estimates the Sskv of the aquitard subject to linearly declining hydraulic heads at boundaries. Both methods are based on analytical solutions for flow within the aquitard, and they are jointly employed to obtain the three parameter estimates. This joint analytic method is applied to estimate the Kv , Sske , and Sskv of a 34.54-m thick aquitard for which the deformation progress has been recorded by an extensometer located in Shanghai, China. The estimated results are then calibrated by PEST (Doherty 2005), a parameter estimation code coupled with a one-dimensional aquitard-drainage model. The Kv and Sske estimated by the joint analytic method are quite close to those estimated via inverse modeling and performed much better in simulating elastic deformation than the estimates obtained from the stress-strain diagram method of Ye and Xue (2005). The newly proposed joint analytic method is an effective tool that provides reasonable initial values for calibrating land subsidence models.
Advancing Methods for Estimating Cropland Area
NASA Astrophysics Data System (ADS)
King, L.; Hansen, M.; Stehman, S. V.; Adusei, B.; Potapov, P.; Krylov, A.
2014-12-01
Measurement and monitoring of complex and dynamic agricultural land systems is essential with increasing demands on food, feed, fuel and fiber production from growing human populations, rising consumption per capita, the expansion of crops oils in industrial products, and the encouraged emphasis on crop biofuels as an alternative energy source. Soybean is an important global commodity crop, and the area of land cultivated for soybean has risen dramatically over the past 60 years, occupying more than 5% of all global croplands (Monfreda et al 2008). Escalating demands for soy over the next twenty years are anticipated to be met by an increase of 1.5 times the current global production, resulting in expansion of soybean cultivated land area by nearly the same amount (Masuda and Goldsmith 2009). Soybean cropland area is estimated with the use of a sampling strategy and supervised non-linear hierarchical decision tree classification for the United States, Argentina and Brazil as the prototype in development of a new methodology for crop specific agricultural area estimation. Comparison of our 30 m2 Landsat soy classification with the National Agricultural Statistical Services Cropland Data Layer (CDL) soy map shows a strong agreement in the United States for 2011, 2012, and 2013. RapidEye 5m2 imagery was also classified for soy presence and absence and used at the field scale for validation and accuracy assessment of the Landsat soy maps, describing a nearly 1 to 1 relationship in the United States, Argentina and Brazil. The strong correlation found between all products suggests high accuracy and precision of the prototype and has proven to be a successful and efficient way to assess soybean cultivated area at the sub-national and national scale for the United States with great potential for application elsewhere.
Rapid Methods for Estimating Navigation Channel Shoaling
2009-01-01
of the data dependence and lack of accounting for channel width. Mayor- Mora et al. (1976) developed an analytical method for infilling in a...1.2 cm/day near the end of the monitoring. The predictive expression of Mayor- Mora et al. (1976) is: /(1 ) (1 ) cosa dFh h FR in hdq q e q e...decision-support or initial planning studies that must be done quickly. Vicente and Uva (1984) present a method based on the assumption that a
Optical method of atomic ordering estimation
Prutskij, T.; Attolini, G.
2013-12-04
It is well known that within metal-organic vapor-phase epitaxy (MOVPE) grown semiconductor III-V ternary alloys atomically ordered regions are spontaneously formed during the epitaxial growth. This ordering leads to bandgap reduction and to valence bands splitting, and therefore to anisotropy of the photoluminescence (PL) emission polarization. The same phenomenon occurs within quaternary semiconductor alloys. While the ordering in ternary alloys is widely studied, for quaternaries there have been only a few detailed experimental studies of it, probably because of the absence of appropriate methods of its detection. Here we propose an optical method to reveal atomic ordering within quaternary alloys by measuring the PL emission polarization.
NASA Astrophysics Data System (ADS)
Klein, Roman
2016-06-01
Electron storage rings with appropriate design are primary source standards, the spectral radiant intensity of which can be calculated from measured parameters using the Schwinger equation. PTB uses the electron storage rings BESSY II and MLS for source-based radiometry in the spectral range from the near-infrared to the x-ray region. The uncertainty of the calculated radiant intensity depends on the uncertainty of the measured parameters used for the calculation. Up to now the procedure described in the guide to the expression of uncertainty in measurement (GUM), i.e. the law of propagation of uncertainty, assuming a linear measurement model, was used to determine the combined uncertainty of the calculated spectral intensity, and for the determination of the coverage interval as well. Now it has been tested with a Monte Carlo simulation, according to Supplement 1 to the GUM, whether this procedure is valid for the rather complicated calculation by means of the Schwinger formalism and for different probability distributions of the input parameters. It was found that for typical uncertainties of the input parameters both methods yield similar results.
Robust time and frequency domain estimation methods in adaptive control
NASA Technical Reports Server (NTRS)
Lamaire, Richard Orville
1987-01-01
A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.
ERIC Educational Resources Information Center
Samejima, Fumiko
1977-01-01
A method of estimating item characteristic functions is proposed, in which a set of test items, whose operating characteristics are known and which give a constant test information function for a wide range of ability, are used. The method is based on maximum likelihood estimation procedures. (Author/JKS)
System and method for motor parameter estimation
Luhrs, Bin; Yan, Ting
2014-03-18
A system and method for determining unknown values of certain motor parameters includes a motor input device connectable to an electric motor having associated therewith values for known motor parameters and an unknown value of at least one motor parameter. The motor input device includes a processing unit that receives a first input from the electric motor comprising values for the known motor parameters for the electric motor and receive a second input comprising motor data on a plurality of reference motors, including values for motor parameters corresponding to the known motor parameters of the electric motor and values for motor parameters corresponding to the at least one unknown motor parameter value of the electric motor. The processor determines the unknown value of the at least one motor parameter from the first input and the second input and determines a motor management strategy for the electric motor based thereon.
A Comparative Study of Distribution System Parameter Estimation Methods
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 both 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.
Carbon footprint: current methods of estimation.
Pandey, Divya; Agrawal, Madhoolika; Pandey, Jai Shanker
2011-07-01
Increasing greenhouse gaseous concentration in the atmosphere is perturbing the environment to cause grievous global warming and associated consequences. Following the rule that only measurable is manageable, mensuration of greenhouse gas intensiveness of different products, bodies, and processes is going on worldwide, expressed as their carbon footprints. The methodologies for carbon footprint calculations are still evolving and it is emerging as an important tool for greenhouse gas management. The concept of carbon footprinting has permeated and is being commercialized in all the areas of life and economy, but there is little coherence in definitions and calculations of carbon footprints among the studies. There are disagreements in the selection of gases, and the order of emissions to be covered in footprint calculations. Standards of greenhouse gas accounting are the common resources used in footprint calculations, although there is no mandatory provision of footprint verification. Carbon footprinting is intended to be a tool to guide the relevant emission cuts and verifications, its standardization at international level are therefore necessary. Present review describes the prevailing carbon footprinting methods and raises the related issues.
Research on the estimation method for Earth rotation parameters
NASA Astrophysics Data System (ADS)
Yao, Yibin
2008-12-01
In this paper, the methods of earth rotation parameter (ERP) estimation based on IGS SINEX file of GPS solution are discussed in details. To estimate ERP, two different ways are involved: one is the parameter transformation method, and the other is direct adjustment method with restrictive conditions. With the IGS daily SINEX files produced by GPS tracking stations can be used to estimate ERP. The parameter transformation method can simplify the process. The process result indicates that the systemic error will exist in the estimated ERP by only using GPS observations. As to the daily GPS SINEX files, why the distinct systemic error is exist in the ERP, or whether this systemic error will affect other parameters estimation, and what its influenced magnitude being, it needs further study in the future.
ERIC Educational Resources Information Center
Mahmud, Jumailiyah; Sutikno, Muzayanah; Naga, Dali S.
2016-01-01
The aim of this study is to determine variance difference between maximum likelihood and expected A posteriori estimation methods viewed from number of test items of aptitude test. The variance presents an accuracy generated by both maximum likelihood and Bayes estimation methods. The test consists of three subtests, each with 40 multiple-choice…
Zhang, Fan; Gao, Yan; Luo, Yazhi; Chen, Zhangyuan; Xu, Anshi
2010-04-26
We propose a stochastic bit error ratio estimation approach based on a statistical analysis of the retrieved signal phase for coherent optical QPSK systems with digital carrier phase recovery. A family of the generalized exponential function is applied to fit the probability density function of the signal samples. The method provides reasonable performance estimation in presence of both linear and nonlinear transmission impairments while reduces the computational intensity greatly compared to Monte Carlo simulation.
NASA Astrophysics Data System (ADS)
Bhatt, Nilay; Bhattacharyya, Subir
2012-02-01
The time series of a gamma-ray burst (GRB) is a non-stationary time series and all of its statistical properties vary with time. Considering that each GRB is a different manifestation of the same stochastic process, we have studied the time-dependent and time-averaged probability density functions (pdfs), which characterize the underlying stochastic process. The pdfs are fitted with a Gaussian distribution function. It has been argued that the Gaussian pdfs possibly indicate the turbulent origin of GRBs. The spectral and temporal evolutions of GRBs are also studied using the evolution of spectral forms, colour-colour diagrams and hysteresis loops. The results do not contradict the interpretation of the turbulence of GRBs.
Evaluation of Methods to Estimate Understory Fruit Biomass
Lashley, Marcus A.; Thompson, Jeffrey R.; Chitwood, M. Colter; DePerno, Christopher S.; Moorman, Christopher E.
2014-01-01
Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in wildlife habitat quality. Yet, designing a fruit sampling protocol that is executable on a frequent basis may be difficult, and knowledge of accuracy within monitoring protocols is lacking. We evaluated the accuracy and efficiency of 3 methods to estimate understory fruit biomass (Fruit Count, Stem Density, and Plant Coverage). The Fruit Count method requires visual counts of fruit to estimate fruit biomass. The Stem Density method uses counts of all stems of fruit producing species to estimate fruit biomass. The Plant Coverage method uses land coverage of fruit producing species to estimate fruit biomass. Using linear regression models under a censored-normal distribution, we determined the Fruit Count and Stem Density methods could accurately estimate fruit biomass; however, when comparing AIC values between models, the Fruit Count method was the superior method for estimating fruit biomass. After determining that Fruit Count was the superior method to accurately estimate fruit biomass, we conducted additional analyses to determine the sampling intensity (i.e., percentage of area) necessary to accurately estimate fruit biomass. The Fruit Count method accurately estimated fruit biomass at a 0.8% sampling intensity. In some cases, sampling 0.8% of an area may not be feasible. In these cases, we suggest sampling understory fruit production with the Fruit Count method at the greatest feasible sampling intensity, which could be valuable to assess annual fluctuations in fruit production. PMID:24819253
A new method for the estimation of the completeness magnitude
NASA Astrophysics Data System (ADS)
Godano, C.
2017-02-01
The estimation of the magnitude of completeness mc have strong consequences in any statistical analysis of seismic catalogue and in the evaluation of the seismic hazard. Here a new method for its estimation is presented. The goodness of the method has been tested using 104 simulated catalogues. Then the method has been applied to five experimental seismic catalogues: Greece, Italy, Japan, Northern California and Southern California.
Investigating the Stability of Four Methods for Estimating Item Bias.
ERIC Educational Resources Information Center
Perlman, Carole L.; And Others
The reliability of item bias estimates was studied for four methods: (1) the transformed delta method; (2) Shepard's modified delta method; (3) Rasch's one-parameter residual analysis; and (4) the Mantel-Haenszel procedure. Bias statistics were computed for each sample using all methods. Data were from administration of multiple-choice items from…
An evaluation of methods for estimating decadal stream loads
NASA Astrophysics Data System (ADS)
Lee, Casey J.; Hirsch, Robert M.; Schwarz, Gregory E.; Holtschlag, David J.; Preston, Stephen D.; Crawford, Charles G.; Vecchia, Aldo V.
2016-11-01
Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen - lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale's ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between
A source number estimation method for single optical fiber sensor
NASA Astrophysics Data System (ADS)
Hu, Junpeng; Huang, Zhiping; Su, Shaojing; Zhang, Yimeng; Liu, Chunwu
2015-10-01
The single-channel blind source separation (SCBSS) technique makes great significance in many fields, such as optical fiber communication, sensor detection, image processing and so on. It is a wide range application to realize blind source separation (BSS) from a single optical fiber sensor received data. The performance of many BSS algorithms and signal process methods will be worsened with inaccurate source number estimation. Many excellent algorithms have been proposed to deal with the source number estimation in array signal process which consists of multiple sensors, but they can not be applied directly to the single sensor condition. This paper presents a source number estimation method dealing with the single optical fiber sensor received data. By delay process, this paper converts the single sensor received data to multi-dimension form. And the data covariance matrix is constructed. Then the estimation algorithms used in array signal processing can be utilized. The information theoretic criteria (ITC) based methods, presented by AIC and MDL, Gerschgorin's disk estimation (GDE) are introduced to estimate the source number of the single optical fiber sensor's received signal. To improve the performance of these estimation methods at low signal noise ratio (SNR), this paper make a smooth process to the data covariance matrix. By the smooth process, the fluctuation and uncertainty of the eigenvalues of the covariance matrix are reduced. Simulation results prove that ITC base methods can not estimate the source number effectively under colored noise. The GDE method, although gets a poor performance at low SNR, but it is able to accurately estimate the number of sources with colored noise. The experiments also show that the proposed method can be applied to estimate the source number of single sensor received data.
Uncertainty estimation in seismo-acoustic reflection travel time inversion.
Dettmer, Jan; Dosso, Stan E; Holland, Charles W
2007-07-01
This paper develops a nonlinear Bayesian inversion for high-resolution seabed reflection travel time data including rigorous uncertainty estimation and examination of statistical assumptions. Travel time data are picked on seismo-acoustic traces and inverted for a layered sediment sound-velocity model. Particular attention is paid to picking errors which are often biased, correlated, and nonstationary. Non-Toeplitz data covariance matrices are estimated and included in the inversion along with unknown travel time offset (bias) parameters to account for these errors. Simulated experiments show that neglecting error covariances and biases can cause misleading inversion results with unrealistically high confidence. The inversion samples the posterior probability density and provides a solution in terms of one- and two-dimensional marginal probability densities, correlations, and credibility intervals. Statistical assumptions are examined through the data residuals with rigorous statistical tests. The method is applied to shallow-water data collected on the Malta Plateau during the SCARAB98 experiment.
An automated method of tuning an attitude estimator
NASA Technical Reports Server (NTRS)
Mason, Paul A. C.; Mook, D. Joseph
1995-01-01
Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.
Evaluating maximum likelihood estimation methods to determine the hurst coefficients
NASA Astrophysics Data System (ADS)
Kendziorski, C. M.; Bassingthwaighte, J. B.; Tonellato, P. J.
1999-12-01
A maximum likelihood estimation method implemented in S-PLUS ( S-MLE) to estimate the Hurst coefficient ( H) is evaluated. The Hurst coefficient, with 0.5< H<1, characterizes long memory time series by quantifying the rate of decay of the autocorrelation function. S-MLE was developed to estimate H for fractionally differenced (fd) processes. However, in practice it is difficult to distinguish between fd processes and fractional Gaussian noise (fGn) processes. Thus, the method is evaluated for estimating H for both fd and fGn processes. S-MLE gave biased results of H for fGn processes of any length and for fd processes of lengths less than 2 10. A modified method is proposed to correct for this bias. It gives reliable estimates of H for both fd and fGn processes of length greater than or equal to 2 11.
Estimation and classification by sigmoids based on mutual information
NASA Technical Reports Server (NTRS)
Baram, Yoram
1994-01-01
An estimate of the probability density function of a random vector is obtained by maximizing the mutual information between the input and the output of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's s method, applied to an estimated density, yields a recursive maximum likelihood estimator, consisting of a single internal layer of sigmoids, for a random variable or a random sequence. Applications to the diamond classification and to the prediction of a sun-spot process are demonstrated.
A new method for estimating extreme rainfall probabilities
Harper, G.A.; O'Hara, T.F. ); Morris, D.I. )
1994-02-01
As part of an EPRI-funded research program, the Yankee Atomic Electric Company developed a new method for estimating probabilities of extreme rainfall. It can be used, along with other techniques, to improve the estimation of probable maximum precipitation values for specific basins or regions.
Quantifying Accurate Calorie Estimation Using the "Think Aloud" Method
ERIC Educational Resources Information Center
Holmstrup, Michael E.; Stearns-Bruening, Kay; Rozelle, Jeffrey
2013-01-01
Objective: Clients often have limited time in a nutrition education setting. An improved understanding of the strategies used to accurately estimate calories may help to identify areas of focused instruction to improve nutrition knowledge. Methods: A "Think Aloud" exercise was recorded during the estimation of calories in a standard dinner meal…
Methods for Estimating Medical Expenditures Attributable to Intimate Partner Violence
ERIC Educational Resources Information Center
Brown, Derek S.; Finkelstein, Eric A.; Mercy, James A.
2008-01-01
This article compares three methods for estimating the medical cost burden of intimate partner violence against U.S. adult women (18 years and older), 1 year postvictimization. To compute the estimates, prevalence data from the National Violence Against Women Survey are combined with cost data from the Medical Expenditure Panel Survey, the…
A Novel Monopulse Angle Estimation Method for Wideband LFM Radars
Zhang, Yi-Xiong; Liu, Qi-Fan; Hong, Ru-Jia; Pan, Ping-Ping; Deng, Zhen-Miao
2016-01-01
Traditional monopulse angle estimations are mainly based on phase comparison and amplitude comparison methods, which are commonly adopted in narrowband radars. In modern radar systems, wideband radars are becoming more and more important, while the angle estimation for wideband signals is little studied in previous works. As noise in wideband radars has larger bandwidth than narrowband radars, the challenge lies in the accumulation of energy from the high resolution range profile (HRRP) of monopulse. In wideband radars, linear frequency modulated (LFM) signals are frequently utilized. In this paper, we investigate the monopulse angle estimation problem for wideband LFM signals. To accumulate the energy of the received echo signals from different scatterers of a target, we propose utilizing a cross-correlation operation, which can achieve a good performance in low signal-to-noise ratio (SNR) conditions. In the proposed algorithm, the problem of angle estimation is converted to estimating the frequency of the cross-correlation function (CCF). Experimental results demonstrate the similar performance of the proposed algorithm compared with the traditional amplitude comparison method. It means that the proposed method for angle estimation can be adopted. When adopting the proposed method, future radars may only need wideband signals for both tracking and imaging, which can greatly increase the data rate and strengthen the capability of anti-jamming. More importantly, the estimated angle will not become ambiguous under an arbitrary angle, which can significantly extend the estimated angle range in wideband radars. PMID:27271629
A Novel Monopulse Angle Estimation Method for Wideband LFM Radars.
Zhang, Yi-Xiong; Liu, Qi-Fan; Hong, Ru-Jia; Pan, Ping-Ping; Deng, Zhen-Miao
2016-06-03
Traditional monopulse angle estimations are mainly based on phase comparison and amplitude comparison methods, which are commonly adopted in narrowband radars. In modern radar systems, wideband radars are becoming more and more important, while the angle estimation for wideband signals is little studied in previous works. As noise in wideband radars has larger bandwidth than narrowband radars, the challenge lies in the accumulation of energy from the high resolution range profile (HRRP) of monopulse. In wideband radars, linear frequency modulated (LFM) signals are frequently utilized. In this paper, we investigate the monopulse angle estimation problem for wideband LFM signals. To accumulate the energy of the received echo signals from different scatterers of a target, we propose utilizing a cross-correlation operation, which can achieve a good performance in low signal-to-noise ratio (SNR) conditions. In the proposed algorithm, the problem of angle estimation is converted to estimating the frequency of the cross-correlation function (CCF). Experimental results demonstrate the similar performance of the proposed algorithm compared with the traditional amplitude comparison method. It means that the proposed method for angle estimation can be adopted. When adopting the proposed method, future radars may only need wideband signals for both tracking and imaging, which can greatly increase the data rate and strengthen the capability of anti-jamming. More importantly, the estimated angle will not become ambiguous under an arbitrary angle, which can significantly extend the estimated angle range in wideband radars.
An improved method of monopulse estimation in PD radar
NASA Astrophysics Data System (ADS)
Wang, Jun; Guo, Peng; Lei, Peng; Wei, Shaoming
2011-10-01
Monopulse estimation is an angle measurement method with high data rate, measurement precision and anti-jamming ability, since the angle information of target is obtained by comparing echoes received in two or more simultaneous antenna beams. However, the data rate of this method decreases due to coherent integration when applied in pulse Doppler (PD) radar. This paper presents an improved method of monopulse estimation in PD radar. In this method, the received echoes are selected by shift before coherent integration, detection and angle measurement. It can increase data rate while maintain angle measurement precision. And the validity of this method is verified by theoretical analysis and simulation results.
Comparison of haemoglobin estimates using direct & indirect cyanmethaemoglobin methods
Bansal, Priyanka Gupta; Toteja, Gurudayal Singh; Bhatia, Neena; Gupta, Sanjeev; Kaur, Manpreet; Adhikari, Tulsi; Garg, Ashok Kumar
2016-01-01
Background & objectives: Estimation of haemoglobin is the most widely used method to assess anaemia. Although direct cyanmethaemoglobin method is the recommended method for estimation of haemoglobin, but it may not be feasible under field conditions. Hence, the present study was undertaken to compare indirect cyanmethaemoglobin method against the conventional direct method for haemoglobin estimation. Methods: Haemoglobin levels were estimated for 888 adolescent girls aged 11-18 yr residing in an urban slum in Delhi by both direct and indirect cyanmethaemoglobin methods, and the results were compared. Results: The mean haemoglobin levels for 888 whole blood samples estimated by direct and indirect cyanmethaemoglobin method were 116.1 ± 12.7 and 110.5 ± 12.5 g/l, respectively, with a mean difference of 5.67 g/l (95% confidence interval: 5.45 to 5.90, P<0.001); which is equivalent to 0.567 g%. The prevalence of anaemia was reported as 59.6 and 78.2 per cent by direct and indirect methods, respectively. Sensitivity and specificity of indirect cyanmethaemoglobin method were 99.2 and 56.4 per cent, respectively. Using regression analysis, prediction equation was developed for indirect haemoglobin values. Interpretation & conclusions: The present findings revealed that indirect cyanmethaemoglobin method overestimated the prevalence of anaemia as compared to the direct method. However, if a correction factor is applied, indirect method could be successfully used for estimating true haemoglobin level. More studies should be undertaken to establish agreement and correction factor between direct and indirect cyanmethaemoglobin methods. PMID:28256465
Computerised prostate boundary estimation of ultrasound images using radial bas-relief method.
Liu, Y J; Ng, W S; Teo, M Y; Lim, H C
1997-09-01
A new method is presented for automatic prostate boundary detection in ultrasound images taken transurethrally or transrectally. This is one of the stages in the implementation of a robotic procedure for prostate surgery performed by a robot known as the robot for urology (UROBOT). Unlike most edge detection methods, which detect object edges by means of either a spatial filter (such as Sobel, Laplacian or something of that nature) or a texture descriptor (local signal-to-noise ratio, joint probability density function etc.), this new approach employs a technique called radial bas-relief (RBR) to outline the prostate boundary area automatically. The results show that the RBR method works well in the detection of the prostate boundary in ultrasound images. It can also be useful for boundary detection problems in medical images where the object boundary is hard to detect using traditional edge detection algorithms, such as ultrasound of the uterus and kidney.
A method for the estimation of urinary testosterone
Ismail, A. A. A.; Harkness, R. A.
1966-01-01
1. A method has been developed for the estimation of testosterone in human urine by using acid hydrolysis followed by a quantitative form of a modified Girard reaction that separates a `conjugated-ketone' fraction from a urine extract; this is followed by column chromatography on alumina and paper chromatography. 2. Comparison of methods of estimation of testosterone in the final fraction shows that estimation by gas–liquid chromatography is more reproducible than by colorimetric methods applied to the same eluates from the paper chromatogram. 3. The mean recovery of testosterone by gas–liquid chromatography is 79·5%, and this method appears to be specific for testosterone. 4. The procedure is relatively rapid. Six determinations can be performed by one worker in 2 days. 5. Results of determinations on human urine are briefly presented. In general, they are similar to earlier estimates, but the maximal values are lower. PMID:5964968
Methods for Estimating Uncertainty in Factor Analytic Solutions
The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DI...
A bootstrap method for estimating uncertainty of water quality trends
Hirsch, Robert M.; Archfield, Stacey A.; DeCicco, Laura
2015-01-01
Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.
Evapotranspiration: Mass balance measurements compared with flux estimation methods
Technology Transfer Automated Retrieval System (TEKTRAN)
Evapotranspiration (ET) may be measured by mass balance methods and estimated by flux sensing methods. The mass balance methods are typically restricted in terms of the area that can be represented (e.g., surface area of weighing lysimeter (LYS) or equivalent representative area of neutron probe (NP...
A posteriori pointwise error estimates for the boundary element method
Paulino, G.H.; Gray, L.J.; Zarikian, V.
1995-01-01
This report presents a new approach for a posteriori pointwise error estimation in the boundary element method. The estimator relies upon the evaluation of hypersingular integral equations, and is therefore intrinsic to the boundary integral equation approach. This property allows some theoretical justification by mathematically correlating the exact and estimated errors. A methodology is developed for approximating the error on the boundary as well as in the interior of the domain. In the interior, error estimates for both the function and its derivatives (e.g. potential and interior gradients for potential problems, displacements and stresses for elasticity problems) are presented. Extensive computational experiments have been performed for the two dimensional Laplace equation on interior domains, employing Dirichlet and mixed boundary conditions. The results indicate that the error estimates successfully track the form of the exact error curve. Moreover, a reasonable estimate of the magnitude of the actual error is also obtained.
An investigation of new methods for estimating parameter sensitivities
NASA Technical Reports Server (NTRS)
Beltracchi, Todd J.; Gabriele, Gary A.
1988-01-01
Parameter sensitivity is defined as the estimation of changes in the modeling functions and the design variables due to small changes in the fixed parameters of the formulation. There are currently several methods for estimating parameter sensitivities requiring either difficult to obtain second order information, or do not return reliable estimates for the derivatives. Additionally, all the methods assume that the set of active constraints does not change in a neighborhood of the estimation point. If the active set does in fact change, than any extrapolations based on these derivatives may be in error. The objective here is to investigate more efficient new methods for estimating parameter sensitivities when the active set changes. The new method is based on the recursive quadratic programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RPQ algorithm. Inital testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity. To handle changes in the active set, a deflection algorithm is proposed for those cases where the new set of active constraints remains linearly independent. For those cases where dependencies occur, a directional derivative is proposed. A few simple examples are included for the algorithm, but extensive testing has not yet been performed.
A hybrid displacement estimation method for ultrasonic elasticity imaging.
Chen, Lujie; Housden, R; Treece, Graham; Gee, Andrew; Prager, Richard
2010-04-01
Axial displacement estimation is fundamental to many freehand quasistatic ultrasonic strain imaging systems. In this paper, we present a novel estimation method that combines the strengths of quality-guided tracking, multi-level correlation, and phase-zero search to achieve high levels of accuracy and robustness. The paper includes a full description of the hybrid method, in vivo examples to illustrate the method's clinical relevance, and finite element simulations to assess its accuracy. Quantitative and qualitative comparisons are made with leading single- and multi-level alternatives. In the in vivo examples, the hybrid method produces fewer obvious peak-hopping errors, and in simulation, the hybrid method is found to reduce displacement estimation errors by 5 to 50%. With typical clinical data, the hybrid method can generate more than 25 strain images per second on commercial hardware; this is comparable with the alternative approaches considered in this paper.
Methods for Estimation of Market Power in Electric Power Industry
NASA Astrophysics Data System (ADS)
Turcik, M.; Oleinikova, I.; Junghans, G.; Kolcun, M.
2012-01-01
The article is related to a topical issue of the newly-arisen market power phenomenon in the electric power industry. The authors point out to the importance of effective instruments and methods for credible estimation of the market power on liberalized electricity market as well as the forms and consequences of market power abuse. The fundamental principles and methods of the market power estimation are given along with the most common relevant indicators. Furthermore, in the work a proposal for determination of the relevant market place taking into account the specific features of power system and a theoretical example of estimating the residual supply index (RSI) in the electricity market are given.
A Channelization-Based DOA Estimation Method for Wideband Signals
Guo, Rui; Zhang, Yue; Lin, Qianqiang; Chen, Zengping
2016-01-01
In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM) and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS) are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR) using direct wideband radio frequency (RF) digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method. PMID:27384566
A Computationally Efficient Method for Polyphonic Pitch Estimation
NASA Astrophysics Data System (ADS)
Zhou, Ruohua; Reiss, Joshua D.; Mattavelli, Marco; Zoia, Giorgio
2009-12-01
This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI) as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.
A new class of methods for functional connectivity estimation
NASA Astrophysics Data System (ADS)
Lin, Wutu
Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.
Demographic estimation methods for plants with unobservable life-states
Kery, M.; Gregg, K.B.; Schaub, M.
2005-01-01
Demographic estimation of vital parameters in plants with an unobservable dormant state is complicated, because time of death is not known. Conventional methods assume that death occurs at a particular time after a plant has last been seen aboveground but the consequences of assuming a particular duration of dormancy have never been tested. Capture-recapture methods do not make assumptions about time of death; however, problems with parameter estimability have not yet been resolved. To date, a critical comparative assessment of these methods is lacking. We analysed data from a 10 year study of Cleistes bifaria, a terrestrial orchid with frequent dormancy, and compared demographic estimates obtained by five varieties of the conventional methods, and two capture-recapture methods. All conventional methods produced spurious unity survival estimates for some years or for some states, and estimates of demographic rates sensitive to the time of death assumption. In contrast, capture-recapture methods are more parsimonious in terms of assumptions, are based on well founded theory and did not produce spurious estimates. In Cleistes, dormant episodes lasted for 1-4 years (mean 1.4, SD 0.74). The capture-recapture models estimated ramet survival rate at 0.86 (SE~ 0.01), ranging from 0.77-0.94 (SEs # 0.1) in anyone year. The average fraction dormant was estimated at 30% (SE 1.5), ranging 16 -47% (SEs # 5.1) in anyone year. Multistate capture-recapture models showed that survival rates were positively related to precipitation in the current year, but transition rates were more strongly related to precipitation in the previous than in the current year, with more ramets going dormant following dry years. Not all capture-recapture models of interest have estimable parameters; for instance, without excavating plants in years when they do not appear aboveground, it is not possible to obtain independent timespecific survival estimates for dormant plants. We introduce rigorous
A new method for parameter estimation in nonlinear dynamical equations
NASA Astrophysics Data System (ADS)
Wang, Liu; He, Wen-Ping; Liao, Le-Jian; Wan, Shi-Quan; He, Tao
2015-01-01
Parameter estimation is an important scientific problem in various fields such as chaos control, chaos synchronization and other mathematical models. In this paper, a new method for parameter estimation in nonlinear dynamical equations is proposed based on evolutionary modelling (EM). This will be achieved by utilizing the following characteristics of EM which includes self-organizing, adaptive and self-learning features which are inspired by biological natural selection, and mutation and genetic inheritance. The performance of the new method is demonstrated by using various numerical tests on the classic chaos model—Lorenz equation (Lorenz 1963). The results indicate that the new method can be used for fast and effective parameter estimation irrespective of whether partial parameters or all parameters are unknown in the Lorenz equation. Moreover, the new method has a good convergence rate. Noises are inevitable in observational data. The influence of observational noises on the performance of the presented method has been investigated. The results indicate that the strong noises, such as signal noise ratio (SNR) of 10 dB, have a larger influence on parameter estimation than the relatively weak noises. However, it is found that the precision of the parameter estimation remains acceptable for the relatively weak noises, e.g. SNR is 20 or 30 dB. It indicates that the presented method also has some anti-noise performance.
Comparison of volume estimation methods for pancreatic islet cells
NASA Astrophysics Data System (ADS)
Dvořák, JiřÃ.; Å vihlík, Jan; Habart, David; Kybic, Jan
2016-03-01
In this contribution we study different methods of automatic volume estimation for pancreatic islets which can be used in the quality control step prior to the islet transplantation. The total islet volume is an important criterion in the quality control. Also, the individual islet volume distribution is interesting -- it has been indicated that smaller islets can be more effective. A 2D image of a microscopy slice containing the islets is acquired. The input of the volume estimation methods are segmented images of individual islets. The segmentation step is not discussed here. We consider simple methods of volume estimation assuming that the islets have spherical or ellipsoidal shape. We also consider a local stereological method, namely the nucleator. The nucleator does not rely on any shape assumptions and provides unbiased estimates if isotropic sections through the islets are observed. We present a simulation study comparing the performance of the volume estimation methods in different scenarios and an experimental study comparing the methods on a real dataset.
A Group Contribution Method for Estimating Cetane and Octane Numbers
Kubic, William Louis
2016-07-28
Much of the research on advanced biofuels is devoted to the study of novel chemical pathways for converting nonfood biomass into liquid fuels that can be blended with existing transportation fuels. Many compounds under consideration are not found in the existing fuel supplies. Often, the physical properties needed to assess the viability of a potential biofuel are not available. The only reliable information available may be the molecular structure. Group contribution methods for estimating physical properties from molecular structure have been used for more than 60 years. The most common application is estimation of thermodynamic properties. More recently, group contribution methods have been developed for estimating rate dependent properties including cetane and octane numbers. Often, published group contribution methods are limited in terms of types of function groups and range of applicability. In this study, a new, broadly-applicable group contribution method based on an artificial neural network was developed to estimate cetane number research octane number, and motor octane numbers of hydrocarbons and oxygenated hydrocarbons. The new method is more accurate over a greater range molecular weights and structural complexity than existing group contribution methods for estimating cetane and octane numbers.
Motion estimation using point cluster method and Kalman filter.
Senesh, M; Wolf, A
2009-05-01
The most frequently used method in a three dimensional human gait analysis involves placing markers on the skin of the analyzed segment. This introduces a significant artifact, which strongly influences the bone position and orientation and joint kinematic estimates. In this study, we tested and evaluated the effect of adding a Kalman filter procedure to the previously reported point cluster technique (PCT) in the estimation of a rigid body motion. We demonstrated the procedures by motion analysis of a compound planar pendulum from indirect opto-electronic measurements of markers attached to an elastic appendage that is restrained to slide along the rigid body long axis. The elastic frequency is close to the pendulum frequency, as in the biomechanical problem, where the soft tissue frequency content is similar to the actual movement of the bones. Comparison of the real pendulum angle to that obtained by several estimation procedures--PCT, Kalman filter followed by PCT, and low pass filter followed by PCT--enables evaluation of the accuracy of the procedures. When comparing the maximal amplitude, no effect was noted by adding the Kalman filter; however, a closer look at the signal revealed that the estimated angle based only on the PCT method was very noisy with fluctuation, while the estimated angle based on the Kalman filter followed by the PCT was a smooth signal. It was also noted that the instantaneous frequencies obtained from the estimated angle based on the PCT method is more dispersed than those obtained from the estimated angle based on Kalman filter followed by the PCT method. Addition of a Kalman filter to the PCT method in the estimation procedure of rigid body motion results in a smoother signal that better represents the real motion, with less signal distortion than when using a digital low pass filter. Furthermore, it can be concluded that adding a Kalman filter to the PCT procedure substantially reduces the dispersion of the maximal and minimal
The estimation of the measurement results with using statistical methods
NASA Astrophysics Data System (ADS)
Velychko, O.; Gordiyenko, T.
2015-02-01
The row of international standards and guides describe various statistical methods that apply for a management, control and improvement of processes with the purpose of realization of analysis of the technical measurement results. The analysis of international standards and guides on statistical methods estimation of the measurement results recommendations for those applications in laboratories is described. For realization of analysis of standards and guides the cause-and-effect Ishikawa diagrams concerting to application of statistical methods for estimation of the measurement results are constructed.
Evaluation of alternative methods for estimating reference evapotranspiration
Technology Transfer Automated Retrieval System (TEKTRAN)
Evapotranspiration is an important component in water-balance and irrigation scheduling models. While the FAO-56 Penman-Monteith method has become the de facto standard for estimating reference evapotranspiration (ETo), it is a complex method requiring several weather parameters. Required weather ...
Comparison of Methods for Estimating and Testing Latent Variable Interactions.
ERIC Educational Resources Information Center
Moulder, Bradley C.; Algina, James
2002-01-01
Used simulation to compare structural equation modeling methods for estimating and testing hypotheses about an interaction between continuous variables. Findings indicate that the two-stage least squares procedure exhibited more bias and lower power than the other methods. The Jaccard-Wan procedure (J. Jaccard and C. Wan, 1995) and maximum…
Assessing the sensitivity of methods for estimating principal causal effects.
Stuart, Elizabeth A; Jo, Booil
2015-12-01
The framework of principal stratification provides a way to think about treatment effects conditional on post-randomization variables, such as level of compliance. In particular, the complier average causal effect (CACE) - the effect of the treatment for those individuals who would comply with their treatment assignment under either treatment condition - is often of substantive interest. However, estimation of the CACE is not always straightforward, with a variety of estimation procedures and underlying assumptions, but little advice to help researchers select between methods. In this article, we discuss and examine two methods that rely on very different assumptions to estimate the CACE: a maximum likelihood ('joint') method that assumes the 'exclusion restriction,' (ER) and a propensity score-based method that relies on 'principal ignorability.' We detail the assumptions underlying each approach, and assess each methods' sensitivity to both its own assumptions and those of the other method using both simulated data and a motivating example. We find that the ER-based joint approach appears somewhat less sensitive to its assumptions, and that the performance of both methods is significantly improved when there are strong predictors of compliance. Interestingly, we also find that each method performs particularly well when the assumptions of the other approach are violated. These results highlight the importance of carefully selecting an estimation procedure whose assumptions are likely to be satisfied in practice and of having strong predictors of principal stratum membership.
Rapid-estimation method for assessing scour at highway bridges
Holnbeck, Stephen R.
1998-01-01
A method was developed by the U.S. Geological Survey for rapid estimation of scour at highway bridges using limited site data and analytical procedures to estimate pier, abutment, and contraction scour depths. The basis for the method was a procedure recommended by the Federal Highway Administration for conducting detailed scour investigations, commonly referred to as the Level 2 method. Using pier, abutment, and contraction scour results obtained from Level 2 investigations at 122 sites in 10 States, envelope curves and graphical relations were developed that enable determination of scour-depth estimates at most bridge sites in a matter of a few hours. Rather than using complex hydraulic variables, surrogate variables more easily obtained in the field were related to calculated scour-depth data from Level 2 studies. The method was tested by having several experienced individuals apply the method in the field, and results were compared among the individuals and with previous detailed analyses performed for the sites. Results indicated that the variability in predicted scour depth among individuals applying the method generally was within an acceptable range, and that conservatively greater scour depths generally were obtained by the rapid-estimation method compared to the Level 2 method. The rapid-estimation method is considered most applicable for conducting limited-detail scour assessments and as a screening tool to determine those bridge sites that may require more detailed analysis. The method is designed to be applied only by a qualified professional possessing knowledge and experience in the fields of bridge scour, hydraulics, and flood hydrology, and having specific expertise with the Level 2 method.
Assessment of Methods for Estimating Risk to Birds from ...
The U.S. EPA Ecological Risk Assessment Support Center (ERASC) announced the release of the final report entitled, Assessment of Methods for Estimating Risk to Birds from Ingestion of Contaminated Grit Particles. This report evaluates approaches for estimating the probability of ingestion by birds of contaminated particles such as pesticide granules or lead particles (i.e. shot or bullet fragments). In addition, it presents an approach for using this information to estimate the risk of mortality to birds from ingestion of lead particles. Response to ERASC Request #16
Precision of two methods for estimating age from burbot otoliths
Edwards, W.H.; Stapanian, M.A.; Stoneman, A.T.
2011-01-01
Lower reproductive success and older age structure are associated with many burbot (Lota lota L.) populations that are declining or of conservation concern. Therefore, reliable methods for estimating the age of burbot are critical for effective assessment and management. In Lake Erie, burbot populations have declined in recent years due to the combined effects of an aging population (&xmacr; = 10 years in 2007) and extremely low recruitment since 2002. We examined otoliths from burbot (N = 91) collected in Lake Erie in 2007 and compared the estimates of burbot age by two agers, each using two established methods (cracked-and-burned and thin-section) of estimating ages from burbot otoliths. One ager was experienced at estimating age from otoliths, the other was a novice. Agreement (precision) between the two agers was higher for the thin-section method, particularly at ages 6–11 years, based on linear regression analyses and 95% confidence intervals. As expected, precision between the two methods was higher for the more experienced ager. Both agers reported that the thin sections offered clearer views of the annuli, particularly near the margins on otoliths from burbot ages ≥8. Slides for the thin sections required some costly equipment and more than 2 days to prepare. In contrast, preparing the cracked-and-burned samples was comparatively inexpensive and quick. We suggest use of the thin-section method for estimating the age structure of older burbot populations.
Bounded Self-Weights Estimation Method for Non-Local Means Image Denoising Using Minimax Estimators.
Nguyen, Minh Phuong; Chun, Se Young
2017-04-01
A non-local means (NLM) filter is a weighted average of a large number of non-local pixels with various image intensity values. The NLM filters have been shown to have powerful denoising performance, excellent detail preservation by averaging many noisy pixels, and using appropriate values for the weights, respectively. The NLM weights between two different pixels are determined based on the similarities between two patches that surround these pixels and a smoothing parameter. Another important factor that influences the denoising performance is the self-weight values for the same pixel. The recently introduced local James-Stein type center pixel weight estimation method (LJS) outperforms other existing methods when determining the contribution of the center pixels in the NLM filter. However, the LJS method may result in excessively large self-weight estimates since no upper bound is assumed, and the method uses a relatively large local area for estimating the self-weights, which may lead to a strong bias. In this paper, we investigated these issues in the LJS method, and then propose a novel local self-weight estimation methods using direct bounds (LMM-DB) and reparametrization (LMM-RP) based on the Baranchik's minimax estimator. Both the LMM-DB and LMM-RP methods were evaluated using a wide range of natural images and a clinical MRI image together with the various levels of additive Gaussian noise. Our proposed parameter selection methods yielded an improved bias-variance trade-off, a higher peak signal-to-noise (PSNR) ratio, and fewer visual artifacts when compared with the results of the classical NLM and LJS methods. Our proposed methods also provide a heuristic way to select a suitable global smoothing parameters that can yield PSNR values that are close to the optimal values.
Spectral estimation of plasma fluctuations. I. Comparison of methods
Riedel, K.S.; Sidorenko, A. ); Thomson, D.J. )
1994-03-01
The relative root mean squared errors (RMSE) of nonparametric methods for spectral estimation is compared for microwave scattering data of plasma fluctuations. These methods reduce the variance of the periodogram estimate by averaging the spectrum over a frequency bandwidth. As the bandwidth increases, the variance decreases, but the bias error increases. The plasma spectra vary by over four orders of magnitude, and therefore, using a spectral window is necessary. The smoothed tapered periodogram is compared with the adaptive multiple taper methods and hybrid methods. It is found that a hybrid method, which uses four orthogonal tapers and then applies a kernel smoother, performs best. For 300 point data segments, even an optimized smoothed tapered periodogram has a 24% larger relative RMSE than the hybrid method. Two new adaptive multitaper weightings which outperform Thomson's original adaptive weighting are presented.
Fault detection in electromagnetic suspension systems with state estimation methods
Sinha, P.K.; Zhou, F.B.; Kutiyal, R.S. . Dept. of Engineering)
1993-11-01
High-speed maglev vehicles need a high level of safety that depends on the whole vehicle system's reliability. There are many ways of attaining high reliability for the system. Conventional method uses redundant hardware with majority vote logic circuits. Hardware redundancy costs more, weigh more and occupy more space than that of analytically redundant methods. Analytically redundant systems use parameter identification and state estimation methods based on the system models to detect and isolate the fault of instruments (sensors), actuator and components. In this paper the authors use the Luenberger observer to estimate three state variables of the electromagnetic suspension system: position (airgap), vehicle velocity, and vertical acceleration. These estimates are compared with the corresponding sensor outputs for fault detection. In this paper, they consider FDI of the accelerometer, the sensor which provides the ride quality.
Simplified triangle method for estimating evaporative fraction over soybean crops
NASA Astrophysics Data System (ADS)
Silva-Fuzzo, Daniela Fernanda; Rocha, Jansle Vieira
2016-10-01
Accurate estimates are emerging with technological advances in remote sensing, and the triangle method has demonstrated to be a useful tool for the estimation of evaporative fraction (EF). The purpose of this study was to estimate the EF using the triangle method at the regional level. We used data from the Moderate Resolution Imaging Spectroradiometer orbital sensor, referring to indices of surface temperature and vegetation index for a 10-year period (2002/2003 to 2011/2012) of cropping seasons in the state of Paraná, Brazil. The triangle method has shown considerable results for the EF, and the validation of the estimates, as compared to observed data of climatological water balance, showed values >0.8 for modified "d" of Wilmott and R2 values between 0.6 and 0.7 for some counties. The errors were low for all years analyzed, and the test showed that the estimated data are very close to the observed data. Based on statistical validation, we can say that the triangle method is a consistent tool, is useful as it uses only images of remote sensing as variables, and can provide support for monitoring large-scale agroclimatic, specially for countries of great territorial dimensions, such as Brazil, which lacks a more dense network of meteorological ground stations, i.e., the country does not appear to cover a large field for data.
New method for estimating low-earth-orbit collision probabilities
NASA Technical Reports Server (NTRS)
Vedder, John D.; Tabor, Jill L.
1991-01-01
An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.
Estimation Method of Body Temperature from Upper Arm Temperature
NASA Astrophysics Data System (ADS)
Suzuki, Arata; Ryu, Kazuteru; Kanai, Nobuyuki
This paper proposes a method for estimation of a body temperature by using a relation between the upper arm temperature and the atmospheric temperature. Conventional method has measured by armpit or oral, because the body temperature from the body surface is influenced by the atmospheric temperature. However, there is a correlation between the body surface temperature and the atmospheric temperature. By using this correlation, the body temperature can estimated from the body surface temperature. Proposed method enables to measure body temperature by the temperature sensor that is embedded in the blood pressure monitor cuff. Therefore, simultaneous measurement of blood pressure and body temperature can be realized. The effectiveness of the proposed method is verified through the actual body temperature experiment. The proposed method might contribute to reduce the medical staff's workloads in the home medical care, and more.
Modified cross-validation as a method for estimating parameter
NASA Astrophysics Data System (ADS)
Shi, Chye Rou; Adnan, Robiah
2014-12-01
Best subsets regression is an effective approach to distinguish models that can attain objectives with as few predictors as would be prudent. Subset models might really estimate the regression coefficients and predict future responses with smaller variance than the full model using all predictors. The inquiry of how to pick subset size λ depends on the bias and variance. There are various method to pick subset size λ. Regularly pick the smallest model that minimizes an estimate of the expected prediction error. Since data are regularly small, so Repeated K-fold cross-validation method is the most broadly utilized method to estimate prediction error and select model. The data is reshuffled and re-stratified before each round. However, the "one-standard-error" rule of Repeated K-fold cross-validation method always picks the most stingy model. The objective of this research is to modify the existing cross-validation method to avoid overfitting and underfitting model, a modified cross-validation method is proposed. This paper compares existing cross-validation and modified cross-validation. Our results reasoned that the modified cross-validation method is better at submodel selection and evaluation than other methods.
A review of action estimation methods for galactic dynamics
NASA Astrophysics Data System (ADS)
Sanders, Jason L.; Binney, James
2016-04-01
We review the available methods for estimating actions, angles and frequencies of orbits in both axisymmetric and triaxial potentials. The methods are separated into two classes. Unless an orbit has been trapped by a resonance, convergent, or iterative, methods are able to recover the actions to arbitrarily high accuracy given sufficient computing time. Faster non-convergent methods rely on the potential being sufficiently close to a separable potential, and the accuracy of the action estimate cannot be improved through further computation. We critically compare the accuracy of the methods and the required computation time for a range of orbits in an axisymmetric multicomponent Galactic potential. We introduce a new method for estimating actions that builds on the adiabatic approximation of Schönrich & Binney and discuss the accuracy required for the actions, angles and frequencies using suitable distribution functions for the thin and thick discs, the stellar halo and a star stream. We conclude that for studies of the disc and smooth halo component of the Milky Way, the most suitable compromise between speed and accuracy is the Stäckel Fudge, whilst when studying streams the non-convergent methods do not offer sufficient accuracy and the most suitable method is computing the actions from an orbit integration via a generating function. All the software used in this study can be downloaded from https://github.com/jls713/tact.
Hydrological model uncertainty due to spatial evapotranspiration estimation methods
NASA Astrophysics Data System (ADS)
Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub
2016-05-01
Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.
The deposit size frequency method for estimating undiscovered uranium deposits
McCammon, R.B.; Finch, W.I.
1993-01-01
The deposit size frequency (DSF) method has been developed as a generalization of the method that was used in the National Uranium Resource Evaluation (NURE) program to estimate the uranium endowment of the United States. The DSF method overcomes difficulties encountered during the NURE program when geologists were asked to provide subjective estimates of (1) the endowed fraction of an area judged favorable (factor F) for the occurrence of undiscovered uranium deposits and (2) the tons of endowed rock per unit area (factor T) within the endowed fraction of the favorable area. Because the magnitudes of factors F and T were unfamiliar to nearly all of the geologists, most geologists responded by estimating the number of undiscovered deposits likely to occur within the favorable area and the average size of these deposits. The DSF method combines factors F and T into a single factor (F??T) that represents the tons of endowed rock per unit area of the undiscovered deposits within the favorable area. Factor F??T, provided by the geologist, is the estimated number of undiscovered deposits per unit area in each of a number of specified deposit-size classes. The number of deposit-size classes and the size interval of each class are based on the data collected from the deposits in known (control) areas. The DSF method affords greater latitude in making subjective estimates than the NURE method and emphasizes more of the everyday experience of exploration geologists. Using the DSF method, new assessments have been made for the "young, organic-rich" surficial uranium deposits in Washington and idaho and for the solution-collapse breccia pipe uranium deposits in the Grand Canyon region in Arizona and adjacent Utah. ?? 1993 Oxford University Press.
Estimation of uncertainty for contour method residual stress measurements
Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; ...
2014-12-03
This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulnessmore » of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).« less
Estimation of uncertainty for contour method residual stress measurements
Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; Hill, Michael R.
2014-12-03
This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulness of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).
NASA Astrophysics Data System (ADS)
Forbes, B. T.
2015-12-01
Due to the predominantly arid climate in Arizona, access to adequate water supply is vital to the economic development and livelihood of the State. Water supply has become increasingly important during periods of prolonged drought, which has strained reservoir water levels in the Desert Southwest over past years. Arizona's water use is dominated by agriculture, consuming about seventy-five percent of the total annual water demand. Tracking current agricultural water use is important for managers and policy makers so that current water demand can be assessed and current information can be used to forecast future demands. However, many croplands in Arizona are irrigated outside of areas where water use reporting is mandatory. To estimate irrigation withdrawals on these lands, we use a combination of field verification, evapotranspiration (ET) estimation, and irrigation system qualification. ET is typically estimated in Arizona using the Modified Blaney-Criddle method which uses meteorological data to estimate annual crop water requirements. The Modified Blaney-Criddle method assumes crops are irrigated to their full potential over the entire growing season, which may or may not be realistic. We now use the Operational Simplified Surface Energy Balance (SSEBop) ET data in a remote-sensing and energy-balance framework to estimate cropland ET. SSEBop data are of sufficient resolution (30m by 30m) for estimation of field-scale cropland water use. We evaluate our SSEBop-based estimates using ground-truth information and irrigation system qualification obtained in the field. Our approach gives the end user an estimate of crop consumptive use as well as inefficiencies in irrigation system performance—both of which are needed by water managers for tracking irrigated water use in Arizona.
Kernel density estimation applied to bond length, bond angle, and torsion angle distributions.
McCabe, Patrick; Korb, Oliver; Cole, Jason
2014-05-27
We describe the method of kernel density estimation (KDE) and apply it to molecular structure data. KDE is a quite general nonparametric statistical method suitable even for multimodal data. The method generates smooth probability density function (PDF) representations and finds application in diverse fields such as signal processing and econometrics. KDE appears to have been under-utilized as a method in molecular geometry analysis, chemo-informatics, and molecular structure optimization. The resulting probability densities have advantages over histograms and, importantly, are also suitable for gradient-based optimization. To illustrate KDE, we describe its application to chemical bond length, bond valence angle, and torsion angle distributions and show the ability of the method to model arbitrary torsion angle distributions.
Inverse method for estimating shear stress in machining
NASA Astrophysics Data System (ADS)
Burns, T. J.; Mates, S. P.; Rhorer, R. L.; Whitenton, E. P.; Basak, D.
2016-01-01
An inverse method is presented for estimating shear stress in the work material in the region of chip-tool contact along the rake face of the tool during orthogonal machining. The method is motivated by a model of heat generation in the chip, which is based on a two-zone contact model for friction along the rake face, and an estimate of the steady-state flow of heat into the cutting tool. Given an experimentally determined discrete set of steady-state temperature measurements along the rake face of the tool, it is shown how to estimate the corresponding shear stress distribution on the rake face, even when no friction model is specified.
Improvement of Source Number Estimation Method for Single Channel Signal
Du, Bolun; He, Yunze
2016-01-01
Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin’s disk estimation (GDE) and minimum description length (MDL), are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC) obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely. PMID:27736959
Method for estimating spin-spin interactions from magnetization curves
NASA Astrophysics Data System (ADS)
Tamura, Ryo; Hukushima, Koji
2017-02-01
We develop a method to estimate the spin-spin interactions in the Hamiltonian from the observed magnetization curve by machine learning based on Bayesian inference. In our method, plausible spin-spin interactions are determined by maximizing the posterior distribution, which is the conditional probability of the spin-spin interactions in the Hamiltonian for a given magnetization curve with observation noise. The conditional probability is obtained with the Markov chain Monte Carlo simulations combined with an exchange Monte Carlo method. The efficiency of our method is tested using synthetic magnetization curve data, and the results show that spin-spin interactions are estimated with a high accuracy. In particular, the relevant terms of the spin-spin interactions are successfully selected from the redundant interaction candidates by the l1 regularization in the prior distribution.
A study of methods to estimate debris flow velocity
Prochaska, A.B.; Santi, P.M.; Higgins, J.D.; Cannon, S.H.
2008-01-01
Debris flow velocities are commonly back-calculated from superelevation events which require subjective estimates of radii of curvature of bends in the debris flow channel or predicted using flow equations that require the selection of appropriate rheological models and material property inputs. This research investigated difficulties associated with the use of these conventional velocity estimation methods. Radii of curvature estimates were found to vary with the extent of the channel investigated and with the scale of the media used, and back-calculated velocities varied among different investigated locations along a channel. Distinct populations of Bingham properties were found to exist between those measured by laboratory tests and those back-calculated from field data; thus, laboratory-obtained values would not be representative of field-scale debris flow behavior. To avoid these difficulties with conventional methods, a new preliminary velocity estimation method is presented that statistically relates flow velocity to the channel slope and the flow depth. This method presents ranges of reasonable velocity predictions based on 30 previously measured velocities. ?? 2008 Springer-Verlag.
Neural Network Based Method for Estimating Helicopter Low Airspeed
1996-10-24
The present invention relates generally to virtual sensors and, more particularly, to a means and method utilizing a neural network for estimating...helicopter airspeed at speeds below about 50 knots using only fixed system parameters (i.e., parameters measured or determined in a reference frame fixed relative to the helicopter fuselage) as inputs to the neural network .
A preliminary comparison of different methods for observer performance estimation
NASA Astrophysics Data System (ADS)
Massanes, Francesc; Brankov, Jovan G.
2013-03-01
In medical imaging, image quality is assessed by the degree to which a human observer can correctly perform a given diagnostic task. Therefore the image quality is typically quantified by using performance measurements from decision/detection theory like the receiver operation characteristic (ROC) curve and the area under ROC curve (AUC). In this paper we compare five different AUC estimation techniques, widely used in the literature, including parametric and non-parametric methods. We compared each method by equivalence hypothesis testing using a model observer as well as data sets from a previously published human observer study. The main conclusions of this work are 1) if a small number of images are scored, one cannot tell apart different AUC estimation methods due to large variability in AUC estimates, regardless whether image scores are reported on a continuous or quantized scale. 2) If the number of scored images is large and image scores are reported on a continuous scale, all tested AUC estimation methods are statistically equivalent.
Applications of truncated QR methods to sinusoidal frequency estimation
NASA Technical Reports Server (NTRS)
Hsieh, S. F.; Liu, K. J. R.; Yao, K.
1990-01-01
Three truncated QR methods are proposed for sinusoidal frequency estimation: (1) truncated QR without column pivoting (TQR), (2) truncated QR with preordered columns, and (3) truncated QR with column pivoting. It is demonstrated that the benefit of truncated SVD for high frequency resolution is achievable under the truncated QR approach with much lower computational cost. Other attractive features of the proposed methods include the ease of updating, which is difficult for the SVD method, and numerical stability. TQR methods thus offer efficient ways to identify sinusoidals closely clustered in frequencies under stationary and nonstationary conditions.
Stress intensity estimates by a computer assisted photoelastic method
NASA Technical Reports Server (NTRS)
Smith, C. W.
1977-01-01
Following an introductory history, the frozen stress photoelastic method is reviewed together with analytical and experimental aspects of cracks in photoelastic models. Analytical foundations are then presented upon which a computer assisted frozen stress photoelastic technique is based for extracting estimates of stress intensity factors from three-dimensional cracked body problems. The use of the method is demonstrated for two currently important three-dimensional crack problems.
Three Different Methods of Estimating LAI in a Small Watershed
NASA Astrophysics Data System (ADS)
Speckman, H. N.; Ewers, B. E.; Beverly, D.
2015-12-01
Leaf area index (LAI) is a critical input of models that improve predictive understanding of ecology, hydrology, and climate change. Multiple techniques exist to quantify LAI, most of which are labor intensive, and all often fail to converge on similar estimates. . Recent large-scale bark beetle induced mortality greatly altered LAI, which is now dominated by younger and more metabolically active trees compared to the pre-beetle forest. Tree mortality increases error in optical LAI estimates due to the lack of differentiation between live and dead branches in dense canopy. Our study aims to quantify LAI using three different LAI methods, and then to compare the techniques to each other and topographic drivers to develop an effective predictive model of LAI. This study focuses on quantifying LAI within a small (~120 ha) beetle infested watershed in Wyoming's Snowy Range Mountains. The first technique estimated LAI using in-situ hemispherical canopy photographs that were then analyzed with Hemisfer software. The second LAI estimation technique was use of the Kaufmann 1982 allometrerics from forest inventories conducted throughout the watershed, accounting for stand basal area, species composition, and the extent of bark beetle driven mortality. The final technique used airborne light detection and ranging (LIDAR) first DMS returns, which were used to estimating canopy heights and crown area. LIDAR final returns provided topographical information and were then ground-truthed during forest inventories. Once data was collected, a fractural analysis was conducted comparing the three methods. Species composition was driven by slope position and elevation Ultimately the three different techniques provided very different estimations of LAI, but each had their advantage: estimates from hemisphere photos were well correlated with SWE and snow depth measurements, forest inventories provided insight into stand health and composition, and LIDAR were able to quickly and
Comparison of Methods for Estimating Low Flow Characteristics of Streams
Tasker, Gary D.
1987-01-01
Four methods for estimating the 7-day, 10-year and 7-day, 20-year low flows for streams are compared by the bootstrap method. The bootstrap method is a Monte Carlo technique in which random samples are drawn from an unspecified sampling distribution defined from observed data. The nonparametric nature of the bootstrap makes it suitable for comparing methods based on a flow series for which the true distribution is unknown. Results show that the two methods based on hypothetical distribution (Log-Pearson III and Weibull) had lower mean square errors than did the G. E. P. Box-D. R. Cox transformation method or the Log-W. C. Boughton method which is based on a fit of plotting positions.
Scanziani, Alessio; Singh, Kamaljit; Blunt, Martin J; Guadagnini, Alberto
2017-06-15
Multiphase flow in porous media is strongly influenced by the wettability of the system, which affects the arrangement of the interfaces of different phases residing in the pores. We present a method for estimating the effective contact angle, which quantifies the wettability and controls the local capillary pressure within the complex pore space of natural rock samples, based on the physical constraint of constant curvature of the interface between two fluids. This algorithm is able to extract a large number of measurements from a single rock core, resulting in a characteristic distribution of effective in situ contact angle for the system, that is modelled as a truncated Gaussian probability density distribution. The method is first validated on synthetic images, where the exact angle is known analytically; then the results obtained from measurements within the pore space of rock samples imaged at a resolution of a few microns are compared to direct manual assessment. Finally the method is applied to X-ray micro computed tomography (micro-CT) scans of two Ketton cores after waterflooding, that display water-wet and mixed-wet behaviour. The resulting distribution of in situ contact angles is characterized in terms of a mixture of truncated Gaussian densities.
Methods for Measuring and Estimating Methane Emission from Ruminants
Storm, Ida M. L. D.; Hellwing, Anne Louise F.; Nielsen, Nicolaj I.; Madsen, Jørgen
2012-01-01
Simple Summary Knowledge about methods used in quantification of greenhouse gasses is currently needed due to international commitments to reduce the emissions. In the agricultural sector one important task is to reduce enteric methane emissions from ruminants. Different methods for quantifying these emissions are presently being used and others are under development, all with different conditions for application. For scientist and other persons working with the topic it is very important to understand the advantages and disadvantage of the different methods in use. This paper gives a brief introduction to existing methods but also a description of newer methods and model-based techniques. Abstract This paper is a brief introduction to the different methods used to quantify the enteric methane emission from ruminants. A thorough knowledge of the advantages and disadvantages of these methods is very important in order to plan experiments, understand and interpret experimental results, and compare them with other studies. The aim of the paper is to describe the principles, advantages and disadvantages of different methods used to quantify the enteric methane emission from ruminants. The best-known methods: Chambers/respiration chambers, SF6 technique and in vitro gas production technique and the newer CO2 methods are described. Model estimations, which are used to calculate national budget and single cow enteric emission from intake and diet composition, are also discussed. Other methods under development such as the micrometeorological technique, combined feeder and CH4 analyzer and proxy methods are briefly mentioned. Methods of choice for estimating enteric methane emission depend on aim, equipment, knowledge, time and money available, but interpretation of results obtained with a given method can be improved if knowledge about the disadvantages and advantages are used in the planning of experiments. PMID:26486915
Noninvasive method of estimating human newborn regional cerebral blood flow
Younkin, D.P.; Reivich, M.; Jaggi, J.; Obrist, W.; Delivoria-Papadopoulos, M.
1982-12-01
A noninvasive method of estimating regional cerebral blood flow (rCBF) in premature and full-term babies has been developed. Based on a modification of the /sup 133/Xe inhalation rCBF technique, this method uses eight extracranial NaI scintillation detectors and an i.v. bolus injection of /sup 133/Xe (approximately 0.5 mCi/kg). Arterial xenon concentration was estimated with an external chest detector. Cerebral blood flow was measured in 15 healthy, neurologically normal premature infants. Using Obrist's method of two-compartment analysis, normal values were calculated for flow in both compartments, relative weight and fractional flow in the first compartment (gray matter), initial slope of gray matter blood flow, mean cerebral blood flow, and initial slope index of mean cerebral blood flow. The application of this technique to newborns, its relative advantages, and its potential uses are discussed.
New Statistical Learning Methods for Estimating Optimal Dynamic Treatment Regimes
Zhao, Ying-Qi; Zeng, Donglin; Laber, Eric B.; Kosorok, Michael R.
2014-01-01
Dynamic treatment regimes (DTRs) are sequential decision rules for individual patients that can adapt over time to an evolving illness. The goal is to accommodate heterogeneity among patients and find the DTR which will produce the best long term outcome if implemented. We introduce two new statistical learning methods for estimating the optimal DTR, termed backward outcome weighted learning (BOWL), and simultaneous outcome weighted learning (SOWL). These approaches convert individualized treatment selection into an either sequential or simultaneous classification problem, and can thus be applied by modifying existing machine learning techniques. The proposed methods are based on directly maximizing over all DTRs a nonparametric estimator of the expected long-term outcome; this is fundamentally different than regression-based methods, for example Q-learning, which indirectly attempt such maximization and rely heavily on the correctness of postulated regression models. We prove that the resulting rules are consistent, and provide finite sample bounds for the errors using the estimated rules. Simulation results suggest the proposed methods produce superior DTRs compared with Q-learning especially in small samples. We illustrate the methods using data from a clinical trial for smoking cessation. PMID:26236062
An aerial survey method to estimate sea otter abundance
Bodkin, J.L.; Udevitz, M.S.; Garner, G.W.; Amstrup, Steven C.; Laake, J.L.; Manly, B. F. J.; McDonald, L.L.; Robertson, Donna G.
1999-01-01
Sea otters (Enhydra lutris) occur in shallow coastal habitats and can be highly visible on the sea surface. They generally rest in groups and their detection depends on factors that include sea conditions, viewing platform, observer technique and skill, distance, habitat and group size. While visible on the surface, they are difficult to see while diving and may dive in response to an approaching survey platform. We developed and tested an aerial survey method that uses intensive searches within portions of strip transects to adjust for availability and sightability biases. Correction factors are estimated independently for each survey and observer. In tests of our method using shore-based observers, we estimated detection probabilities of 0.52-0.72 in standard strip-transects and 0.96 in intensive searches. We used the survey method in Prince William Sound, Alaska to estimate a sea otter population size of 9,092 (SE = 1422). The new method represents an improvement over various aspects of previous methods, but additional development and testing will be required prior to its broad application.
Parameter estimation method for blurred cell images from fluorescence microscope
NASA Astrophysics Data System (ADS)
He, Fuyun; Zhang, Zhisheng; Luo, Xiaoshu; Zhao, Shulin
2016-10-01
Microscopic cell image analysis is indispensable to cell biology. Images of cells can easily degrade due to optical diffraction or focus shift, as this results in low signal-to-noise ratio (SNR) and poor image quality, hence affecting the accuracy of cell analysis and identification. For a quantitative analysis of cell images, restoring blurred images to improve the SNR is the first step. A parameter estimation method for defocused microscopic cell images based on the power law properties of the power spectrum of cell images is proposed. The circular radon transform (CRT) is used to identify the zero-mode of the power spectrum. The parameter of the CRT curve is initially estimated by an improved differential evolution algorithm. Following this, the parameters are optimized through the gradient descent method. Using synthetic experiments, it was confirmed that the proposed method effectively increased the peak SNR (PSNR) of the recovered images with high accuracy. Furthermore, experimental results involving actual microscopic cell images verified that the superiority of the proposed parameter estimation method for blurred microscopic cell images other method in terms of qualitative visual sense as well as quantitative gradient and PSNR.
Method to Estimate the Dissolved Air Content in Hydraulic Fluid
NASA Technical Reports Server (NTRS)
Hauser, Daniel M.
2011-01-01
In order to verify the air content in hydraulic fluid, an instrument was needed to measure the dissolved air content before the fluid was loaded into the system. The instrument also needed to measure the dissolved air content in situ and in real time during the de-aeration process. The current methods used to measure the dissolved air content require the fluid to be drawn from the hydraulic system, and additional offline laboratory processing time is involved. During laboratory processing, there is a potential for contamination to occur, especially when subsaturated fluid is to be analyzed. A new method measures the amount of dissolved air in hydraulic fluid through the use of a dissolved oxygen meter. The device measures the dissolved air content through an in situ, real-time process that requires no additional offline laboratory processing time. The method utilizes an instrument that measures the partial pressure of oxygen in the hydraulic fluid. By using a standardized calculation procedure that relates the oxygen partial pressure to the volume of dissolved air in solution, the dissolved air content is estimated. The technique employs luminescent quenching technology to determine the partial pressure of oxygen in the hydraulic fluid. An estimated Henry s law coefficient for oxygen and nitrogen in hydraulic fluid is calculated using a standard method to estimate the solubility of gases in lubricants. The amount of dissolved oxygen in the hydraulic fluid is estimated using the Henry s solubility coefficient and the measured partial pressure of oxygen in solution. The amount of dissolved nitrogen that is in solution is estimated by assuming that the ratio of dissolved nitrogen to dissolved oxygen is equal to the ratio of the gas solubility of nitrogen to oxygen at atmospheric pressure and temperature. The technique was performed at atmospheric pressure and room temperature. The technique could be theoretically carried out at higher pressures and elevated
Dental age estimation using Willems method: A digital orthopantomographic study
Mohammed, Rezwana Begum; Krishnamraju, P. V.; Prasanth, P. S.; Sanghvi, Praveen; Lata Reddy, M. Asha; Jyotsna, S.
2014-01-01
In recent years, age estimation has become increasingly important in living people for a variety of reasons, including identifying criminal and legal responsibility, and for many other social events such as a birth certificate, marriage, beginning a job, joining the army, and retirement. Objectives: The aim of this study was to assess the developmental stages of left seven mandibular teeth for estimation of dental age (DA) in different age groups and to evaluate the possible correlation between DA and chronological age (CA) in South Indian population using Willems method. Materials and Methods: Digital Orthopantomogram of 332 subjects (166 males, 166 females) who fit the study and the criteria were obtained. Assessment of mandibular teeth (from central incisor to the second molar on left quadrant) development was undertaken and DA was assessed using Willems method. Results and Discussion: The present study showed a significant correlation between DA and CA in both males (r = 0.71 and females (r = 0.88). The overall mean difference between the estimated DA and CA for males was 0.69 ± 2.14 years (P < 0.001) while for females, it was 0.08 ± 1.34 years (P > 0.05). Willems method underestimated the mean age of males by 0.69 years and females by 0.08 years and showed that females mature earlier than males in selected population. The mean difference between DA and CA according to Willems method was 0.39 years and is statistically significant (P < 0.05). Conclusion: This study showed significant relation between DA and CA. Thus, digital radiographic assessment of mandibular teeth development can be used to generate mean DA using Willems method and also the estimated age range for an individual of unknown CA. PMID:25191076
NEW COMPLETENESS METHODS FOR ESTIMATING EXOPLANET DISCOVERIES BY DIRECT DETECTION
Brown, Robert A.; Soummer, Remi
2010-05-20
We report on new methods for evaluating realistic observing programs that search stars for planets by direct imaging, where observations are selected from an optimized star list and stars can be observed multiple times. We show how these methods bring critical insight into the design of the mission and its instruments. These methods provide an estimate of the outcome of the observing program: the probability distribution of discoveries (detection and/or characterization) and an estimate of the occurrence rate of planets ({eta}). We show that these parameters can be accurately estimated from a single mission simulation, without the need for a complete Monte Carlo mission simulation, and we prove the accuracy of this new approach. Our methods provide tools to define a mission for a particular science goal; for example, a mission can be defined by the expected number of discoveries and its confidence level. We detail how an optimized star list can be built and how successive observations can be selected. Our approach also provides other critical mission attributes, such as the number of stars expected to be searched and the probability of zero discoveries. Because these attributes depend strongly on the mission scale (telescope diameter, observing capabilities and constraints, mission lifetime, etc.), our methods are directly applicable to the design of such future missions and provide guidance to the mission and instrument design based on scientific performance. We illustrate our new methods with practical calculations and exploratory design reference missions for the James Webb Space Telescope (JWST) operating with a distant starshade to reduce scattered and diffracted starlight on the focal plane. We estimate that five habitable Earth-mass planets would be discovered and characterized with spectroscopy, with a probability of zero discoveries of 0.004, assuming a small fraction of JWST observing time (7%), {eta} = 0.3, and 70 observing visits, limited by starshade
Methods to estimate irrigated reference crop evapotranspiration - a review.
Kumar, R; Jat, M K; Shankar, V
2012-01-01
Efficient water management of crops requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Irrigation is applied to replenish depleted moisture for optimum plant growth. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. Mathematical models are useful tools to estimate the evapotranspiration and water requirement of crops, which is essential information required to design or choose best water management practices. In this paper the most commonly used models/approaches, which are suitable for the estimation of daily water requirement for agricultural crops grown in different agro-climatic regions, are reviewed. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions.
pyGMMis: Mixtures-of-Gaussians density estimation method
NASA Astrophysics Data System (ADS)
Melchior, Peter; Goulding, Andy D.
2016-11-01
pyGMMis is a mixtures-of-Gaussians density estimation method that accounts for arbitrary incompleteness in the process that creates the samples as long as the incompleteness is known over the entire feature space and does not depend on the sample density (missing at random). pyGMMis uses the Expectation-Maximization procedure and generates its best guess of the unobserved samples on the fly. It can also incorporate an uniform "background" distribution as well as independent multivariate normal measurement errors for each of the observed samples, and then recovers an estimate of the error-free distribution from which both observed and unobserved samples are drawn. The code automatically segments the data into localized neighborhoods, and is capable of performing density estimation with millions of samples and thousands of model components on machines with sufficient memory.
A generic computerized method for estimate of familial risks.
Colombet, Isabelle; Xu, Yigang; Jaulent, Marie-Christine; Desages, Daniel; Degoulet, Patrice; Chatellier, Gilles
2002-01-01
Most guidelines developed for cancers screening and for cardiovascular risk management use rules to estimate familial risk. These rules are complex, difficult to memorize, and need to collect a complete pedigree. This paper describes a generic computerized method to estimate familial risks and its implementation in an internet-based application. The program is based on 3 generic models: a model of the family; a model of familial risk; a display model for the pedigree. The model of family allows to represent each member of the family and to construct and display a family tree. The model of familial risk is generic and allows easy update of the program with new diseases or new rules. It was possible to implement guidelines dealing with breast and colorectal cancer and cardiovascular diseases prevention. First evaluation with general practitioners showed that the program was usable. Impact on quality of familial risk estimate should be more documented. PMID:12463810
Smeared star spot location estimation using directional integral method.
Hou, Wang; Liu, Haibo; Lei, Zhihui; Yu, Qifeng; Liu, Xiaochun; Dong, Jing
2014-04-01
Image smearing significantly affects the accuracy of attitude determination of most star sensors. To ensure the accuracy and reliability of a star sensor under image smearing conditions, a novel directional integral method is presented for high-precision star spot location estimation to improve the accuracy of attitude determination. Simulations based on the orbit data of the challenging mini-satellite payload satellite were performed. Simulation results demonstrated that the proposed method exhibits high performance and good robustness, which indicates that the method can be applied effectively.
Methods of Mmax Estimation East of the Rocky Mountains
Wheeler, Russell L.
2009-01-01
Several methods have been used to estimate the magnitude of the largest possible earthquake (Mmax) in parts of the Central and Eastern United States and adjacent Canada (CEUSAC). Each method has pros and cons. The largest observed earthquake in a specified area provides an unarguable lower bound on Mmax in the area. Beyond that, all methods are undermined by the enigmatic nature of geologic controls on the propagation of large CEUSAC ruptures. Short historical-seismicity records decrease the defensibility of several methods that are based on characteristics of small areas in most of CEUSAC. Methods that use global tectonic analogs of CEUSAC encounter uncertainties in understanding what 'analog' means. Five of the methods produce results that are inconsistent with paleoseismic findings from CEUSAC seismic zones or individual active faults.
A Statistical Method for Estimating Luminosity Functions Using Truncated Data
NASA Astrophysics Data System (ADS)
Schafer, Chad M.
2007-06-01
The observational limitations of astronomical surveys lead to significant statistical inference challenges. One such challenge is the estimation of luminosity functions given redshift (z) and absolute magnitude (M) measurements from an irregularly truncated sample of objects. This is a bivariate density estimation problem; we develop here a statistically rigorous method which (1) does not assume a strict parametric form for the bivariate density; (2) does not assume independence between redshift and absolute magnitude (and hence allows evolution of the luminosity function with redshift); (3) does not require dividing the data into arbitrary bins; and (4) naturally incorporates a varying selection function. We accomplish this by decomposing the bivariate density φ(z,M) vialogφ(z,M)=f(z)+g(M)+h(z,M,θ), where f and g are estimated nonparametrically and h takes an assumed parametric form. There is a simple way of estimating the integrated mean squared error of the estimator; smoothing parameters are selected to minimize this quantity. Results are presented from the analysis of a sample of quasars.
A Subspace Method for Dynamical Estimation of Evoked Potentials
Georgiadis, Stefanos D.; Ranta-aho, Perttu O.; Tarvainen, Mika P.; Karjalainen, Pasi A.
2007-01-01
It is a challenge in evoked potential (EP) analysis to incorporate prior physiological knowledge for estimation. In this paper, we address the problem of single-channel trial-to-trial EP characteristics estimation. Prior information about phase-locked properties of the EPs is assesed by means of estimated signal subspace and eigenvalue decomposition. Then for those situations that dynamic fluctuations from stimulus-to-stimulus could be expected, prior information can be exploited by means of state-space modeling and recursive Bayesian mean square estimation methods (Kalman filtering and smoothing). We demonstrate that a few dominant eigenvectors of the data correlation matrix are able to model trend-like changes of some component of the EPs, and that Kalman smoother algorithm is to be preferred in terms of better tracking capabilities and mean square error reduction. We also demonstrate the effect of strong artifacts, particularly eye blinks, on the quality of the signal subspace and EP estimates by means of independent component analysis applied as a prepossessing step on the multichannel measurements. PMID:18288257
Optimizing Probability of Detection Point Estimate Demonstration
NASA Technical Reports Server (NTRS)
Koshti, Ajay M.
2017-01-01
Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-18231and associated mh18232POD software gives most common methods of POD analysis. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using Point Estimate Method. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible.
Networked Estimation with an Area-Triggered Transmission Method
Nguyen, Vinh Hao; Suh, Young Soo
2008-01-01
This paper is concerned with the networked estimation problem in which sensor data are transmitted over the network. In the event-driven sampling scheme known as level-crossing or send-on-delta, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. The event-driven sampling generally requires less transmission than the time-driven one. However, the transmission rate of the send-on-delta method becomes large when the sensor noise is large since sensor data variation becomes large due to the sensor noise. Motivated by this issue, we propose another event-driven sampling method called area-triggered in which sensor data are sent only when the integral of differences between the current sensor value and the last transmitted one is greater than a given threshold. Through theoretical analysis and simulation results, we show that in the certain cases the proposed method not only reduces data transmission rate but also improves estimation performance in comparison with the conventional event-driven method. PMID:27879742
Estimating the extreme low-temperature event using nonparametric methods
NASA Astrophysics Data System (ADS)
D'Silva, Anisha
This thesis presents a new method of estimating the one-in-N low temperature threshold using a non-parametric statistical method called kernel density estimation applied to daily average wind-adjusted temperatures. We apply our One-in-N Algorithm to local gas distribution companies (LDCs), as they have to forecast the daily natural gas needs of their consumers. In winter, demand for natural gas is high. Extreme low temperature events are not directly related to an LDCs gas demand forecasting, but knowledge of extreme low temperatures is important to ensure that an LDC has enough capacity to meet customer demands when extreme low temperatures are experienced. We present a detailed explanation of our One-in-N Algorithm and compare it to the methods using the generalized extreme value distribution, the normal distribution, and the variance-weighted composite distribution. We show that our One-in-N Algorithm estimates the one-in- N low temperature threshold more accurately than the methods using the generalized extreme value distribution, the normal distribution, and the variance-weighted composite distribution according to root mean square error (RMSE) measure at a 5% level of significance. The One-in- N Algorithm is tested by counting the number of times the daily average wind-adjusted temperature is less than or equal to the one-in- N low temperature threshold.
Advances in Time Estimation Methods for Molecular Data.
Kumar, Sudhir; Hedges, S Blair
2016-04-01
Molecular dating has become central to placing a temporal dimension on the tree of life. Methods for estimating divergence times have been developed for over 50 years, beginning with the proposal of molecular clock in 1962. We categorize the chronological development of these methods into four generations based on the timing of their origin. In the first generation approaches (1960s-1980s), a strict molecular clock was assumed to date divergences. In the second generation approaches (1990s), the equality of evolutionary rates between species was first tested and then a strict molecular clock applied to estimate divergence times. The third generation approaches (since ∼2000) account for differences in evolutionary rates across the tree by using a statistical model, obviating the need to assume a clock or to test the equality of evolutionary rates among species. Bayesian methods in the third generation require a specific or uniform prior on the speciation-process and enable the inclusion of uncertainty in clock calibrations. The fourth generation approaches (since 2012) allow rates to vary from branch to branch, but do not need prior selection of a statistical model to describe the rate variation or the specification of speciation model. With high accuracy, comparable to Bayesian approaches, and speeds that are orders of magnitude faster, fourth generation methods are able to produce reliable timetrees of thousands of species using genome scale data. We found that early time estimates from second generation studies are similar to those of third and fourth generation studies, indicating that methodological advances have not fundamentally altered the timetree of life, but rather have facilitated time estimation by enabling the inclusion of more species. Nonetheless, we feel an urgent need for testing the accuracy and precision of third and fourth generation methods, including their robustness to misspecification of priors in the analysis of large phylogenies and data
Vegetation index methods for estimating evapotranspiration by remote sensing
Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.
2010-01-01
Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45–0.95, and root mean square errors are in the range of 10–30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates.
Richardson, John G.
2009-11-17
An impedance estimation method includes measuring three or more impedances of an object having a periphery using three or more probes coupled to the periphery. The three or more impedance measurements are made at a first frequency. Three or more additional impedance measurements of the object are made using the three or more probes. The three or more additional impedance measurements are made at a second frequency different from the first frequency. An impedance of the object at a point within the periphery is estimated based on the impedance measurements and the additional impedance measurements.
Simple Method for Soil Moisture Estimation from Sentinel-1 Data
NASA Astrophysics Data System (ADS)
Gilewski, Pawei Grzegorz; Kedzior, Mateusz Andrzej; Zawadzki, Jaroslaw
2016-08-01
In this paper, authors calculated high resolution volumetric soil moisture (SM) by means of the Sentinel- 1 data for the Kampinos National Park in Poland and verified obtained results.To do so, linear regression coefficients (LRC) between in-situ SM measurements and Sentinel-1 radar backscatter values were calculated. Next, LRC were applied to obtain SM estimates from Sentinel-1 data. Sentinel-1 SM was verified against in-situ measurements and low-resolution SMOS SM estimates using Pearson's linear correlation coefficient. Simple SM retrieval method from radar data used in this study gives better results for meadows and when Sentinel-1 data in VH polarisation are used.Further research should be conducted to prove usefulness of proposed method.
Estimating surface acoustic impedance with the inverse method.
Piechowicz, Janusz
2011-01-01
Sound field parameters are predicted with numerical methods in sound control systems, in acoustic designs of building and in sound field simulations. Those methods define the acoustic properties of surfaces, such as sound absorption coefficients or acoustic impedance, to determine boundary conditions. Several in situ measurement techniques were developed; one of them uses 2 microphones to measure direct and reflected sound over a planar test surface. Another approach is used in the inverse boundary elements method, in which estimating acoustic impedance of a surface is expressed as an inverse boundary problem. The boundary values can be found from multipoint sound pressure measurements in the interior of a room. This method can be applied to arbitrarily-shaped surfaces. This investigation is part of a research programme on using inverse methods in industrial room acoustics.
Adaptive error covariances estimation methods for ensemble Kalman filters
Zhen, Yicun; Harlim, John
2015-08-01
This paper presents a computationally fast algorithm for estimating, both, the system and observation noise covariances of nonlinear dynamics, that can be used in an ensemble Kalman filtering framework. The new method is a modification of Belanger's recursive method, to avoid an expensive computational cost in inverting error covariance matrices of product of innovation processes of different lags when the number of observations becomes large. When we use only product of innovation processes up to one-lag, the computational cost is indeed comparable to a recently proposed method by Berry–Sauer's. However, our method is more flexible since it allows for using information from product of innovation processes of more than one-lag. Extensive numerical comparisons between the proposed method and both the original Belanger's and Berry–Sauer's schemes are shown in various examples, ranging from low-dimensional linear and nonlinear systems of SDEs and 40-dimensional stochastically forced Lorenz-96 model. Our numerical results suggest that the proposed scheme is as accurate as the original Belanger's scheme on low-dimensional problems and has a wider range of more accurate estimates compared to Berry–Sauer's method on L-96 example.
Methods to Develop Inhalation Cancer Risk Estimates for ...
This document summarizes the approaches and rationale for the technical and scientific considerations used to derive inhalation cancer risks for emissions of chromium and nickel compounds from electric utility steam generating units. The purpose of this document is to discuss the methods used to develop inhalation cancer risk estimates associated with emissions of chromium and nickel compounds from coal- and oil-fired electric utility steam generating units (EGUs) in support of EPA's recently proposed Air Toxics Rule.
Improving stochastic estimates with inference methods: Calculating matrix diagonals
NASA Astrophysics Data System (ADS)
Selig, Marco; Oppermann, Niels; Enßlin, Torsten A.
2012-02-01
Estimating the diagonal entries of a matrix, that is not directly accessible but only available as a linear operator in the form of a computer routine, is a common necessity in many computational applications, especially in image reconstruction and statistical inference. Here, methods of statistical inference are used to improve the accuracy or the computational costs of matrix probing methods to estimate matrix diagonals. In particular, the generalized Wiener filter methodology, as developed within information field theory, is shown to significantly improve estimates based on only a few sampling probes, in cases in which some form of continuity of the solution can be assumed. The strength, length scale, and precise functional form of the exploited autocorrelation function of the matrix diagonal is determined from the probes themselves. The developed algorithm is successfully applied to mock and real world problems. These performance tests show that, in situations where a matrix diagonal has to be calculated from only a small number of computationally expensive probes, a speedup by a factor of 2 to 10 is possible with the proposed method.
Methods for estimating low-flow statistics for Massachusetts streams
Ries, Kernell G.; Friesz, Paul J.
2000-01-01
Methods and computer software are described in this report for determining flow duration, low-flow frequency statistics, and August median flows. These low-flow statistics can be estimated for unregulated streams in Massachusetts using different methods depending on whether the location of interest is at a streamgaging station, a low-flow partial-record station, or an ungaged site where no data are available. Low-flow statistics for streamgaging stations can be estimated using standard U.S. Geological Survey methods described in the report. The MOVE.1 mathematical method and a graphical correlation method can be used to estimate low-flow statistics for low-flow partial-record stations. The MOVE.1 method is recommended when the relation between measured flows at a partial-record station and daily mean flows at a nearby, hydrologically similar streamgaging station is linear, and the graphical method is recommended when the relation is curved. Equations are presented for computing the variance and equivalent years of record for estimates of low-flow statistics for low-flow partial-record stations when either a single or multiple index stations are used to determine the estimates. The drainage-area ratio method or regression equations can be used to estimate low-flow statistics for ungaged sites where no data are available. The drainage-area ratio method is generally as accurate as or more accurate than regression estimates when the drainage-area ratio for an ungaged site is between 0.3 and 1.5 times the drainage area of the index data-collection site. Regression equations were developed to estimate the natural, long-term 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent duration flows; the 7-day, 2-year and the 7-day, 10-year low flows; and the August median flow for ungaged sites in Massachusetts. Streamflow statistics and basin characteristics for 87 to 133 streamgaging stations and low-flow partial-record stations were used to develop the equations. The
The composite method: An improved method for stream-water solute load estimation
Aulenbach, Brent T.; Hooper, R.P.
2006-01-01
The composite method is an alternative method for estimating stream-water solute loads, combining aspects of two commonly used methods: the regression-model method (which is used by the composite method to predict variations in concentrations between collected samples) and a period-weighted approach (which is used by the composite method to apply the residual concentrations from the regression model over time). The extensive dataset collected at the outlet of the Panola Mountain Research Watershed (PMRW) near Atlanta, Georgia, USA, was used in data analyses for illustrative purposes. A bootstrap (subsampling) experiment (using the composite method and the PMRW dataset along with various fixed-interval and large storm sampling schemes) obtained load estimates for the 8-year study period with a magnitude of the bias of less than 1%, even for estimates that included the fewest number of samples. Precisions were always <2% on a study period and annual basis, and <2% precisions were obtained for quarterly and monthly time intervals for estimates that had better sampling. The bias and precision of composite-method load estimates varies depending on the variability in the regression-model residuals, how residuals systematically deviated from the regression model over time, sampling design, and the time interval of the load estimate. The regression-model method did not estimate loads precisely during shorter time intervals, from annually to monthly, because the model could not explain short-term patterns in the observed concentrations. Load estimates using the period-weighted approach typically are biased as a result of sampling distribution and are accurate only with extensive sampling. The formulation of the composite method facilitates exploration of patterns (trends) contained in the unmodelled portion of the load. Published in 2006 by John Wiley & Sons, Ltd.
Evaluation of estimation methods for organic carbon normalized sorption coefficients
Baker, James R.; Mihelcic, James R.; Luehrs, Dean C.; Hickey, James P.
1997-01-01
A critically evaluated set of 94 soil water partition coefficients normalized to soil organic carbon content (Koc) is presented for 11 classes of organic chemicals. This data set is used to develop and evaluate Koc estimation methods using three different descriptors. The three types of descriptors used in predicting Koc were octanol/water partition coefficient (Kow), molecular connectivity (mXt) and linear solvation energy relationships (LSERs). The best results were obtained estimating Koc from Kow, though a slight improvement in the correlation coefficient was obtained by using a two-parameter regression with Kow and the third order difference term from mXt. Molecular connectivity correlations seemed to be best suited for use with specific chemical classes. The LSER provided a better fit than mXt but not as good as the correlation with Koc. The correlation to predict Koc from Kow was developed for 72 chemicals; log Koc = 0.903* log Kow + 0.094. This correlation accounts for 91% of the variability in the data for chemicals with log Kow ranging from 1.7 to 7.0. The expression to determine the 95% confidence interval on the estimated Koc is provided along with an example for two chemicals of different hydrophobicity showing the confidence interval of the retardation factor determined from the estimated Koc. The data showed that Koc is not likely to be applicable for chemicals with log Kow < 1.7. Finally, the Koc correlation developed using Kow as a descriptor was compared with three nonclass-specific correlations and two 'commonly used' class-specific correlations to determine which method(s) are most suitable.
Reliability of field methods for estimating body fat.
Loenneke, Jeremy P; Barnes, Jeremy T; Wilson, Jacob M; Lowery, Ryan P; Isaacs, Melissa N; Pujol, Thomas J
2013-09-01
When health professionals measure the fitness levels of clients, body composition is usually estimated. In practice, the reliability of the measurement may be more important than the actual validity, as reliability determines how much change is needed to be considered meaningful. Therefore, the purpose of this study was to determine the reliability of two bioelectrical impedance analysis (BIA) devices (in athlete and non-athlete mode) and compare that to 3-site skinfold (SKF) readings. Twenty-one college students attended the laboratory on two occasions and had their measurements taken in the following order: body mass, height, SKF, Tanita body fat-350 (BF-350) and Omron HBF-306C. There were no significant pairwise differences between Visit 1 and Visit 2 for any of the estimates (P>0.05). The Pearson product correlations ranged from r = 0.933 for HBF-350 in the athlete mode (A) to r = 0.994 for SKF. The ICC's ranged from 0.93 for HBF-350(A) to 0.992 for SKF, and the MD's ranged from 1.8% for SKF to 5.1% for BF-350(A). The current study found that SKF and HBF-306C(A) were the most reliable (<2%) methods of estimating BF%, with the other methods (BF-350, BF-350(A), HBF-306C) producing minimal differences greater than 2%. In conclusion, the SKF method presented with the best reliability because of its low minimal difference, suggesting this method may be the best field method to track changes over time if you have an experienced tester. However, if technical error is a concern, the practitioner may use the HBF-306C(A) because it had a minimal difference value comparable to SKF.
Method to estimate center of rigidity using vibration recordings
Safak, Erdal; Celebi, Mehmet
1990-01-01
A method to estimate the center of rigidity of buildings by using vibration recordings is presented. The method is based on the criterion that the coherence of translational motions with the rotational motion is minimum at the center of rigidity. Since the coherence is a function of frequency, a gross but frequency-independent measure of the coherency is defined as the integral of the coherence function over the frequency. The center of rigidity is determined by minimizing this integral. The formulation is given for two-dimensional motions. Two examples are presented for the method; a rectangular building with ambient-vibration recordings, and a triangular building with earthquake-vibration recordings. Although the examples given are for buildings, the method can be applied to any structure with two-dimensional motions.
Nonparametric entropy estimation using kernel densities.
Lake, Douglas E
2009-01-01
The entropy of experimental data from the biological and medical sciences provides additional information over summary statistics. Calculating entropy involves estimates of probability density functions, which can be effectively accomplished using kernel density methods. Kernel density estimation has been widely studied and a univariate implementation is readily available in MATLAB. The traditional definition of Shannon entropy is part of a larger family of statistics, called Renyi entropy, which are useful in applications that require a measure of the Gaussianity of data. Of particular note is the quadratic entropy which is related to the Friedman-Tukey (FT) index, a widely used measure in the statistical community. One application where quadratic entropy is very useful is the detection of abnormal cardiac rhythms, such as atrial fibrillation (AF). Asymptotic and exact small-sample results for optimal bandwidth and kernel selection to estimate the FT index are presented and lead to improved methods for entropy estimation.
Methods for cost estimation in software project management
NASA Astrophysics Data System (ADS)
Briciu, C. V.; Filip, I.; Indries, I. I.
2016-02-01
The speed in which the processes used in software development field have changed makes it very difficult the task of forecasting the overall costs for a software project. By many researchers, this task has been considered unachievable, but there is a group of scientist for which this task can be solved using the already known mathematical methods (e.g. multiple linear regressions) and the new techniques as genetic programming and neural networks. The paper presents a solution for building a model for the cost estimation models in the software project management using genetic algorithms starting from the PROMISE datasets related COCOMO 81 model. In the first part of the paper, a summary of the major achievements in the research area of finding a model for estimating the overall project costs is presented together with the description of the existing software development process models. In the last part, a basic proposal of a mathematical model of a genetic programming is proposed including here the description of the chosen fitness function and chromosome representation. The perspective of model described it linked with the current reality of the software development considering as basis the software product life cycle and the current challenges and innovations in the software development area. Based on the author's experiences and the analysis of the existing models and product lifecycle it was concluded that estimation models should be adapted with the new technologies and emerging systems and they depend largely by the chosen software development method.
Laser heating method for estimation of carbon nanotube purity
NASA Astrophysics Data System (ADS)
Terekhov, S. V.; Obraztsova, E. D.; Lobach, A. S.; Konov, V. I.
A new method of a carbon nanotube purity estimation has been developed on the basis of Raman spectroscopy. The spectra of carbon soot containing different amounts of nanotubes were registered under heating from a probing laser beam with a step-by-step increased power density. The material temperature in the laser spot was estimated from a position of the tangential Raman mode demonstrating a linear thermal shift (-0.012 cm-1/K) from the position 1592 cm-1 (at room temperature). The rate of the material temperature rise versus the laser power density (determining the slope of a corresponding graph) appeared to correlate strongly with the nanotube content in the soot. The influence of the experimental conditions on the slope value has been excluded via a simultaneous measurement of a reference sample with a high nanotube content (95 vol.%). After the calibration (done by a comparison of the Raman and the transmission electron microscopy data for the nanotube percentage in the same samples) the Raman-based method is able to provide a quantitative purity estimation for any nanotube-containing material.
A method to estimate groundwater depletion from confining layers
Konikow, L.F.; Neuzil, C.E.
2007-01-01
Although depletion of storage in low-permeability confining layers is the source of much of the groundwater produced from many confined aquifer systems, it is all too frequently overlooked or ignored. This makes effective management of groundwater resources difficult by masking how much water has been derived from storage and, in some cases, the total amount of water that has been extracted from an aquifer system. Analyzing confining layer storage is viewed as troublesome because of the additional computational burden and because the hydraulic properties of confining layers are poorly known. In this paper we propose a simplified method for computing estimates of confining layer depletion, as well as procedures for approximating confining layer hydraulic conductivity (K) and specific storage (Ss) using geologic information. The latter makes the technique useful in developing countries and other settings where minimal data are available or when scoping calculations are needed. As such, our approach may be helpful for estimating the global transfer of groundwater to surface water. A test of the method on a synthetic system suggests that the computational errors will generally be small. Larger errors will probably result from inaccuracy in confining layer property estimates, but these may be no greater than errors in more sophisticated analyses. The technique is demonstrated by application to two aquifer systems: the Dakota artesian aquifer system in South Dakota and the coastal plain aquifer system in Virginia. In both cases, depletion from confining layers was substantially larger than depletion from the aquifers.
ERIC Educational Resources Information Center
Gustafson, S. C.; Costello, C. S.; Like, E. C.; Pierce, S. J.; Shenoy, K. N.
2009-01-01
Bayesian estimation of a threshold time (hereafter simply threshold) for the receipt of impulse signals is accomplished given the following: 1) data, consisting of the number of impulses received in a time interval from zero to one and the time of the largest time impulse; 2) a model, consisting of a uniform probability density of impulse time…
Estimation of regionalized compositions: A comparison of three methods
Pawlowsky, V.; Olea, R.A.; Davis, J.C.
1995-01-01
A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.
Intensity estimation method of LED array for visible light communication
NASA Astrophysics Data System (ADS)
Ito, Takanori; Yendo, Tomohiro; Arai, Shintaro; Yamazato, Takaya; Okada, Hiraku; Fujii, Toshiaki
2013-03-01
This paper focuses on a road-to-vehicle visible light communication (VLC) system using LED traffic light as the transmitter and camera as the receiver. The traffic light is composed of a hundred of LEDs on two dimensional plain. In this system, data is sent as two dimensional brightness patterns by controlling each LED of the traffic light individually, and they are received as images by the camera. Here, there are problems that neighboring LEDs on the received image are merged due to less number of pixels in case that the receiver is distant from the transmitter, and/or due to blurring by defocus of the camera. Because of that, bit error rate (BER) increases due to recognition error of intensity of LEDs To solve the problem, we propose a method that estimates the intensity of LEDs by solving the inverse problem of communication channel characteristic from the transmitter to the receiver. The proposed method is evaluated by BER characteristics which are obtained by computer simulation and experiments. In the result, the proposed method can estimate with better accuracy than the conventional methods, especially in case that the received image is blurred a lot, and the number of pixels is small.
Estimating return on investment in translational research: methods and protocols.
Grazier, Kyle L; Trochim, William M; Dilts, David M; Kirk, Rosalind
2013-12-01
Assessing the value of clinical and translational research funding on accelerating the translation of scientific knowledge is a fundamental issue faced by the National Institutes of Health (NIH) and its Clinical and Translational Awards (CTSAs). To address this issue, the authors propose a model for measuring the return on investment (ROI) of one key CTSA program, the clinical research unit (CRU). By estimating the economic and social inputs and outputs of this program, this model produces multiple levels of ROI: investigator, program, and institutional estimates. A methodology, or evaluation protocol, is proposed to assess the value of this CTSA function, with specific objectives, methods, descriptions of the data to be collected, and how data are to be filtered, analyzed, and evaluated. This article provides an approach CTSAs could use to assess the economic and social returns on NIH and institutional investments in these critical activities.
GPS receiver CODE bias estimation: A comparison of two methods
NASA Astrophysics Data System (ADS)
McCaffrey, Anthony M.; Jayachandran, P. T.; Themens, D. R.; Langley, R. B.
2017-04-01
The Global Positioning System (GPS) is a valuable tool in the measurement and monitoring of ionospheric total electron content (TEC). To obtain accurate GPS-derived TEC, satellite and receiver hardware biases, known as differential code biases (DCBs), must be estimated and removed. The Center for Orbit Determination in Europe (CODE) provides monthly averages of receiver DCBs for a significant number of stations in the International Global Navigation Satellite Systems Service (IGS) network. A comparison of the monthly receiver DCBs provided by CODE with DCBs estimated using the minimization of standard deviations (MSD) method on both daily and monthly time intervals, is presented. Calibrated TEC obtained using CODE-derived DCBs, is accurate to within 0.74 TEC units (TECU) in differenced slant TEC (sTEC), while calibrated sTEC using MSD-derived DCBs results in an accuracy of 1.48 TECU.
A power function method for estimating base flow.
Lott, Darline A; Stewart, Mark T
2013-01-01
Analytical base flow separation techniques are often used to determine the base flow contribution to total stream flow. Most analytical methods derive base flow from discharge records alone without using basin-specific variables other than basin area. This paper derives a power function for estimating base flow, the form being aQ(b) + cQ, an analytical method calibrated against an integrated basin variable, specific conductance, relating base flow to total discharge, and is consistent with observed mathematical behavior of dissolved solids in stream flow with varying discharge. Advantages of the method are being uncomplicated, reproducible, and applicable to hydrograph separation in basins with limited specific conductance data. The power function relationship between base flow and discharge holds over a wide range of basin areas. It better replicates base flow determined by mass balance methods than analytical methods such as filters or smoothing routines that are not calibrated to natural tracers or empirical basin and gauge-specific variables. Also, it can be used with discharge during periods without specific conductance values, including separating base flow from quick flow for single events. However, it may overestimate base flow during very high flow events. Application of geochemical mass balance and power function base flow separation methods to stream flow and specific conductance records from multiple gauges in the same basin suggests that analytical base flow separation methods must be calibrated at each gauge. Using average values of coefficients introduces a potentially significant and unknown error in base flow as compared with mass balance methods.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.
Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2
Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.
1994-07-01
that also have not been fully addressed. This document contains two types of papers that seek to fill part of this void. Some of the papers describe analytical methods that can be applied to one of the five steps of the damage function approach. The other papers discuss some of the complex issues that arise in trying to estimate externalities. This report, the second in a series of eight reports, is part of a joint study by the U.S. Department of Energy (DOE) and the Commission of the European Communities (EC)* on the externalities of fuel cycles. Most of the papers in this report were originally written as working papers during the initial phases of this study. The papers provide descriptions of the (non-radiological) atmospheric dispersion modeling that the study uses; reviews much of the relevant literature on ecological and health effects, and on the economic valuation of those impacts; contains several papers on some of the more complex and contentious issues in estimating externalities; and describes a method for depicting the quality of scientific information that a study uses. The analytical methods and issues that this report discusses generally pertain to more than one of the fuel cycles, though not necessarily to all of them. The report is divided into six parts, each one focusing on a different subject area.
Streamflow-Characteristic Estimation Methods for Unregulated Streams of Tennessee
Law, George S.; Tasker, Gary D.; Ladd, David E.
2009-01-01
Streamflow-characteristic estimation methods for unregulated rivers and streams of Tennessee were developed by the U.S. Geological Survey in cooperation with the Tennessee Department of Environment and Conservation. Streamflow estimates are provided for 1,224 stream sites. Streamflow characteristics include the 7-consecutive-day, 10-year recurrence-interval low flow, the 30-consecutive-day, 5-year recurrence-interval low flow, the mean annual and mean summer flows, and the 99.5-, 99-, 98-, 95-, 90-, 80-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent flow durations. Estimation methods include regional regression (RRE) equations and the region-of-influence (ROI) method. Both methods use zero-flow probability screening to estimate zero-flow quantiles. A low flow and flow duration (LFFD) computer program (TDECv301) performs zero-flow screening and calculation of nonzero-streamflow characteristics using the RRE equations and ROI method and provides quality measures including the 90-percent prediction interval and equivalent years of record. The U.S. Geological Survey StreamStats geographic information system automates the calculation of basin characteristics and streamflow characteristics. In addition, basin characteristics can be manually input to the stand-alone version of the computer program (TDECv301) to calculate streamflow characteristics in Tennessee. The RRE equations were computed using multivariable regression analysis. The two regions used for this study, the western part of the State (West) and the central and eastern part of the State (Central+East), are separated by the Tennessee River as it flows south to north from Hardin County to Stewart County. The West region uses data from 124 of the 1,224 streamflow sites, and the Central+East region uses data from 893 of the 1,224 streamflow sites. The study area also includes parts of the adjacent States of Georgia, North Carolina, Virginia, Alabama, Kentucky, and Mississippi. Total drainage area, a geology
Probabilistic seismic hazard assessment of Italy using kernel estimation methods
NASA Astrophysics Data System (ADS)
Zuccolo, Elisa; Corigliano, Mirko; Lai, Carlo G.
2013-07-01
A representation of seismic hazard is proposed for Italy based on the zone-free approach developed by Woo (BSSA 86(2):353-362, 1996a), which is based on a kernel estimation method governed by concepts of fractal geometry and self-organized seismicity, not requiring the definition of seismogenic zoning. The purpose is to assess the influence of seismogenic zoning on the results obtained for the probabilistic seismic hazard analysis (PSHA) of Italy using the standard Cornell's method. The hazard has been estimated for outcropping rock site conditions in terms of maps and uniform hazard spectra for a selected site, with 10 % probability of exceedance in 50 years. Both spectral acceleration and spectral displacement have been considered as ground motion parameters. Differences in the results of PSHA between the two methods are compared and discussed. The analysis shows that, in areas such as Italy, characterized by a reliable earthquake catalog and in which faults are generally not easily identifiable, a zone-free approach can be considered a valuable tool to address epistemic uncertainty within a logic tree framework.
Using optimal estimation method for upper atmospheric Lidar temperature retrieval
NASA Astrophysics Data System (ADS)
Zou, Rongshi; Pan, Weilin; Qiao, Shuai
2016-07-01
Conventional ground based Rayleigh lidar temperature retrieval use integrate technique, which has limitations that necessitate abandoning temperatures retrieved at the greatest heights due to the assumption of a seeding value required to initialize the integration at the highest altitude. Here we suggests the use of a method that can incorporate information from various sources to improve the quality of the retrieval result. This approach inverts lidar equation via optimal estimation method(OEM) based on Bayesian theory together with Gaussian statistical model. It presents many advantages over the conventional ones: 1) the possibility of incorporating information from multiple heterogeneous sources; 2) provides diagnostic information about retrieval qualities; 3) ability of determining vertical resolution and maximum height to which the retrieval is mostly independent of the a priori profile. This paper compares one-hour temperature profiles retrieved using conventional and optimal estimation methods at Golmud, Qinghai province, China. Results show that OEM results show a better agreement with SABER profile compared with conventional one, in some region it is much lower than SABER profile, which is a very different results compared with previous studies, further studies are needed to explain this phenomenon. The success of applying OEM on temperature retrieval is a validation for using as retrieval framework in large synthetic observation systems including various active remote sensing instruments by incorporating all available measurement information into the model and analyze groups of measurements simultaneously to improve the results.
Analytical method to estimate resin cement diffusion into dentin
NASA Astrophysics Data System (ADS)
de Oliveira Ferraz, Larissa Cristina; Ubaldini, Adriana Lemos Mori; de Oliveira, Bruna Medeiros Bertol; Neto, Antonio Medina; Sato, Fracielle; Baesso, Mauro Luciano; Pascotto, Renata Corrêa
2016-05-01
This study analyzed the diffusion of two resin luting agents (resin cements) into dentin, with the aim of presenting an analytical method for estimating the thickness of the diffusion zone. Class V cavities were prepared in the buccal and lingual surfaces of molars (n=9). Indirect composite inlays were luted into the cavities with either a self-adhesive or a self-etch resin cement. The teeth were sectioned bucco-lingually and the cement-dentin interface was analyzed by using micro-Raman spectroscopy (MRS) and scanning electron microscopy. Evolution of peak intensities of the Raman bands, collected from the functional groups corresponding to the resin monomer (C-O-C, 1113 cm-1) present in the cements, and the mineral content (P-O, 961 cm-1) in dentin were sigmoid shaped functions. A Boltzmann function (BF) was then fitted to the peaks encountered at 1113 cm-1 to estimate the resin cement diffusion into dentin. The BF identified a resin cement-dentin diffusion zone of 1.8±0.4 μm for the self-adhesive cement and 2.5±0.3 μm for the self-etch cement. This analysis allowed the authors to estimate the diffusion of the resin cements into the dentin. Fitting the MRS data to the BF contributed to and is relevant for future studies of the adhesive interface.
Estimation of Convective Momentum Fluxes Using Satellite-Based Methods
NASA Astrophysics Data System (ADS)
Jewett, C.; Mecikalski, J. R.
2009-12-01
Research and case studies have shown that convection plays a significant role in large-scale environmental circulations. Convective momentum fluxes (CMFs) have been studied for many years using in-situ and aircraft measurements, along with numerical simulations. However, despite these successes, little work has been conducted on methods that use satellite remote sensing as a tool to diagnose these fluxes. Uses of satellite data have the capability to provide continuous analysis across regions void of ground-based remote sensing. Therefore, the project's overall goal is to develop a synergistic approach for retrieving CMFs using a collection of instruments including GOES, TRMM, CloudSat, MODIS, and QuikScat. However, this particular study will focus on the work using TRMM and QuikScat, and the methodology of using CloudSat. Sound research has already been conducted for computing CMFs using the GOES instruments (Jewett and Mecikalski 2009, submitted to J. Geophys. Res.). Using satellite-derived winds, namely mesoscale atmospheric motion vectors (MAMVs) as described by Bedka and Mecikalski (2005), one can obtain the actual winds occurring within a convective environment as perturbed by convection. Surface outflow boundaries and upper-tropospheric anvil outflow will produce “perturbation” winds on smaller, convective scales. Combined with estimated vertical motion retrieved using geostationary infrared imagery, CMFs were estimated using MAMVs, with an average profile being calculated across a convective regime or a domain covered by active storms. This study involves estimating draft-tilt from TRMM PR radar reflectivity and sub-cloud base fluxes using QuikScat data. The “slope” of falling hydrometeors (relative to Earth) in data are related to u', v' and w' winds within convection. The main up- and down-drafts within convection are described by precipitation patterns (Mecikalski 2003). Vertical motion estimates are made using model results for deep convection
Comparative study on parameter estimation methods for attenuation relationships
NASA Astrophysics Data System (ADS)
Sedaghati, Farhad; Pezeshk, Shahram
2016-12-01
In this paper, the performance and advantages and disadvantages of various regression methods to derive coefficients of an attenuation relationship have been investigated. A database containing 350 records out of 85 earthquakes with moment magnitudes of 5-7.6 and Joyner-Boore distances up to 100 km in Europe and the Middle East has been considered. The functional form proposed by Ambraseys et al (2005 Bull. Earthq. Eng. 3 1-53) is selected to compare chosen regression methods. Statistical tests reveal that although the estimated parameters are different for each method, the overall results are very similar. In essence, the weighted least squares method and one-stage maximum likelihood perform better than the other considered regression methods. Moreover, using a blind weighting matrix or a weighting matrix related to the number of records would not yield in improving the performance of the results. Further, to obtain the true standard deviation, the pure error analysis is necessary. Assuming that the correlation between different records of a specific earthquake exists, the one-stage maximum likelihood considering the true variance acquired by the pure error analysis is the most preferred method to compute the coefficients of a ground motion predication equation.
Dental age estimation in Brazilian HIV children using Willems' method.
de Souza, Rafael Boschetti; da Silva Assunção, Luciana Reichert; Franco, Ademir; Zaroni, Fábio Marzullo; Holderbaum, Rejane Maria; Fernandes, Ângela
2015-12-01
The notification of the Human Immunodeficiency Virus (HIV) in Brazilian children was first reported in 1984. Since that time more than 21 thousand children became infected. Approximately 99.6% of the children aged less than 13 years old are vertically infected. In this context, most of the children are abandoned after birth, or lose their relatives in a near future, growing with uncertain identification. The present study aims to estimate the dental age of Brazilian HIV patients in face of healthy patients paired by age and gender. The sample consisted of 160 panoramic radiographs of male (n: 80) and female (n: 80) patients aged between 4 and 15 years (mean age: 8.88 years), divided into HIV (n: 80) and control (n: 80) groups. The sample was analyzed by three trained examiners, using Willems' method, 2001. Intraclass Correlation Coefficient (ICC) was applied to test intra- and inter-examiner agreement, and Student paired t-test was used to determine the age association between HIV and control groups. Intra-examiner (ICC: from 0.993 to 0.997) and inter-examiner (ICC: from 0.991 to 0.995) agreement tests indicated high reproducibility of the method between the examiners (P<0.01). Willems' method revealed discrete statistical overestimation in HIV (2.86 months; P=0.019) and control (1.90 months; P=0.039) groups. However, stratified analysis by gender indicate that overestimation were only concentrated in male HIV (3.85 months; P=0.001) and control (2.86 months; P=0.022) patients. The significant statistical differences are not clinically relevant once only few months of discrepancy are detected applying Willems' method in a Brazilian HIV sample, making this method highly recommended for dental age estimation of both HIV and healthy children with unknown age.
NASA Astrophysics Data System (ADS)
Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann
2016-10-01
Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches
The Mayfield method of estimating nesting success: A model, estimators and simulation results
Hensler, G.L.; Nichols, J.D.
1981-01-01
Using a nesting model proposed by Mayfield we show that the estimator he proposes is a maximum likelihood estimator (m.l.e.). M.l.e. theory allows us to calculate the asymptotic distribution of this estimator, and we propose an estimator of the asymptotic variance. Using these estimators we give approximate confidence intervals and tests of significance for daily survival. Monte Carlo simulation results show the performance of our estimators and tests under many sets of conditions. A traditional estimator of nesting success is shown to be quite inferior to the Mayfield estimator. We give sample sizes required for a given accuracy under several sets of conditions.
Current methods for estimating the rate of photorespiration in leaves.
Busch, F A
2013-07-01
Photorespiration is a process that competes with photosynthesis, in which Rubisco oxygenates, instead of carboxylates, its substrate ribulose 1,5-bisphosphate. The photorespiratory metabolism associated with the recovery of 3-phosphoglycerate is energetically costly and results in the release of previously fixed CO2. The ability to quantify photorespiration is gaining importance as a tool to help improve plant productivity in order to meet the increasing global food demand. In recent years, substantial progress has been made in the methods used to measure photorespiration. Current techniques are able to measure multiple aspects of photorespiration at different points along the photorespiratory C2 cycle. Six different methods used to estimate photorespiration are reviewed, and their advantages and disadvantages discussed.
Improved methods of estimating critical indices via fractional calculus
NASA Astrophysics Data System (ADS)
Bandyopadhyay, S. K.; Bhattacharyya, K.
2002-05-01
Efficiencies of certain methods for the determination of critical indices from power-series expansions are shown to be considerably improved by a suitable implementation of fractional differentiation. In the context of the ratio method (RM), kinship of the modified strategy with the ad hoc `shifted' RM is established and the advantages are demonstrated. Further, in the course of the estimation of critical points, significant betterment of convergence properties of diagonal Padé approximants is observed on several occasions by invoking this concept. Test calculations are performed on (i) various Ising spin-1/2 lattice models for susceptibility series attended with a ferromagnetic phase transition, (ii) complex model situations involving confluent and antiferromagnetic singularities and (iii) the chain-generating functions for self-avoiding walks on triangular, square and simple cubic lattices.
A method for obtaining time-periodic Lp estimates
NASA Astrophysics Data System (ADS)
Kyed, Mads; Sauer, Jonas
2017-01-01
We introduce a method for showing a prioriLp estimates for time-periodic, linear, partial differential equations set in a variety of domains such as the whole space, the half space and bounded domains. The method is generic and can be applied to a wide range of problems. We demonstrate it on the heat equation. The main idea is to replace the time axis with a torus in order to reformulate the problem on a locally compact abelian group and to employ Fourier analysis on this group. As a by-product, maximal Lp regularity for the corresponding initial-value problem follows without the notion of R-boundedness. Moreover, we introduce the concept of a time-periodic fundamental solution.
Probabilistic seismic loss estimation via endurance time method
NASA Astrophysics Data System (ADS)
Tafakori, Ehsan; Pourzeynali, Saeid; Estekanchi, Homayoon E.
2017-01-01
Probabilistic Seismic Loss Estimation is a methodology used as a quantitative and explicit expression of the performance of buildings using terms that address the interests of both owners and insurance companies. Applying the ATC 58 approach for seismic loss assessment of buildings requires using Incremental Dynamic Analysis (IDA), which needs hundreds of time-consuming analyses, which in turn hinders its wide application. The Endurance Time Method (ETM) is proposed herein as part of a demand propagation prediction procedure and is shown to be an economical alternative to IDA. Various scenarios were considered to achieve this purpose and their appropriateness has been evaluated using statistical methods. The most precise and efficient scenario was validated through comparison against IDA driven response predictions of 34 code conforming benchmark structures and was proven to be sufficiently precise while offering a great deal of efficiency. The loss values were estimated by replacing IDA with the proposed ETM-based procedure in the ATC 58 procedure and it was found that these values suffer from varying inaccuracies, which were attributed to the discretized nature of damage and loss prediction functions provided by ATC 58.
A QUALITATIVE METHOD TO ESTIMATE HSI DISPLAY COMPLEXITY
Jacques Hugo; David Gertman
2013-04-01
There is mounting evidence that complex computer system displays in control rooms contribute to cognitive complexity and, thus, to the probability of human error. Research shows that reaction time increases and response accuracy decreases as the number of elements in the display screen increase. However, in terms of supporting the control room operator, approaches focusing on addressing display complexity solely in terms of information density and its location and patterning, will fall short of delivering a properly designed interface. This paper argues that information complexity and semantic complexity are mandatory components when considering display complexity and that the addition of these concepts assists in understanding and resolving differences between designers and the preferences and performance of operators. This paper concludes that a number of simplified methods, when combined, can be used to estimate the impact that a particular display may have on the operator's ability to perform a function accurately and effectively. We present a mixed qualitative and quantitative approach and a method for complexity estimation.
Method of Estimating Continuous Cooling Transformation Curves of Glasses
NASA Technical Reports Server (NTRS)
Zhu, Dongmei; Zhou, Wancheng; Ray, Chandra S.; Day, Delbert E.
2006-01-01
A method is proposed for estimating the critical cooling rate and continuous cooling transformation (CCT) curve from isothermal TTT data of glasses. The critical cooling rates and CCT curves for a group of lithium disilicate glasses containing different amounts of Pt as nucleating agent estimated through this method are compared with the experimentally measured values. By analysis of the experimental and calculated data of the lithium disilicate glasses, a simple relationship between the crystallized amount in the glasses during continuous cooling, X, and the temperature of undercooling, (Delta)T, was found to be X = AR(sup-4)exp(B (Delta)T), where (Delta)T is the temperature difference between the theoretical melting point of the glass composition and the temperature in discussion, R is the cooling rate, and A and B are constants. The relation between the amount of crystallisation during continuous cooling and isothermal hold can be expressed as (X(sub cT)/X(sub iT) = (4/B)(sup 4) (Delta)T(sup -4), where X(sub cT) stands for the crystallised amount in a glass during continuous cooling for a time t when the temperature comes to T, and X(sub iT) is the crystallised amount during isothermal hold at temperature T for a time t.
Study on color difference estimation method of medicine biochemical analysis
NASA Astrophysics Data System (ADS)
Wang, Chunhong; Zhou, Yue; Zhao, Hongxia; Sun, Jiashi; Zhou, Fengkun
2006-01-01
The biochemical analysis in medicine is an important inspection and diagnosis method in hospital clinic. The biochemical analysis of urine is one important item. The Urine test paper shows corresponding color with different detection project or different illness degree. The color difference between the standard threshold and the test paper color of urine can be used to judge the illness degree, so that further analysis and diagnosis to urine is gotten. The color is a three-dimensional physical variable concerning psychology, while reflectance is one-dimensional variable; therefore, the estimation method of color difference in urine test can have better precision and facility than the conventional test method with one-dimensional reflectance, it can make an accurate diagnose. The digital camera is easy to take an image of urine test paper and is used to carry out the urine biochemical analysis conveniently. On the experiment, the color image of urine test paper is taken by popular color digital camera and saved in the computer which installs a simple color space conversion (RGB -> XYZ -> L *a *b *)and the calculation software. Test sample is graded according to intelligent detection of quantitative color. The images taken every time were saved in computer, and the whole illness process will be monitored. This method can also use in other medicine biochemical analyses that have relation with color. Experiment result shows that this test method is quick and accurate; it can be used in hospital, calibrating organization and family, so its application prospect is extensive.
Method for estimating road salt contamination of Norwegian lakes
NASA Astrophysics Data System (ADS)
Kitterød, Nils-Otto; Wike Kronvall, Kjersti; Turtumøygaard, Stein; Haaland, Ståle
2013-04-01
Consumption of road salt in Norway, used to improve winter road conditions, has been tripled during the last two decades, and there is a need to quantify limits for optimal use of road salt to avoid further environmental harm. The purpose of this study was to implement methodology to estimate chloride concentration in any given water body in Norway. This goal is feasible to achieve if the complexity of solute transport in the landscape is simplified. The idea was to keep computations as simple as possible to be able to increase spatial resolution of input functions. The first simplification we made was to treat all roads exposed to regular salt application as steady state sources of sodium chloride. This is valid if new road salt is applied before previous contamination is removed through precipitation. The main reasons for this assumption are the significant retention capacity of vegetation; organic matter; and soil. The second simplification we made was that the groundwater table is close to the surface. This assumption is valid for major part of Norway, which means that topography is sufficient to delineate catchment area at any location in the landscape. Given these two assumptions, we applied spatial functions of mass load (mass NaCl pr. time unit) and conditional estimates of normal water balance (volume of water pr. time unit) to calculate steady state chloride concentration along the lake perimeter. Spatial resolution of mass load and estimated concentration along the lake perimeter was 25 m x 25 m while water balance had 1 km x 1 km resolution. The method was validated for a limited number of Norwegian lakes and estimation results have been compared to observations. Initial results indicate significant overlap between measurements and estimations, but only for lakes where the road salt is the major contribution for chloride contamination. For lakes in catchments with high subsurface transmissivity, the groundwater table is not necessarily following the
Estimated Accuracy of Three Common Trajectory Statistical Methods
NASA Technical Reports Server (NTRS)
Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.
2011-01-01
Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h
New Methods for Estimating Seasonal Potential Climate Predictability
NASA Astrophysics Data System (ADS)
Feng, Xia
This study develops two new statistical approaches to assess the seasonal potential predictability of the observed climate variables. One is the univariate analysis of covariance (ANOCOVA) model, a combination of autoregressive (AR) model and analysis of variance (ANOVA). It has the advantage of taking into account the uncertainty of the estimated parameter due to sampling errors in statistical test, which is often neglected in AR based methods, and accounting for daily autocorrelation that is not considered in traditional ANOVA. In the ANOCOVA model, the seasonal signals arising from external forcing are determined to be identical or not to assess any interannual variability that may exist is potentially predictable. The bootstrap is an attractive alternative method that requires no hypothesis model and is available no matter how mathematically complicated the parameter estimator. This method builds up the empirical distribution of the interannual variance from the resamplings drawn with replacement from the given sample, in which the only predictability in seasonal means arises from the weather noise. These two methods are applied to temperature and water cycle components including precipitation and evaporation, to measure the extent to which the interannual variance of seasonal means exceeds the unpredictable weather noise compared with the previous methods, including Leith-Shukla-Gutzler (LSG), Madden, and Katz. The potential predictability of temperature from ANOCOVA model, bootstrap, LSG and Madden exhibits a pronounced tropical-extratropical contrast with much larger predictability in the tropics dominated by El Nino/Southern Oscillation (ENSO) than in higher latitudes where strong internal variability lowers predictability. Bootstrap tends to display highest predictability of the four methods, ANOCOVA lies in the middle, while LSG and Madden appear to generate lower predictability. Seasonal precipitation from ANOCOVA, bootstrap, and Katz, resembling that
Estimating recharge at Yucca Mountain, Nevada, USA: Comparison of methods
Flint, A.L.; Flint, L.E.; Kwicklis, E.M.; Fabryka-Martin, J. T.; Bodvarsson, G.S.
2002-01-01
Obtaining values of net infiltration, groundwater travel time, and recharge is necessary at the Yucca Mountain site, Nevada, USA, in order to evaluate the expected performance of a potential repository as a containment system for high-level radioactive waste. However, the geologic complexities of this site, its low precipitation and net infiltration, with numerous mechanisms operating simultaneously to move water through the system, provide many challenges for the estimation of the spatial distribution of recharge. A variety of methods appropriate for arid environments has been applied, including water-balance techniques, calculations using Darcy's law in the unsaturated zone, a soil-physics method applied to neutron-hole water-content data, inverse modeling of thermal profiles in boreholes extending through the thick unsaturated zone, chloride mass balance, atmospheric radionuclides, and empirical approaches. These methods indicate that near-surface infiltration rates at Yucca Mountain are highly variable in time and space, with local (point) values ranging from zero to several hundred millimeters per year. Spatially distributed net-infiltration values average 5 mm/year, with the highest values approaching 20 mm/year near Yucca Crest. Site-scale recharge estimates range from less than 1 to about 12 mm/year. These results have been incorporated into a site-scale model that has been calibrated using these data sets that reflect infiltration processes acting on highly variable temporal and spatial scales. The modeling study predicts highly non-uniform recharge at the water table, distributed significantly differently from the non-uniform infiltration pattern at the surface.
Estimating recharge at yucca mountain, nevada, usa: comparison of methods
Flint, A. L.; Flint, L. E.; Kwicklis, E. M.; Fabryka-Martin, J. T.; Bodvarsson, G. S.
2001-11-01
Obtaining values of net infiltration, groundwater travel time, and recharge is necessary at the Yucca Mountain site, Nevada, USA, in order to evaluate the expected performance of a potential repository as a containment system for high-level radioactive waste. However, the geologic complexities of this site, its low precipitation and net infiltration, with numerous mechanisms operating simultaneously to move water through the system, provide many challenges for the estimation of the spatial distribution of recharge. A variety of methods appropriate for and environments has been applied, including water-balance techniques, calculations using Darcy's law in the unsaturated zone, a soil-physics method applied to neutron-hole water-content data, inverse modeling of thermal profiles in boreholes extending through the thick unsaturated zone, chloride mass balance, atmospheric radionuclides, and empirical approaches. These methods indicate that near-surface infiltration rates at Yucca Mountain are highly variable in time and space, with local (point) values ranging from zero to several hundred millimeters per year. Spatially distributed net-infiltration values average 5 mm/year, with the highest values approaching 20 nun/year near Yucca Crest. Site-scale recharge estimates range from less than I to about 12 mm/year. These results have been incorporated into a site-scale model that has been calibrated using these data sets that reflect infiltration processes acting on highly variable temporal and spatial scales. The modeling study predicts highly non-uniform recharge at the water table, distributed significantly differently from the non-uniform infiltration pattern at the surface. [References: 57
Computational methods estimating uncertainties for profile reconstruction in scatterometry
NASA Astrophysics Data System (ADS)
Gross, H.; Rathsfeld, A.; Scholze, F.; Model, R.; Bär, M.
2008-04-01
The solution of the inverse problem in scatterometry, i.e. the determination of periodic surface structures from light diffraction patterns, is incomplete without knowledge of the uncertainties associated with the reconstructed surface parameters. With decreasing feature sizes of lithography masks, increasing demands on metrology techniques arise. Scatterometry as a non-imaging indirect optical method is applied to periodic line-space structures in order to determine geometric parameters like side-wall angles, heights, top and bottom widths and to evaluate the quality of the manufacturing process. The numerical simulation of the diffraction process is based on the finite element solution of the Helmholtz equation. The inverse problem seeks to reconstruct the grating geometry from measured diffraction patterns. Restricting the class of gratings and the set of measurements, this inverse problem can be reformulated as a non-linear operator equation in Euclidean spaces. The operator maps the grating parameters to the efficiencies of diffracted plane wave modes. We employ a Gauss-Newton type iterative method to solve this operator equation and end up minimizing the deviation of the measured efficiency or phase shift values from the simulated ones. The reconstruction properties and the convergence of the algorithm, however, is controlled by the local conditioning of the non-linear mapping and the uncertainties of the measured efficiencies or phase shifts. In particular, the uncertainties of the reconstructed geometric parameters essentially depend on the uncertainties of the input data and can be estimated by various methods. We compare the results obtained from a Monte Carlo procedure to the estimations gained from the approximative covariance matrix of the profile parameters close to the optimal solution and apply them to EUV masks illuminated by plane waves with wavelengths in the range of 13 nm.
Estimation of Anthocyanin Content of Berries by NIR Method
Zsivanovits, G.; Ludneva, D.; Iliev, A.
2010-01-21
Anthocyanin contents of fruits were estimated by VIS spectrophotometer and compared with spectra measured by NIR spectrophotometer (600-1100 nm step 10 nm). The aim was to find a relationship between NIR method and traditional spectrophotometric method. The testing protocol, using NIR, is easier, faster and non-destructive. NIR spectra were prepared in pairs, reflectance and transmittance. A modular spectrocomputer, realized on the basis of a monochromator and peripherals Bentham Instruments Ltd (GB) and a photometric camera created at Canning Research Institute, were used. An important feature of this camera is the possibility offered for a simultaneous measurement of both transmittance and reflectance with geometry patterns T0/180 and R0/45. The collected spectra were analyzed by CAMO Unscrambler 9.1 software, with PCA, PLS, PCR methods. Based on the analyzed spectra quality and quantity sensitive calibrations were prepared. The results showed that the NIR method allows measuring of the total anthocyanin content in fresh berry fruits or processed products without destroying them.
Effect of packing density on strain estimation by Fry method
NASA Astrophysics Data System (ADS)
Srivastava, Deepak; Ojha, Arun
2015-04-01
Fry method is a graphical technique that uses relative movement of material points, typically the grain centres or centroids, and yields the finite strain ellipse as the central vacancy of a point distribution. Application of the Fry method assumes an anticlustered and isotropic grain centre distribution in undistorted samples. This assumption is, however, difficult to test in practice. As an alternative, the sedimentological degree of sorting is routinely used as an approximation for the degree of clustering and anisotropy. The effect of the sorting on the Fry method has already been explored by earlier workers. This study tests the effect of the tightness of packing, the packing density%, which equals to the ratio% of the area occupied by all the grains and the total area of the sample. A practical advantage of using the degree of sorting or the packing density% is that these parameters, unlike the degree of clustering or anisotropy, do not vary during a constant volume homogeneous distortion. Using the computer graphics simulations and the programming, we approach the issue of packing density in four steps; (i) generation of several sets of random point distributions such that each set has same degree of sorting but differs from the other sets with respect to the packing density%, (ii) two-dimensional homogeneous distortion of each point set by various known strain ratios and orientation, (iii) estimation of strain in each distorted point set by the Fry method, and, (iv) error estimation by comparing the known strain and those given by the Fry method. Both the absolute errors and the relative root mean squared errors give consistent results. For a given degree of sorting, the Fry method gives better results in the samples having greater than 30% packing density. This is because the grain centre distributions show stronger clustering and a greater degree of anisotropy with the decrease in the packing density. As compared to the degree of sorting alone, a
An extended stochastic method for seismic hazard estimation
NASA Astrophysics Data System (ADS)
Abd el-aal, A. K.; El-Eraki, M. A.; Mostafa, S. I.
2015-12-01
In this contribution, we developed an extended stochastic technique for seismic hazard assessment purposes. This technique depends on the hypothesis of stochastic technique of Boore (2003) "Simulation of ground motion using the stochastic method. Appl. Geophy. 160:635-676". The essential characteristics of extended stochastic technique are to obtain and simulate ground motion in order to minimize future earthquake consequences. The first step of this technique is defining the seismic sources which mostly affect the study area. Then, the maximum expected magnitude is defined for each of these seismic sources. It is followed by estimating the ground motion using an empirical attenuation relationship. Finally, the site amplification is implemented in calculating the peak ground acceleration (PGA) at each site of interest. We tested and applied this developed technique at Cairo, Suez, Port Said, Ismailia, Zagazig and Damietta cities to predict the ground motion. Also, it is applied at Cairo, Zagazig and Damietta cities to estimate the maximum peak ground acceleration at actual soil conditions. In addition, 0.5, 1, 5, 10 and 20 % damping median response spectra are estimated using the extended stochastic simulation technique. The calculated highest acceleration values at bedrock conditions are found at Suez city with a value of 44 cm s-2. However, these acceleration values decrease towards the north of the study area to reach 14.1 cm s-2 at Damietta city. This comes in agreement with the results of previous studies of seismic hazards in northern Egypt and is found to be comparable. This work can be used for seismic risk mitigation and earthquake engineering purposes.
A practical method of estimating energy expenditure during tennis play.
Novas, A M P; Rowbottom, D G; Jenkins, D G
2003-03-01
This study aimed to develop a practical method of estimating energy expenditure (EE) during tennis. Twenty-four elite female tennis players first completed a tennis-specific graded test in which five different Intensity levels were applied randomly. Each intensity level was intended to simulate a "game" of singles tennis and comprised six 14 s periods of activity alternated with 20 s of active rest. Oxygen consumption (VO2) and heart rate (HR) were measured continuously and each player's rate of perceived exertion (RPE) was recorded at the end of each intensity level. Rate of energy expenditure (EE(VO2)) during the test was calculated using the sum of VO2 during play and the 'O2 debt' during recovery, divided by the duration of the activity. There were significant individual linear relationships between EE(VO2) and RPE, EE(VO2) and HR (r > or = 0.89 & r > or = 0.93; p < 0.05). On a second occasion, six players completed a 60-min singles tennis match during which VO2, HR and RPE were recorded; EE(VO2) was compared with EE predicted from the previously derived RPE and HR regression equations. Analysis found that EE(VO2) was overestimated by EE(RPE) (92 +/- 76 kJ x h(-1)) and EE(HR) (435 +/- 678 kJ x h(-1)), but the error of estimation for EE(RPE) (t = -3.01; p = 0.03) was less than 5% whereas for EE(HR) such error was 20.7%. The results of the study show that RPE can be used to estimate the energetic cost of playing tennis.
Estimates of tropical bromoform emissions using an inversion method
NASA Astrophysics Data System (ADS)
Ashfold, M. J.; Harris, N. R. P.; Manning, A. J.; Robinson, A. D.; Warwick, N. J.; Pyle, J. A.
2014-01-01
Bromine plays an important role in ozone chemistry in both the troposphere and stratosphere. When measured by mass, bromoform (CHBr3) is thought to be the largest organic source of bromine to the atmosphere. While seaweed and phytoplankton are known to be dominant sources, the size and the geographical distribution of CHBr3 emissions remains uncertain. Particularly little is known about emissions from the Maritime Continent, which have usually been assumed to be large, and which appear to be especially likely to reach the stratosphere. In this study we aim to reduce this uncertainty by combining the first multi-annual set of CHBr3 measurements from this region, and an inversion process, to investigate systematically the distribution and magnitude of CHBr3 emissions. The novelty of our approach lies in the application of the inversion method to CHBr3. We find that local measurements of a short-lived gas like CHBr3 can be used to constrain emissions from only a relatively small, sub-regional domain. We then obtain detailed estimates of CHBr3 emissions within this area, which appear to be relatively insensitive to the assumptions inherent in the inversion process. We extrapolate this information to produce estimated emissions for the entire tropics (defined as 20° S-20° N) of 225 Gg CHBr3 yr-1. The ocean in the area we base our extrapolations upon is typically somewhat shallower, and more biologically productive, than the tropical average. Despite this, our tropical estimate is lower than most other recent studies, and suggests that CHBr3 emissions in the coastline-rich Maritime Continent may not be stronger than emissions in other parts of the tropics.
Alkema, Leontine; New, Jin Rou; Pedersen, Jon; You, Danzhen
2014-01-01
Background In September 2013, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) published an update of the estimates of the under-five mortality rate (U5MR) and under-five deaths for all countries. Compared to the UN IGME estimates published in 2012, updated data inputs and a new method for estimating the U5MR were used. Methods We summarize the new U5MR estimation method, which is a Bayesian B-spline Bias-reduction model, and highlight differences with the previously used method. Differences in UN IGME U5MR estimates as published in 2012 and those published in 2013 are presented and decomposed into differences due to the updated database and differences due to the new estimation method to explain and motivate changes in estimates. Findings Compared to the previously used method, the new UN IGME estimation method is based on a different trend fitting method that can track (recent) changes in U5MR more closely. The new method provides U5MR estimates that account for data quality issues. Resulting differences in U5MR point estimates between the UN IGME 2012 and 2013 publications are small for the majority of countries but greater than 10 deaths per 1,000 live births for 33 countries in 2011 and 19 countries in 1990. These differences can be explained by the updated database used, the curve fitting method as well as accounting for data quality issues. Changes in the number of deaths were less than 10% on the global level and for the majority of MDG regions. Conclusions The 2013 UN IGME estimates provide the most recent assessment of levels and trends in U5MR based on all available data and an improved estimation method that allows for closer-to-real-time monitoring of changes in the U5MR and takes account of data quality issues. PMID:25013954
How reliable are the methods for estimating repertoire size?
Botero, Carlos A; Mudge, Andrew E; Koltz, Amanda M; Hochachka, Wesley M; Vehrencamp, Sandra L
2008-12-01
Quantifying signal repertoire size is a critical first step towards understanding the evolution of signal complexity. However, counting signal types can be so complicated and time consuming when repertoire size is large, that this trait is often estimated rather than measured directly. We studied how three common methods for repertoire size quantification (i.e., simple enumeration, curve-fitting and capture-recapture analysis) are affected by sample size and presentation style using simulated repertoires of known sizes. As expected, estimation error decreased with increasing sample size and varied among presentation styles. More surprisingly, for all but one of the presentation styles studied, curve-fitting and capture-recapture analysis yielded errors of similar or greater magnitude than the errors researchers would make by simply assuming that the number of types in an incomplete sample is the true repertoire size. Our results also indicate that studies based on incomplete samples are likely to yield incorrect ranking of individuals and spurious correlations with other parameters regardless of the technique of choice. Finally, we argue that biological receivers face similar difficulties in quantifying repertoire size than human observers and we explore some of the biological implications of this hypothesis.
An automatic iris occlusion estimation method based on high-dimensional density estimation.
Li, Yung-Hui; Savvides, Marios
2013-04-01
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. The accuracy of the iris mask is extremely important. The performance of the iris recognition system will decrease dramatically when the iris mask is inaccurate, even when the best recognition algorithm is used. Traditionally, people used the rule-based algorithms to estimate iris masks from iris images. However, the accuracy of the iris masks generated this way is questionable. In this work, we propose to use Figueiredo and Jain's Gaussian Mixture Models (FJ-GMMs) to model the underlying probabilistic distributions of both valid and invalid regions on iris images. We also explored possible features and found that Gabor Filter Bank (GFB) provides the most discriminative information for our goal. Finally, we applied Simulated Annealing (SA) technique to optimize the parameters of GFB in order to achieve the best recognition rate. Experimental results show that the masks generated by the proposed algorithm increase the iris recognition rate on both ICE2 and UBIRIS dataset, verifying the effectiveness and importance of our proposed method for iris occlusion estimation.
A TRMM Rainfall Estimation Method Applicable to Land Areas
NASA Technical Reports Server (NTRS)
Prabhakara, C.; Iacovazzi, R.; Weinman, J.; Dalu, G.
1999-01-01
Methods developed to estimate rain rate on a footprint scale over land with the satellite-borne multispectral dual-polarization Special Sensor Microwave Imager (SSM/1) radiometer have met with limited success. Variability of surface emissivity on land and beam filling are commonly cited as the weaknesses of these methods. On the contrary, we contend a more significant reason for this lack of success is that the information content of spectral and polarization measurements of the SSM/I is limited. because of significant redundancy. As a result, the complex nature and vertical distribution C, of frozen and melting ice particles of different densities, sizes, and shapes cannot resolved satisfactorily. Extinction in the microwave region due to these complex particles can mask the extinction due to rain drops. Because of these reasons, theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. To illustrate the weakness of these models, as an example we can consider the brightness temperature measurement made by the radiometer in the 85 GHz channel (T85). Models indicate that T85 should be inversely related to the rain rate, because of scattering. However, rain rate derived from 15-minute rain gauges on land indicate that this is not true in a majority of footprints. This is also supported by the ship-borne radar observations of rain in the Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) region over the ocean. Based on these observations. we infer that theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. We do not follow the above path of rain retrieval on a footprint scale. Instead, we depend on the limited ability of the microwave radiometer to detect the presence of rain. This capability is useful to determine the rain area in a mesoscale region. We find in a given rain event that this rain area is closely related to the mesoscale-average rain rate
[Methods for the estimation of the renal function].
Fontseré Baldellou, Néstor; Bonal I Bastons, Jordi; Romero González, Ramón
2007-10-13
The chronic kidney disease represents one of the pathologies with greater incidence and prevalence in the present sanitary systems. The ambulatory application of different methods that allow a suitable detection, monitoring and stratification of the renal functionalism is of crucial importance. On the basis of the vagueness obtained by means of the application of the serum creatinine, a set of predictive equations for the estimation of the glomerular filtration rate have been developed. Nevertheless, it is essential for the physician to know its limitations, in situations of normal renal function and hyperfiltration, certain associate pathologies and extreme situations of nutritional status and age. In these cases, the application of the isotopic techniques for the calculation of the renal function is more recommendable.
Some methods of computing platform transmitter terminal location estimates
NASA Astrophysics Data System (ADS)
Hoisington, C. M.
A position estimation algorithm was developed to track a humpback whale tagged with an ARGOS platform after a transmitter deployment failure and the whale's diving behavior precluded standard methods. The algorithm is especially useful where a transmitter location program exists; it determines the classical keplarian elements from the ARGOS spacecraft position vectors included with the probationary file messages. A minimum of three distinct messages are required. Once the spacecraft orbit is determined, the whale is located using standard least squares regression techniques. Experience suggests that in instances where circumstances inherent in the experiment yield message data unsuitable for the standard ARGOS reduction, (message data may be too sparse, span an insufficient period, or include variable-length messages). System ARGOS can still provide much valuable location information if the user is willing to accept the increased location uncertainties.
Flotation kinetics: Methods for estimating distribution of rate constants
Chander, S.; Polat, M.
1995-12-31
Many models have been suggested in the past to obtain a satisfactory fit to flotation data. Of these, first-order kinetics models with a distribution of flotation rate constants are most common. A serious limitation of these models is that type of the distribution must be pre-supposed. Methods to overcome this limitation are discussed and a procedure is suggested for estimating the actual distribution of flotation rate constants. It is demonstrated that the classical first-order model fits the data well when applied to coal flotation in narrow size-specific gravity intervals. When applied to material which is fractionated on the basis of size alone, the use of three parameter models, which were modified from their two parameter analogs such as rectangular, sinusoidal, and triangular, gave most reliable results.
Application of throughfall methods to estimate dry deposition of mercury
Lindberg, S.E.; Owens, J.G.; Stratton, W.
1992-12-31
Several dry deposition methods for Mercury (Hg) are being developed and tested in our laboratory. These include big-leaf and multilayer resistance models, micrometeorological methods such as Bowen ratio gradient approaches, laboratory controlled plant chambers, and throughfall. We have previously described our initial results using modeling and gradient methods. Throughfall may be used to estimate Hg dry deposition if some simplifying assumptions are met. We describe here the application and initial results of throughfull studies at the Walker Branch Watershed forest, and discuss the influence of certain assumptions on interpretation of the data. Throughfall appears useful in that it can place a lower bound to dry deposition under field conditions. Our preliminary throughfall data indicate net dry deposition rates to a pine canopy which increase significantly from winter to summer, as previously predicted by our resistance model. Atmospheric data suggest that rainfall washoff of fine aerosol dry deposition at this site is not sufficient to account for all of the Hg in net throughfall. Potential additional sources include dry deposited gas-phase compounds, soil-derived coarse aerosols, and oxidation reactions at the leaf surface.
A new rapid method for rockfall energies and distances estimation
NASA Astrophysics Data System (ADS)
Giacomini, Anna; Ferrari, Federica; Thoeni, Klaus; Lambert, Cedric
2016-04-01
Rockfalls are characterized by long travel distances and significant energies. Over the last decades, three main methods have been proposed in the literature to assess the rockfall runout: empirical, process-based and GIS-based methods (Dorren, 2003). Process-based methods take into account the physics of rockfall by simulating the motion of a falling rock along a slope and they are generally based on a probabilistic rockfall modelling approach that allows for taking into account the uncertainties associated with the rockfall phenomenon. Their application has the advantage of evaluating the energies, bounce heights and distances along the path of a falling block, hence providing valuable information for the design of mitigation measures (Agliardi et al., 2009), however, the implementation of rockfall simulations can be time-consuming and data-demanding. This work focuses on the development of a new methodology for estimating the expected kinetic energies and distances of the first impact at the base of a rock cliff, subject to the conditions that the geometry of the cliff and the properties of the representative block are known. The method is based on an extensive two-dimensional sensitivity analysis, conducted by means of kinematic simulations based on probabilistic modelling of two-dimensional rockfall trajectories (Ferrari et al., 2016). To take into account for the uncertainty associated with the estimation of the input parameters, the study was based on 78400 rockfall scenarios performed by systematically varying the input parameters that are likely to affect the block trajectory, its energy and distance at the base of the rock wall. The variation of the geometry of the rock cliff (in terms of height and slope angle), the roughness of the rock surface and the properties of the outcropping material were considered. A simplified and idealized rock wall geometry was adopted. The analysis of the results allowed finding empirical laws that relate impact energies
Inverse method for estimating respiration rates from decay time series
NASA Astrophysics Data System (ADS)
Forney, D. C.; Rothman, D. H.
2012-09-01
Long-term organic matter decomposition experiments typically measure the mass lost from decaying organic matter as a function of time. These experiments can provide information about the dynamics of carbon dioxide input to the atmosphere and controls on natural respiration processes. Decay slows down with time, suggesting that organic matter is composed of components (pools) with varied lability. Yet it is unclear how the appropriate rates, sizes, and number of pools vary with organic matter type, climate, and ecosystem. To better understand these relations, it is necessary to properly extract the decay rates from decomposition data. Here we present a regularized inverse method to identify an optimally-fitting distribution of decay rates associated with a decay time series. We motivate our study by first evaluating a standard, direct inversion of the data. The direct inversion identifies a discrete distribution of decay rates, where mass is concentrated in just a small number of discrete pools. It is consistent with identifying the best fitting "multi-pool" model, without prior assumption of the number of pools. However we find these multi-pool solutions are not robust to noise and are over-parametrized. We therefore introduce a method of regularized inversion, which identifies the solution which best fits the data but not the noise. This method shows that the data are described by a continuous distribution of rates, which we find is well approximated by a lognormal distribution, and consistent with the idea that decomposition results from a continuum of processes at different rates. The ubiquity of the lognormal distribution suggest that decay may be simply described by just two parameters: a mean and a variance of log rates. We conclude by describing a procedure that estimates these two lognormal parameters from decay data. Matlab codes for all numerical methods and procedures are provided.
Inverse method for estimating respiration rates from decay time series
NASA Astrophysics Data System (ADS)
Forney, D. C.; Rothman, D. H.
2012-03-01
Long-term organic matter decomposition experiments typically measure the mass lost from decaying organic matter as a function of time. These experiments can provide information about the dynamics of carbon dioxide input to the atmosphere and controls on natural respiration processes. Decay slows down with time, suggesting that organic matter is composed of components (pools) with varied lability. Yet it is unclear how the appropriate rates, sizes, and number of pools vary with organic matter type, climate, and ecosystem. To better understand these relations, it is necessary to properly extract the decay rates from decomposition data. Here we present a regularized inverse method to identify an optimally-fitting distribution of decay rates associated with a decay time series. We motivate our study by first evaluating a standard, direct inversion of the data. The direct inversion identifies a discrete distribution of decay rates, where mass is concentrated in just a small number of discrete pools. It is consistent with identifying the best fitting "multi-pool" model, without prior assumption of the number of pools. However we find these multi-pool solutions are not robust to noise and are over-parametrized. We therefore introduce a method of regularized inversion, which identifies the solution which best fits the data but not the noise. This method shows that the data are described by a continuous distribution of rates which we find is well approximated by a lognormal distribution, and consistent with the idea that decomposition results from a continuum of processes at different rates. The ubiquity of the lognormal distribution suggest that decay may be simply described by just two parameters; a mean and a variance of log rates. We conclude by describing a procedure that estimates these two lognormal parameters from decay data. Matlab codes for all numerical methods and procedures are provided.
NASA Astrophysics Data System (ADS)
Tada, A.; Tanakamaru, H.
2008-12-01
Total mass flux (load) from a catchment is a basic factor in evaluating chemical weathering or in TMDLs implementation. So far, many combinations of load estimation methods with sampling strategies were tested to obtain an unbiased flux estimate. To utilize such flux estimates in the political or scientific application, the information of uncertainty of flux estimates should also be provided. Giving the interval estimate of total flux may be a desirable solution to this situation. Total solute flux from a small, undisturbed forested catchment (12.8ha) during 10 months were calculated based on high-temporal resolution data and used in validation of 95% confidence intervals (CIs) of flux estimates. Water quality data (sodium, potassium, and chloride concentration) were collected and measured every 15 minutes during 10 months in 2004 by the on-site monitoring system using FIP (flow injection potentiometry) method with ion-selective electrodes. Water quantity data (the flow rate data) were measured continuously by V-notch weir at the catchment outlet. Flux estimates and 95% CIs were calculated for three indices with 41 methods; sample average, flow- weighted average, the Beale ratio estimator, rating curve method with simple linear regression between flux and the flow rate, and nine regression models in the USGS Load Estimator (Loadest). Smearing estimates, MVUE estimates, and estimates by composite method were also evaluated concerning nine regression models in Load Estimator. Two sampling strategies were tested; periodical sampling (daily and weekly) and flow stratified sampling. After data were sorted in ascending order of the flow rate, five strata were configured so that each stratum contained same number of data in flow stratified sampling. The performance of these 95% CIs was evaluated by the rate of inclusion of true flux value within these CIs, which should be expected as 0.95. A simple bootstrap method was adopted to construct the CIs with 2,000 bootstrap
A Method for Estimation of Death Tolls in Disastrous Earthquake
NASA Astrophysics Data System (ADS)
Pai, C.; Tien, Y.; Teng, T.
2004-12-01
Fatality tolls caused by the disastrous earthquake are the one of the most important items among the earthquake damage and losses. If we can precisely estimate the potential tolls and distribution of fatality in individual districts as soon as the earthquake occurrences, it not only make emergency programs and disaster management more effective but also supply critical information to plan and manage the disaster and the allotments of disaster rescue manpower and medicine resources in a timely manner. In this study, we intend to reach the estimation of death tolls caused by the Chi-Chi earthquake in individual districts based on the Attributive Database of Victims, population data, digital maps and Geographic Information Systems. In general, there were involved many factors including the characteristics of ground motions, geological conditions, types and usage habits of buildings, distribution of population and social-economic situations etc., all are related to the damage and losses induced by the disastrous earthquake. The density of seismic stations in Taiwan is the greatest in the world at present. In the meantime, it is easy to get complete seismic data by earthquake rapid-reporting systems from the Central Weather Bureau: mostly within about a minute or less after the earthquake happened. Therefore, it becomes possible to estimate death tolls caused by the earthquake in Taiwan based on the preliminary information. Firstly, we form the arithmetic mean of the three components of the Peak Ground Acceleration (PGA) to give the PGA Index for each individual seismic station, according to the mainshock data of the Chi-Chi earthquake. To supply the distribution of Iso-seismic Intensity Contours in any districts and resolve the problems for which there are no seismic station within partial districts through the PGA Index and geographical coordinates in individual seismic station, the Kriging Interpolation Method and the GIS software, The population density depends on
A Novel Parameter Estimation Method for Boltzmann Machines.
Takenouchi, Takashi
2015-11-01
We propose a novel estimator for a specific class of probabilistic models on discrete spaces such as the Boltzmann machine. The proposed estimator is derived from minimization of a convex risk function and can be constructed without calculating the normalization constant, whose computational cost is exponential order. We investigate statistical properties of the proposed estimator such as consistency and asymptotic normality in the framework of the estimating function. Small experiments show that the proposed estimator can attain comparable performance to the maximum likelihood expectation at a much lower computational cost and is applicable to high-dimensional data.
Seismic Methods of Identifying Explosions and Estimating Their Yield
NASA Astrophysics Data System (ADS)
Walter, W. R.; Ford, S. R.; Pasyanos, M.; Pyle, M. L.; Myers, S. C.; Mellors, R. J.; Pitarka, A.; Rodgers, A. J.; Hauk, T. F.
2014-12-01
Seismology plays a key national security role in detecting, locating, identifying and determining the yield of explosions from a variety of causes, including accidents, terrorist attacks and nuclear testing treaty violations (e.g. Koper et al., 2003, 1999; Walter et al. 1995). A collection of mainly empirical forensic techniques has been successfully developed over many years to obtain source information on explosions from their seismic signatures (e.g. Bowers and Selby, 2009). However a lesson from the three DPRK declared nuclear explosions since 2006, is that our historic collection of data may not be representative of future nuclear test signatures (e.g. Selby et al., 2012). To have confidence in identifying future explosions amongst the background of other seismic signals, and accurately estimate their yield, we need to put our empirical methods on a firmer physical footing. Goals of current research are to improve our physical understanding of the mechanisms of explosion generation of S- and surface-waves, and to advance our ability to numerically model and predict them. As part of that process we are re-examining regional seismic data from a variety of nuclear test sites including the DPRK and the former Nevada Test Site (now the Nevada National Security Site (NNSS)). Newer relative location and amplitude techniques can be employed to better quantify differences between explosions and used to understand those differences in term of depth, media and other properties. We are also making use of the Source Physics Experiments (SPE) at NNSS. The SPE chemical explosions are explicitly designed to improve our understanding of emplacement and source material effects on the generation of shear and surface waves (e.g. Snelson et al., 2013). Finally we are also exploring the value of combining seismic information with other technologies including acoustic and InSAR techniques to better understand the source characteristics. Our goal is to improve our explosion models
Bounded Influence Propagation tau -Estimation: A New Robust Method for ARMA Model Estimation
NASA Astrophysics Data System (ADS)
Muma, Michael; Zoubir, Abdelhak M.
2017-04-01
A new robust and statistically efficient estimator for ARMA models called the bounded influence propagation (BIP) {\\tau}-estimator is proposed. The estimator incorporates an auxiliary model, which prevents the propagation of outliers. Strong consistency and asymptotic normality of the estimator for ARMA models that are driven by independently and identically distributed (iid) innovations with symmetric distributions are established. To analyze the infinitesimal effect of outliers on the estimator, the influence function is derived and computed explicitly for an AR(1) model with additive outliers. To obtain estimates for the AR(p) model, a robust Durbin-Levinson type and a forward-backward algorithm are proposed. An iterative algorithm to robustly obtain ARMA(p,q) parameter estimates is also presented. The problem of finding a robust initialization is addressed, which for orders p+q>2 is a non-trivial matter. Numerical experiments are conducted to compare the finite sample performance of the proposed estimator to existing robust methodologies for different types of outliers both in terms of average and of worst-case performance, as measured by the maximum bias curve. To illustrate the practical applicability of the proposed estimator, a real-data example of outlier cleaning for R-R interval plots derived from electrocardiographic (ECG) data is considered. The proposed estimator is not limited to biomedical applications, but is also useful in any real-world problem whose observations can be modeled as an ARMA process disturbed by outliers or impulsive noise.
The Equivalence of Two Methods of Parameter Estimation for the Rasch Model.
ERIC Educational Resources Information Center
Blackwood, Larry G.; Bradley, Edwin L.
1989-01-01
Two methods of estimating parameters in the Rasch model are compared. The equivalence of likelihood estimations from the model of G. J. Mellenbergh and P. Vijn (1981) and from usual unconditional maximum likelihood (UML) estimation is demonstrated. Mellenbergh and Vijn's model is a convenient method of calculating UML estimates. (SLD)
An ultrasonic guided wave method to estimate applied biaxial loads
NASA Astrophysics Data System (ADS)
Shi, Fan; Michaels, Jennifer E.; Lee, Sang Jun
2012-05-01
Guided waves propagating in a homogeneous plate are known to be sensitive to both temperature changes and applied stress variations. Here we consider the inverse problem of recovering homogeneous biaxial stresses from measured changes in phase velocity at multiple propagation directions using a single mode at a specific frequency. Although there is no closed form solution relating phase velocity changes to applied stresses, prior results indicate that phase velocity changes can be closely approximated by a sinusoidal function with respect to angle of propagation. Here it is shown that all sinusoidal coefficients can be estimated from a single uniaxial loading experiment. The general biaxial inverse problem can thus be solved by fitting an appropriate sinusoid to measured phase velocity changes versus propagation angle, and relating the coefficients to the unknown stresses. The phase velocity data are obtained from direct arrivals between guided wave transducers whose direct paths of propagation are oriented at different angles. This method is applied and verified using sparse array data recorded during a fatigue test. The additional complication of the resulting fatigue cracks interfering with some of the direct arrivals is addressed via proper selection of transducer pairs. Results show that applied stresses can be successfully recovered from the measured changes in guided wave signals.
Novel method of channel estimation for WCDMA downlink
NASA Astrophysics Data System (ADS)
Sheng, Bin; You, XiaoHu
2001-10-01
A novel scheme for channel estimation is proposed in this paper for WCDMA Downlink where a pilot channel is simultaneously transmitted with a dada traffic channel. The proposed scheme exploits channel information in both pilot and data traffic channels by combining channel estimates from these two channels. It is demonstrated by computer simulations that the performance of the Rake receiver is improved obviously.
ERIC Educational Resources Information Center
Lafferty, Mark T.
2010-01-01
The number of project failures and those projects completed over cost and over schedule has been a significant issue for software project managers. Among the many reasons for failure, inaccuracy in software estimation--the basis for project bidding, budgeting, planning, and probability estimates--has been identified as a root cause of a high…
Application of age estimation methods based on teeth eruption: how easy is Olze method to use?
De Angelis, D; Gibelli, D; Merelli, V; Botto, M; Ventura, F; Cattaneo, C
2014-09-01
The development of new methods for age estimation has become with time an urgent issue because of the increasing immigration, in order to estimate accurately the age of those subjects who lack valid identity documents. Methods of age estimation are divided in skeletal and dental ones, and among the latter, Olze's method is one of the most recent, since it was introduced in 2010 with the aim to identify the legal age of 18 and 21 years by evaluating the different stages of development of the periodontal ligament of the third molars with closed root apices. The present study aims at verifying the applicability of the method to the daily forensic practice, with special focus on the interobserver repeatability. Olze's method was applied by three different observers (two physicians and one dentist without a specific training in Olze's method) to 61 orthopantomograms from subjects of mixed ethnicity aged between 16 and 51 years. The analysis took into consideration the lower third molars. The results provided by the different observers were then compared in order to verify the interobserver error. Results showed that interobserver error varies between 43 and 57 % for the right lower third molar (M48) and between 23 and 49 % for the left lower third molar (M38). Chi-square test did not show significant differences according to the side of teeth and type of professional figure. The results prove that Olze's method is not easy to apply when used by not adequately trained personnel, because of an intrinsic interobserver error. Since it is however a crucial method in age determination, it should be used only by experienced observers after an intensive and specific training.
Dabalus Islam, M; Schweikert Turcu, M; Cannavan, A
2008-12-01
A simple and inexpensive liquid chromatographic method for the determination of seven sulphonamides in animal tissues was validated. The measurement uncertainty of the method was estimated using two approaches: a 'top-down' approach based on in-house validation data, which used either repeatability data or intra-laboratory reproducibility; and a 'bottom-up' approach, which included repeatability data from spiking experiments. The decision limits (CCalpha) applied in the European Union were calculated for comparison. The bottom-up approach was used to identify critical steps in the analytical procedure, which comprised extraction, concentration, hexane-wash and HPLC-UV analysis. Six replicates of porcine kidney were fortified at the maximum residue limit (100 microg kg(-1)) at three different stages of the analytical procedure, extraction, evaporation, and final wash/HPLC analysis, to provide repeatability data for each step. The uncertainties of the gravimetric and volumetric measurements were estimated and integrated in the calculation of the total combined uncertainties by the bottom-up approach. Estimates for systematic error components were included in both approaches. Combined uncertainty estimates for the seven compounds using the 'top-down' approach ranged from 7.9 to 12.5% (using reproducibility) and from 5.4 to 9.5% (using repeatability data) and from 5.1 to 9.0% using the bottom-up approach. CCalpha values ranged from 105.6 to 108.5 microg kg(-1). The major contributor to the combined uncertainty for each analyte was identified as the extraction step. Since there was no statistical difference between the uncertainty values obtained by either approach, the analyst would be justified in applying the 'top-down' estimation using method validation data, rather than performing additional experiments to obtain uncertainty data.
On-line estimation of nonlinear physical systems
Christakos, G.
1988-01-01
Recursive algorithms for estimating states of nonlinear physical systems are presented. Orthogonality properties are rediscovered and the associated polynomials are used to linearize state and observation models of the underlying random processes. This requires some key hypotheses regarding the structure of these processes, which may then take account of a wide range of applications. The latter include streamflow forecasting, flood estimation, environmental protection, earthquake engineering, and mine planning. The proposed estimation algorithm may be compared favorably to Taylor series-type filters, nonlinear filters which approximate the probability density by Edgeworth or Gram-Charlier series, as well as to conventional statistical linearization-type estimators. Moreover, the method has several advantages over nonrecursive estimators like disjunctive kriging. To link theory with practice, some numerical results for a simulated system are presented, in which responses from the proposed and extended Kalman algorithms are compared. ?? 1988 International Association for Mathematical Geology.
Variational methods to estimate terrestrial ecosystem model parameters
NASA Astrophysics Data System (ADS)
Delahaies, Sylvain; Roulstone, Ian
2016-04-01
Carbon is at the basis of the chemistry of life. Its ubiquity in the Earth system is the result of complex recycling processes. Present in the atmosphere in the form of carbon dioxide it is adsorbed by marine and terrestrial ecosystems and stored within living biomass and decaying organic matter. Then soil chemistry and a non negligible amount of time transform the dead matter into fossil fuels. Throughout this cycle, carbon dioxide is released in the atmosphere through respiration and combustion of fossils fuels. Model-data fusion techniques allow us to combine our understanding of these complex processes with an ever-growing amount of observational data to help improving models and predictions. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Over the last decade several studies have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF, 4DVAR) to estimate model parameters and initial carbon stocks for DALEC and to quantify the uncertainty in the predictions. Despite its simplicity, DALEC represents the basic processes at the heart of more sophisticated models of the carbon cycle. Using adjoint based methods we study inverse problems for DALEC with various data streams (8 days MODIS LAI, monthly MODIS LAI, NEE). The framework of constraint optimization allows us to incorporate ecological common sense into the variational framework. We use resolution matrices to study the nature of the inverse problems and to obtain data importance and information content for the different type of data. We study how varying the time step affect the solutions, and we show how "spin up" naturally improves the conditioning of the inverse problems.
Analytic Method to Estimate Particle Acceleration in Flux Ropes
NASA Technical Reports Server (NTRS)
Guidoni, S. E.; Karpen, J. T.; DeVore, C. R.
2015-01-01
The mechanism that accelerates particles to the energies required to produce the observed high-energy emission in solar flares is not well understood. Drake et al. (2006) proposed a kinetic mechanism for accelerating electrons in contracting magnetic islands formed by reconnection. In this model, particles that gyrate around magnetic field lines transit from island to island, increasing their energy by Fermi acceleration in those islands that are contracting. Based on these ideas, we present an analytic model to estimate the energy gain of particles orbiting around field lines inside a flux rope (2.5D magnetic island). We calculate the change in the velocity of the particles as the flux rope evolves in time. The method assumes a simple profile for the magnetic field of the evolving island; it can be applied to any case where flux ropes are formed. In our case, the flux-rope evolution is obtained from our recent high-resolution, compressible 2.5D MHD simulations of breakout eruptive flares. The simulations allow us to resolve in detail the generation and evolution of large-scale flux ropes as a result of sporadic and patchy reconnection in the flare current sheet. Our results show that the initial energy of particles can be increased by 2-5 times in a typical contracting island, before the island reconnects with the underlying arcade. Therefore, particles need to transit only from 3-7 islands to increase their energies by two orders of magnitude. These macroscopic regions, filled with a large number of particles, may explain the large observed rates of energetic electron production in flares. We conclude that this mechanism is a promising candidate for electron acceleration in flares, but further research is needed to extend our results to 3D flare conditions.
Optimal Filtering Methods to Structural Damage Estimation under Ground Excitation
Hsieh, Chien-Shu; Liaw, Der-Cherng; Lin, Tzu-Hsuan
2013-01-01
This paper considers the problem of shear building damage estimation subject to earthquake ground excitation using the Kalman filtering approach. The structural damage is assumed to take the form of reduced elemental stiffness. Two damage estimation algorithms are proposed: one is the multiple model approach via the optimal two-stage Kalman estimator (OTSKE), and the other is the robust two-stage Kalman filter (RTSKF), an unbiased minimum-variance filtering approach to determine the locations and extents of the damage stiffness. A numerical example of a six-storey shear plane frame structure subject to base excitation is used to illustrate the usefulness of the proposed results. PMID:24453869
An Extreme Learning Machine Approach to Density Estimation Problems.
Cervellera, Cristiano; Maccio, Danilo
2017-01-17
In this paper, we discuss how the extreme learning machine (ELM) framework can be effectively employed in the unsupervised context of multivariate density estimation. In particular, two algorithms are introduced, one for the estimation of the cumulative distribution function underlying the observed data, and one for the estimation of the probability density function. The algorithms rely on the concept of $F$-discrepancy, which is closely related to the Kolmogorov-Smirnov criterion for goodness of fit. Both methods retain the key feature of the ELM of providing the solution through random assignment of the hidden feature map and a very light computational burden. A theoretical analysis is provided, discussing convergence under proper hypotheses on the chosen activation functions. Simulation tests show how ELMs can be successfully employed in the density estimation framework, as a possible alternative to other standard methods.
Bayesian Methods for Radiation Detection and Dosimetry
Peter G. Groer
2002-09-29
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed compartmental activities. From the estimated probability densities of the model parameters we were able to derive the densities for compartmental activities for a two compartment catenary model at different times. We also calculated the average activities and their standard deviation for a simple two compartment model.
Methods to Estimate the Variance of Some Indices of the Signal Detection Theory: A Simulation Study
ERIC Educational Resources Information Center
Suero, Manuel; Privado, Jesús; Botella, Juan
2017-01-01
A simulation study is presented to evaluate and compare three methods to estimate the variance of the estimates of the parameters d and "C" of the signal detection theory (SDT). Several methods have been proposed to calculate the variance of their estimators, "d'" and "c." Those methods have been mostly assessed by…
Dynamic State Estimation Utilizing High Performance Computing Methods
Schneider, Kevin P.; Huang, Zhenyu; Yang, Bo; Hauer, Matthew L.; Nieplocha, Jaroslaw
2009-03-18
The state estimation tools which are currently deployed in power system control rooms are based on a quasi-steady-state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper presents an overview of the Kalman Filtering process and then focuses on the implementation of the predication component on multiple processors.
Life Estimation Method for Optical Disk and Data Migration Method for Digitally Recorded Media
NASA Astrophysics Data System (ADS)
Watanabe, Atsumi
Results of Study about lifetime estimation method for DVD disk are described. The study was performed by Digital Content Association of Japan (DCAj) under commission from The Mechanical Social Systems Foundation with subsidies from JKA's industry promotional funds raised from KEIRIN RACE. DVD disks for which quality control is well performed have lifetime of 50-100 years or more. Data migration method for digitally recorded media is also described. Here, error check is requested every 3 years. If the measured error rate is larger than determined value, immediate data migration to new media is requested.
Shanei, Ahmad; Afshin, Maryam; Moslehi, Masoud; Rastaghi, Sedighe
2015-01-01
To make an accurate estimation of the uptake of radioactivity in an organ using the conjugate view method, corrections of physical factors, such as background activity, scatter, and attenuation are needed. The aim of this study was to evaluate the accuracy of four different methods for background correction in activity quantification of the heart in myocardial perfusion scans. The organ activity was calculated using the conjugate view method. A number of 22 healthy volunteers were injected with 17–19 mCi of 99mTc-methoxy-isobutyl-isonitrile (MIBI) at rest or during exercise. Images were obtained by a dual-headed gamma camera. Four methods for background correction were applied: (1) Conventional correction (referred to as the Gates' method), (2) Buijs method, (3) BgdA subtraction, (4) BgdB subtraction. To evaluate the accuracy of these methods, the results of the calculations using the above-mentioned methods were compared with the reference results. The calculated uptake in the heart using conventional method, Buijs method, BgdA subtraction, and BgdB subtraction methods was 1.4 ± 0.7% (P < 0.05), 2.6 ± 0.6% (P < 0.05), 1.3 ± 0.5% (P < 0.05), and 0.8 ± 0.3% (P < 0.05) of injected dose (I.D) at rest and 1.8 ± 0.6% (P > 0.05), 3.1 ± 0.8% (P > 0.05), 1.9 ± 0.8% (P < 0.05), and 1.2 ± 0.5% (P < 0.05) of I.D, during exercise. The mean estimated myocardial uptake of 99mTc-MIBI was dependent on the correction method used. Comparison among the four different methods of background activity correction applied in this study showed that the Buijs method was the most suitable method for background correction in myocardial perfusion scan. PMID:26955568
Shanei, Ahmad; Afshin, Maryam; Moslehi, Masoud; Rastaghi, Sedighe
2015-01-01
To make an accurate estimation of the uptake of radioactivity in an organ using the conjugate view method, corrections of physical factors, such as background activity, scatter, and attenuation are needed. The aim of this study was to evaluate the accuracy of four different methods for background correction in activity quantification of the heart in myocardial perfusion scans. The organ activity was calculated using the conjugate view method. A number of 22 healthy volunteers were injected with 17-19 mCi of (99m)Tc-methoxy-isobutyl-isonitrile (MIBI) at rest or during exercise. Images were obtained by a dual-headed gamma camera. Four methods for background correction were applied: (1) Conventional correction (referred to as the Gates' method), (2) Buijs method, (3) BgdA subtraction, (4) BgdB subtraction. To evaluate the accuracy of these methods, the results of the calculations using the above-mentioned methods were compared with the reference results. The calculated uptake in the heart using conventional method, Buijs method, BgdA subtraction, and BgdB subtraction methods was 1.4 ± 0.7% (P < 0.05), 2.6 ± 0.6% (P < 0.05), 1.3 ± 0.5% (P < 0.05), and 0.8 ± 0.3% (P < 0.05) of injected dose (I.D) at rest and 1.8 ± 0.6% (P > 0.05), 3.1 ± 0.8% (P > 0.05), 1.9 ± 0.8% (P < 0.05), and 1.2 ± 0.5% (P < 0.05) of I.D, during exercise. The mean estimated myocardial uptake of (99m)Tc-MIBI was dependent on the correction method used. Comparison among the four different methods of background activity correction applied in this study showed that the Buijs method was the most suitable method for background correction in myocardial perfusion scan.
Huang, Hao; Zhang, Guifu; Zhao, Kun; ...
2016-10-20
A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (KDP) and to improve rain estimation. Moreover, the hybrid KDP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δhv) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and KDP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid KDP estimator over existing methods.
Iterative methods for distributed parameter estimation in parabolic PDE
Vogel, C.R.; Wade, J.G.
1994-12-31
The goal of the work presented is the development of effective iterative techniques for large-scale inverse or parameter estimation problems. In this extended abstract, a detailed description of the mathematical framework in which the authors view these problem is presented, followed by an outline of the ideas and algorithms developed. Distributed parameter estimation problems often arise in mathematical modeling with partial differential equations. They can be viewed as inverse problems; the `forward problem` is that of using the fully specified model to predict the behavior of the system. The inverse or parameter estimation problem is: given the form of the model and some observed data from the system being modeled, determine the unknown parameters of the model. These problems are of great practical and mathematical interest, and the development of efficient computational algorithms is an active area of study.
PST - a new method for estimating PSA source terms
1996-12-31
The Parametric Source Term (PST) code has been developed for estimating radioactivity release fractions. The PST code is a framework of equations based on activity transport between volumes in the release pathway from the core, through the vessel, through the containment, and to the environment. The code is fast-running because it obtains exact solutions to differential equations for activity transport in each volume for each time interval. It has successfully been applied to estimate source terms for the six Pressurized Water Reactors (PWRs) that were selected for initial consideration in the Accident Sequence Precursor (ASP) Level 2 model development effort. This paper describes the PST code and the manner in which it has been applied to estimate radioactivity release fractions for the six PWRs initially considered in the ASP Program.
Oguchi, Masahiro; Fuse, Masaaki
2015-02-03
Product lifespan estimates are important information for understanding progress toward sustainable consumption and estimating the stocks and end-of-life flows of products. Publications reported actual lifespan of products; however, quantitative data are still limited for many countries and years. This study presents regional and longitudinal estimation of lifespan distribution of consumer durables, taking passenger cars as an example, and proposes a simplified method for estimating product lifespan distribution. We estimated lifespan distribution parameters for 17 countries based on the age profile of in-use cars. Sensitivity analysis demonstrated that the shape parameter of the lifespan distribution can be replaced by a constant value for all the countries and years. This enabled a simplified estimation that does not require detailed data on the age profile. Applying the simplified method, we estimated the trend in average lifespans of passenger cars from 2000 to 2009 for 20 countries. Average lifespan differed greatly between countries (9-23 years) and was increasing in many countries. This suggests consumer behavior differs greatly among countries and has changed over time, even in developed countries. The results suggest that inappropriate assumptions of average lifespan may cause significant inaccuracy in estimating the stocks and end-of-life flows of products.
Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence
NASA Technical Reports Server (NTRS)
Mark, W. D.
1981-01-01
A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.
PHREATOPHYTE WATER USE ESTIMATED BY EDDY-CORRELATION METHODS.
Weaver, H.L.; Weeks, E.P.; Campbell, G.S.; Stannard, D.I.; Tanner, B.D.
1986-01-01
Water-use was estimated for three phreatophyte communities: a saltcedar community and an alkali-Sacaton grass community in New Mexico, and a greasewood rabbit-brush-saltgrass community in Colorado. These water-use estimates were calculated from eddy-correlation measurements using three different analyses, since the direct eddy-correlation measurements did not satisfy a surface energy balance. The analysis that seems to be most accurate indicated the saltcedar community used from 58 to 87 cm (23 to 34 in. ) of water each year. The other two communities used about two-thirds this quantity.
COMPARISON OF METHODS FOR ESTIMATING GROUND-WATER PUMPAGE FOR IRRIGATION.
Frenzel, Steven A.
1985-01-01
Ground-water pumpage for irrigation was measured at 32 sites on the eastern Snake River Plain in southern Idaho during 1983. Pumpage at these sites also was estimated by three commonly used methods, and pumpage estimates were compared to measured values to determine the accuracy of each estimate. Statistical comparisons of estimated and metered pumpage using an F-test showed that only estimates made using the instantaneous discharge method were not significantly different ( alpha equals 0. 01) from metered values. Pumpage estimates made using the power consumption method reflect variability in pumping efficiency among sites. Pumpage estimates made using the crop-consumptive use method reflect variability in water-management practices. Pumpage estimates made using the instantaneous discharge method reflect variability in discharges at each site during the irrigation season.
Assessing Methods for Generalizing Experimental Impact Estimates to Target Populations
ERIC Educational Resources Information Center
Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P.
2016-01-01
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Assessment of in silico methods to estimate aquatic species sensitivity
Determining the sensitivity of a diversity of species to environmental contaminants continues to be a significant challenge in ecological risk assessment because toxicity data are generally limited to a few standard species. In many cases, QSAR models are used to estimate toxici...
A Modified Frequency Estimation Equating Method for the Common-Item Nonequivalent Groups Design
ERIC Educational Resources Information Center
Wang, Tianyou; Brennan, Robert L.
2009-01-01
Frequency estimation, also called poststratification, is an equating method used under the common-item nonequivalent groups design. A modified frequency estimation method is proposed here, based on altering one of the traditional assumptions in frequency estimation in order to correct for equating bias. A simulation study was carried out to…
Sousa, Fátima Aparecida Emm Faleiros; da Silva, Talita de Cássia Raminelli; Siqueira, Hilze Benigno de Oliveira Moura; Saltareli, Simone; Gomez, Rodrigo Ramon Falconi; Hortense, Priscilla
2016-01-01
Abstract Objective: to describe acute and chronic pain from the perspective of the life cycle. Methods: participants: 861 people in pain. The Multidimensional Pain Evaluation Scale (MPES) was used. Results: in the category estimation method the highest descriptors of chronic pain for children/ adolescents were "Annoying" and for adults "Uncomfortable". The highest descriptors of acute pain for children/adolescents was "Complicated"; and for adults was "Unbearable". In magnitude estimation method, the highest descriptors of chronic pain was "Desperate" and for descriptors of acute pain was "Terrible". Conclusions: the MPES is a reliable scale it can be applied during different stages of development. PMID:27556875
NASA Astrophysics Data System (ADS)
Griffin, Brian M.; Larson, Vincent E.
2016-11-01
Microphysical processes, such as the formation, growth, and evaporation of precipitation, interact with variability and covariances (e.g., fluxes) in moisture and heat content. For instance, evaporation of rain may produce cold pools, which in turn may trigger fresh convection and precipitation. These effects are usually omitted or else crudely parameterized at subgrid scales in weather and climate models.A more formal approach is pursued here, based on predictive, horizontally averaged equations for the variances, covariances, and fluxes of moisture and heat content. These higher-order moment equations contain microphysical source terms. The microphysics terms can be integrated analytically, given a suitably simple warm-rain microphysics scheme and an approximate assumption about the multivariate distribution of cloud-related and precipitation-related variables. Performing the integrations provides exact expressions within an idealized context.A large-eddy simulation (LES) of a shallow precipitating cumulus case is performed here, and it indicates that the microphysical effects on (co)variances and fluxes can be large. In some budgets and altitude ranges, they are dominant terms. The analytic expressions for the integrals are implemented in a single-column, higher-order closure model. Interactive single-column simulations agree qualitatively with the LES. The analytic integrations form a parameterization of microphysical effects in their own right, and they also serve as benchmark solutions that can be compared to non-analytic integration methods.
Griffin, Brian M.; Larson, Vincent E.
2016-11-25
Microphysical processes, such as the formation, growth, and evaporation of precipitation, interact with variability and covariances (e.g., fluxes) in moisture and heat content. For instance, evaporation of rain may produce cold pools, which in turn may trigger fresh convection and precipitation. These effects are usually omitted or else crudely parameterized at subgrid scales in weather and climate models.A more formal approach is pursued here, based on predictive, horizontally averaged equations for the variances, covariances, and fluxes of moisture and heat content. These higher-order moment equations contain microphysical source terms. The microphysics terms can be integrated analytically, given a suitably simplemore » warm-rain microphysics scheme and an approximate assumption about the multivariate distribution of cloud-related and precipitation-related variables. Performing the integrations provides exact expressions within an idealized context.A large-eddy simulation (LES) of a shallow precipitating cumulus case is performed here, and it indicates that the microphysical effects on (co)variances and fluxes can be large. In some budgets and altitude ranges, they are dominant terms. The analytic expressions for the integrals are implemented in a single-column, higher-order closure model. Interactive single-column simulations agree qualitatively with the LES. The analytic integrations form a parameterization of microphysical effects in their own right, and they also serve as benchmark solutions that can be compared to non-analytic integration methods.« less
Flood frequency estimation by hydrological continuous simulation and classical methods
NASA Astrophysics Data System (ADS)
Brocca, L.; Camici, S.; Melone, F.; Moramarco, T.; Tarpanelli, A.
2009-04-01
In recent years, the effects of flood damages have motivated the development of new complex methodologies for the simulation of the hydrologic/hydraulic behaviour of river systems, fundamental to direct the territorial planning as well as for the floodplain management and risk analysis. The valuation of the flood-prone areas can be carried out through various procedures that are usually based on the estimation of the peak discharge for an assigned probability of exceedence. In the case of ungauged or scarcely gauged catchments this is not straightforward, as the limited availability of historical peak flow data induces a relevant uncertainty in the flood frequency analysis. A possible solution to overcome this problem is the application of hydrological simulation studies in order to generate long synthetic discharge time series. For this purpose, recently, new methodologies based on the stochastic generation of rainfall and temperature data have been proposed. The inferred information can be used as input for a continuous hydrological model to generate a synthetic time series of peak river flow and, hence, the flood frequency distribution at a given site. In this study stochastic rainfall data have been generated via the Neyman-Scott Rectangular Pulses (NSRP) model characterized by a flexible structure in which the model parameters broadly relate to underlying physical features observed in rainfall fields and it is capable of preserving statistical properties of a rainfall time series over a range of time scales. The peak river flow time series have been generated through a continuous hydrological model aimed at flood prediction and developed for the purpose (hereinafter named MISDc) (Brocca, L., Melone, F., Moramarco, T., Singh, V.P., 2008. A continuous rainfall-runoff model as tool for the critical hydrological scenario assessment in natural channels. In: M. Taniguchi, W.C. Burnett, Y. Fukushima, M. Haigh, Y. Umezawa (Eds), From headwater to the ocean
Estimating Intracranial Volume in Brain Research: An Evaluation of Methods.
Sargolzaei, Saman; Sargolzaei, Arman; Cabrerizo, Mercedes; Chen, Gang; Goryawala, Mohammed; Pinzon-Ardila, Alberto; Gonzalez-Arias, Sergio M; Adjouadi, Malek
2015-10-01
Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer's disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.
Quantitative estimation of poikilocytosis by the coherent optical method
NASA Astrophysics Data System (ADS)
Safonova, Larisa P.; Samorodov, Andrey V.; Spiridonov, Igor N.
2000-05-01
The investigation upon the necessity and the reliability required of the determination of the poikilocytosis in hematology has shown that existing techniques suffer from grave shortcomings. To determine a deviation of the erythrocytes' form from the normal (rounded) one in blood smears it is expedient to use an integrative estimate. The algorithm which is based on the correlation between erythrocyte morphological parameters with properties of the spatial-frequency spectrum of blood smear is suggested. During analytical and experimental research an integrative form parameter (IFP) which characterizes the increase of the relative concentration of cells with the changed form over 5% and the predominating type of poikilocytes was suggested. An algorithm of statistically reliable estimation of the IFP on the standard stained blood smears has been developed. To provide the quantitative characterization of the morphological features of cells a form vector has been proposed, and its validity for poikilocytes differentiation was shown.
Application of Density Estimation Methods to Datasets from a Glider
2013-09-30
Glider Elizabeth Thorp Küsel and Martin Siderius Portland State University Electrical and Computer Engineering Department 1900 SW 4th Ave...Fitting the glider with two recording sensors, instead of one, provides the opportunity to investigate other density estimation modalities ( Thomas and...Am. 134, 3506-3512. Carretta, J. V., Forney, K. A., Lowry , M. S., Barlow, J., Baker, J., Johnston, D., Hanson, B., Brownell Jr., R. L., Robbins
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Allometric method to estimate leaf area index for row crops
Technology Transfer Automated Retrieval System (TEKTRAN)
Leaf area index (LAI) is critical for predicting plant metabolism, biomass production, evapotranspiration, and greenhouse gas sequestration, but direct LAI measurements are difficult and labor intensive. Several methods are available to measure LAI indirectly or calculate LAI using allometric method...
Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation
NASA Technical Reports Server (NTRS)
Morelli, Eugene a.
2006-01-01
Various practical aspects of the equation-error approach to aircraft parameter estimation were examined. The analysis was based on simulated flight data from an F-16 nonlinear simulation, with realistic noise sequences added to the computed aircraft responses. This approach exposes issues related to the parameter estimation techniques and results, because the true parameter values are known for simulation data. The issues studied include differentiating noisy time series, maximum likelihood parameter estimation, biases in equation-error parameter estimates, accurate computation of estimated parameter error bounds, comparisons of equation-error parameter estimates with output-error parameter estimates, analyzing data from multiple maneuvers, data collinearity, and frequency-domain methods.
NASA Astrophysics Data System (ADS)
Ishigaki, Tsukasa; Yamamoto, Yoshinobu; Nakamura, Yoshiyuki; Akamatsu, Motoyuki
Patients that have an health service by doctor have to wait long time at many hospitals. The long waiting time is the worst factor of patient's dissatisfaction for hospital service according to questionnaire for patients. The present paper describes an estimation method of the waiting time for each patient without an electronic medical chart system. The method applies a portable RFID system to data acquisition and robust estimation of probability distribution of the health service and test time by doctor for high-accurate waiting time estimation. We carried out an health service of data acquisition at a real hospital and verified the efficiency of the proposed method. The proposed system widely can be used as data acquisition system in various fields such as marketing service, entertainment or human behavior measurement.
Golmakani, Nahid; Khaleghinezhad, Khosheh; Dadgar, Selmeh; Hashempor, Majid; Baharian, Nosrat
2015-01-01
Introduction: In developing countries, hemorrhage accounts for 30% of the maternal deaths. Postpartum hemorrhage has been defined as blood loss of around 500 ml or more, after completing the third phase of labor. Most cases of postpartum hemorrhage occur during the first hour after birth. The most common reason for bleeding in the early hours after childbirth is uterine atony. Bleeding during delivery is usually a visual estimate that is measured by the midwife. It has a high error rate. However, studies have shown that the use of a standard can improve the estimation. The aim of the research is to compare the estimation of postpartum hemorrhage using the weighting method and the National Guideline for postpartum hemorrhage estimation. Materials and Methods: This descriptive study was conducted on 112 females in the Omolbanin Maternity Department of Mashhad, for a six-month period, from November 2012 to May 2013. The accessible method was used for sampling. The data collection tools were case selection, observation and interview forms. For postpartum hemorrhage estimation, after the third section of labor was complete, the quantity of bleeding was estimated in the first and second hours after delivery, by the midwife in charge, using the National Guideline for vaginal delivery, provided by the Maternal Health Office. Also, after visual estimation by using the National Guideline, the sheets under parturient in first and second hours after delivery were exchanged and weighted. The data were analyzed using descriptive statistics and the t-test. Results: According to the results, a significant difference was found between the estimated blood loss based on the weighting methods and that using the National Guideline (weighting method 62.68 ± 16.858 cc vs. National Guideline 45.31 ± 13.484 cc in the first hour after delivery) (P = 0.000) and (weighting method 41.26 ± 10.518 vs. National Guideline 30.24 ± 8.439 in second hour after delivery) (P = 0.000). Conclusions
Sound speed estimation and source localization with linearization and particle filtering.
Lin, Tao; Michalopoulou, Zoi-Heleni
2014-03-01
A method is developed for the estimation of source location and sound speed in the water column relying on linearization. The Jacobian matrix, necessary for the proposed linearization approach, includes derivatives with respect to empirical orthogonal function coefficients instead of sound speed directly. First, the inversion technique is tested on synthetic arrival times, using Gaussian distributions for the errors in the considered arrival times. The approach is efficient, requiring a few iterations, and produces accurate results. Probability densities of the estimates are calculated for different levels of noise in the arrival times. Subsequently, particle filtering is employed for the estimation of arrival times from signals recorded during the Shallow Water 06 experiment. It has been shown in the past that particle filtering can be employed for the successful estimation of multipath arrival times from short-range data and, consequently, in geometry, bathymetry, and sound speed inversion. Here probability density functions of arrival times computed via particle filtering are propagated backward through the proposed inversion process. Inversion estimates are consistent with values reported in the literature for the same quantities. Last it is shown that results are consistent with estimates resulting from fast simulated annealing applied to the same data.
Wind power error estimation in resource assessments.
Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel
2015-01-01
Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.
Wind Power Error Estimation in Resource Assessments
Rodríguez, Osvaldo; del Río, Jesús A.; Jaramillo, Oscar A.; Martínez, Manuel
2015-01-01
Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies. PMID:26000444
Computation of nonparametric convex hazard estimators via profile methods
Jankowski, Hanna K.; Wellner, Jon A.
2010-01-01
This paper proposes a profile likelihood algorithm to compute the nonparametric maximum likelihood estimator of a convex hazard function. The maximisation is performed in two steps: First the support reduction algorithm is used to maximise the likelihood over all hazard functions with a given point of minimum (or antimode). Then it is shown that the profile (or partially maximised) likelihood is quasi-concave as a function of the antimode, so that a bisection algorithm can be applied to find the maximum of the profile likelihood, and hence also the global maximum. The new algorithm is illustrated using both artificial and real data, including lifetime data for Canadian males and females. PMID:20300560
NASA Astrophysics Data System (ADS)
Hida, Hajime; Tomigashi, Yoshio; Ueyama, Kenji; Inoue, Yukinori; Morimoto, Shigeo
This paper proposes a new torque estimation method that takes into account the spatial harmonics of permanent magnet synchronous motors and that is capable of real-time estimation. First, the torque estimation equation of the proposed method is derived. In the method, the torque ripple of a motor can be estimated from the average of the torque calculated by the conventional method (cross product of the fluxlinkage and motor current) and the torque calculated from the electric input power to the motor. Next, the effectiveness of the proposed method is verified by simulations in which two kinds of motors with different components of torque ripple are considered. The simulation results show that the proposed method estimates the torque ripple more accurately than the conventional method. Further, the effectiveness of the proposed method is verified by performing on experiment. It is shown that the torque ripple is decreased by using the proposed method to the torque control.
Nonlinear Attitude Filtering Methods
NASA Technical Reports Server (NTRS)
Markley, F. Landis; Crassidis, John L.; Cheng, Yang
2005-01-01
This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.
Estimating the prevalence of anaemia: a comparison of three methods.
Sari, M.; de Pee, S.; Martini, E.; Herman, S.; Sugiatmi; Bloem, M. W.; Yip, R.
2001-01-01
OBJECTIVE: To determine the most effective method for analysing haemoglobin concentrations in large surveys in remote areas, and to compare two methods (indirect cyanmethaemoglobin and HemoCue) with the conventional method (direct cyanmethaemoglobin). METHODS: Samples of venous and capillary blood from 121 mothers in Indonesia were compared using all three methods. FINDINGS: When the indirect cyanmethaemoglobin method was used the prevalence of anaemia was 31-38%. When the direct cyanmethaemoglobin or HemoCue method was used the prevalence was 14-18%. Indirect measurement of cyanmethaemoglobin had the highest coefficient of variation and the largest standard deviation of the difference between the first and second assessment of the same blood sample (10-12 g/l indirect measurement vs 4 g/l direct measurement). In comparison with direct cyanmethaemoglobin measurement of venous blood, HemoCue had the highest sensitivity (82.4%) and specificity (94.2%) when used for venous blood. CONCLUSIONS: Where field conditions and local resources allow it, haemoglobin concentration should be assessed with the direct cyanmethaemoglobin method, the gold standard. However, the HemoCue method can be used for surveys involving different laboratories or which are conducted in relatively remote areas. In very hot and humid climates, HemoCue microcuvettes should be discarded if not used within a few days of opening the container containing the cuvettes. PMID:11436471
Walker, Neff; Hill, Kenneth; Zhao, Fengmin
2012-01-01
In most low- and middle-income countries, child mortality is estimated from data provided by mothers concerning the survival of their children using methods that assume no correlation between the mortality risks of the mothers and those of their children. This assumption is not valid for populations with generalized HIV epidemics, however, and in this review, we show how the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) uses a cohort component projection model to correct for AIDS-related biases in the data used to estimate trends in under-five mortality. In this model, births in a given year are identified as occurring to HIV-positive or HIV-negative mothers, the lives of the infants and mothers are projected forward using survivorship probabilities to estimate survivors at the time of a given survey, and the extent to which excess mortality of children goes unreported because of the deaths of HIV-infected mothers prior to the survey is calculated. Estimates from the survey for past periods can then be adjusted for the estimated bias. The extent of the AIDS-related bias depends crucially on the dynamics of the HIV epidemic, on the length of time before the survey that the estimates are made for, and on the underlying non-AIDS child mortality. This simple methodology (which does not take into account the use of effective antiretroviral interventions) gives results qualitatively similar to those of other studies.
An estimation method of the fault wind turbine power generation loss based on correlation analysis
NASA Astrophysics Data System (ADS)
Zhang, Tao; Zhu, Shourang; Wang, Wei
2017-01-01
A method for estimating the power generation loss of a fault wind turbine is proposed in this paper. In this method, the wind speed is estimated and the estimated value of the loss of power generation is given by combining the actual output power characteristic curve of the wind turbine. In the wind speed estimation, the correlation analysis is used, and the normal operation of the wind speed of the fault wind turbine is selected, and the regression analysis method is used to obtain the estimated value of the wind speed. Based on the estimation method, this paper presents an implementation of the method in the monitoring system of the wind turbine, and verifies the effectiveness of the proposed method.
Advanced Method to Estimate Fuel Slosh Simulation Parameters
NASA Technical Reports Server (NTRS)
Schlee, Keith; Gangadharan, Sathya; Ristow, James; Sudermann, James; Walker, Charles; Hubert, Carl
2005-01-01
The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the
Palatine tonsil volume estimation using different methods after tonsillectomy.
Sağıroğlu, Ayşe; Acer, Niyazi; Okuducu, Hacı; Ertekin, Tolga; Erkan, Mustafa; Durmaz, Esra; Aydın, Mesut; Yılmaz, Seher; Zararsız, Gökmen
2016-06-15
This study was carried out to measure the volume of the palatine tonsil in otorhinolaryngology outpatients with complaints of adenotonsillar hypertrophy and chronic tonsillitis who had undergone tonsillectomy. To date, no study has investigated palatine tonsil volume using different methods and compared with subjective tonsil size in the literature. For this purpose, we used three different methods to measure palatine tonsil volume. The correlation of each parameter with tonsil size was assessed. After tonsillectomy, palatine tonsil volume was measured by Archimedes, Cavalieri and Ellipsoid methods. Mean right-left palatine tonsil volumes were calculated as 2.63 ± 1.34 cm(3) and 2.72 ± 1.51 cm(3) by the Archimedes method, 3.51 ± 1.48 cm(3) and 3.37 ± 1.36 cm(3) by the Cavalieri method, and 2.22 ± 1.22 cm(3) and 2.29 ± 1.42 cm(3) by the Ellipsoid method, respectively. Excellent agreement was found among the three methods of measuring volumetric techniques according to Bland-Altman plots. In addition, tonsil grade was correlated significantly with tonsil volume.
Numerical method for estimating the size of chaotic regions of phase space
Henyey, F.S.; Pomphrey, N.
1987-10-01
A numerical method for estimating irregular volumes of phase space is derived. The estimate weights the irregular area on a surface of section with the average return time to the section. We illustrate the method by application to the stadium and oval billiard systems and also apply the method to the continuous Henon-Heiles system. 15 refs., 10 figs. (LSP)
Method of estimating pulse response using an impedance spectrum
Morrison, John L; Morrison, William H; Christophersen, Jon P; Motloch, Chester G
2014-10-21
Electrochemical Impedance Spectrum data are used to predict pulse performance of an energy storage device. The impedance spectrum may be obtained in-situ. A simulation waveform includes a pulse wave with a period greater than or equal to the lowest frequency used in the impedance measurement. Fourier series coefficients of the pulse train can be obtained. The number of harmonic constituents in the Fourier series are selected so as to appropriately resolve the response, but the maximum frequency should be less than or equal to the highest frequency used in the impedance measurement. Using a current pulse as an example, the Fourier coefficients of the pulse are multiplied by the impedance spectrum at corresponding frequencies to obtain Fourier coefficients of the voltage response to the desired pulse. The Fourier coefficients of the response are then summed and reassembled to obtain the overall time domain estimate of the voltage using the Fourier series analysis.
Semi-quantitative method to estimate levels of Campylobacter
Technology Transfer Automated Retrieval System (TEKTRAN)
Introduction: Research projects utilizing live animals and/or systems often require reliable, accurate quantification of Campylobacter following treatments. Even with marker strains, conventional methods designed to quantify are labor and material intensive requiring either serial dilutions or MPN ...
A history-based method to estimate animal preference
Maia, Caroline Marques; Volpato, Gilson Luiz
2016-01-01
Giving animals their preferred items (e.g., environmental enrichment) has been suggested as a method to improve animal welfare, thus raising the question of how to determine what animals want. Most studies have employed choice tests for detecting animal preferences. However, whether choice tests represent animal preferences remains a matter of controversy. Here, we present a history-based method to analyse data from individual choice tests to discriminate between preferred and non-preferred items. This method differentially weighs choices from older and recent tests performed over time. Accordingly, we provide both a preference index that identifies preferred items contrasted with non-preferred items in successive multiple-choice tests and methods to detect the strength of animal preferences for each item. We achieved this goal by investigating colour choices in the Nile tilapia fish species. PMID:27350213
Evaluation of acidity estimation methods for mine drainage, Pennsylvania, USA.
Park, Daeryong; Park, Byungtae; Mendinsky, Justin J; Paksuchon, Benjaphon; Suhataikul, Ratda; Dempsey, Brian A; Cho, Yunchul
2015-01-01
Eighteen sites impacted by abandoned mine drainage (AMD) in Pennsylvania were sampled and measured for pH, acidity, alkalinity, metal ions, and sulfate. This study compared the accuracy of four acidity calculation methods with measured hot peroxide acidity and identified the most accurate calculation method for each site as a function of pH and sulfate concentration. Method E1 was the sum of proton and acidity based on total metal concentrations; method E2 added alkalinity; method E3 also accounted for aluminum speciation and temperature effects; and method E4 accounted for sulfate speciation. To evaluate errors between measured and predicted acidity, the Nash-Sutcliffe efficiency (NSE), the coefficient of determination (R (2)), and the root mean square error to standard deviation ratio (RSR) methods were applied. The error evaluation results show that E1, E2, E3, and E4 sites were most accurate at 0, 9, 4, and 5 of the sites, respectively. Sites where E2 was most accurate had pH greater than 4.0 and less than 400 mg/L of sulfate. Sites where E3 was most accurate had pH greater than 4.0 and sulfate greater than 400 mg/L with two exceptions. Sites where E4 was most accurate had pH less than 4.0 and more than 400 mg/L sulfate with one exception. The results indicate that acidity in AMD-affected streams can be accurately predicted by using pH, alkalinity, sulfate, Fe(II), Mn(II), and Al(III) concentrations in one or more of the identified equations, and that the appropriate equation for prediction can be selected based on pH and sulfate concentration.
ERIC Educational Resources Information Center
Lei, Pui-Wa; Dunbar, Stephen B.
2004-01-01
The primary purpose of this study was to examine relative performance of 2 power estimation methods in structural equation modeling. Sample size, alpha level, type of manifest variable, type of specification errors, and size of correlation between constructs were manipulated. Type 1 error rate of the model chi-square test, empirical critical…
Estimation of mechanical properties of nanomaterials using artificial intelligence methods
NASA Astrophysics Data System (ADS)
Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.
2014-09-01
Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.
Clement, Matthew; O'Keefe, Joy M; Walters, Brianne
2015-01-01
While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.
NASA Technical Reports Server (NTRS)
Sidik, S. M.
1975-01-01
Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.
A New Method For Cosmological Parameter Estimation From SNIa Data
NASA Astrophysics Data System (ADS)
March, Marisa; Trotta, R.; Berkes, P.; Starkman, G. D.; Vaudrevange, P. M.
2011-01-01
We present a new methodology to extract constraints on cosmological parameters from SNIa data obtained with the SALT2 lightcurve fitter. The power of our Bayesian method lies in its full exploitation of relevant prior information, which is ignored by the usual chisquare approach. Using realistic simulated data sets we demonstrate that our method outperforms the usual chisquare approach 2/3 of the time while achieving better long-term coverage properties. A further benefit of our methodology is its ability to produce a posterior probability distribution for the intrinsic dispersion of SNe. This feature can also be used to detect hidden systematics in the data.
Estimation of missing rainfall data using spatial interpolation and imputation methods
NASA Astrophysics Data System (ADS)
Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Azman, Muhammad Az-zuhri
2015-02-01
This study is aimed to estimate missing rainfall data by dividing the analysis into three different percentages namely 5%, 10% and 20% in order to represent various cases of missing data. In practice, spatial interpolation methods are chosen at the first place to estimate missing data. These methods include normal ratio (NR), arithmetic average (AA), coefficient of correlation (CC) and inverse distance (ID) weighting methods. The methods consider the distance between the target and the neighbouring stations as well as the correlations between them. Alternative method for solving missing data is an imputation method. Imputation is a process of replacing missing data with substituted values. A once-common method of imputation is single-imputation method, which allows parameter estimation. However, the single imputation method ignored the estimation of variability which leads to the underestimation of standard errors and confidence intervals. To overcome underestimation problem, multiple imputations method is used, where each missing value is estimated with a distribution of imputations that reflect the uncertainty about the missing data. In this study, comparison of spatial interpolation methods and multiple imputations method are presented to estimate missing rainfall data. The performance of the estimation methods used are assessed using the similarity index (S-index), mean absolute error (MAE) and coefficient of correlation (R).
A method for estimating both the solubility parameters and molar volumes of liquids
NASA Technical Reports Server (NTRS)
Fedors, R. F.
1974-01-01
Development of an indirect method of estimating the solubility parameter of high molecular weight polymers. The proposed method of estimating the solubility parameter, like Small's method, is based on group additive constants, but is believed to be superior to Small's method for two reasons: (1) the contribution of a much larger number of functional groups have been evaluated, and (2) the method requires only a knowledge of structural formula of the compound.
Estimation of the size of the female sex worker population in Rwanda using three different methods.
Mutagoma, Mwumvaneza; Kayitesi, Catherine; Gwiza, Aimé; Ruton, Hinda; Koleros, Andrew; Gupta, Neil; Balisanga, Helene; Riedel, David J; Nsanzimana, Sabin
2015-10-01
HIV prevalence is disproportionately high among female sex workers compared to the general population. Many African countries lack useful data on the size of female sex worker populations to inform national HIV programmes. A female sex worker size estimation exercise using three different venue-based methodologies was conducted among female sex workers in all provinces of Rwanda in August 2010. The female sex worker national population size was estimated using capture-recapture and enumeration methods, and the multiplier method was used to estimate the size of the female sex worker population in Kigali. A structured questionnaire was also used to supplement the data. The estimated number of female sex workers by the capture-recapture method was 3205 (95% confidence interval: 2998-3412). The female sex worker size was estimated at 3348 using the enumeration method. In Kigali, the female sex worker size was estimated at 2253 (95% confidence interval: 1916-2524) using the multiplier method. Nearly 80% of all female sex workers in Rwanda were found to be based in the capital, Kigali. This study provided a first-time estimate of the female sex worker population size in Rwanda using capture-recapture, enumeration, and multiplier methods. The capture-recapture and enumeration methods provided similar estimates of female sex worker in Rwanda. Combination of such size estimation methods is feasible and productive in low-resource settings and should be considered vital to inform national HIV programmes.
Application of Density Estimation Methods to Datasets from a Glider
2014-09-30
humpback and sperm whales as well as different dolphin species. OBJECTIVES The objective of this research is to extend existing methods for cetacean...OSU) working on this project with known occurrence of many marine mammal species, ranging from pinnipeds, to baleen whales, cetaceans and dolphin
Estimating School Efficiency: A Comparison of Methods Using Simulated Data.
ERIC Educational Resources Information Center
Bifulco, Robert; Bretschneider, Stuart
2001-01-01
Uses simulated data to assess the adequacy of two econometric and linear-programming techniques (data-envelopment analysis and corrected ordinary least squares) for measuring performance-based school reform. In complex data sets (simulated to contain measurement error and endogeneity), these methods are inadequate efficiency measures. (Contains 40…
Effects of Vertical Scaling Methods on Linear Growth Estimation
ERIC Educational Resources Information Center
Lei, Pui-Wa; Zhao, Yu
2012-01-01
Vertical scaling is necessary to facilitate comparison of scores from test forms of different difficulty levels. It is widely used to enable the tracking of student growth in academic performance over time. Most previous studies on vertical scaling methods assume relatively long tests and large samples. Little is known about their performance when…
Dhingra, Pratibha; Sazawa, Sunil; Menon, Venugopal P; Dhingra, Usha; Black, Robert E
2007-03-01
In this observational study, estimation of food intake was evaluated using recording of portion size consumed, instead of post-weighing, as a method. In total, 930 feeding episodes were observed among 128 children aged 12-24 months in which actual intake was available by pre- and post-weighing. For each offering and feeding episode, portion size consumed was recorded by an independent nutritionist-as none, less than half, half or more, and all. Using the pre-weighed offering, available intake was estimated by multiplying portion sizes by the estimated weight. The estimated mean intake was 510.4 kilojoules compared to actual intake of 510.7 kilojoules by weighing. Similar results were found with nestum (52.0 vs 56.2 g), bread (3.8 vs 3.7 g), puffed rice (1.7 vs 1.9 g), banana (31.3 vs 24.4 g), and milk (41.6 vs 44.2 mL). Recording portion size consumed and estimating food intake from that provides a good alternative to the time-consuming and often culturally-unacceptable method of post-weighing food each time after a feeding episode.
A wind tunnel evaluation of methods for estimating surface roughness length at industrial facilities
NASA Astrophysics Data System (ADS)
Petersen, Ronald L.
This paper discusses three objective methods for estimating surface roughness length based on the physical dimensions of structures or obstructions at a refinery (or other industrial sites of interest). The three methods are referred to as the Lettau method, simplified Counihan method, and Counihan method. These three methods were evaluated using five wind tunnel databases. The databases consisted of scale models of three refineries and two uniform roughness configurations. Velocity profiles were measured in the wind tunnel over these refinery models and roughness configurations, and were subsequently analyzed to estimate the surface roughness, z0. Seven different methods were used to estimate surface roughness from the velocity profiles and a wide range of z0 estimates was obtained from these methods. Only two of the methods were deemed adequate for estimating surface roughness length for situations with large roughness elements and where a change of roughness has occurred. These two methods were selected to represent 'true' estimates of the surface roughness length for the modeled refineries and roughness configurations. A statistical evaluation of the predicted (Lettau, simplified Counihan and Counihan) and observed surface roughness lengths was then carried out using a statistical analysis program developed by the American Petroleum Institute (API). The results of the evaluation showed that the Lettau method provides a good estimate (within a factor of 0.5-1.5 at the 95% confidence interval) of surface roughness length and one that is better than the other methods tested.
Comparison of ready biodegradation estimation methods for fragrance materials.
Boethling, Robert
2014-11-01
Biodegradability is fundamental to the assessment of environmental exposure and risk from organic chemicals. Predictive models can be used to pursue both regulatory and chemical design (green chemistry) objectives, which are most effectively met when models are easy to use and available free of charge. The objective of this work was to evaluate no-cost estimation programs with respect to prediction of ready biodegradability. Fragrance materials, which are structurally diverse and have significant exposure potential, were used for this purpose. Using a database of 222 fragrance compounds with measured ready biodegradability, 10 models were compared on the basis of overall accuracy, sensitivity, specificity, and Matthews correlation coefficient (MCC), a measure of quality for binary classification. The 10 models were VEGA© Non-Interactive Client, START (Toxtree©), Biowin©1-6, and two models based on inductive machine learning. Applicability domain (AD) was also considered. Overall accuracy was ca. 70% and varied little over all models, but sensitivity, specificity and MCC showed wider variation. Based on MCC, the best models for fragrance compounds were Biowin6, VEGA and Biowin3. VEGA performance was slightly better for the <50% of the compounds it identified as having "high reliability" predictions (AD index >0.8). However, removing compounds with one and only one quaternary carbon yielded similar improvement in predictivity for VEGA, START, and Biowin3/6, with a smaller penalty in reduced coverage. Of the nine compounds for which the eight models (VEGA, START, Biowin1-6) all disagreed with the measured value, measured analog data were available for seven, and all supported the predicted value. VEGA, Biowin3 and Biowin6 are judged suitable for ready biodegradability screening of fragrance compounds.
A TRMM Rainfall Estimation Method Applicable to Land Areas
NASA Technical Reports Server (NTRS)
Prabhakara, C.; Iacovazzi, R., Jr.; Oki, R.; Weinman, J. A.
1998-01-01
Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that
Feasible methods to estimate disease based price indexes.
Bradley, Ralph
2013-05-01
There is a consensus that statistical agencies should report medical data by disease rather than by service. This study computes price indexes that are necessary to deflate nominal disease expenditures and to decompose their growth into price, treated prevalence and output per patient growth. Unlike previous studies, it uses methods that can be implemented by the Bureau of Labor Statistics (BLS). For the calendar years 2005-2010, I find that these feasible disease based indexes are approximately 1% lower on an annual basis than indexes computed by current methods at BLS. This gives evidence that traditional medical price indexes have not accounted for the more efficient use of medical inputs in treating most diseases.
A new gaze estimation method considering external light.
Lee, Jong Man; Lee, Hyeon Chang; Gwon, Su Yeong; Jung, Dongwook; Pan, Weiyuan; Cho, Chul Woo; Park, Kang Ryoung; Kim, Hyun-Cheol; Cha, Jihun
2015-03-11
Gaze tracking systems usually utilize near-infrared (NIR) lights and NIR cameras, and the performance of such systems is mainly affected by external light sources that include NIR components. This is ascribed to the production of additional (imposter) corneal specular reflection (SR) caused by the external light, which makes it difficult to discriminate between the correct SR as caused by the NIR illuminator of the gaze tracking system and the imposter SR. To overcome this problem, a new method is proposed for determining the correct SR in the presence of external light based on the relationship between the corneal SR and the pupil movable area with the relative position of the pupil and the corneal SR. The experimental results showed that the proposed method makes the gaze tracking system robust to the existence of external light.
Data-Driven Method to Estimate Nonlinear Chemical Equivalence
Mayo, Michael; Collier, Zachary A.; Winton, Corey; Chappell, Mark A
2015-01-01
There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of “equivalency factors,” which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or “biphasic,” responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are “parallel,” which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach. PMID:26158701
A Method to Estimate Fabric Particle Penetration Performance
2014-09-08
OF PAGES 19a. NAME OF RESPONSIBLE PERSON Terence Ghee a . REPORT Unclassified b . ABSTRACT Unclassified c. THIS PAGE Unclassified... A Effective swatch area, 9.6 cm2 b Span length, 0.6096 m Dp Particle diameter, nm N Number concentration P Pressure, millibars P∞ Tunnel static...using the ASTM D1895B method and included two controls: Arizona road dust and glass spheres see Table B -1. DISSEMINATION SYSTEM A dissemination
Systematic variational method for statistical nonlinear state and parameter estimation
NASA Astrophysics Data System (ADS)
Ye, Jingxin; Rey, Daniel; Kadakia, Nirag; Eldridge, Michael; Morone, Uriel I.; Rozdeba, Paul; Abarbanel, Henry D. I.; Quinn, John C.
2015-11-01
In statistical data assimilation one evaluates the conditional expected values, conditioned on measurements, of interesting quantities on the path of a model through observation and prediction windows. This often requires working with very high dimensional integrals in the discrete time descriptions of the observations and model dynamics, which become functional integrals in the continuous-time limit. Two familiar methods for performing these integrals include (1) Monte Carlo calculations and (2) variational approximations using the method of Laplace plus perturbative corrections to the dominant contributions. We attend here to aspects of the Laplace approximation and develop an annealing method for locating the variational path satisfying the Euler-Lagrange equations that comprises the major contribution to the integrals. This begins with the identification of the minimum action path starting with a situation where the model dynamics is totally unresolved in state space, and the consistent minimum of the variational problem is known. We then proceed to slowly increase the model resolution, seeking to remain in the basin of the minimum action path, until a path that gives the dominant contribution to the integral is identified. After a discussion of some general issues, we give examples of the assimilation process for some simple, instructive models from the geophysical literature. Then we explore a slightly richer model of the same type with two distinct time scales. This is followed by a model characterizing the biophysics of individual neurons.
Kaplanoglu, Erkan; Safak, Koray K.; Varol, H. Selcuk
2009-01-12
An experiment based method is proposed for parameter estimation of a class of linear multivariable systems. The method was applied to a pressure-level control process. Experimental time domain input/output data was utilized in a gray-box modeling approach. Prior knowledge of the form of the system transfer function matrix elements is assumed to be known. Continuous-time system transfer function matrix parameters were estimated in real-time by the least-squares method. Simulation results of experimentally determined system transfer function matrix compare very well with the experimental results. For comparison and as an alternative to the proposed real-time estimation method, we also implemented an offline identification method using artificial neural networks and obtained fairly good results. The proposed methods can be implemented conveniently on a desktop PC equipped with a data acquisition board for parameter estimation of moderately complex linear multivariable systems.
Rupšys, P.
2015-10-28
A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.
NASA Astrophysics Data System (ADS)
Rupšys, P.
2015-10-01
A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.
Wu, Zhihong; Lu, Ke; Zhu, Yuan
2015-01-01
The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment.
Zhu, Yuan
2015-01-01
The torque output accuracy of the IPMSM in electric vehicles using a state of the art MTPA strategy highly depends on the accuracy of machine parameters, thus, a torque estimation method is necessary for the safety of the vehicle. In this paper, a torque estimation method based on flux estimator with a modified low pass filter is presented. Moreover, by taking into account the non-ideal characteristic of the inverter, the torque estimation accuracy is improved significantly. The effectiveness of the proposed method is demonstrated through MATLAB/Simulink simulation and experiment. PMID:26114557
EXPERIMENTAL METHODS TO ESTIMATE ACCUMULATED SOLIDS IN NUCLEAR WASTE TANKS
Duignan, M.; Steeper, T.; Steimke, J.
2012-12-10
devices and techniques were very effective to estimate the movement, location, and concentrations of the solids representing plutonium and are expected to perform well at a larger scale. The operation of the techniques and their measurement accuracies will be discussed as well as the overall results of the accumulated solids test.
An Ultrasonic Guided Wave Method to Estimate Applied Biaxial Loads (Preprint)
2011-11-01
orientation are estimated from a sinusoidal fit of ultrasonic data collected from the same spatially distributed array that is being used to detect and...AFRL-RX-WP-TP-2011-4361 AN ULTRASONIC GUIDED WAVE METHOD TO ESTIMATE APPLIED BIAXIAL LOADS (PREPRINT) Fan, Shi, Jennifer E. Michaels, and...Technical Paper 1 November 2011 – 1 November 2011 4. TITLE AND SUBTITLE AN ULTRASONIC GUIDED WAVE METHOD TO ESTIMATE APPLIED BIAXIAL LOADS (PREPRINT
Limitations of model-fitting methods for lensing shear estimation
NASA Astrophysics Data System (ADS)
Voigt, L. M.; Bridle, S. L.
2010-05-01
Gravitational lensing shear has the potential to be the most powerful tool for constraining the nature of dark energy. However, accurate measurement of galaxy shear is crucial and has been shown to be non-trivial by the Shear TEsting Programme. Here, we demonstrate a fundamental limit to the accuracy achievable by model-fitting techniques, if oversimplistic models are used. We show that even if galaxies have elliptical isophotes, model-fitting methods which assume elliptical isophotes can have significant biases if they use the wrong profile. We use noise-free simulations to show that on allowing sufficient flexibility in the profile the biases can be made negligible. This is no longer the case if elliptical isophote models are used to fit galaxies made up of a bulge plus a disc, if these two components have different ellipticities. The limiting accuracy is dependent on the galaxy shape, but we find the most significant biases (~1 per cent of the shear) for simple spiral-like galaxies. The implications for a given cosmic shear survey will depend on the actual distribution of galaxy morphologies in the Universe, taking into account the survey selection function and the point spread function. However, our results suggest that the impact on cosmic shear results from current and near future surveys may be negligible. Meanwhile, these results should encourage the development of existing approaches which are less sensitive to morphology, as well as methods which use priors on galaxy shapes learnt from deep surveys.
ERIC Educational Resources Information Center
Fan, Xitao; Wang, Lin; Thompson, Bruce
1999-01-01
A Monte Carlo simulation study investigated the effects on 10 structural equation modeling fit indexes of sample size, estimation method, and model specification. Some fit indexes did not appear to be comparable, and it was apparent that estimation method strongly influenced almost all fit indexes examined, especially for misspecified models. (SLD)
Parameter estimation technique for boundary value problems by spline collocation method
NASA Technical Reports Server (NTRS)
Kojima, Fumio
1988-01-01
A parameter-estimation technique for boundary-integral equations of the second kind is developed. The output least-squares identification technique using the spline collocation method is considered. The convergence analysis for the numerical method is discussed. The results are applied to boundary parameter estimations for two-dimensional Laplace and Helmholtz equations.
Global mean estimation using a self-organizing dual-zoning method for preferential sampling.
Pan, Yuchun; Ren, Xuhong; Gao, Bingbo; Liu, Yu; Gao, YunBing; Hao, Xingyao; Chen, Ziyue
2015-03-01
Giving an appropriate weight to each sampling point is essential to global mean estimation. The objective of this paper was to develop a global mean estimation method with preferential samples. The procedure for this estimation method was to first zone the study area based on self-organizing dual-zoning method and then to estimate the mean according to stratified sampling method. In this method, spreading of points in both feature and geographical space is considered. The method is tested in a case study on the metal Mn concentrations in Jilin provinces of China. Six sample patterns are selected to estimate the global mean and compared with the global mean calculated by direct arithmetic mean method, polygon method, and cell method. The results show that the proposed method produces more accurate and stable mean estimates under different feature deviation index (FDI) values and sample sizes. The relative errors of the global mean calculated by the proposed method are from 0.14 to 1.47 % and they are the largest (4.83-8.84 %) by direct arithmetic mean method. At the same time, the mean results calculated by the other three methods are sensitive to the FDI values and sample sizes.
System and Method for Outlier Detection via Estimating Clusters
NASA Technical Reports Server (NTRS)
Iverson, David J. (Inventor)
2016-01-01
An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.
Method and system for non-linear motion estimation
NASA Technical Reports Server (NTRS)
Lu, Ligang (Inventor)
2011-01-01
A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.
Study on Comparison of Bidding and Pricing Behavior Distinction between Estimate Methods
NASA Astrophysics Data System (ADS)
Morimoto, Emi; Namerikawa, Susumu
The most characteristic trend on bidding and pricing behavior distinction in recent years is the increasing number of bidders just above the criteria for low-price bidding investigations. The contractor's markup is the difference between the bidding price and the execution price. Therefore, the contractor's markup is the difference between criteria for low-price bidding investigations price and the execution price in the public works bid in Japan. Virtually, bidder's strategies and behavior have been controlled by public engineer's budgets. Estimation and bid are inseparably linked in the Japanese public works procurement system. The trial of the unit price-type estimation method begins in 2004. On another front, accumulated estimation method is one of the general methods in public works. So, there are two types of standard estimation methods in Japan. In this study, we did a statistical analysis on the bid information of civil engineering works for the Ministry of Land, Infrastructure, and Transportation in 2008. It presents several issues that bidding and pricing behavior is related to an estimation method (several estimation methods) for public works bid in Japan. The two types of standard estimation methods produce different results that number of bidders (decide on bid-no bid strategy) and distribution of bid price (decide on mark-up strategy).The comparison on the distribution of bid prices showed that the percentage of the bid concentrated on the criteria for low-price bidding investigations have had a tendency to get higher in the large-sized public works by the unit price-type estimation method, comparing with the accumulated estimation method. On one hand, the number of bidders who bids for public works estimated unit-price tends to increase significantly Public works estimated unit-price is likely to have been one of the factors for the construction companies to decide if they participate in the biddings.
A method to estimate weight and dimensions of large and small gas turbine engines
NASA Technical Reports Server (NTRS)
Onat, E.; Klees, G. W.
1979-01-01
A computerized method was developed to estimate weight and envelope dimensions of large and small gas turbine engines within + or - 5% to 10%. The method is based on correlations of component weight and design features of 29 data base engines. Rotating components were estimated by a preliminary design procedure which is sensitive to blade geometry, operating conditions, material properties, shaft speed, hub tip ratio, etc. The development and justification of the method selected, and the various methods of analysis are discussed.
Comparative Evaluation of Two Methods to Estimate Natural Gas Production in Texas
2003-01-01
This report describes an evaluation conducted by the Energy Information Administration (EIA) in August 2003 of two methods that estimate natural gas production in Texas. The first method (parametric method) was used by EIA from February through August 2003 and the second method (multinomial method) replaced it starting in September 2003, based on the results of this evaluation.
Huang, Hao; Zhang, Guifu; Zhao, Kun; Giangrande, Scott E.
2016-10-20
A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K_{DP}) and to improve rain estimation. Moreover, the hybrid K_{DP} estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ_{hv}) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and K_{DP}-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K_{DP} estimator over existing methods.
An improved method for nonlinear parameter estimation: a case study of the Rössler model
NASA Astrophysics Data System (ADS)
He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan
2016-08-01
Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.
Brassey, Charlotte A; Maidment, Susannah C R; Barrett, Paul M
2015-03-01
Body mass is a key biological variable, but difficult to assess from fossils. Various techniques exist for estimating body mass from skeletal parameters, but few studies have compared outputs from different methods. Here, we apply several mass estimation methods to an exceptionally complete skeleton of the dinosaur Stegosaurus. Applying a volumetric convex-hulling technique to a digital model of Stegosaurus, we estimate a mass of 1560 kg (95% prediction interval 1082-2256 kg) for this individual. By contrast, bivariate equations based on limb dimensions predict values between 2355 and 3751 kg and require implausible amounts of soft tissue and/or high body densities. When corrected for ontogenetic scaling, however, volumetric and linear equations are brought into close agreement. Our results raise concerns regarding the application of predictive equations to extinct taxa with no living analogues in terms of overall morphology and highlight the sensitivity of bivariate predictive equations to the ontogenetic status of the specimen. We emphasize the significance of rare, complete fossil skeletons in validating widely applied mass estimation equations based on incomplete skeletal material and stress the importance of accurately determining specimen age prior to further analyses.
Brassey, Charlotte A.; Maidment, Susannah C. R.; Barrett, Paul M.
2015-01-01
Body mass is a key biological variable, but difficult to assess from fossils. Various techniques exist for estimating body mass from skeletal parameters, but few studies have compared outputs from different methods. Here, we apply several mass estimation methods to an exceptionally complete skeleton of the dinosaur Stegosaurus. Applying a volumetric convex-hulling technique to a digital model of Stegosaurus, we estimate a mass of 1560 kg (95% prediction interval 1082–2256 kg) for this individual. By contrast, bivariate equations based on limb dimensions predict values between 2355 and 3751 kg and require implausible amounts of soft tissue and/or high body densities. When corrected for ontogenetic scaling, however, volumetric and linear equations are brought into close agreement. Our results raise concerns regarding the application of predictive equations to extinct taxa with no living analogues in terms of overall morphology and highlight the sensitivity of bivariate predictive equations to the ontogenetic status of the specimen. We emphasize the significance of rare, complete fossil skeletons in validating widely applied mass estimation equations based on incomplete skeletal material and stress the importance of accurately determining specimen age prior to further analyses. PMID:25740841
Olascoaga, Beñat; Mac Arthur, Alasdair; Atherton, Jon; Porcar-Castell, Albert
2016-01-01
Accurate temporal and spatial measurements of leaf optical traits (i.e., absorption, reflectance and transmittance) are paramount to photosynthetic studies. These optical traits are also needed to couple radiative transfer and physiological models to facilitate the interpretation of optical data. However, estimating leaf optical traits in leaves with complex morphologies remains a challenge. Leaf optical traits can be measured using integrating spheres, either by placing the leaf sample in one of the measuring ports (External Method) or by placing the sample inside the sphere (Internal Method). However, in leaves with complex morphology (e.g., needles), the External Method presents limitations associated with gaps between the leaves, and the Internal Method presents uncertainties related to the estimation of total leaf area. We introduce a modified version of the Internal Method, which bypasses the effect of gaps and the need to estimate total leaf area, by painting the leaves black and measuring them before and after painting. We assess and compare the new method with the External Method using a broadleaf and two conifer species. Both methods yielded similar leaf absorption estimates for the broadleaf, but absorption estimates were higher with the External Method for the conifer species. Factors explaining the differences between methods, their trade-offs and their advantages and limitations are also discussed. We suggest that the new method can be used to estimate leaf absorption in any type of leaf independently of its morphology, and be used to study further the impact of gap fraction in the External Method. PMID:26843207
Multivariate drought frequency estimation using copula method in Southwest China
NASA Astrophysics Data System (ADS)
Hao, Cui; Zhang, Jiahua; Yao, Fengmei
2017-02-01
Drought over Southwest China occurs frequently and has an obvious seasonal characteristic. Proper management of regional droughts requires knowledge of the expected frequency or probability of specific climate information. This study utilized k-means classification and copulas to demonstrate the regional drought occurrence probability and return period based on trivariate drought properties, i.e., drought duration, severity, and peak. A drought event in this study was defined when 3-month Standardized Precipitation Evapotranspiration Index (SPEI) was less than -0.99 according to the regional climate characteristic. Then, the next step was to classify the region into six clusters by k-means method based on annual and seasonal precipitation and temperature and to establish marginal probabilistic distributions for each drought property in each sub-region. Several copula types were selected to test the best fit distribution, and Student t copula was recognized as the best one to integrate drought duration, severity, and peak. The results indicated that a proper classification was important for a regional drought frequency analysis, and copulas were useful tools in exploring the associations of the correlated drought variables and analyzing drought frequency. Student t copula was a robust and proper function for drought joint probability and return period analysis, which is important for analyzing and predicting the regional drought risks.
Estimating basin scale evapotranspiration (ET) by water balance and remote sensing methods
Senay, G.B.; Leake, S.; Nagler, P.L.; Artan, G.; Dickinson, J.; Cordova, J.T.; Glenn, E.P.
2011-01-01
Evapotranspiration (ET) is an important hydrological process that can be studied and estimated at multiple spatial scales ranging from a leaf to a river basin. We present a review of methods in estimating basin scale ET and its applications in understanding basin water balance dynamics. The review focuses on two aspects of ET: (i) how the basin scale water balance approach is used to estimate ET; and (ii) how ‘direct’ measurement and modelling approaches are used to estimate basin scale ET. Obviously, the basin water balance-based ET requires the availability of good precipitation and discharge data to calculate ET as a residual on longer time scales (annual) where net storage changes are assumed to be negligible. ET estimated from such a basin water balance principle is generally used for validating the performance of ET models. On the other hand, many of the direct estimation methods involve the use of remotely sensed data to estimate spatially explicit ET and use basin-wide averaging to estimate basin scale ET. The direct methods can be grouped into soil moisture balance modelling, satellite-based vegetation index methods, and methods based on satellite land surface temperature measurements that convert potential ET into actual ET using a proportionality relationship. The review also includes the use of complementary ET estimation principles for large area applications. The review identifies the need to compare and evaluate the different ET approaches using standard data sets in basins covering different hydro-climatic regions of the world.
Gu, M G; Kong, F H
1998-06-23
We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.
An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia
Kidney, Darren; Rawson, Benjamin M.; Borchers, David L.; Stevenson, Ben C.; Marques, Tiago A.; Thomas, Len
2016-01-01
Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR) methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers’ estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will make this method
LSimpute: accurate estimation of missing values in microarray data with least squares methods.
Bø, Trond Hellem; Dysvik, Bjarte; Jonassen, Inge
2004-02-20
Microarray experiments generate data sets with information on the expression levels of thousands of genes in a set of biological samples. Unfortunately, such experiments often produce multiple missing expression values, normally due to various experimental problems. As many algorithms for gene expression analysis require a complete data matrix as input, the missing values have to be estimated in order to analyze the available data. Alternatively, genes and arrays can be removed until no missing values remain. However, for genes or arrays with only a small number of missing values, it is desirable to impute those values. For the subsequent analysis to be as informative as possible, it is essential that the estimates for the missing gene expression values are accurate. A small amount of badly estimated missing values in the data might be enough for clustering methods, such as hierachical clustering or K-means clustering, to produce misleading results. Thus, accurate methods for missing value estimation are needed. We present novel methods for estimation of missing values in microarray data sets that are based on the least squares principle, and that utilize correlations between both genes and arrays. For this set of methods, we use the common reference name LSimpute. We compare the estimation accuracy of our methods with the widely used KNNimpute on three complete data matrices from public data sets by randomly knocking out data (labeling as missing). From these tests, we conclude that our LSimpute methods produce estimates that consistently are more accurate than those obtained using KNNimpute. Additionally, we examine a more classic approach to missing value estimation based on expectation maximization (EM). We refer to our EM implementations as EMimpute, and the estimate errors using the EMimpute methods are compared with those our novel methods produce. The results indicate that on average, the estimates from our best performing LSimpute method are at least as
Handschin, E.; Langer, M.; Kliokys, E.
1995-12-31
The possibility of power system state estimation with non-traditional measurement configuration is investigated. It is assumed that some substations are equipped with current magnitude measurements. Unique state estimation is possible, in such a situation, if currents are combined with voltage or power measurements and inequality constraints on node power injections are taken into account. The state estimation algorithm facilitating the efficient incorporation of inequality constraints is developed using an interior point optimization method. Simulation results showing the performance of the algorithm are presented. The method can be used for state estimation in medium voltage subtransmission and distribution networks.
Nguyen, Vinh Hao; Suh, Young Soo
2007-01-01
This paper is concerned with improving performance of a state estimation problem over a network in which a send-on-delta (SOD) transmission method is used. The SOD method requires that a sensor node transmit data to the estimator node only if its measurement value changes more than a given specified δ value. This method has been explored and applied by researchers because of its efficiency in the network bandwidth improvement. However, when this method is used, it is not ensured that the estimator node receives data from the sensor nodes regularly at every estimation period. Therefore, we propose a method to reduce estimation error in case of no sensor data reception. When the estimator node does not receive data from the sensor node, the sensor value is known to be in a (−δi,+δi) interval from the last transmitted sensor value. This implicit information has been used to improve estimation performance in previous studies. The main contribution of this paper is to propose an algorithm, where the sensor value interval is reduced to (−δi/2,+δi/2) in certain situations. Thus, the proposed algorithm improves the overall estimation performance without any changes in the send-on-delta algorithms of the sensor nodes. Through numerical simulations, we demonstrate the feasibility and the usefulness of the proposed method.
Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†
Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia
2015-01-01
Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144
Loss Factor Estimation Using the Impulse Response Decay Method on a Stiffened Structure
NASA Technical Reports Server (NTRS)
Cabell, Randolph; Schiller, Noah; Allen, Albert; Moeller, Mark
2009-01-01
High-frequency vibroacoustic modeling is typically performed using energy-based techniques such as Statistical Energy Analysis (SEA). Energy models require an estimate of the internal damping loss factor. Unfortunately, the loss factor is difficult to estimate analytically, and experimental methods such as the power injection method can require extensive measurements over the structure of interest. This paper discusses the implications of estimating damping loss factors using the impulse response decay method (IRDM) from a limited set of response measurements. An automated procedure for implementing IRDM is described and then evaluated using data from a finite element model of a stiffened, curved panel. Estimated loss factors are compared with loss factors computed using a power injection method and a manual curve fit. The paper discusses the sensitivity of the IRDM loss factor estimates to damping of connected subsystems and the number and location of points in the measurement ensemble.
2015-08-01
MODIFIED MAXIMUM LIKELIHOOD ESTIMATION METHOD FOR COMPLETELY SEPARATED AND QUASI-COMPLETELY SEPARATED DATA...Likelihood Estimation Method for Completely Separated and Quasi-Completely Separated Data for a Dose-Response Model 5a. CONTRACT NUMBER 5b. GRANT...quasi-completely separated , the traditional maximum likelihood estimation (MLE) method generates infinite estimates. The bias-reduction (BR) method
Akkaya, Nursel; Yilanci, Hümeyra Özge; Göksülük, Dinçer
2015-09-01
The aim of this study was to evaluate applicability of five dental methods including Demirjian's original, revised, four teeth, and alternate four teeth methods and Willems method for age estimation in a sample of Turkish children. Panoramic radiographs of 799 children (412 females, 387 males) aged between 2.20 and 15.99years were examined by two observers. A repeated measures ANOVA was performed to compare dental methods among gender and age groups. All of the five methods overestimated the chronological age on the average. Among these, Willems method was found to be the most accurate method, which showed 0.07 and 0.15years overestimation for males and females, respectively. It was followed by Demirjian's four teeth methods, revised and original methods. According to the results, Willems method can be recommended for dental age estimation of Turkish children in forensic applications.
Motion estimation using low-band-shift method for wavelet-based moving-picture coding.
Park, H W; Kim, H S
2000-01-01
The discrete wavelet transform (DWT) has several advantages of multiresolution analysis and subband decomposition, which has been successfully used in image processing. However, the shift-variant property is intrinsic due to the decimation process of the wavelet transform, and it makes the wavelet-domain motion estimation and compensation inefficient. To overcome the shift-variant property, a low-band-shift method is proposed and a motion estimation and compensation method in the wavelet-domain is presented. The proposed method has a superior performance to the conventional motion estimation methods in terms of the mean absolute difference (MAD) as well as the subjective quality. The proposed method can be a model method for the motion estimation in wavelet-domain just like the full-search block matching in the spatial domain.
A biphasic parameter estimation method for quantitative analysis of dynamic renal scintigraphic data
NASA Astrophysics Data System (ADS)
Koh, T. S.; Zhang, Jeff L.; Ong, C. K.; Shuter, B.
2006-06-01
Dynamic renal scintigraphy is an established method in nuclear medicine, commonly used for the assessment of renal function. In this paper, a biphasic model fitting method is proposed for simultaneous estimation of both vascular and parenchymal parameters from renal scintigraphic data. These parameters include the renal plasma flow, vascular and parenchymal mean transit times, and the glomerular extraction rate. Monte Carlo simulation was used to evaluate the stability and confidence of the parameter estimates obtained by the proposed biphasic method, before applying the method on actual patient study cases to compare with the conventional fitting approach and other established renal indices. The various parameter estimates obtained using the proposed method were found to be consistent with the respective pathologies of the study cases. The renal plasma flow and extraction rate estimated by the proposed method were in good agreement with those previously obtained using dynamic computed tomography and magnetic resonance imaging.
A Comparison of Methods for Estimating Quadratic Effects in Nonlinear Structural Equation Models
Harring, Jeffrey R.; Weiss, Brandi A.; Hsu, Jui-Chen
2012-01-01
Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent moderated structural equation method, (d) a fully Bayesian approach, and (e) marginal maximum likelihood estimation. Of the 5 estimation methods, it was found that overall the methods based on maximum likelihood estimation and the Bayesian approach performed best in terms of bias, root-mean-square error, standard error ratios, power, and Type I error control, although key differences were observed. Similarities as well as disparities among methods are highlight and general recommendations articulated. As a point of comparison, all 5 approaches were fit to a reparameterized version of the latent quadratic model to educational reading data. PMID:22429193
Estimation of brood and nest survival: Comparative methods in the presence of heterogeneity
Manly, Bryan F.J.; Schmutz, Joel A.
2001-01-01
The Mayfield method has been widely used for estimating survival of nests and young animals, especially when data are collected at irregular observation intervals. However, this method assumes survival is constant throughout the study period, which often ignores biologically relevant variation and may lead to biased survival estimates. We examined the bias and accuracy of 1 modification to the Mayfield method that allows for temporal variation in survival, and we developed and similarly tested 2 additional methods. One of these 2 new methods is simply an iterative extension of Klett and Johnson's method, which we refer to as the Iterative Mayfield method and bears similarity to Kaplan-Meier methods. The other method uses maximum likelihood techniques for estimation and is best applied to survival of animals in groups or families, rather than as independent individuals. We also examined how robust these estimators are to heterogeneity in the data, which can arise from such sources as dependent survival probabilities among siblings, inherent differences among families, and adoption. Testing of estimator performance with respect to bias, accuracy, and heterogeneity was done using simulations that mimicked a study of survival of emperor goose (Chen canagica) goslings. Assuming constant survival for inappropriately long periods of time or use of Klett and Johnson's methods resulted in large bias or poor accuracy (often >5% bias or root mean square error) compared to our Iterative Mayfield or maximum likelihood methods. Overall, estimator performance was slightly better with our Iterative Mayfield than our maximum likelihood method, but the maximum likelihood method provides a more rigorous framework for testing covariates and explicity models a heterogeneity factor. We demonstrated use of all estimators with data from emperor goose goslings. We advocate that future studies use the new methods outlined here rather than the traditional Mayfield method or its previous
2007-11-02
BAROREFLEX SENSITIVITY ESTIMATION BY THE TRANSFER FUNCTION METHOD REVISED: EFFECT OF CHANGING THE COHERENCE CRITERION G.D. Pinna1, R. Maestri1, G...In this study we appraised three new criteria for the computation of baroreflex sensitivity (BRS) using the transfer function magnitude (TFM) method... Baroreflex sensitivity , spectral analysis, transfer function I. INTRODUCTION Among the different spectral methods proposed so far for the estimation of
A clinical evaluation of the ability of the Dentobuff method to estimate buffer capacity of saliva.
Wikner, S; Nedlich, U
1985-01-01
The power of a colourimetric method to estimate buffer capacity of saliva (Dentobuff) was compared with an electrometric method in 220 adults. The methods correlated well but Dentobuff frequently underestimated high buffer values which was considered to be of minor practical importance. Dentobuff identified groups with low, intermediate and high buffer capacity as good as the electrometric method.
Modified periodogram method for estimating the Hurst exponent of fractional Gaussian noise.
Liu, Yingjun; Liu, Yong; Wang, Kun; Jiang, Tianzi; Yang, Lihua
2009-12-01
Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) . Many researchers have proposed methods for estimating the Hurst exponent of fGn. In this paper we put forward a modified periodogram method for estimating the Hurst exponent based on a refined approximation of the spectral density function. Generalizing the spectral exponent from a linear function to a piecewise polynomial, we obtained a closer approximation of the fGn's spectral density function. This procedure is significant because it reduced the bias in the estimation of H . Furthermore, the averaging technique that we used markedly reduced the variance of estimates. We also considered the asymptotical unbiasedness of the method and derived the upper bound of its variance and confidence interval. Monte Carlo simulations showed that the proposed estimator was superior to a wavelet maximum likelihood estimator in terms of mean-squared error and was comparable to Whittle's estimator. In addition, a real data set of Nile river minima was employed to evaluate the efficiency of our proposed method. These tests confirmed that our proposed method was computationally simpler and faster than Whittle's estimator.
Evaluating methods for estimating local effective population size with and without migration.
Gilbert, Kimberly J; Whitlock, Michael C
2015-08-01
Effective population size is a fundamental parameter in population genetics, evolutionary biology, and conservation biology, yet its estimation can be fraught with difficulties. Several methods to estimate Ne from genetic data have been developed that take advantage of various approaches for inferring Ne . The ability of these methods to accurately estimate Ne , however, has not been comprehensively examined. In this study, we employ seven of the most cited methods for estimating Ne from genetic data (Colony2, CoNe, Estim, MLNe, ONeSAMP, TMVP, and NeEstimator including LDNe) across simulated datasets with populations experiencing migration or no migration. The simulated population demographies are an isolated population with no immigration, an island model metapopulation with a sink population receiving immigrants, and an isolation by distance stepping stone model of populations. We find considerable variance in performance of these methods, both within and across demographic scenarios, with some methods performing very poorly. The most accurate estimates of Ne can be obtained by using LDNe, MLNe, or TMVP; however each of these approaches is outperformed by another in a differing demographic scenario. Knowledge of the approximate demography of population as well as the availability of temporal data largely improves Ne estimates.
Modified periodogram method for estimating the Hurst exponent of fractional Gaussian noise
NASA Astrophysics Data System (ADS)
Liu, Yingjun; Liu, Yong; Wang, Kun; Jiang, Tianzi; Yang, Lihua
2009-12-01
Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) . Many researchers have proposed methods for estimating the Hurst exponent of fGn. In this paper we put forward a modified periodogram method for estimating the Hurst exponent based on a refined approximation of the spectral density function. Generalizing the spectral exponent from a linear function to a piecewise polynomial, we obtained a closer approximation of the fGn’s spectral density function. This procedure is significant because it reduced the bias in the estimation of H . Furthermore, the averaging technique that we used markedly reduced the variance of estimates. We also considered the asymptotical unbiasedness of the method and derived the upper bound of its variance and confidence interval. Monte Carlo simulations showed that the proposed estimator was superior to a wavelet maximum likelihood estimator in terms of mean-squared error and was comparable to Whittle’s estimator. In addition, a real data set of Nile river minima was employed to evaluate the efficiency of our proposed method. These tests confirmed that our proposed method was computationally simpler and faster than Whittle’s estimator.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
2013-09-17
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
Parameters estimation using the first passage times method in a jump-diffusion model
NASA Astrophysics Data System (ADS)
Khaldi, K.; Meddahi, S.
2016-06-01
The main purposes of this paper are two contributions: (1) it presents a new method, which is the first passage time (FPT method) generalized for all passage times (GPT method), in order to estimate the parameters of stochastic Jump-Diffusion process. (2) it compares in a time series model, share price of gold, the empirical results of the estimation and forecasts obtained with the GPT method and those obtained by the moments method and the FPT method applied to the Merton Jump-Diffusion (MJD) model.
NASA Astrophysics Data System (ADS)
Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod
2007-11-01
Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramér-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.
Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod
2007-11-20
Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramer-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.
Inter-Method Discrepancies in Brain Volume Estimation May Drive Inconsistent Findings in Autism
Katuwal, Gajendra J.; Baum, Stefi A.; Cahill, Nathan D.; Dougherty, Chase C.; Evans, Eli; Evans, David W.; Moore, Gregory J.; Michael, Andrew M.
2016-01-01
Previous studies applying automatic preprocessing methods on Structural Magnetic Resonance Imaging (sMRI) report inconsistent neuroanatomical abnormalities in Autism Spectrum Disorder (ASD). In this study we investigate inter-method differences as a possible cause behind these inconsistent findings. In particular, we focus on the estimation of the following brain volumes: gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and total intra cranial volume (TIV). T1-weighted sMRIs of 417 ASD subjects and 459 typically developing controls (TDC) from the ABIDE dataset were estimated using three popular preprocessing methods: SPM, FSL, and FreeSurfer (FS). Brain volumes estimated by the three methods were correlated but had significant inter-method differences; except TIVSPM vs. TIVFS, all inter-method differences were significant. ASD vs. TDC group differences in all brain volume estimates were dependent on the method used. SPM showed that TIV, GM, and CSF volumes of ASD were larger than TDC with statistical significance, whereas FS and FSL did not show significant differences in any of the volumes; in some cases, the direction of the differences were opposite to SPM. When methods were compared with each other, they showed differential biases for autism, and several biases were larger than ASD vs. TDC differences of the respective methods. After manual inspection, we found inter-method segmentation mismatches in the cerebellum, sub-cortical structures, and inter-sulcal CSF. In addition, to validate automated TIV estimates we performed manual segmentation on a subset of subjects. Results indicate that SPM estimates are closest to manual segmentation, followed by FS while FSL estimates were significantly lower. In summary, we show that ASD vs. TDC brain volume differences are method dependent and that these inter-method discrepancies can contribute to inconsistent neuroimaging findings in general. We suggest cross-validation across methods and emphasize the
Inter-Method Discrepancies in Brain Volume Estimation May Drive Inconsistent Findings in Autism.
Katuwal, Gajendra J; Baum, Stefi A; Cahill, Nathan D; Dougherty, Chase C; Evans, Eli; Evans, David W; Moore, Gregory J; Michael, Andrew M
2016-01-01
Previous studies applying automatic preprocessing methods on Structural Magnetic Resonance Imaging (sMRI) report inconsistent neuroanatomical abnormalities in Autism Spectrum Disorder (ASD). In this study we investigate inter-method differences as a possible cause behind these inconsistent findings. In particular, we focus on the estimation of the following brain volumes: gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and total intra cranial volume (TIV). T1-weighted sMRIs of 417 ASD subjects and 459 typically developing controls (TDC) from the ABIDE dataset were estimated using three popular preprocessing methods: SPM, FSL, and FreeSurfer (FS). Brain volumes estimated by the three methods were correlated but had significant inter-method differences; except TIVSPM vs. TIVFS, all inter-method differences were significant. ASD vs. TDC group differences in all brain volume estimates were dependent on the method used. SPM showed that TIV, GM, and CSF volumes of ASD were larger than TDC with statistical significance, whereas FS and FSL did not show significant differences in any of the volumes; in some cases, the direction of the differences were opposite to SPM. When methods were compared with each other, they showed differential biases for autism, and several biases were larger than ASD vs. TDC differences of the respective methods. After manual inspection, we found inter-method segmentation mismatches in the cerebellum, sub-cortical structures, and inter-sulcal CSF. In addition, to validate automated TIV estimates we performed manual segmentation on a subset of subjects. Results indicate that SPM estimates are closest to manual segmentation, followed by FS while FSL estimates were significantly lower. In summary, we show that ASD vs. TDC brain volume differences are method dependent and that these inter-method discrepancies can contribute to inconsistent neuroimaging findings in general. We suggest cross-validation across methods and emphasize the
NASA Technical Reports Server (NTRS)
Campbell, John P; Mckinney, Marion O
1952-01-01
A summary of methods for making dynamic lateral stability and response calculations and for estimating the aerodynamic stability derivatives required for use in these calculations is presented. The processes of performing calculations of the time histories of lateral motions, of the period and damping of these motions, and of the lateral stability boundaries are presented as a series of simple straightforward steps. Existing methods for estimating the stability derivatives are summarized and, in some cases, simple new empirical formulas are presented. Detailed estimation methods are presented for low-subsonic-speed conditions but only a brief discussion and a list of references are given for transonic and supersonic speed conditions.
A New Formulation of the Filter-Error Method for Aerodynamic Parameter Estimation in Turbulence
NASA Technical Reports Server (NTRS)
Grauer, Jared A.; Morelli, Eugene A.
2015-01-01
A new formulation of the filter-error method for estimating aerodynamic parameters in nonlinear aircraft dynamic models during turbulence was developed and demonstrated. The approach uses an estimate of the measurement noise covariance to identify the model parameters, their uncertainties, and the process noise covariance, in a relaxation method analogous to the output-error method. Prior information on the model parameters and uncertainties can be supplied, and a post-estimation correction to the uncertainty was included to account for colored residuals not considered in the theory. No tuning parameters, needing adjustment by the analyst, are used in the estimation. The method was demonstrated in simulation using the NASA Generic Transport Model, then applied to the subscale T-2 jet-engine transport aircraft flight. Modeling results in different levels of turbulence were compared with results from time-domain output error and frequency- domain equation error methods to demonstrate the effectiveness of the approach.
Ye, Jingfei; Wang, Wei; Gao, Zhishan; Liu, Zhiying; Wang, Shuai; Benítez, Pablo; Miñano, Juan C; Yuan, Qun
2015-10-05
Wavefront estimation from the slope-based sensing metrologies zis important in modern optical testing. A numerical orthogonal transformation method is proposed for deriving the numerical orthogonal gradient polynomials as numerical orthogonal basis functions for directly fitting the measured slope data and then converting to the wavefront in a straightforward way in the modal approach. The presented method can be employed in the wavefront estimation from its slopes over the general shaped aperture. Moreover, the numerical orthogonal transformation method could be applied to the wavefront estimation from its slope measurements over the dynamic varying aperture. The performance of the numerical orthogonal transformation method is discussed, demonstrated and verified by the examples. They indicate that the presented method is valid, accurate and easily implemented for wavefront estimation from its slopes.
Simplified Estimating Method for Shock Response Spectrum Envelope of V-Band Clamp Separation Shock
NASA Astrophysics Data System (ADS)
Iwasa, Takashi; Shi, Qinzhong
A simplified estimating method for the Shock Response Spectrum (SRS) envelope at the spacecraft interface near the V-band clamp separation device has been established. This simplified method is based on the pyroshock analysis method with a single degree of freedom (D.O.F) model proposed in our previous paper. The parameters required in the estimating method are only geometrical information of the interface and a tension of the V-band clamp. According to the use of these parameters, a simplified calculation of the SRS magnitude at the knee frequency is newly proposed. By comparing the estimation results with actual pyroshock test results, it was verified that the SRS envelope estimated with the simplified method appropriately covered the pyroshock test data of the actual space satellite systems except some specific high frequency responses.
Estimating of equilibrium formation temperature by curve fitting method and it's problems
Kenso Takai; Masami Hyodo; Shinji Takasugi
1994-01-20
Determination of true formation temperature from measured bottom hole temperature is important for geothermal reservoir evaluation after completion of well drilling. For estimation of equilibrium formation temperature, we studied non-linear least squares fitting method adapting the Middleton Model (Chiba et al., 1988). It was pointed out that this method was applicable as simple and relatively reliable method for estimation of the equilibrium formation temperature after drilling. As a next step, we are studying the estimation of equilibrium formation temperature from bottom hole temperature data measured by MWD (measurement while drilling system). In this study, we have evaluated availability of nonlinear least squares fitting method adapting curve fitting method and the numerical simulator (GEOTEMP2) for estimation of the equilibrium formation temperature while drilling.
Khorate, Manisha M; Dinkar, A D; Ahmed, Junaid
2014-01-01
Changes related to chronological age are seen in both hard and soft tissue. A number of methods for age estimation have been proposed which can be classified in four categories, namely, clinical, radiological, histological and chemical analysis. In forensic odontology, age estimation based on tooth development is universally accepted method. The panoramic radiographs of 500 healthy Goan, Indian children (250 boys and 250 girls) aged between 4 and 22.1 years were selected. Modified Demirjian's method (1973/2004), Acharya AB formula (2011), Dr Ajit D. Dinkar (1984) regression equation, Foti and coworkers (2003) formula (clinical and radiological) were applied for estimation of age. The result of our study has shown that Dr Ajit D. Dinkar method is more accurate followed by Acharya Indian-specific formula. Furthermore, in this study by applying all these methods to one regional population, we have attempted to present dental age estimation methodology best suited for the Goan Indian population.
NASA Astrophysics Data System (ADS)
Deshler, Terry
2016-04-01
Balloon-borne optical particle counters were used to make in situ size resolved particle concentration measurements within polar stratospheric clouds (PSCs) over 20 years in the Antarctic and over 10 years in the Arctic. The measurements were made primarily during the late winter in the Antarctic and in the early and mid-winter in the Arctic. Measurements in early and mid-winter were also made during 5 years in the Antarctic. For the analysis bimodal lognormal size distributions are fit to 250 meter averages of the particle concentration data. The characteristics of these fits, along with temperature, water and nitric acid vapor mixing ratios, are used to classify the PSC observations as either NAT, STS, ice, or some mixture of these. The vapor mixing ratios are obtained from satellite when possible, otherwise assumptions are made. This classification of the data is used to construct probability density functions for NAT, STS, and ice number concentration, median radius and distribution width for mid and late winter clouds in the Antarctic and for early and mid-winter clouds in the Arctic. Additional analysis is focused on characterizing the temperature histories associated with the particle classes and the different time periods. The results from theses analyses will be presented, and should be useful to set bounds for retrievals of PSC properties from remote measurements, and to constrain model representations of PSCs.
Fast 2D DOA Estimation Algorithm by an Array Manifold Matching Method with Parallel Linear Arrays
Yang, Lisheng; Liu, Sheng; Li, Dong; Jiang, Qingping; Cao, Hailin
2016-01-01
In this paper, the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation with parallel linear arrays is addressed. Two array manifold matching (AMM) approaches, in this work, are developed for the incoherent and coherent signals, respectively. The proposed AMM methods estimate the azimuth angle only with the assumption that the elevation angles are known or estimated. The proposed methods are time efficient since they do not require eigenvalue decomposition (EVD) or peak searching. In addition, the complexity analysis shows the proposed AMM approaches have lower computational complexity than many current state-of-the-art algorithms. The estimated azimuth angles produced by the AMM approaches are automatically paired with the elevation angles. More importantly, for estimating the azimuth angles of coherent signals, the aperture loss issue is avoided since a decorrelation procedure is not required for the proposed AMM method. Numerical studies demonstrate the effectiveness of the proposed approaches. PMID:26907301
Spacecraft Attitude Estimation Integrating the Q-Method into an Extended Kalman Filter
NASA Astrophysics Data System (ADS)
Ainscough, Thomas G.
A new algorithm is proposed that smoothly integrates the nonlinear estimation of the attitude quaternion using Davenport's q-method and the estimation of non-attitude states within the framework of an extended Kalman filter. A modification to the q-method and associated covariance analysis is derived with the inclusion of an a priori attitude estimate. The non-attitude states are updated from the nonlinear attitude estimate based on linear optimal Kalman filter techniques. The proposed filter is compared to existing methods and is shown to be equivalent to second-order in the attitude update and exactly equivalent in the non-attitude state update with the Sequential Optimal Attitude Recursion filter. Monte Carlo analysis is used in numerical simulations to demonstrate the validity of the proposed approach. This filter successfully estimates the nonlinear attitude and non-attitude states in a single Kalman filter without the need for iterations.
Orlowska-Kowalska, Teresa; Kaminski, Marcin
2014-01-01
The paper deals with the implementation of optimized neural networks (NNs) for state variable estimation of the drive system with an elastic joint. The signals estimated by NNs are used in the control structure with a state-space controller and additional feedbacks from the shaft torque and the load speed. High estimation quality is very important for the correct operation of a closed-loop system. The precision of state variables estimation depends on the generalization properties of NNs. A short review of optimization methods of the NN is presented. Two techniques typical for regularization and pruning methods are described and tested in detail: the Bayesian regularization and the Optimal Brain Damage methods. Simulation results show good precision of both optimized neural estimators for a wide range of changes of the load speed and the load torque, not only for nominal but also changed parameters of the drive system. The simulation results are verified in a laboratory setup.
Improved method for estimating water solubility from octanol/water partition coefficient
Meylan, W.; Howard, P.; Boethling, R.
1994-12-31
Water solubility (wsol) is a critical property in risk assessments for chemicals. It is often necessary to estimate wsol because measured values are unavailable. However, the most widely used estimation methods predict wsol from the logarithm of the octanol/water partition coefficient (log K{sub ow}), via regression equations based on approximately 200 (or fewer) measured values of log K{sub ow}. The overall accuracy of these correlations is only about {+-} one order of magnitude. To update and enhance existing wsol estimation methods, the authors first collected 3,000+ measured values from a variety of sources. The range of chemical structures represented by this data set is much greater than for the older regressions. They then investigated the accuracy of wsol/log K{sub ow} correlations for the entire data set and for various chemical classes, as well as the importance of melting point (mp) to the estimate. The results of this investigation include a new regression equation for estimating wsol. This method has been encoded in a computer program that is compatible with other programs in the Estimation Programs Interface (EPI), a program used by OPPT to estimate key properties and fate parameters for existing and Premanufacture Notice (PMN) chemicals. To estimate wsol the user can enter a measured value of log K{sub ow}, or allow the program to estimate log K{sub ow} from the chemical`s SMILES notation.
NASA Astrophysics Data System (ADS)
Zhao, Fangfang; Zhang, Lu; Xu, Zongxue; Scott, David F.
2010-03-01
Changes in vegetation cover can significantly affect streamflow. Two common methods for estimating vegetation effects on streamflow are the paired catchment method and the time trend analysis technique. In this study, the performance of these methods is evaluated using data from paired catchments in Australia, New Zealand, and South Africa. Results show that these methods generally yield consistent estimates of the vegetation effect, and most of the observed streamflow changes are attributable to vegetation change. These estimates are realistic and are supported by the vegetation history. The accuracy of the estimates, however, largely depends on the length of calibration periods or pretreatment periods. For catchments with short or no pretreatment periods, we find that statistically identified prechange periods can be used as calibration periods. Because streamflow also responds to climate variability, in assessing streamflow changes it is necessary to consider the effect of climate in addition to the effect of vegetation. Here, the climate effect on streamflow was estimated using a sensitivity-based method that calculates changes in rainfall and potential evaporation. A unifying conceptual framework, based on the assumption that climate and vegetation are the only drivers for streamflow changes, enables comparison of all three methods. It is shown that these methods provide consistent estimates of vegetation and climate effects on streamflow for the catchments considered. An advantage of the time trend analysis and sensitivity-based methods is that they are applicable to nonpaired catchments, making them potentially useful in large catchments undergoing vegetation change.
Ball, J.R.; Cohen, S.; Ziegler, E.Z.
1984-10-01
This document provides overall guidance to assist the NRC in preparing the types of cost estimates required by the Regulatory Analysis Guidelines and to assist in the assignment of priorities in resolving generic safety issues. The Handbook presents an overall cost model that allows the cost analyst to develop a chronological series of activities needed to implement a specific regulatory requirement throughout all applicable commercial LWR power plants and to identify the significant cost elements for each activity. References to available cost data are provided along with rules of thumb and cost factors to assist in evaluating each cost element. A suitable code-of-accounts data base is presented to assist in organizing and aggregating costs. Rudimentary cost analysis methods are described to allow the analyst to produce a constant-dollar, lifetime cost for the requirement. A step-by-step example cost estimate is included to demonstrate the overall use of the Handbook.
A New Method for Radar Rainfall Estimation Using Merged Radar and Gauge Derived Fields
NASA Astrophysics Data System (ADS)
Hasan, M. M.; Sharma, A.; Johnson, F.; Mariethoz, G.; Seed, A.
2014-12-01
Accurate estimation of rainfall is critical for any hydrological analysis. The advantage of radar rainfall measurements is their ability to cover large areas. However, the uncertainties in the parameters of the power law, that links reflectivity to rainfall intensity, have to date precluded the widespread use of radars for quantitative rainfall estimates for hydrological studies. There is therefore considerable interest in methods that can combine the strengths of radar and gauge measurements by merging the two data sources. In this work, we propose two new developments to advance this area of research. The first contribution is a non-parametric radar rainfall estimation method (NPZR) which is based on kernel density estimation. Instead of using a traditional Z-R relationship, the NPZR accounts for the uncertainty in the relationship between reflectivity and rainfall intensity. More importantly, this uncertainty can vary for different values of reflectivity. The NPZR method reduces the Mean Square Error (MSE) of the estimated rainfall by 16 % compared to a traditionally fitted Z-R relation. Rainfall estimates are improved at 90% of the gauge locations when the method is applied to the densely gauged Sydney Terrey Hills radar region. A copula based spatial interpolation method (SIR) is used to estimate rainfall from gauge observations at the radar pixel locations. The gauge-based SIR estimates have low uncertainty in areas with good gauge density, whilst the NPZR method provides more reliable rainfall estimates than the SIR method, particularly in the areas of low gauge density. The second contribution of the work is to merge the radar rainfall field with spatially interpolated gauge rainfall estimates. The two rainfall fields are combined using a temporally and spatially varying weighting scheme that can account for the strengths of each method. The weight for each time period at each location is calculated based on the expected estimation error of each method
Methods to Estimate the Between-Study Variance and Its Uncertainty in Meta-Analysis
ERIC Educational Resources Information Center
Veroniki, Areti Angeliki; Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian P. T.; Langan, Dean; Salanti, Georgia
2016-01-01
Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance,…
Technology Transfer Automated Retrieval System (TEKTRAN)
The effects of bias (over and underestimates) in estimates of disease severity on hypothesis testing using different assessment methods was explored. Nearest percent estimates (NPE), the Horsfall-Barratt (H-B) scale, and two different linear category scales (10% increments, with and without addition...
One of the objectives of the National Human Exposure Assessment Survey (NHEXAS) is to estimate exposures to several pollutants in multiple media and determine their distributions for the population of Arizona. This paper presents modeling methods used to estimate exposure dist...
ERIC Educational Resources Information Center
Bauer, Daniel J.; Sterba, Sonya K.
2011-01-01
Previous research has compared methods of estimation for fitting multilevel models to binary data, but there are reasons to believe that the results will not always generalize to the ordinal case. This article thus evaluates (a) whether and when fitting multilevel linear models to ordinal outcome data is justified and (b) which estimator to employ…