Optical losses due to tracking error estimation for a low concentrating solar collector
International Nuclear Information System (INIS)
Sallaberry, Fabienne; García de Jalón, Alberto; Torres, José-Luis; Pujol-Nadal, Ramón
2015-01-01
Highlights: • A solar thermal collector with low concentration and one-axis tracking was tested. • A quasi-dynamic testing procedure for IAM was defined for tracking collector. • The adequation between the concentrator optics and the tracking was checked. • The maximum and long-term optical losses due to tracking error were calculated. - Abstract: The determination of the accuracy of a solar tracker used in domestic hot water solar collectors is not yet standardized. However, while using optical concentration devices, it is important to use a solar tracker with adequate precision with regard to the specific optical concentration factor. Otherwise, the concentrator would sustain high optical losses due to the inadequate focusing of the solar radiation onto its receiver, despite having a good quality. This study is focused on the estimation of long-term optical losses due to the tracking error of a low-temperature collector using low-concentration optics. For this purpose, a testing procedure for the incidence angle modifier on the tracking plane is proposed to determinate the acceptance angle of its concentrator even with different longitudinal incidence angles along the focal line plane. Then, the impact of maximum tracking error angle upon the optical efficiency has been determined. Finally, the calculation of the long-term optical error due to the tracking errors, using the design angular tracking error declared by the manufacturer, is carried out. The maximum tracking error calculated for this collector imply an optical loss of about 8.5%, which is high, but the average long-term optical loss calculated for one year was about 1%, which is reasonable for such collectors used for domestic hot water
Estimation of perspective errors in 2D2C-PIV measurements for 3D concentrated vortices
Ma, Bao-Feng; Jiang, Hong-Gang
2018-06-01
Two-dimensional planar PIV (2D2C) is still extensively employed in flow measurement owing to its availability and reliability, although more advanced PIVs have been developed. It has long been recognized that there exist perspective errors in velocity fields when employing the 2D2C PIV to measure three-dimensional (3D) flows, the magnitude of which depends on out-of-plane velocity and geometric layouts of the PIV. For a variety of vortex flows, however, the results are commonly represented by vorticity fields, instead of velocity fields. The present study indicates that the perspective error in vorticity fields relies on gradients of the out-of-plane velocity along a measurement plane, instead of the out-of-plane velocity itself. More importantly, an estimation approach to the perspective error in 3D vortex measurements was proposed based on a theoretical vortex model and an analysis on physical characteristics of the vortices, in which the gradient of out-of-plane velocity is uniquely determined by the ratio of the maximum out-of-plane velocity to maximum swirling velocity of the vortex; meanwhile, the ratio has upper limits for naturally formed vortices. Therefore, if the ratio is imposed with the upper limits, the perspective error will only rely on the geometric layouts of PIV that are known in practical measurements. Using this approach, the upper limits of perspective errors of a concentrated vortex can be estimated for vorticity and other characteristic quantities of the vortex. In addition, the study indicates that the perspective errors in vortex location, vortex strength, and vortex radius can be all zero for axisymmetric vortices if they are calculated by proper methods. The dynamic mode decomposition on an oscillatory vortex indicates that the perspective errors of each DMD mode are also only dependent on the gradient of out-of-plane velocity if the modes are represented by vorticity.
Error exponents for entanglement concentration
International Nuclear Information System (INIS)
Hayashi, Masahito; Koashi, Masato; Matsumoto, Keiji; Morikoshi, Fumiaki; Winter, Andreas
2003-01-01
Consider entanglement concentration schemes that convert n identical copies of a pure state into a maximally entangled state of a desired size with success probability being close to one in the asymptotic limit. We give the distillable entanglement, the number of Bell pairs distilled per copy, as a function of an error exponent, which represents the rate of decrease in failure probability as n tends to infinity. The formula fills the gap between the least upper bound of distillable entanglement in probabilistic concentration, which is the well-known entropy of entanglement, and the maximum attained in deterministic concentration. The method of types in information theory enables the detailed analysis of the distillable entanglement in terms of the error rate. In addition to the probabilistic argument, we consider another type of entanglement concentration scheme, where the initial state is deterministically transformed into a (possibly mixed) final state whose fidelity to a maximally entangled state of a desired size converges to one in the asymptotic limit. We show that the same formula as in the probabilistic argument is valid for the argument on fidelity by replacing the success probability with the fidelity. Furthermore, we also discuss entanglement yield when optimal success probability or optimal fidelity converges to zero in the asymptotic limit (strong converse), and give the explicit formulae for those cases
International Nuclear Information System (INIS)
Gilbert, R.O.; Baker, K.R.; Nelson, R.A.; Miller, R.H.; Miller, M.L.
1987-07-01
The decision whether to take additional remedial action (removal of soil) from regions contaminated by uranium mill tailings involves collecting 20 plugs of soil from each 10-m by 10-m plot in the region and analyzing a 500-g portion of the mixed soil for 226 Ra. A soil sampling study was conducted in the windblown mill-tailings flood plain area at Shiprock, New Mexico, to evaluate whether reducing the number of soil plugs to 9 would have any appreciable impact on remedial-action decisions. The results of the Shiprock study are described and used in this paper to develop a simple model of the standard deviation of 226 Ra measurements on composite samples formed from 21 or fewer plugs. This model is used to predict as a function of the number of soil plugs per composite, the percent accuracy with which the mean 226 Ra concentration in surface soil can be estimated, and the probability of making incorrect remedial action decisions on the basis of statistical tests. 8 refs., 15 figs., 9 tabs
Clock error models for simulation and estimation
International Nuclear Information System (INIS)
Meditch, J.S.
1981-10-01
Mathematical models for the simulation and estimation of errors in precision oscillators used as time references in satellite navigation systems are developed. The results, based on all currently known oscillator error sources, are directly implementable on a digital computer. The simulation formulation is sufficiently flexible to allow for the inclusion or exclusion of individual error sources as desired. The estimation algorithms, following from Kalman filter theory, provide directly for the error analysis of clock errors in both filtering and prediction
Error Covariance Estimation of Mesoscale Data Assimilation
National Research Council Canada - National Science Library
Xu, Qin
2005-01-01
The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...
Estimation of Total Error in DWPF Reported Radionuclide Inventories
International Nuclear Information System (INIS)
Edwards, T.B.
1995-01-01
This report investigates the impact of random errors due to measurement and sampling on the reported concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch. The objective of this investigation is to estimate the variance of the total error in reporting these radionuclide concentrations
Statistical errors in Monte Carlo estimates of systematic errors
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k2. The specific terms unisim and multisim were coined by Peter Meyers and Steve Brice, respectively, for the MiniBooNE experiment. However, the concepts have been developed over time and have been in general use for some time.
Statistical errors in Monte Carlo estimates of systematic errors
Energy Technology Data Exchange (ETDEWEB)
Roe, Byron P. [Department of Physics, University of Michigan, Ann Arbor, MI 48109 (United States)]. E-mail: byronroe@umich.edu
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k{sup 2}.
Statistical errors in Monte Carlo estimates of systematic errors
International Nuclear Information System (INIS)
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k 2
Wind power error estimation in resource assessments.
Directory of Open Access Journals (Sweden)
Osvaldo Rodríguez
Full Text Available 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.
Error estimation and adaptivity for incompressible hyperelasticity
Whiteley, J.P.
2014-04-30
SUMMARY: A Galerkin FEM is developed for nonlinear, incompressible (hyper) elasticity that takes account of nonlinearities in both the strain tensor and the relationship between the strain tensor and the stress tensor. By using suitably defined linearised dual problems with appropriate boundary conditions, a posteriori error estimates are then derived for both linear functionals of the solution and linear functionals of the stress on a boundary, where Dirichlet boundary conditions are applied. A second, higher order method for calculating a linear functional of the stress on a Dirichlet boundary is also presented together with an a posteriori error estimator for this approach. An implementation for a 2D model problem with known solution, where the entries of the strain tensor exhibit large, rapid variations, demonstrates the accuracy and sharpness of the error estimators. Finally, using a selection of model problems, the a posteriori error estimate is shown to provide a basis for effective mesh adaptivity. © 2014 John Wiley & Sons, Ltd.
Error estimation in plant growth analysis
Directory of Open Access Journals (Sweden)
Andrzej Gregorczyk
2014-01-01
Full Text Available The scheme is presented for calculation of errors of dry matter values which occur during approximation of data with growth curves, determined by the analytical method (logistic function and by the numerical method (Richards function. Further formulae are shown, which describe absolute errors of growth characteristics: Growth rate (GR, Relative growth rate (RGR, Unit leaf rate (ULR and Leaf area ratio (LAR. Calculation examples concerning the growth course of oats and maize plants are given. The critical analysis of the estimation of obtained results has been done. The purposefulness of joint application of statistical methods and error calculus in plant growth analysis has been ascertained.
KMRR thermal power measurement error estimation
International Nuclear Information System (INIS)
Rhee, B.W.; Sim, B.S.; Lim, I.C.; Oh, S.K.
1990-01-01
The thermal power measurement error of the Korea Multi-purpose Research Reactor has been estimated by a statistical Monte Carlo method, and compared with those obtained by the other methods including deterministic and statistical approaches. The results show that the specified thermal power measurement error of 5% cannot be achieved if the commercial RTDs are used to measure the coolant temperatures of the secondary cooling system and the error can be reduced below the requirement if the commercial RTDs are replaced by the precision RTDs. The possible range of the thermal power control operation has been identified to be from 100% to 20% of full power
Error estimation for variational nodal calculations
International Nuclear Information System (INIS)
Zhang, H.; Lewis, E.E.
1998-01-01
Adaptive grid methods are widely employed in finite element solutions to both solid and fluid mechanics problems. Either the size of the element is reduced (h refinement) or the order of the trial function is increased (p refinement) locally to improve the accuracy of the solution without a commensurate increase in computational effort. Success of these methods requires effective local error estimates to determine those parts of the problem domain where the solution should be refined. Adaptive methods have recently been applied to the spatial variables of the discrete ordinates equations. As a first step in the development of adaptive methods that are compatible with the variational nodal method, the authors examine error estimates for use in conjunction with spatial variables. The variational nodal method lends itself well to p refinement because the space-angle trial functions are hierarchical. Here they examine an error estimator for use with spatial p refinement for the diffusion approximation. Eventually, angular refinement will also be considered using spherical harmonics approximations
Feng, S.; Lauvaux, T.; Butler, M. P.; Keller, K.; Davis, K. J.; Jacobson, A. R.; Schuh, A. E.; Basu, S.; Liu, J.; Baker, D.; Crowell, S.; Zhou, Y.; Williams, C. A.
2017-12-01
Regional estimates of biogenic carbon fluxes over North America from top-down atmospheric inversions and terrestrial biogeochemical (or bottom-up) models remain inconsistent at annual and sub-annual time scales. While top-down estimates are impacted by limited atmospheric data, uncertain prior flux estimates and errors in the atmospheric transport models, bottom-up fluxes are affected by uncertain driver data, uncertain model parameters and missing mechanisms across ecosystems. This study quantifies both flux errors and transport errors, and their interaction in the CO2 atmospheric simulation. These errors are assessed by an ensemble approach. The WRF-Chem model is set up with 17 biospheric fluxes from the Multiscale Synthesis and Terrestrial Model Intercomparison Project, CarbonTracker-Near Real Time, and the Simple Biosphere model. The spread of the flux ensemble members represents the flux uncertainty in the modeled CO2 concentrations. For the transport errors, WRF-Chem is run using three physical model configurations with three stochastic perturbations to sample the errors from both the physical parameterizations of the model and the initial conditions. Additionally, the uncertainties from boundary conditions are assessed using four CO2 global inversion models which have assimilated tower and satellite CO2 observations. The error structures are assessed in time and space. The flux ensemble members overall overestimate CO2 concentrations. They also show larger temporal variability than the observations. These results suggest that the flux ensemble is overdispersive. In contrast, the transport ensemble is underdispersive. The averaged spatial distribution of modeled CO2 shows strong positive biogenic signal in the southern US and strong negative signals along the eastern coast of Canada. We hypothesize that the former is caused by the 3-hourly downscaling algorithm from which the nighttime respiration dominates the daytime modeled CO2 signals and that the latter
Huo, Ming-Xia; Li, Ying
2017-12-01
Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.
Radiation risk estimation based on measurement error models
Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya
2017-01-01
This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.
Parts of the Whole: Error Estimation for Science Students
Directory of Open Access Journals (Sweden)
Dorothy Wallace
2017-01-01
Full Text Available It is important for science students to understand not only how to estimate error sizes in measurement data, but also to see how these errors contribute to errors in conclusions they may make about the data. Relatively small errors in measurement, errors in assumptions, and roundoff errors in computation may result in large error bounds on computed quantities of interest. In this column, we look closely at a standard method for measuring the volume of cancer tumor xenografts to see how small errors in each of these three factors may contribute to relatively large observed errors in recorded tumor volumes.
Estimation error algorithm at analysis of beta-spectra
International Nuclear Information System (INIS)
Bakovets, N.V.; Zhukovskij, A.I.; Zubarev, V.N.; Khadzhinov, E.M.
2005-01-01
This work describes the estimation error algorithm at the operations with beta-spectrums, as well as compares the theoretical and experimental errors by the processing of beta-channel's data. (authors)
Comparing computing formulas for estimating concentration ratios
International Nuclear Information System (INIS)
Gilbert, R.O.; Simpson, J.C.
1984-03-01
This paper provides guidance on the choice of computing formulas (estimators) for estimating concentration ratios and other ratio-type measures of radionuclides and other environmental contaminant transfers between ecosystem components. Mathematical expressions for the expected value of three commonly used estimators (arithmetic mean of ratios, geometric mean of ratios, and the ratio of means) are obtained when the multivariate lognormal distribution is assumed. These expressions are used to explain why these estimators will not in general give the same estimate of the average concentration ratio. They illustrate that the magnitude of the discrepancies depends on the magnitude of measurement biases, and on the variances and correlations associated with spatial heterogeneity and measurement errors. This paper also reports on a computer simulation study that compares the accuracy of eight computing formulas for estimating a ratio relationship that is constant over time and/or space. Statistical models appropriate for both controlled spiking experiments and observational field studies for either normal or lognormal distributions are considered. 24 references, 15 figures, 7 tables
Stochastic goal-oriented error estimation with memory
Ackmann, Jan; Marotzke, Jochem; Korn, Peter
2017-11-01
We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.
Data error effects on net radiation and evapotranspiration estimation
International Nuclear Information System (INIS)
Llasat, M.C.; Snyder, R.L.
1998-01-01
The objective of this paper is to evaluate the potential error in estimating the net radiation and reference evapotranspiration resulting from errors in the measurement or estimation of weather parameters. A methodology for estimating the net radiation using hourly weather variables measured at a typical agrometeorological station (e.g., solar radiation, temperature and relative humidity) is presented. Then the error propagation analysis is made for net radiation and for reference evapotranspiration. Data from the Raimat weather station, which is located in the Catalonia region of Spain, are used to illustrate the error relationships. The results show that temperature, relative humidity and cloud cover errors have little effect on the net radiation or reference evapotranspiration. A 5°C error in estimating surface temperature leads to errors as big as 30 W m −2 at high temperature. A 4% solar radiation (R s ) error can cause a net radiation error as big as 26 W m −2 when R s ≈ 1000 W m −2 . However, the error is less when cloud cover is calculated as a function of the solar radiation. The absolute error in reference evapotranspiration (ET o ) equals the product of the net radiation error and the radiation term weighting factor [W = Δ(Δ1+γ)] in the ET o equation. Therefore, the ET o error varies between 65 and 85% of the R n error as air temperature increases from about 20° to 40°C. (author)
Error Estimation in Preconditioned Conjugate Gradients
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2005-01-01
Roč. 45, - (2005), s. 789-817 ISSN 0006-3835 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB1030306 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned conjugate gradient method * error bounds * stopping criteria * evaluation of convergence * numerical stability * finite precision arithmetic * rounding errors Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2005
Fisher classifier and its probability of error estimation
Chittineni, C. B.
1979-01-01
Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.
Effects of exposure estimation errors on estimated exposure-response relations for PM2.5.
Cox, Louis Anthony Tony
2018-07-01
Associations between fine particulate matter (PM2.5) exposure concentrations and a wide variety of undesirable outcomes, from autism and auto theft to elderly mortality, suicide, and violent crime, have been widely reported. Influential articles have argued that reducing National Ambient Air Quality Standards for PM2.5 is desirable to reduce these outcomes. Yet, other studies have found that reducing black smoke and other particulate matter by as much as 70% and dozens of micrograms per cubic meter has not detectably affected all-cause mortality rates even after decades, despite strong, statistically significant positive exposure concentration-response (C-R) associations between them. This paper examines whether this disconnect between association and causation might be explained in part by ignored estimation errors in estimated exposure concentrations. We use EPA air quality monitor data from the Los Angeles area of California to examine the shapes of estimated C-R functions for PM2.5 when the true C-R functions are assumed to be step functions with well-defined response thresholds. The estimated C-R functions mistakenly show risk as smoothly increasing with concentrations even well below the response thresholds, thus incorrectly predicting substantial risk reductions from reductions in concentrations that do not affect health risks. We conclude that ignored estimation errors obscure the shapes of true C-R functions, including possible thresholds, possibly leading to unrealistic predictions of the changes in risk caused by changing exposures. Instead of estimating improvements in public health per unit reduction (e.g., per 10 µg/m 3 decrease) in average PM2.5 concentrations, it may be essential to consider how interventions change the distributions of exposure concentrations. Copyright © 2018 Elsevier Inc. All rights reserved.
Estimating soil zinc concentrations using reflectance spectroscopy
Sun, Weichao; Zhang, Xia
2017-06-01
Soil contamination by heavy metals has been an increasingly severe threat to nature environment and human health. Efficiently investigation of contamination status is essential to soil protection and remediation. Visible and near-infrared reflectance spectroscopy (VNIRS) has been regarded as an alternative for monitoring soil contamination by heavy metals. Generally, the entire VNIR spectral bands are employed to estimate heavy metal concentration, which lacks interpretability and requires much calculation. In this study, 74 soil samples were collected from Hunan Province, China and their reflectance spectra were used to estimate zinc (Zn) concentration in soil. Organic matter and clay minerals have strong adsorption for Zn in soil. Spectral bands associated with organic matter and clay minerals were used for estimation with genetic algorithm based partial least square regression (GA-PLSR). The entire VNIR spectral bands, the bands associated with organic matter and the bands associated with clay minerals were incorporated as comparisons. Root mean square error of prediction, residual prediction deviation, and coefficient of determination (R2) for the model developed using combined bands of organic matter and clay minerals were 329.65 mg kg-1, 1.96 and 0.73, which is better than 341.88 mg kg-1, 1.89 and 0.71 for the entire VNIR spectral bands, 492.65 mg kg-1, 1.31 and 0.40 for the organic matter, and 430.26 mg kg-1, 1.50 and 0.54 for the clay minerals. Additionally, in consideration of atmospheric water vapor absorption in field spectra measurement, combined bands of organic matter and absorption around 2200 nm were used for estimation and achieved high prediction accuracy with R2 reached 0.640. The results indicate huge potential of soil reflectance spectroscopy in estimating Zn concentrations in soil.
Accuracy of crystal structure error estimates
International Nuclear Information System (INIS)
Taylor, R.; Kennard, O.
1986-01-01
A statistical analysis of 100 crystal structures retrieved from the Cambridge Structural Database is reported. Each structure has been determined independently by two different research groups. Comparison of the independent results leads to the following conclusions: (a) The e.s.d.'s of non-hydrogen-atom positional parameters are almost invariably too small. Typically, they are underestimated by a factor of 1.4-1.45. (b) The extent to which e.s.d.'s are underestimated varies significantly from structure to structure and from atom to atom within a structure. (c) Errors in the positional parameters of atoms belonging to the same chemical residue tend to be positively correlated. (d) The e.s.d.'s of heavy-atom positions are less reliable than those of light-atom positions. (e) Experimental errors in atomic positional parameters are normally, or approximately normally, distributed. (f) The e.s.d.'s of cell parameters are grossly underestimated, by an average factor of about 5 for cell lengths and 2.5 for cell angles. There is marginal evidence that the accuracy of atomic-coordinate e.s.d.'s also depends on diffractometer geometry, refinement procedure, whether or not the structure has a centre of symmetry, and the degree of precision attained in the structure determination. (orig.)
Arm locking with Doppler estimation errors
Energy Technology Data Exchange (ETDEWEB)
Yu Yinan; Wand, Vinzenz; Mitryk, Shawn; Mueller, Guido, E-mail: yinan@phys.ufl.ed [Department of Physics, University of Florida, Gainesville, FL 32611 (United States)
2010-05-01
At the University of Florida we developed the University of Florida LISA Interferometer Simulator (UFLIS) in order to study LISA interferometry with hardware in the loop at a system level. One of the proposed laser frequency stabilization techniques in LISA is arm locking. Arm locking uses an adequately filtered linear combination of the LISA arm signals as a frequency reference. We will report about experiments in which we demonstrated arm locking using UFLIS. During these experiments we also discovered a problem associated with the Doppler shift of the return beam. The initial arm locking publications assumed that this Doppler shift can perfectly be subtracted inside the phasemeter or adds an insignificant offset to the sensor signal. However, the remaining Doppler knowledge error will cause a constant change in the laser frequency if unaccounted for. Several ways to circumvent this problem have been identified. We performed detailed simulations and started preliminary experiments to verify the performance of the proposed new controller designs.
Modeling and estimation of measurement errors
International Nuclear Information System (INIS)
Neuilly, M.
1998-01-01
Any person in charge of taking measures is aware of the inaccuracy of the results however cautiously he may handle. Sensibility, accuracy, reproducibility define the significance of a result. The use of statistical methods is one of the important tools to improve the quality of measurement. The accuracy due to these methods revealed the little difference in the isotopic composition of uranium ore which led to the discovery of Oklo fossil reactor. This book is dedicated to scientists and engineers interested in measurement whatever their investigation interests are. Experimental results are presented as random variables and their laws of probability are approximated by normal law, Poison law or Pearson distribution. The impact of 1 or more parameters on the total error can be evaluated by drawing factorial plans and by using variance analysis methods. This method is also used in intercomparison procedures between laboratories and to detect any abnormal shift in a series of measurement. (A.C.)
Error Estimation and Accuracy Improvements in Nodal Transport Methods
International Nuclear Information System (INIS)
Zamonsky, O.M.
2000-01-01
The accuracy of the solutions produced by the Discrete Ordinates neutron transport nodal methods is analyzed.The obtained new numerical methodologies increase the accuracy of the analyzed scheems and give a POSTERIORI error estimators. The accuracy improvement is obtained with new equations that make the numerical procedure free of truncation errors and proposing spatial reconstructions of the angular fluxes that are more accurate than those used until present. An a POSTERIORI error estimator is rigurously obtained for one dimensional systems that, in certain type of problems, allows to quantify the accuracy of the solutions. From comparisons with the one dimensional results, an a POSTERIORI error estimator is also obtained for multidimensional systems. LOCAL indicators, which quantify the spatial distribution of the errors, are obtained by the decomposition of the menctioned estimators. This makes the proposed methodology suitable to perform adaptive calculations. Some numerical examples are presented to validate the theoretical developements and to illustrate the ranges where the proposed approximations are valid
Approaches to relativistic positioning around Earth and error estimations
Puchades, Neus; Sáez, Diego
2016-01-01
In the context of relativistic positioning, the coordinates of a given user may be calculated by using suitable information broadcast by a 4-tuple of satellites. Our 4-tuples belong to the Galileo constellation. Recently, we estimated the positioning errors due to uncertainties in the satellite world lines (U-errors). A distribution of U-errors was obtained, at various times, in a set of points covering a large region surrounding Earth. Here, the positioning errors associated to the simplifying assumption that photons move in Minkowski space-time (S-errors) are estimated and compared with the U-errors. Both errors have been calculated for the same points and times to make comparisons possible. For a certain realistic modeling of the world line uncertainties, the estimated S-errors have proved to be smaller than the U-errors, which shows that the approach based on the assumption that the Earth's gravitational field produces negligible effects on photons may be used in a large region surrounding Earth. The applicability of this approach - which simplifies numerical calculations - to positioning problems, and the usefulness of our S-error maps, are pointed out. A better approach, based on the assumption that photons move in the Schwarzschild space-time governed by an idealized Earth, is also analyzed. More accurate descriptions of photon propagation involving non symmetric space-time structures are not necessary for ordinary positioning and spacecraft navigation around Earth.
Estimation of the measurement error of eccentrically installed orifice plates
Energy Technology Data Exchange (ETDEWEB)
Barton, Neil; Hodgkinson, Edwin; Reader-Harris, Michael
2005-07-01
The presentation discusses methods for simulation and estimation of flow measurement errors. The main conclusions are: Computational Fluid Dynamics (CFD) simulation methods and published test measurements have been used to estimate the error of a metering system over a period when its orifice plates were eccentric and when leaking O-rings allowed some gas to bypass the meter. It was found that plate eccentricity effects would result in errors of between -2% and -3% for individual meters. Validation against test data suggests that these estimates of error should be within 1% of the actual error, but it is unclear whether the simulations over-estimate or under-estimate the error. Simulations were also run to assess how leakage at the periphery affects the metering error. Various alternative leakage scenarios were modelled and it was found that the leakage rate has an effect on the error, but that the leakage distribution does not. Correction factors, based on the CFD results, were then used to predict the system's mis-measurement over a three-year period (tk)
On the dipole approximation with error estimates
Boßmann, Lea; Grummt, Robert; Kolb, Martin
2018-01-01
The dipole approximation is employed to describe interactions between atoms and radiation. It essentially consists of neglecting the spatial variation of the external field over the atom. Heuristically, this is justified by arguing that the wavelength is considerably larger than the atomic length scale, which holds under usual experimental conditions. We prove the dipole approximation in the limit of infinite wavelengths compared to the atomic length scale and estimate the rate of convergence. Our results include N-body Coulomb potentials and experimentally relevant electromagnetic fields such as plane waves and laser pulses.
Assessing concentration uncertainty estimates from passive microwave sea ice products
Meier, W.; Brucker, L.; Miller, J. A.
2017-12-01
Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.
Error Estimation for Indoor 802.11 Location Fingerprinting
DEFF Research Database (Denmark)
Lemelson, Hendrik; Kjærgaard, Mikkel Baun; Hansen, Rene
2009-01-01
providers could adapt their delivered services based on the estimated position error to achieve a higher service quality. Finally, system operators could use the information to inspect whether a location system provides satisfactory positioning accuracy throughout the covered area. For position error...
NDE errors and their propagation in sizing and growth estimates
International Nuclear Information System (INIS)
Horn, D.; Obrutsky, L.; Lakhan, R.
2009-01-01
The accuracy attributed to eddy current flaw sizing determines the amount of conservativism required in setting tube-plugging limits. Several sources of error contribute to the uncertainty of the measurements, and the way in which these errors propagate and interact affects the overall accuracy of the flaw size and flaw growth estimates. An example of this calculation is the determination of an upper limit on flaw growth over one operating period, based on the difference between two measurements. Signal-to-signal comparison involves a variety of human, instrumental, and environmental error sources; of these, some propagate additively and some multiplicatively. In a difference calculation, specific errors in the first measurement may be correlated with the corresponding errors in the second; others may be independent. Each of the error sources needs to be identified and quantified individually, as does its distribution in the field data. A mathematical framework for the propagation of the errors can then be used to assess the sensitivity of the overall uncertainty to each individual error component. This paper quantifies error sources affecting eddy current sizing estimates and presents analytical expressions developed for their effect on depth estimates. A simple case study is used to model the analysis process. For each error source, the distribution of the field data was assessed and propagated through the analytical expressions. While the sizing error obtained was consistent with earlier estimates and with deviations from ultrasonic depth measurements, the error on growth was calculated as significantly smaller than that obtained assuming uncorrelated errors. An interesting result of the sensitivity analysis in the present case study is the quantification of the error reduction available from post-measurement compensation of magnetite effects. With the absolute and difference error equations, variance-covariance matrices, and partial derivatives developed in
Are Low-order Covariance Estimates Useful in Error Analyses?
Baker, D. F.; Schimel, D.
2005-12-01
Atmospheric trace gas inversions, using modeled atmospheric transport to infer surface sources and sinks from measured concentrations, are most commonly done using least-squares techniques that return not only an estimate of the state (the surface fluxes) but also the covariance matrix describing the uncertainty in that estimate. Besides allowing one to place error bars around the estimate, the covariance matrix may be used in simulation studies to learn what uncertainties would be expected from various hypothetical observing strategies. This error analysis capability is routinely used in designing instrumentation, measurement campaigns, and satellite observing strategies. For example, Rayner, et al (2002) examined the ability of satellite-based column-integrated CO2 measurements to constrain monthly-average CO2 fluxes for about 100 emission regions using this approach. Exact solutions for both state vector and covariance matrix become computationally infeasible, however, when the surface fluxes are solved at finer resolution (e.g., daily in time, under 500 km in space). It is precisely at these finer scales, however, that one would hope to be able to estimate fluxes using high-density satellite measurements. Non-exact estimation methods such as variational data assimilation or the ensemble Kalman filter could be used, but they achieve their computational savings by obtaining an only approximate state estimate and a low-order approximation of the true covariance. One would like to be able to use this covariance matrix to do the same sort of error analyses as are done with the full-rank covariance, but is it correct to do so? Here we compare uncertainties and `information content' derived from full-rank covariance matrices obtained from a direct, batch least squares inversion to those from the incomplete-rank covariance matrices given by a variational data assimilation approach solved with a variable metric minimization technique (the Broyden-Fletcher- Goldfarb
Estimation of error fields from ferromagnetic parts in ITER
Energy Technology Data Exchange (ETDEWEB)
Oliva, A. Bonito [Fusion for Energy (Spain); Chiariello, A.G.; Formisano, A.; Martone, R. [Ass. EURATOM/ENEA/CREATE, Dip. di Ing. Industriale e dell’Informazione, Seconda Università di Napoli, Via Roma 29, I-81031 Napoli (Italy); Portone, A., E-mail: alfredo.portone@f4e.europa.eu [Fusion for Energy (Spain); Testoni, P. [Fusion for Energy (Spain)
2013-10-15
Highlights: ► The paper deals with error fields generated in ITER by magnetic masses. ► Magnetization state is computed from simplified FEM models. ► Closed form expressions adopted for the flux density of magnetized parts are given. ► Such expressions allow to simplify the estimation of the effect of iron pieces (or lack of) on error field. -- Abstract: Error fields in tokamaks are small departures from the exact axisymmetry of the ideal magnetic field configuration. Their reduction below a threshold value by the error field correction coils is essential since sufficiently large static error fields lead to discharge disruption. The error fields are originated not only by magnets fabrication and installation tolerances, by the joints and by the busbars, but also by the presence of ferromagnetic elements. It was shown that superconducting joints, feeders and busbars play a secondary effect; however in order to estimate of the importance of each possible error field source, rough evaluations can be very useful because it can provide an order of magnitude of the correspondent effect and, therefore, a ranking in the request for in depth analysis. The paper proposes a two steps procedure. The first step aims to get the approximate magnetization state of ferromagnetic parts; the second aims to estimate the full 3D error field over the whole volume using equivalent sources for magnetic masses and taking advantage from well assessed approximate closed form expressions, well suited for the far distance effects.
Bayesian ensemble approach to error estimation of interatomic potentials
DEFF Research Database (Denmark)
Frederiksen, Søren Lund; Jacobsen, Karsten Wedel; Brown, K.S.
2004-01-01
Using a Bayesian approach a general method is developed to assess error bars on predictions made by models fitted to data. The error bars are estimated from fluctuations in ensembles of models sampling the model-parameter space with a probability density set by the minimum cost. The method...... is applied to the development of interatomic potentials for molybdenum using various potential forms and databases based on atomic forces. The calculated error bars on elastic constants, gamma-surface energies, structural energies, and dislocation properties are shown to provide realistic estimates...
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence
Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo
2018-05-01
The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.
A posteriori error estimates in voice source recovery
Leonov, A. S.; Sorokin, V. N.
2017-12-01
The inverse problem of voice source pulse recovery from a segment of a speech signal is under consideration. A special mathematical model is used for the solution that relates these quantities. A variational method of solving inverse problem of voice source recovery for a new parametric class of sources, that is for piecewise-linear sources (PWL-sources), is proposed. Also, a technique for a posteriori numerical error estimation for obtained solutions is presented. A computer study of the adequacy of adopted speech production model with PWL-sources is performed in solving the inverse problems for various types of voice signals, as well as corresponding study of a posteriori error estimates. Numerical experiments for speech signals show satisfactory properties of proposed a posteriori error estimates, which represent the upper bounds of possible errors in solving the inverse problem. The estimate of the most probable error in determining the source-pulse shapes is about 7-8% for the investigated speech material. It is noted that a posteriori error estimates can be used as a criterion of the quality for obtained voice source pulses in application to speaker recognition.
Estimating the Autocorrelated Error Model with Trended Data: Further Results,
1979-11-01
Perhaps the most serious deficiency of OLS in the presence of autocorrelation is not inefficiency but bias in its estimated standard errors--a bias...k for all t has variance var(b) = o2/ Tk2 2This refutes Maeshiro’s (1976) conjecture that "an estimator utilizing relevant extraneous information
Constrained motion estimation-based error resilient coding for HEVC
Guo, Weihan; Zhang, Yongfei; Li, Bo
2018-04-01
Unreliable communication channels might lead to packet losses and bit errors in the videos transmitted through it, which will cause severe video quality degradation. This is even worse for HEVC since more advanced and powerful motion estimation methods are introduced to further remove the inter-frame dependency and thus improve the coding efficiency. Once a Motion Vector (MV) is lost or corrupted, it will cause distortion in the decoded frame. More importantly, due to motion compensation, the error will propagate along the motion prediction path, accumulate over time, and significantly degrade the overall video presentation quality. To address this problem, we study the problem of encoder-sider error resilient coding for HEVC and propose a constrained motion estimation scheme to mitigate the problem of error propagation to subsequent frames. The approach is achieved by cutting off MV dependencies and limiting the block regions which are predicted by temporal motion vector. The experimental results show that the proposed method can effectively suppress the error propagation caused by bit errors of motion vector and can improve the robustness of the stream in the bit error channels. When the bit error probability is 10-5, an increase of the decoded video quality (PSNR) by up to1.310dB and on average 0.762 dB can be achieved, compared to the reference HEVC.
Radon measurements-discussion of error estimates for selected methods
International Nuclear Information System (INIS)
Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav
2010-01-01
The main sources of uncertainties for grab sampling, short-term (charcoal canisters) and long term (track detectors) measurements are: systematic bias of reference equipment; random Poisson and non-Poisson errors during calibration; random Poisson and non-Poisson errors during measurements. The origins of non-Poisson random errors during calibration are different for different kinds of instrumental measurements. The main sources of uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. It's shown that total measurement error of surface trap retrospective technique can be decreased to 35%.
Mean value estimates of the error terms of Lehmer problem
Indian Academy of Sciences (India)
Mean value estimates of the error terms of Lehmer problem. DONGMEI REN1 and YAMING ... For further properties of N(a,p) in [6], he studied the mean square value of the error term. E(a, p) = N(a,p) − 1. 2 (p − 1) ..... [1] Apostol Tom M, Introduction to Analytic Number Theory (New York: Springer-Verlag). (1976). [2] Guy R K ...
Complementarity based a posteriori error estimates and their properties
Czech Academy of Sciences Publication Activity Database
Vejchodský, Tomáš
2012-01-01
Roč. 82, č. 10 (2012), s. 2033-2046 ISSN 0378-4754 R&D Projects: GA ČR(CZ) GA102/07/0496; GA AV ČR IAA100760702 Institutional research plan: CEZ:AV0Z10190503 Keywords : error majorant * a posteriori error estimates * method of hypercircle Subject RIV: BA - General Mathematics Impact factor: 0.836, year: 2012 http://www.sciencedirect.com/science/article/pii/S0378475411001509
Estimation of subcriticality of TCA using 'indirect estimation method for calculation error'
International Nuclear Information System (INIS)
Naito, Yoshitaka; Yamamoto, Toshihiro; Arakawa, Takuya; Sakurai, Kiyoshi
1996-01-01
To estimate the subcriticality of neutron multiplication factor in a fissile system, 'Indirect Estimation Method for Calculation Error' is proposed. This method obtains the calculational error of neutron multiplication factor by correlating measured values with the corresponding calculated ones. This method was applied to the source multiplication and to the pulse neutron experiments conducted at TCA, and the calculation error of MCNP 4A was estimated. In the source multiplication method, the deviation of measured neutron count rate distributions from the calculated ones estimates the accuracy of calculated k eff . In the pulse neutron method, the calculation errors of prompt neutron decay constants give the accuracy of the calculated k eff . (author)
Selection of anchor values for human error probability estimation
International Nuclear Information System (INIS)
Buffardi, L.C.; Fleishman, E.A.; Allen, J.A.
1989-01-01
There is a need for more dependable information to assist in the prediction of human errors in nuclear power environments. The major objective of the current project is to establish guidelines for using error probabilities from other task settings to estimate errors in the nuclear environment. This involves: (1) identifying critical nuclear tasks, (2) discovering similar tasks in non-nuclear environments, (3) finding error data for non-nuclear tasks, and (4) establishing error-rate values for the nuclear tasks based on the non-nuclear data. A key feature is the application of a classification system to nuclear and non-nuclear tasks to evaluate their similarities and differences in order to provide a basis for generalizing human error estimates across tasks. During the first eight months of the project, several classification systems have been applied to a sample of nuclear tasks. They are discussed in terms of their potential for establishing task equivalence and transferability of human error rates across situations
Tracking and shape errors measurement of concentrating heliostats
Coquand, Mathieu; Caliot, Cyril; Hénault, François
2017-09-01
In solar tower power plants, factors such as tracking accuracy, facets misalignment and surface shape errors of concentrating heliostats are of prime importance on the efficiency of the system. At industrial scale, one critical issue is the time and effort required to adjust the different mirrors of the faceted heliostats, which could take several months using current techniques. Thus, methods enabling quick adjustment of a field with a huge number of heliostats are essential for the rise of solar tower technology. In this communication is described a new method for heliostat characterization that makes use of four cameras located near the solar receiver and simultaneously recording images of the sun reflected by the optical surfaces. From knowledge of a measured sun profile, data processing of the acquired images allows reconstructing the slope and shape errors of the heliostats, including tracking and canting errors. The mathematical basis of this shape reconstruction process is explained comprehensively. Numerical simulations demonstrate that the measurement accuracy of this "backward-gazing method" is compliant with the requirements of solar concentrating optics. Finally, we present our first experimental results obtained at the THEMIS experimental solar tower plant in Targasonne, France.
Verification of unfold error estimates in the unfold operator code
International Nuclear Information System (INIS)
Fehl, D.L.; Biggs, F.
1997-01-01
Spectral unfolding is an inverse mathematical operation that attempts to obtain spectral source information from a set of response functions and data measurements. Several unfold algorithms have appeared over the past 30 years; among them is the unfold operator (UFO) code written at Sandia National Laboratories. In addition to an unfolded spectrum, the UFO code also estimates the unfold uncertainty (error) induced by estimated random uncertainties in the data. In UFO the unfold uncertainty is obtained from the error matrix. This built-in estimate has now been compared to error estimates obtained by running the code in a Monte Carlo fashion with prescribed data distributions (Gaussian deviates). In the test problem studied, data were simulated from an arbitrarily chosen blackbody spectrum (10 keV) and a set of overlapping response functions. The data were assumed to have an imprecision of 5% (standard deviation). One hundred random data sets were generated. The built-in estimate of unfold uncertainty agreed with the Monte Carlo estimate to within the statistical resolution of this relatively small sample size (95% confidence level). A possible 10% bias between the two methods was unresolved. The Monte Carlo technique is also useful in underdetermined problems, for which the error matrix method does not apply. UFO has been applied to the diagnosis of low energy x rays emitted by Z-pinch and ion-beam driven hohlraums. copyright 1997 American Institute of Physics
Investigation of error sources in regional inverse estimates of greenhouse gas emissions in Canada
Chan, E.; Chan, D.; Ishizawa, M.; Vogel, F.; Brioude, J.; Delcloo, A.; Wu, Y.; Jin, B.
2015-08-01
Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion
Aniseikonia quantification: error rate of rule of thumb estimation.
Lubkin, V; Shippman, S; Bennett, G; Meininger, D; Kramer, P; Poppinga, P
1999-01-01
To find the error rate in quantifying aniseikonia by using "Rule of Thumb" estimation in comparison with proven space eikonometry. Study 1: 24 adult pseudophakic individuals were measured for anisometropia, and astigmatic interocular difference. Rule of Thumb quantification for prescription was calculated and compared with aniseikonia measurement by the classical Essilor Projection Space Eikonometer. Study 2: parallel analysis was performed on 62 consecutive phakic patients from our strabismus clinic group. Frequency of error: For Group 1 (24 cases): 5 ( or 21 %) were equal (i.e., 1% or less difference); 16 (or 67% ) were greater (more than 1% different); and 3 (13%) were less by Rule of Thumb calculation in comparison to aniseikonia determined on the Essilor eikonometer. For Group 2 (62 cases): 45 (or 73%) were equal (1% or less); 10 (or 16%) were greater; and 7 (or 11%) were lower in the Rule of Thumb calculations in comparison to Essilor eikonometry. Magnitude of error: In Group 1, in 10/24 (29%) aniseikonia by Rule of Thumb estimation was 100% or more greater than by space eikonometry, and in 6 of those ten by 200% or more. In Group 2, in 4/62 (6%) aniseikonia by Rule of Thumb estimation was 200% or more greater than by space eikonometry. The frequency and magnitude of apparent clinical errors of Rule of Thumb estimation is disturbingly large. This problem is greatly magnified by the time and effort and cost of prescribing and executing an aniseikonic correction for a patient. The higher the refractive error, the greater the anisometropia, and the worse the errors in Rule of Thumb estimation of aniseikonia. Accurate eikonometric methods and devices should be employed in all cases where such measurements can be made. Rule of thumb estimations should be limited to cases where such subjective testing and measurement cannot be performed, as in infants after unilateral cataract surgery.
Influence of measurement errors and estimated parameters on combustion diagnosis
International Nuclear Information System (INIS)
Payri, F.; Molina, S.; Martin, J.; Armas, O.
2006-01-01
Thermodynamic diagnosis models are valuable tools for the study of Diesel combustion. Inputs required by such models comprise measured mean and instantaneous variables, together with suitable values for adjustable parameters used in different submodels. In the case of measured variables, one may estimate the uncertainty associated with measurement errors; however, the influence of errors in model parameter estimation may not be so easily established on an experimental basis. In this paper, a simulated pressure cycle has been used along with known input parameters, so that any uncertainty in the inputs is avoided. Then, the influence of errors in measured variables and geometric and heat transmission parameters on the results of a diagnosis combustion model for direct injection diesel engines have been studied. This procedure allowed to establish the relative importance of these parameters and to set limits to the maximal errors of the model, accounting for both the maximal expected errors in the input parameters and the sensitivity of the model to those errors
Error Estimation for the Linearized Auto-Localization Algorithm
Directory of Open Access Journals (Sweden)
Fernando Seco
2012-02-01
Full Text Available The Linearized Auto-Localization (LAL algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs, using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL, the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.
Development of an integrated system for estimating human error probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, J.L.; Hahn, H.A.; Morzinski, J.A.
1998-12-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This project had as its main objective the development of a Human Reliability Analysis (HRA), knowledge-based expert system that would provide probabilistic estimates for potential human errors within various risk assessments, safety analysis reports, and hazard assessments. HRA identifies where human errors are most likely, estimates the error rate for individual tasks, and highlights the most beneficial areas for system improvements. This project accomplished three major tasks. First, several prominent HRA techniques and associated databases were collected and translated into an electronic format. Next, the project started a knowledge engineering phase where the expertise, i.e., the procedural rules and data, were extracted from those techniques and compiled into various modules. Finally, these modules, rules, and data were combined into a nearly complete HRA expert system.
A precise error bound for quantum phase estimation.
Directory of Open Access Journals (Sweden)
James M Chappell
Full Text Available Quantum phase estimation is one of the key algorithms in the field of quantum computing, but up until now, only approximate expressions have been derived for the probability of error. We revisit these derivations, and find that by ensuring symmetry in the error definitions, an exact formula can be found. This new approach may also have value in solving other related problems in quantum computing, where an expected error is calculated. Expressions for two special cases of the formula are also developed, in the limit as the number of qubits in the quantum computer approaches infinity and in the limit as the extra added qubits to improve reliability goes to infinity. It is found that this formula is useful in validating computer simulations of the phase estimation procedure and in avoiding the overestimation of the number of qubits required in order to achieve a given reliability. This formula thus brings improved precision in the design of quantum computers.
On global error estimation and control for initial value problems
J. Lang (Jens); J.G. Verwer (Jan)
2007-01-01
textabstractThis paper addresses global error estimation and control for initial value problems for ordinary differential equations. The focus lies on a comparison between a novel approach based onthe adjoint method combined with a small sample statistical initialization and the classical approach
On global error estimation and control for initial value problems
Lang, J.; Verwer, J.G.
2007-01-01
Abstract. This paper addresses global error estimation and control for initial value problems for ordinary differential equations. The focus lies on a comparison between a novel approach based on the adjoint method combined with a small sample statistical initialization and the classical approach
Bayesian error estimation in density-functional theory
DEFF Research Database (Denmark)
Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund
2005-01-01
We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...
A posteriori error estimates for axisymmetric and nonlinear problems
Czech Academy of Sciences Publication Activity Database
Křížek, Michal; Němec, J.; Vejchodský, Tomáš
2001-01-01
Roč. 15, - (2001), s. 219-236 ISSN 1019-7168 R&D Projects: GA ČR GA201/01/1200; GA MŠk ME 148 Keywords : weigted Sobolev spaces%a posteriori error estimates%finite elements Subject RIV: BA - General Mathematics Impact factor: 0.886, year: 2001
Error estimates in horocycle averages asymptotics: challenges from string theory
Cardella, M.A.
2010-01-01
For modular functions of rapid decay, a classical result connects the error estimate in their long horocycle average asymptotic to the Riemann hypothesis. We study similar asymptotics, for modular functions with not that mild growing conditions, such as of polynomial growth and of exponential growth
Computational Error Estimate for the Power Series Solution of Odes ...
African Journals Online (AJOL)
This paper compares the error estimation of power series solution with recursive Tau method for solving ordinary differential equations. From the computational viewpoint, the power series using zeros of Chebyshevpolunomial is effective, accurate and easy to use. Keywords: Lanczos Tau method, Chebyshev polynomial, ...
Error Estimates for the Approximation of the Effective Hamiltonian
International Nuclear Information System (INIS)
Camilli, Fabio; Capuzzo Dolcetta, Italo; Gomes, Diogo A.
2008-01-01
We study approximation schemes for the cell problem arising in homogenization of Hamilton-Jacobi equations. We prove several error estimates concerning the rate of convergence of the approximation scheme to the effective Hamiltonian, both in the optimal control setting and as well as in the calculus of variations setting
Estimation of total error in DWPF reported radionuclide inventories. Revision 1
International Nuclear Information System (INIS)
Edwards, T.B.
1995-01-01
The Defense Waste Processing Facility (DWPF) at the Savannah River Site is required to determine and report the radionuclide inventory of its glass product. For each macro-batch, the DWPF will report both the total amount (in curies) of each reportable radionuclide and the average concentration (in curies/gram of glass) of each reportable radionuclide. The DWPF is to provide the estimated error of these reported values of its radionuclide inventory as well. The objective of this document is to provide a framework for determining the estimated error in DWPF's reporting of these radionuclide inventories. This report investigates the impact of random errors due to measurement and sampling on the total amount of each reportable radionuclide in a given macro-batch. In addition, the impact of these measurement and sampling errors and process variation are evaluated to determine the uncertainty in the reported average concentrations of radionuclides in DWPF's filled canister inventory resulting from each macro-batch
Human error probability estimation using licensee event reports
International Nuclear Information System (INIS)
Voska, K.J.; O'Brien, J.N.
1984-07-01
Objective of this report is to present a method for using field data from nuclear power plants to estimate human error probabilities (HEPs). These HEPs are then used in probabilistic risk activities. This method of estimating HEPs is one of four being pursued in NRC-sponsored research. The other three are structured expert judgment, analysis of training simulator data, and performance modeling. The type of field data analyzed in this report is from Licensee Event reports (LERs) which are analyzed using a method specifically developed for that purpose. However, any type of field data or human errors could be analyzed using this method with minor adjustments. This report assesses the practicality, acceptability, and usefulness of estimating HEPs from LERs and comprehensively presents the method for use
Evaluation of human error estimation for nuclear power plants
International Nuclear Information System (INIS)
Haney, L.N.; Blackman, H.S.
1987-01-01
The dominant risk for severe accident occurrence in nuclear power plants (NPPs) is human error. The US Nuclear Regulatory Commission (NRC) sponsored an evaluation of Human Reliability Analysis (HRA) techniques for estimation of human error in NPPs. Twenty HRA techniques identified by a literature search were evaluated with criteria sets designed for that purpose and categorized. Data were collected at a commercial NPP with operators responding in walkthroughs of four severe accident scenarios and full scope simulator runs. Results suggest a need for refinement and validation of the techniques. 19 refs
Estimating error rates for firearm evidence identifications in forensic science
Song, John; Vorburger, Theodore V.; Chu, Wei; Yen, James; Soons, Johannes A.; Ott, Daniel B.; Zhang, Nien Fan
2018-01-01
Estimating error rates for firearm evidence identification is a fundamental challenge in forensic science. This paper describes the recently developed congruent matching cells (CMC) method for image comparisons, its application to firearm evidence identification, and its usage and initial tests for error rate estimation. The CMC method divides compared topography images into correlation cells. Four identification parameters are defined for quantifying both the topography similarity of the correlated cell pairs and the pattern congruency of the registered cell locations. A declared match requires a significant number of CMCs, i.e., cell pairs that meet all similarity and congruency requirements. Initial testing on breech face impressions of a set of 40 cartridge cases fired with consecutively manufactured pistol slides showed wide separation between the distributions of CMC numbers observed for known matching and known non-matching image pairs. Another test on 95 cartridge cases from a different set of slides manufactured by the same process also yielded widely separated distributions. The test results were used to develop two statistical models for the probability mass function of CMC correlation scores. The models were applied to develop a framework for estimating cumulative false positive and false negative error rates and individual error rates of declared matches and non-matches for this population of breech face impressions. The prospect for applying the models to large populations and realistic case work is also discussed. The CMC method can provide a statistical foundation for estimating error rates in firearm evidence identifications, thus emulating methods used for forensic identification of DNA evidence. PMID:29331680
Error Estimation and Uncertainty Propagation in Computational Fluid Mechanics
Zhu, J. Z.; He, Guowei; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
Numerical simulation has now become an integral part of engineering design process. Critical design decisions are routinely made based on the simulation results and conclusions. Verification and validation of the reliability of the numerical simulation is therefore vitally important in the engineering design processes. We propose to develop theories and methodologies that can automatically provide quantitative information about the reliability of the numerical simulation by estimating numerical approximation error, computational model induced errors and the uncertainties contained in the mathematical models so that the reliability of the numerical simulation can be verified and validated. We also propose to develop and implement methodologies and techniques that can control the error and uncertainty during the numerical simulation so that the reliability of the numerical simulation can be improved.
CTER—Rapid estimation of CTF parameters with error assessment
Energy Technology Data Exchange (ETDEWEB)
Penczek, Pawel A., E-mail: Pawel.A.Penczek@uth.tmc.edu [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Fang, Jia [Department of Biochemistry and Molecular Biology, The University of Texas Medical School, 6431 Fannin MSB 6.220, Houston, TX 77054 (United States); Li, Xueming; Cheng, Yifan [The Keck Advanced Microscopy Laboratory, Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94158 (United States); Loerke, Justus; Spahn, Christian M.T. [Institut für Medizinische Physik und Biophysik, Charité – Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin (Germany)
2014-05-01
In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300 kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03 Å without, and 3.85 Å with, inclusion of astigmatism parameters. - Highlights: • We describe methodology for estimation of CTF parameters with error assessment. • Error estimates provide means for automated elimination of inferior micrographs. • High computational efficiency allows real-time monitoring of EM data quality. • Accurate CTF estimation yields structure of the 80S human ribosome at 3.85 Å.
Estimation of Branch Topology Errors in Power Networks by WLAN State Estimation
Energy Technology Data Exchange (ETDEWEB)
Kim, Hong Rae [Soonchunhyang University(Korea); Song, Kyung Bin [Kei Myoung University(Korea)
2000-06-01
The purpose of this paper is to detect and identify topological errors in order to maintain a reliable database for the state estimator. In this paper, a two stage estimation procedure is used to identify the topology errors. At the first stage, the WLAV state estimator which has characteristics to remove bad data during the estimation procedure is run for finding out the suspected branches at which topology errors take place. The resulting residuals are normalized and the measurements with significant normalized residuals are selected. A set of suspected branches is formed based on these selected measurements; if the selected measurement if a line flow, the corresponding branch is suspected; if it is an injection, then all the branches connecting the injection bus to its immediate neighbors are suspected. A new WLAV state estimator adding the branch flow errors in the state vector is developed to identify the branch topology errors. Sample cases of single topology error and topology error with a measurement error are applied to IEEE 14 bus test system. (author). 24 refs., 1 fig., 9 tabs.
Exact error estimation for solutions of nuclide chain equations
International Nuclear Information System (INIS)
Tachihara, Hidekazu; Sekimoto, Hiroshi
1999-01-01
The exact solution of nuclide chain equations within arbitrary figures is obtained for a linear chain by employing the Bateman method in the multiple-precision arithmetic. The exact error estimation of major calculation methods for a nuclide chain equation is done by using this exact solution as a standard. The Bateman, finite difference, Runge-Kutta and matrix exponential methods are investigated. The present study confirms the following. The original Bateman method has very low accuracy in some cases, because of large-scale cancellations. The revised Bateman method by Siewers reduces the occurrence of cancellations and thereby shows high accuracy. In the time difference method as the finite difference and Runge-Kutta methods, the solutions are mainly affected by the truncation errors in the early decay time, and afterward by the round-off errors. Even though the variable time mesh is employed to suppress the accumulation of round-off errors, it appears to be nonpractical. Judging from these estimations, the matrix exponential method is the best among all the methods except the Bateman method whose calculation process for a linear chain is not identical with that for a general one. (author)
GPS/DR Error Estimation for Autonomous Vehicle Localization.
Lee, Byung-Hyun; Song, Jong-Hwa; Im, Jun-Hyuck; Im, Sung-Hyuck; Heo, Moon-Beom; Jee, Gyu-In
2015-08-21
Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.
GPS/DR Error Estimation for Autonomous Vehicle Localization
Directory of Open Access Journals (Sweden)
Byung-Hyun Lee
2015-08-01
Full Text Available Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.
Regularization and error estimates for nonhomogeneous backward heat problems
Directory of Open Access Journals (Sweden)
Duc Trong Dang
2006-01-01
Full Text Available In this article, we study the inverse time problem for the non-homogeneous heat equation which is a severely ill-posed problem. We regularize this problem using the quasi-reversibility method and then obtain error estimates on the approximate solutions. Solutions are calculated by the contraction principle and shown in numerical experiments. We obtain also rates of convergence to the exact solution.
Hall, Eric Joseph; Hoel, Hå kon; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
2016-01-01
posteriori error estimates fail to capture. We propose goal-oriented estimates, based on local error indicators, for the pathwise Galerkin and expected quadrature errors committed in standard, continuous, piecewise linear finite element approximations
Interpolation Error Estimates for Mean Value Coordinates over Convex Polygons.
Rand, Alexander; Gillette, Andrew; Bajaj, Chandrajit
2013-08-01
In a similar fashion to estimates shown for Harmonic, Wachspress, and Sibson coordinates in [Gillette et al., AiCM, to appear], we prove interpolation error estimates for the mean value coordinates on convex polygons suitable for standard finite element analysis. Our analysis is based on providing a uniform bound on the gradient of the mean value functions for all convex polygons of diameter one satisfying certain simple geometric restrictions. This work makes rigorous an observed practical advantage of the mean value coordinates: unlike Wachspress coordinates, the gradient of the mean value coordinates does not become large as interior angles of the polygon approach π.
Error estimates for discretized quantum stochastic differential inclusions
International Nuclear Information System (INIS)
Ayoola, E.O.
2001-09-01
This paper is concerned with the error estimates involved in the solution of a discrete approximation of a quantum stochastic differential inclusion (QSDI). Our main results rely on certain properties of the averaged modulus of continuity for multivalued sesquilinear forms associated with QSDI. We obtained results concerning the estimates of the Hausdorff distance between the set of solutions of the QSDI and the set of solutions of its discrete approximation. This extend the results of Dontchev and Farkhi concerning classical differential inclusions to the present noncommutative Quantum setting involving inclusions in certain locally convex space. (author)
A Simulation-Based Soft Error Estimation Methodology for Computer Systems
Sugihara, Makoto; Ishihara, Tohru; Hashimoto, Koji; Muroyama, Masanori
2006-01-01
This paper proposes a simulation-based soft error estimation methodology for computer systems. Accumulating soft error rates (SERs) of all memories in a computer system results in pessimistic soft error estimation. This is because memory cells are used spatially and temporally and not all soft errors in them make the computer system faulty. Our soft-error estimation methodology considers the locations and the timings of soft errors occurring at every level of memory hierarchy and estimates th...
Rigorous covariance propagation of geoid errors to geodetic MDT estimates
Pail, R.; Albertella, A.; Fecher, T.; Savcenko, R.
2012-04-01
The mean dynamic topography (MDT) is defined as the difference between the mean sea surface (MSS) derived from satellite altimetry, averaged over several years, and the static geoid. Assuming geostrophic conditions, from the MDT the ocean surface velocities as important component of global ocean circulation can be derived from it. Due to the availability of GOCE gravity field models, for the very first time MDT can now be derived solely from satellite observations (altimetry and gravity) down to spatial length-scales of 100 km and even below. Global gravity field models, parameterized in terms of spherical harmonic coefficients, are complemented by the full variance-covariance matrix (VCM). Therefore, for the geoid component a realistic statistical error estimate is available, while the error description of the altimetric component is still an open issue and is, if at all, attacked empirically. In this study we make the attempt to perform, based on the full gravity VCM, rigorous error propagation to derived geostrophic surface velocities, thus also considering all correlations. For the definition of the static geoid we use the third release of the time-wise GOCE model, as well as the satellite-only combination model GOCO03S. In detail, we will investigate the velocity errors resulting from the geoid component in dependence of the harmonic degree, and the impact of using/no using covariances on the MDT errors and its correlations. When deriving an MDT, it is spectrally filtered to a certain maximum degree, which is usually driven by the signal content of the geoid model, by applying isotropic or non-isotropic filters. Since this filtering is acting also on the geoid component, the consistent integration of this filter process into the covariance propagation shall be performed, and its impact shall be quantified. The study will be performed for MDT estimates in specific test areas of particular oceanographic interest.
Directory of Open Access Journals (Sweden)
Nazelie Kassabian
2014-06-01
Full Text Available Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs. This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold.
A Fast Soft Bit Error Rate Estimation Method
Directory of Open Access Journals (Sweden)
Ait-Idir Tarik
2010-01-01
Full Text Available We have suggested in a previous publication a method to estimate the Bit Error Rate (BER of a digital communications system instead of using the famous Monte Carlo (MC simulation. This method was based on the estimation of the probability density function (pdf of soft observed samples. The kernel method was used for the pdf estimation. In this paper, we suggest to use a Gaussian Mixture (GM model. The Expectation Maximisation algorithm is used to estimate the parameters of this mixture. The optimal number of Gaussians is computed by using Mutual Information Theory. The analytical expression of the BER is therefore simply given by using the different estimated parameters of the Gaussian Mixture. Simulation results are presented to compare the three mentioned methods: Monte Carlo, Kernel and Gaussian Mixture. We analyze the performance of the proposed BER estimator in the framework of a multiuser code division multiple access system and show that attractive performance is achieved compared with conventional MC or Kernel aided techniques. The results show that the GM method can drastically reduce the needed number of samples to estimate the BER in order to reduce the required simulation run-time, even at very low BER.
Normalized Minimum Error Entropy Algorithm with Recursive Power Estimation
Directory of Open Access Journals (Sweden)
Namyong Kim
2016-06-01
Full Text Available The minimum error entropy (MEE algorithm is known to be superior in signal processing applications under impulsive noise. In this paper, based on the analysis of behavior of the optimum weight and the properties of robustness against impulsive noise, a normalized version of the MEE algorithm is proposed. The step size of the MEE algorithm is normalized with the power of input entropy that is estimated recursively for reducing its computational complexity. The proposed algorithm yields lower minimum MSE (mean squared error and faster convergence speed simultaneously than the original MEE algorithm does in the equalization simulation. On the condition of the same convergence speed, its performance enhancement in steady state MSE is above 3 dB.
Estimation of Toxicity Equivalent Concentration (TEQ) of ...
African Journals Online (AJOL)
Estimation of Toxicity Equivalent Concentration (TEQ) of carcinogenic polycyclic aromatic hydrocarbons in soils from Idu Ekpeye playground and University of Port ... Effective soil remediation and detoxification method like Dispersion by chemical reaction technology should be deployed to clean-up sites to avoid soil toxicity ...
A Posteriori Error Estimates Including Algebraic Error and Stopping Criteria for Iterative Solvers
Czech Academy of Sciences Publication Activity Database
Jiránek, P.; Strakoš, Zdeněk; Vohralík, M.
2010-01-01
Roč. 32, č. 3 (2010), s. 1567-1590 ISSN 1064-8275 R&D Projects: GA AV ČR IAA100300802 Grant - others:GA ČR(CZ) GP201/09/P464 Institutional research plan: CEZ:AV0Z10300504 Keywords : second-order elliptic partial differential equation * finite volume method * a posteriori error estimates * iterative methods for linear algebraic systems * conjugate gradient method * stopping criteria Subject RIV: BA - General Mathematics Impact factor: 3.016, year: 2010
Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters
Hoshino, Takahiro; Shigemasu, Kazuo
2008-01-01
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Smoothed Spectra, Ogives, and Error Estimates for Atmospheric Turbulence Data
Dias, Nelson Luís
2018-01-01
A systematic evaluation is conducted of the smoothed spectrum, which is a spectral estimate obtained by averaging over a window of contiguous frequencies. The technique is extended to the ogive, as well as to the cross-spectrum. It is shown that, combined with existing variance estimates for the periodogram, the variance—and therefore the random error—associated with these estimates can be calculated in a straightforward way. The smoothed spectra and ogives are biased estimates; with simple power-law analytical models, correction procedures are devised, as well as a global constraint that enforces Parseval's identity. Several new results are thus obtained: (1) The analytical variance estimates compare well with the sample variance calculated for the Bartlett spectrum and the variance of the inertial subrange of the cospectrum is shown to be relatively much larger than that of the spectrum. (2) Ogives and spectra estimates with reduced bias are calculated. (3) The bias of the smoothed spectrum and ogive is shown to be negligible at the higher frequencies. (4) The ogives and spectra thus calculated have better frequency resolution than the Bartlett spectrum, with (5) gradually increasing variance and relative error towards the low frequencies. (6) Power-law identification and extraction of the rate of dissipation of turbulence kinetic energy are possible directly from the ogive. (7) The smoothed cross-spectrum is a valid inner product and therefore an acceptable candidate for coherence and spectral correlation coefficient estimation by means of the Cauchy-Schwarz inequality. The quadrature, phase function, coherence function and spectral correlation function obtained from the smoothed spectral estimates compare well with the classical ones derived from the Bartlett spectrum.
International Nuclear Information System (INIS)
Fruehwirth, R.
1993-01-01
We present an estimation procedure of the error components in a linear regression model with multiple independent stochastic error contributions. After solving the general problem we apply the results to the estimation of the actual trajectory in track fitting with multiple scattering. (orig.)
Fellner, Klemens; Kovtunenko, Victor A
2016-01-01
A nonlinear Poisson-Boltzmann equation with inhomogeneous Robin type boundary conditions at the interface between two materials is investigated. The model describes the electrostatic potential generated by a vector of ion concentrations in a periodic multiphase medium with dilute solid particles. The key issue stems from interfacial jumps, which necessitate discontinuous solutions to the problem. Based on variational techniques, we derive the homogenisation of the discontinuous problem and establish a rigorous residual error estimate up to the first-order correction.
Error estimation for CFD aeroheating prediction under rarefied flow condition
Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian
2014-12-01
Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.
Fractional kalman filter to estimate the concentration of air pollution
Vita Oktaviana, Yessy; Apriliani, Erna; Khusnul Arif, Didik
2018-04-01
Air pollution problem gives important effect in quality environment and quality of human’s life. Air pollution can be caused by nature sources or human activities. Pollutant for example Ozone, a harmful gas formed by NOx and volatile organic compounds (VOCs) emitted from various sources. The air pollution problem can be modeled by TAPM-CTM (The Air Pollution Model with Chemical Transport Model). The model shows concentration of pollutant in the air. Therefore, it is important to estimate concentration of air pollutant. Estimation method can be used for forecast pollutant concentration in future and keep stability of air quality. In this research, an algorithm is developed, based on Fractional Kalman Filter to solve the model of air pollution’s problem. The model will be discretized first and then it will be estimated by the method. The result shows that estimation of Fractional Kalman Filter has better accuracy than estimation of Kalman Filter. The accuracy was tested by applying RMSE (Root Mean Square Error).
Influence of binary mask estimation errors on robust speaker identification
DEFF Research Database (Denmark)
May, Tobias
2017-01-01
Missing-data strategies have been developed to improve the noise-robustness of automatic speech recognition systems in adverse acoustic conditions. This is achieved by classifying time-frequency (T-F) units into reliable and unreliable components, as indicated by a so-called binary mask. Different...... approaches have been proposed to handle unreliable feature components, each with distinct advantages. The direct masking (DM) approach attenuates unreliable T-F units in the spectral domain, which allows the extraction of conventionally used mel-frequency cepstral coefficients (MFCCs). Instead of attenuating....... Since each of these approaches utilizes the knowledge about reliable and unreliable feature components in a different way, they will respond differently to estimation errors in the binary mask. The goal of this study was to identify the most effective strategy to exploit knowledge about reliable...
Using cell phone location to assess misclassification errors in air pollution exposure estimation.
Yu, Haofei; Russell, Armistead; Mulholland, James; Huang, Zhijiong
2018-02-01
Air pollution epidemiologic and health impact studies often rely on home addresses to estimate individual subject's pollution exposure. In this study, we used detailed cell phone location data, the call detail record (CDR), to account for the impact of spatiotemporal subject mobility on estimates of ambient air pollutant exposure. This approach was applied on a sample with 9886 unique simcard IDs in Shenzhen, China, on one mid-week day in October 2013. Hourly ambient concentrations of six chosen pollutants were simulated by the Community Multi-scale Air Quality model fused with observational data, and matched with detailed location data for these IDs. The results were compared with exposure estimates using home addresses to assess potential exposure misclassification errors. We found the misclassifications errors are likely to be substantial when home location alone is applied. The CDR based approach indicates that the home based approach tends to over-estimate exposures for subjects with higher exposure levels and under-estimate exposures for those with lower exposure levels. Our results show that the cell phone location based approach can be used to assess exposure misclassification error and has the potential for improving exposure estimates in air pollution epidemiology studies. Copyright © 2017 Elsevier Ltd. All rights reserved.
CTER-rapid estimation of CTF parameters with error assessment.
Penczek, Pawel A; Fang, Jia; Li, Xueming; Cheng, Yifan; Loerke, Justus; Spahn, Christian M T
2014-05-01
In structural electron microscopy, the accurate estimation of the Contrast Transfer Function (CTF) parameters, particularly defocus and astigmatism, is of utmost importance for both initial evaluation of micrograph quality and for subsequent structure determination. Due to increases in the rate of data collection on modern microscopes equipped with new generation cameras, it is also important that the CTF estimation can be done rapidly and with minimal user intervention. Finally, in order to minimize the necessity for manual screening of the micrographs by a user it is necessary to provide an assessment of the errors of fitted parameters values. In this work we introduce CTER, a CTF parameters estimation method distinguished by its computational efficiency. The efficiency of the method makes it suitable for high-throughput EM data collection, and enables the use of a statistical resampling technique, bootstrap, that yields standard deviations of estimated defocus and astigmatism amplitude and angle, thus facilitating the automation of the process of screening out inferior micrograph data. Furthermore, CTER also outputs the spatial frequency limit imposed by reciprocal space aliasing of the discrete form of the CTF and the finite window size. We demonstrate the efficiency and accuracy of CTER using a data set collected on a 300kV Tecnai Polara (FEI) using the K2 Summit DED camera in super-resolution counting mode. Using CTER we obtained a structure of the 80S ribosome whose large subunit had a resolution of 4.03Å without, and 3.85Å with, inclusion of astigmatism parameters. Copyright © 2014 Elsevier B.V. All rights reserved.
Results and Error Estimates from GRACE Forward Modeling over Antarctica
Bonin, Jennifer; Chambers, Don
2013-04-01
Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Antarctica. However when tested previously, the least squares technique has required constraints in the form of added process noise in order to be reliable. Poor choice of local basin layout has also adversely affected results, as has the choice of spatial smoothing used with GRACE. To develop design parameters which will result in correct high-resolution mass detection and to estimate the systematic errors of the method over Antarctica, we use a "truth" simulation of the Antarctic signal. We apply the optimal parameters found from the simulation to RL05 GRACE data across Antarctica and the surrounding ocean. We particularly focus on separating the Antarctic peninsula's mass signal from that of the rest of western Antarctica. Additionally, we characterize how well the technique works for removing land leakage signal from the nearby ocean, particularly that near the Drake Passage.
Black hole spectroscopy: Systematic errors and ringdown energy estimates
Baibhav, Vishal; Berti, Emanuele; Cardoso, Vitor; Khanna, Gaurav
2018-02-01
The relaxation of a distorted black hole to its final state provides important tests of general relativity within the reach of current and upcoming gravitational wave facilities. In black hole perturbation theory, this phase consists of a simple linear superposition of exponentially damped sinusoids (the quasinormal modes) and of a power-law tail. How many quasinormal modes are necessary to describe waveforms with a prescribed precision? What error do we incur by only including quasinormal modes, and not tails? What other systematic effects are present in current state-of-the-art numerical waveforms? These issues, which are basic to testing fundamental physics with distorted black holes, have hardly been addressed in the literature. We use numerical relativity waveforms and accurate evolutions within black hole perturbation theory to provide some answers. We show that (i) a determination of the fundamental l =m =2 quasinormal frequencies and damping times to within 1% or better requires the inclusion of at least the first overtone, and preferably of the first two or three overtones; (ii) a determination of the black hole mass and spin with precision better than 1% requires the inclusion of at least two quasinormal modes for any given angular harmonic mode (ℓ , m ). We also improve on previous estimates and fits for the ringdown energy radiated in the various multipoles. These results are important to quantify theoretical (as opposed to instrumental) limits in parameter estimation accuracy and tests of general relativity allowed by ringdown measurements with high signal-to-noise ratio gravitational wave detectors.
Directory of Open Access Journals (Sweden)
Zhanshan Wang
2014-01-01
Full Text Available The control of a high performance alternative current (AC motor drive under sensorless operation needs the accurate estimation of rotor position. In this paper, one method of accurately estimating rotor position by using both motor complex number model based position estimation and position estimation error suppression proportion integral (PI controller is proposed for the sensorless control of the surface permanent magnet synchronous motor (SPMSM. In order to guarantee the accuracy of rotor position estimation in the flux-weakening region, one scheme of identifying the permanent magnet flux of SPMSM by extended Kalman filter (EKF is also proposed, which formed the effective combination method to realize the sensorless control of SPMSM with high accuracy. The simulation results demonstrated the validity and feasibility of the proposed position/speed estimation system.
Estimating Canopy Nitrogen Concentration in Sugarcane Using Field Imaging Spectroscopy
Directory of Open Access Journals (Sweden)
Marc Souris
2012-06-01
Full Text Available The retrieval of nutrient concentration in sugarcane through hyperspectral remote sensing is widely known to be affected by canopy architecture. The goal of this research was to develop an estimation model that could explain the nitrogen variations in sugarcane with combined cultivars. Reflectance spectra were measured over the sugarcane canopy using a field spectroradiometer. The models were calibrated by a vegetation index and multiple linear regression. The original reflectance was transformed into a First-Derivative Spectrum (FDS and two absorption features. The results indicated that the sensitive spectral wavelengths for quantifying nitrogen content existed mainly in the visible, red edge and far near-infrared regions of the electromagnetic spectrum. Normalized Differential Index (NDI based on FDS_{(750/700} and Ratio Spectral Index (RVI based on FDS_{(724/700} are best suited for characterizing the nitrogen concentration. The modified estimation model, generated by the Stepwise Multiple Linear Regression (SMLR technique from FDS centered at 410, 426, 720, 754, and 1,216 nm, yielded the highest correlation coefficient value of 0.86 and Root Mean Square Error of the Estimate (RMSE value of 0.033%N (n = 90 with nitrogen concentration in sugarcane. The results of this research demonstrated that the estimation model developed by SMLR yielded a higher correlation coefficient with nitrogen content than the model computed by narrow vegetation indices. The strong correlation between measured and estimated nitrogen concentration indicated that the methods proposed in this study could be used for the reliable diagnosis of nitrogen quantity in sugarcane. Finally, the success of the field spectroscopy used for estimating the nutrient quality of sugarcane allowed an additional experiment using the polar orbiting hyperspectral data for the timely determination of crop nutrient status in rangelands without any requirement of prior
Pollution concentration estimates in ecologically important zones
Energy Technology Data Exchange (ETDEWEB)
Skiba, Y.N. [Mexico City Univ. (Mexico). Center for Atmospheric Sciences
1995-12-31
Method based on using the pollutant transport equation and the adjoint technique is described here for estimating the pollutant concentration level in ecologically important zones. The method directly relates the pollution level in such zones with the power of the pollution sources and the initial pollution field. Assuming that the wind or current velocities are known (from climatic data or dynamic model), the main and adjoint pollutant transport equations can be considered in a limited area to solve such theoretically and practically important problems as: (1) optimal location of new industries in a given region with the aim to minimize the pollution concentration in certain ecologically important zones, (2) optimization of emissions from operating industries, (3) detection of the plants violating sanitary regulations, (4) analysis of the emissions coming from the vehicle traffic (such emissions can be included in the model by means of the linear pollution sources located along the main roadways), (5) estimation of the oil pollution in various ecologically important oceanic (sea) zones in case of accident with the oil tanker, (6) evaluation of the sea water desalination level in estuary regions, and others. These equations considered in a spherical shell domain can also be applied to the problems of transporting the pollutants from a huge industrial complex, or from the zone of an ecological catastrophe similar to the Chernobyl one
Pollution concentration estimates in ecologically important zones
Energy Technology Data Exchange (ETDEWEB)
Skiba, Y N [Mexico City Univ. (Mexico). Center for Atmospheric Sciences
1996-12-31
Method based on using the pollutant transport equation and the adjoint technique is described here for estimating the pollutant concentration level in ecologically important zones. The method directly relates the pollution level in such zones with the power of the pollution sources and the initial pollution field. Assuming that the wind or current velocities are known (from climatic data or dynamic model), the main and adjoint pollutant transport equations can be considered in a limited area to solve such theoretically and practically important problems as: (1) optimal location of new industries in a given region with the aim to minimize the pollution concentration in certain ecologically important zones, (2) optimization of emissions from operating industries, (3) detection of the plants violating sanitary regulations, (4) analysis of the emissions coming from the vehicle traffic (such emissions can be included in the model by means of the linear pollution sources located along the main roadways), (5) estimation of the oil pollution in various ecologically important oceanic (sea) zones in case of accident with the oil tanker, (6) evaluation of the sea water desalination level in estuary regions, and others. These equations considered in a spherical shell domain can also be applied to the problems of transporting the pollutants from a huge industrial complex, or from the zone of an ecological catastrophe similar to the Chernobyl one
Measurement Error Estimation for Capacitive Voltage Transformer by Insulation Parameters
Directory of Open Access Journals (Sweden)
Bin Chen
2017-03-01
Full Text Available Measurement errors of a capacitive voltage transformer (CVT are relevant to its equivalent parameters for which its capacitive divider contributes the most. In daily operation, dielectric aging, moisture, dielectric breakdown, etc., it will exert mixing effects on a capacitive divider’s insulation characteristics, leading to fluctuation in equivalent parameters which result in the measurement error. This paper proposes an equivalent circuit model to represent a CVT which incorporates insulation characteristics of a capacitive divider. After software simulation and laboratory experiments, the relationship between measurement errors and insulation parameters is obtained. It indicates that variation of insulation parameters in a CVT will cause a reasonable measurement error. From field tests and calculation, equivalent capacitance mainly affects magnitude error, while dielectric loss mainly affects phase error. As capacitance changes 0.2%, magnitude error can reach −0.2%. As dielectric loss factor changes 0.2%, phase error can reach 5′. An increase of equivalent capacitance and dielectric loss factor in the high-voltage capacitor will cause a positive real power measurement error. An increase of equivalent capacitance and dielectric loss factor in the low-voltage capacitor will cause a negative real power measurement error.
About Error in Measuring Oxygen Concentration by Solid-Electrolyte Sensors
Directory of Open Access Journals (Sweden)
V. I. Nazarov
2008-01-01
Full Text Available The paper evaluates additional errors while measuring oxygen concentration in a gas mixture by a solid-electrolyte cell. Experimental dependences of additional errors caused by changes in temperature in a sensor zone, discharge of gas mixture supplied to a sensor zone, partial pressure in the gas mixture and fluctuations in oxygen concentrations in the air.
Chang, Howard H; Peng, Roger D; Dominici, Francesca
2011-10-01
In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 μm. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.
A Posteriori Error Estimation for Finite Element Methods and Iterative Linear Solvers
Energy Technology Data Exchange (ETDEWEB)
Melboe, Hallgeir
2001-10-01
This thesis addresses a posteriori error estimation for finite element methods and iterative linear solvers. Adaptive finite element methods have gained a lot of popularity over the last decades due to their ability to produce accurate results with limited computer power. In these methods a posteriori error estimates play an essential role. Not only do they give information about how large the total error is, they also indicate which parts of the computational domain should be given a more sophisticated treatment in order to reduce the error. A posteriori error estimates are traditionally aimed at estimating the global error, but more recently so called goal oriented error estimators have been shown a lot of interest. The name reflects the fact that they estimate the error in user-defined local quantities. In this thesis the main focus is on global error estimators for highly stretched grids and goal oriented error estimators for flow problems on regular grids. Numerical methods for partial differential equations, such as finite element methods and other similar techniques, typically result in a linear system of equations that needs to be solved. Usually such systems are solved using some iterative procedure which due to a finite number of iterations introduces an additional error. Most such algorithms apply the residual in the stopping criterion, whereas the control of the actual error may be rather poor. A secondary focus in this thesis is on estimating the errors that are introduced during this last part of the solution procedure. The thesis contains new theoretical results regarding the behaviour of some well known, and a few new, a posteriori error estimators for finite element methods on anisotropic grids. Further, a goal oriented strategy for the computation of forces in flow problems is devised and investigated. Finally, an approach for estimating the actual errors associated with the iterative solution of linear systems of equations is suggested. (author)
On the mean squared error of the ridge estimator of the covariance and precision matrix
van Wieringen, Wessel N.
2017-01-01
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates the maximum likelihood regression estimator in terms of the mean squared error. Analogous results for the ridge maximum likelihood estimators of covariance and precision matrix are presented.
Remote one-qubit information concentration and decoding of operator quantum error-correction codes
International Nuclear Information System (INIS)
Hsu Liyi
2007-01-01
We propose the general scheme of remote one-qubit information concentration. To achieve the task, the Bell-correlated mixed states are exploited. In addition, the nonremote one-qubit information concentration is equivalent to the decoding of the quantum error-correction code. Here we propose how to decode the stabilizer codes. In particular, the proposed scheme can be used for the operator quantum error-correction codes. The encoded state can be recreated on the errorless qubit, regardless how many bit-flip errors and phase-flip errors have occurred
Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A
2017-11-01
Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)
Adler, Robert; Gu, Guojun; Huffman, George
2012-01-01
A procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within +/- 50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation s of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (s/m, where m is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%-15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (s) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a
Energy Technology Data Exchange (ETDEWEB)
Ju, Lili; Tian, Li; Wang, Desheng
2008-10-31
In this paper, we present a residual-based a posteriori error estimate for the finite volume discretization of steady convection– diffusion–reaction equations defined on surfaces in R3, which are often implicitly represented as level sets of smooth functions. Reliability and efficiency of the proposed a posteriori error estimator are rigorously proved. Numerical experiments are also conducted to verify the theoretical results and demonstrate the robustness of the error estimator.
Directory of Open Access Journals (Sweden)
Yun Shi
2014-01-01
Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.
To Error Problem Concerning Measuring Concentration of Carbon Oxide by Thermo-Chemical Sen
Directory of Open Access Journals (Sweden)
V. I. Nazarov
2007-01-01
Full Text Available The paper gives additional errors in respect of measuring concentration of carbon oxide by thermo-chemical sensors. A number of analytical expressions for calculation of error data and corrections for environmental factor deviations from admissible ones have been obtained in the paper
Eppenhof, Koen A J; Pluim, Josien P W
2018-04-01
Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D convolutional neural network that learns to estimate registration errors from a pair of image patches. By applying the network to patches centered around every voxel, we construct registration error maps. The network is trained using a set of representative images that have been synthetically transformed to construct a set of image pairs with known deformations. The method is evaluated on deformable registrations of inhale-exhale pairs of thoracic CT scans. Using ground truth target registration errors on manually annotated landmarks, we evaluate the method's ability to estimate local registration errors. Estimation of full domain error maps is evaluated using a gold standard approach. The two evaluation approaches show that we can train the network to robustly estimate registration errors in a predetermined range, with subvoxel accuracy. We achieved a root-mean-square deviation of 0.51 mm from gold standard registration errors and of 0.66 mm from ground truth landmark registration errors.
Száz, Dénes; Farkas, Alexandra; Barta, András; Kretzer, Balázs; Egri, Ádám; Horváth, Gábor
2016-07-01
The theory of sky-polarimetric Viking navigation has been widely accepted for decades without any information about the accuracy of this method. Previously, we have measured the accuracy of the first and second steps of this navigation method in psychophysical laboratory and planetarium experiments. Now, we have tested the accuracy of the third step in a planetarium experiment, assuming that the first and second steps are errorless. Using the fists of their outstretched arms, 10 test persons had to estimate the elevation angles (measured in numbers of fists and fingers) of black dots (representing the position of the occluded Sun) projected onto the planetarium dome. The test persons performed 2400 elevation estimations, 48% of which were more accurate than ±1°. We selected three test persons with the (i) largest and (ii) smallest elevation errors and (iii) highest standard deviation of the elevation error. From the errors of these three persons, we calculated their error function, from which the North errors (the angles with which they deviated from the geographical North) were determined for summer solstice and spring equinox, two specific dates of the Viking sailing period. The range of possible North errors Δ ω N was the lowest and highest at low and high solar elevations, respectively. At high elevations, the maximal Δ ω N was 35.6° and 73.7° at summer solstice and 23.8° and 43.9° at spring equinox for the best and worst test person (navigator), respectively. Thus, the best navigator was twice as good as the worst one. At solstice and equinox, high elevations occur the most frequently during the day, thus high North errors could occur more frequently than expected before. According to our findings, the ideal periods for sky-polarimetric Viking navigation are immediately after sunrise and before sunset, because the North errors are the lowest at low solar elevations.
A residual-based a posteriori error estimator for single-phase Darcy flow in fractured porous media
Chen, Huangxin; Sun, Shuyu
2016-01-01
for the problem with non-intersecting fractures. The reliability and efficiency of the a posteriori error estimator are established for the error measured in an energy norm. Numerical results verifying the robustness of the proposed a posteriori error estimator
Subroutine library for error estimation of matrix computation (Ver. 1.0)
International Nuclear Information System (INIS)
Ichihara, Kiyoshi; Shizawa, Yoshihisa; Kishida, Norio
1999-03-01
'Subroutine Library for Error Estimation of Matrix Computation' is a subroutine library which aids the users in obtaining the error ranges of the linear system's solutions or the Hermitian matrices' eigenvalues. This library contains routines for both sequential computers and parallel computers. The subroutines for linear system error estimation calculate norms of residual vectors, matrices's condition numbers, error bounds of solutions and so on. The subroutines for error estimation of Hermitian matrix eigenvalues derive the error ranges of the eigenvalues according to the Korn-Kato's formula. The test matrix generators supply the matrices appeared in the mathematical research, the ones randomly generated and the ones appeared in the application programs. This user's manual contains a brief mathematical background of error analysis on linear algebra and usage of the subroutines. (author)
Comparison of bipolar vs. tripolar concentric ring electrode Laplacian estimates.
Besio, W; Aakula, R; Dai, W
2004-01-01
Potentials on the body surface from the heart are of a spatial and temporal function. The 12-lead electrocardiogram (ECG) provides useful global temporal assessment, but it yields limited spatial information due to the smoothing effect caused by the volume conductor. The smoothing complicates identification of multiple simultaneous bioelectrical events. In an attempt to circumvent the smoothing problem, some researchers used a five-point method (FPM) to numerically estimate the analytical solution of the Laplacian with an array of monopolar electrodes. The FPM is generalized to develop a bi-polar concentric ring electrode system. We have developed a new Laplacian ECG sensor, a trielectrode sensor, based on a nine-point method (NPM) numerical approximation of the analytical Laplacian. For a comparison, the NPM, FPM and compact NPM were calculated over a 400 x 400 mesh with 1/400 spacing. Tri and bi-electrode sensors were also simulated and their Laplacian estimates were compared against the analytical Laplacian. We found that tri-electrode sensors have a much-improved accuracy with significantly less relative and maximum errors in estimating the Laplacian operator. Apart from the higher accuracy, our new electrode configuration will allow better localization of the electrical activity of the heart than bi-electrode configurations.
Estimations of Nitrogen Concentration in Sugarcane Using Hyperspectral Imagery
Directory of Open Access Journals (Sweden)
Poonsak Miphokasap
2018-04-01
Full Text Available This study aims to estimate the spatial variation of sugarcane Canopy Nitrogen Concentration (CNC using spectral data, which were measured from a spaceborne hyperspectral image. Stepwise Multiple Linear Regression (SMLR and Support Vector Regression (SVR were applied to calibrate and validate the CNC estimation models. The raw spectral reflectance was transformed into a First-Derivative Spectrum (FDS and absorption features to remove the spectral noise and finally used as input variables. The results indicate that the estimation models developed by non-linear SVR based Radial Basis Function (RBF kernel yield the higher correlation coefficient with CNC compared with the models computed by SMLR. The best model shows the coefficient of determination value of 0.78 and Root Mean Square Error (RMSE value of 0.035% nitrogen. The narrow sensitive spectral wavelengths for quantifying nitrogen content in the combined cultivar environments existed mainly in the electromagnetic spectrum of the visible-red, longer portion of red edge, shortwave infrared regions and far-near infrared. The most important conclusion from this experiment is that spectral signals from the space hyperspectral data contain the meaningful information for quantifying sugarcane CNC across larger geographic areas. The nutrient deficient areas could be corrected by applying suitable farm management.
Holmes, John B; Dodds, Ken G; Lee, Michael A
2017-03-02
An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.
Estimating and localizing the algebraic and total numerical errors using flux reconstructions
Czech Academy of Sciences Publication Activity Database
Papež, Jan; Strakoš, Z.; Vohralík, M.
2018-01-01
Roč. 138, č. 3 (2018), s. 681-721 ISSN 0029-599X R&D Projects: GA ČR GA13-06684S Grant - others:GA MŠk(CZ) LL1202 Institutional support: RVO:67985807 Keywords : numerical solution of partial differential equations * finite element method * a posteriori error estimation * algebraic error * discretization error * stopping criteria * spatial distribution of the error Subject RIV: BA - General Mathematics Impact factor: 2.152, year: 2016
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
Du, Shaohong; Sun, Shuyu; Xie, Xiaoping
2015-01-01
A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
Du, Shaohong
2015-10-26
A novel residual-type a posteriori error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimensions. The derived a posteriori error estimator for the velocity and pressure error in L-norm consists of discretization and quadrature indicators, and is shown to be reliable and efficient. The main tools of analysis are a locally postprocessed approximation to the pressure solution of an auxiliary problem and a quadrature error estimate. Numerical experiments are presented to illustrate the competitive behavior of the estimator.
Kim, ChangHwan; Tamborini, Christopher R.
2012-01-01
Few studies have considered how earnings inequality estimates may be affected by measurement error in self-reported earnings in surveys. Utilizing restricted-use data that links workers in the Survey of Income and Program Participation with their W-2 earnings records, we examine the effect of measurement error on estimates of racial earnings…
Ambros Berger; Thomas Gschwantner; Ronald E. McRoberts; Klemens. Schadauer
2014-01-01
National forest inventories typically estimate individual tree volumes using models that rely on measurements of predictor variables such as tree height and diameter, both of which are subject to measurement error. The aim of this study was to quantify the impacts of these measurement errors on the uncertainty of the model-based tree stem volume estimates. The impacts...
Error estimates for ice discharge calculated using the flux gate approach
Navarro, F. J.; Sánchez Gámez, P.
2017-12-01
Ice discharge to the ocean is usually estimated using the flux gate approach, in which ice flux is calculated through predefined flux gates close to the marine glacier front. However, published results usually lack a proper error estimate. In the flux calculation, both errors in cross-sectional area and errors in velocity are relevant. While for estimating the errors in velocity there are well-established procedures, the calculation of the error in the cross-sectional area requires the availability of ground penetrating radar (GPR) profiles transverse to the ice-flow direction. In this contribution, we use IceBridge operation GPR profiles collected in Ellesmere and Devon Islands, Nunavut, Canada, to compare the cross-sectional areas estimated using various approaches with the cross-sections estimated from GPR ice-thickness data. These error estimates are combined with those for ice-velocities calculated from Sentinel-1 SAR data, to get the error in ice discharge. Our preliminary results suggest, regarding area, that the parabolic cross-section approaches perform better than the quartic ones, which tend to overestimate the cross-sectional area for flight lines close to the central flowline. Furthermore, the results show that regional ice-discharge estimates made using parabolic approaches provide reasonable results, but estimates for individual glaciers can have large errors, up to 20% in cross-sectional area.
Eppenhof, K.A.J.; Pluim, J.P.W.
2018-01-01
Error estimation in nonlinear medical image registration is a nontrivial problem that is important for validation of registration methods. We propose a supervised method for estimation of registration errors in nonlinear registration of three-dimensional (3-D) images. The method is based on a 3-D
Eppenhof, Koen A.J.; Pluim, Josien P.W.; Styner, M.A.; Angelini, E.D.
2017-01-01
Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation
Performances of estimators of linear auto-correlated error model ...
African Journals Online (AJOL)
The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...
A note on estimating errors from the likelihood function
International Nuclear Information System (INIS)
Barlow, Roger
2005-01-01
The points at which the log likelihood falls by 12 from its maximum value are often used to give the 'errors' on a result, i.e. the 68% central confidence interval. The validity of this is examined for two simple cases: a lifetime measurement and a Poisson measurement. Results are compared with the exact Neyman construction and with the simple Bartlett approximation. It is shown that the accuracy of the log likelihood method is poor, and the Bartlett construction explains why it is flawed
LiDAR error estimation with WAsP engineering
DEFF Research Database (Denmark)
Bingöl, Ferhat; Mann, Jakob; Foussekis, D.
2008-01-01
The LiDAR measurements, vertical wind profile in any height between 10 to 150m, are based on assumption that the measured wind is a product of a homogenous wind. In reality there are many factors affecting the wind on each measurement point which the terrain plays the main role. To model Li......DAR measurements and predict possible error in different wind directions for a certain terrain we have analyzed two experiment data sets from Greece. In both sites LiDAR and met. mast data have been collected and the same conditions are simulated with Riso/DTU software, WAsP Engineering 2.0. Finally measurement...
Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters.
Song, Jin Woo; Park, Chan Gook
2018-04-21
An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.
Institute of Scientific and Technical Information of China (English)
Xiaogu ZHENG
2009-01-01
An adaptive estimation of forecast error covariance matrices is proposed for Kalman filtering data assimilation. A forecast error covariance matrix is initially estimated using an ensemble of perturbation forecasts. This initially estimated matrix is then adjusted with scale parameters that are adaptively estimated by minimizing -2log-likelihood of observed-minus-forecast residuals. The proposed approach could be applied to Kalman filtering data assimilation with imperfect models when the model error statistics are not known. A simple nonlinear model (Burgers' equation model) is used to demonstrate the efficacy of the proposed approach.
Errors and parameter estimation in precipitation-runoff modeling: 1. Theory
Troutman, Brent M.
1985-01-01
Errors in complex conceptual precipitation-runoff models may be analyzed by placing them into a statistical framework. This amounts to treating the errors as random variables and defining the probabilistic structure of the errors. By using such a framework, a large array of techniques, many of which have been presented in the statistical literature, becomes available to the modeler for quantifying and analyzing the various sources of error. A number of these techniques are reviewed in this paper, with special attention to the peculiarities of hydrologic models. Known methodologies for parameter estimation (calibration) are particularly applicable for obtaining physically meaningful estimates and for explaining how bias in runoff prediction caused by model error and input error may contribute to bias in parameter estimation.
Estimation of suspended sediment concentration by acoustic ...
African Journals Online (AJOL)
concentration of sediments such as glass spheres or sand. However, the acoustic properties of natural sediments vary and depend on many parameters such as particle size, shape, mineralogy and distribution of those parameters in sample. Therefore, this study was conducted to determine the possibility of soil sediment ...
A posteriori error estimator and AMR for discrete ordinates nodal transport methods
International Nuclear Information System (INIS)
Duo, Jose I.; Azmy, Yousry Y.; Zikatanov, Ludmil T.
2009-01-01
In the development of high fidelity transport solvers, optimization of the use of available computational resources and access to a tool for assessing quality of the solution are key to the success of large-scale nuclear systems' simulation. In this regard, error control provides the analyst with a confidence level in the numerical solution and enables for optimization of resources through Adaptive Mesh Refinement (AMR). In this paper, we derive an a posteriori error estimator based on the nodal solution of the Arbitrarily High Order Transport Method of the Nodal type (AHOT-N). Furthermore, by making assumptions on the regularity of the solution, we represent the error estimator as a function of computable volume and element-edges residuals. The global L 2 error norm is proved to be bound by the estimator. To lighten the computational load, we present a numerical approximation to the aforementioned residuals and split the global norm error estimator into local error indicators. These indicators are used to drive an AMR strategy for the spatial discretization. However, the indicators based on forward solution residuals alone do not bound the cell-wise error. The estimator and AMR strategy are tested in two problems featuring strong heterogeneity and highly transport streaming regime with strong flux gradients. The results show that the error estimator indeed bounds the global error norms and that the error indicator follows the cell-error's spatial distribution pattern closely. The AMR strategy proves beneficial to optimize resources, primarily by reducing the number of unknowns solved for to achieve prescribed solution accuracy in global L 2 error norm. Likewise, AMR achieves higher accuracy compared to uniform refinement when resolving sharp flux gradients, for the same number of unknowns
International Nuclear Information System (INIS)
Comer, K.; Gaddy, C.D.; Seaver, D.A.; Stillwell, W.G.
1985-01-01
The US Nuclear Regulatory Commission and Sandia National Laboratories sponsored a project to evaluate psychological scaling techniques for use in generating estimates of human error probabilities. The project evaluated two techniques: direct numerical estimation and paired comparisons. Expert estimates were found to be consistent across and within judges. Convergent validity was good, in comparison to estimates in a handbook of human reliability. Predictive validity could not be established because of the lack of actual relative frequencies of error (which will be a difficulty inherent in validation of any procedure used to estimate HEPs). Application of expert estimates in probabilistic risk assessment and in human factors is discussed
Improved estimates of coordinate error for molecular replacement
International Nuclear Information System (INIS)
Oeffner, Robert D.; Bunkóczi, Gábor; McCoy, Airlie J.; Read, Randy J.
2013-01-01
A function for estimating the effective root-mean-square deviation in coordinates between two proteins has been developed that depends on both the sequence identity and the size of the protein and is optimized for use with molecular replacement in Phaser. A top peak translation-function Z-score of over 8 is found to be a reliable metric of when molecular replacement has succeeded. The estimate of the root-mean-square deviation (r.m.s.d.) in coordinates between the model and the target is an essential parameter for calibrating likelihood functions for molecular replacement (MR). Good estimates of the r.m.s.d. lead to good estimates of the variance term in the likelihood functions, which increases signal to noise and hence success rates in the MR search. Phaser has hitherto used an estimate of the r.m.s.d. that only depends on the sequence identity between the model and target and which was not optimized for the MR likelihood functions. Variance-refinement functionality was added to Phaser to enable determination of the effective r.m.s.d. that optimized the log-likelihood gain (LLG) for a correct MR solution. Variance refinement was subsequently performed on a database of over 21 000 MR problems that sampled a range of sequence identities, protein sizes and protein fold classes. Success was monitored using the translation-function Z-score (TFZ), where a TFZ of 8 or over for the top peak was found to be a reliable indicator that MR had succeeded for these cases with one molecule in the asymmetric unit. Good estimates of the r.m.s.d. are correlated with the sequence identity and the protein size. A new estimate of the r.m.s.d. that uses these two parameters in a function optimized to fit the mean of the refined variance is implemented in Phaser and improves MR outcomes. Perturbing the initial estimate of the r.m.s.d. from the mean of the distribution in steps of standard deviations of the distribution further increases MR success rates
PERFORMANCE OF THE ZERO FORCING PRECODING MIMO BROADCAST SYSTEMS WITH CHANNEL ESTIMATION ERRORS
Institute of Scientific and Technical Information of China (English)
Wang Jing; Liu Zhanli; Wang Yan; You Xiaohu
2007-01-01
In this paper, the effect of channel estimation errors upon the Zero Forcing (ZF) precoding Multiple Input Multiple Output Broadcast (MIMO BC) systems was studied. Based on the two kinds of Gaussian estimation error models, the performance analysis is conducted under different power allocation strategies. Analysis and simulation show that if the covariance of channel estimation errors is independent of the received Signal to Noise Ratio (SNR), imperfect channel knowledge deteriorates the sum capacity and the Bit Error Rate (BER) performance severely. However, under the situation of orthogonal training and the Minimum Mean Square Error (MMSE) channel estimation, the sum capacity and BER performance are consistent with those of the perfect Channel State Information (CSI)with only a performance degradation.
Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors
DEFF Research Database (Denmark)
Nguyen, Chuyen T.; Hayashi, Kazunori; Kaneko, Megumi
2013-01-01
Abstract Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio...... is evaluated under dierent system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol. Keywords RFID tag cardinality estimation maximum likelihood detection error...
Measurement Error in Income and Schooling and the Bias of Linear Estimators
DEFF Research Database (Denmark)
Bingley, Paul; Martinello, Alessandro
2017-01-01
and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators......We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing...
Sandberg, Mattias
2015-01-07
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with log normal distributed diffusion coefficients, e.g. modelling ground water flow. Typical models use log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. This talk will address how the total error can be estimated by the computable error.
Hall, Eric
2016-01-09
The Monte Carlo (and Multi-level Monte Carlo) finite element method can be used to approximate observables of solutions to diffusion equations with lognormal distributed diffusion coefficients, e.g. modeling ground water flow. Typical models use lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible and can be larger than the computable low frequency error. We address how the total error can be estimated by the computable error.
On the Estimation of Standard Errors in Cognitive Diagnosis Models
Philipp, Michel; Strobl, Carolin; de la Torre, Jimmy; Zeileis, Achim
2018-01-01
Cognitive diagnosis models (CDMs) are an increasingly popular method to assess mastery or nonmastery of a set of fine-grained abilities in educational or psychological assessments. Several inference techniques are available to quantify the uncertainty of model parameter estimates, to compare different versions of CDMs, or to check model…
Gap filling strategies and error in estimating annual soil respiration
Soil respiration (Rsoil) is one of the largest CO2 fluxes in the global carbon (C) cycle. Estimation of annual Rsoil requires extrapolation of survey measurements or gap-filling of automated records to produce a complete time series. While many gap-filling methodologies have been employed, there is ...
Nonparametric Estimation of Regression Parameters in Measurement Error Models
Czech Academy of Sciences Publication Activity Database
Ehsanes Saleh, A.K.M.D.; Picek, J.; Kalina, Jan
2009-01-01
Roč. 67, č. 2 (2009), s. 177-200 ISSN 0026-1424 Grant - others:GA AV ČR(CZ) IAA101120801; GA MŠk(CZ) LC06024 Institutional research plan: CEZ:AV0Z10300504 Keywords : asymptotic relative efficiency(ARE) * asymptotic theory * emaculate mode * Me model * R-estimation * Reliabilty ratio(RR) Subject RIV: BB - Applied Statistics, Operational Research
Zollanvari, Amin
2013-05-24
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Demonstration Integrated Knowledge-Based System for Estimating Human Error Probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, Jack L.
1999-04-21
Human Reliability Analysis (HRA) is currently comprised of at least 40 different methods that are used to analyze, predict, and evaluate human performance in probabilistic terms. Systematic HRAs allow analysts to examine human-machine relationships, identify error-likely situations, and provide estimates of relative frequencies for human errors on critical tasks, highlighting the most beneficial areas for system improvements. Unfortunately, each of HRA's methods has a different philosophical approach, thereby producing estimates of human error probabilities (HEPs) that area better or worse match to the error likely situation of interest. Poor selection of methodology, or the improper application of techniques can produce invalid HEP estimates, where that erroneous estimation of potential human failure could have potentially severe consequences in terms of the estimated occurrence of injury, death, and/or property damage.
Zollanvari, Amin; Genton, Marc G.
2013-01-01
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model
Rizvi, Farheen
2016-01-01
Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.
Component Analysis of Errors on PERSIANN Precipitation Estimates over Urmia Lake Basin, IRAN
Ghajarnia, N.; Daneshkar Arasteh, P.; Liaghat, A. M.; Araghinejad, S.
2016-12-01
In this study, PERSIANN daily dataset is evaluated from 2000 to 2011 in 69 pixels over Urmia Lake basin in northwest of Iran. Different analytical approaches and indexes are used to examine PERSIANN precision in detection and estimation of rainfall rate. The residuals are decomposed into Hit, Miss and FA estimation biases while continues decomposition of systematic and random error components are also analyzed seasonally and categorically. New interpretation of estimation accuracy named "reliability on PERSIANN estimations" is introduced while the changing manners of existing categorical/statistical measures and error components are also seasonally analyzed over different rainfall rate categories. This study yields new insights into the nature of PERSIANN errors over Urmia lake basin as a semi-arid region in the middle-east, including the followings: - The analyzed contingency table indexes indicate better detection precision during spring and fall. - A relatively constant level of error is generally observed among different categories. The range of precipitation estimates at different rainfall rate categories is nearly invariant as a sign for the existence of systematic error. - Low level of reliability is observed on PERSIANN estimations at different categories which are mostly associated with high level of FA error. However, it is observed that as the rate of precipitation increase, the ability and precision of PERSIANN in rainfall detection also increases. - The systematic and random error decomposition in this area shows that PERSIANN has more difficulty in modeling the system and pattern of rainfall rather than to have bias due to rainfall uncertainties. The level of systematic error also considerably increases in heavier rainfalls. It is also important to note that PERSIANN error characteristics at each season varies due to the condition and rainfall patterns of that season which shows the necessity of seasonally different approach for the calibration of
Estimation of the human error probabilities in the human reliability analysis
International Nuclear Information System (INIS)
Liu Haibin; He Xuhong; Tong Jiejuan; Shen Shifei
2006-01-01
Human error data is an important issue of human reliability analysis (HRA). Using of Bayesian parameter estimation, which can use multiple information, such as the historical data of NPP and expert judgment data to modify the human error data, could get the human error data reflecting the real situation of NPP more truly. This paper, using the numeric compute program developed by the authors, presents some typical examples to illustrate the process of the Bayesian parameter estimation in HRA and discusses the effect of different modification data on the Bayesian parameter estimation. (authors)
DEFF Research Database (Denmark)
Voigt, Andreas Jauernik; Santos, Ilmar
2012-01-01
to ∼ 20% of the nominal air gap the force estimation error is found to be reduced by the linearized force equation as compared to the quadratic force equation, which is supported by experimental results. Additionally the FE model is employed in a comparative study of the force estimation error behavior...... of AMBs by embedding Hall sensors instead of mounting these directly on the pole surfaces, force estimation errors are investigated both numerically and experimentally. A linearized version of the conventionally applied quadratic correspondence between measured Hall voltage and applied AMB force...
A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem
Delaigle, Aurore
2009-03-01
Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.
On systematic and statistic errors in radionuclide mass activity estimation procedure
International Nuclear Information System (INIS)
Smelcerovic, M.; Djuric, G.; Popovic, D.
1989-01-01
One of the most important requirements during nuclear accidents is the fast estimation of the mass activity of the radionuclides that suddenly and without control reach the environment. The paper points to systematic errors in the procedures of sampling, sample preparation and measurement itself, that in high degree contribute to total mass activity evaluation error. Statistic errors in gamma spectrometry as well as in total mass alpha and beta activity evaluation are also discussed. Beside, some of the possible sources of errors in the partial mass activity evaluation for some of the radionuclides are presented. The contribution of the errors in the total mass activity evaluation error is estimated and procedures that could possibly reduce it are discussed (author)
International Nuclear Information System (INIS)
Kim, J G; Liu, H
2007-01-01
Near-infrared spectroscopy or imaging has been extensively applied to various biomedical applications since it can detect the concentrations of oxyhaemoglobin (HbO 2 ), deoxyhaemoglobin (Hb) and total haemoglobin (Hb total ) from deep tissues. To quantify concentrations of these haemoglobin derivatives, the extinction coefficient values of HbO 2 and Hb have to be employed. However, it was not well recognized among researchers that small differences in extinction coefficients could cause significant errors in quantifying the concentrations of haemoglobin derivatives. In this study, we derived equations to estimate errors of haemoglobin derivatives caused by the variation of haemoglobin extinction coefficients. To prove our error analysis, we performed experiments using liquid-tissue phantoms containing 1% Intralipid in a phosphate-buffered saline solution. The gas intervention of pure oxygen was given in the solution to examine the oxygenation changes in the phantom, and 3 mL of human blood was added twice to show the changes in [Hb total ]. The error calculation has shown that even a small variation (0.01 cm -1 mM -1 ) in extinction coefficients can produce appreciable relative errors in quantification of Δ[HbO 2 ], Δ[Hb] and Δ[Hb total ]. We have also observed that the error of Δ[Hb total ] is not always larger than those of Δ[HbO 2 ] and Δ[Hb]. This study concludes that we need to be aware of any variation in haemoglobin extinction coefficients, which could result from changes in temperature, and to utilize corresponding animal's haemoglobin extinction coefficients for the animal experiments, in order to obtain more accurate values of Δ[HbO 2 ], Δ[Hb] and Δ[Hb total ] from in vivo tissue measurements
Kim, J. G.; Liu, H.
2007-10-01
Near-infrared spectroscopy or imaging has been extensively applied to various biomedical applications since it can detect the concentrations of oxyhaemoglobin (HbO2), deoxyhaemoglobin (Hb) and total haemoglobin (Hbtotal) from deep tissues. To quantify concentrations of these haemoglobin derivatives, the extinction coefficient values of HbO2 and Hb have to be employed. However, it was not well recognized among researchers that small differences in extinction coefficients could cause significant errors in quantifying the concentrations of haemoglobin derivatives. In this study, we derived equations to estimate errors of haemoglobin derivatives caused by the variation of haemoglobin extinction coefficients. To prove our error analysis, we performed experiments using liquid-tissue phantoms containing 1% Intralipid in a phosphate-buffered saline solution. The gas intervention of pure oxygen was given in the solution to examine the oxygenation changes in the phantom, and 3 mL of human blood was added twice to show the changes in [Hbtotal]. The error calculation has shown that even a small variation (0.01 cm-1 mM-1) in extinction coefficients can produce appreciable relative errors in quantification of Δ[HbO2], Δ[Hb] and Δ[Hbtotal]. We have also observed that the error of Δ[Hbtotal] is not always larger than those of Δ[HbO2] and Δ[Hb]. This study concludes that we need to be aware of any variation in haemoglobin extinction coefficients, which could result from changes in temperature, and to utilize corresponding animal's haemoglobin extinction coefficients for the animal experiments, in order to obtain more accurate values of Δ[HbO2], Δ[Hb] and Δ[Hbtotal] from in vivo tissue measurements.
Energy Technology Data Exchange (ETDEWEB)
Kim, J G; Liu, H [Joint Graduate Program in Biomedical Engineering, University of Texas at Arlington/University of Texas Southwestern Medical Center at Dallas, Arlington, TX 76019 (United States)
2007-10-21
Near-infrared spectroscopy or imaging has been extensively applied to various biomedical applications since it can detect the concentrations of oxyhaemoglobin (HbO{sub 2}), deoxyhaemoglobin (Hb) and total haemoglobin (Hb{sub total}) from deep tissues. To quantify concentrations of these haemoglobin derivatives, the extinction coefficient values of HbO{sub 2} and Hb have to be employed. However, it was not well recognized among researchers that small differences in extinction coefficients could cause significant errors in quantifying the concentrations of haemoglobin derivatives. In this study, we derived equations to estimate errors of haemoglobin derivatives caused by the variation of haemoglobin extinction coefficients. To prove our error analysis, we performed experiments using liquid-tissue phantoms containing 1% Intralipid in a phosphate-buffered saline solution. The gas intervention of pure oxygen was given in the solution to examine the oxygenation changes in the phantom, and 3 mL of human blood was added twice to show the changes in [Hb{sub total}]. The error calculation has shown that even a small variation (0.01 cm{sup -1} mM{sup -1}) in extinction coefficients can produce appreciable relative errors in quantification of {delta}[HbO{sub 2}], {delta}[Hb] and {delta}[Hb{sub total}]. We have also observed that the error of {delta}[Hb{sub total}] is not always larger than those of {delta}[HbO{sub 2}] and {delta}[Hb]. This study concludes that we need to be aware of any variation in haemoglobin extinction coefficients, which could result from changes in temperature, and to utilize corresponding animal's haemoglobin extinction coefficients for the animal experiments, in order to obtain more accurate values of {delta}[HbO{sub 2}], {delta}[Hb] and {delta}[Hb{sub total}] from in vivo tissue measurements.
BAYES-HEP: Bayesian belief networks for estimation of human error probability
International Nuclear Information System (INIS)
Karthick, M.; Senthil Kumar, C.; Paul, Robert T.
2017-01-01
Human errors contribute a significant portion of risk in safety critical applications and methods for estimation of human error probability have been a topic of research for over a decade. The scarce data available on human errors and large uncertainty involved in the prediction of human error probabilities make the task difficult. This paper presents a Bayesian belief network (BBN) model for human error probability estimation in safety critical functions of a nuclear power plant. The developed model using BBN would help to estimate HEP with limited human intervention. A step-by-step illustration of the application of the method and subsequent evaluation is provided with a relevant case study and the model is expected to provide useful insights into risk assessment studies
A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates
Huang, Weizhang; Kamenski, Lennard; Lang, Jens
2010-03-01
A new anisotropic mesh adaptation strategy for finite element solution of elliptic differential equations is presented. It generates anisotropic adaptive meshes as quasi-uniform ones in some metric space, with the metric tensor being computed based on hierarchical a posteriori error estimates. A global hierarchical error estimate is employed in this study to obtain reliable directional information of the solution. Instead of solving the global error problem exactly, which is costly in general, we solve it iteratively using the symmetric Gauß-Seidel method. Numerical results show that a few GS iterations are sufficient for obtaining a reasonably good approximation to the error for use in anisotropic mesh adaptation. The new method is compared with several strategies using local error estimators or recovered Hessians. Numerical results are presented for a selection of test examples and a mathematical model for heat conduction in a thermal battery with large orthotropic jumps in the material coefficients.
Minimum Mean-Square Error Single-Channel Signal Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas
2008-01-01
This topic of this thesis is MMSE signal estimation for hearing aids when only one microphone is available. The research is relevant for noise reduction systems in hearing aids. To fully benefit from the amplification provided by a hearing aid, noise reduction functionality is important as hearin...... algorithm. Although performance of the two algorithms is found comparable then the particle filter algorithm is doing a much better job tracking the noise.......-impaired persons in some noisy situations need a higher signal to noise ratio for speech to be intelligible when compared to normal-hearing persons. In this thesis two different methods to approach the MMSE signal estimation problem is examined. The methods differ in the way that models for the signal and noise...... inference is performed by particle filtering. The speech model is a time-varying auto-regressive model reparameterized by formant frequencies and bandwidths. The noise is assumed non-stationary and white. Compared to the case of using the AR coefficients directly then it is found very beneficial to perform...
Bazile , Alban; Hachem , Elie; Larroya-Huguet , Juan-Carlos; Mesri , Youssef
2018-01-01
International audience; In this work, we present a new a posteriori error estimator based on the Variational Multiscale method for anisotropic adaptive fluid mechanics problems. The general idea is to combine the large scale error based on the solved part of the solution with the sub-mesh scale error based on the unresolved part of the solution. We compute the latter with two different methods: one using the stabilizing parameters and the other using bubble functions. We propose two different...
International Nuclear Information System (INIS)
Menelaou, Evdokia; Paul, Latoya T.; Perera, Surangi N.; Svoboda, Kurt R.
2015-01-01
Nicotine exposure during embryonic stages of development can affect many neurodevelopmental processes. In the developing zebrafish, exposure to nicotine was reported to cause axonal pathfinding errors in the later born secondary motoneurons (SMNs). These alterations in SMN axon morphology coincided with muscle degeneration at high nicotine concentrations (15–30 μM). Previous work showed that the paralytic mutant zebrafish known as sofa potato exhibited nicotine-induced effects onto SMN axons at these high concentrations but in the absence of any muscle deficits, indicating that pathfinding errors could occur independent of muscle effects. In this study, we used varying concentrations of nicotine at different developmental windows of exposure to specifically isolate its effects onto subpopulations of motoneuron axons. We found that nicotine exposure can affect SMN axon morphology in a dose-dependent manner. At low concentrations of nicotine, SMN axons exhibited pathfinding errors, in the absence of any nicotine-induced muscle abnormalities. Moreover, the nicotine exposure paradigms used affected the 3 subpopulations of SMN axons differently, but the dorsal projecting SMN axons were primarily affected. We then identified morphologically distinct pathfinding errors that best described the nicotine-induced effects on dorsal projecting SMN axons. To test whether SMN pathfinding was potentially influenced by alterations in the early born primary motoneuron (PMN), we performed dual labeling studies, where both PMN and SMN axons were simultaneously labeled with antibodies. We show that only a subset of the SMN axon pathfinding errors coincided with abnormal PMN axonal targeting in nicotine-exposed zebrafish. We conclude that nicotine exposure can exert differential effects depending on the levels of nicotine and developmental exposure window. - Highlights: • Embryonic nicotine exposure can specifically affect secondary motoneuron axons in a dose-dependent manner.
Energy Technology Data Exchange (ETDEWEB)
Menelaou, Evdokia; Paul, Latoya T. [Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 (United States); Perera, Surangi N. [Joseph J. Zilber School of Public Health, University of Wisconsin — Milwaukee, Milwaukee, WI 53205 (United States); Svoboda, Kurt R., E-mail: svobodak@uwm.edu [Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803 (United States); Joseph J. Zilber School of Public Health, University of Wisconsin — Milwaukee, Milwaukee, WI 53205 (United States)
2015-04-01
Nicotine exposure during embryonic stages of development can affect many neurodevelopmental processes. In the developing zebrafish, exposure to nicotine was reported to cause axonal pathfinding errors in the later born secondary motoneurons (SMNs). These alterations in SMN axon morphology coincided with muscle degeneration at high nicotine concentrations (15–30 μM). Previous work showed that the paralytic mutant zebrafish known as sofa potato exhibited nicotine-induced effects onto SMN axons at these high concentrations but in the absence of any muscle deficits, indicating that pathfinding errors could occur independent of muscle effects. In this study, we used varying concentrations of nicotine at different developmental windows of exposure to specifically isolate its effects onto subpopulations of motoneuron axons. We found that nicotine exposure can affect SMN axon morphology in a dose-dependent manner. At low concentrations of nicotine, SMN axons exhibited pathfinding errors, in the absence of any nicotine-induced muscle abnormalities. Moreover, the nicotine exposure paradigms used affected the 3 subpopulations of SMN axons differently, but the dorsal projecting SMN axons were primarily affected. We then identified morphologically distinct pathfinding errors that best described the nicotine-induced effects on dorsal projecting SMN axons. To test whether SMN pathfinding was potentially influenced by alterations in the early born primary motoneuron (PMN), we performed dual labeling studies, where both PMN and SMN axons were simultaneously labeled with antibodies. We show that only a subset of the SMN axon pathfinding errors coincided with abnormal PMN axonal targeting in nicotine-exposed zebrafish. We conclude that nicotine exposure can exert differential effects depending on the levels of nicotine and developmental exposure window. - Highlights: • Embryonic nicotine exposure can specifically affect secondary motoneuron axons in a dose-dependent manner.
An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.
Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan
2017-11-18
Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio
Harutyunyan, D.; Izsak, F.; van der Vegt, Jacobus J.W.; Bochev, Mikhail A.
For the adaptive solution of the Maxwell equations on three-dimensional domains with N´ed´elec edge finite element methods, we consider an implicit a posteriori error estimation technique. On each element of the tessellation an equation for the error is formulated and solved with a properly chosen
Effects of structural error on the estimates of parameters of dynamical systems
Hadaegh, F. Y.; Bekey, G. A.
1986-01-01
In this paper, the notion of 'near-equivalence in probability' is introduced for identifying a system in the presence of several error sources. Following some basic definitions, necessary and sufficient conditions for the identifiability of parameters are given. The effects of structural error on the parameter estimates for both the deterministic and stochastic cases are considered.
On the a priori estimation of collocation error covariance functions: a feasibility study
DEFF Research Database (Denmark)
Arabelos, D.N.; Forsberg, René; Tscherning, C.C.
2007-01-01
and the associated error covariance functions were conducted in the Arctic region north of 64 degrees latitude. The correlation between the known features of the data and the parameters variance and correlation length of the computed error covariance functions was estimated using multiple regression analysis...
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang; Alouini, Mohamed-Slim
2011-01-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over
Estimation of Uncertainty in Aerosol Concentration Measured by Aerosol Sampling System
Energy Technology Data Exchange (ETDEWEB)
Lee, Jong Chan; Song, Yong Jae; Jung, Woo Young; Lee, Hyun Chul; Kim, Gyu Tae; Lee, Doo Yong [FNC Technology Co., Yongin (Korea, Republic of)
2016-10-15
FNC Technology Co., Ltd has been developed test facilities for the aerosol generation, mixing, sampling and measurement under high pressure and high temperature conditions. The aerosol generation system is connected to the aerosol mixing system which injects SiO{sub 2}/ethanol mixture. In the sampling system, glass fiber membrane filter has been used to measure average mass concentration. Based on the experimental results using main carrier gas of steam and air mixture, the uncertainty estimation of the sampled aerosol concentration was performed by applying Gaussian error propagation law. FNC Technology Co., Ltd. has been developed the experimental facilities for the aerosol measurement under high pressure and high temperature. The purpose of the tests is to develop commercial test module for aerosol generation, mixing and sampling system applicable to environmental industry and safety related system in nuclear power plant. For the uncertainty calculation of aerosol concentration, the value of the sampled aerosol concentration is not measured directly, but must be calculated from other quantities. The uncertainty of the sampled aerosol concentration is a function of flow rates of air and steam, sampled mass, sampling time, condensed steam mass and its absolute errors. These variables propagate to the combination of variables in the function. Using operating parameters and its single errors from the aerosol test cases performed at FNC, the uncertainty of aerosol concentration evaluated by Gaussian error propagation law is less than 1%. The results of uncertainty estimation in the aerosol sampling system will be utilized for the system performance data.
Hall, Eric Joseph
2016-12-08
We derive computable error estimates for finite element approximations of linear elliptic partial differential equations with rough stochastic coefficients. In this setting, the exact solutions contain high frequency content that standard a posteriori error estimates fail to capture. We propose goal-oriented estimates, based on local error indicators, for the pathwise Galerkin and expected quadrature errors committed in standard, continuous, piecewise linear finite element approximations. Derived using easily validated assumptions, these novel estimates can be computed at a relatively low cost and have applications to subsurface flow problems in geophysics where the conductivities are assumed to have lognormal distributions with low regularity. Our theory is supported by numerical experiments on test problems in one and two dimensions.
Error estimation in the neural network solution of ordinary differential equations.
Filici, Cristian
2010-06-01
In this article a method of error estimation for the neural approximation of the solution of an Ordinary Differential Equation is presented. Some examples of the application of the method support the theory presented. Copyright 2010. Published by Elsevier Ltd.
Type I Error Rates and Power Estimates of Selected Parametric and Nonparametric Tests of Scale.
Olejnik, Stephen F.; Algina, James
1987-01-01
Estimated Type I Error rates and power are reported for the Brown-Forsythe, O'Brien, Klotz, and Siegal-Tukey procedures. The effect of aligning the data using deviations from group means or group medians is investigated. (RB)
Full information estimations of a system of simultaneous equations with error component structure
Balestra, Pietro; Krishnakumar, Jaya
1987-01-01
In this paper we develop full information methods for estimating the parameters of a system of simultaneous equations with error component struc-ture and establish relationships between the various structural estimat
Energy Technology Data Exchange (ETDEWEB)
Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.
2006-10-01
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
IAS 8, Accounting Policies, Changes in Accounting Estimates and Errors – A Closer Look
Muthupandian, K S
2008-01-01
The International Accounting Standards Board issued the revised version of the International Accounting Standard 8, Accounting Policies, Changes in Accounting Estimates and Errors. The objective of IAS 8 is to prescribe the criteria for selecting, applying and changing accounting policies, together with the accounting treatment and disclosure of changes in accounting policies, changes in accounting estimates and the corrections of errors. This article presents a closer look of the standard (o...
Estimation of Mechanical Signals in Induction Motors using the Recursive Prediction Error Method
DEFF Research Database (Denmark)
Børsting, H.; Knudsen, Morten; Rasmussen, Henrik
1993-01-01
Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed ........Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed .....
DEFF Research Database (Denmark)
Jensen, Jonas; Olesen, Jacob Bjerring; Stuart, Matthias Bo
2016-01-01
radius. The error sources were also studied in vivo under realistic clinical conditions, and the theoretical results were applied for correcting the volume flow errors. Twenty dialysis patients with arteriovenous fistulas were scanned to obtain vector flow maps of fistulas. When fitting an ellipsis......A method for vector velocity volume flow estimation is presented, along with an investigation of its sources of error and correction of actual volume flow measurements. Volume flow errors are quantified theoretically by numerical modeling, through flow phantom measurements, and studied in vivo...
Energy Technology Data Exchange (ETDEWEB)
Lipnikov, Konstantin [Los Alamos National Laboratory; Agouzal, Abdellatif [UNIV DE LYON; Vassilevski, Yuri [Los Alamos National Laboratory
2009-01-01
We present a new technology for generating meshes minimizing the interpolation and discretization errors or their gradients. The key element of this methodology is construction of a space metric from edge-based error estimates. For a mesh with N{sub h} triangles, the error is proportional to N{sub h}{sup -1} and the gradient of error is proportional to N{sub h}{sup -1/2} which are optimal asymptotics. The methodology is verified with numerical experiments.
Carroll, Raymond J.
2010-05-01
This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is nonparametrically identified using the two samples when both could have nonclassical errors, without either instrumental variables or independence between the two samples. When the two samples are independent and the nonlinear regression model is parameterized, we propose sieve Quasi Maximum Likelihood Estimation (Q-MLE) for the parameter of interest, and establish its root-n consistency and asymptotic normality under possible misspecification, and its semiparametric efficiency under correct specification, with easily estimated standard errors. A Monte Carlo simulation and a data application are presented to show the power of the approach.
Measurement error in income and schooling, and the bias of linear estimators
DEFF Research Database (Denmark)
Bingley, Paul; Martinello, Alessandro
The characteristics of measurement error determine the bias of linear estimators. We propose a method for validating economic survey data allowing for measurement error in the validation source, and we apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data...... with Danish administrative registers. We find that measurement error in surveys is classical for annual gross income but non-classical for years of schooling, causing a 21% amplification bias in IV estimators of returns to schooling. Using a 1958 Danish schooling reform, we contextualize our result...
Uncertainty quantification in a chemical system using error estimate-based mesh adaption
International Nuclear Information System (INIS)
Mathelin, Lionel; Le Maitre, Olivier P.
2012-01-01
This paper describes a rigorous a posteriori error analysis for the stochastic solution of non-linear uncertain chemical models. The dual-based a posteriori stochastic error analysis extends the methodology developed in the deterministic finite elements context to stochastic discretization frameworks. It requires the resolution of two additional (dual) problems to yield the local error estimate. The stochastic error estimate can then be used to adapt the stochastic discretization. Different anisotropic refinement strategies are proposed, leading to a cost-efficient tool suitable for multi-dimensional problems of moderate stochastic dimension. The adaptive strategies allow both for refinement and coarsening of the stochastic discretization, as needed to satisfy a prescribed error tolerance. The adaptive strategies were successfully tested on a model for the hydrogen oxidation in supercritical conditions having 8 random parameters. The proposed methodologies are however general enough to be also applicable for a wide class of models such as uncertain fluid flows. (authors)
Ogawa, Takahiro; Haseyama, Miki
2013-03-01
A missing texture reconstruction method based on an error reduction (ER) algorithm, including a novel estimation scheme of Fourier transform magnitudes is presented in this brief. In our method, Fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on the ER algorithm. Specifically, by monitoring errors converged in the ER algorithm, known patches whose Fourier transform magnitudes are similar to that of the target patch are selected from the target image. In the second approach, the Fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. Consequently, by using the ER algorithm, we can estimate both the Fourier transform magnitudes and phases to reconstruct the missing areas.
Error estimation for goal-oriented spatial adaptivity for the SN equations on triangular meshes
International Nuclear Information System (INIS)
Lathouwers, D.
2011-01-01
In this paper we investigate different error estimation procedures for use within a goal oriented adaptive algorithm for the S N equations on unstructured meshes. The method is based on a dual-weighted residual approach where an appropriate adjoint problem is formulated and solved in order to obtain the importance of residual errors in the forward problem on the specific goal of interest. The forward residuals and the adjoint function are combined to obtain both economical finite element meshes tailored to the solution of the target functional as well as providing error estimates. Various approximations made to make the calculation of the adjoint angular flux more economically attractive are evaluated by comparing the performance of the resulting adaptive algorithm and the quality of the error estimators when applied to two shielding-type test problems. (author)
Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil
2011-01-01
Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.
Estimating misclassification error: a closer look at cross-validation based methods
Directory of Open Access Journals (Sweden)
Ounpraseuth Songthip
2012-11-01
Full Text Available Abstract Background To estimate a classifier’s error in predicting future observations, bootstrap methods have been proposed as reduced-variation alternatives to traditional cross-validation (CV methods based on sampling without replacement. Monte Carlo (MC simulation studies aimed at estimating the true misclassification error conditional on the training set are commonly used to compare CV methods. We conducted an MC simulation study to compare a new method of bootstrap CV (BCV to k-fold CV for estimating clasification error. Findings For the low-dimensional conditions simulated, the modest positive bias of k-fold CV contrasted sharply with the substantial negative bias of the new BCV method. This behavior was corroborated using a real-world dataset of prognostic gene-expression profiles in breast cancer patients. Our simulation results demonstrate some extreme characteristics of variance and bias that can occur due to a fault in the design of CV exercises aimed at estimating the true conditional error of a classifier, and that appear not to have been fully appreciated in previous studies. Although CV is a sound practice for estimating a classifier’s generalization error, using CV to estimate the fixed misclassification error of a trained classifier conditional on the training set is problematic. While MC simulation of this estimation exercise can correctly represent the average bias of a classifier, it will overstate the between-run variance of the bias. Conclusions We recommend k-fold CV over the new BCV method for estimating a classifier’s generalization error. The extreme negative bias of BCV is too high a price to pay for its reduced variance.
International Nuclear Information System (INIS)
Menon, R.K.; Bloch, C.A.; Sperling, M.A.
1990-01-01
We investigated whether errors occur in the estimation of ovine maternal-fetal glucose (Glc) kinetics using the isotope dilution technique when the Glc pool is rapidly expanded by exogenous (protocol A) or endogenous (protocol C) Glc entry and sought possible solutions (protocol B). In protocol A (n = 8), after attaining steady-state Glc specific activity (SA) by [U-14C]glucose (period 1), infusion of Glc (period 2) predictably decreased Glc SA, whereas. [U-14C]glucose concentration unexpectedly rose from 7,208 +/- 367 (means +/- SE) in period 1 to 8,558 +/- 308 disintegrations/min (dpm) per ml in period 2 (P less than 0.01). Fetal endogenous Glc production (EGP) was negligible during period 1 (0.44 +/- 1.0), but yielded a physiologically impossible negative value of -2.1 +/- 0.72 mg.kg-1.min-1 during period 2. When the fall in Glc SA during Glc infusion was prevented by addition of [U-14C]glucose admixed with the exogenous Glc (protocol B; n = 7), EGP was no longer negative. In protocol C (n = 6), sequential infusions of four increasing doses of epinephrine serially decreased SA, whereas tracer Glc increased from 7,483 +/- 608 to 11,525 +/- 992 dpm/ml plasma (P less than 0.05), imposing an obligatory underestimation of EGP. Thus a tracer mixing problem leads to erroneous estimations of fetal Glc utilization and Glc production via the three-compartment model in sheep when the Glc pool is expanded exogenously or endogenously. These errors can be minimized by maintaining the Glc SA relatively constant
International Nuclear Information System (INIS)
Burr, T.; Croft, S.; Krieger, T.; Martin, K.; Norman, C.; Walsh, S.
2016-01-01
One example of top-down uncertainty quantification (UQ) involves comparing two or more measurements on each of multiple items. One example of bottom-up UQ expresses a measurement result as a function of one or more input variables that have associated errors, such as a measured count rate, which individually (or collectively) can be evaluated for impact on the uncertainty in the resulting measured value. In practice, it is often found that top-down UQ exhibits larger error variances than bottom-up UQ, because some error sources are present in the fielded assay methods used in top-down UQ that are not present (or not recognized) in the assay studies used in bottom-up UQ. One would like better consistency between the two approaches in order to claim understanding of the measurement process. The purpose of this paper is to refine bottom-up uncertainty estimation by using calibration information so that if there are no unknown error sources, the refined bottom-up uncertainty estimate will agree with the top-down uncertainty estimate to within a specified tolerance. Then, in practice, if the top-down uncertainty estimate is larger than the refined bottom-up uncertainty estimate by more than the specified tolerance, there must be omitted sources of error beyond those predicted from calibration uncertainty. The paper develops a refined bottom-up uncertainty approach for four cases of simple linear calibration: (1) inverse regression with negligible error in predictors, (2) inverse regression with non-negligible error in predictors, (3) classical regression followed by inversion with negligible error in predictors, and (4) classical regression followed by inversion with non-negligible errors in predictors. Our illustrations are of general interest, but are drawn from our experience with nuclear material assay by non-destructive assay. The main example we use is gamma spectroscopy that applies the enrichment meter principle. Previous papers that ignore error in predictors
Prediction of Monte Carlo errors by a theory generalized to treat track-length estimators
International Nuclear Information System (INIS)
Booth, T.E.; Amster, H.J.
1978-01-01
Present theories for predicting expected Monte Carlo errors in neutron transport calculations apply to estimates of flux-weighted integrals sampled directly by scoring individual collisions. To treat track-length estimators, the recent theory of Amster and Djomehri is generalized to allow the score distribution functions to depend on the coordinates of two successive collisions. It has long been known that the expected track length in a region of phase space equals the expected flux integrated over that region, but that the expected statistical error of the Monte Carlo estimate of the track length is different from that of the flux integral obtained by sampling the sum of the reciprocals of the cross sections for all collisions in the region. These conclusions are shown to be implied by the generalized theory, which provides explicit equations for the expected values and errors of both types of estimators. Sampling expected contributions to the track-length estimator is also treated. Other general properties of the errors for both estimators are derived from the equations and physically interpreted. The actual values of these errors are then obtained and interpreted for a simple specific example
GonzáLez, Pablo J.; FernáNdez, José
2011-10-01
Interferometric Synthetic Aperture Radar (InSAR) is a reliable technique for measuring crustal deformation. However, despite its long application in geophysical problems, its error estimation has been largely overlooked. Currently, the largest problem with InSAR is still the atmospheric propagation errors, which is why multitemporal interferometric techniques have been successfully developed using a series of interferograms. However, none of the standard multitemporal interferometric techniques, namely PS or SB (Persistent Scatterers and Small Baselines, respectively) provide an estimate of their precision. Here, we present a method to compute reliable estimates of the precision of the deformation time series. We implement it for the SB multitemporal interferometric technique (a favorable technique for natural terrains, the most usual target of geophysical applications). We describe the method that uses a properly weighted scheme that allows us to compute estimates for all interferogram pixels, enhanced by a Montecarlo resampling technique that properly propagates the interferogram errors (variance-covariances) into the unknown parameters (estimated errors for the displacements). We apply the multitemporal error estimation method to Lanzarote Island (Canary Islands), where no active magmatic activity has been reported in the last decades. We detect deformation around Timanfaya volcano (lengthening of line-of-sight ˜ subsidence), where the last eruption in 1730-1736 occurred. Deformation closely follows the surface temperature anomalies indicating that magma crystallization (cooling and contraction) of the 300-year shallow magmatic body under Timanfaya volcano is still ongoing.
A user's manual of Tools for Error Estimation of Complex Number Matrix Computation (Ver.1.0)
International Nuclear Information System (INIS)
Ichihara, Kiyoshi.
1997-03-01
'Tools for Error Estimation of Complex Number Matrix Computation' is a subroutine library which aids the users in obtaining the error ranges of the complex number linear system's solutions or the Hermitian matrices' eigen values. This library contains routines for both sequential computers and parallel computers. The subroutines for linear system error estimation calulate norms of residual vectors, matrices's condition numbers, error bounds of solutions and so on. The error estimation subroutines for Hermitian matrix eigen values' derive the error ranges of the eigen values according to the Korn-Kato's formula. This user's manual contains a brief mathematical background of error analysis on linear algebra and usage of the subroutines. (author)
On the error estimation and T-stability of the Mann iteration
Maruster, Laura; Maruster, St.
2015-01-01
A formula of error estimation of Mann iteration is given in the case of strongly demicontractive mappings. Based on this estimation, a condition of strong convergence is obtained for the same class of mappings. T-stability for a particular case of strongly demicontractive mappings is proved. Some
The Effect of Error in Item Parameter Estimates on the Test Response Function Method of Linking.
Kaskowitz, Gary S.; De Ayala, R. J.
2001-01-01
Studied the effect of item parameter estimation for computation of linking coefficients for the test response function (TRF) linking/equating method. Simulation results showed that linking was more accurate when there was less error in the parameter estimates, and that 15 or 25 common items provided better results than 5 common items under both…
A framework to estimate probability of diagnosis error in NPP advanced MCR
International Nuclear Information System (INIS)
Kim, Ar Ryum; Kim, Jong Hyun; Jang, Inseok; Seong, Poong Hyun
2018-01-01
Highlights: •As new type of MCR has been installed in NPPs, the work environment is considerably changed. •A new framework to estimate operators’ diagnosis error probabilities should be proposed. •Diagnosis error data were extracted from the full-scope simulator of the advanced MCR. •Using Bayesian inference, a TRC model was updated for use in advanced MCR. -- Abstract: Recently, a new type of main control room (MCR) has been adopted in nuclear power plants (NPPs). The new MCR, known as the advanced MCR, consists of digitalized human-system interfaces (HSIs), computer-based procedures (CPS), and soft controls while the conventional MCR includes many alarm tiles, analog indicators, hard-wired control devices, and paper-based procedures. These changes significantly affect the generic activities of the MCR operators, in relation to diagnostic activities. The aim of this paper is to suggest a framework to estimate the probabilities of diagnosis errors in the advanced MCR by updating a time reliability correlation (TRC) model. Using Bayesian inference, the TRC model was updated with the probabilities of diagnosis errors. Here, the diagnosis error data were collected from a full-scope simulator of the advanced MCR. To do this, diagnosis errors were determined based on an information processing model and their probabilities were calculated. However, these calculated probabilities of diagnosis errors were largely affected by context factors such as procedures, HSI, training, and others, known as PSFs (Performance Shaping Factors). In order to obtain the nominal diagnosis error probabilities, the weightings of PSFs were also evaluated. Then, with the nominal diagnosis error probabilities, the TRC model was updated. This led to the proposal of a framework to estimate the nominal probabilities of diagnosis errors in the advanced MCR.
Research on the Method of Noise Error Estimation of Atomic Clocks
Song, H. J.; Dong, S. W.; Li, W.; Zhang, J. H.; Jing, Y. J.
2017-05-01
The simulation methods of different noises of atomic clocks are given. The frequency flicker noise of atomic clock is studied by using the Markov process theory. The method for estimating the maximum interval error of the frequency white noise is studied by using the Wiener process theory. Based on the operation of 9 cesium atomic clocks in the time frequency reference laboratory of NTSC (National Time Service Center), the noise coefficients of the power-law spectrum model are estimated, and the simulations are carried out according to the noise models. Finally, the maximum interval error estimates of the frequency white noises generated by the 9 cesium atomic clocks have been acquired.
Qin, Guoyou; Zhang, Jiajia; Zhu, Zhongyi; Fung, Wing
2016-12-20
Outliers, measurement error, and missing data are commonly seen in longitudinal data because of its data collection process. However, no method can address all three of these issues simultaneously. This paper focuses on the robust estimation of partially linear models for longitudinal data with dropouts and measurement error. A new robust estimating equation, simultaneously tackling outliers, measurement error, and missingness, is proposed. The asymptotic properties of the proposed estimator are established under some regularity conditions. The proposed method is easy to implement in practice by utilizing the existing standard generalized estimating equations algorithms. The comprehensive simulation studies show the strength of the proposed method in dealing with longitudinal data with all three features. Finally, the proposed method is applied to data from the Lifestyle Education for Activity and Nutrition study and confirms the effectiveness of the intervention in producing weight loss at month 9. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?
Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander
2016-01-01
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.
Estimation of a beam centering error in the JAERI AVF cyclotron
International Nuclear Information System (INIS)
Fukuda, M.; Okumura, S.; Arakawa, K.; Ishibori, I.; Matsumura, A.; Nakamura, N.; Nara, T.; Agematsu, T.; Tamura, H.; Karasawa, T.
1999-01-01
A method for estimating a beam centering error from a beam density distribution obtained by a single radial probe has been developed. Estimation of the centering error is based on an analysis of radial beam positions in the direction of the radial probe. Radial motion of a particle is described as betatron oscillation around an accelerated equilibrium orbit. By fitting the radial beam positions of several consecutive turns to an equation of the radial motion, not only amplitude of the centering error but also frequency of the radial betatron oscillation and energy gain per turn can be evaluated simultaneously. The estimated centering error amplitude was consistent with a result of an orbit simulation. This method was exceedingly helpful for minimizing the centering error of a 10 MeV proton beam during the early stages of acceleration. A well-centered beam was obtained by correcting the magnetic field with a first harmonic produced by two pairs of harmonic coils. In order to push back an orbit center to a magnet center, currents of the harmonic coils were optimized on the basis of the estimated centering error amplitude. (authors)
Facial motion parameter estimation and error criteria in model-based image coding
Liu, Yunhai; Yu, Lu; Yao, Qingdong
2000-04-01
Model-based image coding has been given extensive attention due to its high subject image quality and low bit-rates. But the estimation of object motion parameter is still a difficult problem, and there is not a proper error criteria for the quality assessment that are consistent with visual properties. This paper presents an algorithm of the facial motion parameter estimation based on feature point correspondence and gives the motion parameter error criteria. The facial motion model comprises of three parts. The first part is the global 3-D rigid motion of the head, the second part is non-rigid translation motion in jaw area, and the third part consists of local non-rigid expression motion in eyes and mouth areas. The feature points are automatically selected by a function of edges, brightness and end-node outside the blocks of eyes and mouth. The numbers of feature point are adjusted adaptively. The jaw translation motion is tracked by the changes of the feature point position of jaw. The areas of non-rigid expression motion can be rebuilt by using block-pasting method. The estimation approach of motion parameter error based on the quality of reconstructed image is suggested, and area error function and the error function of contour transition-turn rate are used to be quality criteria. The criteria reflect the image geometric distortion caused by the error of estimated motion parameters properly.
Creel, Scott; Spong, Goran; Sands, Jennifer L; Rotella, Jay; Zeigle, Janet; Joe, Lawrence; Murphy, Kerry M; Smith, Douglas
2003-07-01
Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the 'worst-case threshold' suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a 'matching approach' to eliminate this overestimation bias.
Aquatic concentrations of chemical analytes compared to ecotoxicity estimates
Kostich, Mitchell S.; Flick, Robert W.; Angela L. Batt,; Mash, Heath E.; Boone, J. Scott; Furlong, Edward T.; Kolpin, Dana W.; Glassmeyer, Susan T.
2017-01-01
We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part of a joint USGS/USEPA drinking water plant study. Measured concentrations were compared to biological effect concentration (EC) estimates, including USEPA aquatic life criteria, effective plasma concentrations of pharmaceuticals, published toxicity data summarized in the USEPA ECOTOX database, and chemical structure-based predictions. Potential dietary exposures were estimated using a generic 3-tiered food web accumulation scenario. For many analytes, few or no measured effect data were found, and for some analytes, reporting limits exceeded EC estimates, limiting the scope of conclusions. Results suggest occasional occurrence above ECs for copper, aluminum, strontium, lead, uranium, and nitrate. Sparse effect data for manganese, antimony, and vanadium suggest that these analytes may occur above ECs, but additional effect data would be desirable to corroborate EC estimates. These conclusions were not affected by bioaccumulation estimates. No organic analyte concentrations were found to exceed EC estimates, but ten analytes had concentrations in excess of 1/10th of their respective EC: triclocarban, norverapamil, progesterone, atrazine, metolachlor, triclosan, para-nonylphenol, ibuprofen, venlafaxine, and amitriptyline, suggesting more detailed characterization of these analytes.
Estimation of 3D reconstruction errors in a stereo-vision system
Belhaoua, A.; Kohler, S.; Hirsch, E.
2009-06-01
The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.
B-spline goal-oriented error estimators for geometrically nonlinear rods
2011-04-01
respectively, for the output functionals q2–q4 (linear and nonlinear with the trigonometric functions sine and cosine) in all the tests considered...of the errors resulting from the linear, quadratic and nonlinear (with trigonometric functions sine and cosine) outputs and for p = 1, 2. If the... Portugal . References [1] A.T. Adams. Sobolev Spaces. Academic Press, Boston, 1975. [2] M. Ainsworth and J.T. Oden. A posteriori error estimation in
Estimation of error in using born scaling for collision cross sections involving muonic ions
International Nuclear Information System (INIS)
Stodden, C.D.; Monkhorst, H.J.; Szalewicz, K.
1988-01-01
A quantitative estimate is obtained for the error involved in using Born scaling to calcuated excitation and ionization cross sections for collisions between muonic ions. The impact parameter version of the Born Approximation is used to calculate cross sections and Coulomb corrections for the 1s→2s excitation of αμ in collisions with d. An error of about 50% is found around the peak of the cross section curve. The error falls to less than 5% for velocities above 2 a.u
An estimate and evaluation of design error effects on nuclear power plant design adequacy
International Nuclear Information System (INIS)
Stevenson, J.D.
1984-01-01
An area of considerable concern in evaluating Design Control Quality Assurance procedures applied to design and analysis of nuclear power plant is the level of design error expected or encountered. There is very little published data 1 on the level of error typically found in nuclear power plant design calculations and even less on the impact such errors would be expected to have on overall design adequacy of the plant. This paper is concerned with design error associated with civil and mechanical structural design and analysis found in calculations which form part of the Design or Stress reports. These reports are meant to document the design basis and adequacy of the plant. The estimates contained in this paper are based on the personal experiences of the author. In Table 1 is a partial listing of the design docummentation review performed by the author on which the observations contained in this paper are based. In the preparation of any design calculations, it is a utopian dream to presume such calculations can be made error free. The intent of this paper is to define error levels which might be expected in a competent engineering organizations employing currently technically qualified engineers and accepted methods of Design Control. In addition, the effects of these errors on the probability of failure to meet applicable design code requirements also are estimated
Estimation of heading gyrocompass error using a GPS 3DF system: Impact on ADCP measurements
Directory of Open Access Journals (Sweden)
Simón Ruiz
2002-12-01
Full Text Available Traditionally the horizontal orientation in a ship (heading has been obtained from a gyrocompass. This instrument is still used on research vessels but has an estimated error of about 2-3 degrees, inducing a systematic error in the cross-track velocity measured by an Acoustic Doppler Current Profiler (ADCP. The three-dimensional positioning system (GPS 3DF provides an independent heading measurement with accuracy better than 0.1 degree. The Spanish research vessel BIO Hespérides has been operating with this new system since 1996. For the first time on this vessel, the data from this new instrument are used to estimate gyrocompass error. The methodology we use follows the scheme developed by Griffiths (1994, which compares data from the gyrocompass and the GPS system in order to obtain an interpolated error function. In the present work we apply this methodology on mesoscale surveys performed during the observational phase of the OMEGA project, in the Alboran Sea. The heading-dependent gyrocompass error dominated. Errors in gyrocompass heading of 1.4-3.4 degrees have been found, which give a maximum error in measured cross-track ADCP velocity of 24 cm s-1.
Global Warming Estimation from MSU: Correction for Drift and Calibration Errors
Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Einaudi, Franco (Technical Monitor)
2000-01-01
Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have about 7am/7pm orbital geometry) and afternoon satellites (NOAA 7, 9, 11 and 14 that have about 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error. We find we can decrease the global temperature trend by about 0.07 K/decade. In addition there are systematic time dependent errors present in the data that are introduced by the drift in the satellite orbital geometry arises from the diurnal cycle in temperature which is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observations made in the MSU Ch 1 (50.3 GHz) support this approach. The error is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the errors on the global temperature trend. In one path the
Directory of Open Access Journals (Sweden)
R. Locatelli
2013-10-01
Full Text Available A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes. In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr−1 at the global scale, representing 5% of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr−1 in North America to 7 Tg yr−1 in Boreal Eurasia (from 23 to 48%, respectively. At the model grid-scale, the spread of inverse estimates can reach 150% of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly
Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.
2011-10-01
Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SAREF) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SAPSD) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SAINV1) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SAINV2) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SAPSD was 0.7-1.8 times higher and SAINV1 and SAINV2 were 2.2-8 times higher than SAREF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SAREF. However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SAREF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SAPSD) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.
International Nuclear Information System (INIS)
Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.
2011-01-01
Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SA REF ) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SA PSD ) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SA INV1 ) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SA INV2 ) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SA PSD was 0.7–1.8 times higher and SA INV1 and SA INV2 were 2.2–8 times higher than SA REF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SA REF . However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SA REF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SA PSD ) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.
Directory of Open Access Journals (Sweden)
Oleksandr Makeyev
2016-06-01
Full Text Available Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1-polar electrode with n rings using the (4n + 1-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2 and quadripolar (n = 3 electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected.
Makeyev, Oleksandr; Besio, Walter G.
2016-01-01
Noninvasive concentric ring electrodes are a promising alternative to conventional disc electrodes. Currently, the superiority of tripolar concentric ring electrodes over disc electrodes, in particular, in accuracy of Laplacian estimation, has been demonstrated in a range of applications. In our recent work, we have shown that accuracy of Laplacian estimation can be improved with multipolar concentric ring electrodes using a general approach to estimation of the Laplacian for an (n + 1)-polar electrode with n rings using the (4n + 1)-point method for n ≥ 2. This paper takes the next step toward further improving the Laplacian estimate by proposing novel variable inter-ring distances concentric ring electrodes. Derived using a modified (4n + 1)-point method, linearly increasing and decreasing inter-ring distances tripolar (n = 2) and quadripolar (n = 3) electrode configurations are compared to their constant inter-ring distances counterparts. Finite element method modeling and analytic results are consistent and suggest that increasing inter-ring distances electrode configurations may decrease the truncation error resulting in more accurate Laplacian estimates compared to respective constant inter-ring distances configurations. For currently used tripolar electrode configuration, the truncation error may be decreased more than two-fold, while for the quadripolar configuration more than a six-fold decrease is expected. PMID:27294933
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
J.M. Hull; A.M. Fish; J.J. Keane; S.R. Mori; B.J Sacks; A.C. Hull
2010-01-01
One of the primary assumptions associated with many wildlife and population trend studies is that target species are correctly identified. This assumption may not always be valid, particularly for species similar in appearance to co-occurring species. We examined size overlap and identification error rates among Cooper's (Accipiter cooperii...
DEFF Research Database (Denmark)
Tscherning, Carl Christian
2015-01-01
outside the data area. On the other hand, a comparison of predicted quantities with observed values show that the error also varies depending on the local data standard deviation. This quantity may be (and has been) estimated using the GOCE second order vertical derivative, Tzz, in the area covered...... by the satellite. The ratio between the nearly constant standard deviations of a predicted quantity (e.g. in a 25° × 25° area) and the standard deviations of Tzz in smaller cells (e.g., 1° × 1°) have been used as a scale factor in order to obtain more realistic error estimates. This procedure has been applied...
Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition
van der Zee, Kristoffer G.
2010-10-27
A posteriori estimates of errors in quantities of interest are developed for the nonlinear system of evolution equations embodied in the Cahn-Hilliard model of binary phase transition. These involve the analysis of wellposedness of dual backward-in-time problems and the calculation of residuals. Mixed finite element approximations are developed and used to deliver numerical solutions of representative problems in one- and two-dimensional domains. Estimated errors are shown to be quite accurate in these numerical examples. © 2010 Wiley Periodicals, Inc.
Estimating the approximation error when fixing unessential factors in global sensitivity analysis
Energy Technology Data Exchange (ETDEWEB)
Sobol' , I.M. [Institute for Mathematical Modelling of the Russian Academy of Sciences, Moscow (Russian Federation); Tarantola, S. [Joint Research Centre of the European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 1, 21020 Ispra (Italy)]. E-mail: stefano.tarantola@jrc.it; Gatelli, D. [Joint Research Centre of the European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 1, 21020 Ispra (Italy)]. E-mail: debora.gatelli@jrc.it; Kucherenko, S.S. [Imperial College London (United Kingdom); Mauntz, W. [Department of Biochemical and Chemical Engineering, Dortmund University (Germany)
2007-07-15
One of the major settings of global sensitivity analysis is that of fixing non-influential factors, in order to reduce the dimensionality of a model. However, this is often done without knowing the magnitude of the approximation error being produced. This paper presents a new theorem for the estimation of the average approximation error generated when fixing a group of non-influential factors. A simple function where analytical solutions are available is used to illustrate the theorem. The numerical estimation of small sensitivity indices is discussed.
A review of some a posteriori error estimates for adaptive finite element methods
Czech Academy of Sciences Publication Activity Database
Segeth, Karel
2010-01-01
Roč. 80, č. 8 (2010), s. 1589-1600 ISSN 0378-4754. [European Seminar on Coupled Problems. Jetřichovice, 08.06.2008-13.06.2008] R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : hp-adaptive finite element method * a posteriori error estimators * computational error estimates Subject RIV: BA - General Mathematics Impact factor: 0.812, year: 2010 http://www.sciencedirect.com/science/article/pii/S0378475408004230
Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette
2009-01-01
Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.
Energy Technology Data Exchange (ETDEWEB)
Zamonsky, O M [Comision Nacional de Energia Atomica, Centro Atomico Bariloche (Argentina)
2000-07-01
The accuracy of the solutions produced by the Discrete Ordinates neutron transport nodal methods is analyzed.The obtained new numerical methodologies increase the accuracy of the analyzed scheems and give a POSTERIORI error estimators. The accuracy improvement is obtained with new equations that make the numerical procedure free of truncation errors and proposing spatial reconstructions of the angular fluxes that are more accurate than those used until present. An a POSTERIORI error estimator is rigurously obtained for one dimensional systems that, in certain type of problems, allows to quantify the accuracy of the solutions. From comparisons with the one dimensional results, an a POSTERIORI error estimator is also obtained for multidimensional systems. LOCAL indicators, which quantify the spatial distribution of the errors, are obtained by the decomposition of the menctioned estimators. This makes the proposed methodology suitable to perform adaptive calculations. Some numerical examples are presented to validate the theoretical developements and to illustrate the ranges where the proposed approximations are valid.
Boeschoten, Laura; Oberski, Daniel; De Waal, Ton
2017-01-01
Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible
A method for estimating radioactive cesium concentrations in cattle blood using urine samples.
Sato, Itaru; Yamagishi, Ryoma; Sasaki, Jun; Satoh, Hiroshi; Miura, Kiyoshi; Kikuchi, Kaoru; Otani, Kumiko; Okada, Keiji
2017-12-01
In the region contaminated by the Fukushima nuclear accident, radioactive contamination of live cattle should be checked before slaughter. In this study, we establish a precise method for estimating radioactive cesium concentrations in cattle blood using urine samples. Blood and urine samples were collected from a total of 71 cattle on two farms in the 'difficult-to-return zone'. Urine 137 Cs, specific gravity, electrical conductivity, pH, sodium, potassium, calcium, and creatinine were measured and various estimation methods for blood 137 Cs were tested. The average error rate of the estimation was 54.2% without correction. Correcting for urine creatinine, specific gravity, electrical conductivity, or potassium improved the precision of the estimation. Correcting for specific gravity using the following formula gave the most precise estimate (average error rate = 16.9%): [blood 137 Cs] = [urinary 137 Cs]/([specific gravity] - 1)/329. Urine samples are faster to measure than blood samples because urine can be obtained in larger quantities and has a higher 137 Cs concentration than blood. These advantages of urine and the estimation precision demonstrated in our study, indicate that estimation of blood 137 Cs using urine samples is a practical means of monitoring radioactive contamination in live cattle. © 2017 Japanese Society of Animal Science.
Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation
International Nuclear Information System (INIS)
Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.
2016-01-01
In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also
Doss, Hani; Tan, Aixin
2014-09-01
In the classical biased sampling problem, we have k densities π 1 (·), …, π k (·), each known up to a normalizing constant, i.e. for l = 1, …, k , π l (·) = ν l (·)/ m l , where ν l (·) is a known function and m l is an unknown constant. For each l , we have an iid sample from π l , · and the problem is to estimate the ratios m l /m s for all l and all s . This problem arises frequently in several situations in both frequentist and Bayesian inference. An estimate of the ratios was developed and studied by Vardi and his co-workers over two decades ago, and there has been much subsequent work on this problem from many different perspectives. In spite of this, there are no rigorous results in the literature on how to estimate the standard error of the estimate. We present a class of estimates of the ratios of normalizing constants that are appropriate for the case where the samples from the π l 's are not necessarily iid sequences, but are Markov chains. We also develop an approach based on regenerative simulation for obtaining standard errors for the estimates of ratios of normalizing constants. These standard error estimates are valid for both the iid case and the Markov chain case.
Hydrometer test for estimation of immunoglobulin concentration in bovine colostrum.
Fleenor, W A; Stott, G H
1980-06-01
A practical field method for measuring immunoglobulin concentration in bovine colostrum has been developed from the linear relationship between colostral specific gravity and immunoglobulin concentration. Fourteen colostrums were collected within 24 h postpartum from nursed and unnursed cows and were assayed for specific gravity and major colostral constituents. Additionally, 15 colostrums were collected immediately postpartum prior to suckling and assayed for specific gravity and immunoglobulin concentration. Regression analysis provided an equation to estimate colostral immunoglobulin concentration from the specific gravity of fresh whole colostrum. From this, a colostrometer was developed for practical field use.
Estimation of formaldehyde concentration in working environment by using 14C-labeled formaldehyde
International Nuclear Information System (INIS)
Hamada, Masana; Kitano, Katsuhiro; Miketa, Daigo
2010-01-01
It became to be ruled to check the concentration of formaldehyde as the estimation of airborne concentration in working environment since March, 2009 and then, liquid chromatography and easily analyzing equipment methods, mainly gas detector tube method, are given as the official methods. When we estimate the airborne formaldehyde concentration in a work place where only formalin is used as a formaldehyde emission source such as a room for pathological examination, it is not necessary to separate formaldehyde and therefore not very reasonable to use liquid chromatography including troublesome procedures. On the other hand, gas detector tube method is convenient but has possibility of causing errors by individual differences. The errors might cause the additional differences of the control classes and of the measures to prevent workers from being exposed to harmful materials. In order to solve these problems and to exam alternative analyzing method for formaldehyde, we tried to measure the concentration by using 14 C-labelled one. After 14 C-labelled formaldehyde solution is put into the emission source of formaldehyde (formalin solution), the vaporized samples are taken by silica gel tubes quantitatively as usual at the estimation of airborne concentration in working environment. By counting the desorpted amount of radioactivity from silica gel, it was revealed that the obtained concentrations of formaldehyde are correspond to both the calculated values and the values indicated on the gas detector tubes at various concentrations. In this study, we used the amount below the lower activity limits of radioactive material. Except the users who have radioisotope controlled area, we are allowed to use 14 C-labeled materials below 10 MBq without being regulated under the Law Concerning Prevention of Radiation Hazards. When we use a little amount of 14 C-formaldehyde at formaldehyde using area to check the concentration of vaporized formaldehyde, this method was found to
Wang, Wentao
2012-03-01
Both theoretical analysis and nonlinear 2D numerical simulations are used to study the concentration difference and Peclet number effect on the measurement error of electroosmotic mobility in microchannels. We propose a compact analytical model for this error as a function of normalized concentration difference and Peclet number in micro electroosmotic flow. The analytical predictions of the errors are consistent with the numerical simulations. © 2012 IEEE.
A novel multitemporal insar model for joint estimation of deformation rates and orbital errors
Zhang, Lei
2014-06-01
Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference. © 2013 IEEE.
Fottrell, Edward; Byass, Peter; Berhane, Yemane
2008-03-25
As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of
Directory of Open Access Journals (Sweden)
Berhane Yemane
2008-03-01
estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
International Nuclear Information System (INIS)
Siegrist, R.L.
1991-01-01
Due to their widespread use throughout commerce and industry, volatile hydrocarbons such as toluene, trichloroethene, and 1, 1,1-trichloroethane routinely appears as principal pollutants in contamination of soil system hydrocarbons is necessary to confirm the presence of contamination and its nature and extent; to assess site risks and the need for cleanup; to evaluate remedial technologies; and to verify the performance of a selected alternative. Decisions regarding these issues have far-reaching impacts and, ideally, should be based on accurate measurements of soil hydrocarbon concentrations. Unfortunately, quantification of volatile hydrocarbons in soils is extremely difficult and there is normally little understanding of the accuracy and precision of these measurements. Rather, the assumptions often implicitly made that the hydrocarbon data are sufficiently accurate for the intended purpose. This appear presents a discussion of measurement error potential when quantifying volatile hydrocarbons in soils, and outlines some methods for understanding the managing these errors
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang
2011-10-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over uncorrelated Rayleigh fading channels. We first derive the ergodic (average) capacity expressions for such systems when power adaptation is applied at the transmitter. The exact capacity expression for the uniform power allocation case is also presented. Furthermore, to investigate the diversity order of MIMO MRT-MRC scheme, we derive the BER performance under a uniform power allocation policy. We also present an asymptotic BER performance analysis for the MIMO MRT-MRC system with multiuser diversity. The numerical results are given to illustrate the sensitivity of the main performance to the channel estimation error and the tightness of the approximate cutoff value. © 2011 IEEE.
Directory of Open Access Journals (Sweden)
Khasanov Zimfir
2018-01-01
Full Text Available The article reviews the capabilities and particularities of the approach to the improvement of metrological characteristics of fiber-optic pressure sensors (FOPS based on estimation estimation of dynamic errors in laser optoelectronic dimension gauges for geometric measurement of details. It is shown that the proposed criteria render new methods for conjugation of optoelectronic converters in the dimension gauge for geometric measurements in order to reduce the speed and volume requirements for the Random Access Memory (RAM of the video controller which process the signal. It is found that the lower relative error, the higher the interrogetion speed of the CCD array. It is shown that thus, the maximum achievable dynamic accuracy characteristics of the optoelectronic gauge are determined by the following conditions: the parameter stability of the electronic circuits in the CCD array and the microprocessor calculator; linearity of characteristics; error dynamics and noise in all electronic circuits of the CCD array and microprocessor calculator.
Impact of Channel Estimation Errors on Multiuser Detection via the Replica Method
Directory of Open Access Journals (Sweden)
Li Husheng
2005-01-01
Full Text Available For practical wireless DS-CDMA systems, channel estimation is imperfect due to noise and interference. In this paper, the impact of channel estimation errors on multiuser detection (MUD is analyzed under the framework of the replica method. System performance is obtained in the large system limit for optimal MUD, linear MUD, and turbo MUD, and is validated by numerical results for finite systems.
Some error estimates for the lumped mass finite element method for a parabolic problem
Chatzipantelidis, P.
2012-01-01
We study the spatially semidiscrete lumped mass method for the model homogeneous heat equation with homogeneous Dirichlet boundary conditions. Improving earlier results we show that known optimal order smooth initial data error estimates for the standard Galerkin method carry over to the lumped mass method whereas nonsmooth initial data estimates require special assumptions on the triangulation. We also discuss the application to time discretization by the backward Euler and Crank-Nicolson methods. © 2011 American Mathematical Society.
Estimation of Alcohol Concentration of Red Wine Based on Cole-Cole Plot
Watanabe, Kota; Taka, Yoshinori; Fujiwara, Osamu
To evaluate the quality of wine, we previously measured the complex relative permittivity of wine in the frequency range from 10 MHz to 6 GHz with a network analyzer, and suggested a possibility that the maturity and alcohol concentration of wine can simultaneously be estimated from the Cole-Cole plot. Although the absolute accuracy has not been examined yet, this method will enable one to estimate the alcohol concentration of alcoholic beverages without any distillation equipment simply. In this study, to investigate the estimation accuracy of the alcohol concentration of wine by its Cole-Cole plots, we measured the complex relative permittivity of pure water and diluted ethanol solution from 100 MHz to 40 GHz, and obtained the dependence of the Cole-Cole plot parameters on alcohol concentration and temperature. By using these results as calibration data, we estimated the alcohol concentration of red wine from the Cole-Cole plots, which was compared with the measured one based on a distillation method. As a result, we have confirmed that the estimated alcohol concentration of red wine agrees with the measured results in an absolute error by less than 1 %.
Directory of Open Access Journals (Sweden)
Sarah Ehlers
2018-04-01
Full Text Available Today, non-expensive remote sensing (RS data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.
Dreano, Denis; Tandeo, P.; Pulido, M.; Ait-El-Fquih, Boujemaa; Chonavel, T.; Hoteit, Ibrahim
2017-01-01
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended
International Nuclear Information System (INIS)
Vasil'ev, A.P.; Krepkij, A.S.; Lukin, A.V.; Mikhal'kova, A.G.; Orlov, A.I.; Perezhogin, V.D.; Samojlova, L.Yu.; Sokolov, Yu.A.; Terekhin, V.A.; Chernukhin, Yu.I.
1991-01-01
Critical mass experiments were performed using assemblies which simulated one-dimensional lattice consisting of shielding containers with metal fissile materials. Calculations of the criticality of the above assemblies were carried out using the KLAN program with the BAS neutron constants. Errors in the calculations of the criticality for one-, two-, and three-dimensional lattices are estimated. 3 refs.; 1 tab
Error Estimates for a Semidiscrete Finite Element Method for Fractional Order Parabolic Equations
Jin, Bangti; Lazarov, Raytcho; Zhou, Zhi
2013-01-01
initial data, i.e., ν ∈ H2(Ω) ∩ H0 1(Ω) and ν ∈ L2(Ω). For the lumped mass method, the optimal L2-norm error estimate is valid only under an additional assumption on the mesh, which in two dimensions is known to be satisfied for symmetric meshes. Finally
A novel multitemporal insar model for joint estimation of deformation rates and orbital errors
Zhang, Lei; Ding, Xiaoli; Lu, Zhong; Jung, Hyungsup; Hu, Jun; Feng, Guangcai
2014-01-01
be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long
L∞-error estimates of a finite element method for the Hamilton-Jacobi-Bellman equations
International Nuclear Information System (INIS)
Bouldbrachene, M.
1994-11-01
We study the finite element approximation for the solution of the Hamilton-Jacobi-Bellman equations involving a system of quasi-variational inequalities (QVI). We also give the optimal L ∞ -error estimates, using the concepts of subsolutions and discrete regularity. (author). 7 refs
An error bound estimate and convergence of the Nodal-LTS N solution in a rectangle
International Nuclear Information System (INIS)
Hauser, Eliete Biasotto; Pazos, Ruben Panta; Tullio de Vilhena, Marco
2005-01-01
In this work, we report the mathematical analysis concerning error bound estimate and convergence of the Nodal-LTS N solution in a rectangle. For such we present an efficient algorithm, called LTS N 2D-Diag solution for Cartesian geometry
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www. science direct.com/ science /article/pii/S0377042716301492?via%3Dihub
Partial-Interval Estimation of Count: Uncorrected and Poisson-Corrected Error Levels
Yoder, Paul J.; Ledford, Jennifer R.; Harbison, Amy L.; Tapp, Jon T.
2018-01-01
A simulation study that used 3,000 computer-generated event streams with known behavior rates, interval durations, and session durations was conducted to test whether the main and interaction effects of true rate and interval duration affect the error level of uncorrected and Poisson-transformed (i.e., "corrected") count as estimated by…
Estimation of chromatic errors from broadband images for high contrast imaging
Sirbu, Dan; Belikov, Ruslan
2015-09-01
Usage of an internal coronagraph with an adaptive optical system for wavefront correction for direct imaging of exoplanets is currently being considered for many mission concepts, including as an instrument addition to the WFIRST-AFTA mission to follow the James Web Space Telescope. The main technical challenge associated with direct imaging of exoplanets with an internal coronagraph is to effectively control both the diffraction and scattered light from the star so that the dim planetary companion can be seen. For the deformable mirror (DM) to recover a dark hole region with sufficiently high contrast in the image plane, wavefront errors are usually estimated using probes on the DM. To date, most broadband lab demonstrations use narrowband filters to estimate the chromaticity of the wavefront error, but this reduces the photon flux per filter and requires a filter system. Here, we propose a method to estimate the chromaticity of wavefront errors using only a broadband image. This is achieved by using special DM probes that have sufficient chromatic diversity. As a case example, we simulate the retrieval of the spectrum of the central wavelength from broadband images for a simple shaped- pupil coronagraph with a conjugate DM and compute the resulting estimation error.
L∞-error estimate for a system of elliptic quasivariational inequalities
Directory of Open Access Journals (Sweden)
M. Boulbrachene
2003-01-01
Full Text Available We deal with the numerical analysis of a system of elliptic quasivariational inequalities (QVIs. Under W2,p(Ω-regularity of the continuous solution, a quasi-optimal L∞-convergence of a piecewise linear finite element method is established, involving a monotone algorithm of Bensoussan-Lions type and standard uniform error estimates known for elliptic variational inequalities (VIs.
Some examples of the estimation of error for calorimetric assay of plutonium-bearing solids
International Nuclear Information System (INIS)
Rodenburg, W.W.
1977-04-01
This report provides numerical examples of error estimation and related measurement assurance programs for the calorimetric assay of plutonium. It is primarily intended for users who do not consider themselves experts in the field of calorimetry. These examples will provide practical and useful information in establishing a calorimetric assay capability which fulfills regulatory requirements. 10 tables, 5 figures
A Generalizability Theory Approach to Standard Error Estimates for Bookmark Standard Settings
Lee, Guemin; Lewis, Daniel M.
2008-01-01
The bookmark standard-setting procedure is an item response theory-based method that is widely implemented in state testing programs. This study estimates standard errors for cut scores resulting from bookmark standard settings under a generalizability theory model and investigates the effects of different universes of generalization and error…
Statistical error estimation of the Feynman-α method using the bootstrap method
International Nuclear Information System (INIS)
Endo, Tomohiro; Yamamoto, Akio; Yagi, Takahiro; Pyeon, Cheol Ho
2016-01-01
Applicability of the bootstrap method is investigated to estimate the statistical error of the Feynman-α method, which is one of the subcritical measurement techniques on the basis of reactor noise analysis. In the Feynman-α method, the statistical error can be simply estimated from multiple measurements of reactor noise, however it requires additional measurement time to repeat the multiple times of measurements. Using a resampling technique called 'bootstrap method' standard deviation and confidence interval of measurement results obtained by the Feynman-α method can be estimated as the statistical error, using only a single measurement of reactor noise. In order to validate our proposed technique, we carried out a passive measurement of reactor noise without any external source, i.e. with only inherent neutron source by spontaneous fission and (α,n) reactions in nuclear fuels at the Kyoto University Criticality Assembly. Through the actual measurement, it is confirmed that the bootstrap method is applicable to approximately estimate the statistical error of measurement results obtained by the Feynman-α method. (author)
A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series
Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.
2011-01-01
Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…
Can i just check...? Effects of edit check questions on measurement error and survey estimates
Lugtig, Peter; Jäckle, Annette
2014-01-01
Household income is difficult to measure, since it requires the collection of information about all potential income sources for each member of a household.Weassess the effects of two types of edit check questions on measurement error and survey estimates: within-wave edit checks use responses to
On Estimation of the A-norm of the Error in CG and PCG
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2003-01-01
Roč. 3, - (2003), s. 553-554 ISSN 1617-7061. [GAMM. Padua, 24.03.2003-28.03.2003] R&D Projects: GA ČR GA201/02/0595 Institutional research plan: CEZ:AV0Z1030915 Keywords : preconditioned conjugate gradient * error estimates * stopping criteria Subject RIV: BA - General Mathematics
Czech Academy of Sciences Publication Activity Database
Axelsson, Owe; Karátson, J.
2017-01-01
Roč. 210, January 2017 (2017), s. 155-164 ISSN 0377-0427 Institutional support: RVO:68145535 Keywords : finite difference method * error estimates * matrix splitting * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://www.sciencedirect.com/science/article/pii/S0377042716301492?via%3Dihub
Estimating the annotation error rate of curated GO database sequence annotations
Directory of Open Access Journals (Sweden)
Brown Alfred L
2007-05-01
Full Text Available Abstract Background Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO sequence database (GOSeqLite. This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. Results We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006 at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS had an estimated error rate of 49%. Conclusion While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.
Jones, Reese E.; Mandadapu, Kranthi K.
2012-04-01
We present a rigorous Green-Kubo methodology for calculating transport coefficients based on on-the-fly estimates of: (a) statistical stationarity of the relevant process, and (b) error in the resulting coefficient. The methodology uses time samples efficiently across an ensemble of parallel replicas to yield accurate estimates, which is particularly useful for estimating the thermal conductivity of semi-conductors near their Debye temperatures where the characteristic decay times of the heat flux correlation functions are large. Employing and extending the error analysis of Zwanzig and Ailawadi [Phys. Rev. 182, 280 (1969)], 10.1103/PhysRev.182.280 and Frenkel [in Proceedings of the International School of Physics "Enrico Fermi", Course LXXV (North-Holland Publishing Company, Amsterdam, 1980)] to the integral of correlation, we are able to provide tight theoretical bounds for the error in the estimate of the transport coefficient. To demonstrate the performance of the method, four test cases of increasing computational cost and complexity are presented: the viscosity of Ar and water, and the thermal conductivity of Si and GaN. In addition to producing accurate estimates of the transport coefficients for these materials, this work demonstrates precise agreement of the computed variances in the estimates of the correlation and the transport coefficient with the extended theory based on the assumption that fluctuations follow a Gaussian process. The proposed algorithm in conjunction with the extended theory enables the calculation of transport coefficients with the Green-Kubo method accurately and efficiently.
Dionisio, Kathie L; Chang, Howard H; Baxter, Lisa K
2016-11-25
Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. ZIP-code level estimates of exposure for six pollutants (CO, NO x , EC, PM 2.5 , SO 4 , O 3 ) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.
Directory of Open Access Journals (Sweden)
Jian Yan
2018-01-01
Full Text Available In this paper, a flux distribution model of the focal plane in dish concentrator system has been established based on ray tracking method. This model was adopted for researching the influence of the mirror slope error, solar direct normal irradiance, and tracking error of elevation-azimuth tracking device (EATD on the focal spot characteristics (i.e., flux distribution, geometrical shape, centroid position, and intercept factor. The tracking error transmission law of the EATD transferred to dish concentrator was also studied. The results show that the azimuth tracking error of the concentrator decreases with the increase of the concentrator elevation angle and it decreases to 0 mrad when the elevation angle is 90°. The centroid position of focal spot along x-axis and y-axis has linear relationship with azimuth and elevation tracking error of EATD, respectively, which could be used to evaluate and calibrate the tracking error of the dish concentrator. Finally, the transmission law of the EATD azimuth tracking error in solar heliostats is analyzed, and a dish concentrator using a spin-elevation tracking device is proposed, which can reduce the effect of spin tracking error on the dish concentrator. This work could provide fundamental for manufacturing precision allocation of tracking devices and developing a new type of tracking device.
Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty
Ballantyne, A. P.; Andres, R.; Houghton, R.; Stocker, B. D.; Wanninkhof, R.; Anderegg, W.; Cooper, L. A.; DeGrandpre, M.; Tans, P. P.; Miller, J. B.; Alden, C.; White, J. W. C.
2015-04-01
Over the last 5 decades monitoring systems have been developed to detect changes in the accumulation of carbon (C) in the atmosphere and ocean; however, our ability to detect changes in the behavior of the global C cycle is still hindered by measurement and estimate errors. Here we present a rigorous and flexible framework for assessing the temporal and spatial components of estimate errors and their impact on uncertainty in net C uptake by the biosphere. We present a novel approach for incorporating temporally correlated random error into the error structure of emission estimates. Based on this approach, we conclude that the 2σ uncertainties of the atmospheric growth rate have decreased from 1.2 Pg C yr-1 in the 1960s to 0.3 Pg C yr-1 in the 2000s due to an expansion of the atmospheric observation network. The 2σ uncertainties in fossil fuel emissions have increased from 0.3 Pg C yr-1 in the 1960s to almost 1.0 Pg C yr-1 during the 2000s due to differences in national reporting errors and differences in energy inventories. Lastly, while land use emissions have remained fairly constant, their errors still remain high and thus their global C uptake uncertainty is not trivial. Currently, the absolute errors in fossil fuel emissions rival the total emissions from land use, highlighting the extent to which fossil fuels dominate the global C budget. Because errors in the atmospheric growth rate have decreased faster than errors in total emissions have increased, a ~20% reduction in the overall uncertainty of net C global uptake has occurred. Given all the major sources of error in the global C budget that we could identify, we are 93% confident that terrestrial C uptake has increased and 97% confident that ocean C uptake has increased over the last 5 decades. Thus, it is clear that arguably one of the most vital ecosystem services currently provided by the biosphere is the continued removal of approximately half of atmospheric CO2 emissions from the atmosphere
Carroll, Raymond J.
2011-03-01
In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.
Estimation of sampling error uncertainties in observed surface air temperature change in China
Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun
2017-08-01
This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.
ERROR BOUNDS FOR SURFACE AREA ESTIMATORS BASED ON CROFTON’S FORMULA
Directory of Open Access Journals (Sweden)
Markus Kiderlen
2011-05-01
Full Text Available According to Crofton's formula, the surface area S(A of a sufficiently regular compact set A in Rd is proportional to the mean of all total projections pA (u on a linear hyperplane with normal u, uniformly averaged over all unit vectors u. In applications, pA (u is only measured in k directions and the mean is approximated by a finite weighted sum bS(A of the total projections in these directions. The choice of the weights depends on the selected quadrature rule. We define an associated zonotope Z (depending only on the projection directions and the quadrature rule, and show that the relative error bS (A/S (A is bounded from below by the inradius of Z and from above by the circumradius of Z. Applying a strengthened isoperimetric inequality due to Bonnesen, we show that the rectangular quadrature rule does not give the best possible error bounds for d =2. In addition, we derive asymptotic behavior of the error (with increasing k in the planar case. The paper concludes with applications to surface area estimation in design-based digital stereology where we show that the weights due to Bonnesen's inequality are better than the usual weights based on the rectangular rule and almost optimal in the sense that the relative error of the surface area estimator is very close to the minimal error.
International Nuclear Information System (INIS)
Seaver, D.A.; Stillwell, W.G.
1983-03-01
This report describes and evaluates several procedures for using expert judgment to estimate human-error probabilities (HEPs) in nuclear power plant operations. These HEPs are currently needed for several purposes, particularly for probabilistic risk assessments. Data do not exist for estimating these HEPs, so expert judgment can provide these estimates in a timely manner. Five judgmental procedures are described here: paired comparisons, ranking and rating, direct numerical estimation, indirect numerical estimation and multiattribute utility measurement. These procedures are evaluated in terms of several criteria: quality of judgments, difficulty of data collection, empirical support, acceptability, theoretical justification, and data processing. Situational constraints such as the number of experts available, the number of HEPs to be estimated, the time available, the location of the experts, and the resources available are discussed in regard to their implications for selecting a procedure for use
Influence of the statistical distribution of bioassay measurement errors on the intake estimation
International Nuclear Information System (INIS)
Lee, T. Y; Kim, J. K
2006-01-01
The purpose of this study is to provide the guidance necessary for making a selection of error distributions by analyzing influence of statistical distribution for a type of bioassay measurement error on the intake estimation. For this purpose, intakes were estimated using maximum likelihood method for cases that error distributions are normal and lognormal, and comparisons between two distributions for the estimated intakes were made. According to the results of this study, in case that measurement results for lung retention are somewhat greater than the limit of detection it appeared that distribution types have negligible influence on the results. Whereas in case of measurement results for the daily excretion rate, the results obtained from assumption of a lognormal distribution were 10% higher than those obtained from assumption of a normal distribution. In view of these facts, in case where uncertainty component is governed by counting statistics it is considered that distribution type have no influence on intake estimation. Whereas in case where the others are predominant, it is concluded that it is clearly desirable to estimate the intake assuming a lognormal distribution
Accurate and fast methods to estimate the population mutation rate from error prone sequences
Directory of Open Access Journals (Sweden)
Miyamoto Michael M
2009-08-01
Full Text Available Abstract Background The population mutation rate (θ remains one of the most fundamental parameters in genetics, ecology, and evolutionary biology. However, its accurate estimation can be seriously compromised when working with error prone data such as expressed sequence tags, low coverage draft sequences, and other such unfinished products. This study is premised on the simple idea that a random sequence error due to a chance accident during data collection or recording will be distributed within a population dataset as a singleton (i.e., as a polymorphic site where one sampled sequence exhibits a unique base relative to the common nucleotide of the others. Thus, one can avoid these random errors by ignoring the singletons within a dataset. Results This strategy is implemented under an infinite sites model that focuses on only the internal branches of the sample genealogy where a shared polymorphism can arise (i.e., a variable site where each alternative base is represented by at least two sequences. This approach is first used to derive independently the same new Watterson and Tajima estimators of θ, as recently reported by Achaz 1 for error prone sequences. It is then used to modify the recent, full, maximum-likelihood model of Knudsen and Miyamoto 2, which incorporates various factors for experimental error and design with those for coalescence and mutation. These new methods are all accurate and fast according to evolutionary simulations and analyses of a real complex population dataset for the California seahare. Conclusion In light of these results, we recommend the use of these three new methods for the determination of θ from error prone sequences. In particular, we advocate the new maximum likelihood model as a starting point for the further development of more complex coalescent/mutation models that also account for experimental error and design.
Test models for improving filtering with model errors through stochastic parameter estimation
International Nuclear Information System (INIS)
Gershgorin, B.; Harlim, J.; Majda, A.J.
2010-01-01
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
Development of a framework to estimate human error for diagnosis tasks in advanced control room
International Nuclear Information System (INIS)
Kim, Ar Ryum; Jang, In Seok; Seong, Proong Hyun
2014-01-01
In the emergency situation of nuclear power plants (NPPs), a diagnosis of the occurring events is crucial for managing or controlling the plant to a safe and stable condition. If the operators fail to diagnose the occurring events or relevant situations, their responses can eventually inappropriate or inadequate Accordingly, huge researches have been performed to identify the cause of diagnosis error and estimate the probability of diagnosis error. D.I Gertman et al. asserted that 'the cognitive failures stem from erroneous decision-making, poor understanding of rules and procedures, and inadequate problem solving and this failures may be due to quality of data and people's capacity for processing information'. Also many researchers have asserted that human-system interface (HSI), procedure, training and available time are critical factors to cause diagnosis error. In nuclear power plants, a diagnosis of the event is critical for safe condition of the system. As advanced main control room is being adopted in nuclear power plants, the operators may obtain the plant data via computer-based HSI and procedure. Also many researchers have asserted that HSI, procedure, training and available time are critical factors to cause diagnosis error. In this regards, using simulation data, diagnosis errors and its causes were identified. From this study, some useful insights to reduce diagnosis errors of operators in advanced main control room were provided
International Nuclear Information System (INIS)
Vincent, C.H.
1982-01-01
Bayes' principle is applied to the differential counting measurement of a positive quantity in which the statistical errors are not necessarily small in relation to the true value of the quantity. The methods of estimation derived are found to give consistent results and to avoid the anomalous negative estimates sometimes obtained by conventional methods. One of the methods given provides a simple means of deriving the required estimates from conventionally presented results and appears to have wide potential applications. Both methods provide the actual posterior probability distribution of the quantity to be measured. A particularly important potential application is the correction of counts on low radioacitvity samples for background. (orig.)
Error Estimates for Approximate Solutions of the Riccati Equation with Real or Complex Potentials
Finster, Felix; Smoller, Joel
2010-09-01
A method is presented for obtaining rigorous error estimates for approximate solutions of the Riccati equation, with real or complex potentials. Our main tool is to derive invariant region estimates for complex solutions of the Riccati equation. We explain the general strategy for applying these estimates and illustrate the method in typical examples, where the approximate solutions are obtained by gluing together WKB and Airy solutions of corresponding one-dimensional Schrödinger equations. Our method is motivated by, and has applications to, the analysis of linear wave equations in the geometry of a rotating black hole.
Energy Technology Data Exchange (ETDEWEB)
Kunin, Victor; Engelbrektson, Anna; Ochman, Howard; Hugenholtz, Philip
2009-08-01
Massively parallel pyrosequencing of the small subunit (16S) ribosomal RNA gene has revealed that the extent of rare microbial populations in several environments, the 'rare biosphere', is orders of magnitude higher than previously thought. One important caveat with this method is that sequencing error could artificially inflate diversity estimates. Although the per-base error of 16S rDNA amplicon pyrosequencing has been shown to be as good as or lower than Sanger sequencing, no direct assessments of pyrosequencing errors on diversity estimates have been reported. Using only Escherichia coli MG1655 as a reference template, we find that 16S rDNA diversity is grossly overestimated unless relatively stringent read quality filtering and low clustering thresholds are applied. In particular, the common practice of removing reads with unresolved bases and anomalous read lengths is insufficient to ensure accurate estimates of microbial diversity. Furthermore, common and reproducible homopolymer length errors can result in relatively abundant spurious phylotypes further confounding data interpretation. We suggest that stringent quality-based trimming of 16S pyrotags and clustering thresholds no greater than 97% identity should be used to avoid overestimates of the rare biosphere.
Energy Technology Data Exchange (ETDEWEB)
Jang, Seunghyun; Jae, Moosung [Hanyang University, Seoul (Korea, Republic of)
2016-10-15
The human failure events (HFEs) are considered in the development of system fault trees as well as accident sequence event trees in part of Probabilistic Safety Assessment (PSA). As a method for analyzing the human error, several methods, such as Technique for Human Error Rate Prediction (THERP), Human Cognitive Reliability (HCR), and Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) are used and new methods for human reliability analysis (HRA) are under developing at this time. This paper presents a dynamic HRA method for assessing the human failure events and estimation of human error probability for filtered containment venting system (FCVS) is performed. The action associated with implementation of the containment venting during a station blackout sequence is used as an example. In this report, dynamic HRA method was used to analyze FCVS-related operator action. The distributions of the required time and the available time were developed by MAAP code and LHS sampling. Though the numerical calculations given here are only for illustrative purpose, the dynamic HRA method can be useful tools to estimate the human error estimation and it can be applied to any kind of the operator actions, including the severe accident management strategy.
Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata
Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.
2012-01-01
Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).
Methodology for estimating sodium aerosol concentrations during breeder reactor fires
International Nuclear Information System (INIS)
Fields, D.E.; Miller, C.W.
1985-01-01
We have devised and applied a methodology for estimating the concentration of aerosols released at building surfaces and monitored at other building surface points. We have used this methodology to make calculations that suggest, for one air-cooled breeder reactor design, cooling will not be compromised by severe liquid-metal fires
Estimation of radon concentration in dwellings in and around ...
Indian Academy of Sciences (India)
Besides, it is also known that out of the total radiation dose received from natural and man-made sources, 60% of the dose is due to radon and its progeny. Taking this into account, an attempt has been made to estimate radon concentration in dwellings in and around Guwahati using aluminium dosimeter cups with CR-39 ...
Accuracy and Sources of Error for an Angle Independent Volume Flow Estimator
DEFF Research Database (Denmark)
Jensen, Jonas; Olesen, Jacob Bjerring; Hansen, Peter Møller
2014-01-01
This paper investigates sources of error for a vector velocity volume flow estimator. Quantification of the estima tor’s accuracy is performed theoretically and investigated in vivo . Womersley’s model for pulsatile flow is used to simulate velo city profiles and calculate volume flow errors....... A BK Medical UltraView 800 ultrasound scanner with a 9 MHz linear array transducer is used to obtain Vector Flow Imaging sequences of a superficial part of the fistulas. Cross-sectional diameters of each fistu la are measured on B-mode images by rotating the scan plane 90 degrees. The major axis...
Estimation of the wind turbine yaw error by support vector machines
DEFF Research Database (Denmark)
Sheibat-Othman, Nida; Othman, Sami; Tayari, Raoaa
2015-01-01
Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology...... is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators...
Directory of Open Access Journals (Sweden)
Kim Hyang-Mi
2012-09-01
Full Text Available Abstract Background In epidemiological studies, it is often not possible to measure accurately exposures of participants even if their response variable can be measured without error. When there are several groups of subjects, occupational epidemiologists employ group-based strategy (GBS for exposure assessment to reduce bias due to measurement errors: individuals of a group/job within study sample are assigned commonly to the sample mean of exposure measurements from their group in evaluating the effect of exposure on the response. Therefore, exposure is estimated on an ecological level while health outcomes are ascertained for each subject. Such study design leads to negligible bias in risk estimates when group means are estimated from ‘large’ samples. However, in many cases, only a small number of observations are available to estimate the group means, and this causes bias in the observed exposure-disease association. Also, the analysis in a semi-ecological design may involve exposure data with the majority missing and the rest observed with measurement errors and complete response data collected with ascertainment. Methods In workplaces groups/jobs are naturally ordered and this could be incorporated in estimation procedure by constrained estimation methods together with the expectation and maximization (EM algorithms for regression models having measurement error and missing values. Four methods were compared by a simulation study: naive complete-case analysis, GBS, the constrained GBS (CGBS, and the constrained expectation and maximization (CEM. We illustrated the methods in the analysis of decline in lung function due to exposures to carbon black. Results Naive and GBS approaches were shown to be inadequate when the number of exposure measurements is too small to accurately estimate group means. The CEM method appears to be best among them when within each exposure group at least a ’moderate’ number of individuals have their
Nitrogen concentration estimation with hyperspectral LiDAR
Directory of Open Access Journals (Sweden)
O. Nevalainen
2013-10-01
Full Text Available Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging (LiDAR instrument has been developed at the Finnish Geodetic Institute (FGI. The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point which offers great potential in the field of remote sensing of environment. This study investigates the performance of the hyperspectral LiDAR instrument in nitrogen estimation. The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out cross-validation. The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant improvement to the remote sensing of environment.
Errors in the estimation method for the rejection of vibrations in adaptive optics systems
Kania, Dariusz
2017-06-01
In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.
International Nuclear Information System (INIS)
Silverman, J.A.; Mehta, J.; Brocher, S.; Amenta, J.S.
1985-01-01
Previous studies on protein turnover in 3 H-labelled L-cell cultures have shown recovery of total 3 H at the end of a three-day experiment to be always significantly in excess of the 3 H recovered at the beginning of the experiment. A number of possible sources for this error in measuring radioactivity in cell proteins has been reviewed. 3 H-labelled proteins, when dissolved in NaOH and counted for radioactivity in a liquid-scintillation spectrometer, showed losses of 30-40% of the radioactivity; neither external or internal standardization compensated for this loss. Hydrolysis of these proteins with either Pronase or concentrated HCl significantly increased the measured radioactivity. In addition, 5-10% of the cell protein is left on the plastic culture dish when cells are recovered in phosphate-buffered saline. Furthermore, this surface-adherent protein, after pulse labelling, contains proteins of high radioactivity that turn over rapidly and make a major contribution to the accumulating radioactivity in the medium. These combined errors can account for up to 60% of the total radioactivity in the cell culture. Similar analytical errors have been found in studies of other cell cultures. The effect of these analytical errors on estimates of protein turnover in cell cultures is discussed. (author)
A TOA-AOA-Based NLOS Error Mitigation Method for Location Estimation
Directory of Open Access Journals (Sweden)
Tianshuang Qiu
2007-12-01
Full Text Available This paper proposes a geometric method to locate a mobile station (MS in a mobile cellular network when both the range and angle measurements are corrupted by non-line-of-sight (NLOS errors. The MS location is restricted to an enclosed region by geometric constraints from the temporal-spatial characteristics of the radio propagation channel. A closed-form equation of the MS position, time of arrival (TOA, angle of arrival (AOA, and angle spread is provided. The solution space of the equation is very large because the angle spreads are random variables in nature. A constrained objective function is constructed to further limit the MS position. A Lagrange multiplier-based solution and a numerical solution are proposed to resolve the MS position. The estimation quality of the estimator in term of Ã¢Â€ÂœbiasedÃ¢Â€Â or Ã¢Â€ÂœunbiasedÃ¢Â€Â is discussed. The scale factors, which may be used to evaluate NLOS propagation level, can be estimated by the proposed method. AOA seen at base stations may be corrected to some degree. The performance comparisons among the proposed method and other hybrid location methods are investigated on different NLOS error models and with two scenarios of cell layout. It is found that the proposed method can deal with NLOS error effectively, and it is attractive for location estimation in cellular networks.
Bias Errors due to Leakage Effects When Estimating Frequency Response Functions
Directory of Open Access Journals (Sweden)
Andreas Josefsson
2012-01-01
Full Text Available Frequency response functions are often utilized to characterize a system's dynamic response. For a wide range of engineering applications, it is desirable to determine frequency response functions for a system under stochastic excitation. In practice, the measurement data is contaminated by noise and some form of averaging is needed in order to obtain a consistent estimator. With Welch's method, the discrete Fourier transform is used and the data is segmented into smaller blocks so that averaging can be performed when estimating the spectrum. However, this segmentation introduces leakage effects. As a result, the estimated frequency response function suffers from both systematic (bias and random errors due to leakage. In this paper the bias error in the H1 and H2-estimate is studied and a new method is proposed to derive an approximate expression for the relative bias error at the resonance frequency with different window functions. The method is based on using a sum of real exponentials to describe the window's deterministic autocorrelation function. Simple expressions are derived for a rectangular window and a Hanning window. The theoretical expressions are verified with numerical simulations and a very good agreement is found between the results from the proposed bias expressions and the empirical results.
International Nuclear Information System (INIS)
Yu Watanabe; Masahito Ueda
2012-01-01
Full text: When we try to obtain information about a quantum system, we need to perform measurement on the system. The measurement process causes unavoidable state change. Heisenberg discussed a thought experiment of the position measurement of a particle by using a gamma-ray microscope, and found a trade-off relation between the error of the measured position and the disturbance in the momentum caused by the measurement process. The trade-off relation epitomizes the complementarity in quantum measurements: we cannot perform a measurement of an observable without causing disturbance in its canonically conjugate observable. However, at the time Heisenberg found the complementarity, quantum measurement theory was not established yet, and Kennard and Robertson's inequality erroneously interpreted as a mathematical formulation of the complementarity. Kennard and Robertson's inequality actually implies the indeterminacy of the quantum state: non-commuting observables cannot have definite values simultaneously. However, Kennard and Robertson's inequality reflects the inherent nature of a quantum state alone, and does not concern any trade-off relation between the error and disturbance in the measurement process. In this talk, we report a resolution to the complementarity in quantum measurements. First, we find that it is necessary to involve the estimation process from the outcome of the measurement for quantifying the error and disturbance in the quantum measurement. We clarify the implicitly involved estimation process in Heisenberg's gamma-ray microscope and other measurement schemes, and formulate the error and disturbance for an arbitrary quantum measurement by using quantum estimation theory. The error and disturbance are defined in terms of the Fisher information, which gives the upper bound of the accuracy of the estimation. Second, we obtain uncertainty relations between the measurement errors of two observables [1], and between the error and disturbance in the
Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization
Casas, R.; Marco, A.; Guerrero, J. J.; Falcó, J.
2006-12-01
Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS) errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.). In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS), even when nearly half the measures suffered from NLOS or other coarse errors.
Directory of Open Access Journals (Sweden)
Leszek Klukowski
2012-01-01
Full Text Available This paper presents a review of results of the author in the area of estimation of the relations of equivalence, tolerance and preference within a finite set based on multiple, independent (in a stochastic way pairwise comparisons with random errors, in binary and multivalent forms. These estimators require weaker assumptions than those used in the literature on the subject. Estimates of the relations are obtained based on solutions to problems from discrete optimization. They allow application of both types of comparisons - binary and multivalent (this fact relates to the tolerance and preference relations. The estimates can be verified in a statistical way; in particular, it is possible to verify the type of the relation. The estimates have been applied by the author to problems regarding forecasting, financial engineering and bio-cybernetics. (original abstract
A residual-based a posteriori error estimator for single-phase Darcy flow in fractured porous media
Chen, Huangxin
2016-12-09
In this paper we develop an a posteriori error estimator for a mixed finite element method for single-phase Darcy flow in a two-dimensional fractured porous media. The discrete fracture model is applied to model the fractures by one-dimensional fractures in a two-dimensional domain. We consider Raviart–Thomas mixed finite element method for the approximation of the coupled Darcy flows in the fractures and the surrounding porous media. We derive a robust residual-based a posteriori error estimator for the problem with non-intersecting fractures. The reliability and efficiency of the a posteriori error estimator are established for the error measured in an energy norm. Numerical results verifying the robustness of the proposed a posteriori error estimator are given. Moreover, our numerical results indicate that the a posteriori error estimator also works well for the problem with intersecting fractures.
Pennington, Audrey Flak; Strickland, Matthew J; Klein, Mitchel; Zhai, Xinxin; Russell, Armistead G; Hansen, Craig; Darrow, Lyndsey A
2017-09-01
Prenatal air pollution exposure is frequently estimated using maternal residential location at the time of delivery as a proxy for residence during pregnancy. We describe residential mobility during pregnancy among 19,951 children from the Kaiser Air Pollution and Pediatric Asthma Study, quantify measurement error in spatially resolved estimates of prenatal exposure to mobile source fine particulate matter (PM 2.5 ) due to ignoring this mobility, and simulate the impact of this error on estimates of epidemiologic associations. Two exposure estimates were compared, one calculated using complete residential histories during pregnancy (weighted average based on time spent at each address) and the second calculated using only residence at birth. Estimates were computed using annual averages of primary PM 2.5 from traffic emissions modeled using a Research LINE-source dispersion model for near-surface releases (RLINE) at 250 m resolution. In this cohort, 18.6% of children were born to mothers who moved at least once during pregnancy. Mobile source PM 2.5 exposure estimates calculated using complete residential histories during pregnancy and only residence at birth were highly correlated (r S >0.9). Simulations indicated that ignoring residential mobility resulted in modest bias of epidemiologic associations toward the null, but varied by maternal characteristics and prenatal exposure windows of interest (ranging from -2% to -10% bias).
Error Analysis on the Estimation of Cumulative Infiltration in Soil Using Green and AMPT Model
Directory of Open Access Journals (Sweden)
Muhamad Askari
2006-08-01
Full Text Available Green and Ampt infiltration model is still useful for the infiltration process because of a clear physical basis of the model and of the existence of the model parameter values for a wide range of soil. The objective of thise study was to analyze error on the esimation of cumulative infiltration in sooil using Green and Ampt model and to design laboratory experiment in measuring cumulative infiltration. Parameter of the model was determined based on soil physical properties from laboratory experiment. Newton –Raphson method was esed to estimate wetting front during calculation using visual Basic for Application (VBA in MS Word. The result showed that contributed the highest error in estimation of cumulative infiltration and was followed by K, H0, H1, and t respectively. It also showed that the calculated cumulative infiltration is always lower than both measured cumulative infiltration and volumetric soil water content.
An information-guided channel-hopping scheme for block-fading channels with estimation errors
Yang, Yuli
2010-12-01
Information-guided channel-hopping technique employing multiple transmit antennas was previously proposed for supporting high data rate transmission over fading channels. This scheme achieves higher data rates than some mature schemes, such as the well-known cyclic transmit antenna selection and space-time block coding, by exploiting the independence character of multiple channels, which effectively results in having an additional information transmitting channel. Moreover, maximum likelihood decoding may be performed by simply decoupling the signals conveyed by the different mapping methods. In this paper, we investigate the achievable spectral efficiency of this scheme in the case of having channel estimation errors, with optimum pilot overhead for minimum meansquare error channel estimation, when transmitting over blockfading channels. Our numerical results further substantiate the robustness of the presented scheme, even with imperfect channel state information. ©2010 IEEE.
Approximate damped oscillatory solutions and error estimates for the perturbed Klein–Gordon equation
International Nuclear Information System (INIS)
Ye, Caier; Zhang, Weiguo
2015-01-01
Highlights: • Analyze the dynamical behavior of the planar dynamical system corresponding to the perturbed Klein–Gordon equation. • Present the relations between the properties of traveling wave solutions and the perturbation coefficient. • Obtain all explicit expressions of approximate damped oscillatory solutions. • Investigate error estimates between exact damped oscillatory solutions and the approximate solutions and give some numerical simulations. - Abstract: The influence of perturbation on traveling wave solutions of the perturbed Klein–Gordon equation is studied by applying the bifurcation method and qualitative theory of dynamical systems. All possible approximate damped oscillatory solutions for this equation are obtained by using undetermined coefficient method. Error estimates indicate that the approximate solutions are meaningful. The results of numerical simulations also establish our analysis
Error Estimates for a Semidiscrete Finite Element Method for Fractional Order Parabolic Equations
Jin, Bangti
2013-01-01
We consider the initial boundary value problem for a homogeneous time-fractional diffusion equation with an initial condition ν(x) and a homogeneous Dirichlet boundary condition in a bounded convex polygonal domain Ω. We study two semidiscrete approximation schemes, i.e., the Galerkin finite element method (FEM) and lumped mass Galerkin FEM, using piecewise linear functions. We establish almost optimal with respect to the data regularity error estimates, including the cases of smooth and nonsmooth initial data, i.e., ν ∈ H2(Ω) ∩ H0 1(Ω) and ν ∈ L2(Ω). For the lumped mass method, the optimal L2-norm error estimate is valid only under an additional assumption on the mesh, which in two dimensions is known to be satisfied for symmetric meshes. Finally, we present some numerical results that give insight into the reliability of the theoretical study. © 2013 Society for Industrial and Applied Mathematics.
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger
An economic time series can often be viewed as a noisy proxy for an underlying economic variable. Measurement errors will influence the dynamic properties of the observed process and may conceal the persistence of the underlying time series. In this paper we develop instrumental variable (IV...... application despite the large sample. Unit root tests based on the IV estimator have better finite sample properties in this context....
Verification of functional a posteriori error estimates for obstacle problem in 1D
Czech Academy of Sciences Publication Activity Database
Harasim, P.; Valdman, Jan
2013-01-01
Roč. 49, č. 5 (2013), s. 738-754 ISSN 0023-5954 R&D Projects: GA ČR GA13-18652S Institutional support: RVO:67985556 Keywords : obstacle problem * a posteriori error estimate * variational inequalities Subject RIV: BA - General Mathematics Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2014/MTR/valdman-0424082.pdf
Verification of functional a posteriori error estimates for obstacle problem in 2D
Czech Academy of Sciences Publication Activity Database
Harasim, P.; Valdman, Jan
2014-01-01
Roč. 50, č. 6 (2014), s. 978-1002 ISSN 0023-5954 R&D Projects: GA ČR GA13-18652S Institutional support: RVO:67985556 Keywords : obstacle problem * a posteriori error estimate * finite element method * variational inequalities Subject RIV: BA - General Mathematics Impact factor: 0.541, year: 2014 http://library.utia.cas.cz/separaty/2015/MTR/valdman-0441661.pdf
Rate estimation in partially observed Markov jump processes with measurement errors
Amrein, Michael; Kuensch, Hans R.
2010-01-01
We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced, which allow sampling from the posterior distribution of t...
Czech Academy of Sciences Publication Activity Database
Feireisl, Eduard; Hošek, Radim; Maltese, D.; Novotný, A.
2017-01-01
Roč. 33, č. 4 (2017), s. 1208-1223 ISSN 0749-159X EU Projects: European Commission(XE) 320078 - MATH EF Institutional support: RVO:67985840 Keywords : convergence * error estimates * mixed numerical method * Navier–Stokes system Subject RIV: BA - General Math ematics OBOR OECD: Pure math ematics Impact factor: 1.079, year: 2016 http://onlinelibrary.wiley.com/doi/10.1002/num.22140/abstract
Sensitivity of APSIM/ORYZA model due to estimation errors in solar radiation
Alexandre Bryan Heinemann; Pepijn A.J. van Oort; Diogo Simões Fernandes; Aline de Holanda Nunes Maia
2012-01-01
Crop models are ideally suited to quantify existing climatic risks. However, they require historic climate data as input. While daily temperature and rainfall data are often available, the lack of observed solar radiation (Rs) data severely limits site-specific crop modelling. The objective of this study was to estimate Rs based on air temperature solar radiation models and to quantify the propagation of errors in simulated radiation on several APSIM/ORYZA crop model seasonal outputs, yield, ...
Minimum Mean-Square Error Estimation of Mel-Frequency Cepstral Features
DEFF Research Database (Denmark)
Jensen, Jesper; Tan, Zheng-Hua
2015-01-01
In this work we consider the problem of feature enhancement for noise-robust automatic speech recognition (ASR). We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features, which is based on a minimum number of well-established, theoretically consistent......-of-the-art MFCC feature enhancement algorithms within this class of algorithms, while theoretically suboptimal or based on theoretically inconsistent assumptions, perform close to optimally in the MMSE sense....
Directory of Open Access Journals (Sweden)
Lee HyunYoung
2010-01-01
Full Text Available We analyze discontinuous Galerkin methods with penalty terms, namely, symmetric interior penalty Galerkin methods, to solve nonlinear Sobolev equations. We construct finite element spaces on which we develop fully discrete approximations using extrapolated Crank-Nicolson method. We adopt an appropriate elliptic-type projection, which leads to optimal error estimates of discontinuous Galerkin approximations in both spatial direction and temporal direction.
Jakeman, J. D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.
International Nuclear Information System (INIS)
Jakeman, J.D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation
Dreano, Denis
2017-04-05
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended and ensemble versions of the Kalman smoother. We show that, for additive model errors, the estimate of the error covariance converges. We also investigate other forms of model error, such as parametric or multiplicative errors. We show that additive Gaussian model error is able to compensate for non additive sources of error in the algorithms we propose. We also demonstrate the limitations of the extended version of the algorithm and recommend the use of the more robust and flexible ensemble version. This article is a proof of concept of the methodology with the Lorenz-63 attractor. We developed an open-source Python library to enable future users to apply the algorithm to their own nonlinear dynamical models.
On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator.
Ballesteros, Joaquin; Urdiales, Cristina; Martinez, Antonio B; van Dieën, Jaap H
2016-11-10
Gait analysis can provide valuable information on a person's condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i) there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars-related to the user condition-and the estimation error; and (ii) this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation.
On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator
Directory of Open Access Journals (Sweden)
Joaquin Ballesteros
2016-11-01
Full Text Available Gait analysis can provide valuable information on a person’s condition and rehabilitation progress. Gait is typically captured using external equipment and/or wearable sensors. These tests are largely constrained to specific controlled environments. In addition, gait analysis often requires experts for calibration, operation and/or to place sensors on volunteers. Alternatively, mobility support devices like rollators can be equipped with onboard sensors to monitor gait parameters, while users perform their Activities of Daily Living. Gait analysis in rollators may use odometry and force sensors in the handlebars. However, force based estimation of gait parameters is less accurate than traditional methods, especially when rollators are not properly used. This paper presents an evaluation of force based gait analysis using a smart rollator on different groups of users to determine when this methodology is applicable. In a second stage, the rollator is used in combination with two lab-based gait analysis systems to assess the rollator estimation error. Our results show that: (i there is an inverse relation between the variance in the force difference between handlebars and support on the handlebars—related to the user condition—and the estimation error; and (ii this error is lower than 10% when the variation in the force difference is above 7 N. This lower limit was exceeded by the 95.83% of our challenged volunteers. In conclusion, rollators are useful for gait characterization as long as users really need the device for ambulation.
Estimating the Standard Error of the Judging in a modified-Angoff Standards Setting Procedure
Directory of Open Access Journals (Sweden)
Robert G. MacCann
2004-03-01
Full Text Available For a modified Angoff standards setting procedure, two methods of calculating the standard error of the..judging were compared. The Central Limit Theorem (CLT method is easy to calculate and uses readily..available data. It estimates the variance of mean cut scores as a function of the variance of cut scores within..a judging group, based on the independent judgements at Stage 1 of the process. Its theoretical drawback is..that it is unable to take account of the effects of collaboration among the judges at Stages 2 and 3. The..second method, an application of equipercentile (EQP equating, relies on the selection of very large stable..candidatures and the standardisation of the raw score distributions to remove effects associated with test..difficulty. The standard error estimates were then empirically obtained from the mean cut score variation..observed over a five year period. For practical purposes, the two methods gave reasonable agreement, with..the CLT method working well for the top band, the band that attracts most public attention. For some..bands in English and Mathematics, the CLT standard error was smaller than the EQP estimate, suggesting..the CLT method be used with caution as an approximate guide only.
mBEEF-vdW: Robust fitting of error estimation density functionals
DEFF Research Database (Denmark)
Lundgård, Keld Troen; Wellendorff, Jess; Voss, Johannes
2016-01-01
. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012); J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014)]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function...... catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show...
An error reduction algorithm to improve lidar turbulence estimates for wind energy
Directory of Open Access Journals (Sweden)
J. F. Newman
2017-02-01
Full Text Available Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine
Wang, Wentao; Lee, Yi Kuen
2012-01-01
Both theoretical analysis and nonlinear 2D numerical simulations are used to study the concentration difference and Peclet number effect on the measurement error of electroosmotic mobility in microchannels. We propose a compact analytical model
Lock, Jacobus C.; Smit, Willie J.; Treurnicht, Johann
2016-05-01
The Solar Thermal Energy Research Group (STERG) is investigating ways to make heliostats cheaper to reduce the total cost of a concentrating solar power (CSP) plant. One avenue of research is to use unmanned aerial vehicles (UAVs) to automate and assist with the heliostat calibration process. To do this, the pose estimation error of each UAV must be determined and integrated into a calibration procedure. A computer vision (CV) system is used to measure the pose of a quadcopter UAV. However, this CV system contains considerable measurement errors. Since this is a high-dimensional problem, a sophisticated prediction model must be used to estimate the measurement error of the CV system for any given pose measurement vector. This paper attempts to train and validate such a model with the aim of using it to determine the pose error of a quadcopter in a CSP plant setting.
The Euler equation with habits and measurement errors: Estimates on Russian micro data
Directory of Open Access Journals (Sweden)
Khvostova Irina
2016-01-01
Full Text Available This paper presents estimates of the consumption Euler equation for Russia. The estimation is based on micro-level panel data and accounts for the heterogeneity of agents’ preferences and measurement errors. The presence of multiplicative habits is checked using the Lagrange multiplier (LM test in a generalized method of moments (GMM framework. We obtain estimates of the elasticity of intertemporal substitution and of the subjective discount factor, which are consistent with the theoretical model and can be used for the calibration and the Bayesian estimation of dynamic stochastic general equilibrium (DSGE models for the Russian economy. We also show that the effects of habit formation are not significant. The hypotheses of multiplicative habits (external, internal, and both external and internal are not supported by the data.
Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.
2011-01-01
A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from
In vivo estimation of target registration errors during augmented reality laparoscopic surgery.
Thompson, Stephen; Schneider, Crispin; Bosi, Michele; Gurusamy, Kurinchi; Ourselin, Sébastien; Davidson, Brian; Hawkes, David; Clarkson, Matthew J
2018-06-01
Successful use of augmented reality for laparoscopic surgery requires that the surgeon has a thorough understanding of the likely accuracy of any overlay. Whilst the accuracy of such systems can be estimated in the laboratory, it is difficult to extend such methods to the in vivo clinical setting. Herein we describe a novel method that enables the surgeon to estimate in vivo errors during use. We show that the method enables quantitative evaluation of in vivo data gathered with the SmartLiver image guidance system. The SmartLiver system utilises an intuitive display to enable the surgeon to compare the positions of landmarks visible in both a projected model and in the live video stream. From this the surgeon can estimate the system accuracy when using the system to locate subsurface targets not visible in the live video. Visible landmarks may be either point or line features. We test the validity of the algorithm using an anatomically representative liver phantom, applying simulated perturbations to achieve clinically realistic overlay errors. We then apply the algorithm to in vivo data. The phantom results show that using projected errors of surface features provides a reliable predictor of subsurface target registration error for a representative human liver shape. Applying the algorithm to in vivo data gathered with the SmartLiver image-guided surgery system shows that the system is capable of accuracies around 12 mm; however, achieving this reliably remains a significant challenge. We present an in vivo quantitative evaluation of the SmartLiver image-guided surgery system, together with a validation of the evaluation algorithm. This is the first quantitative in vivo analysis of an augmented reality system for laparoscopic surgery.
DeLacy, Brendan G; Bandy, Alan R
2008-01-01
An atmospheric pressure ionization mass spectrometry/isotopically labeled standard (APIMS/ILS) method has been developed for the determination of carbon dioxide (CO(2)) concentration. Descriptions of the instrumental components, the ionization chemistry, and the statistics associated with the analytical method are provided. This method represents an alternative to the nondispersive infrared (NDIR) technique, which is currently used in the atmospheric community to determine atmospheric CO(2) concentrations. The APIMS/ILS and NDIR methods exhibit a decreased sensitivity for CO(2) in the presence of water vapor. Therefore, dryers such as a nafion dryer are used to remove water before detection. The APIMS/ILS method measures mixing ratios and demonstrates linearity and range in the presence or absence of a dryer. The NDIR technique, on the other hand, measures molar concentrations. The second half of this paper describes errors in molar concentration measurements that are caused by drying. An equation describing the errors was derived from the ideal gas law, the conservation of mass, and Dalton's Law. The purpose of this derivation was to quantify errors in the NDIR technique that are caused by drying. Laboratory experiments were conducted to verify the errors created solely by the dryer in CO(2) concentration measurements post-dryer. The laboratory experiments verified the theoretically predicted errors in the derived equations. There are numerous references in the literature that describe the use of a dryer in conjunction with the NDIR technique. However, these references do not address the errors that are caused by drying.
Silva, Leandro de Carvalho da; Pereira-Monfredini, Carla Ferro; Teixeira, Luis Augusto
2017-09-01
This study aimed at assessing the interaction between subjective error estimation and frequency of extrinsic feedback in the learning of the basketball free shooting pattern by children. 10- to 12-year olds were assigned to 1 of 4 groups combining subjective error estimation and relative frequency of extrinsic feedback (33% × 100%). Analysis of performance was based on quality of movement pattern. Analysis showed superior learning of the group combining error estimation and 100% feedback frequency, both groups receiving feedback on 33% of trials achieved intermediate results, and the group combining no requirement of error estimation and 100% feedback frequency had the poorest learning. Our results show the benefit of subjective error estimation in association with high frequency of extrinsic feedback in children's motor learning of a sport motor pattern.
Estimating the State of Aerodynamic Flows in the Presence of Modeling Errors
da Silva, Andre F. C.; Colonius, Tim
2017-11-01
The ensemble Kalman filter (EnKF) has been proven to be successful in fields such as meteorology, in which high-dimensional nonlinear systems render classical estimation techniques impractical. When the model used to forecast state evolution misrepresents important aspects of the true dynamics, estimator performance may degrade. In this work, parametrization and state augmentation are used to track misspecified boundary conditions (e.g., free stream perturbations). The resolution error is modeled as a Gaussian-distributed random variable with the mean (bias) and variance to be determined. The dynamics of the flow past a NACA 0009 airfoil at high angles of attack and moderate Reynolds number is represented by a Navier-Stokes equations solver with immersed boundaries capabilities. The pressure distribution on the airfoil or the velocity field in the wake, both randomized by synthetic noise, are sampled as measurement data and incorporated into the estimated state and bias following Kalman's analysis scheme. Insights about how to specify the modeling error covariance matrix and its impact on the estimator performance are conveyed. This work has been supported in part by a Grant from AFOSR (FA9550-14-1-0328) with Dr. Douglas Smith as program manager, and by a Science without Borders scholarship from the Ministry of Education of Brazil (Capes Foundation - BEX 12966/13-4).
Owens, A. R.; Kópházi, J.; Welch, J. A.; Eaton, M. D.
2017-04-01
In this paper a hanging-node, discontinuous Galerkin, isogeometric discretisation of the multigroup, discrete ordinates (SN) equations is presented in which each energy group has its own mesh. The equations are discretised using Non-Uniform Rational B-Splines (NURBS), which allows the coarsest mesh to exactly represent the geometry for a wide range of engineering problems of interest; this would not be the case using straight-sided finite elements. Information is transferred between meshes via the construction of a supermesh. This is a non-trivial task for two arbitrary meshes, but is significantly simplified here by deriving every mesh from a common coarsest initial mesh. In order to take full advantage of this flexible discretisation, goal-based error estimators are derived for the multigroup, discrete ordinates equations with both fixed (extraneous) and fission sources, and these estimators are used to drive an adaptive mesh refinement (AMR) procedure. The method is applied to a variety of test cases for both fixed and fission source problems. The error estimators are found to be extremely accurate for linear NURBS discretisations, with degraded performance for quadratic discretisations owing to a reduction in relative accuracy of the "exact" adjoint solution required to calculate the estimators. Nevertheless, the method seems to produce optimal meshes in the AMR process for both linear and quadratic discretisations, and is ≈×100 more accurate than uniform refinement for the same amount of computational effort for a 67 group deep penetration shielding problem.
Estimating and comparing microbial diversity in the presence of sequencing errors
Chiu, Chun-Huo
2016-01-01
Estimating and comparing microbial diversity are statistically challenging due to limited sampling and possible sequencing errors for low-frequency counts, producing spurious singletons. The inflated singleton count seriously affects statistical analysis and inferences about microbial diversity. Previous statistical approaches to tackle the sequencing errors generally require different parametric assumptions about the sampling model or about the functional form of frequency counts. Different parametric assumptions may lead to drastically different diversity estimates. We focus on nonparametric methods which are universally valid for all parametric assumptions and can be used to compare diversity across communities. We develop here a nonparametric estimator of the true singleton count to replace the spurious singleton count in all methods/approaches. Our estimator of the true singleton count is in terms of the frequency counts of doubletons, tripletons and quadrupletons, provided these three frequency counts are reliable. To quantify microbial alpha diversity for an individual community, we adopt the measure of Hill numbers (effective number of taxa) under a nonparametric framework. Hill numbers, parameterized by an order q that determines the measures’ emphasis on rare or common species, include taxa richness (q = 0), Shannon diversity (q = 1, the exponential of Shannon entropy), and Simpson diversity (q = 2, the inverse of Simpson index). A diversity profile which depicts the Hill number as a function of order q conveys all information contained in a taxa abundance distribution. Based on the estimated singleton count and the original non-singleton frequency counts, two statistical approaches (non-asymptotic and asymptotic) are developed to compare microbial diversity for multiple communities. (1) A non-asymptotic approach refers to the comparison of estimated diversities of standardized samples with a common finite sample size or sample completeness. This
Regional estimation of extreme suspended sediment concentrations using watershed characteristics
Tramblay, Yves; Ouarda, Taha B. M. J.; St-Hilaire, André; Poulin, Jimmy
2010-01-01
SummaryThe number of stations monitoring daily suspended sediment concentration (SSC) has been decreasing since the 1980s in North America while suspended sediment is considered as a key variable for water quality. The objective of this study is to test the feasibility of regionalising extreme SSC, i.e. estimating SSC extremes values for ungauged basins. Annual maximum SSC for 72 rivers in Canada and USA were modelled with probability distributions in order to estimate quantiles corresponding to different return periods. Regionalisation techniques, originally developed for flood prediction in ungauged basins, were tested using the climatic, topographic, land cover and soils attributes of the watersheds. Two approaches were compared, using either physiographic characteristics or seasonality of extreme SSC to delineate the regions. Multiple regression models to estimate SSC quantiles as a function of watershed characteristics were built in each region, and compared to a global model including all sites. Regional estimates of SSC quantiles were compared with the local values. Results show that regional estimation of extreme SSC is more efficient than a global regression model including all sites. Groups/regions of stations have been identified, using either the watershed characteristics or the seasonality of occurrence for extreme SSC values providing a method to better describe the extreme events of SSC. The most important variables for predicting extreme SSC are the percentage of clay in the soils, precipitation intensity and forest cover.
Sanderson, Eleanor; Macdonald-Wallis, Corrie; Davey Smith, George
2018-04-01
Negative control exposure studies are increasingly being used in epidemiological studies to strengthen causal inference regarding an exposure-outcome association when unobserved confounding is thought to be present. Negative control exposure studies contrast the magnitude of association of the negative control, which has no causal effect on the outcome but is associated with the unmeasured confounders in the same way as the exposure, with the magnitude of the association of the exposure with the outcome. A markedly larger effect of the exposure on the outcome than the negative control on the outcome strengthens inference that the exposure has a causal effect on the outcome. We investigate the effect of measurement error in the exposure and negative control variables on the results obtained from a negative control exposure study. We do this in models with continuous and binary exposure and negative control variables using analysis of the bias of the estimated coefficients and Monte Carlo simulations. Our results show that measurement error in either the exposure or negative control variables can bias the estimated results from the negative control exposure study. Measurement error is common in the variables used in epidemiological studies; these results show that negative control exposure studies cannot be used to precisely determine the size of the effect of the exposure variable, or adequately adjust for unobserved confounding; however, they can be used as part of a body of evidence to aid inference as to whether a causal effect of the exposure on the outcome is present.
Evaluation of the sources of error in the linepack estimation of a natural gas pipeline
Energy Technology Data Exchange (ETDEWEB)
Marco, Fabio Capelassi Gavazzi de [Transportadora Brasileira Gasoduto Bolivia-Brasil S.A. (TBG), Rio de Janeiro, RJ (Brazil)
2012-07-01
The intent of this work is to explore the behavior of the random error associated with determination of linepack in a complex natural gas pipeline based on the effect introduced by the uncertainty of the different variables involved. There are many parameters involved in the determination of the gas inventory in a transmission pipeline: geometrical (diameter, length and elevation profile), operational (pressure, temperature and gas composition), environmental (ambient / ground temperature) and those dependent on the modeling assumptions (compressibility factor and heat transfer coefficient). Due to the extent of a natural gas pipeline and the vast amount of sensor involved it is infeasible to determine analytically the magnitude of resulting uncertainty in the linepack, thus this problem has been addressed using Monte Carlo Method. The approach consists of introducing random errors in the values of pressure, temperature and gas gravity that are employed in the determination of the linepack and verify its impact. Additionally, the errors associated with three different modeling assumptions to estimate the linepack are explored. The results reveal that pressure is the most critical variable while the temperature is the less critical. In regard to the different methods to estimate the linepack, deviations around 1.6% were verified among the methods. (author)
Estimated effects of temperature on secondary organic aerosol concentrations.
Sheehan, P E; Bowman, F M
2001-06-01
The temperature-dependence of secondary organic aerosol (SOA) concentrations is explored using an absorptive-partitioning model under a variety of simplified atmospheric conditions. Experimentally determined partitioning parameters for high yield aromatics are used. Variation of vapor pressures with temperature is assumed to be the main source of temperature effects. Known semivolatile products are used to define a modeling range of vaporization enthalpy of 10-25 kcal/mol-1. The effect of diurnal temperature variations on model predictions for various assumed vaporization enthalpies, precursor emission rates, and primary organic concentrations is explored. Results show that temperature is likely to have a significant influence on SOA partitioning and resulting SOA concentrations. A 10 degrees C decrease in temperature is estimated to increase SOA yields by 20-150%, depending on the assumed vaporization enthalpy. In model simulations, high daytime temperatures tend to reduce SOA concentrations by 16-24%, while cooler nighttime temperatures lead to a 22-34% increase, compared to constant temperature conditions. Results suggest that currently available constant temperature partitioning coefficients do not adequately represent atmospheric SOA partitioning behavior. Air quality models neglecting the temperature dependence of partitioning are expected to underpredict peak SOA concentrations as well as mistime their occurrence.
Error due to unresolved scales in estimation problems for atmospheric data assimilation
Janjic, Tijana
The error arising due to unresolved scales in data assimilation procedures is examined. The problem of estimating the projection of the state of a passive scalar undergoing advection at a sequence of times is considered. The projection belongs to a finite- dimensional function space and is defined on the continuum. Using the continuum projection of the state of a passive scalar, a mathematical definition is obtained for the error arising due to the presence, in the continuum system, of scales unresolved by the discrete dynamical model. This error affects the estimation procedure through point observations that include the unresolved scales. In this work, two approximate methods for taking into account the error due to unresolved scales and the resulting correlations are developed and employed in the estimation procedure. The resulting formulas resemble the Schmidt-Kalman filter and the usual discrete Kalman filter, respectively. For this reason, the newly developed filters are called the Schmidt-Kalman filter and the traditional filter. In order to test the assimilation methods, a two- dimensional advection model with nonstationary spectrum was developed for passive scalar transport in the atmosphere. An analytical solution on the sphere was found depicting the model dynamics evolution. Using this analytical solution the model error is avoided, and the error due to unresolved scales is the only error left in the estimation problem. It is demonstrated that the traditional and the Schmidt- Kalman filter work well provided the exact covariance function of the unresolved scales is known. However, this requirement is not satisfied in practice, and the covariance function must be modeled. The Schmidt-Kalman filter cannot be computed in practice without further approximations. Therefore, the traditional filter is better suited for practical use. Also, the traditional filter does not require modeling of the full covariance function of the unresolved scales, but only
Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning
Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.
2017-12-01
Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree
DEFF Research Database (Denmark)
Wellendorff, Jess; Lundgård, Keld Troen; Møgelhøj, Andreas
2012-01-01
A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding the overfit......A methodology for semiempirical density functional optimization, using regularization and cross-validation methods from machine learning, is developed. We demonstrate that such methods enable well-behaved exchange-correlation approximations in very flexible model spaces, thus avoiding...... the energetics of intramolecular and intermolecular, bulk solid, and surface chemical bonding, and the developed optimization method explicitly handles making the compromise based on the directions in model space favored by different materials properties. The approach is applied to designing the Bayesian error...... sets validates the applicability of BEEF-vdW to studies in chemistry and condensed matter physics. Applications of the approximation and its Bayesian ensemble error estimate to two intricate surface science problems support this....
Model methodology for estimating pesticide concentration extremes based on sparse monitoring data
Vecchia, Aldo V.
2018-03-22
This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.
International Nuclear Information System (INIS)
Yashiki, Taturou; Yagawa, Genki; Okuda, Hiroshi
1995-01-01
The adaptive finite element method based on an 'a posteriori error estimation' is known to be a powerful technique for analyzing the engineering practical problems, since it excludes the instinctive aspect of the mesh subdivision and gives high accuracy with relatively low computational cost. In the adaptive procedure, both the error estimation and the mesh generation according to the error estimator are essential. In this paper, the adaptive procedure is realized by the automatic mesh generation based on the control of node density distribution, which is decided according to the error estimator. The global percentage error, CPU time, the degrees of freedom and the accuracy of the solution of the adaptive procedure are compared with those of the conventional method using regular meshes. Such numerical examples as the driven cavity flows of various Reynolds numbers and the flows around a cylinder have shown the very high performance of the proposed adaptive procedure. (author)
Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.
Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko
2017-06-01
Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.
A feasibility study of mutual information based setup error estimation for radiotherapy
International Nuclear Information System (INIS)
Kim, Jeongtae; Fessler, Jeffrey A.; Lam, Kwok L.; Balter, James M.; Haken, Randall K. ten
2001-01-01
We have investigated a fully automatic setup error estimation method that aligns DRRs (digitally reconstructed radiographs) from a three-dimensional planning computed tomography image onto two-dimensional radiographs that are acquired in a treatment room. We have chosen a MI (mutual information)-based image registration method, hoping for robustness to intensity differences between the DRRs and the radiographs. The MI-based estimator is fully automatic since it is based on the image intensity values without segmentation. Using 10 repeated scans of an anthropomorphic chest phantom in one position and two single scans in two different positions, we evaluated the performance of the proposed method and a correlation-based method against the setup error determined by fiducial marker-based method. The mean differences between the proposed method and the fiducial marker-based method were smaller than 1 mm for translational parameters and 0.8 degree for rotational parameters. The standard deviations of estimates from the proposed method due to detector noise were smaller than 0.3 mm and 0.07 degree for the translational parameters and rotational parameters, respectively
Recursive prediction error methods for online estimation in nonlinear state-space models
Directory of Open Access Journals (Sweden)
Dag Ljungquist
1994-04-01
Full Text Available Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive prediction error method are included, as well as a new method based on a line-search strategy. A comparison of the algorithms illustrates that they are very similar although the differences can be important for the online tracking capabilities and robustness. Simulation experiments on a simple nonlinear process show that the performance under certain conditions can be improved by including a line-search strategy.
Yang, Shuang-Long; Liang, Li-Ping; Liu, Hou-De; Xu, Ke-Jun
2018-03-01
Aiming at reducing the estimation error of the sensor frequency response function (FRF) estimated by the commonly used window-based spectral estimation method, the error models of interpolation and transient errors are derived in the form of non-parameter models. Accordingly, window effects on the errors are analyzed and reveal that the commonly used hanning window leads to smaller interpolation error which can also be significantly eliminated by the cubic spline interpolation method when estimating the FRF from the step response data, and window with smaller front-end value can restrain more transient error. Thus, a new dual-cosine window with its non-zero discrete Fourier transform bins at -3, -1, 0, 1, and 3 is constructed for FRF estimation. Compared with the hanning window, the new dual-cosine window has the equivalent interpolation error suppression capability and better transient error suppression capability when estimating the FRF from the step response; specifically, it reduces the asymptotic property of the transient error from O(N-2) of the hanning window method to O(N-4) while only increases the uncertainty slightly (about 0.4 dB). Then, one direction of a wind tunnel strain gauge balance which is a high order, small damping, and non-minimum phase system is employed as the example for verifying the new dual-cosine window-based spectral estimation method. The model simulation result shows that the new dual-cosine window method is better than the hanning window method for FRF estimation, and compared with the Gans method and LPM method, it has the advantages of simple computation, less time consumption, and short data requirement; the actual data calculation result of the balance FRF is consistent to the simulation result. Thus, the new dual-cosine window is effective and practical for FRF estimation.
International Nuclear Information System (INIS)
Acquaviva, Viviana; Raichoor, Anand; Gawiser, Eric
2015-01-01
We seek to improve the accuracy of joint galaxy photometric redshift estimation and spectral energy distribution (SED) fitting. By simulating different sources of uncorrected systematic errors, we demonstrate that if the uncertainties in the photometric redshifts are estimated correctly, so are those on the other SED fitting parameters, such as stellar mass, stellar age, and dust reddening. Furthermore, we find that if the redshift uncertainties are over(under)-estimated, the uncertainties in SED parameters tend to be over(under)-estimated by similar amounts. These results hold even in the presence of severe systematics and provide, for the first time, a mechanism to validate the uncertainties on these parameters via comparison with spectroscopic redshifts. We propose a new technique (annealing) to re-calibrate the joint uncertainties in the photo-z and SED fitting parameters without compromising the performance of the SED fitting + photo-z estimation. This procedure provides a consistent estimation of the multi-dimensional probability distribution function in SED fitting + z parameter space, including all correlations. While the performance of joint SED fitting and photo-z estimation might be hindered by template incompleteness, we demonstrate that the latter is “flagged” by a large fraction of outliers in redshift, and that significant improvements can be achieved by using flexible stellar populations synthesis models and more realistic star formation histories. In all cases, we find that the median stellar age is better recovered than the time elapsed from the onset of star formation. Finally, we show that using a photometric redshift code such as EAZY to obtain redshift probability distributions that are then used as priors for SED fitting codes leads to only a modest bias in the SED fitting parameters and is thus a viable alternative to the simultaneous estimation of SED parameters and photometric redshifts
Unit Root Testing and Estimation in Nonlinear ESTAR Models with Normal and Non-Normal Errors.
Directory of Open Access Journals (Sweden)
Umair Khalil
Full Text Available Exponential Smooth Transition Autoregressive (ESTAR models can capture non-linear adjustment of the deviations from equilibrium conditions which may explain the economic behavior of many variables that appear non stationary from a linear viewpoint. Many researchers employ the Kapetanios test which has a unit root as the null and a stationary nonlinear model as the alternative. However this test statistics is based on the assumption of normally distributed errors in the DGP. Cook has analyzed the size of the nonlinear unit root of this test in the presence of heavy-tailed innovation process and obtained the critical values for both finite variance and infinite variance cases. However the test statistics of Cook are oversized. It has been found by researchers that using conventional tests is dangerous though the best performance among these is a HCCME. The over sizing for LM tests can be reduced by employing fixed design wild bootstrap remedies which provide a valuable alternative to the conventional tests. In this paper the size of the Kapetanios test statistic employing hetroscedastic consistent covariance matrices has been derived and the results are reported for various sample sizes in which size distortion is reduced. The properties for estimates of ESTAR models have been investigated when errors are assumed non-normal. We compare the results obtained through the fitting of nonlinear least square with that of the quantile regression fitting in the presence of outliers and the error distribution was considered to be from t-distribution for various sample sizes.
Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization
Directory of Open Access Journals (Sweden)
Marco A
2006-01-01
Full Text Available Indoor localization systems are undoubtedly of interest in many application fields. Like outdoor systems, they suffer from non-line-of-sight (NLOS errors which hinder their robustness and accuracy. Though many ad hoc techniques have been developed to deal with this problem, unfortunately most of them are not applicable indoors due to the high variability of the environment (movement of furniture and of people, etc.. In this paper, we describe the use of robust regression techniques to detect and reject NLOS measures in a location estimation using multilateration. We show how the least-median-of-squares technique can be used to overcome the effects of NLOS errors, even in environments with little infrastructure, and validate its suitability by comparing it to other methods described in the bibliography. We obtained remarkable results when using it in a real indoor positioning system that works with Bluetooth and ultrasound (BLUPS, even when nearly half the measures suffered from NLOS or other coarse errors.
Guchhait, Shyamal; Banerjee, Biswanath
2018-04-01
In this paper, a variant of constitutive equation error based material parameter estimation procedure for linear elastic plates is developed from partially measured free vibration sig-natures. It has been reported in many research articles that the mode shape curvatures are much more sensitive compared to mode shape themselves to localize inhomogeneity. Complying with this idea, an identification procedure is framed as an optimization problem where the proposed cost function measures the error in constitutive relation due to incompatible curvature/strain and moment/stress fields. Unlike standard constitutive equation error based procedure wherein a solution of a couple system is unavoidable in each iteration, we generate these incompatible fields via two linear solves. A simple, yet effective, penalty based approach is followed to incorporate measured data. The penalization parameter not only helps in incorporating corrupted measurement data weakly but also acts as a regularizer against the ill-posedness of the inverse problem. Explicit linear update formulas are then developed for anisotropic linear elastic material. Numerical examples are provided to show the applicability of the proposed technique. Finally, an experimental validation is also provided.
Capacity estimation and verification of quantum channels with arbitrarily correlated errors.
Pfister, Corsin; Rol, M Adriaan; Mantri, Atul; Tomamichel, Marco; Wehner, Stephanie
2018-01-02
The central figure of merit for quantum memories and quantum communication devices is their capacity to store and transmit quantum information. Here, we present a protocol that estimates a lower bound on a channel's quantum capacity, even when there are arbitrarily correlated errors. One application of these protocols is to test the performance of quantum repeaters for transmitting quantum information. Our protocol is easy to implement and comes in two versions. The first estimates the one-shot quantum capacity by preparing and measuring in two different bases, where all involved qubits are used as test qubits. The second verifies on-the-fly that a channel's one-shot quantum capacity exceeds a minimal tolerated value while storing or communicating data. We discuss the performance using simple examples, such as the dephasing channel for which our method is asymptotically optimal. Finally, we apply our method to a superconducting qubit in experiment.
Sensitivity of APSIM/ORYZA model due to estimation errors in solar radiation
Directory of Open Access Journals (Sweden)
Alexandre Bryan Heinemann
2012-01-01
Full Text Available Crop models are ideally suited to quantify existing climatic risks. However, they require historic climate data as input. While daily temperature and rainfall data are often available, the lack of observed solar radiation (Rs data severely limits site-specific crop modelling. The objective of this study was to estimate Rs based on air temperature solar radiation models and to quantify the propagation of errors in simulated radiation on several APSIM/ORYZA crop model seasonal outputs, yield, biomass, leaf area (LAI and total accumulated solar radiation (SRA during the crop cycle. The accuracy of the 5 models for estimated daily solar radiation was similar, and it was not substantially different among sites. For water limited environments (no irrigation, crop model outputs yield, biomass and LAI was not sensitive for the uncertainties in radiation models studied here.
Estimating oil product demand in Indonesia using a cointegrating error correction model
International Nuclear Information System (INIS)
Dahl, C.
2001-01-01
Indonesia's long oil production history and large population mean that Indonesian oil reserves, per capita, are the lowest in OPEC and that, eventually, Indonesia will become a net oil importer. Policy-makers want to forestall this day, since oil revenue comprised around a quarter of both the government budget and foreign exchange revenues for the fiscal years 1997/98. To help policy-makers determine how economic growth and oil-pricing policy affect the consumption of oil products, we estimate the demand for six oil products and total petroleum consumption, using an error correction-cointegration approach, and compare it with estimates on a lagged endogenous model using data for 1970-95. (author)
Borovikov, Anna; Rienecker, Michele M.; Keppenne, Christian; Johnson, Gregory C.
2004-01-01
One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the
Global error estimation based on the tolerance proportionality for some adaptive Runge-Kutta codes
Calvo, M.; González-Pinto, S.; Montijano, J. I.
2008-09-01
Modern codes for the numerical solution of Initial Value Problems (IVPs) in ODEs are based in adaptive methods that, for a user supplied tolerance [delta], attempt to advance the integration selecting the size of each step so that some measure of the local error is [similar, equals][delta]. Although this policy does not ensure that the global errors are under the prescribed tolerance, after the early studies of Stetter [Considerations concerning a theory for ODE-solvers, in: R. Burlisch, R.D. Grigorieff, J. Schröder (Eds.), Numerical Treatment of Differential Equations, Proceedings of Oberwolfach, 1976, Lecture Notes in Mathematics, vol. 631, Springer, Berlin, 1978, pp. 188-200; Tolerance proportionality in ODE codes, in: R. März (Ed.), Proceedings of the Second Conference on Numerical Treatment of Ordinary Differential Equations, Humbold University, Berlin, 1980, pp. 109-123] and the extensions of Higham [Global error versus tolerance for explicit Runge-Kutta methods, IMA J. Numer. Anal. 11 (1991) 457-480; The tolerance proportionality of adaptive ODE solvers, J. Comput. Appl. Math. 45 (1993) 227-236; The reliability of standard local error control algorithms for initial value ordinary differential equations, in: Proceedings: The Quality of Numerical Software: Assessment and Enhancement, IFIP Series, Springer, Berlin, 1997], it has been proved that in many existing explicit Runge-Kutta codes the global errors behave asymptotically as some rational power of [delta]. This step-size policy, for a given IVP, determines at each grid point tn a new step-size hn+1=h(tn;[delta]) so that h(t;[delta]) is a continuous function of t. In this paper a study of the tolerance proportionality property under a discontinuous step-size policy that does not allow to change the size of the step if the step-size ratio between two consecutive steps is close to unity is carried out. This theory is applied to obtain global error estimations in a few problems that have been solved with
Trends and Correlation Estimation in Climate Sciences: Effects of Timescale Errors
Mudelsee, M.; Bermejo, M. A.; Bickert, T.; Chirila, D.; Fohlmeister, J.; Köhler, P.; Lohmann, G.; Olafsdottir, K.; Scholz, D.
2012-12-01
Trend describes time-dependence in the first moment of a stochastic process, and correlation measures the linear relation between two random variables. Accurately estimating the trend and correlation, including uncertainties, from climate time series data in the uni- and bivariate domain, respectively, allows first-order insights into the geophysical process that generated the data. Timescale errors, ubiquitious in paleoclimatology, where archives are sampled for proxy measurements and dated, poses a problem to the estimation. Statistical science and the various applied research fields, including geophysics, have almost completely ignored this problem due to its theoretical almost-intractability. However, computational adaptations or replacements of traditional error formulas have become technically feasible. This contribution gives a short overview of such an adaptation package, bootstrap resampling combined with parametric timescale simulation. We study linear regression, parametric change-point models and nonparametric smoothing for trend estimation. We introduce pairwise-moving block bootstrap resampling for correlation estimation. Both methods share robustness against autocorrelation and non-Gaussian distributional shape. We shortly touch computing-intensive calibration of bootstrap confidence intervals and consider options to parallelize the related computer code. Following examples serve not only to illustrate the methods but tell own climate stories: (1) the search for climate drivers of the Agulhas Current on recent timescales, (2) the comparison of three stalagmite-based proxy series of regional, western German climate over the later part of the Holocene, and (3) trends and transitions in benthic oxygen isotope time series from the Cenozoic. Financial support by Deutsche Forschungsgemeinschaft (FOR 668, FOR 1070, MU 1595/4-1) and the European Commission (MC ITN 238512, MC ITN 289447) is acknowledged.
Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.
Directory of Open Access Journals (Sweden)
Timothy B Hallett
2009-05-01
Full Text Available The BED Capture Enzyme Immunoassay, believed to distinguish recent HIV infections, is being used to estimate HIV incidence, although an important property of the test--how specificity changes with time since infection--has not been not measured.We construct hypothetical scenarios for the performance of BED test, consistent with current knowledge, and explore how this could influence errors in BED estimates of incidence using a mathematical model of six African countries. The model is also used to determine the conditions and the sample sizes required for the BED test to reliably detect trends in HIV incidence.If the chance of misclassification by BED increases with time since infection, the overall proportion of individuals misclassified could vary widely between countries, over time, and across age-groups, in a manner determined by the historic course of the epidemic and the age-pattern of incidence. Under some circumstances, changes in BED estimates over time can approximately track actual changes in incidence, but large sample sizes (50,000+ will be required for recorded changes to be statistically significant.The relationship between BED test specificity and time since infection has not been fully measured, but, if it decreases, errors in estimates of incidence could vary by place, time and age-group. This means that post-assay adjustment procedures using parameters from different populations or at different times may not be valid. Further research is urgently needed into the properties of the BED test, and the rate of misclassification in a wide range of populations.
Measurement Error Affects Risk Estimates for Recruitment to the Hudson River Stock of Striped Bass
Directory of Open Access Journals (Sweden)
Dennis J. Dunning
2002-01-01
Full Text Available We examined the consequences of ignoring the distinction between measurement error and natural variability in an assessment of risk to the Hudson River stock of striped bass posed by entrainment at the Bowline Point, Indian Point, and Roseton power plants. Risk was defined as the probability that recruitment of age-1+ striped bass would decline by 80% or more, relative to the equilibrium value, at least once during the time periods examined (1, 5, 10, and 15 years. Measurement error, estimated using two abundance indices from independent beach seine surveys conducted on the Hudson River, accounted for 50% of the variability in one index and 56% of the variability in the other. If a measurement error of 50% was ignored and all of the variability in abundance was attributed to natural causes, the risk that recruitment of age-1+ striped bass would decline by 80% or more after 15 years was 0.308 at the current level of entrainment mortality (11%. However, the risk decreased almost tenfold (0.032 if a measurement error of 50% was considered. The change in risk attributable to decreasing the entrainment mortality rate from 11 to 0% was very small (0.009 and similar in magnitude to the change in risk associated with an action proposed in Amendment #5 to the Interstate Fishery Management Plan for Atlantic striped bass (0.006— an increase in the instantaneous fishing mortality rate from 0.33 to 0.4. The proposed increase in fishing mortality was not considered an adverse environmental impact, which suggests that potentially costly efforts to reduce entrainment mortality on the Hudson River stock of striped bass are not warranted.
Lee, Y.; Keehm, Y.
2011-12-01
Estimating the degree of weathering in stone cultural heritage, such as pagodas and statues is very important to plan conservation and restoration. The ultrasonic measurement is one of commonly-used techniques to evaluate weathering index of stone cultual properties, since it is easy to use and non-destructive. Typically we use a portable ultrasonic device, PUNDIT with exponential sensors. However, there are many factors to cause errors in measurements such as operators, sensor layouts or measurement directions. In this study, we carried out variety of measurements with different operators (male and female), different sensor layouts (direct and indirect), and sensor directions (anisotropy). For operators bias, we found that there were not significant differences by the operator's sex, while the pressure an operator exerts can create larger error in measurements. Calibrating with a standard sample for each operator is very essential in this case. For the sensor layout, we found that the indirect measurement (commonly used for cultural properties, since the direct measurement is difficult in most cases) gives lower velocity than the real one. We found that the correction coefficient is slightly different for different types of rocks: 1.50 for granite and sandstone and 1.46 for marble. From the sensor directions, we found that many rocks have slight anisotropy in their ultrasonic velocity measurement, though they are considered isotropic in macroscopic scale. Thus averaging four different directional measurement (0°, 45°, 90°, 135°) gives much less errors in measurements (the variance is 2-3 times smaller). In conclusion, we reported the error in ultrasonic meaurement of stone cultural properties by various sources quantitatively and suggested the amount of correction and procedures to calibrate the measurements. Acknowledgement: This study, which forms a part of the project, has been achieved with the support of national R&D project, which has been hosted by
Practical error estimates for Reynolds' lubrication approximation and its higher order corrections
Energy Technology Data Exchange (ETDEWEB)
Wilkening, Jon
2008-12-10
Reynolds lubrication approximation is used extensively to study flows between moving machine parts, in narrow channels, and in thin films. The solution of Reynolds equation may be thought of as the zeroth order term in an expansion of the solution of the Stokes equations in powers of the aspect ratio {var_epsilon} of the domain. In this paper, we show how to compute the terms in this expansion to arbitrary order on a two-dimensional, x-periodic domain and derive rigorous, a-priori error bounds for the difference between the exact solution and the truncated expansion solution. Unlike previous studies of this sort, the constants in our error bounds are either independent of the function h(x) describing the geometry, or depend on h and its derivatives in an explicit, intuitive way. Specifically, if the expansion is truncated at order 2k, the error is O({var_epsilon}{sup 2k+2}) and h enters into the error bound only through its first and third inverse moments {integral}{sub 0}{sup 1} h(x){sup -m} dx, m = 1,3 and via the max norms {parallel} 1/{ell}! h{sup {ell}-1}{partial_derivative}{sub x}{sup {ell}}h{parallel}{sub {infinity}}, 1 {le} {ell} {le} 2k + 2. We validate our estimates by comparing with finite element solutions and present numerical evidence that suggests that even when h is real analytic and periodic, the expansion solution forms an asymptotic series rather than a convergent series.
Hardy, Ryan A.; Nerem, R. Steven; Wiese, David N.
2017-12-01
Systematic errors in Gravity Recovery and Climate Experiment (GRACE) monthly mass estimates over the Greenland and Antarctic ice sheets can originate from low-frequency biases in the European Centre for Medium-Range Weather Forecasts (ECMWF) Operational Analysis model, the atmospheric component of the Atmospheric and Ocean Dealising Level-1B (AOD1B) product used to forward model atmospheric and ocean gravity signals in GRACE processing. These biases are revealed in differences in surface pressure between the ECMWF Operational Analysis model, state-of-the-art reanalyses, and in situ surface pressure measurements. While some of these errors are attributable to well-understood discrete model changes and have published corrections, we examine errors these corrections do not address. We compare multiple models and in situ data in Antarctica and Greenland to determine which models have the most skill relative to monthly averages of the dealiasing model. We also evaluate linear combinations of these models and synthetic pressure fields generated from direct interpolation of pressure observations. These models consistently reveal drifts in the dealiasing model that cause the acceleration of Antarctica's mass loss between April 2002 and August 2016 to be underestimated by approximately 4 Gt yr-2. We find similar results after attempting to solve the inverse problem, recovering pressure biases directly from the GRACE Jet Propulsion Laboratory RL05.1 M mascon solutions. Over Greenland, we find a 2 Gt yr-1 bias in mass trend. While our analysis focuses on errors in Release 05 of AOD1B, we also evaluate the new AOD1B RL06 product. We find that this new product mitigates some of the aforementioned biases.
Barth, Timothy J.
2014-01-01
This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.
Results and Error Estimates from GRACE Forward Modeling over Greenland, Canada, and Alaska
Bonin, J. A.; Chambers, D. P.
2012-12-01
Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Greenland and Antarctica. However, the accuracy of the forward model technique has not been determined, nor is it known how the distribution of the local basins affects the results. We use a "truth" model composed of hydrology and ice-melt slopes as an example case, to estimate the uncertainties of this forward modeling method and expose those design parameters which may result in an incorrect high-resolution mass distribution. We then apply these optimal parameters in a forward model estimate created from RL05 GRACE data. We compare the resulting mass slopes with the expected systematic errors from the simulation, as well as GIA and basic trend-fitting uncertainties. We also consider whether specific regions (such as Ellesmere Island and Baffin Island) can be estimated reliably using our optimal basin layout.
International Nuclear Information System (INIS)
Kinnamon, Daniel D; Ludwig, David A; Lipshultz, Steven E; Miller, Tracie L; Lipsitz, Stuart R
2010-01-01
The hydration of fat-free mass, or hydration fraction (HF), is often defined as a constant body composition parameter in a two-compartment model and then estimated from in vivo measurements. We showed that the widely used estimator for the HF parameter in this model, the mean of the ratios of measured total body water (TBW) to fat-free mass (FFM) in individual subjects, can be inaccurate in the presence of additive technical errors. We then proposed a new instrumental variables estimator that accurately estimates the HF parameter in the presence of such errors. In Monte Carlo simulations, the mean of the ratios of TBW to FFM was an inaccurate estimator of the HF parameter, and inferences based on it had actual type I error rates more than 13 times the nominal 0.05 level under certain conditions. The instrumental variables estimator was accurate and maintained an actual type I error rate close to the nominal level in all simulations. When estimating and performing inference on the HF parameter, the proposed instrumental variables estimator should yield accurate estimates and correct inferences in the presence of additive technical errors, but the mean of the ratios of TBW to FFM in individual subjects may not
Chelton, Dudley B.; Schlax, Michael G.
1991-01-01
The sampling error of an arbitrary linear estimate of a time-averaged quantity constructed from a time series of irregularly spaced observations at a fixed located is quantified through a formalism. The method is applied to satellite observations of chlorophyll from the coastal zone color scanner. The two specific linear estimates under consideration are the composite average formed from the simple average of all observations within the averaging period and the optimal estimate formed by minimizing the mean squared error of the temporal average based on all the observations in the time series. The resulting suboptimal estimates are shown to be more accurate than composite averages. Suboptimal estimates are also found to be nearly as accurate as optimal estimates using the correct signal and measurement error variances and correlation functions for realistic ranges of these parameters, which makes it a viable practical alternative to the composite average method generally employed at present.
International Nuclear Information System (INIS)
Fernández, Eduardo F.; Almonacid, Florencia
2015-01-01
Highlights: • Concentrating grid-connected systems are working at maximum power point. • The operating cell temperature is inherently lower than at open circuit. • Two novel methods for estimating the cell temperature are proposed. • Both predict the operating cell temperature from atmospheric parameters. • Experimental results show that both methods perform effectively. - Abstract: The working cell temperature of high concentrator photovoltaic systems is a crucial parameter when analysing their performance and reliability. At the same time, due to the special features of this technology, the direct measurement of the cell temperature is very complex and is usually obtained by using different indirect methods. High concentrator photovoltaic modules in a system are operating at maximum power since they are connected to an inverter. So that, their cell temperature is lower than the cell temperature of a module at open-circuit voltage since an important part of the light power density is converted into electricity. In this paper, a procedure for indirectly estimating the cell temperature of a high concentrator photovoltaic system from atmospheric parameters is addressed. Therefore, this new procedure has the advantage that is valid for estimating the cell temperature of a system at any location of interest if the atmospheric parameters are available. To achieve this goal, two different methods are proposed: one based on simple mathematical relationships and another based on artificial intelligent techniques. Results show that both methods predicts the cell temperature of a module connected to an inverter with a low margin of error with a normalised root mean square error lower or equal than 3.3%, an absolute root mean square error lower or equal than 2 °C, a mean absolute error lower or equal then 1.5 °C, and a mean bias error and a mean relative error almost equal to 0%
Kiessling, Jonas; Tempone, Raul
2014-01-01
jump activity, then the jumps smaller than some (Formula presented.) are approximated by diffusion. The resulting diffusion approximation error is also estimated, with leading order term in computable form, as well as the dependence of the time
A new three-band algorithm for estimating chlorophyll concentrations in turbid inland lakes
International Nuclear Information System (INIS)
Duan Hongtao; Ma Ronghua; Zhao Chenlu; Zhou Lin; Shang Linlin; Zhang Yuanzhi; Loiselle, Steven Arthur; Xu Jingping
2010-01-01
A new three-band model was developed to estimate chlorophyll-a concentrations in turbid inland waters. This model makes a number of important improvements with respect to the three-band model commonly used, including lower restrictions on wavelength optimization and the use of coefficients which represent specific inherent optical properties. Results showed that the new model provides a significantly higher determination coefficient and lower root mean squared error (RMSE) with respect to the original model for upwelling data from Taihu Lake, China. The new model was tested using simulated data for the MERIS and GOCI satellite systems, showing high correlations with the former and poorer correlations with the latter, principally due to the lack of a 709 nm centered waveband. The new model provides numerous advantages, making it a suitable alternative for chlorophyll-a estimations in turbid and eutrophic waters.
Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators
International Nuclear Information System (INIS)
Flammia, Steven T; Gross, David; Liu, Yi-Kai; Eisert, Jens
2012-01-01
Intuitively, if a density operator has small rank, then it should be easier to estimate from experimental data, since in this case only a few eigenvectors need to be learned. We prove two complementary results that confirm this intuition. Firstly, we show that a low-rank density matrix can be estimated using fewer copies of the state, i.e. the sample complexity of tomography decreases with the rank. Secondly, we show that unknown low-rank states can be reconstructed from an incomplete set of measurements, using techniques from compressed sensing and matrix completion. These techniques use simple Pauli measurements, and their output can be certified without making any assumptions about the unknown state. In this paper, we present a new theoretical analysis of compressed tomography, based on the restricted isometry property for low-rank matrices. Using these tools, we obtain near-optimal error bounds for the realistic situation where the data contain noise due to finite statistics, and the density matrix is full-rank with decaying eigenvalues. We also obtain upper bounds on the sample complexity of compressed tomography, and almost-matching lower bounds on the sample complexity of any procedure using adaptive sequences of Pauli measurements. Using numerical simulations, we compare the performance of two compressed sensing estimators—the matrix Dantzig selector and the matrix Lasso—with standard maximum-likelihood estimation (MLE). We find that, given comparable experimental resources, the compressed sensing estimators consistently produce higher fidelity state reconstructions than MLE. In addition, the use of an incomplete set of measurements leads to faster classical processing with no loss of accuracy. Finally, we show how to certify the accuracy of a low-rank estimate using direct fidelity estimation, and describe a method for compressed quantum process tomography that works for processes with small Kraus rank and requires only Pauli eigenstate preparations
Patino, Eduardo
1996-01-01
A field experiment was conducted at the Levee 4 canal site below control structure G-88 in the Everglades agricultural area in northwestern Broward County, Florida, to study the relation of acoustic attenuation to suspended-solids concentrations. Acoustic velocity meter and temperature data were obtained with concurrent water samples analyzed for suspended-solids concentrations. Two separate acoustic velocity meter frequencies were used, 200 and 500 kilohertz, to determine the sensitivity of acoustic attenuation to frequency for the measured suspended-solids concentration range. Suspended-solids concentrations for water samples collected at the Levee 4 canal site from July 1993 to September 1994 ranged from 22 to 1,058 milligrams per liter, and organic content ranged from about 30 to 93 percent. Regression analyses showed that attenuation data from the acoustic velocity meter (automatic gain control) and temperature data alone do not provide enough information to adequately describe the concentrations of suspended solids. However, if velocity is also included as one of the independent variables in the regression model, a satisfactory correlation can be obtained. Thus, it is feasible to use acoustic velocity meter instrumentation to estimate suspended-solids concentrations in streams, even when suspended solids are primarily composed of organic material. Using the most comprehensive data set available for the study (500 kiloherz data), the best fit regression model produces a standard error of 69.7 milligrams per liter, with actual errors ranging from 2 to 128 milligrams per liter. Both acoustic velocity meter transmission frequencies of 200 and 500 hilohertz produced similar results, suggesting that transducers of either frequency could be used to collect attenuation data at the study site. Results indicate that calibration will be required for each acoustic velocity meter system to the unique suspended-solids regime existing at each site. More robust solutions may
Estimating radionuclide air concentrations near buildings: a screening approach
International Nuclear Information System (INIS)
Miller, C.W.; Yildiran, M.
1984-01-01
For some facilities that routinely release small amounts of radionuclides to the atmosphere, such as hospitals, research laboratories, contaminated clothing laundries, and others, it is necessary to estimate the dose to persons very near the buildings from which the releases occur. Such facilities need simple screening procedures which provide reasonable assurance that as long as the calculated dose is less than some fraction of a relevant dose limit no individual will receive a dose in excess of that limit. Screening procedures have been proposed for persons living within hundreds of meters to a few kilometers from a source of radioactive effluent. This paper examines a screening technique for estimating long-term average radionuclide air concentrations within approximately 100 m of a building from which the release occurs. The technique is based on a modified gaussion plume model (HB model) which considers the influence of the tallest building within 100 m and is independant of atmospheric stability and downwind distance. 4 references, 2 tables
Shimansky, Y P
2011-05-01
It is well known from numerous studies that perception can be significantly affected by intended action in many everyday situations, indicating that perception and related decision-making is not a simple, one-way sequence, but a complex iterative cognitive process. However, the underlying functional mechanisms are yet unclear. Based on an optimality approach, a quantitative computational model of one such mechanism has been developed in this study. It is assumed in the model that significant uncertainty about task-related parameters of the environment results in parameter estimation errors and an optimal control system should minimize the cost of such errors in terms of the optimality criterion. It is demonstrated that, if the cost of a parameter estimation error is significantly asymmetrical with respect to error direction, the tendency to minimize error cost creates a systematic deviation of the optimal parameter estimate from its maximum likelihood value. Consequently, optimization of parameter estimate and optimization of control action cannot be performed separately from each other under parameter uncertainty combined with asymmetry of estimation error cost, thus making the certainty equivalence principle non-applicable under those conditions. A hypothesis that not only the action, but also perception itself is biased by the above deviation of parameter estimate is supported by ample experimental evidence. The results provide important insights into the cognitive mechanisms of interaction between sensory perception and planning an action under realistic conditions. Implications for understanding related functional mechanisms of optimal control in the CNS are discussed.
Zheng, Yuejiu; Ouyang, Minggao; Han, Xuebing; Lu, Languang; Li, Jianqiu
2018-02-01
Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.
Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions
Jung, J. Y.; Niemann, J. D.; Greimann, B. P.
2016-12-01
Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.
International Nuclear Information System (INIS)
Kim, Yochan; Park, Jinkyun; Jung, Wondea
2017-01-01
Because it has been indicated that empirical data supporting the estimates used in human reliability analysis (HRA) is insufficient, several databases have been constructed recently. To generate quantitative estimates from human reliability data, it is important to appropriately sort the erroneous behaviors found in the reliability data. Therefore, this paper proposes a scheme to classify the erroneous behaviors identified by the HuREX (Human Reliability data Extraction) framework through a review of the relevant literature. A case study of the human error probability (HEP) calculations is conducted to verify that the proposed scheme can be successfully implemented for the categorization of the erroneous behaviors and to assess whether the scheme is useful for the HEP quantification purposes. Although continuously accumulating and analyzing simulator data is desirable to secure more reliable HEPs, the resulting HEPs were insightful in several important ways with regard to human reliability in off-normal conditions. From the findings of the literature review and the case study, the potential and limitations of the proposed method are discussed. - Highlights: • A taxonomy of erroneous behaviors is proposed to estimate HEPs from a database. • The cognitive models, procedures, HRA methods, and HRA databases were reviewed. • HEPs for several types of erroneous behaviors are calculated as a case study.
Global Estimates of Errors in Quantum Computation by the Feynman-Vernon Formalism
Aurell, Erik
2018-04-01
The operation of a quantum computer is considered as a general quantum operation on a mixed state on many qubits followed by a measurement. The general quantum operation is further represented as a Feynman-Vernon double path integral over the histories of the qubits and of an environment, and afterward tracing out the environment. The qubit histories are taken to be paths on the two-sphere S^2 as in Klauder's coherent-state path integral of spin, and the environment is assumed to consist of harmonic oscillators initially in thermal equilibrium, and linearly coupled to to qubit operators \\hat{S}_z . The environment can then be integrated out to give a Feynman-Vernon influence action coupling the forward and backward histories of the qubits. This representation allows to derive in a simple way estimates that the total error of operation of a quantum computer without error correction scales linearly with the number of qubits and the time of operation. It also allows to discuss Kitaev's toric code interacting with an environment in the same manner.
Abuzaid, Abdulrahman I.
2014-09-01
Efficient receiver designs for cooperative communication systems are becoming increasingly important. In previous work, cooperative networks communicated with the use of $L$ relays. As the receiver is constrained, it can only process $U$ out of $L$ relays. Channel shortening and reduced-rank techniques were employed to design the preprocessing matrix. In this paper, a receiver structure is proposed which combines the joint iterative optimization (JIO) algorithm and our proposed threshold selection criteria. This receiver structure assists in determining the optimal $U-{opt}$. Furthermore, this receiver provides the freedom to choose $U ≤ U-{opt}$ for each frame depending upon the tolerable difference allowed for mean square error (MSE). Our study and simulation results show that by choosing an appropriate threshold, it is possible to gain in terms of complexity savings without affecting the BER performance of the system. Furthermore, in this paper the effect of channel estimation errors is investigated on the MSE performance of the amplify-and-forward (AF) cooperative relaying system.
Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli
2017-11-01
The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.
Global Estimates of Errors in Quantum Computation by the Feynman-Vernon Formalism
Aurell, Erik
2018-06-01
The operation of a quantum computer is considered as a general quantum operation on a mixed state on many qubits followed by a measurement. The general quantum operation is further represented as a Feynman-Vernon double path integral over the histories of the qubits and of an environment, and afterward tracing out the environment. The qubit histories are taken to be paths on the two-sphere S^2 as in Klauder's coherent-state path integral of spin, and the environment is assumed to consist of harmonic oscillators initially in thermal equilibrium, and linearly coupled to to qubit operators \\hat{S}_z. The environment can then be integrated out to give a Feynman-Vernon influence action coupling the forward and backward histories of the qubits. This representation allows to derive in a simple way estimates that the total error of operation of a quantum computer without error correction scales linearly with the number of qubits and the time of operation. It also allows to discuss Kitaev's toric code interacting with an environment in the same manner.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
International Nuclear Information System (INIS)
Bokanowski, Olivier; Picarelli, Athena; Zidani, Hasnaa
2015-01-01
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
Energy Technology Data Exchange (ETDEWEB)
Bokanowski, Olivier, E-mail: boka@math.jussieu.fr [Laboratoire Jacques-Louis Lions, Université Paris-Diderot (Paris 7) UFR de Mathématiques - Bât. Sophie Germain (France); Picarelli, Athena, E-mail: athena.picarelli@inria.fr [Projet Commands, INRIA Saclay & ENSTA ParisTech (France); Zidani, Hasnaa, E-mail: hasnaa.zidani@ensta.fr [Unité de Mathématiques appliquées (UMA), ENSTA ParisTech (France)
2015-02-15
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.
Impact of mixed modes on measurement errors and estimates of change in panel data
Directory of Open Access Journals (Sweden)
Alexandru Cernat
2015-07-01
Full Text Available Mixed mode designs are receiving increased interest as a possible solution for saving costs in panel surveys, although the lasting effects on data quality are unknown. To better understand the effects of mixed mode designs on panel data we will examine its impact on random and systematic error and on estimates of change. The SF12, a health scale, in the Understanding Society Innovation Panel is used for the analysis. Results indicate that only one variable out of 12 has systematic differences due to the mixed mode design. Also, four of the 12 items overestimate variance of change in time in the mixed mode design. We conclude that using a mixed mode approach leads to minor measurement differences but it can result in the overestimation of individual change compared to a single mode design.
DEFF Research Database (Denmark)
Kressner, Abigail Anne; May, Tobias; Malik Thaarup Høegh, Rasmus
2017-01-01
A recent study suggested that the most important factor for obtaining high speech intelligibility in noise with cochlear implant recipients is to preserve the low-frequency amplitude modulations of speech across time and frequency by, for example, minimizing the amount of noise in speech gaps....... In contrast, other studies have argued that the transients provide the most information. Thus, the present study investigates the relative impact of these two factors in the framework of noise reduction by systematically correcting noise-estimation errors within speech segments, speech gaps......, and the transitions between them. Speech intelligibility in noise was measured using a cochlear implant simulation tested on normal-hearing listeners. The results suggest that minimizing noise in the speech gaps can substantially improve intelligibility, especially in modulated noise. However, significantly larger...
International Nuclear Information System (INIS)
Gillet, M.
1986-07-01
This thesis presents a study for the surveillance of the ''primary coolant circuit inventory monitoring'' of a pressurized water reactor. A reference model is developed in view of an automatic system ensuring detection and diagnostic in real time. The methods used for the present application are statistical tests and a method related to pattern recognition. The estimation of failures detected, difficult owing to the non-linearity of the problem, is treated by the least error squares method of the predictor or corrector type, and by filtering. It is in this frame that a new optimized method with superlinear convergence is developed, and that a segmented linearization of the model is introduced, in view of a multiple filtering [fr
Regularization and error estimates for asymmetric backward nonhomogeneous heat equations in a ball
Directory of Open Access Journals (Sweden)
Le Minh Triet
2016-09-01
Full Text Available The backward heat problem (BHP has been researched by many authors in the last five decades; it consists in recovering the initial distribution from the final temperature data. There are some articles [1,2,3] related the axi-symmetric BHP in a disk but the study in spherical coordinates is rare. Therefore, we wish to study a backward problem for nonhomogenous heat equation associated with asymmetric final data in a ball. In this article, we modify the quasi-boundary value method to construct a stable approximate solution for this problem. As a result, we obtain regularized solution and a sharp estimates for its error. At the end, a numerical experiment is provided to illustrate our method.
International Nuclear Information System (INIS)
Gershgorin, B.; Harlim, J.; Majda, A.J.
2010-01-01
The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates
Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network
Directory of Open Access Journals (Sweden)
Vitor Badiale Furlong
2013-02-01
Full Text Available In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days, number of clusters (10, 30 and 50 clusters and internal weight softening parameter (Sigma (0.30, 0.45 and 0.60. These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A and 18 (B days of culture growth. The validations demonstrated that in long-term experiments (Validation A the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B, Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.
An estimation on the derived limits of effluent water concentration
International Nuclear Information System (INIS)
Okamura, Yasuharu; Kobayashi, Katuhiko; Kusama, Tomoko; Yoshizawa, Yasuo
1984-01-01
The values of Derived Limits of Effluent Water Concentration, (DLEC)sub(w), have been estimated in accordance with the principles of the recent recommendations of the International Commission on Radiological Protection. The (DLEC)sub(w)'s were derived from the Annual Limits on Intake for individual members of the public (ALIsub(p)), considering realistic models of exposure pathways and annual intake rates of foods. The ALIsub(p)'s were decided after consideration of body organ mass and other age dependent parameters. We assumed that the materials which brought exposure to the public were drinking water, fish, seaweed, invertebrate and seashore. The age dependence of annual intake rate of food might be proportional to a person's energy expenditure rate. The following results were obtained. Infants were the critical group of the public at the time of derivation of (DLEC)sub(w). The ALIsub(p)'s for the infants were about one-hundredth of those for workers and their (DLEC)sub(w)'s were about one-third of those for the adult members of the public. (author)
International Nuclear Information System (INIS)
Kobayashi, H.; Matsunaga, T.; Hoyano, A.
2002-01-01
Absorbed photosynthetically active radiation (APAR), which is defined as downward solar radiation in 400-700 nm absorbed by vegetation, is one of the significant variables for Net Primary Production (NPP) estimation from satellite data. Toward the reduction of the uncertainties in the global NPP estimation, it is necessary to clarify the APAR accuracy. In this paper, first we proposed the improved PAR estimation method based on Eck and Dye's method in which the ultraviolet (UV) reflectivity data derived from Total Ozone Mapping Spectrometer (TOMS) at the top of atmosphere were used for clouds transmittance estimation. The proposed method considered the variable effects of land surface UV reflectivity on the satellite-observed UV data. Monthly mean PAR comparisons between satellite-derived and ground-based data at various meteorological stations in Japan indicated that the improved PAR estimation method reduced the bias errors in the summer season. Assuming the relative error of the fraction of PAR (FPAR) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) to be 10%, we estimated APAR relative errors to be 10-15%. Annual NPP is calculated using APAR derived from MODIS/ FPAR and the improved PAR estimation method. It is shown that random and bias errors of annual NPP in a 1 km resolution pixel are less than 4% and 6% respectively. The APAR bias errors due to the PAR bias errors also affect the estimated total NPP. We estimated the most probable total annual NPP in Japan by subtracting the bias PAR errors. It amounts about 248 MtC/yr. Using the improved PAR estimation method, and Eck and Dye's method, total annual NPP is 4% and 9% difference from most probable value respectively. The previous intercomparison study among using fifteen NPP models4) showed that global NPP estimations among NPP models are 44.4-66.3 GtC/yr (coefficient of variation = 14%). Hence we conclude that the NPP estimation uncertainty due to APAR estimation error is small
Joint Estimation of Contamination, Error and Demography for Nuclear DNA from Ancient Humans
Slatkin, Montgomery
2016-01-01
When sequencing an ancient DNA sample from a hominin fossil, DNA from present-day humans involved in excavation and extraction will be sequenced along with the endogenous material. This type of contamination is problematic for downstream analyses as it will introduce a bias towards the population of the contaminating individual(s). Quantifying the extent of contamination is a crucial step as it allows researchers to account for possible biases that may arise in downstream genetic analyses. Here, we present an MCMC algorithm to co-estimate the contamination rate, sequencing error rate and demographic parameters—including drift times and admixture rates—for an ancient nuclear genome obtained from human remains, when the putative contaminating DNA comes from present-day humans. We assume we have a large panel representing the putative contaminant population (e.g. European, East Asian or African). The method is implemented in a C++ program called ‘Demographic Inference with Contamination and Error’ (DICE). We applied it to simulations and genome data from ancient Neanderthals and modern humans. With reasonable levels of genome sequence coverage (>3X), we find we can recover accurate estimates of all these parameters, even when the contamination rate is as high as 50%. PMID:27049965
Granato, Gregory E.; Smith, Kirk P.
1999-01-01
Discrete or composite samples of highway runoff may not adequately represent in-storm water-quality fluctuations because continuous records of water stage, specific conductance, pH, and temperature of the runoff indicate that these properties fluctuate substantially during a storm. Continuous records of water-quality properties can be used to maximize the information obtained about the stormwater runoff system being studied and can provide the context needed to interpret analyses of water samples. Concentrations of the road-salt constituents calcium, sodium, and chloride in highway runoff were estimated from theoretical and empirical relations between specific conductance and the concentrations of these ions. These relations were examined using the analysis of 233 highwayrunoff samples collected from August 1988 through March 1995 at four highway-drainage monitoring stations along State Route 25 in southeastern Massachusetts. Theoretically, the specific conductance of a water sample is the sum of the individual conductances attributed to each ionic species in solution-the product of the concentrations of each ion in milliequivalents per liter (meq/L) multiplied by the equivalent ionic conductance at infinite dilution-thereby establishing the principle of superposition. Superposition provides an estimate of actual specific conductance that is within measurement error throughout the conductance range of many natural waters, with errors of less than ?5 percent below 1,000 microsiemens per centimeter (?S/cm) and ?10 percent between 1,000 and 4,000 ?S/cm if all major ionic constituents are accounted for. A semi-empirical method (adjusted superposition) was used to adjust for concentration effects-superposition-method prediction errors at high and low concentrations-and to relate measured specific conductance to that calculated using superposition. The adjusted superposition method, which was developed to interpret the State Route 25 highway-runoff records, accounts for
Gelbrich, Bianca; Frerking, Carolin; Weiss, Sandra; Schwerdt, Sebastian; Stellzig-Eisenhauer, Angelika; Tausche, Eve; Gelbrich, Götz
2015-01-01
Forensic age estimation in living adolescents is based on several methods, e.g. the assessment of skeletal and dental maturation. Combination of several methods is mandatory, since age estimates from a single method are too imprecise due to biological variability. The correlation of the errors of the methods being combined must be known to calculate the precision of combined age estimates. To examine the correlation of the errors of the hand and the third molar method and to demonstrate how to calculate the combined age estimate. Clinical routine radiographs of the hand and dental panoramic images of 383 patients (aged 7.8-19.1 years, 56% female) were assessed. Lack of correlation (r = -0.024, 95% CI = -0.124 to + 0.076, p = 0.64) allows calculating the combined age estimate as the weighted average of the estimates from hand bones and third molars. Combination improved the standard deviations of errors (hand = 0.97, teeth = 1.35 years) to 0.79 years. Uncorrelated errors of the age estimates obtained from both methods allow straightforward determination of the common estimate and its variance. This is also possible when reference data for the hand and the third molar method are established independently from each other, using different samples.
GREAT3 results - I. Systematic errors in shear estimation and the impact of real galaxy morphology
Energy Technology Data Exchange (ETDEWEB)
Mandelbaum, R.; Rowe, B.; Armstrong, R.; Bard, D.; Bertin, E.; Bosch, J.; Boutigny, D.; Courbin, F.; Dawson, W. A.; Donnarumma, A.; Fenech Conti, I.; Gavazzi, R.; Gentile, M.; Gill, M. S. S.; Hogg, D. W.; Huff, E. M.; Jee, M. J.; Kacprzak, T.; Kilbinger, M.; Kuntzer, T.; Lang, D.; Luo, W.; March, M. C.; Marshall, P. J.; Meyers, J. E.; Miller, L.; Miyatake, H.; Nakajima, R.; Ngole Mboula, F. M.; Nurbaeva, G.; Okura, Y.; Paulin-Henriksson, S.; Rhodes, J.; Schneider, M. D.; Shan, H.; Sheldon, E. S.; Simet, M.; Starck, J. -L.; Sureau, F.; Tewes, M.; Zarb Adami, K.; Zhang, J.; Zuntz, J.
2015-05-01
We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by ~1 per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the Sérsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods’ results support the simple model in which additive shear biases depend linearly on PSF ellipticity.
Pernot, Pascal; Savin, Andreas
2018-06-01
Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform end-users on the expected amplitude of prediction errors attached to these methods. We show that, the distributions of model errors being neither normal nor zero-centered, these error statistics cannot be used to infer prediction error probabilities. To overcome this limitation, we advocate for the use of more informative statistics, based on the empirical cumulative distribution function of unsigned errors, namely, (1) the probability for a new calculation to have an absolute error below a chosen threshold and (2) the maximal amplitude of errors one can expect with a chosen high confidence level. Those statistics are also shown to be well suited for benchmarking and ranking studies. Moreover, the standard error on all benchmarking statistics depends on the size of the reference dataset. Systematic publication of these standard errors would be very helpful to assess the statistical reliability of benchmarking conclusions.
Testolin, C G; Gore, R; Rivkin, T; Horlick, M; Arbo, J; Wang, Z; Chiumello, G; Heymsfield, S B
2000-12-01
Dual-energy X-ray absorptiometry (DXA) percent (%) fat estimates may be inaccurate in young children, who typically have high tissue hydration levels. This study was designed to provide a comprehensive analysis of pediatric tissue hydration effects on DXA %fat estimates. Phase 1 was experimental and included three in vitro studies to establish the physical basis of DXA %fat-estimation models. Phase 2 extended phase 1 models and consisted of theoretical calculations to estimate the %fat errors emanating from previously reported pediatric hydration effects. Phase 1 experiments supported the two-compartment DXA soft tissue model and established that pixel ratio of low to high energy (R values) are a predictable function of tissue elemental content. In phase 2, modeling of reference body composition values from birth to age 120 mo revealed that %fat errors will arise if a "constant" adult lean soft tissue R value is applied to the pediatric population; the maximum %fat error, approximately 0.8%, would be present at birth. High tissue hydration, as observed in infants and young children, leads to errors in DXA %fat estimates. The magnitude of these errors based on theoretical calculations is small and may not be of clinical or research significance.
International Nuclear Information System (INIS)
Sathyabama, N.
2014-01-01
It is now widely recognized that, when all of the known or suspected components of errors have been evaluated and corrected, there still remains an uncertainty, that is, a doubt about how well the result of the measurement represents the value of the quantity being measured. Evaluation of measurement data - Guide to the expression of Uncertainty in Measurement (GUM) is a guidance document, the purpose of which is to promote full information on how uncertainty statements are arrived at and to provide a basis for the international comparison of measurement results. In this paper, uncertainty estimations following GUM guidelines have been made for the measured values of online thoron concentrations using Lucas scintillation cell to prove that the correction for disequilibrium between 220 Rn and 216 Po is significant in online 220 Rn measurements
Pencil kernel correction and residual error estimation for quality-index-based dose calculations
International Nuclear Information System (INIS)
Nyholm, Tufve; Olofsson, Joergen; Ahnesjoe, Anders; Georg, Dietmar; Karlsson, Mikael
2006-01-01
Experimental data from 593 photon beams were used to quantify the errors in dose calculations using a previously published pencil kernel model. A correction of the kernel was derived in order to remove the observed systematic errors. The remaining residual error for individual beams was modelled through uncertainty associated with the kernel model. The methods were tested against an independent set of measurements. No significant systematic error was observed in the calculations using the derived correction of the kernel and the remaining random errors were found to be adequately predicted by the proposed method
Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.
2009-01-01
The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.
Kiessling, Jonas
2014-05-06
Option prices in exponential Lévy models solve certain partial integro-differential equations. This work focuses on developing novel, computable error approximations for a finite difference scheme that is suitable for solving such PIDEs. The scheme was introduced in (Cont and Voltchkova, SIAM J. Numer. Anal. 43(4):1596-1626, 2005). The main results of this work are new estimates of the dominating error terms, namely the time and space discretisation errors. In addition, the leading order terms of the error estimates are determined in a form that is more amenable to computations. The payoff is only assumed to satisfy an exponential growth condition, it is not assumed to be Lipschitz continuous as in previous works. If the underlying Lévy process has infinite jump activity, then the jumps smaller than some (Formula presented.) are approximated by diffusion. The resulting diffusion approximation error is also estimated, with leading order term in computable form, as well as the dependence of the time and space discretisation errors on this approximation. Consequently, it is possible to determine how to jointly choose the space and time grid sizes and the cut off parameter (Formula presented.). © 2014 Springer Science+Business Media Dordrecht.
Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R
Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.
2016-12-01
Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.
DEFF Research Database (Denmark)
Jin, Shuanggen; Feng, Guiping; Andersen, Ole Baltazar
2014-01-01
and geostrophic current estimates from satellite gravimetry and altimetry are investigated and evaluated in China's marginal seas. The cumulative error in MDT from GOCE is reduced from 22.75 to 9.89 cm when compared to the Gravity Recovery and Climate Experiment (GRACE) gravity field model ITG-Grace2010 results......The Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) and satellite altimetry can provide very detailed and accurate estimates of the mean dynamic topography (MDT) and geostrophic currents in China's marginal seas, such as, the newest high-resolution GOCE gravity field model GO......-CONS-GCF-2-TIM-R4 and the new Centre National d'Etudes Spatiales mean sea surface model MSS_CNES_CLS_11 from satellite altimetry. However, errors and uncertainties of MDT and geostrophic current estimates from satellite observations are not generally quantified. In this paper, errors and uncertainties of MDT...
The effect of TWD estimation error on the geometry of machined surfaces in micro-EDM milling
DEFF Research Database (Denmark)
Puthumana, Govindan; Bissacco, Giuliano; Hansen, Hans Nørgaard
In micro EDM (electrical discharge machining) milling, tool electrode wear must be effectively compensated in order to achieve high accuracy of machined features [1]. Tool wear compensation in micro-EDM milling can be based on off-line techniques with limited accuracy such as estimation...... and statistical characterization of the discharge population [3]. The TWD based approach permits the direct control of the position of the tool electrode front surface. However, TWD estimation errors will generate a self-amplifying error on the tool electrode axial depth during micro-EDM milling. Therefore....... The error propagation effect is demonstrated through a software simulation tool developed by the authors for determination of the correct TWD for subsequent use in compensation of electrode wear in EDM milling. The implemented model uses an initial arbitrary estimation of TWD and a single experiment...
International Nuclear Information System (INIS)
Dhole, K.; Roy, M.; Ghosh, S.; Datta, A.; Tripathy, M.K.; Bose, H.
2013-01-01
Highlights: ► Rapid analysis of heavy water samples, with precise temperature control. ► Entire composition range covered. ► Both variations in mole and wt.% of D 2 O in the heavy water sample studied. ► Standard error of calibration and prediction were estimated. - Abstract: The method of refractometry has been investigated for the quantitative estimation of isotopic concentration of heavy water (D 2 O) in a simulated water sample. Feasibility of refractometry as an excellent analytical technique for rapid and non-invasive determination of D 2 O concentration in water samples has been amply demonstrated. Temperature of the samples has been precisely controlled to eliminate the effect of temperature fluctuation on refractive index measurement. The method is found to exhibit a reasonable analytical response to its calibration performance over the purity range of 0–100% D 2 O. An accuracy of below ±1% in the measurement of isotopic purity of heavy water for the entire range could be achieved
Range camera on conveyor belts: estimating size distribution and systematic errors due to occlusion
Blomquist, Mats; Wernersson, Ake V.
1999-11-01
When range cameras are used for analyzing irregular material on a conveyor belt there will be complications like missing segments caused by occlusion. Also, a number of range discontinuities will be present. In a frame work towards stochastic geometry, conditions are found for the cases when range discontinuities take place. The test objects in this paper are pellets for the steel industry. An illuminating laser plane will give range discontinuities at the edges of each individual object. These discontinuities are used to detect and measure the chord created by the intersection of the laser plane and the object. From the measured chords we derive the average diameter and its variance. An improved method is to use a pair of parallel illuminating light planes to extract two chords. The estimation error for this method is not larger than the natural shape fluctuations (the difference in diameter) for the pellets. The laser- camera optronics is sensitive enough both for material on a conveyor belt and free falling material leaving the conveyor.
International Nuclear Information System (INIS)
Jorgensen, E.J.
1987-01-01
This study is an application of production-cost duality theory. Duality theory is reviewed for the competitive and rate-of-return regulated firm. The cost function is developed for the nuclear electric-power-generating industry of the United States using capital, fuel, and labor factor inputs. A comparison is made between the Generalized Box-Cox (GBC) and Fourier Flexible (FF) functional forms. The GBC functional form nests the Generalized Leontief, Generalized Square Root Quadratic and Translog functional forms, and is based upon a second-order Taylor-series expansion. The FF form follows from a Fourier-series expansion in sine and cosine terms using the Sobolev norm as the goodness-of-fit measure. The Sobolev norm takes into account first and second derivatives. The cost function and two factor shares are estimated as a system of equations using maximum-likelihood techniques, with Additive Standard Normal and Logistic Normal error distributions. In summary, none of the special cases of the GBC function form are accepted. Homotheticity of the underlying production technology can be rejected for both GBC and FF forms, leaving only the unrestricted versions supported by the data. Residual analysis indicates a slight improvement in skewness and kurtosis for univariate and multivariate cases when the Logistic Normal distribution is used
Shirley, Natalie R; Ramirez Montes, Paula Andrea
2015-01-01
The purpose of this study was to assess observer error in phase versus component-based scoring systems used to develop age estimation methods in forensic anthropology. A method preferred by forensic anthropologists in the AAFS was selected for this evaluation (the Suchey-Brooks method for the pubic symphysis). The Suchey-Brooks descriptions were used to develop a corresponding component-based scoring system for comparison. Several commonly used reliability statistics (kappa, weighted kappa, and the intraclass correlation coefficient) were calculated to assess observer agreement between two observers and to evaluate the efficacy of each of these statistics for this study. The linear weighted kappa was determined to be the most suitable measure of observer agreement. The results show that a component-based system offers the possibility for more objective scoring than a phase system as long as the coding possibilities for each trait do not exceed three states of expression, each with as little overlap as possible. © 2014 American Academy of Forensic Sciences.
Smith, G. L.; Bess, T. D.; Minnis, P.
1983-01-01
The processes which determine the weather and climate are driven by the radiation received by the earth and the radiation subsequently emitted. A knowledge of the absorbed and emitted components of radiation is thus fundamental for the study of these processes. In connection with the desire to improve the quality of long-range forecasting, NASA is developing the Earth Radiation Budget Experiment (ERBE), consisting of a three-channel scanning radiometer and a package of nonscanning radiometers. A set of these instruments is to be flown on both the NOAA-F and NOAA-G spacecraft, in sun-synchronous orbits, and on an Earth Radiation Budget Satellite. The purpose of the scanning radiometer is to obtain measurements from which the average reflected solar radiant exitance and the average earth-emitted radiant exitance at a reference level can be established. The estimate of regional average exitance obtained will not exactly equal the true value of the regional average exitance, but will differ due to spatial sampling. A method is presented for evaluating this spatial sampling error.
Ionospheric errors compensation for ground deformation estimation with new generation SAR
Gomba, Giorgio; De Zan, Francesco; Rodriguez Gonzalez, Fernando
2017-04-01
Synthetic aperture radar (SAR) and interferometric SAR (InSAR) measurements are disturbed by the propagation velocity changes of microwaves that are caused by the high density of free electrons in the ionosphere. Most affected are low-frequency (L- or P-band) radars, as the recently launched ALOS-2 and the future Tandem-L and NISAR, although higher frequency (C- or X-band) systems, as the recently launched Sentinel-1, are not immune. Since the ionosphere is an obstacle to increasing the precision of new generation SAR systems needed to remotely measure the Earth's dynamic processes as for example ground deformation, it is necessary to estimate and compensate ionospheric propagation delays in SAR signals. In this work we discuss about the influence of the ionosphere on interferograms and the possible correction methods with relative accuracies. Consequently, the effect of ionospheric induced errors on ground deformation measurements prior and after ionosphere compensation will be analyzed. Examples will be presented of corrupted measurements of earthquakes and fault motion along with the corrected results using different methods.
A method for the estimation of the residual error in the SALP approach for fault tree analysis
International Nuclear Information System (INIS)
Astolfi, M.; Contini, S.
1980-01-01
The aim of this report is the illustration of the algorithms implemented in the SALP-MP code for the estimation of the residual error. These algorithms are of more general use, and it would be possible to implement them on all codes of the series SALP previously developed, as well as, with minor modifications, to analysis procedures based on 'top-down' approaches. At the time, combined 'top-down' - 'bottom up' procedures are being studied in order to take advantage from both approaches for further reduction of computer time and better estimation of the residual error, for which the developed algorithms are still applicable
An A Posteriori Error Estimate for Symplectic Euler Approximation of Optimal Control Problems
Karlsson, Peer Jesper
2015-01-07
This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading order term consisting of an error density that is computable from Symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations.
An Error Estimate for Symplectic Euler Approximation of Optimal Control Problems
Karlsson, Jesper; Larsson, Stig; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
2015-01-01
This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns symplectic Euler solutions of the Hamiltonian system connected with the optimal control problem. The error representation has a leading-order term consisting of an error density that is computable from symplectic Euler solutions. Under an assumption of the pathwise convergence of the approximate dual function as the maximum time step goes to zero, we prove that the remainder is of higher order than the leading-error density part in the error representation. With the error representation, it is possible to perform adaptive time stepping. We apply an adaptive algorithm originally developed for ordinary differential equations. The performance is illustrated by numerical tests.
Munsinger, H
1977-01-01
Published studies show that among identical twins, lower birthweight is associated with lower adult intelligence. However, no such relation between birthweight and adult IQ exists among fraternal twins. A likely explanation for the association between birthweight and intelligence among identical twins is the identical twin transfusion syndrome which occurs only between some monochorionic identical twin pairs. The IQ scores from separated identical twins were reanalysed to explore the consequences of identical twin transfusion syndrome for IQ resemblance and heritability. Among 129 published cases of identical twin pairs reared apart, 76 pairs contained some birthweight information. The 76 pairs were separated into three classes: 23 pairs in which there was clear evidence of a substantial birthweight differences (indicating the probable existence of the identical twin transfusion syndrome), 27 pairs in which the information on birthweight was ambiguous (?), and 26 pairs in which there was clear evidence that the twins were similar in birthweight. The reanalyses showed: (1) birthweight differences are positively associated with IQ differences in the total sample of separated identical twins; (2) within the group of 23 twin pairs who showed large birthweight differences, there was a positive relation between birthweight differences and IQ differences; (3) when heritability of IQ is estimated for those twins who do not suffer large birthweight differences, the resemblance (and thus, h2/b) of the separated identical twins' IG is 0-95. Given that the average reliability of the individual IQ test is around 0-95, these data suggest that genetic factors and errors of measurement cause the individual differences in IQ among human beings. Because of the identical twin transfusion syndrome, previous studies of MZ twins have underestimated the effect of genetic factors on IQ. An analysis of the IQs for heavier and lighter birthweight twins suggests that the main effect of the
Directory of Open Access Journals (Sweden)
Xue Li
2015-01-01
Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.
Han, Mira V; Thomas, Gregg W C; Lugo-Martinez, Jose; Hahn, Matthew W
2013-08-01
Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.
International Nuclear Information System (INIS)
Fournier, D.; Le Tellier, R.; Suteau, C.
2011-01-01
We present an error estimator for the S N neutron transport equation discretized with an arbitrary high-order discontinuous Galerkin method. As a starting point, the estimator is obtained for conforming Cartesian meshes with a uniform polynomial order for the trial space then adapted to deal with non-conforming meshes and a variable polynomial order. Some numerical tests illustrate the properties of the estimator and its limitations. Finally, a simple shielding benchmark is analyzed in order to show the relevance of the estimator in an adaptive process.
International Nuclear Information System (INIS)
Lopez, C.; Koski, J.A.; Razani, A.
2000-01-01
A study of the errors introduced when one-dimensional inverse heat conduction techniques are applied to problems involving two-dimensional heat transfer effects was performed. The geometry used for the study was a cylinder with similar dimensions as a typical container used for the transportation of radioactive materials. The finite element analysis code MSC P/Thermal was used to generate synthetic test data that was then used as input for an inverse heat conduction code. Four different problems were considered including one with uniform flux around the outer surface of the cylinder and three with non-uniform flux applied over 360 deg C, 180 deg C, and 90 deg C sections of the outer surface of the cylinder. The Sandia One-Dimensional Direct and Inverse Thermal (SODDIT) code was used to estimate the surface heat flux of all four cases. The error analysis was performed by comparing the results from SODDIT and the heat flux calculated based on the temperature results obtained from P/Thermal. Results showed an increase in error of the surface heat flux estimates as the applied heat became more localized. For the uniform case, SODDIT provided heat flux estimates with a maximum error of 0.5% whereas for the non-uniform cases, the maximum errors were found to be about 3%, 7%, and 18% for the 360 deg C, 180 deg C, and 90 deg C cases, respectively
Aquatic concentrations of chemical analytes compared to ecotoxicity estimates
U.S. Environmental Protection Agency — We describe screening level estimates of potential aquatic toxicity posed by 227 chemical analytes that were measured in 25 ambient water samples collected as part...
Hall, Eric; Haakon, Hoel; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
2016-01-01
lognormal diffusion coefficients with H´ older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible
Sandberg, Mattias
2015-01-01
log normal diffusion coefficients with H¨older regularity of order up to 1/2 a.s. This low regularity implies that the high frequency finite element approximation error (i.e. the error from frequencies larger than the mesh frequency) is not negligible
National Suicide Rates a Century after Durkheim: Do We Know Enough to Estimate Error?
Claassen, Cynthia A.; Yip, Paul S.; Corcoran, Paul; Bossarte, Robert M.; Lawrence, Bruce A.; Currier, Glenn W.
2010-01-01
Durkheim's nineteenth-century analysis of national suicide rates dismissed prior concerns about mortality data fidelity. Over the intervening century, however, evidence documenting various types of error in suicide data has only mounted, and surprising levels of such error continue to be routinely uncovered. Yet the annual suicide rate remains the…
Adjoint-Based a Posteriori Error Estimation for Coupled Time-Dependent Systems
Asner, Liya; Tavener, Simon; Kay, David
2012-01-01
We consider time-dependent parabolic problem s coupled across a common interface which we formulate using a Lagrange multiplier construction and solve by applying a monolithic solution technique. We derive an adjoint-based a posteriori error representation for a quantity of interest given by a linear functional of the solution. We establish the accuracy of our error representation formula through numerical experimentation and investigate the effect of error in the adjoint solution. Crucially, the error representation affords a distinction between temporal and spatial errors and can be used as a basis for a blockwise time-space refinement strategy. Numerical tests illustrate the efficacy of the refinement strategy by capturing the distinctive behavior of a localized traveling wave solution. The saddle point systems considered here are equivalent to those arising in the mortar finite element technique for parabolic problems. © 2012 Society for Industrial and Applied Mathematics.
Kumar, Sudhir; Datta, D; Sharma, S D; Chourasiya, G; Babu, D A R; Sharma, D N
2014-04-01
Verification of the strength of high dose rate (HDR) (192)Ir brachytherapy sources on receipt from the vendor is an important component of institutional quality assurance program. Either reference air-kerma rate (RAKR) or air-kerma strength (AKS) is the recommended quantity to specify the strength of gamma-emitting brachytherapy sources. The use of Farmer-type cylindrical ionization chamber of sensitive volume 0.6 cm(3) is one of the recommended methods for measuring RAKR of HDR (192)Ir brachytherapy sources. While using the cylindrical chamber method, it is required to determine the positioning error of the ionization chamber with respect to the source which is called the distance error. An attempt has been made to apply the fuzzy set theory to estimate the subjective uncertainty associated with the distance error. A simplified approach of applying this fuzzy set theory has been proposed in the quantification of uncertainty associated with the distance error. In order to express the uncertainty in the framework of fuzzy sets, the uncertainty index was estimated and was found to be within 2.5%, which further indicates that the possibility of error in measuring such distance may be of this order. It is observed that the relative distance li estimated by analytical method and fuzzy set theoretic approach are consistent with each other. The crisp values of li estimated using analytical method lie within the bounds computed using fuzzy set theory. This indicates that li values estimated using analytical methods are within 2.5% uncertainty. This value of uncertainty in distance measurement should be incorporated in the uncertainty budget, while estimating the expanded uncertainty in HDR (192)Ir source strength measurement.
Borgia, Andrea; Spera, Frank J.
1990-01-01
This work discusses the propagation of errors for the recovery of the shear rate from wide-gap concentric cylinder viscometric measurements of non-Newtonian fluids. A least-square regression of stress on angular velocity data to a system of arbitrary functions is used to propagate the errors for the series solution to the viscometric flow developed by Krieger and Elrod (1953) and Pawlowski (1953) ('power-law' approximation) and for the first term of the series developed by Krieger (1968). A numerical experiment shows that, for measurements affected by significant errors, the first term of the Krieger-Elrod-Pawlowski series ('infinite radius' approximation) and the power-law approximation may recover the shear rate with equal accuracy as the full Krieger-Elrod-Pawlowski solution. An experiment on a clay slurry indicates that the clay has a larger yield stress at rest than during shearing, and that, for the range of shear rates investigated, a four-parameter constitutive equation approximates reasonably well its rheology. The error analysis presented is useful for studying the rheology of fluids such as particle suspensions, slurries, foams, and magma.
Effect of Numerical Error on Gravity Field Estimation for GRACE and Future Gravity Missions
McCullough, Christopher; Bettadpur, Srinivas
2015-04-01
In recent decades, gravity field determination from low Earth orbiting satellites, such as the Gravity Recovery and Climate Experiment (GRACE), has become increasingly more effective due to the incorporation of high accuracy measurement devices. Since instrumentation quality will only increase in the near future and the gravity field determination process is computationally and numerically intensive, numerical error from the use of double precision arithmetic will eventually become a prominent error source. While using double-extended or quadruple precision arithmetic will reduce these errors, the numerical limitations of current orbit determination algorithms and processes must be accurately identified and quantified in order to adequately inform the science data processing techniques of future gravity missions. The most obvious numerical limitation in the orbit determination process is evident in the comparison of measured observables with computed values, derived from mathematical models relating the satellites' numerically integrated state to the observable. Significant error in the computed trajectory will corrupt this comparison and induce error in the least squares solution of the gravitational field. In addition, errors in the numerically computed trajectory propagate into the evaluation of the mathematical measurement model's partial derivatives. These errors amalgamate in turn with numerical error from the computation of the state transition matrix, computed using the variational equations of motion, in the least squares mapping matrix. Finally, the solution of the linearized least squares system, computed using a QR factorization, is also susceptible to numerical error. Certain interesting combinations of each of these numerical errors are examined in the framework of GRACE gravity field determination to analyze and quantify their effects on gravity field recovery.
Directory of Open Access Journals (Sweden)
Boeschoten Laura
2017-12-01
Full Text Available Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible combinations with scores on other variables. Furthermore, the latent class model, by multiply imputing a new variable, enhances the quality of statistics based on the composite data set. The performance of this method is investigated by a simulation study, which shows that whether or not the method can be applied depends on the entropy R2 of the latent class model and the type of analysis a researcher is planning to do. Finally, the method is applied to public data from Statistics Netherlands.
Frolov, Maxim; Chistiakova, Olga
2017-06-01
Paper is devoted to a numerical justification of the recent a posteriori error estimate for Reissner-Mindlin plates. This majorant provides a reliable control of accuracy of any conforming approximate solution of the problem including solutions obtained with commercial software for mechanical engineering. The estimate is developed on the basis of the functional approach and is applicable to several types of boundary conditions. To verify the approach, numerical examples with mesh refinements are provided.
An error bound estimate and convergence of the Nodal-LTS {sub N} solution in a rectangle
Energy Technology Data Exchange (ETDEWEB)
Hauser, Eliete Biasotto [Faculty of Mathematics, PUCRS Av Ipiranga 6681, Building 15, Porto Alegre - RS 90619-900 (Brazil)]. E-mail: eliete@pucrs.br; Pazos, Ruben Panta [Department of Mathematics, UNISC Av Independencia, 2293, room 1301, Santa Cruz do Sul - RS 96815-900 (Brazil)]. E-mail: rpp@impa.br; Tullio de Vilhena, Marco [Graduate Program in Applied Mathematics, UFRGS Av Bento Goncalves 9500, Building 43-111, Porto Alegre - RS 91509-900 (Brazil)]. E-mail: vilhena@mat.ufrgs.br
2005-07-15
In this work, we report the mathematical analysis concerning error bound estimate and convergence of the Nodal-LTS {sub N} solution in a rectangle. For such we present an efficient algorithm, called LTS {sub N} 2D-Diag solution for Cartesian geometry.
Goswami, Deepjyoti
2013-05-01
In the first part of this article, a new mixed method is proposed and analyzed for parabolic integro-differential equations (PIDE) with nonsmooth initial data. Compared to the standard mixed method for PIDE, the present method does not bank on a reformulation using a resolvent operator. Based on energy arguments combined with a repeated use of an integral operator and without using parabolic type duality technique, optimal L2 L2-error estimates are derived for semidiscrete approximations, when the initial condition is in L2 L2. Due to the presence of the integral term, it is, further, observed that a negative norm estimate plays a crucial role in our error analysis. Moreover, the proposed analysis follows the spirit of the proof techniques used in deriving optimal error estimates for finite element approximations to PIDE with smooth data and therefore, it unifies both the theories, i.e., one for smooth data and other for nonsmooth data. Finally, we extend the proposed analysis to the standard mixed method for PIDE with rough initial data and provide an optimal error estimate in L2, L 2, which improves upon the results available in the literature. © 2013 Springer Science+Business Media New York.
Estimates of CO2 traffic emissions from mobile concentration measurements
Maness, H. L.; Thurlow, M. E.; McDonald, B. C.; Harley, R. A.
2015-03-01
We present data from a new mobile system intended to aid in the design of upcoming urban CO2-monitoring networks. Our collected data include GPS probe data, video-derived traffic density, and accurate CO2 concentration measurements. The method described here is economical, scalable, and self-contained, allowing for potential future deployment in locations without existing traffic infrastructure or vehicle fleet information. Using a test data set collected on California Highway 24 over a 2 week period, we observe that on-road CO2 concentrations are elevated by a factor of 2 in congestion compared to free-flow conditions. This result is found to be consistent with a model including vehicle-induced turbulence and standard engine physics. In contrast to surface concentrations, surface emissions are found to be relatively insensitive to congestion. We next use our model for CO2 concentration together with our data to independently derive vehicle emission rate parameters. Parameters scaling the leading four emission rate terms are found to be within 25% of those expected for a typical passenger car fleet, enabling us to derive instantaneous emission rates directly from our data that compare generally favorably to predictive models presented in the literature. The present results highlight the importance of high spatial and temporal resolution traffic data for interpreting on- and near-road concentration measurements. Future work will focus on transport and the integration of mobile platforms into existing stationary network designs.
Quantitative estimation of the human error probability during soft control operations
International Nuclear Information System (INIS)
Lee, Seung Jun; Kim, Jaewhan; Jung, Wondea
2013-01-01
Highlights: ► An HRA method to evaluate execution HEP for soft control operations was proposed. ► The soft control tasks were analyzed and design-related influencing factors were identified. ► An application to evaluate the effects of soft controls was performed. - Abstract: In this work, a method was proposed for quantifying human errors that can occur during operation executions using soft controls. Soft controls of advanced main control rooms have totally different features from conventional controls, and thus they may have different human error modes and occurrence probabilities. It is important to identify the human error modes and quantify the error probability for evaluating the reliability of the system and preventing errors. This work suggests an evaluation framework for quantifying the execution error probability using soft controls. In the application result, it was observed that the human error probabilities of soft controls showed both positive and negative results compared to the conventional controls according to the design quality of advanced main control rooms
International Nuclear Information System (INIS)
Ishima, Rieko; Torchia, Dennis A.
2005-01-01
Off-resonance effects can introduce significant systematic errors in R 2 measurements in constant-time Carr-Purcell-Meiboom-Gill (CPMG) transverse relaxation dispersion experiments. For an off-resonance chemical shift of 500 Hz, 15 N relaxation dispersion profiles obtained from experiment and computer simulation indicated a systematic error of ca. 3%. This error is three- to five-fold larger than the random error in R 2 caused by noise. Good estimates of total R 2 uncertainty are critical in order to obtain accurate estimates in optimized chemical exchange parameters and their uncertainties derived from χ 2 minimization of a target function. Here, we present a simple empirical approach that provides a good estimate of the total error (systematic + random) in 15 N R 2 values measured for the HIV protease. The advantage of this empirical error estimate is that it is applicable even when some of the factors that contribute to the off-resonance error are not known. These errors are incorporated into a χ 2 minimization protocol, in which the Carver-Richards equation is used fit the observed R 2 dispersion profiles, that yields optimized chemical exchange parameters and their confidence limits. Optimized parameters are also derived, using the same protein sample and data-fitting protocol, from 1 H R 2 measurements in which systematic errors are negligible. Although 1 H and 15 N relaxation profiles of individual residues were well fit, the optimized exchange parameters had large uncertainties (confidence limits). In contrast, when a single pair of exchange parameters (the exchange lifetime, τ ex , and the fractional population, p a ), were constrained to globally fit all R 2 profiles for residues in the dimer interface of the protein, confidence limits were less than 8% for all optimized exchange parameters. In addition, F-tests showed that quality of the fits obtained using τ ex , p a as global parameters were not improved when these parameters were free to fit the R
Ng, Kar Yong; Awang, Norhashidah
2018-01-06
Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
Cost estimates for flat plate and concentrator collector arrays
Shimada, K.
1982-01-01
The current module and installation costs for the U.S. National Photovoltaic Program's grid-connected systems are significantly higher than required for economic viability of this alternative. Attention is accordingly given to the prospects for installed module cost reductions in flat plate, linear focus Fresnel concentrator, and point focus Fresnel concentrator candidate systems. Cost projections indicate that all three systems would meet near-term and midterm goals, provided that module costs of $2.80/W(p) and $0.70/W(p), respectively, are met. The point focus Fresnel system emerges as the most viable for the near term.
International Nuclear Information System (INIS)
Verma, Surendra P.; Andaverde, Jorge; Santoyo, E.
2006-01-01
We used the error propagation theory to calculate uncertainties in static formation temperature estimates in geothermal and petroleum wells from three widely used methods (line-source or Horner method; spherical and radial heat flow method; and cylindrical heat source method). Although these methods commonly use an ordinary least-squares linear regression model considered in this study, we also evaluated two variants of a weighted least-squares linear regression model for the actual relationship between the bottom-hole temperature and the corresponding time functions. Equations based on the error propagation theory were derived for estimating uncertainties in the time function of each analytical method. These uncertainties in conjunction with those on bottom-hole temperatures were used to estimate individual weighting factors required for applying the two variants of the weighted least-squares regression model. Standard deviations and 95% confidence limits of intercept were calculated for both types of linear regressions. Applications showed that static formation temperatures computed with the spherical and radial heat flow method were generally greater (at the 95% confidence level) than those from the other two methods under study. When typical measurement errors of 0.25 h in time and 5 deg. C in bottom-hole temperature were assumed for the weighted least-squares model, the uncertainties in the estimated static formation temperatures were greater than those for the ordinary least-squares model. However, if these errors were smaller (about 1% in time and 0.5% in temperature measurements), the weighted least-squares linear regression model would generally provide smaller uncertainties for the estimated temperatures than the ordinary least-squares linear regression model. Therefore, the weighted model would be statistically correct and more appropriate for such applications. We also suggest that at least 30 precise and accurate BHT and time measurements along with
Point-of-care estimation of haemoglobin concentration in neonates ...
African Journals Online (AJOL)
Objective. The HemoCue is a point-of-care analytical system for haemoglobin concentration (Hb) measurement. Point-of-care testing has been validated in hospitals and outpatient departments to assist with urgent patient management by providing rapid laboratory test results. Method. In this prospective study we compared ...
Energy Technology Data Exchange (ETDEWEB)
Takamiya, Masanori [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan and Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Nakamura, Mitsuhiro, E-mail: m-nkmr@kuhp.kyoto-u.ac.jp; Akimoto, Mami; Ueki, Nami; Yamada, Masahiro; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro [Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507 (Japan); Tanabe, Hiroaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047 (Japan); Kokubo, Masaki [Division of Radiation Oncology, Institute of Biomedical Research and Innovation, Kobe 650-0047, Japan and Department of Radiation Oncology, Kobe City Medical Center General Hospital, Kobe 650-0047 (Japan); Itoh, Akio [Department of Nuclear Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501 (Japan)
2016-04-15
Purpose: To assess the target localization error (TLE) in terms of the distance between the target and the localization point estimated from the surrogates (|TMD|), the average of respiratory motion for the surrogates and the target (|aRM|), and the number of fiducial markers used for estimating the target (n). Methods: This study enrolled 17 lung cancer patients who subsequently underwent four fractions of real-time tumor tracking irradiation. Four or five fiducial markers were implanted around the lung tumor. The three-dimensional (3D) distance between the tumor and markers was at maximum 58.7 mm. One of the markers was used as the target (P{sub t}), and those markers with a 3D |TMD{sub n}| ≤ 58.7 mm at end-exhalation were then selected. The estimated target position (P{sub e}) was calculated from a localization point consisting of one to three markers except P{sub t}. Respiratory motion for P{sub t} and P{sub e} was defined as the root mean square of each displacement, and |aRM| was calculated from the mean value. TLE was defined as the root mean square of each difference between P{sub t} and P{sub e} during the monitoring of each fraction. These procedures were performed repeatedly using the remaining markers. To provide the best guidance on the answer with n and |TMD|, fiducial markers with a 3D |aRM ≥ 10 mm were selected. Finally, a total of 205, 282, and 76 TLEs that fulfilled the 3D |TMD| and 3D |aRM| criteria were obtained for n = 1, 2, and 3, respectively. Multiple regression analysis (MRA) was used to evaluate TLE as a function of |TMD| and |aRM| in each n. Results: |TMD| for n = 1 was larger than that for n = 3. Moreover, |aRM| was almost constant for all n, indicating a similar scale for the marker’s motion near the lung tumor. MRA showed that |aRM| in the left–right direction was the major cause of TLE; however, the contribution made little difference to the 3D TLE because of the small amount of motion in the left–right direction. The TLE
An A Posteriori Error Estimate for Symplectic Euler Approximation of Optimal Control Problems
Karlsson, Peer Jesper; Larsson, Stig; Sandberg, Mattias; Szepessy, Anders; Tempone, Raul
2015-01-01
This work focuses on numerical solutions of optimal control problems. A time discretization error representation is derived for the approximation of the associated value function. It concerns Symplectic Euler solutions of the Hamiltonian system
An Extended Quadratic Frobenius Primality Test with Average and Worst Case Error Estimates
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2003-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
An Extended Quadratic Frobenius Primality Test with Average- and Worst-Case Error Estimate
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2006-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
An Extended Quadratic Frobenius Primality Test with Average Case Error Estimates
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Frandsen, Gudmund Skovbjerg
2001-01-01
We present an Extended Quadratic Frobenius Primality Test (EQFT), which is related to an extends the Miller-Rabin test and the Quadratic Frobenius test (QFT) by Grantham. EQFT takes time about equivalent to 2 Miller-Rabin tests, but has much smaller error probability, namely 256/331776t for t...... for the error probability of this algorithm as well as a general closed expression bounding the error. For instance, it is at most 2-143 for k = 500, t = 2. Compared to earlier similar results for the Miller-Rabin test, the results indicates that our test in the average case has the effect of 9 Miller......-Rabin tests, while only taking time equivalent to about 2 such tests. We also give bounds for the error in case a prime is sought by incremental search from a random starting point....
International Nuclear Information System (INIS)
HAALAND, DAVID M.; VAN BENTHEM, MARK H.; WEHLBURG, CHRISTINE M.; KOEHLER, IV FREDERICK W.
2002-01-01
Hyperspectral Fourier transform infrared images have been obtained from a neoprene sample aged in air at elevated temperatures. The massive amount of spectra available from this heterogeneous sample provides the opportunity to perform quantitative analysis of the spectral data without the need for calibration standards. Multivariate curve resolution (MCR) methods with non-negativity constraints applied to the iterative alternating least squares analysis of the spectral data has been shown to achieve the goal of quantitative image analysis without the use of standards. However, the pure-component spectra and the relative concentration maps were heavily contaminated by the presence of system artifacts in the spectral data. We have demonstrated that the detrimental effects of these artifacts can be minimized by adding an estimate of the error covariance structure of the spectral image data to the MCR algorithm. The estimate is added by augmenting the concentration and pure-component spectra matrices with scores and eigenvectors obtained from the mean-centered repeat image differences of the sample. The implementation of augmentation is accomplished by employing efficient equality constraints on the MCR analysis. Augmentation with the scores from the repeat images is found to primarily improve the pure-component spectral estimates while augmentation with the corresponding eigenvectors primarily improves the concentration maps. Augmentation with both scores and eigenvectors yielded the best result by generating less noisy pure-component spectral estimates and relative concentration maps that were largely free from a striping artifact that is present due to system errors in the FT-IR images. The MCR methods presented are general and can also be applied productively to non-image spectral data
International Nuclear Information System (INIS)
Kim, Yochan; Park, Jinkyun; Jung, Wondea; Jang, Inseok; Hyun Seong, Poong
2015-01-01
Despite recent efforts toward data collection for supporting human reliability analysis, there remains a lack of empirical basis in determining the effects of performance shaping factors (PSFs) on human error probabilities (HEPs). To enhance the empirical basis regarding the effects of the PSFs, a statistical methodology using a logistic regression and stepwise variable selection was proposed, and the effects of the PSF on HEPs related with the soft controls were estimated through the methodology. For this estimation, more than 600 human error opportunities related to soft controls in a computerized control room were obtained through laboratory experiments. From the eight PSF surrogates and combinations of these variables, the procedure quality, practice level, and the operation type were identified as significant factors for screen switch and mode conversion errors. The contributions of these significant factors to HEPs were also estimated in terms of a multiplicative form. The usefulness and limitation of the experimental data and the techniques employed are discussed herein, and we believe that the logistic regression and stepwise variable selection methods will provide a way to estimate the effects of PSFs on HEPs in an objective manner. - Highlights: • It is necessary to develop an empirical basis for the effects of the PSFs on the HEPs. • A statistical method using a logistic regression and variable selection was proposed. • The effects of PSFs on the HEPs of soft controls were empirically investigated. • The significant factors were identified and their effects were estimated
Liang Yang,
2013-06-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we first consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation errors and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use them to evaluate the outage probability, error probability, and achievable rate. Subsequently, to investigate the joint effects of the channel estimation error and CCI on the system performance, we extend our analysis to a multiple-relay network and derive several asymptotic performance expressions. For comparison purposes, we also provide the analysis for the relay selection scheme under the total power constraint at the relays. For AF TWRN with channel estimation error and CCI, numerical results show that the performance of the relay selection scheme is not always better than that of the all-relay participating case. In particular, the relay selection scheme can improve the system performance in the case of high power levels at the sources and small powers at the relays.
Minaudo, C.; Moatar, F.; Abbott, B. W.; Dupas, R.; Gascuel-Odoux, C.; Pinay, G.; Roubeix, V.; Danis, P. A.
2017-12-01
Many lakes and reservoirs in Europe suffer from severe eutrophication. Accurate quantification of nutrient loads are critical for effective mitigation measures, but this information is often unknown. For example, in France, only 50 out of 481 lakes and reservoirs have national monitoring allowing estimation of interannual nitrogen and phosphorus loads, and even these loads are computed from low-frequency data. To address this lack of data, we developed a straightforward method to predict seasonal loads in lake tributaries. First, we analyzed concentration-discharge (C-Q) curves in monitored catchments and identified slopes, intercepts, and coefficient of variation of the log(C)-log(Q) regressions determined for both low and high flows, separated by the median daily flow [Moatar et al., 2017]. Then, we used stepwise multiple linear regression models to empirically link the characteristics of C-Q curves with a set of catchment descriptors such as land use, lithology, morphology indices, climate, and hydrological indicators. Modeled C-Q relationships were then used to estimate annual and seasonal nutrient loads in nearby and similar unmonitored catchments. We implemented this approach on a large dataset from France where stream flow was surveyed daily and water quality (suspended solids, nitrate, total phosphorus, and orthophosphate concentrations) was measured on a monthly basis at 233 stations over the past 20 years in catchments from 10 to 3000 km². The concentration at the median daily flow (seen here as a metric of the general level of contamination in a catchment) was predicted with uncertainty ranging between 30 and 100 %, depending on the variable. C-Q slopes were predicted with large errors, but a sensitivity analysis was conducted to determine the impact of C-Q slopes uncertainties on computed annual and seasonal loads. This approach allows estimation of seasonal and annual nutrient loads and could be potentially implemented to improve protection and
Yang, Liang
2013-04-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation error and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use these expressions to evaluate the outage probability and error probability. Numerical results show that the approximate closed-form expressions are very close to the exact ones. © 2013 IEEE.
Lasky, Tamar; Sun, Wenyu; Kadry, Abdel; Hoffman, Michael K
2004-01-01
The purpose of this study was to estimate mean concentrations of total arsenic in chicken liver tissue and then estimate total and inorganic arsenic ingested by humans through chicken consumption. We used national monitoring data from the Food Safety and Inspection Service National Residue Program to estimate mean arsenic concentrations for 1994-2000. Incorporating assumptions about the concentrations of arsenic in liver and muscle tissues as well as the proportions of inorganic and organic a...
Estimation of suspended sediment concentration in rivers using acoustic methods.
Elçi, Sebnem; Aydin, Ramazan; Work, Paul A
2009-12-01
Acoustic Doppler current meters (ADV, ADCP, and ADP) are widely used in water systems to measure flow velocities and velocity profiles. Although these meters are designed for flow velocity measurements, they can also provide information defining the quantity of particulate matter in the water, after appropriate calibration. When an acoustic instrument is calibrated for a water system, no additional sensor is needed to measure suspended sediment concentration (SSC). This provides the simultaneous measurements of velocity and concentration required for most sediment transport studies. The performance of acoustic Doppler current meters for measuring SSC was investigated in different studies where signal-to-noise ratio (SNR) and suspended sediment concentration were related using different formulations. However, these studies were each limited to a single study site where neither the effect of particle size nor the effect of temperature was investigated. In this study, different parameters that affect the performance of an ADV for the prediction of SSC are investigated. In order to investigate the reliability of an ADV for SSC measurements in different environments, flow and SSC measurements were made in different streams located in the Aegean region of Turkey having different soil types. Soil samples were collected from all measuring stations and particle size analysis was conducted by mechanical means. Multivariate analysis was utilized to investigate the effect of soil type and water temperature on the measurements. Statistical analysis indicates that SNR readings ob tained from the ADV are affected by water temperature and particle size distribution of the soil, as expected, and a prediction model is presented relating SNR readings to SSC mea surements where both water temperature and sediment characteristics type are incorporated into the model. The coefficients of the suggested model were obtained using the multivariate anal ysis. Effect of high turbidity
Nair, S. P.; Righetti, R.
2015-05-01
Recent elastography techniques focus on imaging information on properties of materials which can be modeled as viscoelastic or poroelastic. These techniques often require the fitting of temporal strain data, acquired from either a creep or stress-relaxation experiment to a mathematical model using least square error (LSE) parameter estimation. It is known that the strain versus time relationships for tissues undergoing creep compression have a non-linear relationship. In non-linear cases, devising a measure of estimate reliability can be challenging. In this article, we have developed and tested a method to provide non linear LSE parameter estimate reliability: which we called Resimulation of Noise (RoN). RoN provides a measure of reliability by estimating the spread of parameter estimates from a single experiment realization. We have tested RoN specifically for the case of axial strain time constant parameter estimation in poroelastic media. Our tests show that the RoN estimated precision has a linear relationship to the actual precision of the LSE estimator. We have also compared results from the RoN derived measure of reliability against a commonly used reliability measure: the correlation coefficient (CorrCoeff). Our results show that CorrCoeff is a poor measure of estimate reliability for non-linear LSE parameter estimation. While the RoN is specifically tested only for axial strain time constant imaging, a general algorithm is provided for use in all LSE parameter estimation.
International Nuclear Information System (INIS)
Zhang Yuanzhi; Lin Hui; Chen, Chuqun; Chen Liding; Zhang Bing; Gitelson, Anatoly A
2011-01-01
The objective of this work is to estimate chlorophyll-a (chl-a) concentration in the Pearl River estuary in China. To test the performance of algorithms for the estimation of the chl-a concentration in these productive turbid waters, the maximum band ratio (MBR) and near-infrared-red (NIR-red) models are used in this study. Specific focus is placed on (a) comparing the ability of the models to estimate chl-a in the range 1-12 mg m -3 , which is typical for coastal and estuarine waters, and (b) assessing the potential of the Moderate Resolution Imaging Spectrometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS) to estimate chl-a concentrations. Reflectance spectra and water samples were collected at 13 stations with chl-a ranging from 0.83 to 11.8 mg m -3 and total suspended matter from 9.9 to 21.5 g m -3 . A close relationship was found between chl-a concentration and total suspended matter concentration with the determining coefficient (R 2 ) above 0.89. The MBR calculated in the spectral bands of MODIS proved to be a good proxy for chl-a concentration (R 2 > 0.93). On the other hand, both the NIR-red three-band model, with wavebands around 665, 700, and 730 nm, and the NIR-red two-band model (with bands around 665 and 700 nm) explained more than 95% of the chl-a variation, and we were able to estimate chl-a concentrations with a root mean square error below 1 mg m -3 . The two- and three-band NIR-red models with MERIS spectral bands accounted for 93% of the chl-a variation. These findings imply that the extensive database of MODIS and MERIS images could be used to quantitatively monitor chl-a in the Pearl River estuary.
Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.
Directory of Open Access Journals (Sweden)
Wei He
Full Text Available A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF for space instruments. A model for the system functional error rate (SFER is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA is presented. Based on experimental results of different ions (O, Si, Cl, Ti under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10-3(error/particle/cm2, while the MTTF is approximately 110.7 h.
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2002-01-01
Roč. 13, - (2002), s. 56-80 ISSN 1068-9613 R&D Projects: GA ČR GA201/02/0595 Institutional research plan: AV0Z1030915 Keywords : conjugate gradient method * Gauss kvadrature * evaluation of convergence * error bounds * finite precision arithmetic * rounding errors * loss of orthogonality Subject RIV: BA - General Mathematics Impact factor: 0.565, year: 2002 http://etna.mcs.kent.edu/volumes/2001-2010/vol13/abstract.php?vol=13&pages=56-80
Hallez, Hans; Staelens, Steven; Lemahieu, Ignace
2009-10-01
EEG source analysis is a valuable tool for brain functionality research and for diagnosing neurological disorders, such as epilepsy. It requires a geometrical representation of the human head or a head model, which is often modeled as an isotropic conductor. However, it is known that some brain tissues, such as the skull or white matter, have an anisotropic conductivity. Many studies reported that the anisotropic conductivities have an influence on the calculated electrode potentials. However, few studies have assessed the influence of anisotropic conductivities on the dipole estimations. In this study, we want to determine the dipole estimation errors due to not taking into account the anisotropic conductivities of the skull and/or brain tissues. Therefore, head models are constructed with the same geometry, but with an anisotropically conducting skull and/or brain tissue compartment. These head models are used in simulation studies where the dipole location and orientation error is calculated due to neglecting anisotropic conductivities of the skull and brain tissue. Results show that not taking into account the anisotropic conductivities of the skull yields a dipole location error between 2 and 25 mm, with an average of 10 mm. When the anisotropic conductivities of the brain tissues are neglected, the dipole location error ranges between 0 and 5 mm. In this case, the average dipole location error was 2.3 mm. In all simulations, the dipole orientation error was smaller than 10°. We can conclude that the anisotropic conductivities of the skull have to be incorporated to improve the accuracy of EEG source analysis. The results of the simulation, as presented here, also suggest that incorporation of the anisotropic conductivities of brain tissues is not necessary. However, more studies are needed to confirm these suggestions.
International Nuclear Information System (INIS)
Hallez, Hans; Staelens, Steven; Lemahieu, Ignace
2009-01-01
EEG source analysis is a valuable tool for brain functionality research and for diagnosing neurological disorders, such as epilepsy. It requires a geometrical representation of the human head or a head model, which is often modeled as an isotropic conductor. However, it is known that some brain tissues, such as the skull or white matter, have an anisotropic conductivity. Many studies reported that the anisotropic conductivities have an influence on the calculated electrode potentials. However, few studies have assessed the influence of anisotropic conductivities on the dipole estimations. In this study, we want to determine the dipole estimation errors due to not taking into account the anisotropic conductivities of the skull and/or brain tissues. Therefore, head models are constructed with the same geometry, but with an anisotropically conducting skull and/or brain tissue compartment. These head models are used in simulation studies where the dipole location and orientation error is calculated due to neglecting anisotropic conductivities of the skull and brain tissue. Results show that not taking into account the anisotropic conductivities of the skull yields a dipole location error between 2 and 25 mm, with an average of 10 mm. When the anisotropic conductivities of the brain tissues are neglected, the dipole location error ranges between 0 and 5 mm. In this case, the average dipole location error was 2.3 mm. In all simulations, the dipole orientation error was smaller than 10 deg. We can conclude that the anisotropic conductivities of the skull have to be incorporated to improve the accuracy of EEG source analysis. The results of the simulation, as presented here, also suggest that incorporation of the anisotropic conductivities of brain tissues is not necessary. However, more studies are needed to confirm these suggestions.
de Almeida, Maurício Liberal; Saatkamp, Cassiano Junior; Fernandes, Adriana Barrinha; Pinheiro, Antonio Luiz Barbosa; Silveira, Landulfo
2016-09-01
Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.
DEFF Research Database (Denmark)
Gaynor, J. E.; Kristensen, Leif
1986-01-01
Observatory tower. The approximate magnitude of the error due to spatial and temporal pulse volume separation is presented as a function of mean wind angle relative to the sodar configuration and for several antenna pulsing orders. Sodar-derived standard deviations of the lateral wind component, before...
Directory of Open Access Journals (Sweden)
Wack David S
2012-07-01
Full Text Available Abstract Background Presented is the method “Detection and Outline Error Estimates” (DOEE for assessing rater agreement in the delineation of multiple sclerosis (MS lesions. The DOEE method divides operator or rater assessment into two parts: 1 Detection Error (DE -- rater agreement in detecting the same regions to mark, and 2 Outline Error (OE -- agreement of the raters in outlining of the same lesion. Methods DE, OE and Similarity Index (SI values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA of the raters' Region of Interests (ROIs. Results When correlated with MTA, neither DE (ρ = .056, p=.83 nor the ratio of OE to MTA (ρ = .23, p=.37, referred to as Outline Error Rate (OER, exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p Conclusions The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement.
DEFF Research Database (Denmark)
Hansen, Peter Reinhard; Lunde, Asger
2014-01-01
An economic time series can often be viewed as a noisy proxy for an underlying economic variable. Measurement errors will influence the dynamic properties of the observed process and may conceal the persistence of the underlying time series. In this paper we develop instrumental variable (IV...
International Nuclear Information System (INIS)
Guelden, Michael; Seibert, Hasso
2003-01-01
In the present study an extrapolation model for estimating serum concentrations of chemicals equivalent to in vitro effective concentrations is developed and applied to median cytotoxic concentrations (EC 50 ) determined in vitro. Nominal concentrations of a chemical in serum and in vitro are regarded as equivalent, if they result in the same aqueous concentration of the unbound form. The algorithm used is based on equilibrium distribution and requires albumin binding data, the octanol-water partition coefficient (K ow ), and the albumin concentrations and lipid volume fractions in vitro and in serum. The chemicals studied cover wide ranges of cytotoxic potency (EC 50 : 2.5-530000 μM) and lipophilicity (log K ow : -5 to 7). Their albumin binding characteristics have been determined by means of an in vitro cytotoxicity test as described previously. The equivalent serum concentrations of 19 of the 33 compounds investigated, having high protein binding and/or lipophilicity, were substantially higher than the EC 50 -values, by factors of 2.5-58. Prominent deviations between the equivalent nominal concentrations in serum and in vitro were largely restricted to chemicals with higher cytotoxic potency (EC 50 ≤1000 μM). The results suggest that estimates of equivalent serum concentrations based on in vitro data are robust for chemicals with low lipophilicity (log K ow ≤2) and low potency (EC 50 >1000 μM). With more potent chemicals or those with higher lipophilicity partitioning into lipids and/or binding to serum proteins have to be taken into account when estimating in vivo serum concentrations equivalent to in vitro effective concentrations
International Nuclear Information System (INIS)
Oliveira, G.M. de; Leitao, M. de M.V.B.R.
2000-01-01
The objective of this study was to analyze the consequences in the evapotranspiration estimates (ET) during the growing cycle of a peanut crop due to the errors committed in the determination of the radiation balance (Rn), as well as those caused by the advective effects. This research was conducted at the Experimental Station of CODEVASF in an irrigated perimeter located in the city of Rodelas, BA, during the period of September to December of 1996. The results showed that errors of the order of 2.2 MJ m -2 d -1 in the calculation of Rn, and consequently in the estimate of ET, can occur depending on the time considered for the daily total of Rn. It was verified that the surrounding areas of the experimental field, as well as the areas of exposed soil within the field, contributed significantly to the generation of local advection of sensible heat, which resulted in the increase of the evapotranspiration [pt
Directory of Open Access Journals (Sweden)
Hyun Young Lee
2010-01-01
Full Text Available We analyze discontinuous Galerkin methods with penalty terms, namely, symmetric interior penalty Galerkin methods, to solve nonlinear Sobolev equations. We construct finite element spaces on which we develop fully discrete approximations using extrapolated Crank-Nicolson method. We adopt an appropriate elliptic-type projection, which leads to optimal ℓ∞(L2 error estimates of discontinuous Galerkin approximations in both spatial direction and temporal direction.
Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang
2018-01-01
Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.
Bhargava, K.; Kalnay, E.; Carton, J.; Yang, F.
2017-12-01
Systematic forecast errors, arising from model deficiencies, form a significant portion of the total forecast error in weather prediction models like the Global Forecast System (GFS). While much effort has been expended to improve models, substantial model error remains. The aim here is to (i) estimate the model deficiencies in the GFS that lead to systematic forecast errors, (ii) implement an online correction (i.e., within the model) scheme to correct GFS following the methodology of Danforth et al. [2007] and Danforth and Kalnay [2008, GRL]. Analysis Increments represent the corrections that new observations make on, in this case, the 6-hr forecast in the analysis cycle. Model bias corrections are estimated from the time average of the analysis increments divided by 6-hr, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012-2016, seasonal means of the 6-hr model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the sub-monthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which is attributed to improvements in the specification of the SSTs. These results encourage application of online correction, as suggested by Danforth and Kalnay, for mean, seasonal and diurnal and semidiurnal model biases in GFS to reduce both systematic and random errors. As the error growth in the short-term is still linear, estimated model bias corrections can be added as a forcing term in the model tendency equation to correct online. Preliminary experiments with GFS, correcting temperature and specific humidity online show reduction in model bias in 6-hr forecast. This approach can then be used to guide and optimize the design of sub
Directory of Open Access Journals (Sweden)
Githure John I
2009-09-01
Full Text Available Abstract Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression. The eigenfunction
International Nuclear Information System (INIS)
Stillwell, W.G.; Seaver, D.A.; Schwartz, J.P.
1982-05-01
This report reviews probability assessment and psychological scaling techniques that could be used to estimate human error probabilities (HEPs) in nuclear power plant operations. The techniques rely on expert opinion and can be used to estimate HEPs where data do not exist or are inadequate. These techniques have been used in various other contexts and have been shown to produce reasonably accurate probabilities. Some problems do exist, and limitations are discussed. Additional topics covered include methods for combining estimates from multiple experts, the effects of training on probability estimates, and some ideas on structuring the relationship between performance shaping factors and HEPs. Preliminary recommendations are provided along with cautions regarding the costs of implementing the recommendations. Additional research is required before definitive recommendations can be made
Directory of Open Access Journals (Sweden)
Adytia Darmawan
2016-12-01
Full Text Available Position estimation using WIMU (Wireless Inertial Measurement Unit is one of emerging technology in the field of indoor positioning systems. WIMU can detect movement and does not depend on GPS signals. The position is then estimated using a modified ZUPT (Zero Velocity Update method that was using Filter Magnitude Acceleration (FMA, Variance Magnitude Acceleration (VMA and Angular Rate (AR estimation. Performance of this method was justified on a six-legged robot navigation system. Experimental result shows that the combination of VMA-AR gives the best position estimation.
Energy Technology Data Exchange (ETDEWEB)
Gitelson, Anatoly A; Gurlin, Daniela; Moses, Wesley J; Barrow, Tadd, E-mail: agitelson2@unl.ed [Center for Advanced Land Management Information Technologies (CALMIT), School of Natural Resources, University of Nebraska-Lincoln (United States)
2009-10-15
The objective of this work was to test the performance of a recently developed three-band model and its special case, a two-band model, for the remote estimation of the chlorophyll- a (chl-a) concentration in turbid productive case 2 waters. We specifically focused on (a) determining the ability of the models to estimate chl- a <20 mg m{sup -3}, typical for coastal and estuarine waters, and (b) assessing the potential of MODIS and MERIS to estimate chl-a concentrations in turbid productive waters, using red and near-infrared (NIR) bands. Reflectance spectra and water samples were collected in 89 stations over lakes in the United States with a wide variability in optical parameters (i.e. 2.1
International Nuclear Information System (INIS)
Gitelson, Anatoly A; Gurlin, Daniela; Moses, Wesley J; Barrow, Tadd
2009-01-01
The objective of this work was to test the performance of a recently developed three-band model and its special case, a two-band model, for the remote estimation of the chlorophyll- a (chl-a) concentration in turbid productive case 2 waters. We specifically focused on (a) determining the ability of the models to estimate chl- a -3 , typical for coastal and estuarine waters, and (b) assessing the potential of MODIS and MERIS to estimate chl-a concentrations in turbid productive waters, using red and near-infrared (NIR) bands. Reflectance spectra and water samples were collected in 89 stations over lakes in the United States with a wide variability in optical parameters (i.e. 2.1 -3 ; 0.5 -1 ). The three-band model, using wavebands around 670, 710 and 750 nm, explains more than 89% of the chl- a variation for chl- a ranging from 2 to 20 mg m -3 and can be used to estimate chlorophyll-a concentrations with a root mean square error (RMSE) of -3 . MODIS (bands 13 and 15) and MERIS (bands 7, 9, and 10) red and NIR reflectances were simulated from the collected reflectance spectra and potential estimation errors were assessed. The MODIS two-band model is able to estimate chl- a concentrations with a RMSE of -3 for chl-a ranging from 2 to 50 mg m -3 ; however, the model loses its sensitivity for chl- a -3 . Benefiting from the higher spectral resolution of the MERIS data, the MERIS three-band model accounts for 93% of chl- a variation and is able to estimate chl-a concentrations with a RMSE of -3 for chl-a ranging from 2 to 50 mg m -3 , and a RMSE of -3 for chl-a ranging from 2 to 20 mg m -3 . These findings imply that, provided that an atmospheric correction scheme specific to the red and NIR spectral region is available, the extensive database of MODIS and MERIS images could be used to quantitatively monitor chl- a in case 2 waters.
International Nuclear Information System (INIS)
Nascimento, C.S. do; Mesquita, R.N. de
2009-01-01
Recent studies point human error as an important factor for many industrial and nuclear accidents: Three Mile Island (1979), Bhopal (1984), Chernobyl and Challenger (1986) are classical examples. Human contribution to these accidents may be better understood and analyzed by using Human Reliability Analysis (HRA), which has being taken as an essential part on Probabilistic Safety Analysis (PSA) of nuclear plants. Both HRA and PSA depend on Human Error Probability (HEP) for a quantitative analysis. These probabilities are extremely affected by the Performance Shaping Factors (PSF), which has a direct effect on human behavior and thus shape HEP according with specific environment conditions and personal individual characteristics which are responsible for these actions. This PSF dependence raises a great problem on data availability as turn these scarcely existent database too much generic or too much specific. Besides this, most of nuclear plants do not keep historical records of human error occurrences. Therefore, in order to overcome this occasional data shortage, a methodology based on Fuzzy Inference and expert judgment was employed in this paper in order to determine human error occurrence probabilities and to evaluate PSF's on performed actions by operators in a nuclear power plant (IEA-R1 nuclear reactor). Obtained HEP values were compared with reference tabled data used on current literature in order to show method coherence and valid approach. This comparison leads to a conclusion that this work results are able to be employed both on HRA and PSA enabling efficient prospection of plant safety conditions, operational procedures and local working conditions potential improvements (author)
Barth, Timothy J.
2014-01-01
Simulation codes often utilize finite-dimensional approximation resulting in numerical error. Some examples include, numerical methods utilizing grids and finite-dimensional basis functions, particle methods using a finite number of particles. These same simulation codes also often contain sources of uncertainty, for example, uncertain parameters and fields associated with the imposition of initial and boundary data,uncertain physical model parameters such as chemical reaction rates, mixture model parameters, material property parameters, etc.
Error estimation for ADS nuclear properties by using nuclear data covariances
International Nuclear Information System (INIS)
Tsujimoto, Kazufumi
2005-01-01
Error for nuclear properties of accelerator-driven subcritical system by the uncertainties of nuclear data was performed. An uncertainty analysis was done using the sensitivity coefficients based on the generalized perturbation theory and the variance matrix data. For major actinides and structural material, the covariance data in JENDL-3.3 library were used. For MA, newly evaluated covariance data was used since there had been no reliable data in all libraries. (author)
A Statistical Algorithm for Estimating Chlorophyll Concentration in the New Caledonian Lagoon
Directory of Open Access Journals (Sweden)
Guillaume Wattelez
2016-01-01
Full Text Available Spatial and temporal dynamics of phytoplankton biomass and water turbidity can provide crucial information about the function, health and vulnerability of lagoon ecosystems (coral reefs, sea grasses, etc.. A statistical algorithm is proposed to estimate chlorophyll-a concentration ([chl-a] in optically complex waters of the New Caledonian lagoon from MODIS-derived “remote-sensing” reflectance (Rrs. The algorithm is developed via supervised learning on match-ups gathered from 2002 to 2010. The best performance is obtained by combining two models, selected according to the ratio of Rrs in spectral bands centered on 488 and 555 nm: a log-linear model for low [chl-a] (AFLC and a support vector machine (SVM model or a classic model (OC3 for high [chl-a]. The log-linear model is developed based on SVM regression analysis. This approach outperforms the classical OC3 approach, especially in shallow waters, with a root mean squared error 30% lower. The proposed algorithm enables more accurate assessments of [chl-a] and its variability in this typical oligo- to meso-trophic tropical lagoon, from shallow coastal waters and nearby reefs to deeper waters and in the open ocean.
Chan, Leo Li-Ying; Laverty, Daniel J; Smith, Tim; Nejad, Parham; Hei, Hillary; Gandhi, Roopali; Kuksin, Dmitry; Qiu, Jean
2013-02-28
Peripheral blood mononuclear cells (PBMCs) have been widely researched in the fields of immunology, infectious disease, oncology, transplantation, hematological malignancy, and vaccine development. Specifically, in immunology research, PBMCs have been utilized to monitor concentration, viability, proliferation, and cytokine production from immune cells, which are critical for both clinical trials and biomedical research. The viability and concentration of isolated PBMCs are traditionally measured by manual counting with trypan blue (TB) using a hemacytometer. One of the common issues of PBMC isolation is red blood cell (RBC) contamination. The RBC contamination can be dependent on the donor sample and/or technical skill level of the operator. RBC contamination in a PBMC sample can introduce error to the measured concentration, which can pass down to future experimental assays performed on these cells. To resolve this issue, RBC lysing protocol can be used to eliminate potential error caused by RBC contamination. In the recent years, a rapid fluorescence-based image cytometry system has been utilized for bright-field and fluorescence imaging analysis of cellular characteristics (Nexcelom Bioscience LLC, Lawrence, MA). The Cellometer image cytometry system has demonstrated the capability of automated concentration and viability detection in disposable counting chambers of unpurified mouse splenocytes and PBMCs stained with acridine orange (AO) and propidium iodide (PI) under fluorescence detection. In this work, we demonstrate the ability of Cellometer image cytometry system to accurately measure PBMC concentration, despite RBC contamination, by comparison of five different total PBMC counting methods: (1) manual counting of trypan blue-stained PBMCs in hemacytometer, (2) manual counting of PBMCs in bright-field images, (3) manual counting of acetic acid lysing of RBCs with TB-stained PBMCs, (4) automated counting of acetic acid lysing of RBCs with PI-stained PBMCs
DEFF Research Database (Denmark)
Lowes, F.J.; Olsen, Nils
2004-01-01
Most modern spherical harmonic geomagnetic models based on satellite data include estimates of the variances of the spherical harmonic coefficients of the model; these estimates are based on the geometry of the data and the fitting functions, and on the magnitude of the residuals. However...
Detecting Topological Errors with Pre-Estimation Filtering of Bad Data in Wide-Area Measurements
DEFF Research Database (Denmark)
Møller, Jakob Glarbo; Sørensen, Mads; Jóhannsson, Hjörtur
2017-01-01
It is expected that bad data and missing topology information will become an issue of growing concern when power system state estimators are to exploit the high measurement reporting rates from phasor measurement units. This paper suggests to design state estimators with enhanced resilience again...
Rosch, E.
1975-01-01
The task of time estimation, an activity occasionally performed by pilots during actual flight, was investigated with the objective of providing human factors investigators with an unobtrusive and minimally loading additional task that is sensitive to differences in flying conditions and flight instrumentation associated with the main task of piloting an aircraft simulator. Previous research indicated that the duration and consistency of time estimates is associated with the cognitive, perceptual, and motor loads imposed by concurrent simple tasks. The relationships between the length and variability of time estimates and concurrent task variables under a more complex situation involving simulated flight were clarified. The wrap-around effect with respect to baseline duration, a consequence of mode switching at intermediate levels of concurrent task distraction, should contribute substantially to estimate variability and have a complex effect on the shape of the resulting distribution of estimates.
Estimating Terrestrial Wood Biomass from Observed Concentrations of Atmospheric Carbon Dioxide
Schaefer, K. M.; Peters, W.; Carvalhais, N.; van der Werf, G.; Miller, J.
2008-01-01
We estimate terrestrial disequilibrium state and wood biomass from observed concentrations of atmospheric CO2 using the CarbonTracker system coupled to the SiBCASA biophysical model. Starting with a priori estimates of carbon flux from the land, ocean, and fossil fuels, CarbonTracker estimates net
High-frequency productivity estimates for a lake from free-water CO2 concentration measurements
Provenzale, Maria; Ojala, Anne; Heiskanen, Jouni; Erkkilä, Kukka-Maaria; Mammarella, Ivan; Hari, Pertti; Vesala, Timo
2018-04-01
Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon global budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique), which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP) is limited: the estimates are prone to errors and the NEP cannot be parameterised from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was first proposed in 2008, but was tested on a very short data set (3 days) under specific conditions (autumn turnover); despite showing promising results, this method has been neglected by the scientific community. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes) and on a much longer data set (40 days), and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes) and found a very good agreement (R2 ≥ 0.71) with the models. We also estimated the parameters of the productivity-irradiance (PI) curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing this method so that it becomes more widely used.
High-frequency productivity estimates for a lake from free-water CO2 concentration measurements
Directory of Open Access Journals (Sweden)
M. Provenzale
2018-04-01
Full Text Available Lakes are important actors in biogeochemical cycles and a powerful natural source of CO2. However, they are not yet fully integrated in carbon global budgets, and the carbon cycle in the water is still poorly understood. In freshwater ecosystems, productivity studies have usually been carried out with traditional methods (bottle incubations, 14C technique, which are imprecise and have a poor temporal resolution. Consequently, our ability to quantify and predict the net ecosystem productivity (NEP is limited: the estimates are prone to errors and the NEP cannot be parameterised from environmental variables. Here we expand the testing of a free-water method based on the direct measurement of the CO2 concentration in the water. The approach was first proposed in 2008, but was tested on a very short data set (3 days under specific conditions (autumn turnover; despite showing promising results, this method has been neglected by the scientific community. We tested the method under different conditions (summer stratification, typical summer conditions for boreal dark-water lakes and on a much longer data set (40 days, and quantitatively validated it comparing our data and productivity models. We were able to evaluate the NEP with a high temporal resolution (minutes and found a very good agreement (R2 ≥ 0.71 with the models. We also estimated the parameters of the productivity–irradiance (PI curves that allow the calculation of the NEP from irradiance and water temperature. Overall, our work shows that the approach is suitable for productivity studies under a wider range of conditions, and is an important step towards developing this method so that it becomes more widely used.
Directory of Open Access Journals (Sweden)
David P Piñero
2015-01-01
Full Text Available Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP. Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52-77 years and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (P IOLadj based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (n kadj for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELP adj . P IOLadj was compared to the real IOL power implanted (P IOLReal , calculated with the SRK-T formula and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between P IOLReal and P IOLadj when ELP adj was used (P = 0.10, with a range of agreement between calculations of 1.23 D. In contrast, P IOLReal was significantly higher when compared to P IOLadj without using ELP adj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.
Estimation of error on the cross-correlation, phase and time lag between evenly sampled light curves
Misra, R.; Bora, A.; Dewangan, G.
2018-04-01
Temporal analysis of radiation from Astrophysical sources like Active Galactic Nuclei, X-ray Binaries and Gamma-ray bursts provides information on the geometry and sizes of the emitting regions. Establishing that two light-curves in different energy bands are correlated, and measuring the phase and time-lag between them is an important and frequently used temporal diagnostic. Generally the estimates are done by dividing the light-curves into large number of adjacent intervals to find the variance or by using numerically expensive simulations. In this work we have presented alternative expressions for estimate of the errors on the cross-correlation, phase and time-lag between two shorter light-curves when they cannot be divided into segments. Thus the estimates presented here allow for analysis of light-curves with relatively small number of points, as well as to obtain information on the longest time-scales available. The expressions have been tested using 200 light curves simulated from both white and 1 / f stochastic processes with measurement errors. We also present an application to the XMM-Newton light-curves of the Active Galactic Nucleus, Akn 564. The example shows that the estimates presented here allow for analysis of light-curves with relatively small (∼ 1000) number of points.
Estimation of errors due to inhomogeneous distribution of radionuclides in lungs
International Nuclear Information System (INIS)
Pelled, O.; German, U.; Pollak, G.; Alfassi, Z.B.
2006-01-01
The uncertainty in the activity determination of uranium contamination due to real inhomogeneous distribution and assumption of homogenous distribution can reach more than one order of magnitude when using one detector in a set of 4 detectors covering most of the whole lungs. Using the information from several detectors may improve the accuracy, as obtained by summing the responses from the 3 or 4 detectors. However, even with this improvement, the errors are still very large, up to almost a factor of 10 when the analysis is based on the 92 keV energy peak and up to 7 for the 185 keV peak
Reliable methods for computer simulation error control and a posteriori estimates
Neittaanmäki, P
2004-01-01
Recent decades have seen a very rapid success in developing numerical methods based on explicit control over approximation errors. It may be said that nowadays a new direction is forming in numerical analysis, the main goal of which is to develop methods ofreliable computations. In general, a reliable numerical method must solve two basic problems: (a) generate a sequence of approximations that converges to a solution and (b) verify the accuracy of these approximations. A computer code for such a method must consist of two respective blocks: solver and checker.In this book, we are chie
Directory of Open Access Journals (Sweden)
Şuayip Yüzbaşı
2017-03-01
Full Text Available In this paper, we suggest a matrix method for obtaining the approximate solutions of the delay linear Fredholm integro-differential equations with constant coefficients using the shifted Legendre polynomials. The problem is considered with mixed conditions. Using the required matrix operations, the delay linear Fredholm integro-differential equation is transformed into a matrix equation. Additionally, error analysis for the method is presented using the residual function. Illustrative examples are given to demonstrate the efficiency of the method. The results obtained in this study are compared with the known results.
A FEM approximation of a two-phase obstacle problem and its a posteriori error estimate
Czech Academy of Sciences Publication Activity Database
Bozorgnia, F.; Valdman, Jan
2017-01-01
Roč. 73, č. 3 (2017), s. 419-432 ISSN 0898-1221 R&D Projects: GA ČR(CZ) GF16-34894L; GA MŠk(CZ) 7AMB16AT015 Institutional support: RVO:67985556 Keywords : A free boundary problem * A posteriori error analysis * Finite element method Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.531, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/valdman-0470507.pdf
Energy Technology Data Exchange (ETDEWEB)
Malygina, Hanna [Goethe Universitaet Frankfurt (Germany); KINR, Kyiv (Ukraine); GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Darmstadt (Germany); Friese, Volker; Zyzak, Maksym [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Darmstadt (Germany); Collaboration: CBM-Collaboration
2016-07-01
The Compressed Baryonic Matter experiment(CBM) at FAIR is designed to explore the QCD phase diagram in the region of high net-baryon densities. As the central detector component, the Silicon Tracking System (STS) is based on double-sided micro-strip sensors. To achieve realistic modelling, the response of the silicon strip sensors should be precisely included in the digitizer which simulates a complete chain of physical processes caused by charged particles traversing the detector, from charge creation in silicon to a digital output signal. The current implementation of the STS digitizer comprises non-uniform energy loss distributions (according to the Urban theory), thermal diffusion and charge redistribution over the read-out channels due to interstrip capacitances. Using the digitizer, one can test an influence of each physical processes on hit error separately. We have developed a new cluster position finding algorithm and a hit error estimation method for it. Estimated errors were verified by the width of pull distribution (expected to be about unity) and its shape.
International Nuclear Information System (INIS)
Fournier, D.; Le Tellier, R.; Suteau, C.; Herbin, R.
2011-01-01
The solution of the time-independent neutron transport equation in a deterministic way invariably consists in the successive discretization of the three variables: energy, angle and space. In the SNATCH solver used in this study, the energy and the angle are respectively discretized with a multigroup approach and the discrete ordinate method. A set of spatial coupled transport equations is obtained and solved using the Discontinuous Galerkin Finite Element Method (DGFEM). Within this method, the spatial domain is decomposed into elements and the solution is approximated by a hierarchical polynomial basis in each one. This approach is time and memory consuming when the mesh becomes fine or the basis order high. To improve the computational time and the memory footprint, adaptive algorithms are proposed. These algorithms are based on an error estimation in each cell. If the error is important in a given region, the mesh has to be refined (h−refinement) or the polynomial basis order increased (p−refinement). This paper is related to the choice between the two types of refinement. Two ways to estimate the error are compared on different benchmarks. Analyzing the differences, a hp−refinement method is proposed and tested. (author)
Some error estimates for the lumped mass finite element method for a parabolic problem
Chatzipantelidis, P.; Lazarov, R. D.; Thomé e, V.
2012-01-01
for the standard Galerkin method carry over to the lumped mass method whereas nonsmooth initial data estimates require special assumptions on the triangulation. We also discuss the application to time discretization by the backward Euler and Crank-Nicolson methods
Del Valle, José C; Gallardo-López, Antonio; Buide, Mª Luisa; Whittall, Justen B; Narbona, Eduardo
2018-03-01
Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio, anthocyanin content-chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the
Identifying grain-size dependent errors on global forest area estimates and carbon studies
Daolan Zheng; Linda S. Heath; Mark J. Ducey
2008-01-01
Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our...
DEFF Research Database (Denmark)
Jensen, Jesper; Tan, Zheng-Hua
2014-01-01
We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features for noise robust automatic speech recognition (ASR). The method is based on a minimum number of well-established statistical assumptions; no assumptions are made which are inconsistent with others....... The strength of the proposed method is that it allows MMSE estimation of mel-frequency cepstral coefficients (MFCC's), cepstral mean-subtracted MFCC's (CMS-MFCC's), velocity, and acceleration coefficients. Furthermore, the method is easily modified to take into account other compressive non-linearities than...... the logarithmic which is usually used for MFCC computation. The proposed method shows estimation performance which is identical to or better than state-of-the-art methods. It further shows comparable ASR performance, where the advantage of being able to use mel-frequency speech features based on a power non...
Ramírez-Pérez, M.; Twardowski, M.; Trees, C.; Piera, J.; McKee, D.
2018-01-01
A deconvolution approach is presented to use spectral light absorption and attenuation data to estimate the concentration of the major nonwater compounds in complex shelf sea waters. The inversion procedure requires knowledge of local material-specific inherent optical properties (SIOPs) which are determined from natural samples using a bio-optical model that differentiates between Case I and Case II waters and uses least squares linear regression analysis to provide optimal SIOP values. A synthetic data set is used to demonstrate that the approach is fundamentally consistent and to test the sensitivity to injection of controlled levels of artificial noise into the input data. Self-consistency of the approach is further demonstrated by application to field data collected in the Ligurian Sea, with chlorophyll (Chl), the nonbiogenic component of total suspended solids (TSSnd), and colored dissolved organic material (CDOM) retrieved with RMSE of 0.61 mg m-3, 0.35 g m-3, and 0.02 m-1, respectively. The utility of the approach is finally demonstrated by application to depth profiles of in situ absorption and attenuation data resulting in profiles of optically significant constituents with associated error bar estimates. The advantages of this procedure lie in the simple input requirements, the avoidance of error amplification, full exploitation of the available spectral information from both absorption and attenuation channels, and the reasonably successful retrieval of constituent concentrations in an optically complex shelf sea.
Robust experiment design for estimating myocardial β adrenergic receptor concentration using PET
International Nuclear Information System (INIS)
Salinas, Cristian; Muzic, Raymond F. Jr.; Ernsberger, Paul; Saidel, Gerald M.
2007-01-01
Myocardial β adrenergic receptor (β-AR) concentration can substantially decrease in congestive heart failure and significantly increase in chronic volume overload, such as in severe aortic valve regurgitation. Positron emission tomography (PET) with an appropriate ligand-receptor model can be used for noninvasive estimation of myocardial β-AR concentration in vivo. An optimal design of the experiment protocol, however, is needed for sufficiently precise estimates of β-AR concentration in a heterogeneous population. Standard methods of optimal design do not account for a heterogeneous population with a wide range of β-AR concentrations and other physiological parameters and consequently are inadequate. To address this, we have developed a methodology to design a robust two-injection protocol that provides reliable estimates of myocardial β-AR concentration in normal and pathologic states. A two-injection protocol of the high affinity β-AR antagonist [ 18 F]-(S)-fluorocarazolol was designed based on a computer-generated (or synthetic) population incorporating a wide range of β-AR concentrations. Timing and dosage of the ligand injections were optimally designed with minimax criterion to provide the least bad β-AR estimates for the worst case in the synthetic population. This robust experiment design for PET was applied to experiments with pigs before and after β-AR upregulation by chemical sympathectomy. Estimates of β-AR concentration were found by minimizing the difference between the model-predicted and experimental PET data. With this robust protocol, estimates of β-AR concentration showed high precision in both normal and pathologic states. The increase in β-AR concentration after sympathectomy predicted noninvasively with PET is consistent with the increase shown by in vitro assays in pig myocardium. A robust experiment protocol was designed for PET that yields reliable estimates of β-AR concentration in a population with normal and pathologic
Directory of Open Access Journals (Sweden)
Boulesteix Anne-Laure
2009-12-01
Full Text Available Abstract Background In biometric practice, researchers often apply a large number of different methods in a "trial-and-error" strategy to get as much as possible out of their data and, due to publication pressure or pressure from the consulting customer, present only the most favorable results. This strategy may induce a substantial optimistic bias in prediction error estimation, which is quantitatively assessed in the present manuscript. The focus of our work is on class prediction based on high-dimensional data (e.g. microarray data, since such analyses are particularly exposed to this kind of bias. Methods In our study we consider a total of 124 variants of classifiers (possibly including variable selection or tuning steps within a cross-validation evaluation scheme. The classifiers are applied to original and modified real microarray data sets, some of which are obtained by randomly permuting the class labels to mimic non-informative predictors while preserving their correlation structure. Results We assess the minimal misclassification rate over the different variants of classifiers in order to quantify the bias arising when the optimal classifier is selected a posteriori in a data-driven manner. The bias resulting from the parameter tuning (including gene selection parameters as a special case and the bias resulting from the choice of the classification method are examined both separately and jointly. Conclusions The median minimal error rate over the investigated classifiers was as low as 31% and 41% based on permuted uninformative predictors from studies on colon cancer and prostate cancer, respectively. We conclude that the strategy to present only the optimal result is not acceptable because it yields a substantial bias in error rate estimation, and suggest alternative approaches for properly reporting classification accuracy.
International Nuclear Information System (INIS)
Telegadas, K.
1979-01-01
A simple technique is presented for estimating maximum credible gross beta air concentrations from nuclear detonations in the atmosphere, based on aircraft sampling of radioactivity following each Chinese nuclear test from 1964 to 1976. The calculated concentration is a function of the total yield and fission yield, initial vertical radioactivity distribution, time after detonation, and rate of horizontal spread of the debris with time. calculated maximum credible concentrations are compared with the highest concentrations measured during aircraft sampling. The technique provides a reasonable estimate of maximum air concentrations from 1 to 10 days after a detonation. An estimate of the whole-body external gamma dose rate corresponding to the maximum credible gross beta concentration is also given. (author)
Phase correction and error estimation in InSAR time series analysis
Zhang, Y.; Fattahi, H.; Amelung, F.
2017-12-01
During the last decade several InSAR time series approaches have been developed in response to the non-idea acquisition strategy of SAR satellites, such as large spatial and temporal baseline with non-regular acquisitions. The small baseline tubes and regular acquisitions of new SAR satellites such as Sentinel-1 allows us to form fully connected networks of interferograms and simplifies the time series analysis into a weighted least square inversion of an over-determined system. Such robust inversion allows us to focus more on the understanding of different components in InSAR time-series and its uncertainties. We present an open-source python-based package for InSAR time series analysis, called PySAR (https://yunjunz.github.io/PySAR/), with unique functionalities for obtaining unbiased ground displacement time-series, geometrical and atmospheric correction of InSAR data and quantifying the InSAR uncertainty. Our implemented strategy contains several features including: 1) improved spatial coverage using coherence-based network of interferograms, 2) unwrapping error correction using phase closure or bridging, 3) tropospheric delay correction using weather models and empirical approaches, 4) DEM error correction, 5) optimal selection of reference date and automatic outlier detection, 6) InSAR uncertainty due to the residual tropospheric delay, decorrelation and residual DEM error, and 7) variance-covariance matrix of final products for geodetic inversion. We demonstrate the performance using SAR datasets acquired by Cosmo-Skymed and TerraSAR-X, Sentinel-1 and ALOS/ALOS-2, with application on the highly non-linear volcanic deformation in Japan and Ecuador (figure 1). Our result shows precursory deformation before the 2015 eruptions of Cotopaxi volcano, with a maximum uplift of 3.4 cm on the western flank (fig. 1b), with a standard deviation of 0.9 cm (fig. 1a), supporting the finding by Morales-Rivera et al. (2017, GRL); and a post-eruptive subsidence on the same
Methods for estimating on-site ambient air concentrations at disposal sites
International Nuclear Information System (INIS)
Hwang, S.T.
1987-01-01
Currently, Gaussian type dispersion modeling and point source approximation are combined to estimate the ambient air concentrations of pollutants dispersed downwind of an areawide emission source, using the approach of virtual point source approximation. This Gaussian dispersion modeling becomes less accurate as the receptor comes closer to the source, and becomes inapplicable for the estimation of on-site ambient air concentrations at disposal sites. Partial differential equations are solved with appropriate boundary conditions for use in estimating the on-site concentrations in the ambient air impacted by emissions from an area source such as land disposal sites. Two variations of solution techniques are presented, and their predictions are compared
Kukush, Alexander
2011-01-16
With a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R)(-1), R = λ(0) + EAR D, where λ(0) is the baseline incidence rate and EAR is the excess absolute risk per gray. The calculated thyroid dose of a person i is expressed as Dimes=fiQi(mes)/Mi(mes). Here, Qi(mes) is the measured content of radioiodine in the thyroid gland of person i at time t(mes), Mi(mes) is the estimate of the thyroid mass, and f(i) is the normalizing multiplier. The Q(i) and M(i) are measured with multiplicative errors Vi(Q) and ViM, so that Qi(mes)=Qi(tr)Vi(Q) (this is classical measurement error model) and Mi(tr)=Mi(mes)Vi(M) (this is Berkson measurement error model). Here, Qi(tr) is the true content of radioactivity in the thyroid gland, and Mi(tr) is the true value of the thyroid mass. The error in f(i) is much smaller than the errors in ( Qi(mes), Mi(mes)) and ignored in the analysis. By means of Parametric Full Maximum Likelihood and Regression Calibration (under the assumption that the data set of true doses has lognormal distribution), Nonparametric Full Maximum Likelihood, Nonparametric Regression Calibration, and by properly tuned SIMEX method we study the influence of measurement errors in thyroid dose on the estimates of λ(0) and EAR. The simulation study is presented based on a real sample from the epidemiological studies. The doses were reconstructed in the framework of the Ukrainian-American project on the investigation of Post-Chernobyl thyroid cancers in Ukraine, and the underlying subpolulation was artificially enlarged in order to increase the statistical power. The true risk parameters were given by the values to earlier epidemiological studies, and then the binary response was simulated according to the dose-response model.
Kukush, Alexander; Shklyar, Sergiy; Masiuk, Sergii; Likhtarov, Illya; Kovgan, Lina; Carroll, Raymond J; Bouville, Andre
2011-02-16
With a binary response Y, the dose-response model under consideration is logistic in flavor with pr(Y=1 | D) = R (1+R)(-1), R = λ(0) + EAR D, where λ(0) is the baseline incidence rate and EAR is the excess absolute risk per gray. The calculated thyroid dose of a person i is expressed as Dimes=fiQi(mes)/Mi(mes). Here, Qi(mes) is the measured content of radioiodine in the thyroid gland of person i at time t(mes), Mi(mes) is the estimate of the thyroid mass, and f(i) is the normalizing multiplier. The Q(i) and M(i) are measured with multiplicative errors Vi(Q) and ViM, so that Qi(mes)=Qi(tr)Vi(Q) (this is classical measurement error model) and Mi(tr)=Mi(mes)Vi(M) (this is Berkson measurement error model). Here, Qi(tr) is the true content of radioactivity in the thyroid gland, and Mi(tr) is the true value of the thyroid mass. The error in f(i) is much smaller than the errors in ( Qi(mes), Mi(mes)) and ignored in the analysis. By means of Parametric Full Maximum Likelihood and Regression Calibration (under the assumption that the data set of true doses has lognormal distribution), Nonparametric Full Maximum Likelihood, Nonparametric Regression Calibration, and by properly tuned SIMEX method we study the influence of measurement errors in thyroid dose on the estimates of λ(0) and EAR. The simulation study is presented based on a real sample from the epidemiological studies. The doses were reconstructed in the framework of the Ukrainian-American project on the investigation of Post-Chernobyl thyroid cancers in Ukraine, and the underlying subpolulation was artificially enlarged in order to increase the statistical power. The true risk parameters were given by the values to earlier epidemiological studies, and then the binary response was simulated according to the dose-response model.
Evolutionary enhancement of the SLIM-MAUD method of estimating human error rates
International Nuclear Information System (INIS)
Zamanali, J.H.; Hubbard, F.R.; Mosleh, A.; Waller, M.A.
1992-01-01
The methodology described in this paper assigns plant-specific dynamic human error rates (HERs) for individual plant examinations based on procedural difficulty, on configuration features, and on the time available to perform the action. This methodology is an evolutionary improvement of the success likelihood index methodology (SLIM-MAUD) for use in systemic scenarios. It is based on the assumption that the HER in a particular situation depends of the combined effects of a comprehensive set of performance-shaping factors (PSFs) that influence the operator's ability to perform the action successfully. The PSFs relate the details of the systemic scenario in which the action must be performed according to the operator's psychological and cognitive condition
Stochastic approach to error estimation for image-guided robotic systems.
Haidegger, Tamas; Gyõri, Sándor; Benyo, Balazs; Benyó, Zoltáán
2010-01-01
Image-guided surgical systems and surgical robots are primarily developed to provide patient safety through increased precision and minimal invasiveness. Even more, robotic devices should allow for refined treatments that are not possible by other means. It is crucial to determine the accuracy of a system, to define the expected overall task execution error. A major step toward this aim is to quantitatively analyze the effect of registration and tracking-series of multiplication of erroneous homogeneous transformations. First, the currently used models and algorithms are introduced along with their limitations, and a new, probability distribution based method is described. The new approach has several advantages, as it was demonstrated in our simulations. Primarily, it determines the full 6 degree of freedom accuracy of the point of interest, allowing for the more accurate use of advanced application-oriented concepts, such as Virtual Fixtures. On the other hand, it becomes feasible to consider different surgical scenarios with varying weighting factors.
Directory of Open Access Journals (Sweden)
Ting Zhao
2015-01-01
Full Text Available Accurate and reliable state of charge (SOC estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1 Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2 The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3 The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.
Salmerón, Diego; Cano, Juan A; Chirlaque, María D
2015-08-30
In cohort studies, binary outcomes are very often analyzed by logistic regression. However, it is well known that when the goal is to estimate a risk ratio, the logistic regression is inappropriate if the outcome is common. In these cases, a log-binomial regression model is preferable. On the other hand, the estimation of the regression coefficients of the log-binomial model is difficult owing to the constraints that must be imposed on these coefficients. Bayesian methods allow a straightforward approach for log-binomial regression models and produce smaller mean squared errors in the estimation of risk ratios than the frequentist methods, and the posterior inferences can be obtained using the software WinBUGS. However, Markov chain Monte Carlo methods implemented in WinBUGS can lead to large Monte Carlo errors in the approximations to the posterior inferences because they produce correlated simulations, and the accuracy of the approximations are inversely related to this correlation. To reduce correlation and to improve accuracy, we propose a reparameterization based on a Poisson model and a sampling algorithm coded in R. Copyright © 2015 John Wiley & Sons, Ltd.
Data driven estimation of imputation error-a strategy for imputation with a reject option
DEFF Research Database (Denmark)
Bak, Nikolaj; Hansen, Lars Kai
2016-01-01
Missing data is a common problem in many research fields and is a challenge that always needs careful considerations. One approach is to impute the missing values, i.e., replace missing values with estimates. When imputation is applied, it is typically applied to all records with missing values i...
Development and estimation of a semi-compensatory model with flexible error structure
DEFF Research Database (Denmark)
Kaplan, Sigal; Shiftan, Yoram; Bekhor, Shlomo
2009-01-01
, and utility-based choice accommodating alternatively nested substitution patterns across the alternatives and random taste variation across the population. The proposed model is applied to off-campus rental apartment choice of students. Results show (i) the estimated model for a universal realm of 200...
International Nuclear Information System (INIS)
Jang, Hong; Lee, Jay H.; Braatz, Richard D.
2016-01-01
This paper proposes a maximum likelihood estimation (MLE) method for estimating time varying local concentration of the target molecule proximate to the sensor from the time profile of monomolecular adsorption and desorption on the surface of the sensor at nanoscale. Recently, several carbon nanotube sensors have been developed that can selectively detect target molecules at a trace concentration level. These sensors use light intensity changes mediated by adsorption or desorption phenomena on their surfaces. The molecular events occurring at trace concentration levels are inherently stochastic, posing a challenge for optimal estimation. The stochastic behavior is modeled by the chemical master equation (CME), composed of a set of ordinary differential equations describing the time evolution of probabilities for the possible adsorption states. Given the significant stochastic nature of the underlying phenomena, rigorous stochastic estimation based on the CME should lead to an improved accuracy over than deterministic estimation formulated based on the continuum model. Motivated by this expectation, we formulate the MLE based on an analytical solution of the relevant CME, both for the constant and the time-varying local concentrations, with the objective of estimating the analyte concentration field in real time from the adsorption readings of the sensor array. The performances of the MLE and the deterministic least squares are compared using data generated by kinetic Monte Carlo (KMC) simulations of the stochastic process. Some future challenges are described for estimating and controlling the concentration field in a distributed domain using the sensor technology.
Estimating cancer risk from outdoor concentrations of hazardous air pollutants in 1990
Energy Technology Data Exchange (ETDEWEB)
Woodruff, T.J.; Caldwell, J.; Cogliano, V.J.; Axelrad, D.A.
2000-03-01
A public health concern regarding hazardous air pollutants (HAPs) is their potential to cause cancer. It has been difficult to assess potential cancer risks from HAPs, due primarily to lack of ambient concentration data for the general population. The Environmental Protection Agency's Cumulative Exposure Project modeled 1990 outdoor concentrations of HAPs across the United States, which were combined with inhalation unit risk estimates to estimate the potential increase in excess cancer risk for individual carcinogenic HAPs. These were summed3d to provide an estimate of cancer risk from multiple HAPs. The analysis estimates a median excess cancer risk of 18 lifetime cancer cases per 100,000 people for all HAP concentrations. About 75% of estimated cancer risk was attributable to exposure to polycyclic organic matter, 1,3-butadiene, formaldehyde, benzene, and chromium. Consideration of some specific uncertainties, including underestimation of ambient concentrations, combining upper 95% confidence bound potency estimates, and changes to potency estimates, found that cancer risk may be underestimated by 15% or overestimated by 40--50%. Other unanalyzed uncertainties could make these under- or overestimates larger. This analysis used 1990 estimates of concentrations and can be used to track progress toward reducing cancer risk to the general population.
Sample sizes to control error estimates in determining soil bulk density in California forest soils
Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber
2016-01-01
Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...
Hori, Hajime; Ishidao, Toru; Ishimatsu, Sumiyo
2010-12-01
We measured vapor concentrations continuously evaporated from two-component organic solvents in a reservoir and proposed a method to estimate and predict the evaporation rate or generated vapor concentrations. Two kinds of organic solvents were put into a small reservoir made of glass (3 cm in diameter and 3 cm high) that was installed in a cylindrical glass vessel (10 cm in diameter and 15 cm high). Air was introduced into the glass vessel at a flow rate of 150 ml/min, and the generated vapor concentrations were intermittently monitored for up to 5 hours with a gas chromatograph equipped with a flame ionization detector. The solvent systems tested in this study were the methanoltoluene system and the ethyl acetate-toluene system. The vapor concentrations of the more volatile component, that is, methanol in the methanol-toluene system and ethyl acetate in the ethyl acetate-toluene system, were high at first, and then decreased with time. On the other hand, the concentrations of the less volatile component were low at first, and then increased with time. A model for estimating multicomponent organic vapor concentrations was developed, based on a theory of vapor-liquid equilibria and a theory of the mass transfer rate, and estimated values were compared with experimental ones. The estimated vapor concentrations were in relatively good agreement with the experimental ones. The results suggest that changes in concentrations of two-component organic vapors continuously evaporating from a liquid reservoir can be estimated by the proposed model.
International Nuclear Information System (INIS)
Stripling, H.F.; Anitescu, M.; Adams, M.L.
2013-01-01
Highlights: ► We develop an abstract framework for computing the adjoint to the neutron/nuclide burnup equations posed as a system of differential algebraic equations. ► We validate use of the adjoint for computing both sensitivity to uncertain inputs and for estimating global time discretization error. ► Flexibility of the framework is leveraged to add heat transfer physics and compute its adjoint without a reformulation of the adjoint system. ► Such flexibility is crucial for high performance computing applications. -- Abstract: We develop a general framework for computing the adjoint variable to nuclear engineering problems governed by a set of differential–algebraic equations (DAEs). The nuclear engineering community has a rich history of developing and applying adjoints for sensitivity calculations; many such formulations, however, are specific to a certain set of equations, variables, or solution techniques. Any change or addition to the physics model would require a reformulation of the adjoint problem and substantial difficulties in its software implementation. In this work we propose an abstract framework that allows for the modification and expansion of the governing equations, leverages the existing theory of adjoint formulation for DAEs, and results in adjoint equations that can be used to efficiently compute sensitivities for parametric uncertainty quantification. Moreover, as we justify theoretically and demonstrate numerically, the same framework can be used to estimate global time discretization error. We first motivate the framework and show that the coupled Bateman and transport equations, which govern the time-dependent neutronic behavior of a nuclear reactor, may be formulated as a DAE system with a power constraint. We then use a variational approach to develop the parameter-dependent adjoint framework and apply existing theory to give formulations for sensitivity and global time discretization error estimates using the adjoint
International Nuclear Information System (INIS)
Borak, T.B.; Stinchcomb, T.G.
1982-01-01
Neutron dose equivalent is obtained from quality factors which are defined in terms of LET. It is possible to estimate the dose averaged quality factor, antiQ, directly from distributions in lineal energy, y, that are measured in tissue-equivalent proportional counters. This eliminates a mathematical transformation of the absorbed dose from D(y) to D(L). We evaluate the inherent error in computing Q from D(y) rather than D(L) for neutron spectra below 4 MeV. The effects of neutron energy and simulated tissue diameters within a gas cavity are examined in detail. (author)
Point-of-care estimation of haemoglobin concentration in all age ...
African Journals Online (AJOL)
Point-of-care estimation of haemoglobin concentration in all age groups in clinical ... and the results were compared using standard scatter and difference plots. ... Hb measurements with a smaller sample volume, improved turnaround time, ...
Tier I Rice Model - Version 1.0 - Guidance for Estimating Pesticide Concentrations in Rice Paddies
Describes a Tier I Rice Model (Version 1.0) for estimating surface water exposure from the use of pesticides in rice paddies. The concentration calculated can be used for aquatic ecological risk and drinking water exposure assessments.
Soft error rate estimations of the Kintex-7 FPGA within the ATLAS Liquid Argon (LAr) Calorimeter
International Nuclear Information System (INIS)
Wirthlin, M J; Harding, A; Takai, H
2014-01-01
This paper summarizes the radiation testing performed on the Xilinx Kintex-7 FPGA in an effort to determine if the Kintex-7 can be used within the ATLAS Liquid Argon (LAr) Calorimeter. The Kintex-7 device was tested with wide-spectrum neutrons, protons, heavy-ions, and mixed high-energy hadron environments. The results of these tests were used to estimate the configuration ram and block ram upset rate within the ATLAS LAr. These estimations suggest that the configuration memory will upset at a rate of 1.1 × 10 −10 upsets/bit/s and the bram memory will upset at a rate of 9.06 × 10 −11 upsets/bit/s. For the Kintex 7K325 device, this translates to 6.85 × 10 −3 upsets/device/s for configuration memory and 1.49 × 10 −3 for block memory
International Nuclear Information System (INIS)
Finegood, D.T.; Bergman, R.N.; Vranic, M.
1988-01-01
We previously demonstrated that conventional tracer methods applied to euglycemic-hyperinsulinemic glucose clamps result in substantially negative estimates for the rate of endogenous glucose production, particularly during the first half of 180-min clamps. We also showed that addition of tracer to the exogenous glucose infusate resulted in nonnegative endogenous glucose production (Ra) estimates. In this study, we investigated the underlying cause of negative estimates of Ra from conventional clamp/tracer methods and the reason for the difference in estimates when tracer is added to the exogenous glucose infusate. We performed euglycemic-hyperinsulinemic (300-microU/ml) clamps in normal dogs without (cold GINF protocol, n = 6) or with (hot GINF protocol, n = 6) tracer (D-[3-3H]glucose) added to the exogenous glucose infusate. In the hot GINF protocol, sufficient tracer was added to the exogenous glucose infusate such that arterial plasma specific activity (SAa) did not change from basal through the clamp period (P greater than .05). In the cold GINF studies, plasma SAa fell 81 +/- 2% from the basal level by the 3rd h of clamping. We observed a significant, transient, positive venous-arterial difference in specific activity (SAv-SAa difference) during the cold GINF studies. The SAv-SAa difference reached a peak of 27 +/- 6% at 30 min and diminished to a plateau of 7 +/- 1% between 70 and 180 min. We also observed a positive but constant SAv-SAa difference (4.6 +/- 0.2% between 10 and 180 min) during the hot GINF studies
Errors in estimation of the input signal for integrate-and-fire neuronal models
Czech Academy of Sciences Publication Activity Database
Bibbona, E.; Lánský, Petr; Sacerdote, L.; Sirovich, R.
2008-01-01
Roč. 78, č. 1 (2008), s. 1-10 ISSN 1539-3755 R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401 Grant - others:EC(XE) MIUR PRIN 2005 Institutional research plan: CEZ:AV0Z50110509 Keywords : parameter estimation * stochastic neuronal model Subject RIV: BO - Biophysics Impact factor: 2.508, year: 2008 http://link.aps.org/abstract/PRE/v78/e011918
Huan, Xun; Safta, Cosmin; Sargsyan, Khachik; Geraci, Gianluca; Eldred, Michael S.; Vane, Zachary P.; Lacaze, Guilhem; Oefelein, Joseph C.; Najm, Habib N.
2018-03-01
The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the systems stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. These methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.