WorldWideScience

Sample records for local parametric estimation

  1. PHAZE, Parametric Hazard Function Estimation

    International Nuclear Information System (INIS)

    2002-01-01

    1 - Description of program or function: Phaze performs statistical inference calculations on a hazard function (also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking of the model assumptions. 2 - Methods: PHAZE assumes that the failures of a component follow a time-dependent (or non-homogenous) Poisson process and that the failure counts in non-overlapping time intervals are independent. Implicit in the independence property is the assumption that the component is restored to service immediately after any failure, with negligible repair time. The failures of one component are assumed to be independent of those of another component; a proportional hazards model is used. Data for a component are called time censored if the component is observed for a fixed time-period, or plant records covering a fixed time-period are examined, and the failure times are recorded. The number of these failures is random. Data are called failure censored if the component is kept in service until a predetermined number of failures has occurred, at which time the component is removed from service. In this case, the number of failures is fixed, but the end of the observation period equals the final failure time and is random. A typical PHAZE session consists of reading failure data from a file prepared previously, selecting one of the three models, and performing data analysis (i.e., performing the usual statistical inference about the parameters of the model, with special emphasis on the parameter(s) that determine whether the hazard function is increasing). The final goals of the inference are a point estimate

  2. Variance in parametric images: direct estimation from parametric projections

    International Nuclear Information System (INIS)

    Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

    2000-01-01

    Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

  3. Non-Parametric Estimation of Correlation Functions

    DEFF Research Database (Denmark)

    Brincker, Rune; Rytter, Anders; Krenk, Steen

    In this paper three methods of non-parametric correlation function estimation are reviewed and evaluated: the direct method, estimation by the Fast Fourier Transform and finally estimation by the Random Decrement technique. The basic ideas of the techniques are reviewed, sources of bias are point...

  4. Semi-parametric estimation for ARCH models

    Directory of Open Access Journals (Sweden)

    Raed Alzghool

    2018-03-01

    Full Text Available In this paper, we conduct semi-parametric estimation for autoregressive conditional heteroscedasticity (ARCH model with Quasi likelihood (QL and Asymptotic Quasi-likelihood (AQL estimation methods. The QL approach relaxes the distributional assumptions of ARCH processes. The AQL technique is obtained from the QL method when the process conditional variance is unknown. We present an application of the methods to a daily exchange rate series. Keywords: ARCH model, Quasi likelihood (QL, Asymptotic Quasi-likelihood (AQL, Martingale difference, Kernel estimator

  5. On Algebraic Approach for MSD Parametric Estimation

    OpenAIRE

    Oueslati , Marouene; Thiery , Stéphane; Gibaru , Olivier; Béarée , Richard; Moraru , George

    2011-01-01

    This article address the identification problem of the natural frequency and the damping ratio of a second order continuous system where the input is a sinusoidal signal. An algebra based approach for identifying parameters of a Mass Spring Damper (MSD) system is proposed and compared to the Kalman-Bucy filter. The proposed estimator uses the algebraic parametric method in the frequency domain yielding exact formula, when placed in the time domain to identify the unknown parameters. We focus ...

  6. Parametric cost estimation for space science missions

    Science.gov (United States)

    Lillie, Charles F.; Thompson, Bruce E.

    2008-07-01

    Cost estimation for space science missions is critically important in budgeting for successful missions. The process requires consideration of a number of parameters, where many of the values are only known to a limited accuracy. The results of cost estimation are not perfect, but must be calculated and compared with the estimates that the government uses for budgeting purposes. Uncertainties in the input parameters result from evolving requirements for missions that are typically the "first of a kind" with "state-of-the-art" instruments and new spacecraft and payload technologies that make it difficult to base estimates on the cost histories of previous missions. Even the cost of heritage avionics is uncertain due to parts obsolescence and the resulting redesign work. Through experience and use of industry best practices developed in participation with the Aerospace Industries Association (AIA), Northrop Grumman has developed a parametric modeling approach that can provide a reasonably accurate cost range and most probable cost for future space missions. During the initial mission phases, the approach uses mass- and powerbased cost estimating relationships (CER)'s developed with historical data from previous missions. In later mission phases, when the mission requirements are better defined, these estimates are updated with vendor's bids and "bottoms- up", "grass-roots" material and labor cost estimates based on detailed schedules and assigned tasks. In this paper we describe how we develop our CER's for parametric cost estimation and how they can be applied to estimate the costs for future space science missions like those presented to the Astronomy & Astrophysics Decadal Survey Study Committees.

  7. Parametric resonance of intrinsic localized modes in coupled cantilever arrays

    Energy Technology Data Exchange (ETDEWEB)

    Kimura, Masayuki, E-mail: kimura.masayuki.8c@kyoto-u.ac.jp [Department of Electrical Engineering, Kyoto University, Katsura, Nishikyo-ku, Kyoto 615-8510 (Japan); Matsushita, Yasuo [Advanced Mathematical Institute, Osaka City University, 3-3-138 Sughimoto, Sumiyoshi-ku, Osaka 558-8585 (Japan); Hikihara, Takashi [Department of Electrical Engineering, Kyoto University, Katsura, Nishikyo-ku, Kyoto 615-8510 (Japan)

    2016-08-19

    In this study, the parametric resonances of pinned intrinsic localized modes (ILMs) were investigated by computing the unstable regions in parameter space consisting of parametric excitation amplitude and frequency. In the unstable regions, the pinned ILMs were observed to lose stability and begin to fluctuate. A nonlinear Klein–Gordon, Fermi–Pasta–Ulam-like, and mixed lattices were investigated. The pinned ILMs, particularly in the mixed lattice, were destabilized by parametric resonances, which were determined by comparing the shapes of the unstable regions with those in the Mathieu differential equation. In addition, traveling ILMs could be generated by parametric excitation. - Highlights: • Destabilization of intrinsic localized modes (ILMs) by parametric excitation is investigated for FPU, NKG, and mixed lattices. • Frequency and amplitude of parametric excitation is determined based on characteristic multipliers of ILMs. • Unstable regions for the mixed lattice case show very similar shape to those of the Mathieu equation. • ILMs become unstable by causing parametric resonance.

  8. Parametric resonance of intrinsic localized modes in coupled cantilever arrays

    International Nuclear Information System (INIS)

    Kimura, Masayuki; Matsushita, Yasuo; Hikihara, Takashi

    2016-01-01

    In this study, the parametric resonances of pinned intrinsic localized modes (ILMs) were investigated by computing the unstable regions in parameter space consisting of parametric excitation amplitude and frequency. In the unstable regions, the pinned ILMs were observed to lose stability and begin to fluctuate. A nonlinear Klein–Gordon, Fermi–Pasta–Ulam-like, and mixed lattices were investigated. The pinned ILMs, particularly in the mixed lattice, were destabilized by parametric resonances, which were determined by comparing the shapes of the unstable regions with those in the Mathieu differential equation. In addition, traveling ILMs could be generated by parametric excitation. - Highlights: • Destabilization of intrinsic localized modes (ILMs) by parametric excitation is investigated for FPU, NKG, and mixed lattices. • Frequency and amplitude of parametric excitation is determined based on characteristic multipliers of ILMs. • Unstable regions for the mixed lattice case show very similar shape to those of the Mathieu equation. • ILMs become unstable by causing parametric resonance.

  9. Sensitivity of Technical Efficiency Estimates to Estimation Methods: An Empirical Comparison of Parametric and Non-Parametric Approaches

    OpenAIRE

    de-Graft Acquah, Henry

    2014-01-01

    This paper highlights the sensitivity of technical efficiency estimates to estimation approaches using empirical data. Firm specific technical efficiency and mean technical efficiency are estimated using the non parametric Data Envelope Analysis (DEA) and the parametric Corrected Ordinary Least Squares (COLS) and Stochastic Frontier Analysis (SFA) approaches. Mean technical efficiency is found to be sensitive to the choice of estimation technique. Analysis of variance and Tukey’s test sugge...

  10. Parametric Cost Estimates for an International Competitive Edge

    International Nuclear Information System (INIS)

    Murphy, L.T.; Hickey, M.

    2006-01-01

    This paper summarizes the progress to date by CH2M HILL and the UKAEA in development of a parametric modelling capability for estimating the costs of large nuclear decommissioning projects in the United Kingdom (UK) and Europe. The ability to successfully apply parametric cost estimating techniques will be a key factor to commercial success in the UK and European multi-billion dollar waste management, decommissioning and environmental restoration markets. The most useful parametric models will be those that incorporate individual components representing major elements of work: reactor decommissioning, fuel cycle facility decommissioning, waste management facility decommissioning and environmental restoration. Models must be sufficiently robust to estimate indirect costs and overheads, permit pricing analysis and adjustment, and accommodate the intricacies of international monetary exchange, currency fluctuations and contingency. The development of a parametric cost estimating capability is also a key component in building a forward estimating strategy. The forward estimating strategy will enable the preparation of accurate and cost-effective out-year estimates, even when work scope is poorly defined or as yet indeterminate. Preparation of cost estimates for work outside the organizations current sites, for which detailed measurement is not possible and historical cost data does not exist, will also be facilitated. (authors)

  11. Kernel bandwidth estimation for non-parametric density estimation: a comparative study

    CSIR Research Space (South Africa)

    Van der Walt, CM

    2013-12-01

    Full Text Available We investigate the performance of conventional bandwidth estimators for non-parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of these estimators in high...

  12. Estimation of Parametric Fault in Closed-loop Systems

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2015-01-01

    The aim of this paper is to present a method for estimation of parametric faults in closed-loop systems. The key technology applied in this paper is coprime factorization of both the dynamic system as well as the feedback controller. Using the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization...

  13. Parametric Bayesian Estimation of Differential Entropy and Relative Entropy

    OpenAIRE

    Gupta; Srivastava

    2010-01-01

    Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian est...

  14. Parametric estimation for reinforced concrete relief shelter for Aceh cases

    Science.gov (United States)

    Atthaillah; Saputra, Eri; Iqbal, Muhammad

    2018-05-01

    This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

  15. Parametric Bayesian Estimation of Differential Entropy and Relative Entropy

    Directory of Open Access Journals (Sweden)

    Maya Gupta

    2010-04-01

    Full Text Available Given iid samples drawn from a distribution with known parametric form, we propose the minimization of expected Bregman divergence to form Bayesian estimates of differential entropy and relative entropy, and derive such estimators for the uniform, Gaussian, Wishart, and inverse Wishart distributions. Additionally, formulas are given for a log gamma Bregman divergence and the differential entropy and relative entropy for the Wishart and inverse Wishart. The results, as always with Bayesian estimates, depend on the accuracy of the prior parameters, but example simulations show that the performance can be substantially improved compared to maximum likelihood or state-of-the-art nonparametric estimators.

  16. Non-parametric estimation of the individual's utility map

    OpenAIRE

    Noguchi, Takao; Sanborn, Adam N.; Stewart, Neil

    2013-01-01

    Models of risky choice have attracted much attention in behavioural economics. Previous research has repeatedly demonstrated that individuals' choices are not well explained by expected utility theory, and a number of alternative models have been examined using carefully selected sets of choice alternatives. The model performance however, can depend on which choice alternatives are being tested. Here we develop a non-parametric method for estimating the utility map over the wide range of choi...

  17. Onset patterns in a simple model of localized parametric forcing.

    Science.gov (United States)

    Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J

    2013-10-01

    We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.

  18. A novel SURE-based criterion for parametric PSF estimation.

    Science.gov (United States)

    Xue, Feng; Blu, Thierry

    2015-02-01

    We propose an unbiased estimate of a filtered version of the mean squared error--the blur-SURE (Stein's unbiased risk estimate)--as a novel criterion for estimating an unknown point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated blur kernel, we then perform nonblind deconvolution using our recently developed algorithm. The SURE-based framework is exemplified with a number of parametric PSF, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel. The experimental results demonstrate that minimizing the blur-SURE yields highly accurate estimates of the PSF parameters, which also result in a restoration quality that is very similar to the one obtained with the exact PSF, when plugged into our recent multi-Wiener SURE-LET deconvolution algorithm. The highly competitive results obtained outline the great potential of developing more powerful blind deconvolution algorithms based on SURE-like estimates.

  19. A non-parametric framework for estimating threshold limit values

    Directory of Open Access Journals (Sweden)

    Ulm Kurt

    2005-11-01

    Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

  20. Parametric estimation in the wave buoy analogy - an elaborated approach based on energy considerations

    DEFF Research Database (Denmark)

    Montazeri, Najmeh; Nielsen, Ulrik Dam

    2014-01-01

    the ship’s wave-induced responses based on different statistical inferences including parametric and non-parametric approaches. This paper considers a concept to improve the estimate obtained by the parametric method for sea state estimation. The idea is illustrated by an analysis made on full-scale...

  1. Parametric estimation of time varying baselines in airborne interferometric SAR

    DEFF Research Database (Denmark)

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    1996-01-01

    A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...

  2. Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models

    Directory of Open Access Journals (Sweden)

    Marius Pesavento

    2004-08-01

    Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.

  3. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  4. Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison

    NARCIS (Netherlands)

    Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, J.G.P.W.; Camps-Valls, Gustau; Moreno, José

    2015-01-01

    Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC),

  5. Linear minimax estimation for random vectors with parametric uncertainty

    KAUST Repository

    Bitar, E

    2010-06-01

    In this paper, we take a minimax approach to the problem of computing a worst-case linear mean squared error (MSE) estimate of X given Y , where X and Y are jointly distributed random vectors with parametric uncertainty in their distribution. We consider two uncertainty models, PA and PB. Model PA represents X and Y as jointly Gaussian whose covariance matrix Λ belongs to the convex hull of a set of m known covariance matrices. Model PB characterizes X and Y as jointly distributed according to a Gaussian mixture model with m known zero-mean components, but unknown component weights. We show: (a) the linear minimax estimator computed under model PA is identical to that computed under model PB when the vertices of the uncertain covariance set in PA are the same as the component covariances in model PB, and (b) the problem of computing the linear minimax estimator under either model reduces to a semidefinite program (SDP). We also consider the dynamic situation where x(t) and y(t) evolve according to a discrete-time LTI state space model driven by white noise, the statistics of which is modeled by PA and PB as before. We derive a recursive linear minimax filter for x(t) given y(t).

  6. A local non-parametric model for trade sign inference

    Science.gov (United States)

    Blazejewski, Adam; Coggins, Richard

    2005-03-01

    We investigate a regularity in market order submission strategies for 12 stocks with large market capitalization on the Australian Stock Exchange. The regularity is evidenced by a predictable relationship between the trade sign (trade initiator), size of the trade, and the contents of the limit order book before the trade. We demonstrate this predictability by developing an empirical inference model to classify trades into buyer-initiated and seller-initiated. The model employs a local non-parametric method, k-nearest neighbor, which in the past was used successfully for chaotic time series prediction. The k-nearest neighbor with three predictor variables achieves an average out-of-sample classification accuracy of 71.40%, compared to 63.32% for the linear logistic regression with seven predictor variables. The result suggests that a non-linear approach may produce a more parsimonious trade sign inference model with a higher out-of-sample classification accuracy. Furthermore, for most of our stocks the observed regularity in market order submissions seems to have a memory of at least 30 trading days.

  7. Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

    Science.gov (United States)

    Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

    2016-01-01

    In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

  8. Determinant of flexible Parametric Estimation of Mixture Cure ...

    African Journals Online (AJOL)

    PROF. OLIVER OSUAGWA

    2015-12-01

    Dec 1, 2015 ... Suitability of four parametric mixture cure models were considered namely; Log .... regression analysis which relies on the ... The parameter of mixture cure fraction model was ..... Stochastic Models of Tumor Latency and Their.

  9. Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration

    DEFF Research Database (Denmark)

    Nielsen, Morten Ø.; Frederiksen, Per Houmann

    2005-01-01

    In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods. The es...... the time domain parametric methods, and (4) without sufficient trimming of scales the wavelet-based estimators are heavily biased.......In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches, and we consider both parametric and semiparametric estimation methods....... The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that (1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, (2) all...

  10. Determinant of flexible Parametric Estimation of Mixture Cure ...

    African Journals Online (AJOL)

    AIC, mean time to cure), variance and cure fraction (c) were used to determine the flexible Parametric Cure Fraction Model among the considered models. Gastric Cancer data from 76 patients received adjuvant CRT and 125 receiving resection (surgery) alone were used to confirm the suitability of the models. The data was ...

  11. Parametric and Non-Parametric System Modelling

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg

    1999-01-01

    the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...

  12. A Study on Parametric Wave Estimation Based on Measured Ship Motions

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Iseki, Toshio

    2011-01-01

    The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics of the param......The paper studies parametric wave estimation based on the ‘wave buoy analogy’, and data and results obtained from the training ship Shioji-maru are compared with estimates of the sea states obtained from other measurements and observations. Furthermore, the estimating characteristics...... of the parametric model are discussed by considering the results of a similar estimation concept based on Bayesian modelling. The purpose of the latter comparison is not to favour the one estimation approach to the other but rather to highlight some of the advantages and disadvantages of the two approaches....

  13. The Effects of Policy Guidance Emphasizing the Use of Parametric Methods in Cost Estimating

    National Research Council Canada - National Science Library

    Patton, James

    1996-01-01

    .... As one of many initiatives to improve the DoD acquisition process through use of commercial practices, parametric cost estimating has the potential to be helpful in many applications for which it...

  14. Parametric model to estimate containment loads following an ex-vessel steam spike

    International Nuclear Information System (INIS)

    Lopez, R.; Hernandez, J.; Huerta, A.

    1998-01-01

    This paper describes the use of a relatively simple parametric model to estimate containment loads following an ex-vessel steam spike. The study was motivated because several PSAs have identified containment loads accompanying reactor vessel failures as a major contributor to early containment failure. The paper includes a detailed description of the simple but physically sound parametric model which was adopted to estimate containment loads following a steam spike into the reactor cavity. (author)

  15. Parametric instabilities excited by localized pumps near the lower-hybrid frequency

    International Nuclear Information System (INIS)

    Kuo, Y.Y.; Chen, L.

    1976-04-01

    Parametric instabilities excited in non-uniform plasmas by spatially localized pump fields oscillating near the local lower-hybrid frequency are analytically investigated. Corresponding threshold conditions, temporal growth rates, and spatial amplification factors are obtained for the oscillating-two-stream instability and the decay instabilities due to nonlinear electron and ion Landau dampings

  16. ROBUST ALGORITHMS OF PARAMETRIC ESTIMATION IN SOME STABILIZATION PROBLEMS

    Directory of Open Access Journals (Sweden)

    A.A. Vedyakov

    2016-07-01

    Full Text Available Subject of Research.The tasks of dynamic systems provision in the stable state by means of ensuring of trite solution stability for various dynamic systems in the education regime with the aid of their parameters tuning are considered. Method. The problems are solved by application of ideology of the robust finitely convergent algorithms creation. Main Results. The concepts of parametric algorithmization of stability and steady asymptotic stability are introduced and the results are presented on synthesis of coarsed gradient algorithms solving the proposed tasks for finite number of iterations with the purpose of the posed problems decision. Practical Relevance. The article results may be called for decision of practical stabilization tasks in the process of various engineering constructions and devices operation.

  17. Parametric localized modes in quadratic nonlinear photonic structures

    DEFF Research Database (Denmark)

    Sukhorukov, Andrey A.; Kivshar, Yuri S.; Bang, Ole

    2001-01-01

    interfaces, we derive an effective discrete model for the amplitudes of the fundamental and second-harmonic waves at the interfaces (the so-called discrete chi2 equations) and find, numerically and analytically, the spatially localized solutions-discrete gap solitons. For a single nonlinear interface...

  18. Determining input values for a simple parametric model to estimate ...

    African Journals Online (AJOL)

    Estimating soil evaporation (Es) is an important part of modelling vineyard evapotranspiration for irrigation purposes. Furthermore, quantification of possible soil texture and trellis effects is essential. Daily Es from six topsoils packed into lysimeters was measured under grapevines on slanting and vertical trellises, ...

  19. Parametric change point estimation, testing and confidence interval ...

    African Journals Online (AJOL)

    In many applications like finance, industry and medicine, it is important to consider that the model parameters may undergo changes at unknown moment in time. This paper deals with estimation, testing and confidence interval of a change point for a univariate variable which is assumed to be normally distributed. To detect ...

  20. Oracle estimation of parametric models under boundary constraints.

    Science.gov (United States)

    Wong, Kin Yau; Goldberg, Yair; Fine, Jason P

    2016-12-01

    In many classical estimation problems, the parameter space has a boundary. In most cases, the standard asymptotic properties of the estimator do not hold when some of the underlying true parameters lie on the boundary. However, without knowledge of the true parameter values, confidence intervals constructed assuming that the parameters lie in the interior are generally over-conservative. A penalized estimation method is proposed in this article to address this issue. An adaptive lasso procedure is employed to shrink the parameters to the boundary, yielding oracle inference which adapt to whether or not the true parameters are on the boundary. When the true parameters are on the boundary, the inference is equivalent to that which would be achieved with a priori knowledge of the boundary, while if the converse is true, the inference is equivalent to that which is obtained in the interior of the parameter space. The method is demonstrated under two practical scenarios, namely the frailty survival model and linear regression with order-restricted parameters. Simulation studies and real data analyses show that the method performs well with realistic sample sizes and exhibits certain advantages over standard methods. © 2016, The International Biometric Society.

  1. Non-parametric PSF estimation from celestial transit solar images using blind deconvolution

    Directory of Open Access Journals (Sweden)

    González Adriana

    2016-01-01

    Full Text Available Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the convolution of an ideal image with a Point Spread Function (PSF. Additionally, the image acquisition process is also contaminated by other sources of noise (read-out, photon-counting. The problem of estimating both the PSF and a denoised image is called blind deconvolution and is ill-posed. Aims: We propose a blind deconvolution scheme that relies on image regularization. Contrarily to most methods presented in the literature, our method does not assume a parametric model of the PSF and can thus be applied to any telescope. Methods: Our scheme uses a wavelet analysis prior model on the image and weak assumptions on the PSF. We use observations from a celestial transit, where the occulting body can be assumed to be a black disk. These constraints allow us to retain meaningful solutions for the filter and the image, eliminating trivial, translated, and interchanged solutions. Under an additive Gaussian noise assumption, they also enforce noise canceling and avoid reconstruction artifacts by promoting the whiteness of the residual between the blurred observations and the cleaned data. Results: Our method is applied to synthetic and experimental data. The PSF is estimated for the SECCHI/EUVI instrument using the 2007 Lunar transit, and for SDO/AIA using the 2012 Venus transit. Results show that the proposed non-parametric blind deconvolution method is able to estimate the core of the PSF with a similar quality to parametric methods proposed in the literature. We also show that, if these parametric estimations are incorporated in the acquisition model, the resulting PSF outperforms both the parametric and non-parametric methods.

  2. Analysis and application of two recursive parametric estimation algorithms for an asynchronous machine

    International Nuclear Information System (INIS)

    Damek, Nawel; Kamoun, Samira

    2011-01-01

    In this communication, two recursive parametric estimation algorithms are analyzed and applied to an squirrelcage asynchronous machine located at the research ''Unit of Automatic Control'' (UCA) at ENIS. The first algorithm which, use the transfer matrix mathematical model, is based on the gradient principle. The second algorithm, which use the state-space mathematical model, is based on the minimization of the estimation error. These algorithms are applied as a key technique to estimate asynchronous machine with unknown, but constant or timevarying parameters. Stator voltage and current are used as measured data. The proposed recursive parametric estimation algorithms are validated on the experimental data of an asynchronous machine under normal operating condition as full load. The results show that these algorithms can estimate effectively the machine parameters with reliability.

  3. The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models

    OpenAIRE

    GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.

    2008-01-01

    In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.

  4. Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

    DEFF Research Database (Denmark)

    Høg, Esben

    In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

  5. Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods

    DEFF Research Database (Denmark)

    Høg, Esben

    2003-01-01

    In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...

  6. Joint Parametric Fault Diagnosis and State Estimation Using KF-ML Method

    DEFF Research Database (Denmark)

    Sun, Zhen; Yang, Zhenyu

    2014-01-01

    The paper proposes a new method for a kind of parametric fault online diagnosis with state estimation jointly. The considered fault affects not only the deterministic part of the system but also the random circumstance. The proposed method first applies Kalman Filter (KF) and Maximum Likelihood (...

  7. Principles of parametric estimation in modeling language competition.

    Science.gov (United States)

    Zhang, Menghan; Gong, Tao

    2013-06-11

    It is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka-Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.

  8. Local polynomial Whittle estimation of perturbed fractional processes

    DEFF Research Database (Denmark)

    Frederiksen, Per; Nielsen, Frank; Nielsen, Morten Ørregaard

    We propose a semiparametric local polynomial Whittle with noise (LPWN) estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the spectrum of the perturbation as well as that of the short-memory component...... of the signal by two separate polynomials. Including these polynomials we obtain a reduction in the order of magnitude of the bias, but also in‡ate the asymptotic variance of the long memory estimate by a multiplicative constant. We show that the estimator is consistent for d 2 (0; 1), asymptotically normal...... for d ε (0, 3/4), and if the spectral density is infinitely smooth near frequency zero, the rate of convergence can become arbitrarily close to the parametric rate, pn. A Monte Carlo study reveals that the LPWN estimator performs well in the presence of a serially correlated perturbation term...

  9. Local parametric instability near elliptic points in vortex flows under shear deformation

    Energy Technology Data Exchange (ETDEWEB)

    Koshel, Konstantin V., E-mail: kvkoshel@poi.dvo.ru [Pacific Oceanological Institute, FEB RAS, 43, Baltiyskaya Street, Vladivostok 690041 (Russian Federation); Institute of Applied Mathematics, FEB RAS, 7, Radio Street, Vladivostok 690022 (Russian Federation); Far Eastern Federal University, 8, Sukhanova Street, Vladivostok 690950 (Russian Federation); Ryzhov, Eugene A., E-mail: ryzhovea@gmail.com [Pacific Oceanological Institute, FEB RAS, 43, Baltiyskaya Street, Vladivostok 690041 (Russian Federation)

    2016-08-15

    The dynamics of two point vortices embedded in an oscillatory external flow consisted of shear and rotational components is addressed. The region associated with steady-state elliptic points of the vortex motion is established to experience local parametric instability. The instability forces the point vortices with initial positions corresponding to the steady-state elliptic points to move in spiral-like divergent trajectories. This divergent motion continues until the nonlinear effects suppress their motion near the region associated with the steady-state separatrices. The local parametric instability is then demonstrated not to contribute considerably to enhancing the size of the chaotic motion regions. Instead, the size of the chaotic motion region mostly depends on overlaps of the nonlinear resonances emerging in the perturbed system.

  10. Direct Parametric Reconstruction With Joint Motion Estimation/Correction for Dynamic Brain PET Data.

    Science.gov (United States)

    Jiao, Jieqing; Bousse, Alexandre; Thielemans, Kris; Burgos, Ninon; Weston, Philip S J; Schott, Jonathan M; Atkinson, David; Arridge, Simon R; Hutton, Brian F; Markiewicz, Pawel; Ourselin, Sebastien

    2017-01-01

    Direct reconstruction of parametric images from raw photon counts has been shown to improve the quantitative analysis of dynamic positron emission tomography (PET) data. However it suffers from subject motion which is inevitable during the typical acquisition time of 1-2 hours. In this work we propose a framework to jointly estimate subject head motion and reconstruct the motion-corrected parametric images directly from raw PET data, so that the effects of distorted tissue-to-voxel mapping due to subject motion can be reduced in reconstructing the parametric images with motion-compensated attenuation correction and spatially aligned temporal PET data. The proposed approach is formulated within the maximum likelihood framework, and efficient solutions are derived for estimating subject motion and kinetic parameters from raw PET photon count data. Results from evaluations on simulated [ 11 C]raclopride data using the Zubal brain phantom and real clinical [ 18 F]florbetapir data of a patient with Alzheimer's disease show that the proposed joint direct parametric reconstruction motion correction approach can improve the accuracy of quantifying dynamic PET data with large subject motion.

  11. truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models

    Directory of Open Access Journals (Sweden)

    Maria Karlsson

    2014-05-01

    Full Text Available Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and ?nite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.

  12. Non-parametric identification of multivariable systems : a local rational modeling approach with application to a vibration isolation benchmark

    NARCIS (Netherlands)

    Voorhoeve, R.J.; van der Maas, A.; Oomen, T.A.J.

    2018-01-01

    Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification. The aim of this paper is to develop a multiple-input multiple-output (MIMO) local parametric modeling approach for FRF

  13. Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications

    Science.gov (United States)

    Qian, Xuewen; Deng, Honggui; He, Hailang

    2017-10-01

    Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.

  14. Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.

    Science.gov (United States)

    Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

    2013-10-21

    In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study

  15. Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation

    International Nuclear Information System (INIS)

    Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman

    2013-01-01

    In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (∼15–20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate K i and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final K i parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion

  16. Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

    Science.gov (United States)

    Siciliani, Luigi

    2006-01-01

    Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

  17. Parametric estimation of the Duffing system by using a modified gradient algorithm

    International Nuclear Information System (INIS)

    Aguilar-Ibanez, Carlos; Sanchez Herrera, Jorge; Garrido-Moctezuma, Ruben

    2008-01-01

    The Letter presents a strategy for recovering the unknown parameters of the Duffing oscillator using a measurable output signal. The suggested approach employs the construction of an integral parametrization of one auxiliary output. It is calculated by measuring the difference between the output and its respective delay output. First we estimate the auxiliary output, followed by the application of a modified gradient algorithm, then we adjust the gains of the proposed linear estimator, until this error converges to zero. The convergence of the proposed scheme is shown using Lyapunov method

  18. Relativistic effects in local inertial frames including parametrized-post-Newtonian effects

    International Nuclear Information System (INIS)

    Shahid-Saless, B.; Ashby, N.

    1988-01-01

    We use the concept of a generalized Fermi frame to describe relativistic effects, due to local and distant sources of gravitation, on a body placed in a local inertial frame of reference. In particular we have considered a model of two spherically symmetric gravitating point sources, moving in circular orbits around a common barycenter where one of the bodies is chosen to be the local and the other the distant one. This has been done using the slow-motion, weak-field approximation and including four of the parametrized-post-Newtonian (PPN) parameters. The position of the classical center of mass must be modified when the PPN parameter zeta 2 is included. We show that the main relativistic effect on a local satellite is described by the Schwarzschild field of the local body and the nonlinear term corresponding to the self-interaction of the local source with itself. There are also much smaller terms that are proportional, respectively, to the product of the potentials of local and distant bodies and to the distant body's self-interactions. The spatial axes of the local frame undergo geodetic precession. In addition we have an acceleration of the order of 10/sup -11/ cm sec -2 that vanish in the case of general relativity, which is discussed in detail

  19. Kinetic parametric estimation in animal PET molecular imaging based on artificial immune network

    International Nuclear Information System (INIS)

    Chen Yuting; Ding Hong; Lu Rui; Huang Hongbo; Liu Li

    2011-01-01

    Objective: To develop an accurate,reliable method without the need of initialization in animal PET modeling for estimation of the tracer kinetic parameters based on the artificial immune network. Methods: The hepatic and left ventricular time activity curves (TACs) were obtained by drawing ROIs of liver tissue and left ventricle on dynamic 18 F-FDG PET imaging of small mice. Meanwhile, the blood TAC was analyzed by sampling the tail vein blood at different time points after injection. The artificial immune network for parametric optimization of pharmacokinetics (PKAIN) was adapted to estimate the model parameters and the metabolic rate of glucose (K i ) was calculated. Results: TACs of liver,left ventricle and tail vein blood were obtained.Based on the artificial immune network, K i in 3 mice was estimated as 0.0024, 0.0417 and 0.0047, respectively. The average weighted residual sum of squares of the output model generated by PKAIN was less than 0.0745 with a maximum standard deviation of 0.0084, which indicated that the proposed PKAIN method can provide accurate and reliable parametric estimation. Conclusion: The PKAIN method could provide accurate and reliable tracer kinetic modeling in animal PET imaging without the need of initialization of model parameters. (authors)

  20. Parametric estimation of P(X > Y) for normal distributions in the context of probabilistic environmental risk assessment.

    Science.gov (United States)

    Jacobs, Rianne; Bekker, Andriëtte A; van der Voet, Hilko; Ter Braak, Cajo J F

    2015-01-01

    Estimating the risk, P(X > Y), in probabilistic environmental risk assessment of nanoparticles is a problem when confronted by potentially small risks and small sample sizes of the exposure concentration X and/or the effect concentration Y. This is illustrated in the motivating case study of aquatic risk assessment of nano-Ag. A non-parametric estimator based on data alone is not sufficient as it is limited by sample size. In this paper, we investigate the maximum gain possible when making strong parametric assumptions as opposed to making no parametric assumptions at all. We compare maximum likelihood and Bayesian estimators with the non-parametric estimator and study the influence of sample size and risk on the (interval) estimators via simulation. We found that the parametric estimators enable us to estimate and bound the risk for smaller sample sizes and small risks. Also, the Bayesian estimator outperforms the maximum likelihood estimators in terms of coverage and interval lengths and is, therefore, preferred in our motivating case study.

  1. Localization of one-photon state in space and Einstein-Podolsky-Rosen paradox in spontaneous parametric down conversion

    Science.gov (United States)

    Penin, A. N.; Reutova, T. A.; Sergienko, A. V.

    1992-01-01

    An experiment on one-photon state localization in space using a correlation technique in Spontaneous Parametric Down Conversion (SPDC) process is discussed. Results of measurements demonstrate an idea of the Einstein-Podolsky-Rosen (EPR) paradox for coordinate and momentum variables of photon states. Results of the experiment can be explained with the help of an advanced wave technique. The experiment is based on the idea that two-photon states of optical electromagnetic fields arising in the nonlinear process of the spontaneous parametric down conversion (spontaneous parametric light scattering) can be explained by quantum mechanical theory with the help of a single wave function.

  2. Localization of one-photon state in space and Einstein-Podolsky-Rosen paradox in Spontaneous Parametric Down Conversion

    International Nuclear Information System (INIS)

    Penin, A.N.; Reutova, T.A.; Sergienko, A.V.

    1992-01-01

    An experiment on one-photon state localization in space using a correlation technique in Spontaneous Parametric Down Conversion (SPDC) process is discussed. Results of measurements demonstrate an idea of the Einstein-Podolsky-Rosen (EPR) paradox for coordinate and momentum variables of photon states. Results of the experiment can be explained with the help of an advanced wave technique. The experiment is based on the idea that two-photon states of optical electromagnetic fields arising in the nonlinear process of the spontaneous parametric down conversion (spontaneous parametric light scattering) can be explained by quantum mechanical theory with the help of a single wave function

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

    International Nuclear Information System (INIS)

    Morio, Jerome

    2011-01-01

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

  4. Estimating the cost of improving quality in electricity distribution: A parametric distance function approach

    International Nuclear Information System (INIS)

    Coelli, Tim J.; Gautier, Axel; Perelman, Sergio; Saplacan-Pop, Roxana

    2013-01-01

    The quality of electricity distribution is being more and more scrutinized by regulatory authorities, with explicit reward and penalty schemes based on quality targets having been introduced in many countries. It is then of prime importance to know the cost of improving the quality for a distribution system operator. In this paper, we focus on one dimension of quality, the continuity of supply, and we estimated the cost of preventing power outages. For that, we make use of the parametric distance function approach, assuming that outages enter in the firm production set as an input, an imperfect substitute for maintenance activities and capital investment. This allows us to identify the sources of technical inefficiency and the underlying trade-off faced by operators between quality and other inputs and costs. For this purpose, we use panel data on 92 electricity distribution units operated by ERDF (Electricité de France - Réseau Distribution) in the 2003–2005 financial years. Assuming a multi-output multi-input translog technology, we estimate that the cost of preventing one interruption is equal to 10.7€ for an average DSO. Furthermore, as one would expect, marginal quality improvements tend to be more expensive as quality itself improves. - Highlights: ► We estimate the implicit cost of outages for the main distribution company in France. ► For this purpose, we make use of a parametric distance function approach. ► Marginal quality improvements tend to be more expensive as quality itself improves. ► The cost of preventing one interruption varies from 1.8 € to 69.2 € (2005 prices). ► We estimate that, in average, it lays 33% above the regulated price of quality.

  5. A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain

    Directory of Open Access Journals (Sweden)

    Ibn-Elhaj E

    2009-01-01

    Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.

  6. A Robust Subpixel Motion Estimation Algorithm Using HOS in the Parametric Domain

    Directory of Open Access Journals (Sweden)

    E. M. Ismaili Aalaoui

    2009-02-01

    Full Text Available Motion estimation techniques are widely used in todays video processing systems. The most frequently used techniques are the optical flow method and phase correlation method. The vast majority of these algorithms consider noise-free data. Thus, in the case of the image sequences are severely corrupted by additive Gaussian (perhaps non-Gaussian noises of unknown covariance, the classical techniques will fail to work because they will also estimate the noise spatial correlation. In this paper, we have studied this topic from a viewpoint different from the above to explore the fundamental limits in image motion estimation. Our scheme is based on subpixel motion estimation algorithm using bispectrum in the parametric domain. The motion vector of a moving object is estimated by solving linear equations involving third-order hologram and the matrix containing Dirac delta function. Simulation results are presented and compared to the optical flow and phase correlation algorithms; this approach provides more reliable displacement estimates particularly for complex noisy image sequences. In our simulation, we used the database freely available on the web.

  7. A comparison of selected parametric and non-parametric imputation methods for estimating forest biomass and basal area

    Science.gov (United States)

    Donald Gagliasso; Susan Hummel; Hailemariam. Temesgen

    2014-01-01

    Various methods have been used to estimate the amount of above ground forest biomass across landscapes and to create biomass maps for specific stands or pixels across ownership or project areas. Without an accurate estimation method, land managers might end up with incorrect biomass estimate maps, which could lead them to make poorer decisions in their future...

  8. Estimating genetic covariance functions assuming a parametric correlation structure for environmental effects

    Directory of Open Access Journals (Sweden)

    Meyer Karin

    2001-11-01

    Full Text Available Abstract A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects.

  9. A multiresolution spatial parametrization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions.

    Energy Technology Data Exchange (ETDEWEB)

    Ray, Jaideep; Lee, Jina; Lefantzi, Sophia; Yadav, Vineet [Carnegie Institution for Science, Stanford, CA; Michalak, Anna M. [Carnegie Institution for Science, Stanford, CA; van Bloemen Waanders, Bart Gustaaf [Sandia National Laboratories, Albuquerque, NM; McKenna, Sean Andrew [IBM Research, Mulhuddart, Dublin 15, Ireland

    2013-04-01

    The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.

  10. Direct diffusion tensor estimation using a model-based method with spatial and parametric constraints.

    Science.gov (United States)

    Zhu, Yanjie; Peng, Xi; Wu, Yin; Wu, Ed X; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2017-02-01

    To develop a new model-based method with spatial and parametric constraints (MB-SPC) aimed at accelerating diffusion tensor imaging (DTI) by directly estimating the diffusion tensor from highly undersampled k-space data. The MB-SPC method effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images using an L1-L2 norm and the smoothness of the diffusion tensor using a total variation seminorm. The undersampled k-space datasets were obtained from fully sampled DTI datasets of a simulated phantom and an ex-vivo experimental rat heart with acceleration factors ranging from 2 to 4. The diffusion tensor was directly reconstructed by solving a minimization problem with a nonlinear conjugate gradient descent algorithm. The reconstruction performance was quantitatively assessed using the normalized root mean square error (nRMSE) of the DTI indices. The MB-SPC method achieves acceptable DTI measures at an acceleration factor up to 4. Experimental results demonstrate that the proposed method can estimate the diffusion tensor more accurately than most existing methods operating at higher net acceleration factors. The proposed method can significantly reduce artifact, particularly at higher acceleration factors or lower SNRs. This method can easily be adapted to MR relaxometry parameter mapping and is thus useful in the characterization of biological tissue such as nerves, muscle, and heart tissue. © 2016 American Association of Physicists in Medicine.

  11. Low default credit scoring using two-class non-parametric kernel density estimation

    CSIR Research Space (South Africa)

    Rademeyer, E

    2016-12-01

    Full Text Available This paper investigates the performance of two-class classification credit scoring data sets with low default ratios. The standard two-class parametric Gaussian and non-parametric Parzen classifiers are extended, using Bayes’ rule, to include either...

  12. Estimators for local non-Gaussianities

    International Nuclear Information System (INIS)

    Creminelli, P.; Senatore, L.; Zaldarriaga, M.

    2006-05-01

    We study the Likelihood function of data given f NL for the so-called local type of non-Gaussianity. In this case the curvature perturbation is a non-linear function, local in real space, of a Gaussian random field. We compute the Cramer-Rao bound for f NL and show that for small values of f NL the 3- point function estimator saturates the bound and is equivalent to calculating the full Likelihood of the data. However, for sufficiently large f NL , the naive 3-point function estimator has a much larger variance than previously thought. In the limit in which the departure from Gaussianity is detected with high confidence, error bars on f NL only decrease as 1/ln N pix rather than N pix -1/2 as the size of the data set increases. We identify the physical origin of this behavior and explain why it only affects the local type of non- Gaussianity, where the contribution of the first multipoles is always relevant. We find a simple improvement to the 3-point function estimator that makes the square root of its variance decrease as N pix -1/2 even for large f NL , asymptotically approaching the Cramer-Rao bound. We show that using the modified estimator is practically equivalent to computing the full Likelihood of f NL given the data. Thus other statistics of the data, such as the 4-point function and Minkowski functionals, contain no additional information on f NL . In particular, we explicitly show that the recent claims about the relevance of the 4-point function are not correct. By direct inspection of the Likelihood, we show that the data do not contain enough information for any statistic to be able to constrain higher order terms in the relation between the Gaussian field and the curvature perturbation, unless these are orders of magnitude larger than the size suggested by the current limits on f NL . (author)

  13. Parametric estimation of covariance function in Gaussian-process based Kriging models. Application to uncertainty quantification for computer experiments

    International Nuclear Information System (INIS)

    Bachoc, F.

    2013-01-01

    The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr

  14. A parametric cost model for estimating operating and support costs of US Navy (non-nuclear) surface ships

    OpenAIRE

    Brandt, James M.

    1999-01-01

    Approved for public release; distribution is unlimited With few effective decision-making tools to assess the affordability of major weapon systems, management of total ownership costs is continually misunderstood. Cost analysis provides a quick and reliable assessment of affordability. Because there is no standardized method for calculating reliable estimates of operating and support (O&S) costs (the principal component of total ownership cost), this thesis formulates a parametric cost mo...

  15. Parametric fault estimation based on H∞ optimization in a satellite launch vehicle

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Stoustrup, Jakob

    2008-01-01

    Correct diagnosis under harsh environmental conditions is crucial for space vehiclespsila health management systems to avoid possible hazardous situations. Consequently, the diagnosis methods are required to be robust toward these conditions. Design of a parametric fault detector, where the fault...... for the satellite launch vehicle and the results are discussed....

  16. A non-parametric estimator for the doubly-periodic Poisson intensity function

    NARCIS (Netherlands)

    R. Helmers (Roelof); I.W. Mangku (Wayan); R. Zitikis

    2007-01-01

    textabstractIn a series of papers, J. Garrido and Y. Lu have proposed and investigated a doubly-periodic Poisson model, and then applied it to analyze hurricane data. The authors have suggested several parametric models for the underlying intensity function. In the present paper we construct and

  17. On the parallelization of a three-parametric log-logistic estimation algorithm

    OpenAIRE

    Asenjo-Plaza, Rafael; Rodríguez, Andrés; Navarro, Ángeles; Fernández-Madrigal, Juan Antonio; Cruz-Martin, Ana Maria

    2014-01-01

    Networked telerobots transmit data from its sensors to the remote controller. To provide guarantees on the time requirements of these systems it is mandatory to keep the transmission time delays below a given threshold, and to that end we should predict them. In this paper we tackle the parallelization of a procedure that models these stochastic time delays. More precisely, we focus on fitting the time delay signal using a three-parametrical log-logistic distribution. Since, the robot and the...

  18. Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

    Science.gov (United States)

    Moore, Julia L; Remais, Justin V

    2014-03-01

    Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

  19. Estimating solar ultraviolet irradiance (290-385 nm by means of the spectral parametric models: SPCTRAL2 and SMARTS2

    Directory of Open Access Journals (Sweden)

    I. Foyo-Moreno

    2000-11-01

    Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those

  20. Estimating solar ultraviolet irradiance (290-385 nm by means of the spectral parametric models: SPCTRAL2 and SMARTS2

    Directory of Open Access Journals (Sweden)

    I. Foyo-Moreno

    Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those

  1. Estimating Mutual Information by Local Gaussian Approximation

    Science.gov (United States)

    2015-07-13

    proposed a variety of methods to overcome the bias, such as the reflection method (Schuster, 1985), ( Silverman , 1986); the boundary kernel method...Stephen Marron and David Ruppert. Transformations to reduce boundary bias in kernel density estimation. Journal of the Royal Statistical Society. Series B...estimation with applications to machine learning on distributions. In Proceedings of Uncertainty in Artificial In- telligence (UAI), 2011. David N Reshef

  2. Local polynomial Whittle estimation covering non-stationary fractional processes

    DEFF Research Database (Denmark)

    Nielsen, Frank

    to the non-stationary region. By approximating the short-run component of the spectrum by a polynomial, instead of a constant, in a shrinking neighborhood of zero we alleviate some of the bias that the classical local Whittle estimators is prone to. This bias reduction comes at a cost as the variance is in...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....

  3. Parameter Estimation with Entangled Photons Produced by Parametric Down-Conversion

    Science.gov (United States)

    Cable, Hugo; Durkin, Gabriel A.

    2010-01-01

    We explore the advantages offered by twin light beams produced in parametric down-conversion for precision measurement. The symmetry of these bipartite quantum states, even under losses, suggests that monitoring correlations between the divergent beams permits a high-precision inference of any symmetry-breaking effect, e.g., fiber birefringence. We show that the quantity of entanglement is not the key feature for such an instrument. In a lossless setting, scaling of precision at the ultimate "Heisenberg" limit is possible with photon counting alone. Even as photon losses approach 100% the precision is shot-noise limited, and we identify the crossover point between quantum and classical precision as a function of detected flux. The predicted hypersensitivity is demonstrated with a Bayesian simulation.

  4. Significance of application of the nine parametric coordinate transformation where local state network is not enough reliable

    Directory of Open Access Journals (Sweden)

    Ristić Kornelija T.

    2016-01-01

    Full Text Available The most commonly used method for establishing the mathematical basis of surveying and spatial data collection is the method of Global Navigation Satellite Positioning System (GNSS. However, these data relate to the World Geodetic Date WGS84 which is different from the State geodetic network,. As a part of realization the project of determining spatial local reference network Mrkonjić Grad the GNSS observations on 15 trigonometric points whose position is known to the State system of coordinates (x, y, h were made. For the purpose of coordinate transformation between the two system two different transformation models were anlyzed. Beside the most commonly used Helmert seven parameter transformation, afina nine parametric transformation was tested. Comparing the two transformations models, conclusion was made that showes some benefits of using affina nine parameter transformation models in Republic of Serpska.

  5. Estimation of leakage power and delay in CMOS circuits using parametric variation

    Directory of Open Access Journals (Sweden)

    Preeti Verma

    2016-09-01

    Full Text Available With the advent of deep-submicron technologies, leakage power dissipation is a major concern for scaling down portable devices that have burst-mode type integrated circuits. In this paper leakage reduction technique HTLCT (High Threshold Leakage Control Transistor is discussed. Using high threshold transistors at the place of low threshold leakage control transistors, result in more leakage power reduction as compared to LCT (leakage control transistor technique but at the scarifies of area and delay. Further, analysis of effect of parametric variation on leakage current and propagation delay in CMOS circuits is performed. It is found that the leakage power dissipation increases with increasing temperature, supply voltage and aspect ratio. However, opposite pattern is noticed for the propagation delay. Leakage power dissipation for LCT NAND gate increases up to 14.32%, 6.43% and 36.21% and delay decreases by 22.5%, 42% and 9% for variation of temperature, supply voltage and aspect ratio. Maximum peak of equivalent output noise is obtained as 127.531 nV/Sqrt(Hz at 400 mHz.

  6. Semi-parametric estimation of random effects in a logistic regression model using conditional inference

    DEFF Research Database (Denmark)

    Petersen, Jørgen Holm

    2016-01-01

    This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...

  7. Non-parametric estimation of the availability in a general repairable system

    International Nuclear Information System (INIS)

    Gamiz, M.L.; Roman, Y.

    2008-01-01

    This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform

  8. Non-parametric estimation of the availability in a general repairable system

    Energy Technology Data Exchange (ETDEWEB)

    Gamiz, M.L. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)], E-mail: mgamiz@ugr.es; Roman, Y. [Departamento de Estadistica e I.O., Facultad de Ciencias, Universidad de Granada, Granada 18071 (Spain)

    2008-08-15

    This work deals with repairable systems with unknown failure and repair time distributions. We focus on the estimation of the instantaneous availability, that is, the probability that the system is functioning at a given time, which we consider as the most significant measure for evaluating the effectiveness of a repairable system. The estimation of the availability function is not, in general, an easy task, i.e., analytical techniques are difficult to apply. We propose a smooth estimation of the availability based on kernel estimator of the cumulative distribution functions (CDF) of the failure and repair times, for which the bandwidth parameters are obtained by bootstrap procedures. The consistency properties of the availability estimator are established by using techniques based on the Laplace transform.

  9. Single event upset threshold estimation based on local laser irradiation

    International Nuclear Information System (INIS)

    Chumakov, A.I.; Egorov, A.N.; Mavritsky, O.B.; Yanenko, A.V.

    1999-01-01

    An approach for estimation of ion-induced SEU threshold based on local laser irradiation is presented. Comparative experiment and software simulation research were performed at various pulse duration and spot size. Correlation of single event threshold LET to upset threshold laser energy under local irradiation was found. The computer analysis of local laser irradiation of IC structures was developed for SEU threshold LET estimation. The correlation of local laser threshold energy with SEU threshold LET was shown. Two estimation techniques were suggested. The first one is based on the determination of local laser threshold dose taking into account the relation of sensitive area to local irradiated area. The second technique uses the photocurrent peak value instead of this relation. The agreement between the predicted and experimental results demonstrates the applicability of this approach. (authors)

  10. Type I Error Rates and Power Estimates of Selected Parametric and Nonparametric Tests of Scale.

    Science.gov (United States)

    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)

  11. On the method of logarithmic cumulants for parametric probability density function estimation.

    Science.gov (United States)

    Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane

    2013-10-01

    Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.

  12. A parametrization of two-dimensional turbulence based on a maximum entropy production principle with a local conservation of energy

    International Nuclear Information System (INIS)

    Chavanis, Pierre-Henri

    2014-01-01

    In the context of two-dimensional (2D) turbulence, we apply the maximum entropy production principle (MEPP) by enforcing a local conservation of energy. This leads to an equation for the vorticity distribution that conserves all the Casimirs, the energy, and that increases monotonically the mixing entropy (H-theorem). Furthermore, the equation for the coarse-grained vorticity dissipates monotonically all the generalized enstrophies. These equations may provide a parametrization of 2D turbulence. They do not generally relax towards the maximum entropy state. The vorticity current vanishes for any steady state of the 2D Euler equation. Interestingly, the equation for the coarse-grained vorticity obtained from the MEPP turns out to coincide, after some algebraic manipulations, with the one obtained with the anticipated vorticity method. This shows a connection between these two approaches when the conservation of energy is treated locally. Furthermore, the newly derived equation, which incorporates a diffusion term and a drift term, has a nice physical interpretation in terms of a selective decay principle. This sheds new light on both the MEPP and the anticipated vorticity method. (paper)

  13. Empirical Bayes Estimation of Semi-parametric Hierarchical Mixture Models for Unbiased Characterization of Polygenic Disease Architectures

    Directory of Open Access Journals (Sweden)

    Jo Nishino

    2018-04-01

    Full Text Available Genome-wide association studies (GWAS suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1. For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases.

  14. Noise removal in multichannel image data by a parametric maximum noise fraction estimator

    DEFF Research Database (Denmark)

    Conradsen, Knut; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg

    1991-01-01

    Some approaches to noise removal in multispectral imagery are presented. The primary contribution of the present work is the establishment of several ways of estimating the noise covariance matrix from image data and a comparison of the noise separation performances. A case study with Landsat MSS...

  15. An estimating equation for parametric shared frailty models with marginal additive hazards

    DEFF Research Database (Denmark)

    Pipper, Christian Bressen; Martinussen, Torben

    2004-01-01

    Multivariate failure time data arise when data consist of clusters in which the failure times may be dependent. A popular approach to such data is the marginal proportional hazards model with estimation under the working independence assumption. In some contexts, however, it may be more reasonable...

  16. A probabilistic parametrization for geological uncertainty estimation using the ensemble Kalman filter (EnKF)

    NARCIS (Netherlands)

    Sebacher, B.; Hanea, R.G.; Heemink, A.

    2013-01-01

    In the past years, many applications of historymatching methods in general and ensemble Kalman filter in particular have been proposed, especially in order to estimate fields that provide uncertainty in the stochastic process defined by the dynamical system of hydrocarbon recovery. Such fields can

  17. Multiple leakage localization and leak size estimation in water networks

    NARCIS (Netherlands)

    Abbasi, N.; Habibi, H.; Hurkens, C.A.J.; Klabbers, M.D.; Tijsseling, A.S.; Eijndhoven, van S.J.L.

    2012-01-01

    Water distribution networks experience considerable losses due to leakage, often at multiple locations simultaneously. Leakage detection and localization based on sensor placement and online pressure monitoring could be fast and economical. Using the difference between estimated and measured

  18. Essays on parametric and nonparametric modeling and estimation with applications to energy economics

    Science.gov (United States)

    Gao, Weiyu

    My dissertation research is composed of two parts: a theoretical part on semiparametric efficient estimation and an applied part in energy economics under different dynamic settings. The essays are related in terms of their applications as well as the way in which models are constructed and estimated. In the first essay, efficient estimation of the partially linear model is studied. We work out the efficient score functions and efficiency bounds under four stochastic restrictions---independence, conditional symmetry, conditional zero mean, and partially conditional zero mean. A feasible efficient estimation method for the linear part of the model is developed based on the efficient score. A battery of specification test that allows for choosing between the alternative assumptions is provided. A Monte Carlo simulation is also conducted. The second essay presents a dynamic optimization model for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from different sources to estimate the oil production cost function and the revenue function. We pay particular attention to the dynamic aspect of the oil production by employing petroleum-engineering software to simulate the interaction between control variables and reservoir state variables. Optimal solutions are studied under different scenarios to account for the possible changes in the exogenous variables and the uncertainty about the forecasts. The third essay examines the effect of oil price volatility on the level of innovation displayed by the U.S. economy. A measure of innovation is calculated by decomposing an output-based Malmquist index. We also construct a nonparametric measure for oil price volatility. Technical change and oil price volatility are then placed in a VAR system with oil price and a variable indicative of monetary policy. The system is estimated and analyzed for significant relationships. We find that oil price volatility displays a significant

  19. Habitat suitability criteria via parametric distributions: estimation, model selection and uncertainty

    Science.gov (United States)

    Som, Nicholas A.; Goodman, Damon H.; Perry, Russell W.; Hardy, Thomas B.

    2016-01-01

    Previous methods for constructing univariate habitat suitability criteria (HSC) curves have ranged from professional judgement to kernel-smoothed density functions or combinations thereof. We present a new method of generating HSC curves that applies probability density functions as the mathematical representation of the curves. Compared with previous approaches, benefits of our method include (1) estimation of probability density function parameters directly from raw data, (2) quantitative methods for selecting among several candidate probability density functions, and (3) concise methods for expressing estimation uncertainty in the HSC curves. We demonstrate our method with a thorough example using data collected on the depth of water used by juvenile Chinook salmon (Oncorhynchus tschawytscha) in the Klamath River of northern California and southern Oregon. All R code needed to implement our example is provided in the appendix. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  20. Relating Local to Global Spatial Knowledge: Heuristic Influence of Local Features on Direction Estimates

    Science.gov (United States)

    Phillips, Daniel W.; Montello, Daniel R.

    2015-01-01

    Previous research has examined heuristics--simplified decision-making rules-of-thumb--for geospatial reasoning. This study examined at two locations the influence of beliefs about local coastline orientation on estimated directions to local and distant places; estimates were made immediately or after fifteen seconds. This study goes beyond…

  1. spa: Semi-Supervised Semi-Parametric Graph-Based Estimation in R

    Directory of Open Access Journals (Sweden)

    Mark Culp

    2011-04-01

    Full Text Available In this paper, we present an R package that combines feature-based (X data and graph-based (G data for prediction of the response Y . In this particular case, Y is observed for a subset of the observations (labeled and missing for the remainder (unlabeled. We examine an approach for fitting Y = Xβ + f(G where β is a coefficient vector and f is a function over the vertices of the graph. The procedure is semi-supervised in nature (trained on the labeled and unlabeled sets, requiring iterative algorithms for fitting this estimate. The package provides several key functions for fitting and evaluating an estimator of this type. The package is illustrated on a text analysis data set, where the observations are text documents (papers, the response is the category of paper (either applied or theoretical statistics, the X information is the name of the journal in which the paper resides, and the graph is a co-citation network, with each vertex an observation and each edge the number of times that the two papers cite a common paper. An application involving classification of protein location using a protein interaction graph and an application involving classification on a manifold with part of the feature data converted to a graph are also presented.

  2. Unstable volatility functions: the break preserving local linear estimator

    DEFF Research Database (Denmark)

    Casas, Isabel; Gijbels, Irene

    The objective of this paper is to introduce the break preserving local linear (BPLL) estimator for the estimation of unstable volatility functions. Breaks in the structure of the conditional mean and/or the volatility functions are common in Finance. Markov switching models (Hamilton, 1989......) and threshold models (Lin and Terasvirta, 1994) are amongst the most popular models to describe the behaviour of data with structural breaks. The local linear (LL) estimator is not consistent at points where the volatility function has a break and it may even report negative values for finite samples...

  3. A Comparison of Kernel Equating and Traditional Equipercentile Equating Methods and the Parametric Bootstrap Methods for Estimating Standard Errors in Equipercentile Equating

    Science.gov (United States)

    Choi, Sae Il

    2009-01-01

    This study used simulation (a) to compare the kernel equating method to traditional equipercentile equating methods under the equivalent-groups (EG) design and the nonequivalent-groups with anchor test (NEAT) design and (b) to apply the parametric bootstrap method for estimating standard errors of equating. A two-parameter logistic item response…

  4. 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.

  5. Parametric validations of analytical lifetime estimates for radiation belt electron diffusion by whistler waves

    Directory of Open Access Journals (Sweden)

    A. V. Artemyev

    2013-04-01

    Full Text Available The lifetimes of electrons trapped in Earth's radiation belts can be calculated from quasi-linear pitch-angle diffusion by whistler-mode waves, provided that their frequency spectrum is broad enough and/or their average amplitude is not too large. Extensive comparisons between improved analytical lifetime estimates and full numerical calculations have been performed in a broad parameter range representative of a large part of the magnetosphere from L ~ 2 to 6. The effects of observed very oblique whistler waves are taken into account in both numerical and analytical calculations. Analytical lifetimes (and pitch-angle diffusion coefficients are found to be in good agreement with full numerical calculations based on CRRES and Cluster hiss and lightning-generated wave measurements inside the plasmasphere and Cluster lower-band chorus waves measurements in the outer belt for electron energies ranging from 100 keV to 5 MeV. Comparisons with lifetimes recently obtained from electron flux measurements on SAMPEX, SCATHA, SAC-C and DEMETER also show reasonable agreement.

  6. A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

    Science.gov (United States)

    Karabatsos, George

    2017-02-01

    Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected

  7. Classification rates: non‐parametric verses parametric models using ...

    African Journals Online (AJOL)

    This research sought to establish if non parametric modeling achieves a higher correct classification ratio than a parametric model. The local likelihood technique was used to model fit the data sets. The same sets of data were modeled using parametric logit and the abilities of the two models to correctly predict the binary ...

  8. Estimation and prediction under local volatility jump-diffusion model

    Science.gov (United States)

    Kim, Namhyoung; Lee, Younhee

    2018-02-01

    Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump-diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump-diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump-diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.

  9. Correlation Dimension Estimates of Global and Local Temperature Data.

    Science.gov (United States)

    Wang, Qiang

    1995-11-01

    The author has attempted to detect the presence of low-dimensional deterministic chaos in temperature data by estimating the correlation dimension with the Hill estimate that has been recently developed by Mikosch and Wang. There is no convincing evidence of low dimensionality with either global dataset (Southern Hemisphere monthly average temperatures from 1858 to 1984) or local temperature dataset (daily minimums at Auckland, New Zealand). Any apparent reduction in the dimension estimates appears to be due large1y, if not entirely, to effects of statistical bias, but neither is it a purely random stochastic process. The dimension of the climatic attractor may be significantly larger than 10.

  10. Local gradient estimate for harmonic functions on Finsler manifolds

    OpenAIRE

    Xia, Chao

    2013-01-01

    In this paper, we prove the local gradient estimate for harmonic functions on complete, noncompact Finsler measure spaces under the condition that the weighted Ricci curvature has a lower bound. As applications, we obtain Liouville type theorem on Finsler manifolds with nonnegative Ricci curvature.

  11. Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

    Energy Technology Data Exchange (ETDEWEB)

    Tadayyon, Hadi [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Sadeghi-Naini, Ali; Czarnota, Gregory, E-mail: Gregory.Czarnota@sunnybrook.ca [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario M5T 1P5 (Canada); Wirtzfeld, Lauren [Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Wright, Frances C. [Division of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada)

    2014-01-15

    Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor

  12. Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

    International Nuclear Information System (INIS)

    Tadayyon, Hadi; Sadeghi-Naini, Ali; Czarnota, Gregory; Wirtzfeld, Lauren; Wright, Frances C.

    2014-01-01

    Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor

  13. Cooperative Robot Localization Using Event-Triggered Estimation

    Science.gov (United States)

    Iglesias Echevarria, David I.

    It is known that multiple robot systems that need to cooperate to perform certain activities or tasks incur in high energy costs that hinder their autonomous functioning and limit the benefits provided to humans by these kinds of platforms. This work presents a communications-based method for cooperative robot localization. Implementing concepts from event-triggered estimation, used with success in the field of wireless sensor networks but rarely to do robot localization, agents are able to only send measurements to their neighbors when the expected novelty in this information is high. Since all agents know the condition that triggers a measurement to be sent or not, the lack of a measurement is therefore informative and fused into state estimates. In the case agents do not receive either direct nor indirect measurements of all others, the agents employ a covariance intersection fusion rule in order to keep the local covariance error metric bounded. A comprehensive analysis of the proposed algorithm and its estimation performance in a variety of scenarios is performed, and the algorithm is compared to similar cooperative localization approaches. Extensive simulations are performed that illustrate the effectiveness of this method.

  14. The concept of estimation of elevator shaft control measurement results in the local 3D coordinate system

    Directory of Open Access Journals (Sweden)

    Filipiak-Kowszyk Daria

    2018-01-01

    Full Text Available Geodetic control measurements play an important part because they provide information about the current state of repair of the construction, which has a direct impact on the safety assessment of its exploitation. Authors in this paper have focused on control measurements of the elevator shaft. The article discusses the problem of determining the deviation of elevator shaft walls from the vertical plane in the local 3D coordinate system. It presents a concept of estimation of measurements results base on the parametric method with conditions on parameters. The simulated measurement results were used to verify the concept presented in the paper.

  15. Estimating monotonic rates from biological data using local linear regression.

    Science.gov (United States)

    Olito, Colin; White, Craig R; Marshall, Dustin J; Barneche, Diego R

    2017-03-01

    Accessing many fundamental questions in biology begins with empirical estimation of simple monotonic rates of underlying biological processes. Across a variety of disciplines, ranging from physiology to biogeochemistry, these rates are routinely estimated from non-linear and noisy time series data using linear regression and ad hoc manual truncation of non-linearities. Here, we introduce the R package LoLinR, a flexible toolkit to implement local linear regression techniques to objectively and reproducibly estimate monotonic biological rates from non-linear time series data, and demonstrate possible applications using metabolic rate data. LoLinR provides methods to easily and reliably estimate monotonic rates from time series data in a way that is statistically robust, facilitates reproducible research and is applicable to a wide variety of research disciplines in the biological sciences. © 2017. Published by The Company of Biologists Ltd.

  16. Estimation from PET data of transient changes in dopamine concentration induced by alcohol: support for a non-parametric signal estimation method

    Energy Technology Data Exchange (ETDEWEB)

    Constantinescu, C C; Yoder, K K; Normandin, M D; Morris, E D [Department of Radiology, Indiana University School of Medicine, Indianapolis, IN (United States); Kareken, D A [Department of Neurology, Indiana University School of Medicine, Indianapolis, IN (United States); Bouman, C A [Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN (United States); O' Connor, S J [Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN (United States)], E-mail: emorris@iupui.edu

    2008-03-07

    We previously developed a model-independent technique (non-parametric ntPET) for extracting the transient changes in neurotransmitter concentration from paired (rest and activation) PET studies with a receptor ligand. To provide support for our method, we introduced three hypotheses of validation based on work by Endres and Carson (1998 J. Cereb. Blood Flow Metab. 18 1196-210) and Yoder et al (2004 J. Nucl. Med. 45 903-11), and tested them on experimental data. All three hypotheses describe relationships between the estimated free (synaptic) dopamine curves (F{sup DA}(t)) and the change in binding potential ({delta}BP). The veracity of the F{sup DA}(t) curves recovered by nonparametric ntPET is supported when the data adhere to the following hypothesized behaviors: (1) {delta}BP should decline with increasing DA peak time, (2) {delta}BP should increase as the strength of the temporal correlation between F{sup DA}(t) and the free raclopride (F{sup RAC}(t)) curve increases, (3) {delta}BP should decline linearly with the effective weighted availability of the receptor sites. We analyzed regional brain data from 8 healthy subjects who received two [{sup 11}C]raclopride scans: one at rest, and one during which unanticipated IV alcohol was administered to stimulate dopamine release. For several striatal regions, nonparametric ntPET was applied to recover F{sup DA}(t), and binding potential values were determined. Kendall rank-correlation analysis confirmed that the F{sup DA}(t) data followed the expected trends for all three validation hypotheses. Our findings lend credence to our model-independent estimates of F{sup DA}(t). Application of nonparametric ntPET may yield important insights into how alterations in timing of dopaminergic neurotransmission are involved in the pathologies of addiction and other psychiatric disorders.

  17. Estimating preferences for local public services using migration data.

    Science.gov (United States)

    Dahlberg, Matz; Eklöf, Matias; Fredriksson, Peter; Jofre-Monseny, Jordi

    2012-01-01

    Using Swedish micro data, the paper examines the impact of local public services on community choice. The choice of community is modelled as a choice between a discrete set of alternatives. It is found that, given taxes, high spending on child care attracts migrants. Less conclusive results are obtained with respect to the role of spending on education and elderly care. High local taxes deter migrants. Relaxing the independence of the irrelevant alternatives assumption, by estimating a mixed logit model, has a significant impact on the results.

  18. From neurons to circuits: linear estimation of local field potentials

    Science.gov (United States)

    Rasch, Malte; Logthetis, Nikos K.; Kreiman, Gabriel

    2010-01-01

    Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons. PMID:19889990

  19. FEH Local: Improving flood estimates using historical data

    Directory of Open Access Journals (Sweden)

    Prosdocimi Ilaria

    2016-01-01

    Full Text Available The traditional approach to design flood estimation (for example, to derive the 100-year flood is to apply a statistical model to time series of peak river flow measured by gauging stations. Such records are typically not very long, for example in the UK only about 10% of the stations have records that are more than 50 years in length. Along-explored way to augment the data available from a gauging station is to derive information about historical flood events and paleo-floods, which can be obtained from careful exploration of archives, old newspapers, flood marks or other signs of past flooding that are still discernible in the catchment, and the history of settlements. The inclusion of historical data in flood frequency estimation has been shown to substantially reduce the uncertainty around the estimated design events and is likely to provide insight into the rarest events which might have pre-dated the relatively short systematic records. Among other things, the FEH Local project funded by the Environment Agency aims to develop methods to easily incorporate historical information into the standard method of statistical flood frequency estimation in the UK. Different statistical estimation procedures are explored, namely maximum likelihood and partial probability weighted moments, and the strengths and weaknesses of each method are investigated. The project assesses the usefulness of historical data and aims to provide practitioners with useful guidelines to indicate in what circumstances the inclusion of historical data is likely to be beneficial in terms of reducing both the bias and the variability of the estimated flood frequency curves. The guidelines are based on the results of a large Monte Carlo simulation study, in which different estimation procedures and different data availability scenarios are studied. The study provides some indication of the situations under which different estimation procedures might give a better performance.

  20. Local and global nonlinear dynamics of a parametrically excited rectangular symmetric cross-ply laminated composite plate

    International Nuclear Information System (INIS)

    Ye Min; Lu Jing; Zhang Wei; Ding Qian

    2005-01-01

    The present investigation deals with nonlinear dynamic behavior of a parametrically excited simply supported rectangular symmetric cross-ply laminated composite thin plate for the first time. The governing equation of motion for rectangular symmetric cross-ply laminated composite thin plate is derived by using von Karman equation. The geometric nonlinearity and nonlinear damping are included in the governing equations of motion. The Galerkin approach is used to obtain a two-degree-of-freedom nonlinear system under parametric excitation. The method of multiple scales is utilized to transform the second-order non-autonomous differential equations to the first-order averaged equations. Using numerical method, the averaged equations are analyzed to obtain the steady state bifurcation responses. The analysis of stability for steady state bifurcation responses in laminated composite thin plate is also given. Under certain conditions laminated composite thin plate may have two or multiple steady state bifurcation solutions. Jumping phenomenon occurs in the steady state bifurcation solutions. The chaotic motions of rectangular symmetric cross-ply laminated composite thin plate are also found by using numerical simulation. The results obtained here demonstrate that the periodic, quasi-periodic and chaotic motions coexist for a parametrically excited fore-edge simply supported rectangular symmetric cross-ply laminated composite thin plate under certain conditions

  1. Towards local progression estimation of pulmonary emphysema using CT.

    Science.gov (United States)

    Staring, M; Bakker, M E; Stolk, J; Shamonin, D P; Reiber, J H C; Stoel, B C

    2014-02-01

    Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying linearity assumption

  2. Towards local progression estimation of pulmonary emphysema using CT

    International Nuclear Information System (INIS)

    Staring, M.; Bakker, M. E.; Shamonin, D. P.; Reiber, J. H. C.; Stoel, B. C.; Stolk, J.

    2014-01-01

    Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying

  3. GPS/DR Error Estimation for Autonomous Vehicle Localization.

    Science.gov (United States)

    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.

  4. 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.

  5. Estimation of local rainfall erosivity using artificial neural network

    Directory of Open Access Journals (Sweden)

    Paulo Tarso Sanches Oliveira

    2011-08-01

    Full Text Available The information retrieval of local values of rainfall erosivity is essential for soil loss estimation with the Universal Soil Loss Equation (USLE, and thus is very useful in soil and water conservation planning. In this manner, the objective of this study was to develop an Artificial Neural Network (ANN with the capacity of estimating, with satisfactory accuracy, the rainfall erosivity in any location of the Mato Grosso do Sul state. We used data from rain erosivity, latitude, longitude, altitude of pluviometric and pluviographic stations located in the state to train and test an ANN. After training with various network configurations, we selected the best performance and higher coefficient of determination calculated on the basis of data erosivity of the sample test and the values estimated by ANN. In evaluating the results, the confidence and the agreement indices were used in addition to the coefficient of determination. It was found that it is possible to estimate the rainfall erosivity for any location in the state of Mato Grosso do Sul, in a reliable way, using only data of geographical coordinates and altitude.

  6. Towards local progression estimation of pulmonary emphysema using CT

    Energy Technology Data Exchange (ETDEWEB)

    Staring, M., E-mail: m.staring@lumc.nl; Bakker, M. E.; Shamonin, D. P.; Reiber, J. H. C.; Stoel, B. C. [Department of Radiology, Division of Image Processing, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden (Netherlands); Stolk, J. [Department of Pulmonology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden (Netherlands)

    2014-02-15

    Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying

  7. SU-E-T-598: Parametric Equation for Quick and Reliable Estimate of Stray Neutron Doses in Proton Therapy and Application for Intracranial Tumor Treatments

    Energy Technology Data Exchange (ETDEWEB)

    Bonfrate, A; Farah, J; Sayah, R; Clairand, I [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-roses (France); De Marzi, L; Delacroix, S [Institut Curie Centre de Protontherapie d Orsay (CPO), Orsay (France); Herault, J [Centre Antoine Lacassagne (CAL) Cyclotron biomedical, Nice (France); Lee, C [National Cancer Institute, Rockville, MD (United States); Bolch, W [Univ Florida, Gainesville, FL (United States)

    2015-06-15

    Purpose: Development of a parametric equation suitable for a daily use in routine clinic to provide estimates of stray neutron doses in proton therapy. Methods: Monte Carlo (MC) calculations using the UF-NCI 1-year-old phantom were exercised to determine the variation of stray neutron doses as a function of irradiation parameters while performing intracranial treatments. This was done by individually changing the proton beam energy, modulation width, collimator aperture and thickness, compensator thickness and the air gap size while their impact on neutron doses were put into a single equation. The variation of neutron doses with distance from the target volume was also included in it. Then, a first step consisted in establishing the fitting coefficients by using 221 learning data which were neutron absorbed doses obtained with MC simulations while a second step consisted in validating the final equation. Results: The variation of stray neutron doses with irradiation parameters were fitted with linear, polynomial, etc. model while a power-law model was used to fit the variation of stray neutron doses with the distance from the target volume. The parametric equation fitted well MC simulations while establishing fitting coefficients as the discrepancies on the estimate of neutron absorbed doses were within 10%. The discrepancy can reach ∼25% for the bladder, the farthest organ from the target volume. Finally, the validation showed results in compliance with MC calculations since the discrepancies were also within 10% for head-and-neck and thoracic organs while they can reach ∼25%, again for pelvic organs. Conclusion: The parametric equation presents promising results and will be validated for other target sites as well as other facilities to go towards a universal method.

  8. Dose-response curve estimation: a semiparametric mixture approach.

    Science.gov (United States)

    Yuan, Ying; Yin, Guosheng

    2011-12-01

    In the estimation of a dose-response curve, parametric models are straightforward and efficient but subject to model misspecifications; nonparametric methods are robust but less efficient. As a compromise, we propose a semiparametric approach that combines the advantages of parametric and nonparametric curve estimates. In a mixture form, our estimator takes a weighted average of the parametric and nonparametric curve estimates, in which a higher weight is assigned to the estimate with a better model fit. When the parametric model assumption holds, the semiparametric curve estimate converges to the parametric estimate and thus achieves high efficiency; when the parametric model is misspecified, the semiparametric estimate converges to the nonparametric estimate and remains consistent. We also consider an adaptive weighting scheme to allow the weight to vary according to the local fit of the models. We conduct extensive simulation studies to investigate the performance of the proposed methods and illustrate them with two real examples. © 2011, The International Biometric Society.

  9. Estimating Preferences for Treatments in Patients With Localized Prostate Cancer

    International Nuclear Information System (INIS)

    Ávila, Mónica; Becerra, Virginia; Guedea, Ferran; Suárez, José Francisco; Fernandez, Pablo; Macías, Víctor; Mariño, Alfonso

    2015-01-01

    Purpose: Studies of patients' preferences for localized prostate cancer treatments have assessed radical prostatectomy and external radiation therapy, but none of them has evaluated brachytherapy. The aim of our study was to assess the preferences and willingness to pay of patients with localized prostate cancer who had been treated with radical prostatectomy, external radiation therapy, or brachytherapy, and their related urinary, sexual, and bowel side effects. Methods and Materials: This was an observational, prospective cohort study with follow-up until 5 years after treatment. A total of 704 patients with low or intermediate risk localized prostate cancer were consecutively recruited from 2003 to 2005. The estimation of preferences was conducted using time trade-off, standard gamble, and willingness-to-pay methods. Side effects were measured with the Expanded Prostate Index Composite (EPIC), a prostate cancer-specific questionnaire. Tobit models were constructed to assess the impact of treatment and side effects on patients' preferences. Propensity score was applied to adjust for treatment selection bias. Results: Of the 580 patients reporting preferences, 165 were treated with radical prostatectomy, 152 with external radiation therapy, and 263 with brachytherapy. Both time trade-off and standard gamble results indicated that the preferences of patients treated with brachytherapy were 0.06 utilities higher than those treated with radical prostatectomy (P=.01). Similarly, willingness-to-pay responses showed a difference of €57/month (P=.004) between these 2 treatments. Severe urinary incontinence presented an independent impact on the preferences elicited (P<.05), whereas no significant differences were found by bowel and sexual side effects. Conclusions: Our findings indicate that urinary incontinence is the side effect with the highest impact on preferences and that brachytherapy and external radiation therapy are more valued than radical

  10. Estimating Preferences for Treatments in Patients With Localized Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Ávila, Mónica [Health Services Research Unit, IMIM (Hospital del Mar Medical Research Institute), Barcelona (Spain); CIBER en Epidemiología y Salud Pública (CIBERESP) (Spain); Universitat Pompeu Fabra, Barcelona (Spain); Becerra, Virginia [Health Services Research Unit, IMIM (Hospital del Mar Medical Research Institute), Barcelona (Spain); Guedea, Ferran [Servicio de Oncología Radioterápica, Institut Català d' Oncologia, L' Hospitalet de Llobregat (Spain); Suárez, José Francisco [Servicio de Urología, Hospital Universitari de Bellvitge, L' Hospitalet de Llobregat (Spain); Fernandez, Pablo [Servicio de Oncología Radioterápica, Instituto Oncológico de Guipúzcoa, San Sebastián (Spain); Macías, Víctor [Servicio de Oncología Radioterápica, Hospital Clínico Universitario de Salamanca, Salamanca (Spain); Servicio de Oncología Radioterápica, Institut Oncologic del Valles-Hospital General de Catalunya, Sant Cugat del Vallès (Spain); Mariño, Alfonso [Servicio de Oncología Radioterápica, Centro Oncológico de Galicia, A Coruña (Spain); and others

    2015-02-01

    Purpose: Studies of patients' preferences for localized prostate cancer treatments have assessed radical prostatectomy and external radiation therapy, but none of them has evaluated brachytherapy. The aim of our study was to assess the preferences and willingness to pay of patients with localized prostate cancer who had been treated with radical prostatectomy, external radiation therapy, or brachytherapy, and their related urinary, sexual, and bowel side effects. Methods and Materials: This was an observational, prospective cohort study with follow-up until 5 years after treatment. A total of 704 patients with low or intermediate risk localized prostate cancer were consecutively recruited from 2003 to 2005. The estimation of preferences was conducted using time trade-off, standard gamble, and willingness-to-pay methods. Side effects were measured with the Expanded Prostate Index Composite (EPIC), a prostate cancer-specific questionnaire. Tobit models were constructed to assess the impact of treatment and side effects on patients' preferences. Propensity score was applied to adjust for treatment selection bias. Results: Of the 580 patients reporting preferences, 165 were treated with radical prostatectomy, 152 with external radiation therapy, and 263 with brachytherapy. Both time trade-off and standard gamble results indicated that the preferences of patients treated with brachytherapy were 0.06 utilities higher than those treated with radical prostatectomy (P=.01). Similarly, willingness-to-pay responses showed a difference of €57/month (P=.004) between these 2 treatments. Severe urinary incontinence presented an independent impact on the preferences elicited (P<.05), whereas no significant differences were found by bowel and sexual side effects. Conclusions: Our findings indicate that urinary incontinence is the side effect with the highest impact on preferences and that brachytherapy and external radiation therapy are more valued than radical

  11. Search-free license plate localization based on saliency and local variance estimation

    Science.gov (United States)

    Safaei, Amin; Tang, H. L.; Sanei, S.

    2015-02-01

    In recent years, the performance and accuracy of automatic license plate number recognition (ALPR) systems have greatly improved, however the increasing number of applications for such systems have made ALPR research more challenging than ever. The inherent computational complexity of search dependent algorithms remains a major problem for current ALPR systems. This paper proposes a novel search-free method of localization based on the estimation of saliency and local variance. Gabor functions are then used to validate the choice of candidate license plate. The algorithm was applied to three image datasets with different levels of complexity and the results compared with a number of benchmark methods, particularly in terms of speed. The proposed method outperforms the state of the art methods and can be used for real time applications.

  12. Deriving local demand for stumpage from estimates of regional supply and demand.

    Science.gov (United States)

    Kent P. Connaughton; Gerard A. Majerus; David H. Jackson

    1989-01-01

    The local (Forest-level or local-area) demand for stumpage can be derived from estimates of regional supply and demand. The derivation of local demand is justified when the local timber economy is similar to the regional timber economy; a simple regression of local on nonlocal prices can be used as an empirical test of similarity between local and regional economies....

  13. Estimation of the limit of detection with a bootstrap-derived standard error by a partly non-parametric approach. Application to HPLC drug assays

    DEFF Research Database (Denmark)

    Linnet, Kristian

    2005-01-01

    Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...

  14. Estimation of trace metal contents in locally-baked breads

    International Nuclear Information System (INIS)

    Khalid, N.; Rehman, S.

    2013-01-01

    In order to establish base line levels, estimation of some essential trace metals (Cu, Fe, Mn and Zn) has been conducted in four brands of fifteen locally baked breads of Rawalpindi /Islamabad area employing Atomic Absorption Spectrophotometry (AAS). The samples were digested in a mixture of nitric acid and perchloric acid and the analysis was done with air-acetylene flame. The reliability of the procedure employed was verify by analyzing Standard Reference Material, i.e., wheat flour (NBS-SRM-1567) for its Cu, Fe, Mn and Zn contents which were in good agreement with the certified values. The results revealed that brown breads contained higher amount of Fe 177.3 micro g g/sup -1/and Zn 19.27 micro g g/sup -1/while levels of Cu 21.90 micro g g/-sup 1/was found higher in the samples of plain bread. The determined metal concentrations in the bread samples were compared with the reported values for other countries. The effect of kneading/baking/slicing processes on the concentration levels of these metals was also studied. The daily intake of these metals through this source was calculated and compared with the recommended dietary allowance. (author)

  15. A Robust Parametric Technique for Multipath Channel Estimation in the Uplink of a DS-CDMA System

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available The problem of estimating the multipath channel parameters of a new user entering the uplink of an asynchronous direct sequence-code division multiple access (DS-CDMA system is addressed. The problem is described via a least squares (LS cost function with a rich structure. This cost function, which is nonlinear with respect to the time delays and linear with respect to the gains of the multipath channel, is proved to be approximately decoupled in terms of the path delays. Due to this structure, an iterative procedure of 1D searches is adequate for time delays estimation. The resulting method is computationally efficient, does not require any specific pilot signal, and performs well for a small number of training symbols. Simulation results show that the proposed technique offers a better estimation accuracy compared to existing related methods, and is robust to multiple access interference.

  16. Influence of Battery Parametric Uncertainties on the State-of-Charge Estimation of Lithium Titanate Oxide-Based Batteries

    DEFF Research Database (Denmark)

    Stroe, Ana-Irina; Meng, Jinhao; Stroe, Daniel-Ioan

    2018-01-01

    to describe the battery dynamics. The SOC estimation method proposed in this paper is based on an Extended Kalman Filter (EKF) and nonlinear battery model which was parameterized using extended laboratory tests performed on several 13 Ah lithium titanate oxide (LTO)-based lithium-ion batteries. The developed......State of charge (SOC) is one of the most important parameters in battery management systems, as it indicates the available battery capacity at every moment. There are numerous battery model-based methods used for SOC estimation, the accuracy of which depends on the accuracy of the model considered...... a sensitivity analysis it was showed that the SOC and voltage estimation error are only slightly dependent on the variation of the battery model parameters with the SOC....

  17. Brain F-18 FDG PET for localization of epileptogenic zones in frontal lobe epilepsy: visual assessment and statistical parametric mapping analysis

    International Nuclear Information System (INIS)

    Kim, Yu Kyeong; Lee, Dong Soo; Lee, Sang Kun; Chung, Chun Kee; Yeo, Jeong Seok; Chung, June Key; Lee, Myung Chul

    2001-01-01

    We evaluated the sensitivity of the F-18 FDG PET by visual assessment and statistical parametric mapping (SPM) analysis for the localization of the epileptogenic zones in frontal lobe epilepsy. Twenty-four patients with frontal lobe epilepsy were examined. All patients exhibited improvements after surgical resection (Engel class I or II). Upon pathological examination, 18 patients revealed cortical dysplasia, 4 patients revealed tumor, and 2 patients revealed cortical scar. The hypometabolic lesions were found in F-18 FDG PET by visual assessment and SPM analysis. On SPM analysis, cutoff threshold was changed. MRI showed structural lesions in 12 patients and normal results in the remaining 12. F-18 FDG PET correctly localized epileptogenic zones in 13 patients (54%) by visual assessment. Sensitivity of F-18 FDG PET in MR-negative patients (50%) was similar to that in MR-positive patients (67%). On SPM analysis, sensitivity deceased according to the decrease of p value. Using uncorrected p value of 0.05 as threshold, sensitivity of SPM analysis was 63%, which was not statistically different from that of visual assessment. F-18 FDG PET was sensitive in finding epileptogenic zones by revealing hypometabolic areas even in MR-negative patients with frontal lobe epilepsy as well as in MR-positive patients. SPM analysis showed comparable sensitivity to visual assessment and could be used as an aid in the diagnosis of epileptogenic zones in frontal lobe epilepsy

  18. Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI.

    Science.gov (United States)

    Kratochvíla, Jiří; Jiřík, Radovan; Bartoš, Michal; Standara, Michal; Starčuk, Zenon; Taxt, Torfinn

    2016-03-01

    One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup. © 2015 Wiley Periodicals, Inc.

  19. Direct estimation of functionals of density operators by local operations and classical communication

    International Nuclear Information System (INIS)

    Alves, Carolina Moura; Horodecki, Pawel; Oi, Daniel K. L.; Kwek, L. C.; Ekert, Artur K.

    2003-01-01

    We present a method of direct estimation of important properties of a shared bipartite quantum state, within the ''distant laboratories'' paradigm, using only local operations and classical communication. We apply this procedure to spectrum estimation of shared states, and locally implementable structural physical approximations to incompletely positive maps. This procedure can also be applied to the estimation of channel capacity and measures of entanglement

  20. Evaluation of geostatistical parameters based on well tests; Estimation de parametres geostatistiques a partir de tests de puits

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, Y.

    1997-10-20

    Geostatistical tools are increasingly used to model permeability fields in subsurface reservoirs, which are considered as a particular random variable development depending of several geostatistical parameters such as variance and correlation length. The first part of the thesis is devoted to the study of relations existing between the transient well pressure (the well test) and the stochastic permeability field, using the apparent permeability concept.The well test performs a moving permeability average over larger and larger volume with increasing time. In the second part, the geostatistical parameters are evaluated using well test data; a Bayesian framework is used and parameters are estimated using the maximum likelihood principle by maximizing the well test data probability density function with respect to these parameters. This method, involving a well test fast evaluation, provides an estimation of the correlation length and the variance over different realizations of a two-dimensional permeability field

  1. SPECIES-SPECIFIC FOREST VARIABLE ESTIMATION USING NON-PARAMETRIC MODELING OF MULTI-SPECTRAL PHOTOGRAMMETRIC POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    J. Bohlin

    2012-07-01

    Full Text Available The recent development in software for automatic photogrammetric processing of multispectral aerial imagery, and the growing nation-wide availability of Digital Elevation Model (DEM data, are about to revolutionize data capture for forest management planning in Scandinavia. Using only already available aerial imagery and ALS-assessed DEM data, raster estimates of the forest variables mean tree height, basal area, total stem volume, and species-specific stem volumes were produced and evaluated. The study was conducted at a coniferous hemi-boreal test site in southern Sweden (lat. 58° N, long. 13° E. Digital aerial images from the Zeiss/Intergraph Digital Mapping Camera system were used to produce 3D point-cloud data with spectral information. Metrics were calculated for 696 field plots (10 m radius from point-cloud data and used in k-MSN to estimate forest variables. For these stands, the tree height ranged from 1.4 to 33.0 m (18.1 m mean, stem volume from 0 to 829 m3 ha-1 (249 m3 ha-1 mean and basal area from 0 to 62.2 m2 ha-1 (26.1 m2 ha-1 mean, with mean stand size of 2.8 ha. Estimates made using digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet showed RMSEs (in percent of the surveyed stand mean of 7.5% for tree height, 11.4% for basal area, 13.2% for total stem volume, 90.6% for pine stem volume, 26.4 for spruce stem volume, and 72.6% for deciduous stem volume. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.

  2. Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics

    Science.gov (United States)

    Welch, Stephen M.; White, Jeffrey W.; Thorp, Kelly R.; Bello, Nora M.

    2018-01-01

    Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP’s) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP’s as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10−6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP’s becomes a robust means to help solve the genotype-to-phenotype problem in crops. PMID:29672629

  3. Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

    KAUST Repository

    Douglas, Craig C.; Lee, Hyoseop; Sheen, Dongwoo

    2010-01-01

    We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Fréchet derivative when calculating the Jacobian matrix. We analyze

  4. Localization of periodic orbits of polynomial systems by ellipsoidal estimates

    International Nuclear Information System (INIS)

    Starkov, Konstantin E.; Krishchenko, Alexander P.

    2005-01-01

    In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered

  5. Estimation of the lifetime distribution of mechatronic systems in the presence of a covariate: A comparison among parametric, semiparametric and nonparametric models

    International Nuclear Information System (INIS)

    Bobrowski, Sebastian; Chen, Hong; Döring, Maik; Jensen, Uwe; Schinköthe, Wolfgang

    2015-01-01

    In practice manufacturers may have lots of failure data of similar products using the same technology basis under different operating conditions. Thus, one can try to derive predictions for the distribution of the lifetime of newly developed components or new application environments through the existing data using regression models based on covariates. Three categories of such regression models are considered: a parametric, a semiparametric and a nonparametric approach. First, we assume that the lifetime is Weibull distributed, where its parameters are modelled as linear functions of the covariate. Second, the Cox proportional hazards model, well-known in Survival Analysis, is applied. Finally, a kernel estimator is used to interpolate between empirical distribution functions. In particular the last case is new in the context of reliability analysis. We propose a goodness of fit measure (GoF), which can be applied to all three types of regression models. Using this GoF measure we discuss a new model selection procedure. To illustrate this method of reliability prediction, the three classes of regression models are applied to real test data of motor experiments. Further the performance of the approaches is investigated by Monte Carlo simulations. - Highlights: • We estimate the lifetime distribution in the presence of a covariate. • Three types of regression models are considered and compared. • A new nonparametric estimator based on our particular data structure is introduced. • We propose a goodness of fit measure and show a new model selection procedure. • A case study with real data and Monte Carlo simulations are performed

  6. A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem

    KAUST Repository

    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.

  7. Localization of periodic orbits of polynomial systems by ellipsoidal estimates

    Energy Technology Data Exchange (ETDEWEB)

    Starkov, Konstantin E. [CITEDI-IPN, Avenue del Parque 1310, Mesa de Otay, Tijuana, BC (Mexico)]. E-mail: konst@citedi.mx; Krishchenko, Alexander P. [Bauman Moscow State Technical University, 2nd Baumanskaya Street, 5, Moscow 105005 (Russian Federation)]. E-mail: apkri@999.ru

    2005-02-01

    In this paper we study the localization problem of periodic orbits of multidimensional continuous-time systems in the global setting. Our results are based on the solution of the conditional extremum problem and using sign-definite quadratic and quartic forms. As examples, the Rikitake system and the Lamb's equations for a three-mode operating cavity in a laser are considered.

  8. Parallelized Local Volatility Estimation Using GP-GPU Hardware Acceleration

    KAUST Repository

    Douglas, Craig C.

    2010-01-01

    We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Fréchet derivative when calculating the Jacobian matrix. We analyze the existence of the Fréchet derivative and its numerical computation. To reduce the computational time of the inverse problem, a GP-GPU environment is considered for parallel computation. Numerical results confirm the validity and efficiency of the proposed method. ©2010 IEEE.

  9. FEH Local: improving flood estimates using historical data

    OpenAIRE

    Prosdocimi, Ilaria; Stewart, Lisa; Faulkner, Duncan; Mitchell, Chrissy

    2016-01-01

    The traditional approach to design flood estimation (for example, to derive the 100-year flood) is to apply a statistical model to time series of peak river flow measured by gauging stations. Such records are typically not very long, for example in the UK only about 10% of the stations have records that are more than 50 years in length. Along-explored way to augment the data available from a gauging station is to derive information about historical flood events and paleo-floods, which can be ...

  10. Influence of the aircraft crash induced local nonlinearities on the overall dynamic response of a RC structure through a parametric study

    International Nuclear Information System (INIS)

    Rouzaud, C.; Gatuingt, F.; Hervé, G.; Moussallam, N.; Dorival, O.

    2016-01-01

    Highlights: • Structures could resist to the induced accelerations which they might undergo. • The characterization of non-linearities in the signal of an aircraft impact. • The non linear impact area are studied through a sensitivity analysis. • This analysis should allow to achieve a link between aircraft impact parameters. - Abstract: In the process of nuclear power plant design, the safety of structures is an important aspect. Civil engineering structures have to resist the accelerations induced by, for example, seismic loads or shaking loads resulting from the aircraft impact. This is even more important for the in-structures equipments that have also to be qualified against the vibrations generated by this kind of hazards. In the case of aircraft crash, as a large variety of scenarios has to be envisaged, it is necessary to use methods that are less CPU-time consuming and that consider appropriately the nonlinearities. The analysis presented in this paper deals with the problem of the characterization of nonlinearities (damaged area, transmitted force) in the response of a structure subjected to an aircraft impact. The purpose of our study is part of the development of a new decoupled nonlinear and elastic way for calculating the shaking of structures following an aircraft impact which could be very numerically costly if studied with classical finite element methods. The aim is to identify which parameters control the dimensions of the nonlinear zone and so will have a direct impact on the induced vibrations. In a design context, several load cases (and simulations) are analyzed in order to consider a wide range of impact (different loading surfaces, momentum) and data sets of the target (thickness, reinforcements). In this work, the nonlinear area generated by the impact is localized and studied through a parametric analysis associated with a sensitivity analysis to identify the boundaries between the elastic domain and this nonlinear area.

  11. Multi-person localization and orientation estimation in volumetric scene reconstructions

    NARCIS (Netherlands)

    Liem, M.C.

    2014-01-01

    Accurate localization of persons and estimation of their pose are important topics in current-day computer vision research. As part of the pose estimation, estimating the body orientation of a person (i.e. rotation around torso major axis) conveys important information about the person's current

  12. Noise measurement from magnitude MRI using local estimates of variance and skewness

    International Nuclear Information System (INIS)

    Rajan, Jeny; Poot, Dirk; Juntu, Jaber; Sijbers, Jan

    2010-01-01

    In this note, we address the estimation of the noise level in magnitude magnetic resonance (MR) images in the absence of background data. Most of the methods proposed earlier exploit the Rayleigh distributed background region in MR images to estimate the noise level. These methods, however, cannot be used for images where no background information is available. In this note, we propose two different approaches for noise level estimation in the absence of the image background. The first method is based on the local estimation of the noise variance using maximum likelihood estimation and the second method is based on the local estimation of the skewness of the magnitude data distribution. Experimental results on synthetic and real MR image datasets show that the proposed estimators accurately estimate the noise level in a magnitude MR image, even without background data. (note)

  13. Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.

    Science.gov (United States)

    Ding, A Adam; Wu, Hulin

    2014-10-01

    We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.

  14. Distancing from experienced self: how global versus local perception affects estimation of psychological distance

    NARCIS (Netherlands)

    Liberman, N.; Förster, J.

    2009-01-01

    In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition).

  15. An age estimation method using brain local features for T1-weighted images.

    Science.gov (United States)

    Kondo, Chihiro; Ito, Koichi; Kai Wu; Sato, Kazunori; Taki, Yasuyuki; Fukuda, Hiroshi; Aoki, Takafumi

    2015-08-01

    Previous statistical analysis studies using large-scale brain magnetic resonance (MR) image databases have examined that brain tissues have age-related morphological changes. This fact indicates that one can estimate the age of a subject from his/her brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features extracted from T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into local regions defined by the automated anatomical labeling atlas. The proposed method selects optimal local regions to improve the performance of age estimation. We evaluate performance of the proposed method using 1,146 T1-weighted images from a Japanese MR image database. We also discuss the medical implication of selected optimal local regions.

  16. Optimal Attitude Estimation and Filtering Without Using Local Coordinates Part I: Uncontrolled and Deterministic Attitude Dynamics

    OpenAIRE

    Sanyal, Amit K.

    2005-01-01

    There are several attitude estimation algorithms in existence, all of which use local coordinate representations for the group of rigid body orientations. All local coordinate representations of the group of orientations have associated problems. While minimal coordinate representations exhibit kinematic singularities for large rotations, the quaternion representation requires satisfaction of an extra constraint. This paper treats the attitude estimation and filtering problem as an optimizati...

  17. Estimating organic, local, and other price premiums in the Hawaii fluid milk market.

    Science.gov (United States)

    Loke, Matthew K; Xu, Xun; Leung, PingSun

    2015-04-01

    With retail scanner data, we applied hedonic price modeling to explore price premiums for organic, local, and other product attributes of fluid milk in Hawaii. Within the context of revealed preference, this analysis of organic and local attributes, under a single unified framework, is significant, as research in this area is deficient in the existing literature. This paper finds both organic and local attributes delivered price premiums over imported, conventional, whole fluid milk. However, the estimated price premium for organic milk (24.6%) is significantly lower than findings in the existing literature. Likewise, the price premium for the local attribute is estimated at 17.4%, again substantially lower compared with an earlier, stated preference study in Hawaii. Beyond that, we estimated a robust price premium of 19.7% for nutritional benefits claimed. The magnitude of this estimated coefficient reinforces the notion that nutrition information on food is deemed beneficial and valuable. Finally, package size measures the influence of product weight. With each larger package size, the estimate led to a corresponding larger price discount. This result is consistent with the practice of weight discounting that retailers usually offer with fresh packaged food. Additionally, we estimated a fairly high Armington elasticity of substitution, which suggests a relatively high degree of substitution between local and imported fluid milk when their relative price changes. Overall, this study establishes price premiums for organic, local, and nutrition benefits claimed for fluid milk in Hawaii. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  18. Estimating the financial resources needed for local public health departments in Minnesota: a multimethod approach.

    Science.gov (United States)

    Riley, William; Briggs, Jill; McCullough, Mac

    2011-01-01

    This study presents a model for determining total funding needed for individual local health departments. The aim is to determine the financial resources needed to provide services for statewide local public health departments in Minnesota based on a gaps analysis done to estimate the funding needs. We used a multimethod analysis consisting of 3 approaches to estimate gaps in local public health funding consisting of (1) interviews of selected local public health leaders, (2) a Delphi panel, and (3) a Nominal Group Technique. On the basis of these 3 approaches, a consensus estimate of funding gaps was generated for statewide projections. The study includes an analysis of cost, performance, and outcomes from 2005 to 2007 for all 87 local governmental health departments in Minnesota. For each of the methods, we selected a panel to represent a profile of Minnesota health departments. The 2 main outcome measures were local-level gaps in financial resources and total resources needed to provide public health services at the local level. The total public health expenditure in Minnesota for local governmental public health departments was $302 million in 2007 ($58.92 per person). The consensus estimate of the financial gaps in local public health departments indicates that an additional $32.5 million (a 10.7% increase or $6.32 per person) is needed to adequately serve public health needs in the local communities. It is possible to make informed estimates of funding gaps for public health activities on the basis of a combination of quantitative methods. There is a wide variation in public health expenditure at the local levels, and methods are needed to establish minimum baseline expenditure levels to adequately treat a population. The gaps analysis can be used by stakeholders to inform policy makers of the need for improved funding of the public health system.

  19. The influence of local mechanisms on large scale seismic vulnerability estimation of masonry building aggregates

    Science.gov (United States)

    Formisano, Antonio; Chieffo, Nicola; Milo, Bartolomeo; Fabbrocino, Francesco

    2016-12-01

    The current paper deals with the seismic vulnerability evaluation of masonry constructions grouped in aggregates through an "ad hoc" quick vulnerability form based on new assessment parameters considering local collapse mechanisms. First, a parametric kinematic analysis on masonry walls with different height (h) / thickness (t) ratios has been developed with the purpose of identifying the collapse load multiplier for activation of the main four first-order failure mechanisms. Subsequently, a form initially conceived for building aggregates suffering second-mode collapse mechanisms, has been expanded on the basis of the achieved results. Tre proposed quick vulnerability technique has been applied to one case study within the territory of Arsita (Teramo, Italy) and, finally, it has been also validated by the comparison of results with those deriving from application of the well-known FaMIVE procedure.

  20. Estimating 3D tilt from local image cues in natural scenes

    OpenAIRE

    Burge, Johannes; McCann, Brian C.; Geisler, Wilson S.

    2016-01-01

    Estimating three-dimensional (3D) surface orientation (slant and tilt) is an important first step toward estimating 3D shape. Here, we examine how three local image cues from the same location (disparity gradient, luminance gradient, and dominant texture orientation) should be combined to estimate 3D tilt in natural scenes. We collected a database of natural stereoscopic images with precisely co-registered range images that provide the ground-truth distance at each pixel location. We then ana...

  1. Estimating local noise power spectrum from a few FBP-reconstructed CT scans

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, Rongping, E-mail: rongping.zeng@fda.hhs.gov; Gavrielides, Marios A.; Petrick, Nicholas; Sahiner, Berkman; Li, Qin; Myers, Kyle J. [Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH, FDA, Silver Spring, Maryland 20993 (United States)

    2016-01-15

    Purpose: Traditional ways to estimate 2D CT noise power spectrum (NPS) involve an ensemble average of the power spectrums of many noisy scans. When only a few scans are available, regions of interest are often extracted from different locations to obtain sufficient samples to estimate the NPS. Using image samples from different locations ignores the nonstationarity of CT noise and thus cannot accurately characterize its local properties. The purpose of this work is to develop a method to estimate local NPS using only a few fan-beam CT scans. Methods: As a result of FBP reconstruction, the CT NPS has the same radial profile shape for all projection angles, with the magnitude varying with the noise level in the raw data measurement. This allows a 2D CT NPS to be factored into products of a 1D angular and a 1D radial function in polar coordinates. The polar separability of CT NPS greatly reduces the data requirement for estimating the NPS. The authors use this property and derive a radial NPS estimation method: in brief, the radial profile shape is estimated from a traditional NPS based on image samples extracted at multiple locations. The amplitudes are estimated by fitting the traditional local NPS to the estimated radial profile shape. The estimated radial profile shape and amplitudes are then combined to form a final estimate of the local NPS. We evaluate the accuracy of the radial NPS method and compared it to traditional NPS methods in terms of normalized mean squared error (NMSE) and signal detectability index. Results: For both simulated and real CT data sets, the local NPS estimated with no more than six scans using the radial NPS method was very close to the reference NPS, according to the metrics of NMSE and detectability index. Even with only two scans, the radial NPS method was able to achieve a fairly good accuracy. Compared to those estimated using traditional NPS methods, the accuracy improvement was substantial when a few scans were available

  2. Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

    KAUST Repository

    Camilo, Daniela Castro

    2017-10-02

    In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

  3. Local likelihood estimation of complex tail dependence structures in high dimensions, applied to US precipitation extremes

    KAUST Repository

    Camilo, Daniela Castro; Huser, Raphaë l

    2017-01-01

    In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.

  4. Wind Speed Estimation and Parametrization of Wake Models for Downregulated Offshore Wind Farms within the scope of PossPOW Project

    DEFF Research Database (Denmark)

    Göçmen Bozkurt, Tuhfe; Giebel, Gregor; Poulsen, Niels Kjølstad

    2014-01-01

    With increasing installed capacity, wind farms are requested to downregulate more frequently, especially in the offshore environment. Determination and verification of possible (or available) power of downregulated offshore wind farms are the aims of the PossPOW project (see PossPOW.dtu.dk). Two ...... period. The re-calibrated model has to be further parametrized to include dynamic effects such as wind direction variability and meandering also considering different averaging time scales before implemented in full scale wind farms....

  5. Distancing from experienced self: how global-versus-local perception affects estimation of psychological distance.

    Science.gov (United States)

    Liberman, Nira; Förster, Jens

    2009-08-01

    In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition). Relative to the control condition, global processing made participants estimate larger psychological distances in time (Study 1), space (Study 2), social distance (Study 3), and hypotheticality (Study 4). Local processing had the opposite effect. Consistent with CLT, all studies show that the effect of global-versus-local processing did emerge when participants estimated egocentric distances, which are distances from the experienced self in the here and now, but did not emerge with temporal distances not from now (Study 1), spatial distances not from here (Study 2), social distances not from the self (Study 3), or hypothetical events that did not involve altering an experienced reality (Study 4).

  6. Optimal parametric modelling of measured short waves

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    the importance of selecting a suitable sampling interval for better estimates of parametric modelling and also for better statistical representation. Implementation of the above algorithms in a structural monitoring system has the potential advantage of storing...

  7. LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions

    Directory of Open Access Journals (Sweden)

    Weihua An

    2016-07-01

    Full Text Available LARF is an R package that provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument (i.e., the treatment inducement are binary. The method (Abadie 2003 involves two steps. First, pseudo-weights are constructed from the probability of receiving the treatment inducement. By default LARF estimates the probability by a probit regression. It also provides semiparametric power series estimation of the probability and allows users to employ other external methods to estimate the probability. Second, the pseudo-weights are used to estimate the local average response function conditional on treatment and covariates. LARF provides both least squares and maximum likelihood estimates of the conditional treatment effects.

  8. Indoor Localization and Radio Map Estimation using Unsupervised Manifold Alignment with Geometry Perturbation

    KAUST Repository

    Majeed, Khaqan; Sorour, Sameh; Al-Naffouri, Tareq Y.; Valaee, Shahrokh

    2015-01-01

    The Received Signal Strength (RSS) based fingerprinting approaches for indoor localization pose a need for updating the fingerprint databases due to dynamic nature of the indoor environment. This process is hectic and time-consuming when the size of the indoor area is large. The semi-supervised approaches reduce this workload and achieve good accuracy around 15% of the fingerprinting load but the performance is severely degraded if it is reduced below this level. We propose an indoor localization framework that uses unsupervised manifold alignment. It requires only 1% of the fingerprinting load, some crowd sourced readings and plan coordinates of the indoor area. The 1% fingerprinting load is used only in perturbing the local geometries of the plan coordinates. The proposed framework achieves less than 5m mean localization error, which is considerably better than semi-supervised approaches at very small amount of fingerprinting load. In addition, the few location estimations together with few fingerprints help to estimate the complete radio map of the indoor environment. The estimation of radio map does not demand extra workload rather it employs the already available information from the proposed indoor localization framework. The testing results for radio map estimation show almost 50% performance improvement by using this information as compared to using only fingerprints.

  9. Application of Matrix Pencil Algorithm to Mobile Robot Localization Using Hybrid DOA/TOA Estimation

    Directory of Open Access Journals (Sweden)

    Lan Anh Trinh

    2012-12-01

    Full Text Available Localization plays an important role in robotics for the tasks of monitoring, tracking and controlling a robot. Much effort has been made to address robot localization problems in recent years. However, despite many proposed solutions and thorough consideration, in terms of developing a low-cost and fast processing method for multiple-source signals, the robot localization problem is still a challenge. In this paper, we propose a solution for robot localization with regards to these concerns. In order to locate the position of a robot, both the coordinate and the orientation of a robot are necessary. We develop a localization method using the Matrix Pencil (MP algorithm for hybrid detection of direction of arrival (DOA and time of arrival (TOA. TOA of the signal is estimated for computing the distance between the mobile robot and a base station (BS. Based on the distance and the estimated DOA, we can estimate the mobile robot's position. The characteristics of the algorithm are examined through analysing simulated experiments and the results demonstrate the advantages of our method over previous works in dealing with the above challenges. The method is constructed based on the low-cost infrastructure of radio frequency devices; the DOA/TOA estimation is performed with just single value decomposition for fast processing. Finally, the MP algorithm combined with tracking using a Kalman filter allows our proposed method to locate the positions of multiple source signals.

  10. Indoor Localization and Radio Map Estimation using Unsupervised Manifold Alignment with Geometry Perturbation

    KAUST Repository

    Majeed, Khaqan

    2015-12-22

    The Received Signal Strength (RSS) based fingerprinting approaches for indoor localization pose a need for updating the fingerprint databases due to dynamic nature of the indoor environment. This process is hectic and time-consuming when the size of the indoor area is large. The semi-supervised approaches reduce this workload and achieve good accuracy around 15% of the fingerprinting load but the performance is severely degraded if it is reduced below this level. We propose an indoor localization framework that uses unsupervised manifold alignment. It requires only 1% of the fingerprinting load, some crowd sourced readings and plan coordinates of the indoor area. The 1% fingerprinting load is used only in perturbing the local geometries of the plan coordinates. The proposed framework achieves less than 5m mean localization error, which is considerably better than semi-supervised approaches at very small amount of fingerprinting load. In addition, the few location estimations together with few fingerprints help to estimate the complete radio map of the indoor environment. The estimation of radio map does not demand extra workload rather it employs the already available information from the proposed indoor localization framework. The testing results for radio map estimation show almost 50% performance improvement by using this information as compared to using only fingerprints.

  11. Estimating local atmosphere-surface fluxes using eddy covariance and numerical Ogive optimization

    DEFF Research Database (Denmark)

    Sievers, Jakob; Papakyriakou, Tim; Larsen, Søren

    2014-01-01

    Estimating representative surface-fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modeling efforts, low-frequency cont......Estimating representative surface-fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modeling efforts, low...

  12. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection.

    OpenAIRE

    Kim, Sanghong; Kano, Manabu; Nakagawa, Hiroshi; Hasebe, Shinji

    2011-01-01

    Development of quality estimation models using near infrared spectroscopy (NIRS) and multivariate analysis has been accelerated as a process analytical technology (PAT) tool in the pharmaceutical industry. Although linear regression methods such as partial least squares (PLS) are widely used, they cannot always achieve high estimation accuracy because physical and chemical properties of a measuring object have a complex effect on NIR spectra. In this research, locally weighted PLS (LW-PLS) wh...

  13. A Robust Localization, Slip Estimation, and Compensation System for WMR in the Indoor Environments

    Directory of Open Access Journals (Sweden)

    Zakir Ullah

    2018-05-01

    Full Text Available A novel approach is proposed for the path tracking of a Wheeled Mobile Robot (WMR in the presence of an unknown lateral slip. Much of the existing work has assumed pure rolling conditions between the wheel and ground. Under the pure rolling conditions, the wheels of a WMR are supposed to roll without slipping. Complex wheel-ground interactions, acceleration and steering system noise are the factors which cause WMR wheel slip. A basic research problem in this context is localization and slip estimation of WMR from a stream of noisy sensors data when the robot is moving on a slippery surface, or moving at a high speed. DecaWave based ranging system and Particle Filter (PF are good candidates to estimate the location of WMR indoors and outdoors. Unfortunately, wheel-slip of WMR limits the ultimate performance that can be achieved by real-world implementation of the PF, because location estimation systems typically partially rely on the robot heading. A small error in the WMR heading leads to a large error in location estimation of the PF because of its cumulative nature. In order to enhance the tracking and localization performance of the PF in the environments where the main reason for an error in the PF location estimation is angular noise, two methods were used for heading estimation of the WMR (1: Reinforcement Learning (RL and (2: Location-based Heading Estimation (LHE. Trilateration is applied to DecaWave based ranging system for calculating the probable location of WMR, this noisy location along with PF current mean is used to estimate the WMR heading by using the above two methods. Beside the WMR location calculation, DecaWave based ranging system is also used to update the PF weights. The localization and tracking performance of the PF is significantly improved through incorporating heading error in localization by applying RL and LHE. Desired trajectory information is then used to develop an algorithm for extracting the lateral slip along

  14. On Parametric (and Non-Parametric Variation

    Directory of Open Access Journals (Sweden)

    Neil Smith

    2009-11-01

    Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.

  15. Estimation of local concentration from measurements of stochastic adsorption dynamics using carbon nanotube-based sensors

    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.

  16. A Parametric k-Means Algorithm

    Science.gov (United States)

    Tarpey, Thaddeus

    2007-01-01

    Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

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

    Directory of Open Access Journals (Sweden)

    Cailing Wang

    2016-02-01

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

  18. Assessing pupil and school performance by non-parametric and parametric techniques

    NARCIS (Netherlands)

    de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.

    2010-01-01

    This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall

  19. Experimental Verification of a Vehicle Localization based on Moving Horizon Estimation Integrating LRS and Odometry

    International Nuclear Information System (INIS)

    Sakaeta, Kuniyuki; Nonaka, Kenichiro; Sekiguchi, Kazuma

    2016-01-01

    Localization is an important function for the robots to complete various tasks. For localization, both internal and external sensors are used generally. The odometry is widely used as the method based on the internal sensors, but it suffers from cumulative errors. In the method using the laser range sensor (LRS) which is a kind of external sensor, the estimation accuracy is affected by the number of available measurement data. In our previous study, we applied moving horizon estimation (MHE) to the vehicle localization for integrating the LRS measurement data and the odometry information where the weightings of them are balanced relatively adapting to the number of the available LRS measurement data. In this paper, the effectiveness of the proposed localization method is verified through both numerical simulations and experiments using a 1/10 scale vehicle. The verification is conducted in the situations where the vehicle position cannot be localized uniquely on a certain direction using the LRS measurement data only. We achieve accurate localization even in such a situation by integrating the odometry and LRS based on MHE. We also show the superiority of the method through comparisons with a method using extended Kalman filter (EKF). (paper)

  20. ALTERNATIVE METHODOLOGIES FOR THE ESTIMATION OF LOCAL POINT DENSITY INDEX: MOVING TOWARDS ADAPTIVE LIDAR DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-07-01

    Full Text Available Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification. Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for

  1. Estimating the Health and Economic Impacts of Changes in Local Air Quality

    Science.gov (United States)

    Carvour, Martha L.; Hughes, Amy E.; Fann, Neal

    2018-01-01

    Objectives. To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration–response and health–economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences. Methods. We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas–Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level. Results. Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data. Conclusions. BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities. PMID:29698094

  2. Local scattering property scales flow speed estimation in laser speckle contrast imaging

    International Nuclear Information System (INIS)

    Miao, Peng; Chao, Zhen; Feng, Shihan; Ji, Yuanyuan; Yu, Hang; Thakor, Nitish V; Li, Nan

    2015-01-01

    Laser speckle contrast imaging (LSCI) has been widely used in in vivo blood flow imaging. However, the effect of local scattering property (scattering coefficient µ s ) on blood flow speed estimation has not been well investigated. In this study, such an effect was quantified and involved in relation between speckle autocorrelation time τ c and flow speed v based on simulation flow experiments. For in vivo blood flow imaging, an improved estimation strategy was developed to eliminate the estimation bias due to the inhomogeneous distribution of the scattering property. Compared to traditional LSCI, a new estimation method significantly suppressed the imaging noise and improves the imaging contrast of vasculatures. Furthermore, the new method successfully captured the blood flow changes and vascular constriction patterns in rats’ cerebral cortex from normothermia to mild and moderate hypothermia. (letter)

  3. Using local multiplicity to improve effect estimation from a hypothesis-generating pharmacogenetics study.

    Science.gov (United States)

    Zou, W; Ouyang, H

    2016-02-01

    We propose a multiple estimation adjustment (MEA) method to correct effect overestimation due to selection bias from a hypothesis-generating study (HGS) in pharmacogenetics. MEA uses a hierarchical Bayesian approach to model individual effect estimates from maximal likelihood estimation (MLE) in a region jointly and shrinks them toward the regional effect. Unlike many methods that model a fixed selection scheme, MEA capitalizes on local multiplicity independent of selection. We compared mean square errors (MSEs) in simulated HGSs from naive MLE, MEA and a conditional likelihood adjustment (CLA) method that model threshold selection bias. We observed that MEA effectively reduced MSE from MLE on null effects with or without selection, and had a clear advantage over CLA on extreme MLE estimates from null effects under lenient threshold selection in small samples, which are common among 'top' associations from a pharmacogenetics HGS.

  4. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Science.gov (United States)

    Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

    2018-03-01

    We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  5. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Directory of Open Access Journals (Sweden)

    Jinchao Feng

    2018-03-01

    Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

  6. Improvement of least-squares collocation error estimates using local GOCE Tzz signal standard deviations

    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...

  7. Local Recurrence of Hepatocellular Carcinoma after Segmental Transarterial Chemoembolization: Risk Estimates Based on Multiple Prognostic Factors

    International Nuclear Information System (INIS)

    Park, Seung Hyun; Cho, Yun Ku; Ahn, Yong Sik; Park, Yoon Ok; Kim, Jae Kyun; Chung, Jin Wook

    2007-01-01

    To determine the prognostic factors for local recurrence of nodular hepatocellular carcinoma after segmental transarterial chemoembolization. Seventy-four nodular hepatocellular carcinoma tumors ≤5 cm were retrospectively analyzed for local recurrence after segmental transarterial chemoembolization using follow-up CT images (median follow-up of 17 months, 4 77 months in range). The tumors were divided into four groups (IA, IB, IIA, and IIB) according to whether the one-month follow-up CT imaging, after segmental transarterial chemoembolization, showed homogeneous (Group I) or inhomogeneous (Group II) iodized oil accumulation, or whether the tumors were located within the liver segment (Group A) or in a segmental border zone (Group B). Comparison of tumor characteristics between Group IA and the other three groups was performed using the chi-square test. Local recurrence rates were compared among the groups using the Kaplan-Meier estimation and log rank test. Local tumor recurrence occurred in 19 hepatocellular carcinoma tumors (25.7%). There were: 28, 18, 17, and 11 tumors in Group IA, IB, IIA, and IIB, respectively. One of 28 (3.6%) tumors in Group IA, and 18 of 46 (39.1%) tumors in the other three groups showed local recurrence. Comparisons between Group IA and the other three groups showed that the tumor characteristics were similar. One-, two-, and three-year estimated local recurrence rates in Group IA were 0%, 11.1%, and 11.1%, respectively. The difference between Group IA and the other three groups was statistically significant (p 0.000). An acceptably low rate of local recurrence was observed for small or intermediate nodular tumors located within the liver segment with homogeneous iodized oil accumulation

  8. Using LUCAS topsoil database to estimate soil organic carbon content in local spectral libraries

    Science.gov (United States)

    Castaldi, Fabio; van Wesemael, Bas; Chabrillat, Sabine; Chartin, Caroline

    2017-04-01

    The quantification of the soil organic carbon (SOC) content over large areas is mandatory to obtain accurate soil characterization and classification, which can improve site specific management at local or regional scale exploiting the strong relationship between SOC and crop growth. The estimation of the SOC is not only important for agricultural purposes: in recent years, the increasing attention towards global warming highlighted the crucial role of the soil in the global carbon cycle. In this context, soil spectroscopy is a well consolidated and widespread method to estimate soil variables exploiting the interaction between chromophores and electromagnetic radiation. The importance of spectroscopy in soil science is reflected by the increasing number of large soil spectral libraries collected in the world. These large libraries contain soil samples derived from a consistent number of pedological regions and thus from different parent material and soil types; this heterogeneity entails, in turn, a large variability in terms of mineralogical and organic composition. In the light of the huge variability of the spectral responses to SOC content and composition, a rigorous classification process is necessary to subset large spectral libraries and to avoid the calibration of global models failing to predict local variation in SOC content. In this regard, this study proposes a method to subset the European LUCAS topsoil database into soil classes using a clustering analysis based on a large number of soil properties. The LUCAS database was chosen to apply a standardized multivariate calibration approach valid for large areas without the need for extensive field and laboratory work for calibration of local models. Seven soil classes were detected by the clustering analyses and the samples belonging to each class were used to calibrate specific partial least square regression (PLSR) models to estimate SOC content of three local libraries collected in Belgium (Loam belt

  9. Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels.

    Science.gov (United States)

    Schwartz, Joel; Bind, Marie-Abele; Koutrakis, Petros

    2017-01-01

    Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking. We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations. Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed. We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50). We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA

  10. The impact of local public services and geographical cost of living differences on poverty estimates

    OpenAIRE

    Aaberge, Rolf; Langørgen, Audun; Mogstad, Magne; Østensen, Marit

    2008-01-01

    Abstract: Despite a broad consensus on the need to account for the value of public services and geographical cost of living differences on the measurement of poverty, there is little reliable evidence on how these factors actually affect poverty estimates. Unlike the standard approach in studies of the distribution of public services, this paper employs a method for valuing sector-specific local public services that accounts for differences between municipalities in the costs and capacity ...

  11. Methodology for estimation of secondary meteorological variables to be used in local dispersion of air pollutants

    International Nuclear Information System (INIS)

    Turtos, L.; Sanchez, M.; Roque, A.; Soltura, R.

    2003-01-01

    Methodology for estimation of secondary meteorological variables to be used in local dispersion of air pollutants. This paper include the main works, carried out into the frame of the project Atmospheric environmental externalities of the electricity generation in Cuba, aiming to develop methodologies and corresponding software, which will allow to improve the quality of the secondary meteorological data used in atmospheric pollutant calculations; specifically the wind profiles coefficient, urban and rural mixed high and temperature gradients

  12. Parametric resonance in an expanding universe

    International Nuclear Information System (INIS)

    Zlatev, I.; Huey, G.; Steinhardt, P.J.

    1998-01-01

    Parametric resonance has been discussed as a mechanism for copious particle production following inflation. Here we present a simple and intuitive calculational method for estimating the efficiency of parametric amplification as a function of parameters. This is important for determining whether resonant amplification plays an important role in the reheating process. We find that significant amplification occurs only for a limited range of couplings and interactions. copyright 1998 The American Physical Society

  13. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

    Science.gov (United States)

    Sills, Erin O; Herrera, Diego; Kirkpatrick, A Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

    2015-01-01

    Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on policies

  14. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation

    Science.gov (United States)

    Sills, Erin O.; Herrera, Diego; Kirkpatrick, A. Justin; Brandão, Amintas; Dickson, Rebecca; Hall, Simon; Pattanayak, Subhrendu; Shoch, David; Vedoveto, Mariana; Young, Luisa; Pfaff, Alexander

    2015-01-01

    Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts’ selection of best case comparisons. The synthetic control method (SCM) offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal “blacklist” that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual) scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012). This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and permutations on

  15. Estimating the Impacts of Local Policy Innovation: The Synthetic Control Method Applied to Tropical Deforestation.

    Directory of Open Access Journals (Sweden)

    Erin O Sills

    Full Text Available Quasi-experimental methods increasingly are used to evaluate the impacts of conservation interventions by generating credible estimates of counterfactual baselines. These methods generally require large samples for statistical comparisons, presenting a challenge for evaluating innovative policies implemented within a few pioneering jurisdictions. Single jurisdictions often are studied using comparative methods, which rely on analysts' selection of best case comparisons. The synthetic control method (SCM offers one systematic and transparent way to select cases for comparison, from a sizeable pool, by focusing upon similarity in outcomes before the intervention. We explain SCM, then apply it to one local initiative to limit deforestation in the Brazilian Amazon. The municipality of Paragominas launched a multi-pronged local initiative in 2008 to maintain low deforestation while restoring economic production. This was a response to having been placed, due to high deforestation, on a federal "blacklist" that increased enforcement of forest regulations and restricted access to credit and output markets. The local initiative included mapping and monitoring of rural land plus promotion of economic alternatives compatible with low deforestation. The key motivation for the program may have been to reduce the costs of blacklisting. However its stated purpose was to limit deforestation, and thus we apply SCM to estimate what deforestation would have been in a (counterfactual scenario of no local initiative. We obtain a plausible estimate, in that deforestation patterns before the intervention were similar in Paragominas and the synthetic control, which suggests that after several years, the initiative did lower deforestation (significantly below the synthetic control in 2012. This demonstrates that SCM can yield helpful land-use counterfactuals for single units, with opportunities to integrate local and expert knowledge and to test innovations and

  16. Maximum likelihood estimation-based denoising of magnetic resonance images using restricted local neighborhoods

    International Nuclear Information System (INIS)

    Rajan, Jeny; Jeurissen, Ben; Sijbers, Jan; Verhoye, Marleen; Van Audekerke, Johan

    2011-01-01

    In this paper, we propose a method to denoise magnitude magnetic resonance (MR) images, which are Rician distributed. Conventionally, maximum likelihood methods incorporate the Rice distribution to estimate the true, underlying signal from a local neighborhood within which the signal is assumed to be constant. However, if this assumption is not met, such filtering will lead to blurred edges and loss of fine structures. As a solution to this problem, we put forward the concept of restricted local neighborhoods where the true intensity for each noisy pixel is estimated from a set of preselected neighboring pixels. To this end, a reference image is created from the noisy image using a recently proposed nonlocal means algorithm. This reference image is used as a prior for further noise reduction. A scheme is developed to locally select an appropriate subset of pixels from which the underlying signal is estimated. Experimental results based on the peak signal to noise ratio, structural similarity index matrix, Bhattacharyya coefficient and mean absolute difference from synthetic and real MR images demonstrate the superior performance of the proposed method over other state-of-the-art methods.

  17. Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaoxue Feng

    2014-11-01

    Full Text Available Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS, which gets better filtering performance than NILS without constraint.

  18. Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

    Science.gov (United States)

    Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

    2014-01-01

    Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

  19. Constrained state estimation for individual localization in wireless body sensor networks.

    Science.gov (United States)

    Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

    2014-11-10

    Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint.

  20. Synthesizing Global and Local Datasets to Estimate Jurisdictional Forest Carbon Fluxes in Berau, Indonesia.

    Science.gov (United States)

    Griscom, Bronson W; Ellis, Peter W; Baccini, Alessandro; Marthinus, Delon; Evans, Jeffrey S; Ruslandi

    2016-01-01

    Forest conservation efforts are increasingly being implemented at the scale of sub-national jurisdictions in order to mitigate global climate change and provide other ecosystem services. We see an urgent need for robust estimates of historic forest carbon emissions at this scale, as the basis for credible measures of climate and other benefits achieved. Despite the arrival of a new generation of global datasets on forest area change and biomass, confusion remains about how to produce credible jurisdictional estimates of forest emissions. We demonstrate a method for estimating the relevant historic forest carbon fluxes within the Regency of Berau in eastern Borneo, Indonesia. Our method integrates best available global and local datasets, and includes a comprehensive analysis of uncertainty at the regency scale. We find that Berau generated 8.91 ± 1.99 million tonnes of net CO2 emissions per year during 2000-2010. Berau is an early frontier landscape where gross emissions are 12 times higher than gross sequestration. Yet most (85%) of Berau's original forests are still standing. The majority of net emissions were due to conversion of native forests to unspecified agriculture (43% of total), oil palm (28%), and fiber plantations (9%). Most of the remainder was due to legal commercial selective logging (17%). Our overall uncertainty estimate offers an independent basis for assessing three other estimates for Berau. Two other estimates were above the upper end of our uncertainty range. We emphasize the importance of including an uncertainty range for all parameters of the emissions equation to generate a comprehensive uncertainty estimate-which has not been done before. We believe comprehensive estimates of carbon flux uncertainty are increasingly important as national and international institutions are challenged with comparing alternative estimates and identifying a credible range of historic emissions values.

  1. Robust Non-Local TV-L1 Optical Flow Estimation with Occlusion Detection.

    Science.gov (United States)

    Zhang, Congxuan; Chen, Zhen; Wang, Mingrun; Li, Ming; Jiang, Shaofeng

    2017-06-05

    In this paper, we propose a robust non-local TV-L1 optical flow method with occlusion detection to address the problem of weak robustness of optical flow estimation with motion occlusion. Firstly, a TV-L1 form for flow estimation is defined using a combination of the brightness constancy and gradient constancy assumptions in the data term and by varying the weight under the Charbonnier function in the smoothing term. Secondly, to handle the potential risk of the outlier in the flow field, a general non-local term is added in the TV-L1 optical flow model to engender the typical non-local TV-L1 form. Thirdly, an occlusion detection method based on triangulation is presented to detect the occlusion regions of the sequence. The proposed non-local TV-L1 optical flow model is performed in a linearizing iterative scheme using improved median filtering and a coarse-to-fine computing strategy. The results of the complex experiment indicate that the proposed method can overcome the significant influence of non-rigid motion, motion occlusion, and large displacement motion. Results of experiments comparing the proposed method and existing state-of-the-art methods by respectively using Middlebury and MPI Sintel database test sequences show that the proposed method has higher accuracy and better robustness.

  2. Multiobjective Memetic Estimation of Distribution Algorithm Based on an Incremental Tournament Local Searcher

    Directory of Open Access Journals (Sweden)

    Kaifeng Yang

    2014-01-01

    Full Text Available A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  3. Multiobjective memetic estimation of distribution algorithm based on an incremental tournament local searcher.

    Science.gov (United States)

    Yang, Kaifeng; Mu, Li; Yang, Dongdong; Zou, Feng; Wang, Lei; Jiang, Qiaoyong

    2014-01-01

    A novel hybrid multiobjective algorithm is presented in this paper, which combines a new multiobjective estimation of distribution algorithm, an efficient local searcher and ε-dominance. Besides, two multiobjective problems with variable linkages strictly based on manifold distribution are proposed. The Pareto set to the continuous multiobjective optimization problems, in the decision space, is a piecewise low-dimensional continuous manifold. The regularity by the manifold features just build probability distribution model by globally statistical information from the population, yet, the efficiency of promising individuals is not well exploited, which is not beneficial to search and optimization process. Hereby, an incremental tournament local searcher is designed to exploit local information efficiently and accelerate convergence to the true Pareto-optimal front. Besides, since ε-dominance is a strategy that can make multiobjective algorithm gain well distributed solutions and has low computational complexity, ε-dominance and the incremental tournament local searcher are combined here. The novel memetic multiobjective estimation of distribution algorithm, MMEDA, was proposed accordingly. The algorithm is validated by experiment on twenty-two test problems with and without variable linkages of diverse complexities. Compared with three state-of-the-art multiobjective optimization algorithms, our algorithm achieves comparable results in terms of convergence and diversity metrics.

  4. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Directory of Open Access Journals (Sweden)

    Xujun Han

    Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  5. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Science.gov (United States)

    Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

    2015-01-01

    The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  6. Estimating rates of local species extinction, colonization and turnover in animal communities

    Science.gov (United States)

    Nichols, James D.; Boulinier, T.; Hines, J.E.; Pollock, K.H.; Sauer, J.R.

    1998-01-01

    Species richness has been identified as a useful state variable for conservation and management purposes. Changes in richness over time provide a basis for predicting and evaluating community responses to management, to natural disturbance, and to changes in factors such as community composition (e.g., the removal of a keystone species). Probabilistic capture-recapture models have been used recently to estimate species richness from species count and presence-absence data. These models do not require the common assumption that all species are detected in sampling efforts. We extend this approach to the development of estimators useful for studying the vital rates responsible for changes in animal communities over time; rates of local species extinction, turnover, and colonization. Our approach to estimation is based on capture-recapture models for closed animal populations that permit heterogeneity in detection probabilities among the different species in the sampled community. We have developed a computer program, COMDYN, to compute many of these estimators and associated bootstrap variances. Analyses using data from the North American Breeding Bird Survey (BBS) suggested that the estimators performed reasonably well. We recommend estimators based on probabilistic modeling for future work on community responses to management efforts as well as on basic questions about community dynamics.

  7. Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

    Science.gov (United States)

    Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

    2017-09-01

    Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

  8. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Science.gov (United States)

    Zhu, Aichun; Wang, Tian; Snoussi, Hichem

    2018-03-01

    This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  9. Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

    Directory of Open Access Journals (Sweden)

    Aichun Zhu

    2018-03-01

    Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

  10. Estimating local, organic, and other price premiums of shell eggs in Hawaii.

    Science.gov (United States)

    Loke, Matthew K; Xu, Xun; Leung, PingSun

    2016-05-01

    Hedonic modeling and retail scanner data were utilized to investigate the influence of local, organic, nutrition benefits, and other attributes of shell eggs on retail price premium in Hawaii. Within a revealed preference framework, the analysis of local and organic attributes, simultaneously, under a single unified setting is important, as such work is highly deficient in the published literature. This paper finds high to moderate price premiums in four key attributes of shell eggs - organic (64%), local (40%), nutrition benefits claimed (33%), and brown shell (18.4%). Large and extra-large sized eggs also experience price premiums over medium sized eggs. With each larger packing size, the estimated coefficients were negative, indicating a price discount, relative to the baseline packing size. However, there is no evidence to support the overwhelming influence of "local" over "organic", as hypothesized in other research work. Overall, the findings in this paper suggest industry producers and retailers should highlight and market effusively the primary attributes of their shell eggs, including "local", to remain competitive in the marketplace. Effective communication channels are crucial to delivering the product information, capturing the attention of consumers, and securing retail sales. © 2016 Poultry Science Association Inc.

  11. Estimating the mass of the Local Group using machine learning applied to numerical simulations

    Science.gov (United States)

    McLeod, M.; Libeskind, N.; Lahav, O.; Hoffman, Y.

    2017-12-01

    We present a new approach to calculating the combined mass of the Milky Way (MW) and Andromeda (M31), which together account for the bulk of the mass of the Local Group (LG). We base our work on an ensemble of 30,190 halo pairs from the Small MultiDark simulation, assuming a ΛCDM (Cosmological Constant and Cold Dark Matter) cosmology. This is used in conjunction with machine learning methods (artificial neural networks, ANN) to investigate the relationship between the mass and selected parameters characterising the orbit and local environment of the binary. ANN are employed to take account of additional physics arising from interactions with larger structures or dynamical effects which are not analytically well understood. Results from the ANN are most successful when the velocity shear is provided, which demonstrates the flexibility of machine learning to model physical phenomena and readily incorporate new information. The resulting estimate for the Local Group mass, when shear information is included, is 4.9×1012Msolar, with an error of ±0.8×1012Msolar from the 68% uncertainty in observables, and a r.m.s. scatter interval of +1.7‑1.3×1012Msolar estimated scatter from the differences between the model estimates and simulation masses for a testing sample of halo pairs. We also consider a recently reported large relative transverse velocity of M31 and the Milky Way, and produce an alternative mass estimate of 3.6±0.3+2.1‑1.3×1012Msolar. Although the methods used predict similar values for the most likely mass of the LG, application of ANN compared to the traditional Timing Argument reduces the scatter in the log mass by approximately half when tested on samples from the simulation.

  12. Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection.

    Science.gov (United States)

    Kim, Sanghong; Kano, Manabu; Nakagawa, Hiroshi; Hasebe, Shinji

    2011-12-15

    Development of quality estimation models using near infrared spectroscopy (NIRS) and multivariate analysis has been accelerated as a process analytical technology (PAT) tool in the pharmaceutical industry. Although linear regression methods such as partial least squares (PLS) are widely used, they cannot always achieve high estimation accuracy because physical and chemical properties of a measuring object have a complex effect on NIR spectra. In this research, locally weighted PLS (LW-PLS) which utilizes a newly defined similarity between samples is proposed to estimate active pharmaceutical ingredient (API) content in granules for tableting. In addition, a statistical wavelength selection method which quantifies the effect of API content and other factors on NIR spectra is proposed. LW-PLS and the proposed wavelength selection method were applied to real process data provided by Daiichi Sankyo Co., Ltd., and the estimation accuracy was improved by 38.6% in root mean square error of prediction (RMSEP) compared to the conventional PLS using wavelengths selected on the basis of variable importance on the projection (VIP). The results clearly show that the proposed calibration modeling technique is useful for API content estimation and is superior to the conventional one. Copyright © 2011 Elsevier B.V. All rights reserved.

  13. A constrained polynomial regression procedure for estimating the local False Discovery Rate

    Directory of Open Access Journals (Sweden)

    Broët Philippe

    2007-06-01

    Full Text Available Abstract Background In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR, which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The lFDR not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (FDR for subsets of genes. Results In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the lFDR is described. The results of a simulation study indicated good performances for the proposed estimator in comparison to four published ones. The five different procedures were applied to real datasets. Conclusion A novel and efficient procedure for estimating lFDR was developed and evaluated.

  14. Anxiety and dysthymia: local prevalence estimates based on drug prescriptions by general practitioners in Turin (Italy).

    Science.gov (United States)

    Mamo, C; Farina, E; Cicio, R; Fanì, M

    2014-01-01

    The aim of the study was to obtain local estimates of the prevalence of anxiety and dysthymic disorders among attendees of primary care at local level, useful to pursue a better management of the health care services. The study was conducted in the Health District no. 2 of Turin (industrial town in northwest Italy). The criteria for identification of cases were based on the drugs prescriptions made by general practitioners (GPs), selected in order to assure high specificity. The study involved 86 physicians (with 87,885 attendees). As expected, the crude and standardized prevalences were higher in women (anxiety: 2.9% vs 1.3% in men; dysthymia: 3.8% vs 1.7% in men), with a peak in women aged over 75 yrs (anxiety: 4.8%; dysthymia: 6.2%). In comparison to male GPs, female GPs had an higher prevalence of patients with anxious disorders, whereas the prevalences of dysthymia were similar. Despite the discussed limitations, the used methodology allows to obtain sufficiently reliable estimates of prevalence of common mental disorders at local level, providing informations useful for organizing the primary care in the Health district.

  15. Fatigue Strength Estimation Based on Local Mechanical Properties for Aluminum Alloy FSW Joints

    Directory of Open Access Journals (Sweden)

    Kittima Sillapasa

    2017-02-01

    Full Text Available Overall fatigue strengths and hardness distributions of the aluminum alloy similar and dissimilar friction stir welding (FSW joints were determined. The local fatigue strengths as well as local tensile strengths were also obtained by using small round bar specimens extracted from specific locations, such as the stir zone, heat affected zone, and base metal. It was found from the results that fatigue fracture of the FSW joint plate specimen occurred at the location of the lowest local fatigue strength as well as the lowest hardness, regardless of microstructural evolution. To estimate the fatigue strengths of aluminum alloy FSW joints from the hardness measurements, the relationship between fatigue strength and hardness for aluminum alloys was investigated based on the present experimental results and the available wide range of data from the references. It was found as: σa (R = −1 = 1.68 HV (σa is in MPa and HV has no unit. It was also confirmed that the estimated fatigue strengths were in good agreement with the experimental results for aluminum alloy FSW joints.

  16. Position Estimation and Local Mapping Using Omnidirectional Images and Global Appearance Descriptors

    Directory of Open Access Journals (Sweden)

    Yerai Berenguer

    2015-10-01

    Full Text Available This work presents some methods to create local maps and to estimate the position of a mobile robot, using the global appearance of omnidirectional images. We use a robot that carries an omnidirectional vision system on it. Every omnidirectional image acquired by the robot is described only with one global appearance descriptor, based on the Radon transform. In the work presented in this paper, two different possibilities have been considered. In the first one, we assume the existence of a map previously built composed of omnidirectional images that have been captured from previously-known positions. The purpose in this case consists of estimating the nearest position of the map to the current position of the robot, making use of the visual information acquired by the robot from its current (unknown position. In the second one, we assume that we have a model of the environment composed of omnidirectional images, but with no information about the location of where the images were acquired. The purpose in this case consists of building a local map and estimating the position of the robot within this map. Both methods are tested with different databases (including virtual and real images taking into consideration the changes of the position of different objects in the environment, different lighting conditions and occlusions. The results show the effectiveness and the robustness of both methods.

  17. A test for Improvement of high resolution Quantitative Precipitation Estimation for localized heavy precipitation events

    Science.gov (United States)

    Lee, Jung-Hoon; Roh, Joon-Woo; Park, Jeong-Gyun

    2017-04-01

    Accurate estimation of precipitation is one of the most difficult and significant tasks in the area of weather diagnostic and forecasting. In the Korean Peninsula, heavy precipitations are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. In addition to, various geographical and topographical elements make production of temporal and spatial distribution of precipitation is very complicated. Especially, localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances. In weather radar data with high temporal and spatial resolution, accurate estimation of rain rate from radar reflectivity data is too difficult. Z-R relationship (Marshal and Palmer 1948) have adapted representatively. In addition to, several methods such as support vector machine (SVM), neural network, Fuzzy logic, Kriging were utilized in order to improve the accuracy of rain rate. These methods show the different quantitative precipitation estimation (QPE) and the performances of accuracy are different for heavy precipitation cases. In this study, in order to improve the accuracy of QPE for localized heavy precipitation, ensemble method for Z-R relationship and various techniques was tested. This QPE ensemble method was developed by a concept based on utilizing each advantage of precipitation calibration methods. The ensemble members were produced for a combination of different Z-R coefficient and calibration method.

  18. The estimation of local marine dispersion of radionuclides from hydrographic survey data

    International Nuclear Information System (INIS)

    Maul, P.R.

    1985-05-01

    One of the most important stages in the assessment of the radiological impact of routine discharges of activity to the sea is the estimation of the local dispersion characteristics. Existing methods for defining the parameters required by the computer program CODAR2 are expanded to take into account the significance of the turbulence generated by the discharge, the effect of a shelving sea bed and the variation with time of the lateral dispersion coefficient. These methods also enable the importance of the timing of discharges and the variation of radionuclide concentrations along the coast to be considered. Calculations of local marine dispersion depend directly upon the information that is available from hydrographic surveys. Detailed consideration is given to the definition of model parameter values from data that are generally available from such surveys. The uncertainties involved in mathematical modelling and parameter specification suggest that the long term average radionuclide concentration in the vicinity of the release can be estimated to within a factor of 2 or 3, with estimates more likely to be greater than, rather than less than the actual value. This uncertainty will contribute to the net uncertainty in any radiological assessment of critical group exposure. (author)

  19. Motivations of parametric studies

    International Nuclear Information System (INIS)

    Birac, C.

    1988-01-01

    The paper concerns the motivations of parametric studies in connection with the Programme for the Inspection of Steel Components PISC II. The objective of the PISC II exercise is to evaluate the effectiveness of current and advanced NDT techniques for inspection of reactor pressure vessel components. The parametric studies were initiated to determine the influence of some parameters on defect detection and dimensioning, and to increase the technical bases of the Round Robin Tests. A description is given of the content of the parametric studies including:- the effect of the defects' characteristics, the effect of equipment characteristics, the effect of cladding, and possible use of electromagnetic techniques. (U.K.)

  20. The variance of the locally measured Hubble parameter explained with different estimators

    DEFF Research Database (Denmark)

    Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

    2017-01-01

    We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

  1. Estimating risks of importation and local transmission of Zika virus infection

    Directory of Open Access Journals (Sweden)

    Kyeongah Nah

    2016-04-01

    Full Text Available Background. An international spread of Zika virus (ZIKV infection has attracted global attention. ZIKV is conveyed by a mosquito vector, Aedes species, which also acts as the vector species of dengue and chikungunya viruses. Methods. Arrival time of ZIKV importation (i.e., the time at which the first imported case was diagnosed in each imported country was collected from publicly available data sources. Employing a survival analysis model in which the hazard is an inverse function of the effective distance as informed by the airline transportation network data, and using dengue and chikungunya virus transmission data, risks of importation and local transmission were estimated. Results. A total of 78 countries with imported case(s have been identified, with the arrival time ranging from 1 to 44 weeks since the first ZIKV was identified in Brazil, 2015. Whereas the risk of importation was well explained by the airline transportation network data, the risk of local transmission appeared to be best captured by additionally accounting for the presence of dengue and chikungunya viruses. Discussion. The risk of importation may be high given continued global travel of mildly infected travelers but, considering that the public health concerns over ZIKV infection stems from microcephaly, it is more important to focus on the risk of local and widespread transmission that could involve pregnant women. The predicted risk of local transmission was frequently seen in tropical and subtropical countries with dengue or chikungunya epidemic experience.

  2. Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

    Science.gov (United States)

    Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

    2011-01-01

    Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

  3. A Local Stable Bootstrap for Power Variations of Pure-Jump Semimartingales and Activity Index Estimation

    DEFF Research Database (Denmark)

    Hounyo, Ulrich; Varneskov, Rasmus T.

    We provide a new resampling procedure - the local stable bootstrap - that is able to mimic the dependence properties of realized power variations for pure-jump semimartingales observed at different frequencies. This allows us to propose a bootstrap estimator and inference procedure for the activity...... index of the underlying process, β, as well as a bootstrap test for whether it obeys a jump-diffusion or a pure-jump process, that is, of the null hypothesis H₀: β=2 against the alternative H₁: βbootstrap power variations, activity index...... estimator, and diffusion test for H0. Moreover, the finite sample size and power properties of the proposed diffusion test are compared to those of benchmark tests using Monte Carlo simulations. Unlike existing procedures, our bootstrap test is correctly sized in general settings. Finally, we illustrate use...

  4. A method for estimating the local area economic damages of Superfund waste sites

    International Nuclear Information System (INIS)

    Walker, D.R.

    1992-01-01

    National Priority List (NPL) sites, or more commonly called Superfund sites, are hazardous waste sites (HWS) deemed by the Environmental Protection Agency (EPA) to impose the greatest risks to human health or welfare or to the environment. HWS are placed and ranked for cleanup on the NPL based on a score derived from the Hazard Ranking System (HRS), which is a scientific assessment of the health and environmental risks posed by HWS. A concern of the HRS is that the rank of sites is not based on benefit-cost analysis. The main objective of this dissertation is to develop a method for estimating the local area economic damages associated with Superfund waste sites. Secondarily, the model is used to derive county-level damage estimates for use in ranking the county level damages from Superfund sites. The conceptual model used to describe the damages associated with Superfund sites is a household-firm location decision model. In this model assumes that households and firms make their location choice based on the local level of wages, rents and amenities. The model was empirically implemented using 1980 census microdata on households and workers in 253 counties across the US. The household sample includes data on the value and structural characteristics of homes. The worker sample includes the annual earnings of workers and a vector worker attributes. The microdata was combined with county level amenity data, including the number of Superfund sites. The hedonic pricing technique was used to estimate the effect of Superfund sites on average annual wages per household and on monthly expenditures on housing. The results show that Superfund sites impose statistically significant damages on households. The annual county damages from Superfund sites for a sample of 151 counties was over 14 billion dollars. The ranking of counties using the damage estimates is correlated with the rank of counties using the HRS

  5. Digital spectral analysis parametric, non-parametric and advanced methods

    CERN Document Server

    Castanié, Francis

    2013-01-01

    Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature.The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models.An entire chapter is devoted to the non-parametric methods most widely used in industry.High resolution methods a

  6. ROBUST: an interactive FORTRAN-77 package for exploratory data analysis using parametric, ROBUST and nonparametric location and scale estimates, data transformations, normality tests, and outlier assessment

    Science.gov (United States)

    Rock, N. M. S.

    ROBUST calculates 53 statistics, plus significance levels for 6 hypothesis tests, on each of up to 52 variables. These together allow the following properties of the data distribution for each variable to be examined in detail: (1) Location. Three means (arithmetic, geometric, harmonic) are calculated, together with the midrange and 19 high-performance robust L-, M-, and W-estimates of location (combined, adaptive, trimmed estimates, etc.) (2) Scale. The standard deviation is calculated along with the H-spread/2 (≈ semi-interquartile range), the mean and median absolute deviations from both mean and median, and a biweight scale estimator. The 23 location and 6 scale estimators programmed cover all possible degrees of robustness. (3) Normality: Distributions are tested against the null hypothesis that they are normal, using the 3rd (√ h1) and 4th ( b 2) moments, Geary's ratio (mean deviation/standard deviation), Filliben's probability plot correlation coefficient, and a more robust test based on the biweight scale estimator. These statistics collectively are sensitive to most usual departures from normality. (4) Presence of outliers. The maximum and minimum values are assessed individually or jointly using Grubbs' maximum Studentized residuals, Harvey's and Dixon's criteria, and the Studentized range. For a single input variable, outliers can be either winsorized or eliminated and all estimates recalculated iteratively as desired. The following data-transformations also can be applied: linear, log 10, generalized Box Cox power (including log, reciprocal, and square root), exponentiation, and standardization. For more than one variable, all results are tabulated in a single run of ROBUST. Further options are incorporated to assess ratios (of two variables) as well as discrete variables, and be concerned with missing data. Cumulative S-plots (for assessing normality graphically) also can be generated. The mutual consistency or inconsistency of all these measures

  7. Efficient Characterization of Parametric Uncertainty of Complex (Biochemical Networks.

    Directory of Open Access Journals (Sweden)

    Claudia Schillings

    2015-08-01

    Full Text Available Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

  8. A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution.

    Science.gov (United States)

    Lee, Duncan; Rushworth, Alastair; Sahu, Sujit K

    2014-06-01

    Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models. © 2014, The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  9. Distributed Input and State Estimation Using Local Information in Heterogeneous Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dzung Tran

    2017-07-01

    Full Text Available A new distributed input and state estimation architecture is introduced and analyzed for heterogeneous sensor networks. Specifically, nodes of a given sensor network are allowed to have heterogeneous information roles in the sense that a subset of nodes can be active (that is, subject to observations of a process of interest and the rest can be passive (that is, subject to no observation. Both fixed and varying active and passive roles of sensor nodes in the network are investigated. In addition, these nodes are allowed to have non-identical sensor modalities under the common underlying assumption that they have complimentary properties distributed over the sensor network to achieve collective observability. The key feature of our framework is that it utilizes local information not only during the execution of the proposed distributed input and state estimation architecture but also in its design in that global uniform ultimate boundedness of error dynamics is guaranteed once each node satisfies given local stability conditions independent from the graph topology and neighboring information of these nodes. As a special case (e.g., when all nodes are active and a positive real condition is satisfied, the asymptotic stability can be achieved with our algorithm. Several illustrative numerical examples are further provided to demonstrate the efficacy of the proposed architecture.

  10. Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

    Science.gov (United States)

    Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

    2017-09-01

    Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

  11. Nonlinear estimation-based dipole source localization for artificial lateral line systems

    International Nuclear Information System (INIS)

    Abdulsadda, Ahmad T; Tan Xiaobo

    2013-01-01

    As a flow-sensing organ, the lateral line system plays an important role in various behaviors of fish. An engineering equivalent of a biological lateral line is of great interest to the navigation and control of underwater robots and vehicles. A vibrating sphere, also known as a dipole source, can emulate the rhythmic movement of fins and body appendages, and has been widely used as a stimulus in the study of biological lateral lines. Dipole source localization has also become a benchmark problem in the development of artificial lateral lines. In this paper we present two novel iterative schemes, referred to as Gauss–Newton (GN) and Newton–Raphson (NR) algorithms, for simultaneously localizing a dipole source and estimating its vibration amplitude and orientation, based on the analytical model for a dipole-generated flow field. The performance of the GN and NR methods is first confirmed with simulation results and the Cramer–Rao bound (CRB) analysis. Experiments are further conducted on an artificial lateral line prototype, consisting of six millimeter-scale ionic polymer–metal composite sensors with intra-sensor spacing optimized with CRB analysis. Consistent with simulation results, the experimental results show that both GN and NR schemes are able to simultaneously estimate the source location, vibration amplitude and orientation with comparable precision. Specifically, the maximum localization error is less than 5% of the body length (BL) when the source is within the distance of one BL. Experimental results have also shown that the proposed schemes are superior to the beamforming method, one of the most competitive approaches reported in literature, in terms of accuracy and computational efficiency. (paper)

  12. Static roll-tilt over 5 minutes locally distorts the internal estimate of direction of gravity.

    Science.gov (United States)

    Tarnutzer, A A; Bockisch, C J; Straumann, D; Marti, S; Bertolini, G

    2014-12-01

    The subjective visual vertical (SVV) indicates perceived direction of gravity. Even in healthy human subjects, roll angle-dependent misestimations, roll overcompensation (A-effect, head-roll > 60° and head-roll tilt, SVV estimates when upright are biased toward the preceding roll position, which indicates that perceived vertical (PV) is shifted by the prior tilt (Tarnutzer AA, Bertolini G, Bockisch CJ, Straumann D, Marti S. PLoS One 8: e78079, 2013). Hypothetically, PV in any roll position could be biased toward the previous roll position. We asked whether such a "global" bias occurs or whether the bias is "local". The SVV of healthy human subjects (N = 9) was measured in nine roll positions (-120° to +120°, steps = 30°) after 5 min of roll-tilt in one of two adaptation positions (±90°) and compared with control trials without adaptation. After adapting, adjustments were shifted significantly (P tilted positions (±30°, ±60°) and upright only. We computationally simulated errors based on the sum of a monotonically increasing function (producing roll undercompensation) and a mixture of Gaussian functions (representing roll overcompensation centered around PV). In combination, the pattern of A- and E-effects could be generated. By shifting the function representing local overcompensation toward the adaptation position, the experimental postadaptation data could be fitted successfully. We conclude that prolonged roll-tilt locally distorts PV rather than globally shifting it. Short-term adaptation of roll overcompensation may explain these shifts and could reflect the brain's strategy to optimize SVV estimates around recent roll positions. Thus postural stability can be improved by visually-mediated compensatory responses at any sustained body-roll orientation. Copyright © 2014 the American Physiological Society.

  13. Robust Estimation of Value-at-Risk through Distribution-Free and Parametric Approaches Using the Joint Severity and Frequency Model: Applications in Financial, Actuarial, and Natural Calamities Domains

    Directory of Open Access Journals (Sweden)

    Sabyasachi Guharay

    2017-07-01

    Full Text Available Value-at-Risk (VaR is a well-accepted risk metric in modern quantitative risk management (QRM. The classical Monte Carlo simulation (MCS approach, denoted henceforth as the classical approach, assumes the independence of loss severity and loss frequency. In practice, this assumption does not always hold true. Through mathematical analyses, we show that the classical approach is prone to significant biases when the independence assumption is violated. This is also corroborated by studying both simulated and real-world datasets. To overcome the limitations and to more accurately estimate VaR, we develop and implement the following two approaches for VaR estimation: the data-driven partitioning of frequency and severity (DPFS using clustering analysis, and copula-based parametric modeling of frequency and severity (CPFS. These two approaches are verified using simulation experiments on synthetic data and validated on five publicly available datasets from diverse domains; namely, the financial indices data of Standard & Poor’s 500 and the Dow Jones industrial average, chemical loss spills as tracked by the US Coast Guard, Australian automobile accidents, and US hurricane losses. The classical approach estimates VaR inaccurately for 80% of the simulated data sets and for 60% of the real-world data sets studied in this work. Both the DPFS and the CPFS methodologies attain VaR estimates within 99% bootstrap confidence interval bounds for both simulated and real-world data. We provide a process flowchart for risk practitioners describing the steps for using the DPFS versus the CPFS methodology for VaR estimation in real-world loss datasets.

  14. MHODE: a local-homogeneity theory for improved source-parameter estimation of potential fields

    Science.gov (United States)

    Fedi, Maurizio; Florio, Giovanni; Paoletti, Valeria

    2015-08-01

    We describe a multihomogeneity theory for source-parameter estimation of potential fields. Similar to what happens for random source models, where the monofractal scaling-law has been generalized into a multifractal law, we propose to generalize the homogeneity law into a multihomogeneity law. This allows a theoretically correct approach to study real-world potential fields, which are inhomogeneous and so do not show scale invariance, except in the asymptotic regions (very near to or very far from their sources). Since the scaling properties of inhomogeneous fields change with the scale of observation, we show that they may be better studied at a set of scales than at a single scale and that a multihomogeneous model is needed to explain its complex scaling behaviour. In order to perform this task, we first introduce fractional-degree homogeneous fields, to show that: (i) homogeneous potential fields may have fractional or integer degree; (ii) the source-distributions for a fractional-degree are not confined in a bounded region, similarly to some integer-degree models, such as the infinite line mass and (iii) differently from the integer-degree case, the fractional-degree source distributions are no longer uniform density functions. Using this enlarged set of homogeneous fields, real-world anomaly fields are studied at different scales, by a simple search, at any local window W, for the best homogeneous field of either integer or fractional-degree, this yielding a multiscale set of local homogeneity-degrees and depth estimations which we call multihomogeneous model. It is so defined a new technique of source parameter estimation (Multi-HOmogeneity Depth Estimation, MHODE), permitting retrieval of the source parameters of complex sources. We test the method with inhomogeneous fields of finite sources, such as faults or cylinders, and show its effectiveness also in a real-case example. These applications show the usefulness of the new concepts, multihomogeneity and

  15. Estimation of genetic parameters for milk traits in Romanian local sheep breed

    Directory of Open Access Journals (Sweden)

    Pelmus RS

    2014-03-01

    Full Text Available Objective. Estimate the genetic parameters for milk traits in a Romanian local sheep population Teleorman Black Head. Material and methods. Records of 262 sheep belonging to 17 rams and 139 ewes were used in the study. The following traits were investigated: milk yield, fat yield, protein yield, fat percentage and protein percentage. The genetic parameters were estimated using the Restricted Maximum Likelihood method, with a model including maternal effects. Results. The results from our study revealed that direct heritability estimates were moderate for milk yield (0.449, fat yield (0.442, protein yield (0.386 while for protein percentage (0.708 and fat percentage (0.924 were high. The high direct and maternal genetic correlation was between milk yield and protein yield (0.979, 0.973 and between protein yield and fat yield (0.952, 0.913 while the phenotypic correlation between the milk yield and fat yield (0.968, the milk yield and protein yield (0.967, fat yield and protein yield (0.936 was high and positive. Conclusions. The genetic parameters are important in selection program on this breed for genetic improvement.

  16. Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12

    Science.gov (United States)

    Thompson, Ryan F.; Wattier, Chelsea M.; Liggett, Richard R.; Truax, Ryan A.

    2014-01-01

    In 2009, the U.S. Geological Survey and South Dakota Department of Transportation (SDDOT) began a study to estimate potential scour at selected bridges on local government (county, township, and municipal) roads in South Dakota. A rapid scour-estimation method (level-1.5) and a more detailed method (level-2) were used to develop estimates of contraction, abutment, and pier scour. Data from 41 level-2 analyses completed for this study were combined with data from level-2 analyses completed in previous studies to develop new South Dakota-specific regression equations: four regional equations for main-channel velocity at the bridge contraction to account for the widely varying stream conditions within South Dakota, and one equation for head change. Velocity data from streamgages also were used in the regression for average velocity through the bridge contraction. Using these new regression equations, scour analyses were completed using the level-1.5 method on 361 bridges on local government roads. Typically, level-1.5 analyses are completed at flows estimated to have annual exceedance probabilities of 1 percent (100-year flood) and 0.2 percent (500-year flood); however, at some sites the bridge would not pass these flows. A level-1.5 analysis was then completed at the flow expected to produce the maximum scour. Data presented for level-1.5 scour analyses at the 361 bridges include contraction, abutment, and pier scour. Estimates of potential contraction scour ranged from 0 to 32.5 feet for the various flows evaluated. Estimated potential abutment scour ranged from 0 to 40.9 feet for left abutments, and from 0 to 37.7 feet for right abutments. Pier scour values ranged from 2.7 to 31.6 feet. The scour depth estimates provided in this report can be used by the SDDOT to compare with foundation depths at each bridge to determine if abutments or piers are at risk of being undermined by scour at the flows evaluated. Replicate analyses were completed at 24 of the 361 bridges

  17. Testing isotropy in the local Universe

    Energy Technology Data Exchange (ETDEWEB)

    Appleby, Stephen; Shafieloo, Arman, E-mail: stephen.appleby@apctp.org, E-mail: arman@apctp.org [Asia Pacific Center for Theoretical Physics, Pohang, Gyeongbuk 790-784 (Korea, Republic of)

    2014-10-01

    We test the isotropy of the local distribution of galaxies using the 2MASS extended source catalogue. By decomposing the full sky survey into distinct patches and using a combination of photometric and spectroscopic redshift data, we use both parametric and non-parametric methods to obtain the shape of the luminosity function in each patch. We use the shape of the luminosity function to test the statistical isotropy of the underlying galaxy distribution. The parametric estimator shows some evidence of a hemispherical asymmetry in the north/south Galactic plane. However the non-parametric estimator exhibits no significant anisotropy, with the galaxy distribution being consistent with the assumption of isotropy in all regions considered. The parametric asymmetry is attributed to the relatively poor fit of the functional form to the underlying data. When using the non-parametric estimator, we do find a dipole in the shape of the luminosity function, with maximal deviation from isotropy at galactic coordinate (b,l)=(30{sup o},315{sup o}). However we can ascribe no strong statistical significance to this observation.

  18. The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model.

    Science.gov (United States)

    de Graaf-Ruizendaal, Willemijn A; de Bakker, Dinny H

    2013-10-27

    This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary care and supply is missing. The research goal is to examine the construction of a decision tool which enables healthcare planners to analyse local supply and demand in order to arrive at a better match. National sample-based medical record data of general practitioners (GPs) were used to predict the local demand for GP care based on local populations using a synthetic estimation technique. Next, the surplus or deficit in local GP supply were calculated using the national GP registry. Subsequently, a dynamic internet tool was built to present demand, supply and the confrontation between supply and demand regarding GP care for local areas and their surroundings in the Netherlands. Regression analysis showed a significant relationship between sociodemographic predictors of postcode areas and GP consultation time (F [14, 269,467] = 2,852.24; P 1,000 inhabitants in the Netherlands covering 97% of the total population. Confronting these estimated demand figures with the actual GP supply resulted in the average GP workload and the number of full-time equivalent (FTE) GP too much/too few for local areas to cover the demand for GP care. An estimated shortage of one FTE GP or more was prevalent in about 19% of the postcode areas with >1,000 inhabitants if the surrounding postcode areas were taken into consideration. Underserved areas were mainly found in rural regions. The constructed decision tool is freely accessible on the Internet and can be used as a starting point in the discussion on primary care service provision in local communities and it can make a considerable contribution to a primary care system which provides care when and where people need it.

  19. Absolute decay parametric instability of high-temperature plasma

    International Nuclear Information System (INIS)

    Zozulya, A.A.; Silin, V.P.; Tikhonchuk, V.T.

    1986-01-01

    A new absolute decay parametric instability having wide spatial localization region is shown to be possible near critical plasma density. Its excitation is conditioned by distributed feedback of counter-running Langmuir waves occurring during parametric decay of incident and reflected pumping wave components. In a hot plasma with the temperature of the order of kiloelectronvolt its threshold is lower than that of a known convective decay parametric instability. Minimum absolute instability threshold is shown to be realized under conditions of spatial parametric resonance of higher orders

  20. Estimation of combined sewer overflow discharge: a software sensor approach based on local water level measurements.

    Science.gov (United States)

    Ahm, Malte; Thorndahl, Søren; Nielsen, Jesper E; Rasmussen, Michael R

    2016-12-01

    Combined sewer overflow (CSO) structures are constructed to effectively discharge excess water during heavy rainfall, to protect the urban drainage system from hydraulic overload. Consequently, most CSO structures are not constructed according to basic hydraulic principles for ideal measurement weirs. It can, therefore, be a challenge to quantify the discharges from CSOs. Quantification of CSO discharges are important in relation to the increased environmental awareness of the receiving water bodies. Furthermore, CSO discharge quantification is essential for closing the rainfall-runoff mass-balance in combined sewer catchments. A closed mass-balance is an advantage for calibration of all urban drainage models based on mass-balance principles. This study presents three different software sensor concepts based on local water level sensors, which can be used to estimate CSO discharge volumes from hydraulic complex CSO structures. The three concepts were tested and verified under real practical conditions. All three concepts were accurate when compared to electromagnetic flow measurements.

  1. Robust Estimator for Non-Line-of-Sight Error Mitigation in Indoor Localization

    Science.gov (United States)

    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.

  2. Deoxyglucose method for the estimation of local myocardial glucose metabolism with positron computed tomography

    International Nuclear Information System (INIS)

    Ratib, O.; Phelps, M.E.; Huang, S.C.; Henze, E.; Selin, C.E.; Schelbert, H.R.

    1981-01-01

    The deoxyglucose method originally developed for measurements of the local cerebral metabolic rate for glucose has been investigated in terms of its application to studies of the heart with positron computed tomography (PCT) and FDG. Studies were performed in dogs to measure the tissue kinetics of FDG with PCT and by direct arterial-venous sampling. The operational equation developed in our laboratory as an extension of the Sokoloff model was used to analyze the data. The FDG method accurately predicted the true MMRGlc even when the glucose metabolic rate was normal but myocardial blood flow (MBF) was elevated 5 times the control value or when metabolism was reduced to 10% of normal and MBF increased 5 times normal. Improvements in PCT resolution are required to improve the accuracy of the estimates of the rate constants and the MMRGlc

  3. A novel cost-effective parallel narrowband ANC system with local secondary-path estimation

    Science.gov (United States)

    Delegà, Riccardo; Bernasconi, Giancarlo; Piroddi, Luigi

    2017-08-01

    Many noise reduction applications are targeted at multi-tonal disturbances. Active noise control (ANC) solutions for such problems are generally based on the combination of multiple adaptive notch filters. Both the performance and the computational cost are negatively affected by an increase in the number of controlled frequencies. In this work we study a different modeling approach for the secondary path, based on the estimation of various small local models in adjacent frequency subbands, that greatly reduces the impact of reference-filtering operations in the ANC algorithm. Furthermore, in combination with a frequency-specific step size tuning method it provides a balanced attenuation performance over the whole controlled frequency range (and particularly in the high end of the range). Finally, the use of small local models is greatly beneficial for the reactivity of the online secondary path modeling algorithm when the characteristics of the acoustic channels are time-varying. Several simulations are provided to illustrate the positive features of the proposed method compared to other well-known techniques.

  4. PARAMETRIC DRAWINGS VS. AUTOLISP

    Directory of Open Access Journals (Sweden)

    PRUNĂ Liviu

    2015-06-01

    Full Text Available In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed by the drawing, in the idea to construct outlines or blocks which can be used in the projection process.

  5. PARAMETRIC DRAWINGS VS. AUTOLISP

    OpenAIRE

    PRUNĂ Liviu; SLONOVSCHI Andrei

    2015-01-01

    In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed...

  6. Estimating local scaling properties for the classification of interstitial lung disease patterns

    Science.gov (United States)

    Huber, Markus B.; Nagarajan, Mahesh B.; Leinsinger, Gerda; Ray, Lawrence A.; Wismueller, Axel

    2011-03-01

    Local scaling properties of texture regions were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honeycombing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and the estimation of local scaling properties with Scaling Index Method (SIM). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions including the Bonferroni correction. The best classification results were obtained by the set of SIM features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers with the highest accuracy (94.1%, 93.7%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced texture features using local scaling properties can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

  7. Applying Parametric Fault Detection to a Mechanical System

    DEFF Research Database (Denmark)

    Felício, P.; Stoustrup, Jakob; Niemann, H.

    2002-01-01

    A way of doing parametric fault detection is described. It is based on the representation of parameter changes as linear fractional transformations (lfts). We describe a model with parametric uncertainty. Then a stabilizing controller is chosen and its robustness properties are studied via mu. Th....... The parameter changes (faults) are estimated based on estimates of the fictitious signals that enter the delta block in the lft. These signal estimators are designed by H-infinity techniques. The chosen example is an inverted pendulum....

  8. Statistical prediction of parametric roll using FORM

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Choi, Ju-hyuck; Nielsen, Ulrik Dam

    2017-01-01

    Previous research has shown that the First Order Reliability Method (FORM) can be an efficient method for estimation of outcrossing rates and extreme value statistics for stationary stochastic processes. This is so also for bifurcation type of processes like parametric roll of ships. The present...

  9. Parametric number covariance in quantum chaotic spectra.

    Science.gov (United States)

    Vinayak; Kumar, Sandeep; Pandey, Akhilesh

    2016-03-01

    We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.

  10. Microdiamond grade as a regionalised variable - some basic requirements for successful local microdiamond resource estimation of kimberlites

    Science.gov (United States)

    Stiefenhofer, Johann; Thurston, Malcolm L.; Bush, David E.

    2018-04-01

    Microdiamonds offer several advantages as a resource estimation tool, such as access to deeper parts of a deposit which may be beyond the reach of large diameter drilling (LDD) techniques, the recovery of the total diamond content in the kimberlite, and a cost benefit due to the cheaper treatment cost compared to large diameter samples. In this paper we take the first step towards local estimation by showing that micro-diamond samples can be treated as a regionalised variable suitable for use in geostatistical applications and we show examples of such output. Examples of microdiamond variograms are presented, the variance-support relationship for microdiamonds is demonstrated and consistency of the diamond size frequency distribution (SFD) is shown with the aid of real datasets. The focus therefore is on why local microdiamond estimation should be possible, not how to generate such estimates. Data from our case studies and examples demonstrate a positive correlation between micro- and macrodiamond sample grades as well as block estimates. This relationship can be demonstrated repeatedly across multiple mining operations. The smaller sample support size for microdiamond samples is a key difference between micro- and macrodiamond estimates and this aspect must be taken into account during the estimation process. We discuss three methods which can be used to validate or reconcile the estimates against macrodiamond data, either as estimates or in the form of production grades: (i) reconcilliation using production data, (ii) by comparing LDD-based grade estimates against microdiamond-based estimates and (iii) using simulation techniques.

  11. Universal parametrization for quark and lepton substructure

    International Nuclear Information System (INIS)

    Akama, Keiichi; Terazawa, Hidezumi.

    1994-01-01

    A universal parametrization for possible quark and lepton substructure is advocated in terms of quark and lepton form factors. It is emphasized that the lower bounds on compositeness scale, Λ c , to be determined experimentally strongly depend on their definitions in composite models. From the recent HERA data, it is estimated to be Λ c > 50 GeV, 0.4 TeV and 10 TeV, depending on the parametrizations with a single-pole form factor, a contact interaction and a logarithmic form factor, respectively. (author)

  12. Controlling Parametric Resonance

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Pettersen, Kristin Ytterstad

    2012-01-01

    the authors review the conditions for the onset of parametric resonance, and propose a nonlinear control strategy in order to both induce the resonant oscillations and to stabilize the unstable motion. Lagrange’s theory is used to derive the dynamics of the system and input–output feedback linearization...

  13. Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

    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

  14. Estimating concentration of fluoride in edible leaves locally grown around Raipur, Chhattisgarh

    Directory of Open Access Journals (Sweden)

    Anubhuti Jain

    2017-01-01

    Full Text Available Introduction: Fluorine is the 13th most abundant element in the earth crust and is available in various environmental, clinical, and food samples in varied concentrations. Aim: To estimate concentration of fluoride in five medicinal and five nonmedicinal edible leaves locally grown around Raipur, Chhattisgarh, India. Materials and Methods: Samples of ten medicinal and nonmedicinal edible leaves, namely, spinach (Spinacia oleracea, coriander leaves (Coriandrum sativum, chawli bhaji (Amaranthus spinach, lal bhaji (Alternanthera bettzickiana, mooli bhaji (Raphanus sativus, neem (Azadirachta indica, tulsi (Ocimum tenuiflorum, mint leaves (Mentha longifolia, betel leaves (Piper betle, and bael leaves (Aegle marmelos were collected in the clean polyethene bags. After thorough washing with water, leaves were left to dry in ambient temperature and crushed into powder using a mixer grinder. One gram of each of the powdered samples was taken and analyzed for fluoride concentration using a 2-(4-sulfophenylazo 1,8-dihydroxy-3,6-naphthalenedisulfonic acid trisodium salt spectrophotometric method. Results: The presence of fluoride in varied concentrations in locally grown edible leaves were analyzed. The highest concentration of fluoride was reported in tulsi (6.0 μg/g and lowest in mint leaves (1.1 μg/g. Two edible leaves, neem and bael, showed fluoride concentration below detection limit. Conclusion: Knowledge regarding the importance of edible leaves may be lost in the near future unless efforts are made to educate younger generations about their importance. Hence, the time has come to make good use of centuries-old knowledge through modern approaches for their better economic and therapeutic utilization.

  15. Parametric imaging of tumor perfusion and neovascular morphology using ultrasound

    Science.gov (United States)

    Hoyt, Kenneth

    2015-03-01

    A new image processing strategy is detailed for the simultaneous measurement of tumor perfusion and neovascular morphology parameters from a sequence of dynamic contrast-enhanced ultrasound (DCE-US) images. A technique for locally mapping tumor perfusion parameters using skeletonized neovascular data is also introduced. Simulated images were used to test the neovascular skeletonization technique and variance (error) of relevant parametric estimates. Preliminary DCE-US image datasets were collected in 6 female patients diagnosed with invasive breast cancer and using a Philips iU22 ultrasound system equipped with a L9-3 MHz transducer and Definity contrast agent. Simulation data demonstrates that neovascular morphology parametric estimation is reproducible albeit measurement error can occur at a lower signal-to-noise ratio (SNR). Experimental results indicate the feasibility of our approach to performing both tumor perfusion and neovascular morphology measurements from DCE-US images. Future work will expand on our initial clinical findings and also extent our image processing strategy to 3-dimensional space to allow whole tumor characterization.

  16. Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation

    Science.gov (United States)

    Pasaniuc, Bogdan; Sankararaman, Sriram; Torgerson, Dara G.; Gignoux, Christopher; Zaitlen, Noah; Eng, Celeste; Rodriguez-Cintron, William; Chapela, Rocio; Ford, Jean G.; Avila, Pedro C.; Rodriguez-Santana, Jose; Chen, Gary K.; Le Marchand, Loic; Henderson, Brian; Reich, David; Haiman, Christopher A.; Gonzàlez Burchard, Esteban; Halperin, Eran

    2013-01-01

    Motivation: Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging. Results: Here, we use 489 nuclear families from the mainland USA, Puerto Rico and Mexico in conjunction with 3204 unrelated Latinos from the Multiethnic Cohort study to provide the first empirical characterization of local ancestry inference accuracy in Latinos. Our approach for identifying errors does not rely on simulations but on the observation that local ancestry in families follows Mendelian inheritance. We measure the rate of local ancestry assignments that lead to Mendelian inconsistencies in local ancestry in trios (MILANC), which provides a lower bound on errors in the local ancestry estimates. We show that MILANC rates observed in simulations underestimate the rate observed in real data, and that MILANC varies substantially across the genome. Second, across a wide range of methods, we observe that loci with large deviations in local ancestry also show enrichment in MILANC rates. Therefore, local ancestry estimates at such loci should be interpreted with caution. Finally, we reconstruct ancestral haplotype panels to be used as reference panels in local ancestry inference and show that ancestry inference is significantly improved by incoroprating these reference panels. Availability and implementation: We provide the reconstructed reference panels together with the maps of MILANC rates as a public resource for researchers analyzing local ancestry in Latinos at http://bogdanlab.pathology.ucla.edu. Contact: bpasaniuc@mednet.ucla.edu Supplementary information: Supplementary data are

  17. A hybrid downscaling procedure for estimating the vertical distribution of ambient temperature in local scale

    Science.gov (United States)

    Yiannikopoulou, I.; Philippopoulos, K.; Deligiorgi, D.

    2012-04-01

    The vertical thermal structure of the atmosphere is defined by a combination of dynamic and radiation transfer processes and plays an important role in describing the meteorological conditions at local scales. The scope of this work is to develop and quantify the predictive ability of a hybrid dynamic-statistical downscaling procedure to estimate the vertical profile of ambient temperature at finer spatial scales. The study focuses on the warm period of the year (June - August) and the method is applied to an urban coastal site (Hellinikon), located in eastern Mediterranean. The two-step methodology initially involves the dynamic downscaling of coarse resolution climate data via the RegCM4.0 regional climate model and subsequently the statistical downscaling of the modeled outputs by developing and training site-specific artificial neural networks (ANN). The 2.5ox2.5o gridded NCEP-DOE Reanalysis 2 dataset is used as initial and boundary conditions for the dynamic downscaling element of the methodology, which enhances the regional representivity of the dataset to 20km and provides modeled fields in 18 vertical levels. The regional climate modeling results are compared versus the upper-air Hellinikon radiosonde observations and the mean absolute error (MAE) is calculated between the four grid point values nearest to the station and the ambient temperature at the standard and significant pressure levels. The statistical downscaling element of the methodology consists of an ensemble of ANN models, one for each pressure level, which are trained separately and employ the regional scale RegCM4.0 output. The ANN models are theoretically capable of estimating any measurable input-output function to any desired degree of accuracy. In this study they are used as non-linear function approximators for identifying the relationship between a number of predictor variables and the ambient temperature at the various vertical levels. An insight of the statistically derived input

  18. Towards Stabilizing Parametric Active Contours

    DEFF Research Database (Denmark)

    Liu, Jinchao; Fan, Zhun; Olsen, Søren Ingvor

    2014-01-01

    Numerical instability often occurs in evolving of parametric active contours. This is mainly due to the undesired change of parametrization during evolution. In this paper, we propose a new tangential diffusion term to compensate this undesired change. As a result, the parametrization will converge...

  19. Local power peaking factor estimation in nuclear fuel by artificial neural networks

    International Nuclear Information System (INIS)

    Montes, Jose Luis; Francois, Juan Luis; Ortiz, Juan Jose; Martin-del-Campo, Cecilia; Perusquia, Raul

    2009-01-01

    This paper presents the training of an artificial neural network (ANN) to accurately predict, in very short time, a physical parameter used in nuclear fuel reactor optimization: the local power peaking factor (LPPF) in a typical boiling water reactor (BWR) fuel lattice. The ANN training patterns are distribution of fissile and burnable poison materials in the fuel lattice and their associated LPPF. These data were obtained by modeling the fuel lattices with a neutronic simulator: the HELIOS transport code. The combination of the pin U 235 enrichment and the Gd 2 O 3 (gadolinia) concentration, inside the 10 x 10 fuel lattice array, was encoded by three different methods. However, the only encoding method that was able to give a good prediction of the LPPF was the method which added the U 235 enrichment and the gadolinia concentration. The results show that the relative error in the estimation of the LPPF, obtained by the trained ANN, ranged from 0.022% to 0.045%, with respect to the HELIOS results

  20. Observation of aftershocks of the 2003 Tokachi-Oki earthquake for estimation of local site effects

    Science.gov (United States)

    Yamanaka, Hiroaki; Motoki, Kentaro; Etoh, Kiminobu; Murayama, Masanari; Komaba, Nobuhiko

    2004-03-01

    Observation of aftershocks of the 2003 Tokachi-Oki earthquake was conducted in the southern part of the Tokachi basin in Hokkaido, Japan for estimation of local site effects. We installed accelerographs at 12 sites in Chokubetsu, Toyokoro, and Taiki areas, where large strong motion records were obtained during the main shock at stations of the K-NET and KiK-net. The stations of the aftershock observation are situated with different geological conditions and some of the sites were installed on Pleistocene layers as reference sites. The site amplifications are investigated using spectral ratio of S-waves from the aftershocks. The S-wave amplification factor is dominant at a period of about 1 second at the site near the KiK-net site in Toyokoro. This amplification fits well with calculated 1D amplification of S-wave in alluvial layers with a thickness of 50 meters. In addition to the site effects, we detected nonlinear amplification of the soft soils only during the main shock. The site effects at the strong motion site of the K-NET at Chokubetsu have a dominate peak at a period of 0.4 seconds. This amplification is due to soft soils having a thickness of about 13 meters. Contrary to the results at the two areas, site effects are not significantly different at the stations in the Taiki area, because of similarity on surface geological conditions.

  1. 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.

  2. MEMS digital parametric loudspeaker

    KAUST Repository

    Carreno, Armando Arpys Arevalo

    2016-03-23

    This paper reports on the design and fabrication of MEMS actuator arrays suitable for Digital Sound reconstruction and Parametric Directional Loudspeakers. Two distinct versions of the device were fabricated: one using the electrostatic principle actuation and the other one, the piezoelectric principle. Both versions used similar membrane dimensions, with a diameter of 500 μm. These devices are the smallest Micro-Machined Ultrasound Transducer (MUT) arrays that can be operated for both modes: Digital Sound Reconstruction and Parametric Loudspeaker. The chips consist of an array with 256 transducers, in a footprint of 12 mm by 12 mm. The total single chip size is: 2.3 cm by 2.3 cm, including the contact pads. © 2016 IEEE.

  3. Parametric Explosion Spectral Model

    Energy Technology Data Exchange (ETDEWEB)

    Ford, S R; Walter, W R

    2012-01-19

    Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.

  4. MEMS digital parametric loudspeaker

    KAUST Repository

    Carreno, Armando Arpys Arevalo; Castro, David; Conchouso Gonzalez, David; Kosel, Jü rgen; Foulds, Ian G.

    2016-01-01

    This paper reports on the design and fabrication of MEMS actuator arrays suitable for Digital Sound reconstruction and Parametric Directional Loudspeakers. Two distinct versions of the device were fabricated: one using the electrostatic principle actuation and the other one, the piezoelectric principle. Both versions used similar membrane dimensions, with a diameter of 500 μm. These devices are the smallest Micro-Machined Ultrasound Transducer (MUT) arrays that can be operated for both modes: Digital Sound Reconstruction and Parametric Loudspeaker. The chips consist of an array with 256 transducers, in a footprint of 12 mm by 12 mm. The total single chip size is: 2.3 cm by 2.3 cm, including the contact pads. © 2016 IEEE.

  5. Macromechanical Parametric Amplification

    DEFF Research Database (Denmark)

    Neumeyer, Stefan

    between the two peaks can be altered. The first experimental bistable amplified steady-state responses are also reported. The derived analytical models and experimental setups can readily be extended to investigate other factors. Some of the results are also applicable to the more general field of systems...... for energy harvesting. Using analytical, numerical, and experimental methods, the thesis focuses on superthreshold pumping (above the systems parametric instability threshold), nonlinear effects, frequency response backbones, and frequency detuning effects for parametric amplifiers. Part one of the thesis...... covers superthreshold pumping and nonlinear effects. Superthresh-old pumping produces some useful characteristics. For instance, strong superthreshold pumping yields a high gain even though nonlinear effects tend to reduce it. In addition, a narrower excitation phase range is realized for which...

  6. Non-parametric cell-based photometric proxies for galaxy morphology: methodology and application to the morphologically defined star formation-stellar mass relation of spiral galaxies in the local universe

    Science.gov (United States)

    Grootes, M. W.; Tuffs, R. J.; Popescu, C. C.; Robotham, A. S. G.; Seibert, M.; Kelvin, L. S.

    2014-02-01

    We present a non-parametric cell-based method of selecting highly pure and largely complete samples of spiral galaxies using photometric and structural parameters as provided by standard photometric pipelines and simple shape fitting algorithms. The performance of the method is quantified for different parameter combinations, using purely human-based classifications as a benchmark. The discretization of the parameter space allows a markedly superior selection than commonly used proxies relying on a fixed curve or surface of separation. Moreover, we find structural parameters derived using passbands longwards of the g band and linked to older stellar populations, especially the stellar mass surface density μ* and the r-band effective radius re, to perform at least equally well as parameters more traditionally linked to the identification of spirals by means of their young stellar populations, e.g. UV/optical colours. In particular, the distinct bimodality in the parameter μ*, consistent with expectations of different evolutionary paths for spirals and ellipticals, represents an often overlooked yet powerful parameter in differentiating between spiral and non-spiral/elliptical galaxies. We use the cell-based method for the optical parameter set including re in combination with the Sérsic index n and the i-band magnitude to investigate the intrinsic specific star formation rate-stellar mass relation (ψ*-M*) for a morphologically defined volume-limited sample of local Universe spiral galaxies. The relation is found to be well described by ψ _* ∝ M_*^{-0.5} over the range of 109.5 ≤ M* ≤ 1011 M⊙ with a mean interquartile range of 0.4 dex. This is somewhat steeper than previous determinations based on colour-selected samples of star-forming galaxies, primarily due to the inclusion in the sample of red quiescent discs.

  7. A simulation of Earthquake Loss Estimation in Southeastern Korea using HAZUS and the local site classification Map

    Science.gov (United States)

    Kang, S.; Kim, K.

    2013-12-01

    Regionally varying seismic hazards can be estimated using an earthquake loss estimation system (e.g. HAZUS-MH). The estimations for actual earthquakes help federal and local authorities develop rapid, effective recovery measures. Estimates for scenario earthquakes help in designing a comprehensive earthquake hazard mitigation plan. Local site characteristics influence the ground motion. Although direct measurements are desirable to construct a site-amplification map, such data are expensive and time consuming to collect. Thus we derived a site classification map of the southern Korean Peninsula using geologic and geomorphologic data, which are readily available for the entire southern Korean Peninsula. Class B sites (mainly rock) are predominant in the area, although localized areas of softer soils are found along major rivers and seashores. The site classification map is compared with independent site classification studies to confirm our site classification map effectively represents the local behavior of site amplification during an earthquake. We then estimated the losses due to a magnitude 6.7 scenario earthquake in Gyeongju, southeastern Korea, with and without the site classification map. Significant differences in loss estimates were observed. The loss without the site classification map decreased without variation with increasing epicentral distance, while the loss with the site classification map varied from region to region, due to both the epicentral distance and local site effects. The major cause of the large loss expected in Gyeongju is the short epicentral distance. Pohang Nam-Gu is located farther from the earthquake source region. Nonetheless, the loss estimates in the remote city are as large as those in Gyeongju and are attributed to the site effect of soft soil found widely in the area.

  8. Convenience Sampling of Children Presenting to Hospital-Based Outpatient Clinics to Estimate Childhood Obesity Levels in Local Surroundings.

    Science.gov (United States)

    Gilliland, Jason; Clark, Andrew F; Kobrzynski, Marta; Filler, Guido

    2015-07-01

    Childhood obesity is a critical public health matter associated with numerous pediatric comorbidities. Local-level data are required to monitor obesity and to help administer prevention efforts when and where they are most needed. We hypothesized that samples of children visiting hospital clinics could provide representative local population estimates of childhood obesity using data from 2007 to 2013. Such data might provide more accurate, timely, and cost-effective obesity estimates than national surveys. Results revealed that our hospital-based sample could not serve as a population surrogate. Further research is needed to confirm this finding.

  9. Parametric trapping of electromagnetic waves in an inhomogeneous plasma

    International Nuclear Information System (INIS)

    Silin, V.P.; Starodub, A.N.

    1977-01-01

    Considered is parametric instability in an inhomogeneous plasma at which a pumping wave is transformed to an electromagnetic wave and aperiodically in-time-growing disturbances. It is shown that after achievement of some boundary pumping value by electric field intensity an absolute parametric instability evolution becomes possible. In-time growing plasma disturbances are localized near electric field extremums of a pumping wave. Such localization areas are small as compared to characteristic size of pumping inhomogeneity in a plasma. The secondary electromagnetic waves stay within the localization areas and, therefore, are not scattered by a plasma. As following from this it has been established, that due to parametric instability electromagnetic radiation trapping by a plasma occurs. Such a trapping is considerably connected with a spatial structure of a pumping field and it cannot arise within the field of a running wave in the theoretical model considered. However parametric trapping turns out to be possible even with very small reflection coefficients

  10. Parametric Resonance in Dynamical Systems

    CERN Document Server

    Nijmeijer, Henk

    2012-01-01

    Parametric Resonance in Dynamical Systems discusses the phenomenon of parametric resonance and its occurrence in mechanical systems,vehicles, motorcycles, aircraft and marine craft, and micro-electro-mechanical systems. The contributors provide an introduction to the root causes of this phenomenon and its mathematical equivalent, the Mathieu-Hill equation. Also included is a discussion of how parametric resonance occurs on ships and offshore systems and its frequency in mechanical and electrical systems. This book also: Presents the theory and principles behind parametric resonance Provides a unique collection of the different fields where parametric resonance appears including ships and offshore structures, automotive vehicles and mechanical systems Discusses ways to combat, cope with and prevent parametric resonance including passive design measures and active control methods Parametric Resonance in Dynamical Systems is ideal for researchers and mechanical engineers working in application fields such as MEM...

  11. Using non-parametric methods in econometric production analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    2012-01-01

    by investigating the relationship between the elasticity of scale and the farm size. We use a balanced panel data set of 371~specialised crop farms for the years 2004-2007. A non-parametric specification test shows that neither the Cobb-Douglas function nor the Translog function are consistent with the "true......Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify a functional form of the production function of which the Cobb...... parameter estimates, but also in biased measures which are derived from the parameters, such as elasticities. Therefore, we propose to use non-parametric econometric methods. First, these can be applied to verify the functional form used in parametric production analysis. Second, they can be directly used...

  12. Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

    Directory of Open Access Journals (Sweden)

    Ibsen Chivatá Cárdenas

    2008-05-01

    Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

  13. Parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method of ledre profile attributes

    Science.gov (United States)

    Hastuti, S.; Harijono; Murtini, E. S.; Fibrianto, K.

    2018-03-01

    This current study is aimed to investigate the use of parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method. Ledre as Bojonegoro unique local food product was used as point of interest, in which 319 panelists were involved in the study. The result showed that ledre is characterized as easy-crushed texture, sticky in mouth, stingy sensation and easy to swallow. It has also strong banana flavour with brown in colour. Compared to eggroll and semprong, ledre has more variances in terms of taste as well the roll length. As RATA questionnaire is designed to collect categorical data, non-parametric approach is the common statistical procedure. However, similar results were also obtained as parametric approach, regardless the fact of non-normal distributed data. Thus, it suggests that parametric approach can be applicable for consumer study with large number of respondents, even though it may not satisfy the assumption of ANOVA (Analysis of Variances).

  14. Brownian parametric oscillators

    Science.gov (United States)

    Zerbe, Christine; Jung, Peter; Hänggi, Peter

    1994-05-01

    We discuss the stochastic dynamics of dissipative, white-noise-driven Floquet oscillators, characterized by a time-periodic stiffness. Thus far, little attention has been paid to these exactly solvable nonstationary systems, although they carry a rich potential for several experimental applications. Here, we calculate and discuss the mean values and variances, as well as the correlation functions and the Floquet spectrum. As one main result, we find for certain parameter values that the fluctuations of the position coordinate are suppressed as compared to the equilibrium value of a harmonic oscillator (parametric squeezing).

  15. A variational approach to parametric instabilities in inhomogeneous plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Afeyan, B.B.

    1993-12-31

    A variational principle is constructed for the pump strength of a three-wave parametric instability in a spatially nonuniform medium. Using this expression together with appropriate trial functions, analytic estimates of the growth rate of the most unstable mode of a given parametric instability may be calculated. The usefullness of the variational method is first demonstrated on the Rosenbluth model problem with a power-law phase-mismatch, followed by a treatment of the Liu, Rosenbluth, and White sidescattering model equation. Two particular instabilities which are of interest in laser fusion and laser-plasma interaction experiments are treated next. These are Stimulated Raman Scattering and Two-Plasmon Decay. Various incidence and scattering geometries, and different density profiles are considered. Previously known results are reproduced in a unified manner and extended to cases where the usual local-expansion techniques do not apply. In particular, using the variational approach, the growth rate of the Two-Plasmon Decay instability occurring at or anywhere below the apex of a parabolic density profile is obtained for the first time. Similarly, Stimulated Raman Scattering from a density extremum at or anywhere below quarter critical, and for all scattering angles from backscattering to sidescattering inclusively is considered for the first time. The limit where the Two-Plasmon Decay and Stimulated Raman Scattering instabilities merge and become indistinguishable is also treated.

  16. Parametric inference for discretely sampled stochastic differential equations

    DEFF Research Database (Denmark)

    Sørensen, Michael

    A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion processes. The main focus is on estimating functions and asymp- totic results. Maximum likelihood estimation is briefly considered, but the emphasis is on computationally less demanding martingale...

  17. local

    Directory of Open Access Journals (Sweden)

    Abílio Amiguinho

    2005-01-01

    Full Text Available The process of socio-educational territorialisation in rural contexts is the topic of this text. The theme corresponds to a challenge to address it having as main axis of discussion either the problem of social exclusion or that of local development. The reasons to locate the discussion in this last field of analysis are discussed in the first part of the text. Theoretical and political reasons are there articulated because the question is about projects whose intentions and practices call for the political both in the theoretical debate and in the choices that anticipate intervention. From research conducted for several years, I use contributions that aim at discuss and enlighten how school can be a potential locus of local development. Its identification and recognition as local institution (either because of those that work and live in it or because of those that act in the surrounding context are crucial steps to progressively constitute school as a partner for development. The promotion of the local values and roots, the reconstruction of socio-personal and local identities, the production of sociabilities and the equation and solution of shared problems were the dimensions of a socio-educative intervention, markedly globalising. This scenario, as it is argued, was also, intentionally, one of transformation and of deliberate change of school and of the administration of the educative territoires.

  18. A parametric reconstruction of the deceleration parameter

    Energy Technology Data Exchange (ETDEWEB)

    Al Mamon, Abdulla [Manipal University, Manipal Centre for Natural Sciences, Manipal (India); Visva-Bharati, Department of Physics, Santiniketan (India); Das, Sudipta [Visva-Bharati, Department of Physics, Santiniketan (India)

    2017-07-15

    The present work is based on a parametric reconstruction of the deceleration parameter q(z) in a model for the spatially flat FRW universe filled with dark energy and non-relativistic matter. In cosmology, the parametric reconstruction technique deals with an attempt to build up a model by choosing some specific evolution scenario for a cosmological parameter and then estimate the values of the parameters with the help of different observational datasets. In this paper, we have proposed a logarithmic parametrization of q(z) to probe the evolution history of the universe. Using the type Ia supernova, baryon acoustic oscillation and the cosmic microwave background datasets, the constraints on the arbitrary model parameters q{sub 0} and q{sub 1} are obtained (within 1σ and 2σ confidence limits) by χ{sup 2}-minimization technique. We have then reconstructed the deceleration parameter, the total EoS parameter ω{sub tot}, the jerk parameter and have compared the reconstructed results of q(z) with other well-known parametrizations of q(z). We have also shown that two model selection criteria (namely, the Akaike information criterion and Bayesian information criterion) provide a clear indication that our reconstructed model is well consistent with other popular models. (orig.)

  19. Parametric Linear Dynamic Logic

    Directory of Open Access Journals (Sweden)

    Peter Faymonville

    2014-08-01

    Full Text Available We introduce Parametric Linear Dynamic Logic (PLDL, which extends Linear Dynamic Logic (LDL by temporal operators equipped with parameters that bound their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL that is able to express all ω-regular specifications while still maintaining many of LTL's desirable properties like an intuitive syntax and a translation into non-deterministic Büchi automata of exponential size. But LDL lacks capabilities to express timing constraints. By adding parameterized operators to LDL, we obtain a logic that is able to express all ω-regular properties and that subsumes parameterized extensions of LTL like Parametric LTL and PROMPT-LTL. Our main technical contribution is a translation of PLDL formulas into non-deterministic Büchi word automata of exponential size via alternating automata. This yields a PSPACE model checking algorithm and a realizability algorithm with doubly-exponential running time. Furthermore, we give tight upper and lower bounds on optimal parameter values for both problems. These results show that PLDL model checking and realizability are not harder than LTL model checking and realizability.

  20. Supervised local error estimation for nonlinear image registration using convolutional neural networks

    NARCIS (Netherlands)

    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

  1. Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

    Science.gov (United States)

    Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

    2006-01-01

    We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

  2. Local digital algorithms for estimating the mean integrated curvature of r-regular sets

    DEFF Research Database (Denmark)

    Svane, Anne Marie

    , no asymptotically unbiased estimator of this type exists in dimension greater than or equal to three, while for stationary isotropic lattices, asymptotically unbiased estimators are plenty. Both results follow from a general formula that we state and prove, describing the asymptotic behavior of hit...

  3. A soft double regularization approach to parametric blind image deconvolution.

    Science.gov (United States)

    Chen, Li; Yap, Kim-Hui

    2005-05-01

    This paper proposes a blind image deconvolution scheme based on soft integration of parametric blur structures. Conventional blind image deconvolution methods encounter a difficult dilemma of either imposing stringent and inflexible preconditions on the problem formulation or experiencing poor restoration results due to lack of information. This paper attempts to address this issue by assessing the relevance of parametric blur information, and incorporating the knowledge into the parametric double regularization (PDR) scheme. The PDR method assumes that the actual blur satisfies up to a certain degree of parametric structure, as there are many well-known parametric blurs in practical applications. Further, it can be tailored flexibly to include other blur types if some prior parametric knowledge of the blur is available. A manifold soft parametric modeling technique is proposed to generate the blur manifolds, and estimate the fuzzy blur structure. The PDR scheme involves the development of the meaningful cost function, the estimation of blur support and structure, and the optimization of the cost function. Experimental results show that it is effective in restoring degraded images under different environments.

  4. Local dark matter and dark energy as estimated on a scale of ~1 Mpc in a self-consistent way

    Science.gov (United States)

    Chernin, A. D.; Teerikorpi, P.; Valtonen, M. J.; Dolgachev, V. P.; Domozhilova, L. M.; Byrd, G. G.

    2009-12-01

    Context: Dark energy was first detected from large distances on gigaparsec scales. If it is vacuum energy (or Einstein's Λ), it should also exist in very local space. Here we discuss its measurement on megaparsec scales of the Local Group. Aims: We combine the modified Kahn-Woltjer method for the Milky Way-M 31 binary and the HST observations of the expansion flow around the Local Group in order to study in a self-consistent way and simultaneously the local density of dark energy and the dark matter mass contained within the Local Group. Methods: A theoretical model is used that accounts for the dynamical effects of dark energy on a scale of ~1 Mpc. Results: The local dark energy density is put into the range 0.8-3.7ρv (ρv is the globally measured density), and the Local Group mass lies within 3.1-5.8×1012 M⊙. The lower limit of the local dark energy density, about 4/5× the global value, is determined by the natural binding condition for the group binary and the maximal zero-gravity radius. The near coincidence of two values measured with independent methods on scales differing by ~1000 times is remarkable. The mass ~4×1012 M⊙ and the local dark energy density ~ρv are also consistent with the expansion flow close to the Local Group, within the standard cosmological model. Conclusions: One should take into account the dark energy in dynamical mass estimation methods for galaxy groups, including the virial theorem. Our analysis gives new strong evidence in favor of Einstein's idea of the universal antigravity described by the cosmological constant.

  5. Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

    Directory of Open Access Journals (Sweden)

    Basile Pauthier

    2016-01-01

    Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

  6. The Approach to an Estimation of a Local Area Network Functioning Efficiency

    Directory of Open Access Journals (Sweden)

    M. M. Taraskin

    2010-09-01

    Full Text Available In the article authors call attention to a choice of system of metrics, which permits to take a qualitative assessment of local area network functioning efficiency in condition of computer attacks.

  7. Local linear density estimation for filtered survival data, with bias correction

    DEFF Research Database (Denmark)

    Nielsen, Jens Perch; Tanggaard, Carsten; Jones, M.C.

    2009-01-01

    it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a 'pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias-correction methods...... within our framework. The multiplicative bias-correction method proves to be the best in a simulation study comparing the performance of the considered estimators. An example concerning old-age mortality demonstrates the importance of the improvements provided....

  8. Local Linear Density Estimation for Filtered Survival Data with Bias Correction

    DEFF Research Database (Denmark)

    Tanggaard, Carsten; Nielsen, Jens Perch; Jones, M.C.

    it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a ‘pilot' estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias correction methods...... within our framework. The multiplicative bias correction method proves to be best in a simulation study comparing the performance of the considered estimators. An example concerning old age mortality demonstrates the importance of the improvements provided....

  9. Using Spline Regression in Semi-Parametric Stochastic Frontier Analysis: An Application to Polish Dairy Farms

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    of specifying an unsuitable functional form and thus, model misspecification and biased parameter estimates. Given these problems of the DEA and the SFA, Fan, Li and Weersink (1996) proposed a semi-parametric stochastic frontier model that estimates the production function (frontier) by non......), Kumbhakar et al. (2007), and Henningsen and Kumbhakar (2009). The aim of this paper and its main contribution to the existing literature is the estimation semi-parametric stochastic frontier models using a different non-parametric estimation technique: spline regression (Ma et al. 2011). We apply...... efficiency of Polish dairy farms contributes to the insight into this dynamic process. Furthermore, we compare and evaluate the results of this spline-based semi-parametric stochastic frontier model with results of other semi-parametric stochastic frontier models and of traditional parametric stochastic...

  10. Estimate of whole body doses for Lynette Tew and Becky Farnsworth from Nevada Test Site local fallout

    International Nuclear Information System (INIS)

    Anspaugh, L.R.; Ng, Y.C.

    1985-01-01

    Lynette Tew and Becky Farnsworth are decendents whose relatives are litigants in Timothy vs US. The litigants allege that the decendents were harmed by radiation doses received as a result of local fallout from the testing of nuclear weapons at the Nevada Test Site. We have calculated a best estimate of the whole body dose received by each decendent from external exposure and the ingestion of radionuclides with food. In each case the dose via ingestion is trivial compared to the external dose. For Lynette Tew the dose estimate is 0.28 rads. For Becky Farnsworth it is 0.0035 rads. 23 references, 4 tables

  11. Nanoscale electromechanical parametric amplifier

    Science.gov (United States)

    Aleman, Benjamin Jose; Zettl, Alexander

    2016-09-20

    This disclosure provides systems, methods, and apparatus related to a parametric amplifier. In one aspect, a device includes an electron source electrode, a counter electrode, and a pumping electrode. The electron source electrode may include a conductive base and a flexible conductor. The flexible conductor may have a first end and a second end, with the second end of the flexible conductor being coupled to the conductive base. A cross-sectional dimension of the flexible conductor may be less than about 100 nanometers. The counter electrode may be disposed proximate the first end of the flexible conductor and spaced a first distance from the first end of the flexible conductor. The pumping electrode may be disposed proximate a length of the flexible conductor and spaced a second distance from the flexible conductor.

  12. Parametric Room Acoustic Workflows

    DEFF Research Database (Denmark)

    Parigi, Dario; Svidt, Kjeld; Molin, Erik

    2017-01-01

    The paper investigates and assesses different room acoustics software and the opportunities they offer to engage in parametric acoustics workflow and to influence architectural designs. The first step consists in the testing and benchmarking of different tools on the basis of accuracy, speed...... and interoperability with Grasshopper 3d. The focus will be placed to the benchmarking of three different acoustic analysis tools based on raytracing. To compare the accuracy and speed of the acoustic evaluation across different tools, a homogeneous set of acoustic parameters is chosen. The room acoustics parameters...... included in the set are reverberation time (EDT, RT30), clarity (C50), loudness (G), and definition (D50). Scenarios are discussed for determining at different design stages the most suitable acoustic tool. Those scenarios are characterized, by the use of less accurate but fast evaluation tools to be used...

  13. Parametric Human Movements

    DEFF Research Database (Denmark)

    Herzog, Dennis

    adapt the primitives to the actual appearance of the tracked motion, since the appearance of actions depends on the object locations. From the recognition perspective, it is necessary to recognize a performed action, but the understanding requires also the recovery of the action parameters, which can......The thesis aims at the learning of action primitives and their application on the perceptive side (tracking/recognition) and the generative side (synthesizing for robot control). A motivation is to use a unified primitive representation applicable on both sides. The thesis considers arm actions...... with an investigation of PHMM training methods and structures to utilize the PHMM as a unified representation of parametric primitives, which is adequate for recognition and for synthesis. This is evaluated on a large motion data set. Main contributions of the thesis are the development and evaluation of approaches...

  14. Real-time approaches to the estimation of local wind velocity for a fixed-wing unmanned air vehicle

    International Nuclear Information System (INIS)

    Chan, W L; Lee, C S; Hsiao, F B

    2011-01-01

    Three real-time approaches to estimating local wind velocity for a fixed-wing unmanned air vehicle are presented in this study. All three methods work around the navigation equations with added wind components. The first approach calculates the local wind speed by substituting the ground speed and ascent rate data given by the Global Positioning System (GPS) into the navigation equations. The second and third approaches utilize the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), respectively. The results show that, despite the nonlinearity of the navigation equations, the EKF performance is proven to be on a par with the UKF. A time-varying noise estimation method based on the Wiener filter is also discussed. Results are compared with the average wind speed measured on the ground. All three approaches are proven to be reliable with stated advantages and disadvantages

  15. Instantaneous local wave vector estimation from multi-spacecraft measurements using few spatial points

    Directory of Open Access Journals (Sweden)

    T. D. Carozzi

    2004-07-01

    Full Text Available We introduce a technique to determine instantaneous local properties of waves based on discrete-time sampled, real-valued measurements from 4 or more spatial points. The technique is a generalisation to the spatial domain of the notion of instantaneous frequency used in signal processing. The quantities derived by our technique are closely related to those used in geometrical optics, namely the local wave vector and instantaneous phase velocity. Thus, this experimental technique complements ray-tracing. We provide example applications of the technique to electric field and potential data from the EFW instrument on Cluster. Cluster is the first space mission for which direct determination of the full 3-dimensional local wave vector is possible, as described here.

  16. Estimating Aquifer Storage and Recovery (ASR Regional and Local Suitability: A Case Study in Washington State, USA

    Directory of Open Access Journals (Sweden)

    Maria T. Gibson

    2018-01-01

    Full Text Available Developing aquifers as underground water supply reservoirs is an advantageous approach applicable to meeting water management objectives. Aquifer storage and recovery (ASR is a direct injection and subsequent withdrawal technology that is used to increase water supply storage through injection wells. Due to site-specific hydrogeological quantification and evaluation to assess ASR suitability, limited methods have been developed to identify suitability on regional scales that are also applicable at local scales. This paper presents an ASR site scoring system developed to qualitatively assess regional and local suitability of ASR using 9 scored metrics to determine total percent of ASR suitability, partitioned into hydrogeologic properties, operational considerations, and regulatory influences. The development and application of a qualitative water well suitability method was used to assess the potential groundwater response to injection, estimate suitability based on predesignated injection rates, and provide cumulative approximation of statewide and local storage prospects. The two methods allowed for rapid assessment of ASR suitability and its applicability to regional and local water management objectives at over 280 locations within 62 watersheds in Washington, USA. It was determined that over 50% of locations evaluated are suitable for ASR and statewide injection potential equaled 6400 million liters per day. The results also indicate current limitations and/or potential benefits of developing ASR systems at the local level with the intent of assisting local water managers in strategic water supply planning.

  17. The local forest management associations as estimators of the fuelwood market in Finland

    International Nuclear Information System (INIS)

    Salakari, M.

    1996-01-01

    The Finnish Forest Research Institute inquired of the local forest management associations for their opinions about fuelwood consumption in their area. A further purpose was to establish a register of local fuelwood dealers. According to the inquiry the consumption of fuelwood has increased during the last five years and the increase will continue during the next three years. Although in some areas demand of fuelwood is greater than its supply, principally the fuelwood supply is sufficient. In Finland there seems to be 500 - 550 fuelwood dealers with sales over 50 m 3 /a. Half of them acquired the sold fuelwood from their own farm. (3 refs.)

  18. Illuminant direction estimation for a single image based on local region complexity analysis and average gray value.

    Science.gov (United States)

    Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Compare, Angelo

    2014-01-10

    Illuminant direction estimation is an important research issue in the field of image processing. Due to low cost for getting texture information from a single image, it is worthwhile to estimate illuminant direction by employing scenario texture information. This paper proposes a novel computation method to estimate illuminant direction on both color outdoor images and the extended Yale face database B. In our paper, the luminance component is separated from the resized YCbCr image and its edges are detected with the Canny edge detector. Then, we divide the binary edge image into 16 local regions and calculate the edge level percentage in each of them. Afterward, we use the edge level percentage to analyze the complexity of each local region included in the luminance component. Finally, according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model, we calculate the illuminant directions of the luminance component's three local regions, which meet the requirements of lower complexity and larger average gray value, and synthesize them as the final illuminant direction. Unlike previous works, the proposed method requires neither all of the information of the image nor the texture that is included in the training set. Experimental results show that the proposed method works better at the correct rate and execution time than the existing ones.

  19. Parametric Cost Models for Space Telescopes

    Science.gov (United States)

    Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney

    2010-01-01

    Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.

  20. Parametric cost models for space telescopes

    Science.gov (United States)

    Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtnay

    2017-11-01

    Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.

  1. Distributed push-pull estimation for node localization in wireless sensor networks

    NARCIS (Netherlands)

    Dang, Viet-Hung; Le Viet Duc, L Duc; Lee, Young-Koo; Lee, Sungyoung

    A great deal of research achievements on localization in wireless sensor networks (WSNs) has been obtained in recent years. Nevertheless, its interesting challenges in terms of cost-reduction, accuracy improvement, scalability, and distributed ability design have led to the development of a new

  2. A statistical model to estimate the local vulnerability to severe weather

    Science.gov (United States)

    Pardowitz, Tobias

    2018-06-01

    We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

  3. Estimation of local and regional components of drain - flow from an irrigated field

    International Nuclear Information System (INIS)

    Eching, S.O.; Hopmans, J.W.; Wallender, W.W.; Macyntyre, J.L.; Peters, D.

    1995-01-01

    The contribution of regional ground water and deep percolation from a furrow irrigated field to total drain flow was estimated using salt load analysis. It was found that 64% of the drain flow comes from regional ground water flow. The electrical conductivity of the drain water was highly correlated with the drain flow rate. From the field water balance with deep percolation as estimated from the salt load analysis, using yield function derived evapotranspiration, and measured changes in root zone water storage, it was shown that 14% of the crop evapotranspiration comes from ground water during the study period. 8 figs; 5 tabs; 15 refs ( Author )

  4. Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

    Science.gov (United States)

    Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

    2016-01-01

    Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

  5. Wegner estimate and localization for alloy-type models with sign-changing exponentially decaying single-site potentials

    Science.gov (United States)

    Leonhardt, Karsten; Peyerimhoff, Norbert; Tautenhahn, Martin; Veselić, Ivan

    2015-05-01

    We study Schrödinger operators on L2(ℝd) and ℓ2(ℤd) with a random potential of alloy-type. The single-site potential is assumed to be exponentially decaying but not necessarily of fixed sign. In the continuum setting, we require a generalized step-function shape. Wegner estimates are bounds on the average number of eigenvalues in an energy interval of finite box restrictions of these types of operators. In the described situation, a Wegner estimate, which is polynomial in the volume of the box and linear in the size of the energy interval, holds. We apply the established Wegner estimate as an ingredient for a localization proof via multiscale analysis.

  6. Using non-parametric methods in econometric production analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    Econometric estimation of production functions is one of the most common methods in applied economic production analysis. These studies usually apply parametric estimation techniques, which obligate the researcher to specify the functional form of the production function. Most often, the Cobb...... results—including measures that are of interest of applied economists, such as elasticities. Therefore, we propose to use nonparametric econometric methods. First, they can be applied to verify the functional form used in parametric estimations of production functions. Second, they can be directly used...

  7. An Iterative Maximum a Posteriori Estimation of Proficiency Level to Detect Multiple Local Likelihood Maxima

    Science.gov (United States)

    Magis, David; Raiche, Gilles

    2010-01-01

    In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its…

  8. Dynamic N -occupancy models: estimating demographic rates and local abundance from detection-nondetection data

    Science.gov (United States)

    Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin

    2016-01-01

    Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (“dynamic

  9. Estimation of the electric conductivity from scalp measurements: Feasibility and application to source localization

    NARCIS (Netherlands)

    van Burik, M.J.; Peters, M.J.

    2000-01-01

    Objectives: The accuracy of electrical impedance tomography was investigated. - Methods: The conductivities of the different compartments of the volume conductor were estimated by utilizing the boundary element method. The approach was tested for realistic head models with either 3 or 4

  10. GNSS-SLR satellite co-location for the estimate of local ties

    Science.gov (United States)

    Bruni, Sara; Zerbini, Susanna; Errico, Maddalena; Santi, Efisio

    2013-04-01

    The current realization of the International Terrestrial Reference Frame (ITRF) is based on four different space-geodetic techniques, so that the benefits brought by each observing system to the definition of the frame can compensate for the drawbacks of the others and technique-specific systematic errors might be identified. The strategy used to combine the observations from the different techniques is then of prominent importance for the realization of a precise and stable reference frame. This study concentrates, in particular, on the combination of Satellite Laser Ranging (SLR) and Global Navigation Satellite System (GNSS) observations by exploiting satellite co-locations. This innovative approach is based on the fact that laser tracking of GNSS satellites, carrying on board laser reflector arrays, allows for the combination of optical and microwave signals in the determination of the spacecraft orbit. Besides, the use of satellite co-locations differs quite significantly from the traditional combination method in which each single technique solution is carried out autonomously and is interrelated in a second step. One of the benefits of the approach adopted in this study is that it allows for an independent validation of the local tie, i.e. of the vector connecting the SLR and GNSS reference points in a multi-techniques station. Typically, local ties are expressed by a single value, measured with ground-based geodetic techniques and taken as constant. In principle, however, local ties might show time variations likely caused by the different monumentation characteristics of the GNSS antennas with respect to those of a SLR system. This study evaluates the possibility of using the satellite co-location approach to generate local-ties time series by means of observations available for a selected network of ILRS stations. The data analyzed in this study were acquired as part of the NASA's Earth Science Data Systems and are archived and distributed by the Crustal

  11. Estimating the Cumulative Ecological Effect of Local Scale Landscape Changes in South Florida

    Science.gov (United States)

    Hogan, Dianna M.; Labiosa, William; Pearlstine, Leonard; Hallac, David; Strong, David; Hearn, Paul; Bernknopf, Richard

    2012-01-01

    Ecosystem restoration in south Florida is a state and national priority centered on the Everglades wetlands. However, urban development pressures affect the restoration potential and remaining habitat functions of the natural undeveloped areas. Land use (LU) planning often focuses at the local level, but a better understanding of the cumulative effects of small projects at the landscape level is needed to support ecosystem restoration and preservation. The South Florida Ecosystem Portfolio Model (SFL EPM) is a regional LU planning tool developed to help stakeholders visualize LU scenario evaluation and improve communication about regional effects of LU decisions. One component of the SFL EPM is ecological value (EV), which is evaluated through modeled ecological criteria related to ecosystem services using metrics for (1) biodiversity potential, (2) threatened and endangered species, (3) rare and unique habitats, (4) landscape pattern and fragmentation, (5) water quality buffer potential, and (6) ecological restoration potential. In this article, we demonstrate the calculation of EV using two case studies: (1) assessing altered EV in the Biscayne Gateway area by comparing 2004 LU to potential LU in 2025 and 2050, and (2) the cumulative impact of adding limestone mines south of Miami. Our analyses spatially convey changing regional EV resulting from conversion of local natural and agricultural areas to urban, industrial, or extractive use. Different simulated local LU scenarios may result in different alterations in calculated regional EV. These case studies demonstrate methods that may facilitate evaluation of potential future LU patterns and incorporate EV into decision making.

  12. Estimating yellow potato (Solanum phureja Juz. et Buk.) solar radiation interception in three Colombian localities

    International Nuclear Information System (INIS)

    Cabezas, M; Corchuelo, G

    2005-01-01

    Three experiments were simultaneously carried out in three Colombian localities (Firavitoba, Carmen de Carupa y Bogotá) to measure and compare photosynthetically active radiation (PAR) interception patterns in Solanum phureja. Three random complete block design planting densities (8,33, 4.17 and 2.67 plants/m 2 ) were evaluated, having four replicates and an experimental unit consisting of five four-metre-long rows or planting lines. Overall PAR, reflected PAR, transmitted PAR and absorbed PAR were determined. The Monsie and Saeky model was used for establishing the PAR k extinction coefficient in canopies. Results revealed statistically significant differences within localities and plant densities, but not for LAI interaction. There was a higher overall incidence of radiation in those localities situated at high altitudes. PAR distribution was similar in high and low stratum in all cases, proving that plant architecture allows a suitable distribution of PAR within the canopy. The k extinction coefficient was mainly affected by leaf development. Values ranged from 0.39 to 0.61. It was revealed that plants may become quickly saturated above 2,800 m a.s.l. due to effects of luminescence, thus inducing stressful conditions interfering with leaf development and therefore distribution of tuber photo- assimilation, so affecting agronomic yield. (author) [es

  13. A single frequency component-based re-estimated MUSIC algorithm for impact localization on complex composite structures

    International Nuclear Information System (INIS)

    Yuan, Shenfang; Bao, Qiao; Qiu, Lei; Zhong, Yongteng

    2015-01-01

    The growing use of composite materials on aircraft structures has attracted much attention for impact monitoring as a kind of structural health monitoring (SHM) method. Multiple signal classification (MUSIC)-based monitoring technology is a promising method because of its directional scanning ability and easy arrangement of the sensor array. However, for applications on real complex structures, some challenges still exist. The impact-induced elastic waves usually exhibit a wide-band performance, giving rise to the difficulty in obtaining the phase velocity directly. In addition, composite structures usually have obvious anisotropy, and the complex structural style of real aircrafts further enhances this performance, which greatly reduces the localization precision of the MUSIC-based method. To improve the MUSIC-based impact monitoring method, this paper first analyzes and demonstrates the influence of measurement precision of the phase velocity on the localization results of the MUSIC impact localization method. In order to improve the accuracy of the phase velocity measurement, a single frequency component extraction method is presented. Additionally, a single frequency component-based re-estimated MUSIC (SFCBR-MUSIC) algorithm is proposed to reduce the localization error caused by the anisotropy of the complex composite structure. The proposed method is verified on a real composite aircraft wing box, which has T-stiffeners and screw holes. Three typical categories of 41 impacts are monitored. Experimental results show that the SFCBR-MUSIC algorithm can localize impact on complex composite structures with an obviously improved accuracy. (paper)

  14. SEMIPARAMETRIC VERSUS PARAMETRIC CLASSIFICATION MODELS - AN APPLICATION TO DIRECT MARKETING

    NARCIS (Netherlands)

    BULT, [No Value

    In this paper we are concerned with estimation of a classification model using semiparametric and parametric methods. Benefits and limitations of semiparametric models in general, and of Manski's maximum score method in particular, are discussed. The maximum score method yields consistent estimates

  15. 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

  16. Pinsker estimators for local helioseismology: inversion of travel times for mass-conserving flows

    International Nuclear Information System (INIS)

    Fournier, Damien; Holzke, Martin; Hohage, Thorsten; Gizon, Laurent

    2016-01-01

    A major goal of helioseismology is the three-dimensional reconstruction of the three velocity components of convective flows in the solar interior from sets of wave travel-time measurements. For small amplitude flows, the forward problem is described in good approximation by a large system of convolution equations. The input observations are highly noisy random vectors with a known dense covariance matrix. This leads to a large statistical linear inverse problem. Whereas for deterministic linear inverse problems several computationally efficient minimax optimal regularization methods exist, only one minimax-optimal linear estimator exists for statistical linear inverse problems: the Pinsker estimator. However, it is often computationally inefficient because it requires a singular value decomposition of the forward operator or it is not applicable because of an unknown noise covariance matrix, so it is rarely used for real-world problems. These limitations do not apply in helioseismology. We present a simplified proof of the optimality properties of the Pinsker estimator and show that it yields significantly better reconstructions than traditional inversion methods used in helioseismology, i.e. regularized least squares (Tikhonov regularization) and SOLA (approximate inverse) methods. Moreover, we discuss the incorporation of the mass conservation constraint in the Pinsker scheme using staggered grids. With this improvement we can reconstruct not only horizontal, but also vertical velocity components that are much smaller in amplitude. (paper)

  17. Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames.

    Science.gov (United States)

    Singh, Ajay V; Gollner, Michael J

    2016-06-01

    Modeling the realistic burning behavior of condensed-phase fuels has remained out of reach, in part because of an inability to resolve the complex interactions occurring at the interface between gas-phase flames and condensed-phase fuels. The current research provides a technique to explore the dynamic relationship between a combustible condensed fuel surface and gas-phase flames in laminar boundary layers. Experiments have previously been conducted in both forced and free convective environments over both solid and liquid fuels. A unique methodology, based on the Reynolds Analogy, was used to estimate local mass burning rates and flame heat fluxes for these laminar boundary layer diffusion flames utilizing local temperature gradients at the fuel surface. Local mass burning rates and convective and radiative heat feedback from the flames were measured in both the pyrolysis and plume regions by using temperature gradients mapped near the wall by a two-axis traverse system. These experiments are time-consuming and can be challenging to design as the condensed fuel surface burns steadily for only a limited period of time following ignition. The temperature profiles near the fuel surface need to be mapped during steady burning of a condensed fuel surface at a very high spatial resolution in order to capture reasonable estimates of local temperature gradients. Careful corrections for radiative heat losses from the thermocouples are also essential for accurate measurements. For these reasons, the whole experimental setup needs to be automated with a computer-controlled traverse mechanism, eliminating most errors due to positioning of a micro-thermocouple. An outline of steps to reproducibly capture near-wall temperature gradients and use them to assess local burning rates and heat fluxes is provided.

  18. Parametric Mass Reliability Study

    Science.gov (United States)

    Holt, James P.

    2014-01-01

    The International Space Station (ISS) systems are designed based upon having redundant systems with replaceable orbital replacement units (ORUs). These ORUs are designed to be swapped out fairly quickly, but some are very large, and some are made up of many components. When an ORU fails, it is replaced on orbit with a spare; the failed unit is sometimes returned to Earth to be serviced and re-launched. Such a system is not feasible for a 500+ day long-duration mission beyond low Earth orbit. The components that make up these ORUs have mixed reliabilities. Components that make up the most mass-such as computer housings, pump casings, and the silicon board of PCBs-typically are the most reliable. Meanwhile components that tend to fail the earliest-such as seals or gaskets-typically have a small mass. To better understand the problem, my project is to create a parametric model that relates both the mass of ORUs to reliability, as well as the mass of ORU subcomponents to reliability.

  19. Airborne DoA estimation of gunshot acoustic signals using drones with application to sniper localization systems

    Science.gov (United States)

    Fernandes, Rigel P.; Ramos, António L. L.; Apolinário, José A.

    2017-05-01

    Shooter localization systems have been subject of a growing attention lately owing to its wide span of possible applications, e.g., civil protection, law enforcement, and support to soldiers in missions where snipers might pose a serious threat. These devices are based on the processing of electromagnetic or acoustic signatures associated with the firing of a gun. This work is concerned with the latter, where the shooter's position can be obtained based on the estimation of the direction-of-arrival (DoA) of the acoustic components of a gunshot signal (muzzle blast and shock wave). A major limitation of current commercially available acoustic sniper localization systems is the impossibility of finding the shooter's position when one of these acoustic signatures is not detected. This is very likely to occur in real-life situations, especially when the microphones are not in the field of view of the shockwave or when the presence of obstacles like buildings can prevent a direct-path to sensors. This work addresses the problem of DoA estimation of the muzzle blast using a planar array of sensors deployed in a drone. Results supported by actual gunshot data from a realistic setup are very promising and pave the way for the development of enhanced sniper localization systems featuring two main advantages over stationary ones: (1) wider surveillance area; and (2) increased likelihood of a direct-path detection of at least one of the gunshot signals, thereby adding robustness and reliability to the system.

  20. Regional estimation of geomagnetically induced currents based on the local magnetic or electric field

    Directory of Open Access Journals (Sweden)

    Viljanen Ari

    2015-01-01

    Full Text Available Previous studies have demonstrated a close relationship between the time derivative of the horizontal geomagnetic field vector (dH/dt and geomagnetically induced currents (GIC at a nearby location in a power grid. Similarly, a high correlation exists between GIC and the local horizontal geoelectric field (E, typically modelled from a measured magnetic field. Considering GIC forecasting, it is not feasible to assume that detailed prediction of time series will be possible. Instead, other measures summarising the activity level over a given period are preferable. In this paper, we consider the 30-min maximum of dH/dt or E as a local activity indicator (|dH/dt|30 or |E|30. Concerning GIC, we use the sum of currents through the neutral leads at substations and apply its 30-min maximum as a regional activity measure (GIC30. We show that |dH/dt|30 at a single point yields a proxy for GIC activity in a larger region. A practical consequence is that if |dH/dt|30 can be predicted at some point then it is also possible to assess the expected GIC level in the surrounding area. As is also demonstrated, |E|30 and GIC30 depend linearly on |dH/dt|30, so there is no saturation with increasing geomagnetic activity contrary to often used activity indices.

  1. Comparison of parametric and bootstrap method in bioequivalence test.

    Science.gov (United States)

    Ahn, Byung-Jin; Yim, Dong-Seok

    2009-10-01

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

  2. An Extension to a Filter Implementation of Local Quadratic Surface for Image Noise Estimation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    1999-01-01

    Based on regression analysis this paper gives a description for simple image filter design. Specifically 3x3 filter implementations of a quadratic surface, residuals from this surface, gradients and the Laplacian are given. For the residual a 5x5 filter is given also. It is shown that the 3x3......) it is concluded that if striping is to be considered as a part of the noise, the residual from a 3x3 median filter seems best. If we are interested in a salt-and-pepper noise estimator the proposed extension to the 3x3 filter for the residual from a quadratic surface seems best. Simple statistics...

  3. Estimating the Counterparty Risk Exposure by Using the Brownian Motion Local Time

    Directory of Open Access Journals (Sweden)

    Bonollo Michele

    2017-06-01

    Full Text Available In recent years, the counterparty credit risk measure, namely the default risk in over-the-counter (OTC derivatives contracts, has received great attention by banking regulators, specifically within the frameworks of Basel II and Basel III. More explicitly, to obtain the related risk figures, one is first obliged to compute intermediate output functionals related to the mark-to-market position at a given time no exceeding a positive and finite time horizon. The latter implies an enormous amount of computational effort is needed, with related highly time consuming procedures to be carried out, turning out into significant costs. To overcome the latter issue, we propose a smart exploitation of the properties of the (local time spent by the Brownian motion close to a given value.

  4. Preliminary Estimation of Local Bypass Flow Gap Sizes for a Prismatic VHTR Core

    International Nuclear Information System (INIS)

    Kim, Min Hwan; Jo, Chang Keun; Lee, Won Jae

    2009-01-01

    The Very High Temperature Reactor (VHTR) has been selected for the Nuclear Hydrogen Development and Demonstration (NHDD) project. In the VHTR design, core bypass flow has been one of key issues for core thermal margins and target temperature of the core outlet. The core bypass flow in the prismatic VHTR varies with the core life due to the irradiation shrinkage/ swelling and thermal expansion of the graphite blocks, which could be a significant proportion of the total core flow. Thus, accurate prediction of the bypass flow is of major importance in assuring the core thermal margin. To predict the bypass flow, first of all, local gap sizes between graphite blocks in the core should be determined. The objectives of this work are to develop a methodology for determining the gap sizes and to perform a preliminary evaluation for a reference reactor

  5. Ultrasensitivity in signaling cascades revisited: Linking local and global ultrasensitivity estimations.

    Directory of Open Access Journals (Sweden)

    Edgar Altszyler

    Full Text Available Ultrasensitive response motifs, capable of converting graded stimuli into binary responses, are well-conserved in signal transduction networks. Although it has been shown that a cascade arrangement of multiple ultrasensitive modules can enhance the system's ultrasensitivity, how a given combination of layers affects a cascade's ultrasensitivity remains an open question for the general case. Here, we introduce a methodology that allows us to determine the presence of sequestration effects and to quantify the relative contribution of each module to the overall cascade's ultrasensitivity. The proposed analysis framework provides a natural link between global and local ultrasensitivity descriptors and it is particularly well-suited to characterize and understand mathematical models used to study real biological systems. As a case study, we have considered three mathematical models introduced by O'Shaughnessy et al. to study a tunable synthetic MAPK cascade, and we show how our methodology can help modelers better understand alternative models.

  6. A saliva molecular imprinted localized surface plasmon resonance biosensor for wine astringency estimation.

    Science.gov (United States)

    Guerreiro, J Rafaela L; Teixeira, Natércia; De Freitas, Victor; Sales, M Goreti F; Sutherland, Duncan S

    2017-10-15

    Wine astringency was evaluated based on the interaction of two complex matrices (red wine and saliva) by combining localized surface plasmon resonance (LSPR) and molecular imprinted polymers (MIP) at gold nanodisks as an alternative to sensorial analysis. The main objective of the work was to simulate wine astringency inside the mouth by mimicking this biological system. The LSPR/MIP sensor provided a linear response for astringency expressed in pentagalloyl glucose (PGG) units in concentrations ranging from 1 to 140μmol/L. The sensor was also applied to wine samples correlating well with sensorial analysis obtained by a trained panel. The correlation of astringency and wine composition was also evaluated showing that anthocyanins may have an important role, not only for pigmentation but also in astringency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Parametric motivation bases of floranimic nomination

    Directory of Open Access Journals (Sweden)

    Olga P. Ryabko

    2016-09-01

    Full Text Available The period of further development in the cognitive theory of nomination has been extensive in recent years. Our research has been concentrated on the formation of conceptual foundations in cognitive theory of flora nomination. The macrofield of flora namings embraces three microfields: parametric, pragmatic and locative-temporal ones. They determine motivation processes in cognitive theory of flora nomination, i.e., the presentation of systematic qualities in flora namings in the English language. The description and characterization of such qualities presupposes the existence of their taxonomic organization and methodology criteria, both general and practical ones. Flora namings on the phenomenological level are considered to be the products of naöve-cognitive consciousness of language speakers. They are determined, from the one hand, by the external perceptive adaptations (parametric nomination and, from the other hand, by practical needs (pure pragmatic nomination and local-temporal nomination. In this article we have concentrated on the complex parametric motivated basis of flora nomination. It is presented by a number of qualities, firstly, by dominative qualities («form», «appearance and manner of growth», «color», secondly, by peripheral qualities («odour», «taste», «size» and, finally, by minor qualities («sound», «weight», «genger». In the structure of complex parametric nomination the only one conerete qualitative element from the whole combination of qualities becomes the leading one. The cultural-archetypal dominant element determines. In each concrete situation, the choice of preferable prototypal motivated quality.

  8. Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation

    International Nuclear Information System (INIS)

    Zorita, E.; Hughes, J.P.

    1993-01-01

    Two statistical approaches for linking large-scale atmospheric circulation patterns and daily local rainfall are described and applied to several GCM (general circulation model) climate simulations. The ultimate objective is to simulate local precipitation associated with alternative climates. The index stations are located near the West and East North American coasts. The first method is based on CART analysis (Classification and Regression trees). It finds the classification of observed daily SLR (sea level pressure) fields in weather types that are most strongly associated with the presence/absence of rainfall in a set of index stations. The best results were obtained for winter rainfall for the West Coast, where a set of physically reasonable weather types could be identified, whereas for the East Coast the rainfall process seemed to be spatially less coherent. The GCM simulations were validated against observations in terms of probability of occurrence and survival time of these weather states. Some discrepancies werefound but there was no systematic bias, indicating that this behavior depends on the particular dynamics of each model. This classification method was then used for the generation of daily rainfall time series from the daily SLP fields from historical observation and from the GCM simulations. Whereas the mean rainfall and probability distributions were rather well replicated, the simulated dry periods were in all cases shorter than in the rainfall observations. The second rainfall generator is based on the analog method and uses information on the evolution of the SLP field in several previous days. It was found to perform reasonably well, although some downward bias in the simulated rainfall persistence was still present. Rainfall changes in a 2xCO 2 climate were investigated by applying both methods to the output of a greenhouse-gas experiment. The simulated precipitation changes were small. (orig.)

  9. Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

    Science.gov (United States)

    Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

    2012-10-12

    Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

  10. Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali

    Directory of Open Access Journals (Sweden)

    Minetti Andrea

    2012-10-01

    Full Text Available Abstract Background Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS approach has been proposed as an alternative, as smaller sample sizes are required. Methods We explored (i the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. Results VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i health areas not requiring supplemental activities; ii health areas requiring additional vaccination; iii health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3, standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Conclusions Small sample cluster surveys (10 × 15 are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

  11. Planar Parametrization in Isogeometric Analysis

    DEFF Research Database (Denmark)

    Gravesen, Jens; Evgrafov, Anton; Nguyen, Dang-Manh

    2012-01-01

    Before isogeometric analysis can be applied to solving a partial differential equation posed over some physical domain, one needs to construct a valid parametrization of the geometry. The accuracy of the analysis is affected by the quality of the parametrization. The challenge of computing...... and maintaining a valid geometry parametrization is particularly relevant in applications of isogemetric analysis to shape optimization, where the geometry varies from one optimization iteration to another. We propose a general framework for handling the geometry parametrization in isogeometric analysis and shape...... are suitable for our framework. The non-linear methods we consider are based on solving a constrained optimization problem numerically, and are divided into two classes, geometry-oriented methods and analysis-oriented methods. Their performance is illustrated through a few numerical examples....

  12. Parametric FEM for geometric biomembranes

    Science.gov (United States)

    Bonito, Andrea; Nochetto, Ricardo H.; Sebastian Pauletti, M.

    2010-05-01

    We consider geometric biomembranes governed by an L2-gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector formulation, based on shape differential calculus, and corresponding discretization via parametric FEM using quadratic isoparametric elements and a semi-implicit Euler method. We document the performance of the new parametric FEM with a number of simulations leading to dumbbell, red blood cell and toroidal equilibrium shapes while exhibiting large deformations.

  13. ModFOLD6: an accurate web server for the global and local quality estimation of 3D protein models.

    Science.gov (United States)

    Maghrabi, Ali H A; McGuffin, Liam J

    2017-07-03

    Methods that reliably estimate the likely similarity between the predicted and native structures of proteins have become essential for driving the acceptance and adoption of three-dimensional protein models by life scientists. ModFOLD6 is the latest version of our leading resource for Estimates of Model Accuracy (EMA), which uses a pioneering hybrid quasi-single model approach. The ModFOLD6 server integrates scores from three pure-single model methods and three quasi-single model methods using a neural network to estimate local quality scores. Additionally, the server provides three options for producing global score estimates, depending on the requirements of the user: (i) ModFOLD6_rank, which is optimized for ranking/selection, (ii) ModFOLD6_cor, which is optimized for correlations of predicted and observed scores and (iii) ModFOLD6 global for balanced performance. The ModFOLD6 methods rank among the top few for EMA, according to independent blind testing by the CASP12 assessors. The ModFOLD6 server is also continuously automatically evaluated as part of the CAMEO project, where significant performance gains have been observed compared to our previous server and other publicly available servers. The ModFOLD6 server is freely available at: http://www.reading.ac.uk/bioinf/ModFOLD/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Dispersive estimates for rational symbols and local well-posedness of the nonzero energy NV equation. II

    Science.gov (United States)

    Kazeykina, Anna; Muñoz, Claudio

    2018-04-01

    We continue our study on the Cauchy problem for the two-dimensional Novikov-Veselov (NV) equation, integrable via the inverse scattering transform for the two dimensional Schrödinger operator at a fixed energy parameter. This work is concerned with the more involved case of a positive energy parameter. For the solution of the linearized equation we derive smoothing and Strichartz estimates by combining new estimates for two different frequency regimes, extending our previous results for the negative energy case [18]. The low frequency regime, which our previous result was not able to treat, is studied in detail. At non-low frequencies we also derive improved smoothing estimates with gain of almost one derivative. Then we combine the linear estimates with a Fourier decomposition method and Xs,b spaces to obtain local well-posedness of NV at positive energy in Hs, s > 1/2. Our result implies, in particular, that at least for s > 1/2, NV does not change its behavior from semilinear to quasilinear as energy changes sign, in contrast to the closely related Kadomtsev-Petviashvili equations. As a complement to our LWP results, we also provide some new explicit solutions of NV at zero energy, generalizations of the lumps solutions, which exhibit new and nonstandard long time behavior. In particular, these solutions blow up in infinite time in L2.

  15. Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

    Science.gov (United States)

    Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

    2015-08-01

    Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

  16. Estimation of chromium (VI) in various body parts of local chicken

    International Nuclear Information System (INIS)

    Mahmud, T.; Rehman, R.; Anwar, J.; Abbas, A.; Farooq, M.

    2011-01-01

    Chicken is a common type of meat source in our food. It is fed with the feed containing small pieces of leather having Cr (VI) which persisted in it during chrome tanning process. The core purpose of present study was to determine the concentration of Cr (VI) in different body parts of chicken like leg, arm, head, heart, liver and bone. Estimation of Cr (VI) was done by preparing the sample solutions after ashing and digestion with nitric acid, by atomic absorption spectrophotometer. The results depicted that the meat part of leg had higher mean concentration (1.266 mg/kg) with 0.037 mg/kg standard error while the lowest average concentration was found in arm (0.233 mg/kg) with standard error as 0.019 mg/kg. In case of bones, the maximum mean concentration was found in head (1.433 mg/kg) with standard error as 0.670 mg/kg. The concentration of Cr (VI) was not found similar in meat and bones of chicken by employing Kruskal Wallis Test. (author)

  17. Parametric Portfolio Policies with Common Volatility Dynamics

    DEFF Research Database (Denmark)

    Ergemen, Yunus Emre; Taamouti, Abderrahim

    A parametric portfolio policy function is considered that incorporates common stock volatility dynamics to optimally determine portfolio weights. Reducing dimension of the traditional portfolio selection problem significantly, only a number of policy parameters corresponding to first- and second......-order characteristics are estimated based on a standard method-of-moments technique. The method, allowing for the calculation of portfolio weight and return statistics, is illustrated with an empirical application to 30 U.S. industries to study the economic activity before and after the recent financial crisis....

  18. Incorporating parametric uncertainty into population viability analysis models

    Science.gov (United States)

    McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

    2011-01-01

    Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

  19. Parametric design using IGRIP

    International Nuclear Information System (INIS)

    Baker, C.

    1994-10-01

    The Department of Energy's (DOE) Hanford site near Richland, Washington is being cleaned up after 50 years of nuclear materials production. One of the most serious problems at the site is the waste stored in single-shell underground storage tanks. There are 149 of these tanks containing the spent fuel residue remaining after the fuel is dissolved in acid and the desired materials (primarily plutonium and uranium) are separated out. The tanks are upright cylinders 75 ft. in diameter with domed tops. They are made of reinforced concrete, have steel liners, and each tank is buried under 7--12 ft. of overburden. The tanks are up to 40-ft. high, and have capacities of 500,000, 750,000, or 1,000,000 gallons of waste. As many as one-third of these tanks are known or suspected to leak. The waste form contained in the tanks varies in consistency from liquid supernatant to peanut-butter-like gels and sludges to hard salt cake (perhaps as hard as low-grade concrete). The current waste retrieval plan is to insert a large long-reach manipulator through a hole cut in the top of the tank, and use a variety of end-effectors to mobilize the waste and remove it from the tank. PNL has, with the assistance of Deneb robotics employees, developed a means of using the IGRIP code to perform parametric design of mechanical systems. This method requires no modifications to the IGRIP code, and all design data are stored in the IGRIP workcell. The method is presented in the context of development of a passive articulated mechanism that is used to deliver down-arm services to a gantry robot. The method is completely general, however, and could be used to design a fully articulated manipulator. Briefly, the method involves using IGCALC expressions to control manipulator joint angles, and IGCALC variables to allow user control of link lengths and offsets. This paper presents the method in detail, with examples drawn from PNL's experience with the gantry robot service-providing mechanism

  20. Estimate of main local sources to ambient ultrafine particle number concentrations in an urban area

    Science.gov (United States)

    Rahman, Md Mahmudur; Mazaheri, Mandana; Clifford, Sam; Morawska, Lidia

    2017-09-01

    Quantifying and apportioning the contribution of a range of sources to ultrafine particles (UFPs, D oil refineries, and seaport) sources to the total ambient particle number concentration (PNC) in a busy, inner-city area in Brisbane, Australia using Bayesian statistical modelling and other exploratory tools. The Bayesian model was trained on the PNC data on days where NP formations were known to have not occurred, hourly traffic counts, solar radiation data, and smooth daily trend. The model was applied to apportion and quantify the contribution of NP formations and local traffic and non-traffic sources to UFPs. The data analysis incorporated long-term measured time-series of total PNC (D ≥ 6 nm), particle number size distributions (PSD, D = 8 to 400 nm), PM2.5, PM10, NOx, CO, meteorological parameters and traffic counts at a stationary monitoring site. The developed Bayesian model showed reliable predictive performances in quantifying the contribution of NP formation events to UFPs (up to 4 × 104 particles cm- 3), with a significant day to day variability. The model identified potential NP formation and no-formations days based on PNC data and quantified the sources contribution to UFPs. Exploratory statistical analyses show that total mean PNC during the middle of the day was up to 32% higher than during peak morning and evening traffic periods, which were associated with NP formation events. The majority of UFPs measured during the peak traffic and NP formation periods were between 30-100 nm and smaller than 30 nm, respectively. To date, this is the first application of Bayesian model to apportion different sources contribution to UFPs, and therefore the importance of this study is not only in its modelling outcomes but in demonstrating the applicability and advantages of this statistical approach to air pollution studies.

  1. Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

    Science.gov (United States)

    Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

    2017-01-01

    The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

  2. Conditional estimation of local pooled dispersion parameter in small-sample RNA-Seq data improves differential expression test.

    Science.gov (United States)

    Gim, Jungsoo; Won, Sungho; Park, Taesung

    2016-10-01

    High throughput sequencing technology in transcriptomics studies contribute to the understanding of gene regulation mechanism and its cellular function, but also increases a need for accurate statistical methods to assess quantitative differences between experiments. Many methods have been developed to account for the specifics of count data: non-normality, a dependence of the variance on the mean, and small sample size. Among them, the small number of samples in typical experiments is still a challenge. Here we present a method for differential analysis of count data, using conditional estimation of local pooled dispersion parameters. A comprehensive evaluation of our proposed method in the aspect of differential gene expression analysis using both simulated and real data sets shows that the proposed method is more powerful than other existing methods while controlling the false discovery rates. By introducing conditional estimation of local pooled dispersion parameters, we successfully overcome the limitation of small power and enable a powerful quantitative analysis focused on differential expression test with the small number of samples.

  3. Estimation of aortic valve leaflets from 3D CT images using local shape dictionaries and linear coding

    Science.gov (United States)

    Liang, Liang; Martin, Caitlin; Wang, Qian; Sun, Wei; Duncan, James

    2016-03-01

    Aortic valve (AV) disease is a significant cause of morbidity and mortality. The preferred treatment modality for severe AV disease is surgical resection and replacement of the native valve with either a mechanical or tissue prosthetic. In order to develop effective and long-lasting treatment methods, computational analyses, e.g., structural finite element (FE) and computational fluid dynamic simulations, are very effective for studying valve biomechanics. These computational analyses are based on mesh models of the aortic valve, which are usually constructed from 3D CT images though many hours of manual annotation, and therefore an automatic valve shape reconstruction method is desired. In this paper, we present a method for estimating the aortic valve shape from 3D cardiac CT images, which is represented by triangle meshes. We propose a pipeline for aortic valve shape estimation which includes novel algorithms for building local shape dictionaries and for building landmark detectors and curve detectors using local shape dictionaries. The method is evaluated on real patient image dataset using a leave-one-out approach and achieves an average accuracy of 0.69 mm. The work will facilitate automatic patient-specific computational modeling of the aortic valve.

  4. Density estimation by maximum quantum entropy

    International Nuclear Information System (INIS)

    Silver, R.N.; Wallstrom, T.; Martz, H.F.

    1993-01-01

    A new Bayesian method for non-parametric density estimation is proposed, based on a mathematical analogy to quantum statistical physics. The mathematical procedure is related to maximum entropy methods for inverse problems and image reconstruction. The information divergence enforces global smoothing toward default models, convexity, positivity, extensivity and normalization. The novel feature is the replacement of classical entropy by quantum entropy, so that local smoothing is enforced by constraints on differential operators. The linear response of the estimate is proportional to the covariance. The hyperparameters are estimated by type-II maximum likelihood (evidence). The method is demonstrated on textbook data sets

  5. Examples in parametric inference with R

    CERN Document Server

    Dixit, Ulhas Jayram

    2016-01-01

    This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest developments and trends in statistical inference for students who do not have an advanced mathematical and statistical background. The topics discussed in the book are fundamental and common to many fields of statistical inference and thus serve as a point of departure for in-depth study. The book is divided into eight chapters: Chapter 1 provides an overview of topics on sufficiency and completeness, while Chapter 2 briefly discusses unbiased estimation. Chapter 3 focuses on the study of moments and maximum likelihood estimators, and Chapter 4 presents bounds for the variance. In Chapter 5, topics on consistent estimator are discussed. Chapter 6 discusses Bayes, while Chapter 7 studies some more powerful tests. Lastly, Chapter 8 examines unbiased and other tests. Senior undergraduate and graduate students in statistics and mathematics, and those who have taken an introductory cou...

  6. Estimation of methane emissions from local and crossbreed beef cattle in Daklak province of Vietnam

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Ramírez-Restrepo

    2017-07-01

    Full Text Available Objective This study was aimed at evaluating effects of cattle breed resources and alternative mixed-feeding practices on meat productivity and emission intensities from household farming systems (HFS in Daklak Province, Vietnam. Methods Records from Local Yellow×Red Sindhi (Bos indicus; Lai Sind and 1/2 Limousin, 1/2 Drought Master, and 1/2 Red Angus cattle during the growth (0 to 21 months and fattening (22 to 25 months periods were used to better understand variations on meat productivity and enteric methane emissions. Parameters were determined by the ruminant model. Four scenarios were developed: (HFS1 grazing from birth to slaughter on native grasses for approximately 10 h plus 1.5 kg dry matter/d (0.8% live weight [LW] of a mixture of guinea grass (19%, cassava (43% powder, cotton (23% seed, and rice (15% straw; (HFS2 growth period fed with elephant grass (1% of LW plus supplementation (1.5% of LW of rice bran (36%, maize (33%, and cassava (31% meals; and HFS3 and HFS4 computed elephant grass, but concentrate supplementation reaching 2% and 1% of LW, respectively. Results Results show that compared to HFS1, emissions (72.3±0.96 kg CH4/animal/life; least squares means± standard error of the mean were 15%, 6%, and 23% lower (p<0.01 for the HFS2, HFS3, and HFS4, respectively. The predicted methane efficiencies (CO2eq per kg of LW at slaughter (4.3±0.15, carcass weight (8.8±0.25 kg and kg of edible protein (44.1±1.29 were also lower (p<0.05 in the HFS4. In particular, irrespective of the HSF, feed supply and ratio changes had a more positive impact on emission intensities when crossbred 1/2 Red Angus cattle were fed than in their crossbred counterparts. Conclusion Modest improvements on feeding practices and integrated modelling frameworks may offer potential trade-offs to respond to climate change in Vietnam.

  7. Using velocity dispersion to estimate halo mass: Is the Local Group in tension with ΛCDM?

    Science.gov (United States)

    Elahi, Pascal J.; Power, Chris; Lagos, Claudia del P.; Poulton, Rhys; Robotham, Aaron S. G.

    2018-06-01

    Satellite galaxies are commonly used as tracers to measure the line-of-sight (LOS)velocity dispersion (σLOS) of the dark matter halo associated with their central galaxy, and thereby to estimate the halo's mass. Recent observational dispersion estimates of the Local Group, including the Milky Way and M31, suggest σ ˜50 km s-1, which is surprisingly low when compared to the theoretical expectation of σ ˜100 km s-1 for systems of their mass. Does this pose a problem for Lambda cold dark matter (ΛCDM)? We explore this tension using the SURFS suite of N-body simulations, containing over 10000 (sub)haloes with well tracked orbits. We test how well a central galaxy's host halo velocity dispersion can be recovered by sampling σLOS of subhaloes and surrounding haloes. Our results demonstrate that σLOS is biased mass proxy. We define an optimal window in vLOS and projected distance (Dp) - 0.5 ≲ Dp/Rvir ≲ 1.0 and vLOS ≲ 0.5Vesc, where Rvir is the virial radius and Vesc is the escape velocity - such that the scatter in LOS to halo dispersion is minimized - σLOS = (0.5 ± 0.1)σv, H. We argue that this window should be used to measure LOS dispersions as a proxy for mass, as it minimises scatter in the σLOS-Mvir relation. This bias also naturally explains the results from McConnachie (2012), who used similar cuts when estimating σLOS, LG, producing a bias of σLG = (0.44 ± 0.14)σv, H. We conclude that the Local Group's velocity dispersion does not pose a problem for ΛCDM and has a mass of log M_{LG, vir}/M_{⊙}=12.0^{+0.8}_{-2.0}.

  8. Estimating the snowfall limit in alpine and pre-alpine valleys: A local evaluation of operational approaches

    Science.gov (United States)

    Fehlmann, Michael; Gascón, Estíbaliz; Rohrer, Mario; Schwarb, Manfred; Stoffel, Markus

    2018-05-01

    The snowfall limit has important implications for different hazardous processes associated with prolonged or heavy precipitation such as flash floods, rain-on-snow events and freezing precipitation. To increase preparedness and to reduce risk in such situations, early warning systems are frequently used to monitor and predict precipitation events at different temporal and spatial scales. However, in alpine and pre-alpine valleys, the estimation of the snowfall limit remains rather challenging. In this study, we characterize uncertainties related to snowfall limit for different lead times based on local measurements of a vertically pointing micro rain radar (MRR) and a disdrometer in the Zulg valley, Switzerland. Regarding the monitoring, we show that the interpolation of surface temperatures tends to overestimate the altitude of the snowfall limit and can thus lead to highly uncertain estimates of liquid precipitation in the catchment. This bias is much smaller in the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which integrates surface station and remotely sensed data as well as outputs of a numerical weather prediction model. To reduce systematic error, we perform a bias correction based on local MRR measurements and thereby demonstrate the added value of such measurements for the estimation of liquid precipitation in the catchment. Regarding the nowcasting, we show that the INCA system provides good estimates up to 6 h ahead and is thus considered promising for operational hydrological applications. Finally, we explore the medium-range forecasting of precipitation type, especially with respect to rain-on-snow events. We show for a selected case study that the probability for a certain precipitation type in an ensemble-based forecast is more persistent than the respective type in the high-resolution forecast (HRES) of the European Centre for Medium Range Weather Forecasts Integrated Forecasting System (ECMWF IFS). In this case study, the

  9. STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

    International Nuclear Information System (INIS)

    David, Hugh

    1990-01-01

    1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

  10. Ionospheric modification and parametric instabilities

    International Nuclear Information System (INIS)

    Fejer, J.A.

    1979-01-01

    Thresholds and linear growth rates for stimulated Brillouin and Raman scattering and for the parametric decay instability are derived by using arguments of energy transfer. For this purpose an expression for the ponderomotive force is derived. Conditions under which the partial pressure force due to differential dissipation exceeds the ponderomotive force are also discussed. Stimulated Brillouin and Raman scattering are weakly excited by existing incoherent backscatter radars. The parametric decay instability is strongly excited in ionospheric heating experiments. Saturation theories of the parametric decay instability are therefore described. After a brief discussion of the purely growing instability the effect of using several pumps is discussed as well as the effects of inhomogenicity. Turning to detailed theories of ionospheric heating, artificial spread F is discussed in terms of a purely growing instability where the nonlinearity is due to dissipation. Field-aligned short-scale striations are explained in terms of dissipation of the parametrically excited Langmuir waves (plasma oscillations): they might be further amplified by an explosive instability (except the magnetic equator). Broadband absorption is probably responsible for the 'overshoot' effect: the initially observed level of parametrically excited Langmuir waves is much higher than the steady state level

  11. Critical sets in one-parametric mathematical programs with complementarity constraints

    NARCIS (Netherlands)

    Bouza Allende, G.; Guddat, J.; Still, Georg J.

    2008-01-01

    One-parametric mathematical programs with complementarity constraints are considered. The structure of the set of generalized critical points is analysed for the generic case. It is shown how this analysis can locally be reduced to the study of appropriate standard one-parametric finite problems. By

  12. Asymmetric gain-saturated spectrum in fiber optical parametric amplifiers

    DEFF Research Database (Denmark)

    Lali-Dastjerdi, Zohreh; Rottwitt, Karsten; Galili, Michael

    2012-01-01

    We demonstrate experimentally and numerically an unexpected spectral asymmetry in the saturated-gain spectrum of single-pump fiber optical parametric amplifiers. The interaction between higher-order four-wave mixing products and dispersive waves radiated as an effect of third-order dispersion inf...... characteristics of the amplifier and shows local maxima for specific dispersion values....

  13. Variabilidade local e regional da evapotranspiração estimada pelo algoritmo SEBAL Local and regional variability of evapotranspiration estimated by SEBAL algorithm

    Directory of Open Access Journals (Sweden)

    Luis C. J. Moreira

    2010-12-01

    Full Text Available Em face da importância em conhecer a evapotranspiração (ET para uso racional da água na irrigação no contexto atual de escassez desse recurso, algoritmos de estimativa da ET a nível regional foram desenvolvidos utilizando-se de ferramentas de sensoriamento remoto. Este estudo objetivou aplicar o algoritmo SEBAL (Surface Energy Balance Algorithms for Land em três imagens do satélite Landsat 5, do segundo semestre de 2006. As imagens correspondem a áreas irrigadas, floresta nativa densa e a Caatinga do Estado do Ceará (Baixo Acaraú, Chapada do Apodi e Chapada do Araripe. Este algoritmo calcula a evapotranspiração horária a partir do fluxo de calor latente, estimado como resíduo do balanço de energia na superfície. Os valores de ET obtidos nas três regiões foram superiores a 0,60 mm h-1 nas áreas irrigadas ou de vegetação nativa densa. As áreas de vegetação nativa menos densa apresentaram taxa da ET horária de 0,35 a 0,60 mm h-1, e valores quase nulos em áreas degradadas. A análise das médias de evapotranspiração horária pelo teste de Tukey a 5% de probabilidade permitiu evidenciar uma variabilidade significativa local, bem como regional no Estado do Ceará.In the context of water resources scarcity, the rational use of water for irrigation is necessary, implying precise estimations of the actual evapotranspiration (ET. With the recent progresses of remote-sensed technologies, regional algorithms estimating evapotranspiration from satellite observations were developed. This work aimed at applying the SEBAL algorithm (Surface Energy Balance Algorithms for Land at three Landsat-5 images during the second semester of 2006. These images cover irrigated areas, dense native forest areas and caatinga areas in three regions of the state of Ceará (Baixo Acaraú, Chapada do Apodi and Chapada do Araripe. The SEBAL algorithm calculates the hourly evapotranspiration from the latent heat flux, estimated from the surface energy

  14. Life expectancy estimation in small administrative areas with non-uniform population sizes: application to Australian New South Wales local government areas

    OpenAIRE

    Stephens, Alexandre S; Purdie, Stuart; Yang, Baohui; Moore, Helen

    2013-01-01

    Objective To determine a practical approach for deriving life expectancy estimates in Australian New South Wales local government areas which display a large diversity in population sizes. Design Population-based study utilising mortality and estimated residential population data. Setting 153 local government areas in New South Wales, Australia. Outcome measures Key performance measures of Chiang II, Silcocks, adjusted Chiang II and Bayesian random effects model methodologies of life expectan...

  15. Parametric Thinking in Urban Design

    DEFF Research Database (Denmark)

    Steinø, Nicolai

    2010-01-01

    The paper states that most applications of parametric mod- elling to architecture and urban design fall into one of two strands of either form for form’s sake, or the negotiation of environmental con- cerns, while approaches which allow scenarios to be easily tested and modified without the appli...... of the paper. The pros and cons of this simple approach is discussed, and the paper con- cludes, that while it does not represent a suitable solution in all cases, it fills a gap among the existing approaches to parametric urban de- sign.......The paper states that most applications of parametric mod- elling to architecture and urban design fall into one of two strands of either form for form’s sake, or the negotiation of environmental con- cerns, while approaches which allow scenarios to be easily tested and modified without...

  16. Improving the Estimation of Local Welfare Costs of Conservation in Low-Income Countries Using Choice Experiments

    DEFF Research Database (Denmark)

    Rakotonarivo, Onjamirindra Sarobidy

    and comprises a systematic review and three field tests of DCE in a new REDD+ (Reducing Emissions from Deforestation and forest Degradation) project and national park in eastern Madagascar. I first conducted a systematic review of empirical evidence on the reliability and validity of DCEs when valuing non-market...... the validity of DCE in estimating the costs of conservation restrictions ex-ante. I found that experience of forest protection matters; households who have been exposed to forest protection for a comparatively longer period had significantly higher welfare costs for restricting forest clearance than those who...... techniques. It also has major implications for how forest conservation policy may be devised in low-income countries, including devolution of secure forestland tenure to local people and genuinely negotiating conservation with forest users....

  17. Optimal Design of Experiments for Parametric Identification of Civil Engineering Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning

    Optimal Systems of experiments for parametric identification of civil engineering structures is investigated. Design of experiments for parametric identification of dynamic systems is usually done by minimizing a scalar measure, e.g the determinant, the trace ect., of an estimated parameter...

  18. Entanglement in a parametric converter

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Su-Yong; Qamar, Shahid; Lee, Hai-Woong; Zubairy, M Suhail [Center for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan)], E-mail: shahid_qamar@pieas.edu.pk, E-mail: zubairy@physics.tamu.edu

    2008-07-28

    In this paper, we consider a parametric converter as a source of entangled radiation. We examine recently derived conditions (Hillery and Zubairy 2006 Phys. Rev. Lett. 96 050503, Duan et al 2000 Phys. Rev. Lett. 84 2722) for determining when the two output modes in a parametric converter are entangled. We show that for different initial field states, the two criteria give different conditions that ensure that the output states are entangled. We also present an input-output calculation for the entanglement of the output field.

  19. The Impact of Star Formation Histories on Stellar Mass Estimation: Implications from the Local Group Dwarf Galaxies

    Science.gov (United States)

    Zhang, Hong-Xin; Puzia, Thomas H.; Weisz, Daniel R.

    2017-11-01

    Building on the relatively accurate star formation histories (SFHs) and metallicity evolution of 40 Local Group (LG) dwarf galaxies derived from resolved color-magnitude diagram modeling, we carried out a comprehensive study of the influence of SFHs, metallicity evolution, and dust extinction on the UV-to-near-IR color-mass-to-light ratio (color-{log}{{{\\Upsilon }}}\\star (λ)) distributions and M ⋆ estimation of local universe galaxies. We find that (1) the LG galaxies follow color-{log}{{{\\Upsilon }}}\\star (λ) relations that fall in between the ones calibrated by previous studies; (2) optical color-{log}{{{\\Upsilon }}}\\star (λ) relations at higher [M/H] are generally broader and steeper; (3) the SFH “concentration” does not significantly affect the color-{log}{{{\\Upsilon }}}\\star (λ) relations; (4) light-weighted ages }λ and metallicities }λ together constrain {log}{{{\\Upsilon }}}\\star (λ) with uncertainties ranging from ≲0.1 dex for the near-IR up to 0.2 dex for the optical passbands; (5) metallicity evolution induces significant uncertainties to the optical but not near-IR {{{\\Upsilon }}}\\star (λ) at a given }λ and }λ ; (6) the V band is the ideal luminance passband for estimating {{{\\Upsilon }}}\\star (λ) from single colors, because the combinations of {{{\\Upsilon }}}\\star (V) and optical colors such as B - V and g - r exhibit the weakest systematic dependences on SFHs, metallicities, and dust extinction; and (7) without any prior assumption on SFHs, M ⋆ is constrained with biases ≲0.3 dex by the optical-to-near-IR SED fitting. Optical passbands alone constrain M ⋆ with biases ≲0.4 dex (or ≲0.6 dex) when dust extinction is fixed (or variable) in SED fitting. SED fitting with monometallic SFH models tends to underestimate M ⋆ of real galaxies. M ⋆ tends to be overestimated (or underestimated) at the youngest (or oldest) }{mass}.

  20. Estimation of efficiency of new local rehabilitation method at the early post-operative period after dental implantation

    Directory of Open Access Journals (Sweden)

    A. V. Pasechnik

    2017-01-01

      Summary Despite of success of dental implantation, there are often complications at the early post-operative period of implant placing associated with wound damage and aseptic inflammation. Purpose of the work is studying clinical efficiency of combined local application of new mucosal gel “Apior” and magnetotherapy at the early post-operative period after dental implantation. Combined local application of the mucosal gel “Apior” and pulsating low-frequency electromagnetic field in the complex medical treatment of patients after conducting an operation of setting dental implants favourably affects the common state of patients and clinical symptoms of inflammation in the area of operating wound. As compared with patients who had traditional anti-inflammatory therapy, the patients treated with local application of apigel and magnetoterapy had decline of edema incidence, of gingival mucosa hyperemia, of discomfort in the area of conducted operation. There occurred more rapid improvement of inflammation painfulness, which correlated with the improvement of hygienic state of oral cavity and promoted to prevention of bacterial content of damaged mucous surfaces. Estimation of microvasculatory blood stream by the method of ultrasonic doppler flowmetry revealed more rapid normalization of volume and linear high systole speed of blood stream in the periimplant tissues in case of use of new complex local rehabilitation method, that testified to the less pronounced inflammation of oral mucosa after the operation. The authors came to conclusion that the local application of the offered method of medical treatment of early post-operative complications of dental implantation reduces terms of renewal of structural-functional integrity of oral mucosa, helps in preventing development of inflammatory complications and strengthening endosseus implant. The inclusion in the treatment management of a new combined method of application of mucosal gel “Apior” and

  1. Non-Parametric Analysis of Rating Transition and Default Data

    DEFF Research Database (Denmark)

    Fledelius, Peter; Lando, David; Perch Nielsen, Jens

    2004-01-01

    We demonstrate the use of non-parametric intensity estimation - including construction of pointwise confidence sets - for analyzing rating transition data. We find that transition intensities away from the class studied here for illustration strongly depend on the direction of the previous move b...

  2. The construction of a decision tool to analyse local demand and local supply for GP care using a synthetic estimation model

    NARCIS (Netherlands)

    de Graaf-Ruizendaal, Willemijn A.; de Bakker, Dinny H.

    2013-01-01

    Background This study addresses the growing academic and policy interest in the appropriate provision of local healthcare services to the healthcare needs of local populations to increase health status and decrease healthcare costs. However, for most local areas information on the demand for primary

  3. Estimation of mercury emissions from forest fires, lakes, regional and local sources using measurements in Milwaukee and an inverse method

    Directory of Open Access Journals (Sweden)

    B. de Foy

    2012-10-01

    Full Text Available Gaseous elemental mercury is a global pollutant that can lead to serious health concerns via deposition to the biosphere and bio-accumulation in the food chain. Hourly measurements between June 2004 and May 2005 in an urban site (Milwaukee, WI show elevated levels of mercury in the atmosphere with numerous short-lived peaks as well as longer-lived episodes. The measurements are analyzed with an inverse model to obtain information about mercury emissions. The model is based on high resolution meteorological simulations (WRF, hourly back-trajectories (WRF-FLEXPART and a chemical transport model (CAMx. The hybrid formulation combining back-trajectories and Eulerian simulations is used to identify potential source regions as well as the impacts of forest fires and lake surface emissions. Uncertainty bounds are estimated using a bootstrap method on the inversions. Comparison with the US Environmental Protection Agency's National Emission Inventory (NEI and Toxic Release Inventory (TRI shows that emissions from coal-fired power plants are properly characterized, but emissions from local urban sources, waste incineration and metal processing could be significantly under-estimated. Emissions from the lake surface and from forest fires were found to have significant impacts on mercury levels in Milwaukee, and to be underestimated by a factor of two or more.

  4. Parametrization of contrails in a comprehensive climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ponater, M; Brinkop, S; Sausen, R; Schumann, U [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere

    1998-12-31

    A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.

  5. Parametrization of contrails in a comprehensive climate model

    Energy Technology Data Exchange (ETDEWEB)

    Ponater, M.; Brinkop, S.; Sausen, R.; Schumann, U. [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere

    1997-12-31

    A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.

  6. PARAMETRIC MODEL OF LUMBAR VERTEBRA

    Directory of Open Access Journals (Sweden)

    CAPPETTI Nicola

    2010-11-01

    Full Text Available The present work proposes the realization of a parametric/variational CAD model of a normotype lumbar vertebra, which could be used for improving the effectiveness of actual imaging techniques in informational augmentation of the orthopaedic and traumatological diagnosis. In addition it could be used for ergonomic static and dynamical analysis of the lumbar region and vertebral column.

  7. Parametric programming of industrial robots

    Directory of Open Access Journals (Sweden)

    Szulczyński Paweł

    2015-06-01

    Full Text Available This article proposes the use of parametric design software, commonly used by architects, in order to obtain complex trajectory and program code for industrial robots. The paper describes the drawbacks of existing solutions and proposes a new script to obtain a correct program. The result of the algorithm was verified experimentally.

  8. Relational Parametricity and Separation Logic

    DEFF Research Database (Denmark)

    Birkedal, Lars; Yang, Hongseok

    2008-01-01

    Separation logic is a recent extension of Hoare logic for reasoning about programs with references to shared mutable data structures. In this paper, we provide a new interpretation of the logic for a programming language with higher types. Our interpretation is based on Reynolds's relational...... parametricity, and it provides a formal connection between separation logic and data abstraction. Udgivelsesdato: 2008...

  9. Quantum tomography enhanced through parametric amplification

    Science.gov (United States)

    Knyazev, E.; Spasibko, K. Yu; Chekhova, M. V.; Khalili, F. Ya

    2018-01-01

    Quantum tomography is the standard method of reconstructing the Wigner function of quantum states of light by means of balanced homodyne detection. The reconstruction quality strongly depends on the photodetectors quantum efficiency and other losses in the measurement setup. In this article we analyze in detail a protocol of enhanced quantum tomography, proposed by Leonhardt and Paul [1] which allows one to reduce the degrading effect of detection losses. It is based on phase-sensitive parametric amplification, with the phase of the amplified quadrature being scanned synchronously with the local oscillator phase. Although with sufficiently strong amplification the protocol enables overcoming any detection inefficiency, it was so far not implemented in the experiment, probably due to the losses in the amplifier. Here we discuss a possible proof-of-principle experiment with a traveling-wave parametric amplifier. We show that with the state-of-the-art optical elements, the protocol enables high fidelity tomographic reconstruction of bright non-classical states of light. We consider two examples: bright squeezed vacuum and squeezed single-photon state, with the latter being a non-Gaussian state and both strongly affected by the losses.

  10. Towards a parametrization of multiparticle hadronic reactions

    International Nuclear Information System (INIS)

    Giffon, M.; Hama, Y.; Predazzi, E.

    1979-11-01

    An explicit parametrization of high energy exclusive production cross-sections is shown to give a reasonable account of inclusive data. This is a first step towards a phenomenological parametrization of multiparticle hadronic amplitudes

  11. Bianchi surfaces: integrability in an arbitrary parametrization

    International Nuclear Information System (INIS)

    Nieszporski, Maciej; Sym, Antoni

    2009-01-01

    We discuss integrability of normal field equations of arbitrarily parametrized Bianchi surfaces. A geometric definition of the Bianchi surfaces is presented as well as the Baecklund transformation for the normal field equations in an arbitrarily chosen surface parametrization.

  12. Parametric uncertainty in optical image modeling

    Science.gov (United States)

    Potzick, James; Marx, Egon; Davidson, Mark

    2006-10-01

    Optical photomask feature metrology and wafer exposure process simulation both rely on optical image modeling for accurate results. While it is fair to question the accuracies of the available models, model results also depend on several input parameters describing the object and imaging system. Errors in these parameter values can lead to significant errors in the modeled image. These parameters include wavelength, illumination and objective NA's, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k, etc. for the object. In this paper each input parameter is varied over a range about its nominal value and the corresponding images simulated. Second order parameter interactions are not explored. Using the scenario of the optical measurement of photomask features, these parametric sensitivities are quantified by calculating the apparent change of the measured linewidth for a small change in the relevant parameter. Then, using reasonable values for the estimated uncertainties of these parameters, the parametric linewidth uncertainties can be calculated and combined to give a lower limit to the linewidth measurement uncertainty for those parameter uncertainties.

  13. Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

    NARCIS (Netherlands)

    Kotasidis, F. A.; Mehranian, A.; Zaidi, H.

    2016-01-01

    Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from

  14. Detection of Parametric Roll on Ships

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Blanke, Mogens; Poulsen, Niels Kjølstad

    2012-01-01

    phenomenon could make the navigator change ship’s speed and heading, and these remedial actions could make the vessel escape the bifurcation. This chapter proposes non-parametric methods to detect the onset of parametric roll resonance. Theoretical conditions for parametric resonance are re...... on experimental data from towing tank tests and data from a container ship passing an Atlantic storm....

  15. Estimation of the local and long-range contributions to particulate matter levels using continuous measurements in a single urban background site

    Science.gov (United States)

    Diamantopoulou, Marianna; Skyllakou, Ksakousti; Pandis, Spyros N.

    2016-06-01

    The Particulate Matter Source Apportionment Technology (PSAT) algorithm is used together with PMCAMx, a regional chemical transport model, to develop a simple observation-based method (OBM) for the estimation of local and regional contributions of sources of primary and secondary pollutants in urban areas. We test the hypothesis that the minimum of the diurnal average concentration profile of the pollutant is a good estimate of the average contribution of long range transport levels. We use PMCAMx to generate "pseudo-observations" for four different European cities (Paris, London, Milan, and Dusseldorf) and PSAT to estimate the corresponding "true" local and regional contributions. The predictions of the proposed OBM are compared to the "true" values for different definitions of the source area. During winter, the estimates by the OBM for the local contributions to the concentrations of total PM2.5, primary pollutants, and sulfate are within 25% of the "true" contributions of the urban area sources. For secondary organic aerosol the OBM overestimates the importance of the local sources and it actually estimates the contributions of sources within 200 km from the receptor. During summer for primary pollutants and cities with low nearby emissions (ratio of emissions in an area extending 100 km from the city over local emissions lower than 10) the OBM estimates correspond to the city emissions within 25% or so. For cities with relatively high nearby emissions the OBM estimates correspond to emissions within 100 km from the receptor. For secondary PM2.5 components like sulfate and secondary organic aerosol the OBM's estimates correspond to sources within 200 km from the receptor. Finally, for total PM2.5 the OBM provides approximately the contribution of city emissions during the winter and the contribution of sources within 100 km from the receptor during the summer.

  16. Parametric resonance in quantum electrodynamics vacuum birefringence

    Science.gov (United States)

    Arza, Ariel; Elias, Ricardo Gabriel

    2018-05-01

    Vacuum magnetic birefringence is one of the most interesting nonlinear phenomena in quantum electrodynamics because it is a pure photon-photon result of the theory and it directly signalizes the violation of the classical superposition principle of electromagnetic fields in the full quantum theory. We perform analytical and numerical calculations when an electromagnetic wave interacts with an oscillating external magnetic field. We find that in an ideal cavity, when the external field frequency is around the electromagnetic wave frequency, the normal and parallel components of the wave suffer parametric resonance at different rates, producing a vacuum birefringence effect growing in time. We also study the case where there is no cavity and the oscillating magnetic field is spatially localized in a region of length L . In both cases we find also a rotation of the elliptical axis.

  17. Parametric HMMs for Movement Recognition and Synthesis

    DEFF Research Database (Denmark)

    Herzog, Dennis; Krüger, Volker

    2009-01-01

    , we develop an exemplar-based parametric hidden Markov model (PHMM) that allows to represent movements of a particular type. Since we use model interpolation to reduce the necessary amount of training data, we had to develop a method to setup local models in a synchronized way. In our experiments we......A common problem in human movement recognition is the recognition of movements of a particular type (semantic). E.g., grasping movements have a particular semantic (grasping) but the actual movements usually have very different appearances due to, e.g., different grasping directions. In this paper...... to recover the movement type, and, e.g., the object position a human is pointing at. Our experiments show the flexibility of the PHMMs in terms of the amount of training data and its robustness in terms of noisy observation data. In addition, we compare our PHMM to an other kind of PHMM, which has been...

  18. Parametric Design Strategies for Collaborative Urban Design

    DEFF Research Database (Denmark)

    Steinø, Nicolai; Yıldırım, Miray Baş; Özkar, Mine

    2013-01-01

    to the collaboration between professionals, participation by different non-professional stakeholders, such as residents, local authorities, non-governmental organizations and investors, is another important component of collaborative urban design processes. The involvement of community in decision making process...... implications of planning and design decisions, unless they are presented with relatively detailed architectural models, whether physical or virtual. This however, typically presents steep demands in terms of time and resources. As a foundation for our work with parametric urban design lies the hypothesis...... to solve different scripting challenges. The paper is organized into an introduction, three main sections and closing section with conclusions and perspectives. The first section of the paper gives a theoretical discussion of the notion of collaborative design and the challenges of collaborative urban...

  19. A Novel Differential Time-of-Arrival Estimation Technique for Impact Localization on Carbon Fiber Laminate Sheets

    Directory of Open Access Journals (Sweden)

    Eugenio Marino Merlo

    2017-10-01

    Full Text Available Composite material structures are commonly used in many industrial sectors (aerospace, automotive, transportation, and can operate in harsh environments where impacts with other parts or debris may cause critical safety and functionality issues. This work presents a method for improving the accuracy of impact position determination using acoustic source triangulation schemes based on the data collected by piezoelectric sensors attached to the structure. A novel approach is used to estimate the Differential Time-of-Arrival (DToA between the impact response signals collected by a triplet of sensors, overcoming the limitations of classical methods that rely on amplitude thresholds calibrated for a specific sensor type. An experimental evaluation of the proposed technique was performed with specially made circular piezopolymer (PVDF sensors designed for Structural Health Monitoring (SHM applications, and compared with commercial piezoelectric SHM sensors of similar dimensions. Test impacts at low energies from 35 mJ to 600 mJ were generated in a laboratory by free-falling metal spheres on a 500 mm × 500 mm × 1.25 mm quasi-isotropic Carbon Fiber Reinforced Polymer (CFRP laminate plate. From the analysis of many impact signals, the resulting localization error was improved for all types of sensors and, in particular, for the circular PVDF sensor an average error of 20.3 mm and a standard deviation of 8.9 mm was obtained.

  20. Interactive Dimensioning of Parametric Models

    KAUST Repository

    Kelly, T.

    2015-06-22

    We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.

  1. Parametric Optimization of Hospital Design

    DEFF Research Database (Denmark)

    Holst, Malene Kirstine; Kirkegaard, Poul Henning; Christoffersen, L.D.

    2013-01-01

    Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements...... and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences....

  2. Parametric decay of the curvaton

    International Nuclear Information System (INIS)

    Enqvist, K; Nurmi, S; Rigopoulos, G I

    2008-01-01

    We argue that the curvaton decay takes place most naturally by way of a broad parametric resonance. The mechanism is analogous to resonant inflaton decay but does not require any tuning of the curvaton coupling strength to other scalar fields. For low scale inflation and a correspondingly low mass scale for the curvaton, we speculate on observable consequences including the possibility of stochastic gravitational waves

  3. New estimates of direct N2O emissions from Chinese croplands from 1980 to 2007 using localized emission factors

    Directory of Open Access Journals (Sweden)

    F. S. Zhang

    2011-10-01

    Full Text Available Nitrous oxide (N2O is a long-lived greenhouse gas with a large radiation intensity and it is emitted mainly from agricultural land. Accurate estimates of total direct N2O emissions from croplands on a country scale are important for global budgets of anthropogenic sources of N2O emissions and for the development of effective mitigation strategies. The objectives of this study were to re-estimate direct N2O emissions using localized emission factors and a database of measurements from Chinese croplands. We obtained N2O emission factors for paddy fields (0.41 ± 0.04% and uplands (1.05 ± 0.02% from a normalization process through cube root transformation of the original data. After comparing the results of normalization from the original values, Logarithmic and cube root transformations were used because the frequency of the original data was not normally distributed. Direct N2O emissions from Chinese croplands from 1980 to 2007 were estimated using IPCC (2006 guidelines combined with separate localized emission factors for paddy fields and upland areas. Direct N2O emissions from paddy fields showed little change, increasing by 10.5% with an annual rate of increase of 0.4% from 32.3 Gg N2O-N in 1980 to 35.7 Gg N2O-N in 2007. In contrast, emissions from uplands changed dramatically, increasing by 308% with an annual rate of 11% from 68.0 Gg N2O-N in 1980 to 278 Gg N2O-N in 2007. Total direct N2O emissions from Chinese croplands increased by 213% with an annual rate of 7.6% from 100 Gg N2O-N in 1980 to 313 Gg N2O-N in 2007, and were determined mainly by upland emissions (accounting for 67.8–88.6% of total emissions from 1980 to 2007. Synthetic N fertilizers played a major role in N2O emissions from agricultural land, and the magnitude of the contributions to total direct N2O emissions made by different amendments was synthetic N fertilizer > manure > straw, representing about 78, 15, and 6% of total direct N2O emissions, respectively, between

  4. A Transformational Approach to Parametric Accumulated-Cost Static Profiling

    DEFF Research Database (Denmark)

    Haemmerlé, Rémy; López García, Pedro; Liqat, Umer

    2016-01-01

    Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound...... of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based...... on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource...

  5. Parametric Fires for Structural Design

    DEFF Research Database (Denmark)

    Hertz, Kristian

    2012-01-01

    The authorities, the construction association, and a number of companies in Denmark have supported the author writing a guide for design of building structures for parametric fires. The guide is published by the ministry as a supplement to the building regulations. However, consultants and contra......The authorities, the construction association, and a number of companies in Denmark have supported the author writing a guide for design of building structures for parametric fires. The guide is published by the ministry as a supplement to the building regulations. However, consultants...... and contractors have asked for a reference in English in order to make the guide-lines and the background for them available internationally. The paper therefore presents recommendations from the design guide especially concerning how to assess parametric design fires based on the opening factor method for large...... compartments. Findings leading to the guide-lines are discussed, and it is indicated what a safe design fire model means for structural design and how it differs from a safe design fire model for evacuation. Furthermore, the paper includes some experiences from the application of the design guide in practise...

  6. Upper Estimates on the Higher-dimensional Multifractal Spectrum of Local Entropy%局部熵高维重分形谱的上界估计

    Institute of Scientific and Technical Information of China (English)

    严珍珍; 陈二才

    2008-01-01

    We discuss the problem of higher-dimensional multifractal spectrum of lo-cal entropy for arbitrary invariant measures. By utilizing characteristics of a dynam-ical system, namely, higher-dimensional entropy capacities and higher-dimensional correlation entropies, we obtain three upper estimates on the higher-dimensional mul-tifractal spectrum of local entropies. We also study the domain of higher-dimensional multifractal spetrum of entropies.

  7. The impact of parametrized convection on cloud feedback

    Science.gov (United States)

    Webb, Mark J.; Lock, Adrian P.; Bretherton, Christopher S.; Bony, Sandrine; Cole, Jason N. S.; Idelkadi, Abderrahmane; Kang, Sarah M.; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C.; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D.; Zhao, Ming

    2015-01-01

    We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud

  8. Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling

    International Nuclear Information System (INIS)

    Liehn, J.C.; Hannequin, P.; Valeyre, J.

    1989-01-01

    This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr

  9. Stellar parametrization from Gaia RVS spectra

    Science.gov (United States)

    Recio-Blanco, A.; de Laverny, P.; Allende Prieto, C.; Fustes, D.; Manteiga, M.; Arcay, B.; Bijaoui, A.; Dafonte, C.; Ordenovic, C.; Ordoñez Blanco, D.

    2016-01-01

    Context. Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as GRVS~ 16. A specific stellar parametrization will be performed on most of these RVS spectra, I.e. those with enough high signal-to-noise ratio (S/N), which should correspond to single stars that have a magnitude in the RVS band brighter than ~14.5. Some individual chemical abundances will also be estimated for the brightest targets. Aims: We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-Spec working group of the analysis consortium. The tested codes are based on optimisation (FERRE and GAUGUIN), projection (MATISSE), or pattern-recognition methods (Artificial Neural Networks). We present and discuss each of their expected performances in the recovered stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity) for B- to K-type stars. The performances for determining of [α/Fe] ratios are also presented for cool stars. Methods: Each code has been homogeneously tested with a large grid of RVS simulated synthetic spectra of BAFGK-spectral types (dwarfs and giants), with metallicities varying from 10-2.5 to 10+ 0.5 the solar metallicity, and taking variations of ±0.4 dex in the composition of the α-elements into consideration. The tests were performed for S/N ranging from ten to 350. Results: For all the stellar types we considered, stars brighter than GRVS~ 12.5 are very efficiently parametrized by the GSP-Spec pipeline, including reliable estimations of [α/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40 K in Teff, 0.10 dex in log(g), 0.04 dex in [M/H], and 0.03 dex in [α/Fe] at GRVS = 10.3. They degrade to 155 K in Teff, 0.15 dex in log(g), 0.10 dex in [M/H], and 0.1 dex in [α/Fe] at GRVS~ 12. Similar accuracies in Teff and [M/H] are

  10. Life expectancy estimation in small administrative areas with non-uniform population sizes: application to Australian New South Wales local government areas.

    Science.gov (United States)

    Stephens, Alexandre S; Purdie, Stuart; Yang, Baohui; Moore, Helen

    2013-12-02

    To determine a practical approach for deriving life expectancy estimates in Australian New South Wales local government areas which display a large diversity in population sizes. Population-based study utilising mortality and estimated residential population data. 153 local government areas in New South Wales, Australia. Key performance measures of Chiang II, Silcocks, adjusted Chiang II and Bayesian random effects model methodologies of life expectancy estimation including agreement analysis of life expectancy estimates and comparison of estimate SEs. Chiang II and Silcocks methods produced almost identical life expectancy estimates across a large range of population sizes but calculation failures and excessively large SEs limited their use in small populations. A population of 25 000 or greater was required to estimate life expectancy with SE of 1 year or less using adjusted Chiang II (a composite of Chiang II and Silcocks methods). Data aggregation offered some remedy for extending the use of adjusted Chiang II in small populations but reduced estimate currency. A recently developed Bayesian random effects model utilising the correlation in mortality rates between genders, age groups and geographical areas markedly improved the precision of life expectancy estimates in small populations. We propose a hybrid approach for the calculation of life expectancy using the Bayesian random effects model in populations of 25 000 or lower permitting the precise derivation of life expectancy in small populations. In populations above 25 000, we propose the use of adjusted Chiang II to guard against violations of spatial correlation, to benefit from a widely accepted method that is simpler to communicate to local health authorities and where its slight inferior performance compared with the Bayesian approach is of minor practical significance.

  11. A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy.

    Science.gov (United States)

    Corbett-Detig, Russell; Nielsen, Rasmus

    2017-01-01

    Admixture-the mixing of genomes from divergent populations-is increasingly appreciated as a central process in evolution. To characterize and quantify patterns of admixture across the genome, a number of methods have been developed for local ancestry inference. However, existing approaches have a number of shortcomings. First, all local ancestry inference methods require some prior assumption about the expected ancestry tract lengths. Second, existing methods generally require genotypes, which is not feasible to obtain for many next-generation sequencing projects. Third, many methods assume samples are diploid, however a wide variety of sequencing applications will fail to meet this assumption. To address these issues, we introduce a novel hidden Markov model for estimating local ancestry that models the read pileup data, rather than genotypes, is generalized to arbitrary ploidy, and can estimate the time since admixture during local ancestry inference. We demonstrate that our method can simultaneously estimate the time since admixture and local ancestry with good accuracy, and that it performs well on samples of high ploidy-i.e. 100 or more chromosomes. As this method is very general, we expect it will be useful for local ancestry inference in a wider variety of populations than what previously has been possible. We then applied our method to pooled sequencing data derived from populations of Drosophila melanogaster on an ancestry cline on the east coast of North America. We find that regions of local recombination rates are negatively correlated with the proportion of African ancestry, suggesting that selection against foreign ancestry is the least efficient in low recombination regions. Finally we show that clinal outlier loci are enriched for genes associated with gene regulatory functions, consistent with a role of regulatory evolution in ecological adaptation of admixed D. melanogaster populations. Our results illustrate the potential of local ancestry

  12. A parametric costing model for wave energy technology

    International Nuclear Information System (INIS)

    1992-01-01

    This document describes the philosophy and technical approach to a parametric cost model for offshore wave energy systems. Consideration is given both to existing known devices and other devices yet to be conceptualised. The report is complementary to a spreadsheet based cost estimating model. The latter permits users to derive capital cost estimates using either inherent default data or user provided data, if a particular scheme provides sufficient design definition for more accurate estimation. The model relies on design default data obtained from wave energy device designs and a set of specifically collected cost data. (author)

  13. Parametric Verification of Weighted Systems

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Hansen, Mikkel; Mariegaard, Anders

    2015-01-01

    are themselves indexed with linear equations. The parameters change the model-checking problem into a problem of computing a linear system of inequalities that characterizes the parameters that guarantee the satisfiability. To address this problem, we use parametric dependency graphs (PDGs) and we propose...... a global update function that yields an assignment to each node in a PDG. For an iterative application of the function, we prove that a fixed point assignment to PDG nodes exists and the set of assignments constitutes a well-quasi ordering, thus ensuring that the fixed point assignment can be found after...

  14. Parametric Sensibility in Lixiviation Reactors

    Directory of Open Access Journals (Sweden)

    Dra. Margarita Rivera-Soto

    2015-11-01

    Full Text Available This work presents the results obtained in an analysis of the parametric sensibility, on the base of a mathematical model, which describes the behavior a lixiviation reactors battery inside the limits of the habitual work of the industrial plant, in a concrete process and of high complexity. The analysis was carried out with the purpose of determining the effect that the changes in different operation variables have on the behavior of the system and it gave as result that the most important variables are: the mineral-acid relationship, the concentration of magnesium and of nickel.

  15. Bim and Gis: when Parametric Modeling Meets Geospatial Data

    Science.gov (United States)

    Barazzetti, L.; Banfi, F.

    2017-12-01

    Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building) scale to the infrastructure (where geospatial data cannot be neglected) has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by "pure" GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator) industry, as well as new solutions for parametric modelling with additional geoinformation.

  16. BIM AND GIS: WHEN PARAMETRIC MODELING MEETS GEOSPATIAL DATA

    Directory of Open Access Journals (Sweden)

    L. Barazzetti

    2017-12-01

    Full Text Available Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building scale to the infrastructure (where geospatial data cannot be neglected has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by “pure” GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator industry, as well as new solutions for parametric modelling with additional geoinformation.

  17. Evaluation of Two Energy Balance Closure Parametrizations

    Science.gov (United States)

    Eder, Fabian; De Roo, Frederik; Kohnert, Katrin; Desjardins, Raymond L.; Schmid, Hans Peter; Mauder, Matthias

    2014-05-01

    A general lack of energy balance closure indicates that tower-based eddy-covariance (EC) measurements underestimate turbulent heat fluxes, which calls for robust correction schemes. Two parametrization approaches that can be found in the literature were tested using data from the Canadian Twin Otter research aircraft and from tower-based measurements of the German Terrestrial Environmental Observatories (TERENO) programme. Our analysis shows that the approach of Huang et al. (Boundary-Layer Meteorol 127:273-292, 2008), based on large-eddy simulation, is not applicable to typical near-surface flux measurements because it was developed for heights above the surface layer and over homogeneous terrain. The biggest shortcoming of this parametrization is that the grid resolution of the model was too coarse so that the surface layer, where EC measurements are usually made, is not properly resolved. The empirical approach of Panin and Bernhofer (Izvestiya Atmos Oceanic Phys 44:701-716, 2008) considers landscape-level roughness heterogeneities that induce secondary circulations and at least gives a qualitative estimate of the energy balance closure. However, it does not consider any feature of landscape-scale heterogeneity other than surface roughness, such as surface temperature, surface moisture or topography. The failures of both approaches might indicate that the influence of mesoscale structures is not a sufficient explanation for the energy balance closure problem. However, our analysis of different wind-direction sectors shows that the upwind landscape-scale heterogeneity indeed influences the energy balance closure determined from tower flux data. We also analyzed the aircraft measurements with respect to the partitioning of the "missing energy" between sensible and latent heat fluxes and we could confirm the assumption of scalar similarity only for Bowen ratios 1.

  18. Parametric nanomechanical amplification at very high frequency.

    Science.gov (United States)

    Karabalin, R B; Feng, X L; Roukes, M L

    2009-09-01

    Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.

  19. Speaker Linking and Applications using Non-Parametric Hashing Methods

    Science.gov (United States)

    2016-09-08

    nonparametric estimate of a multivariate density function,” The Annals of Math- ematical Statistics , vol. 36, no. 3, pp. 1049–1051, 1965. [9] E. A. Patrick...Speaker Linking and Applications using Non-Parametric Hashing Methods† Douglas Sturim and William M. Campbell MIT Lincoln Laboratory, Lexington, MA...with many approaches [1, 2]. For this paper, we focus on using i-vectors [2], but the methods apply to any embedding. For the task of speaker QBE and

  20. Power of non-parametric linkage analysis in mapping genes contributing to human longevity in long-lived sib-pairs

    DEFF Research Database (Denmark)

    Tan, Qihua; Zhao, J H; Iachine, I

    2004-01-01

    This report investigates the power issue in applying the non-parametric linkage analysis of affected sib-pairs (ASP) [Kruglyak and Lander, 1995: Am J Hum Genet 57:439-454] to localize genes that contribute to human longevity using long-lived sib-pairs. Data were simulated by introducing a recently...... developed statistical model for measuring marker-longevity associations [Yashin et al., 1999: Am J Hum Genet 65:1178-1193], enabling direct power comparison between linkage and association approaches. The non-parametric linkage (NPL) scores estimated in the region harboring the causal allele are evaluated...... in case of a dominant effect. Although the power issue may depend heavily on the true genetic nature in maintaining survival, our study suggests that results from small-scale sib-pair investigations should be referred with caution, given the complexity of human longevity....

  1. Parametric Study of Sealant Nozzle

    Science.gov (United States)

    Yamamoto, Yoshimi

    It has become apparent in recent years the advancement of manufacturing processes in the aerospace industry. Sealant nozzles are a critical device in the use of fuel tank applications for optimal bonds and for ground service support and repair. Sealants has always been a challenging area for optimizing and understanding the flow patterns. A parametric study was conducted to better understand geometric effects of sealant flow and to determine whether the sealant rheology can be numerically modeled. The Star-CCM+ software was used to successfully develop the parametric model, material model, physics continua, and simulate the fluid flow for the sealant nozzle. The simulation results of Semco sealant nozzles showed the geometric effects of fluid flow patterns and the influences from conical area reduction, tip length, inlet diameter, and tip angle parameters. A smaller outlet diameter induced maximum outlet velocity at the exit, and contributed to a high pressure drop. The conical area reduction, tip angle and inlet diameter contributed most to viscosity variation phenomenon. Developing and simulating 2 different flow models (Segregated Flow and Viscous Flow) proved that both can be used to obtain comparable velocity and pressure drop results, however; differences are seen visually in the non-uniformity of the velocity and viscosity fields for the Viscous Flow Model (VFM). A comprehensive simulation setup for sealant nozzles was developed so other analysts can utilize the data.

  2. A general approach to optomechanical parametric instabilities

    International Nuclear Information System (INIS)

    Evans, M.; Barsotti, L.; Fritschel, P.

    2010-01-01

    We present a simple feedback description of parametric instabilities which can be applied to a variety of optical systems. Parametric instabilities are of particular interest to the field of gravitational-wave interferometry where high mechanical quality factors and a large amount of stored optical power have the potential for instability. In our use of Advanced LIGO as an example application, we find that parametric instabilities, if left unaddressed, present a potential threat to the stability of high-power operation.

  3. Connections between classical and parametric network entropies.

    Directory of Open Access Journals (Sweden)

    Matthias Dehmer

    Full Text Available This paper explores relationships between classical and parametric measures of graph (or network complexity. Classical measures are based on vertex decompositions induced by equivalence relations. Parametric measures, on the other hand, are constructed by using information functions to assign probabilities to the vertices. The inequalities established in this paper relating classical and parametric measures lay a foundation for systematic classification of entropy-based measures of graph complexity.

  4. The Kernel Estimation in Biosystems Engineering

    Directory of Open Access Journals (Sweden)

    Esperanza Ayuga Téllez

    2008-04-01

    Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

  5. Acceleration of the direct reconstruction of linear parametric images using nested algorithms

    International Nuclear Information System (INIS)

    Wang Guobao; Qi Jinyi

    2010-01-01

    Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

  6. On the problem of neutron spectroscopy of parametrically non-equilibrium quasiparticles in solids

    International Nuclear Information System (INIS)

    Vo Khong An'.

    1981-01-01

    A suitable for numerical estimations formula for coherent neutron inelastic scattering cross sections on the plasmon-phonon mixed modes of electron-phonon systems in the parametric resonance conditions is obtained from the analytical one presented in the previous work using some relations of the general parametric excitation theory. The cross sections of neutron scattering on the high-frequency plasmon-like and the low-frequency longitudinal optical phonon-like modes in InSb crystals are calculated as functions of the driving laser field intensity, which show an increase in values by about two orders of magnitude as the field intensity approaches the parametric excitation threshold

  7. Influence of Surge Motion on the Probability of Parametric Roll in a Stationary Sea State

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Vidic-Perunovic, Jelena; Pedersen, Preben Terndrup

    2007-01-01

    A typical parametric roll scenario for a ship in head waves implies that the roll motion is coupled with vertical motion of the vessel. The added resistance of the ship is increased when the bow pitches down in a wave crest. As a consequence, the ship speed is slowed down and, hence, the roll...... resonance condition might be changed. In an attempt to study the influence of this speed variation in waves on parametric roll, the procedure for estimation of probability of parametric roll by Jensen and Pedersen (2006) has been extended to account for the surge motion of the vessel....

  8. Housing price prediction: parametric versus semi-parametric spatial hedonic models

    Science.gov (United States)

    Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

    2018-01-01

    House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

  9. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    International Nuclear Information System (INIS)

    Dimas, George; Iakovidis, Dimitris K; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-01-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup. (paper)

  10. An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

    Science.gov (United States)

    Dimas, George; Iakovidis, Dimitris K.; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

    2017-09-01

    Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup.

  11. Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation

    Science.gov (United States)

    Pentaris, Fragkiskos P.; Fouskitakis, George N.

    2014-05-01

    The problem of modal identification in civil structures is of crucial importance, and thus has been receiving increasing attention in recent years. Vibration-based methods are quite promising as they are capable of identifying the structure's global characteristics, they are relatively easy to implement and they tend to be time effective and less expensive than most alternatives [1]. This paper focuses on the off-line structural/modal identification of civil (concrete) structures subjected to low-level earthquake excitations, under which, they remain within their linear operating regime. Earthquakes and their details are recorded and provided by the seismological network of Crete [2], which 'monitors' the broad region of south Hellenic arc, an active seismic region which functions as a natural laboratory for earthquake engineering of this kind. A sufficient number of seismic events are analyzed in order to reveal the modal characteristics of the structures under study, that consist of the two concrete buildings of the School of Applied Sciences, Technological Education Institute of Crete, located in Chania, Crete, Hellas. Both buildings are equipped with high-sensitivity and accuracy seismographs - providing acceleration measurements - established at the basement (structure's foundation) presently considered as the ground's acceleration (excitation) and at all levels (ground floor, 1st floor, 2nd floor and terrace). Further details regarding the instrumentation setup and data acquisition may be found in [3]. The present study invokes stochastic, both non-parametric (frequency-based) and parametric methods for structural/modal identification (natural frequencies and/or damping ratios). Non-parametric methods include Welch-based spectrum and Frequency response Function (FrF) estimation, while parametric methods, include AutoRegressive (AR), AutoRegressive with eXogeneous input (ARX) and Autoregressive Moving-Average with eXogeneous input (ARMAX) models[4, 5

  12. Design of parametric software tools

    DEFF Research Database (Denmark)

    Sabra, Jakob Borrits; Mullins, Michael

    2011-01-01

    The studies investigate the field of evidence-based design used in architectural design practice and propose a method using 2D/3D CAD applications to: 1) enhance integration of evidence-based design knowledge in architectural design phases with a focus on lighting and interior design and 2) assess...... fulfilment of evidence-based design criterion regarding light distribution and location in relation to patient safety in architectural health care design proposals. The study uses 2D/3D CAD modelling software Rhinoceros 3D with plug-in Grasshopper to create parametric tool prototypes to exemplify...... the operations and functions of the design method. To evaluate the prototype potentials, surveys with architectural and healthcare design companies are conducted. Evaluation is done by the administration of questionnaires being part of the development of the tools. The results show that architects, designers...

  13. Parametric instabilities in large plasmas

    International Nuclear Information System (INIS)

    Brambilla, Marco; Liberman, Bernardo.

    1979-01-01

    Parametric decay processes in large plasmas are considered as the linear stage of a three wave interaction (pump, sideband and beat wave) in which the amplitude of the externally excited pump is sufficiently large to neglect pump depletion to first order, yet sufficiently small to allow a linearized treatment of the pump propagation to zeroth order. The coupling coefficients are then obtained from an iterative solution of Vlasov equation, and a compact expression is derived, in which the multiple series over Bessel functions is explicitly summed. Even in the limit of a very long wavelength pump, the dispersion relation obtained in this way does not coincide with the one obtained using the well-known ''dipole'' approximation, unless both the sideband and beat wave are resonant modes of the plasma. An analysis of the origin of this discrepancy allows us to conclude that ''quasimodes'' (evanescent waves driven absolutely unstable by the pump) are more correctly described by the iterative approach

  14. Parametric embedding for class visualization.

    Science.gov (United States)

    Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

    2007-09-01

    We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

  15. Parametric studies on automotive radiators

    International Nuclear Information System (INIS)

    Oliet, C.; Oliva, A.; Castro, J.; Perez-Segarra, C.D.

    2007-01-01

    This paper presents a set of parametric studies performed on automotive radiators by means of a detailed rating and design heat exchanger model developed by the authors. This numerical tool has been previously verified and validated using a wide experimental data bank. A first part of the analysis focuses on the influence of working conditions on both fluids (mass flows, inlet temperatures) and the impact of the selected coolant fluid. Following these studies, the influence of some geometrical parameters is analysed (fin pitch, louver angle) as well as the importance of coolant flow lay-out on the radiator global performance. This work provides an overall behaviour report of automobile radiators working at usual range of operating conditions, while significant knowledge-based design conclusions have also been reported. The results show the utility of this numerical model as a rating and design tool for heat exchangers manufacturers, being a reasonable compromise between classic ε - NTU methods and CFD

  16. Parametric instabilities in inhomogeneous plasma

    International Nuclear Information System (INIS)

    Nicholson, D.R.

    1975-01-01

    The nonlinear coupling of three waves in a plasma is considered. One of the waves is assumed large and constant; its amplitude is the parameter of the parametric instability. The spatial-temporal evolution of the other two waves is treated theoretically, in one dimension, by analytic methods and by direct numerical integration of the basic equations. Various monotonic forms of inhomogeneity are considered; agreement with previous work is found and new results are established. Nonmonotonic inhomogeneities are considered, in the form of turbulence and, as a model problem, in the form of a simple sinusoidal modulation. Relatively small amounts of nonmonotonic inhomogeneity, in the presence of a linear density gradient, are found to destabilize the well-known convective saturation, absolute growth occurring instead. (U.S.)

  17. Optimal Design of Experiments for Parametric Identification of Civil Engineering Structures

    OpenAIRE

    Kirkegaard, Poul Henning

    1991-01-01

    Optimal Systems of experiments for parametric identification of civil engineering structures is investigated. Design of experiments for parametric identification of dynamic systems is usually done by minimizing a scalar measure, e.g the determinant, the trace ect., of an estimated parameter covariance matrix, based on prior knowledge. The experimental conditions available for adjustment, considering in this thesis, are input signal, sampling rate, the location of sensors and number of sensors.

  18. Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.

    Science.gov (United States)

    Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao

    2013-01-01

    Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.

  19. Mrg: A Magnitude Scale for 1 s Rayleigh Waves at Local Distances with Focus on Yield Estimation

    Science.gov (United States)

    2016-08-23

    definition for filtering Rg near 1 s period at distances between 2-100 km. We used the new formula to estimate MRg for 39 small (37 ≤ Y ≤ 12,270 kg TNT...the Butterworth filter order (Russell, 2006). Filter Definition . To estimate the time-domain amplitude of Rg, we filter the time series with a 2nd... phenomenology experiments, including the Arizona Source Phenomenology Experiment (AZ-SPE), Bighorn Active Seismic Experiment (BASE), the HUMMING ALBATROS

  20. Integrable multi parametric SU(N) chain

    International Nuclear Information System (INIS)

    Foerster, Angela; Roditi, Itzhak; Rodrigues, Ligia M.C.S.

    1996-03-01

    We analyse integrable models associated to a multi parametric SU(N) R-matrix. We show that the Hamiltonians describe SU(N) chains with twisted boundary conditions and that the underlying algebraic structure is the multi parametric deformation of SU(N) enlarged by the introduction of a central element. (author). 15 refs

  1. Observation of Parametric Instability in Advanced LIGO.

    Science.gov (United States)

    Evans, Matthew; Gras, Slawek; Fritschel, Peter; Miller, John; Barsotti, Lisa; Martynov, Denis; Brooks, Aidan; Coyne, Dennis; Abbott, Rich; Adhikari, Rana X; Arai, Koji; Bork, Rolf; Kells, Bill; Rollins, Jameson; Smith-Lefebvre, Nicolas; Vajente, Gabriele; Yamamoto, Hiroaki; Adams, Carl; Aston, Stuart; Betzweiser, Joseph; Frolov, Valera; Mullavey, Adam; Pele, Arnaud; Romie, Janeen; Thomas, Michael; Thorne, Keith; Dwyer, Sheila; Izumi, Kiwamu; Kawabe, Keita; Sigg, Daniel; Derosa, Ryan; Effler, Anamaria; Kokeyama, Keiko; Ballmer, Stefan; Massinger, Thomas J; Staley, Alexa; Heinze, Matthew; Mueller, Chris; Grote, Hartmut; Ward, Robert; King, Eleanor; Blair, David; Ju, Li; Zhao, Chunnong

    2015-04-24

    Parametric instabilities have long been studied as a potentially limiting effect in high-power interferometric gravitational wave detectors. Until now, however, these instabilities have never been observed in a kilometer-scale interferometer. In this Letter, we describe the first observation of parametric instability in a gravitational wave detector, and the means by which it has been removed as a barrier to progress.

  2. Parametric Methods for Order Tracking Analysis

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm

    2017-01-01

    Order tracking analysis is often used to find the critical speeds at which structural resonances are excited by a rotating machine. Typically, order tracking analysis is performed via non-parametric methods. In this report, however, we demonstrate some of the advantages of using a parametric method...

  3. Parametric resonance in neutrino oscillations in matter

    Indian Academy of Sciences (India)

    Neutrino oscillations in matter can exhibit a specific resonance enhancement - parametric resonance, which is different from the MSW resonance. Oscillations of atmospheric and solar neutrinos inside the earth can undergo parametric enhancement when neutrino trajectories cross the core of the earth. In this paper we ...

  4. On the parametric approximation in quantum optics

    Energy Technology Data Exchange (ETDEWEB)

    D' Ariano, G.M.; Paris, M.G.A.; Sacchi, M.F. [Istituto Nazionale di Fisica Nucleare, Pavia (Italy); Pavia Univ. (Italy). Dipt. di Fisica ' Alessandro Volta'

    1999-03-01

    The authors perform the exact numerical diagonalization of Hamiltonians that describe both degenerate and nondegenerate parametric amplifiers, by exploiting the conservation laws pertaining each device. It is clarify the conditions under which the parametric approximation holds, showing that the most relevant requirements is the coherence of the pump after the interaction, rather than its un depletion.

  5. On the parametric approximation in quantum optics

    International Nuclear Information System (INIS)

    D'Ariano, G.M.; Paris, M.G.A.; Sacchi, M.F.; Pavia Univ.

    1999-01-01

    The authors perform the exact numerical diagonalization of Hamiltonians that describe both degenerate and nondegenerate parametric amplifiers, by exploiting the conservation laws pertaining each device. It is clarify the conditions under which the parametric approximation holds, showing that the most relevant requirements is the coherence of the pump after the interaction, rather than its un depletion

  6. Parametric form of QCD travelling waves

    OpenAIRE

    Peschanski, R.

    2005-01-01

    We derive parametric travelling-wave solutions of non-linear QCD equations. They describe the evolution towards saturation in the geometric scaling region. The method, based on an expansion in the inverse of the wave velocity, leads to a solvable hierarchy of differential equations. A universal parametric form of travelling waves emerges from the first two orders of the expansion.

  7. Parametric spatiotemporal oscillation in reaction-diffusion systems.

    Science.gov (United States)

    Ghosh, Shyamolina; Ray, Deb Shankar

    2016-03-01

    We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

  8. Parametric modeling for damped sinusoids from multiple channels

    DEFF Research Database (Denmark)

    Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

    2013-01-01

    frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

  9. Developing a Parametric Urban Design Tool

    DEFF Research Database (Denmark)

    Steinø, Nicolai; Obeling, Esben

    2014-01-01

    Parametric urban design is a potentially powerful tool for collaborative urban design processes. Rather than making one- off designs which need to be redesigned from the ground up in case of changes, parametric design tools make it possible keep the design open while at the same time allowing...... for a level of detailing which is high enough to facilitate an understan- ding of the generic qualities of proposed designs. Starting from a brief overview of parametric design, this paper presents initial findings from the development of a parametric urban design tool with regard to developing a structural...... logic which is flexible and expandable. It then moves on to outline and discuss further development work. Finally, it offers a brief reflection on the potentials and shortcomings of the software – CityEngine – which is used for developing the parametric urban design tool....

  10. Parametric, nonparametric and parametric modelling of a chaotic circuit time series

    Science.gov (United States)

    Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

    2000-09-01

    The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

  11. Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods : A Comparison with Clinical Assessment

    NARCIS (Netherlands)

    Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H; Maurits, Natasha M

    2016-01-01

    In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a

  12. Parametric level correlations in random-matrix models

    International Nuclear Information System (INIS)

    Weidenmueller, Hans A

    2005-01-01

    We show that parametric level correlations in random-matrix theories are closely related to a breaking of the symmetry between the advanced and the retarded Green functions. The form of the parametric level correlation function is the same as for the disordered case considered earlier by Simons and Altshuler and is given by the graded trace of the commutator of the saddle-point solution with the particular matrix that describes the symmetry breaking in the actual case of interest. The strength factor differs from the case of disorder. It is determined solely by the Goldstone mode. It is essentially given by the number of levels that are strongly mixed as the external parameter changes. The factor can easily be estimated in applications

  13. Parametric wave penetration through an overdense plasma layer

    International Nuclear Information System (INIS)

    Gradov, O.M.; Suender, D.

    1981-01-01

    The nonlinear penetration of an electromagnetic wave through an overdense plasma layer due to the excitation of parametric instabilities is studied. The quasistatic h.f. surface wave and the ion-acoustic wave, both parametrically growing, generate a nonlinear current which also exist beyound the linear skin length of the incident electromagnetic wave. This current leads to an exponential amplification of the electromagnetic wave amplitude in the layer. The growth rate of this process depends on the overthreshold value of the external wave intensity and the thickness of the layer. The saturation level of the transmitted wave amplitude is estimated for the case, when the instabilities are stabilized by generation of ion-acoustic harmonics. (author)

  14. Multi-parametric variational data assimilation for hydrological forecasting

    Science.gov (United States)

    Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

    2017-12-01

    Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

  15. Notes on the Implementation of Non-Parametric Statistics within the Westinghouse Realistic Large Break LOCA Evaluation Model (ASTRUM)

    International Nuclear Information System (INIS)

    Frepoli, Cesare; Oriani, Luca

    2006-01-01

    In recent years, non-parametric or order statistics methods have been widely used to assess the impact of the uncertainties within Best-Estimate LOCA evaluation models. The bounding of the uncertainties is achieved with a direct Monte Carlo sampling of the uncertainty attributes, with the minimum trial number selected to 'stabilize' the estimation of the critical output values (peak cladding temperature (PCT), local maximum oxidation (LMO), and core-wide oxidation (CWO A non-parametric order statistics uncertainty analysis was recently implemented within the Westinghouse Realistic Large Break LOCA evaluation model, also referred to as 'Automated Statistical Treatment of Uncertainty Method' (ASTRUM). The implementation or interpretation of order statistics in safety analysis is not fully consistent within the industry. This has led to an extensive public debate among regulators and researchers which can be found in the open literature. The USNRC-approved Westinghouse method follows a rigorous implementation of the order statistics theory, which leads to the execution of 124 simulations within a Large Break LOCA analysis. This is a solid approach which guarantees that a bounding value (at 95% probability) of the 95 th percentile for each of the three 10 CFR 50.46 ECCS design acceptance criteria (PCT, LMO and CWO) is obtained. The objective of this paper is to provide additional insights on the ASTRUM statistical approach, with a more in-depth analysis of pros and cons of the order statistics and of the Westinghouse approach in the implementation of this statistical methodology. (authors)

  16. A variation of the housing unit method for estimating the age and gender distribution of small, rural areas: A case study of the local expert procedure

    International Nuclear Information System (INIS)

    Carlson, J.F.; Roe, L.K.; Williams, C.A.; Swanson, D.A.

    1993-01-01

    This paper describes the methodologies used in the development of a demographic data base established in support of the Yucca Mountain Site Characterization Project Radiological Monitoring Plan (RadMP). It also examines the suitability of a survey-based procedure for estimating population in small, rural areas. The procedure is a variation of the Housing Unit Method. It employs the use of local experts enlisted to provide information about the demographic characteristics of households randomly selected from residential units sample frames developed from utility records. The procedure is nonintrusive and less costly than traditional survey data collection efforts. Because the procedure is based on random sampling, confidence intervals can be constructed around the population estimated by the technique. The results of a case study are provided in which the total population, and age and gender of the population, is estimated for three unincorporated communities in rural, southern Nevada

  17. Functional brain mapping using H215O positron emission tomography (I): statistical parametric mapping method

    International Nuclear Information System (INIS)

    Lee, Dong Soo; Lee, Jae Sung; Kim, Kyeong Min; Chung, June Key; Lee, Myung Chul

    1998-01-01

    We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq H 2 15 O at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel. To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory

  18. Ionization Cooling using Parametric Resonances

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, Rolland P.

    2008-06-07

    Ionization Cooling using Parametric Resonances was an SBIR project begun in July 2004 and ended in January 2008 with Muons, Inc., (Dr. Rolland Johnson, PI), and Thomas Jefferson National Accelerator Facility (JLab) (Dr. Yaroslav Derbenev, Subcontract PI). The project was to develop the theory and simulations of Parametric-resonance Ionization Cooling (PIC) so that it could be used to provide the extra transverse cooling needed for muon colliders in order to relax the requirements on the proton driver, reduce the site boundary radiation, and provide a better environment for experiments. During the course of the project, the theoretical understanding of PIC was developed and a final exposition is ready for publication. Workshops were sponsored by Muons, Inc. in May and September of 2007 that were devoted to the PIC technique. One outcome of the workshops was the interesting and somewhat unexpected realization that the beam emittances using the PIC technique can get small enough that space charge forces can be important. A parallel effort to develop our G4beamline simulation program to include space charge effects was initiated to address this problem. A method of compensating for chromatic aberrations by employing synchrotron motion was developed and simulated. A method of compensating for spherical aberrations using beamline symmetry was also developed and simulated. Different optics designs have been developed using the OptiM program in preparation for applying our G4beamline simulation program, which contains all the power of the Geant4 toolkit. However, no PIC channel design that has been developed has had the desired cooling performance when subjected to the complete G4beamline simulation program. This is believed to be the consequence of the difficulties of correcting the aberrations associated with the naturally large beam angles and beam sizes of the PIC method that are exacerbated by the fringe fields of the rather complicated channel designs that have been

  19. Ionization Cooling using Parametric Resonances

    International Nuclear Information System (INIS)

    Johnson, Rolland P.

    2008-01-01

    Ionization Cooling using Parametric Resonances was an SBIR project begun in July 2004 and ended in January 2008 with Muons, Inc., (Dr. Rolland Johnson, PI), and Thomas Jefferson National Accelerator Facility (JLab) (Dr. Yaroslav Derbenev, Subcontract PI). The project was to develop the theory and simulations of Parametric-resonance Ionization Cooling (PIC) so that it could be used to provide the extra transverse cooling needed for muon colliders in order to relax the requirements on the proton driver, reduce the site boundary radiation, and provide a better environment for experiments. During the course of the project, the theoretical understanding of PIC was developed and a final exposition is ready for publication. Workshops were sponsored by Muons, Inc. in May and September of 2007 that were devoted to the PIC technique. One outcome of the workshops was the interesting and somewhat unexpected realization that the beam emittances using the PIC technique can get small enough that space charge forces can be important. A parallel effort to develop our G4beamline simulation program to include space charge effects was initiated to address this problem. A method of compensating for chromatic aberrations by employing synchrotron motion was developed and simulated. A method of compensating for spherical aberrations using beamline symmetry was also developed and simulated. Different optics designs have been developed using the OptiM program in preparation for applying our G4beamline simulation program, which contains all the power of the Geant4 toolkit. However, no PIC channel design that has been developed has had the desired cooling performance when subjected to the complete G4beamline simulation program. This is believed to be the consequence of the difficulties of correcting the aberrations associated with the naturally large beam angles and beam sizes of the PIC method that are exacerbated by the fringe fields of the rather complicated channel designs that have been

  20. Education Demographic and Geographic Estimates Program (EDGE): Locale Boundaries User's Manual. NCES 2016-012

    Science.gov (United States)

    Geverdt, Douglas E.

    2015-01-01

    The National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) program develops geographic data to help policymakers, program administrators, and the public understand relationships between educational institutions and the communities they serve. One of the commonly used geographic data items is the NCES…

  1. Parametric Decay during HHFW on NSTX

    International Nuclear Information System (INIS)

    Wilson, J.R.; Bernabei, S.; Biewer, T.; Diem, S.; Hosea, J.; LeBlanc, B.; Phillips, C.K.; Ryan, P.; Swain, D.W.

    2005-01-01

    High Harmonic Fast Wave (HHFW) heating experiments on NSTX have been observed to be accompanied by significant edge ion heating (T i >> T e ). This heating is found to be anisotropic with T perp > T par . Simultaneously, coherent oscillations have been detected with an edge Langmuir probe. The oscillations are consistent with parametric decay of the incident fast wave (ω > 13ω ci ) into ion Bernstein waves and an unobserved ion-cyclotron quasi-mode. The observation of anisotropic heating is consistent with Bernstein wave damping, and the Bernstein waves should completely damp in the plasma periphery as they propagate toward a cyclotron harmonic resonance. The number of daughter waves is found to increase with rf power, and to increase as the incident wave's toroidal wavelength increases. The frequencies of the daughter wave are separated by the edge ion cyclotron frequency. Theoretical calculations of the threshold for this decay in uniform plasma indicate an extremely small value of incident power should be required to drive the instability. While such decays are commonly observed at lower harmonics in conventional ICRF heating scenarios, they usually do not involve the loss of significant wave power from the pump wave. On NSTX an estimate of the power loss can be found by calculating the minimum power required to support the edge ion heating (presumed to come from the decay Bernstein wave). This calculation indicates at least 20-30% of the incident rf power ends up as decay waves

  2. Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction

    NARCIS (Netherlands)

    Picchio, M.; Mussida, C.

    2010-01-01

    Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which incorporates

  3. Estimation of the local response to a forcing in a high dimensional system using the fluctuation-dissipation theorem

    Directory of Open Access Journals (Sweden)

    F. C. Cooper

    2013-04-01

    Full Text Available The fluctuation-dissipation theorem (FDT has been proposed as a method of calculating the response of the earth's atmosphere to a forcing. For this problem the high dimensionality of the relevant data sets makes truncation necessary. Here we propose a method of truncation based upon the assumption that the response to a localised forcing is spatially localised, as an alternative to the standard method of choosing a number of the leading empirical orthogonal functions. For systems where this assumption holds, the response to any sufficiently small non-localised forcing may be estimated using a set of truncations that are chosen algorithmically. We test our algorithm using 36 and 72 variable versions of a stochastic Lorenz 95 system of ordinary differential equations. We find that, for long integrations, the bias in the response estimated by the FDT is reduced from ~75% of the true response to ~30%.

  4. Controlling flexible rotor vibrations using parametric excitation

    Energy Technology Data Exchange (ETDEWEB)

    Atepor, L, E-mail: katepor@yahoo.co [Department of Mechanical Engineering, University of Glasgow, G12 8QQ (United Kingdom)

    2009-08-01

    This paper presents both theoretical and experimental studies of an active vibration controller for vibration in a flexible rotor system. The paper shows that the vibration amplitude can be modified by introducing an axial parametric excitation. The perturbation method of multiple scales is used to solve the equations of motion. The steady-state responses, with and without the parametric excitation terms, is investigated. An experimental test machine uses a piezoelectric exciter mounted on the end of the shaft. The results show a reduction in the rotor response amplitude under principal parametric resonance, and some good correlation between theory and experiment.

  5. Linear Parametric Model Checking of Timed Automata

    DEFF Research Database (Denmark)

    Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle

    2001-01-01

    We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...... of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach...

  6. Chaotic parametric soliton-like pulses in ferromagnetic-film active ring resonators

    International Nuclear Information System (INIS)

    Grishin, S. V.; Golova, T. M.; Morozova, M. A.; Romanenko, D. V.; Seleznev, E. P.; Sysoev, I. V.; Sharaevskii, Yu. P.

    2015-01-01

    The generation of quasi-periodic sequences of parametric soliton-like pulses in an active ring resonator with a ferromagnetic film via the three-wave parametric instability of a magnetostatic surface wave is studied theoretically and experimentally. These dissipative structures form in time due to the competition between the cubic nonlinearity caused by parametric coupling between spin waves and the time dispersion caused by the resonant cavity that is present in a self-oscillatory system. The development of dynamic chaos due to the parametric instability of a magnetostatic surface wave results in irregular behavior of a phase. However, this behavior does not break a quasi-periodic pulse sequence when the gain changes over a wide range. The generated soliton-like pulses have a chaotic nature, which is supported by the maximum Lyapunov exponent estimated from experimental time series

  7. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

    Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

    2011-01-01

    The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

  8. A two-stage approach to estimate spatial and spatio-temporal disease risks in the presence of local discontinuities and clusters.

    Science.gov (United States)

    Adin, A; Lee, D; Goicoa, T; Ugarte, María Dolores

    2018-01-01

    Disease risk maps for areal unit data are often estimated from Poisson mixed models with local spatial smoothing, for example by incorporating random effects with a conditional autoregressive prior distribution. However, one of the limitations is that local discontinuities in the spatial pattern are not usually modelled, leading to over-smoothing of the risk maps and a masking of clusters of hot/coldspot areas. In this paper, we propose a novel two-stage approach to estimate and map disease risk in the presence of such local discontinuities and clusters. We propose approaches in both spatial and spatio-temporal domains, where for the latter the clusters can either be fixed or allowed to vary over time. In the first stage, we apply an agglomerative hierarchical clustering algorithm to training data to provide sets of potential clusters, and in the second stage, a two-level spatial or spatio-temporal model is applied to each potential cluster configuration. The superiority of the proposed approach with regard to a previous proposal is shown by simulation, and the methodology is applied to two important public health problems in Spain, namely stomach cancer mortality across Spain and brain cancer incidence in the Navarre and Basque Country regions of Spain.

  9. Estimation of local spectrum content of cervical cancer-related features via two dimensional method of geometric restriction in frequency domain

    International Nuclear Information System (INIS)

    Van Raad, V.

    2004-01-01

    Digital colposcopy is an emerging new technology, which can be used as adjunct to the conventional Pap test for staging of cervical cancer and it can improve the diagnostic accuracy of the test. Computer aided diagnosis (CAD) in digital colposcopy has as a goal to segment and outline abnormal areas on the cervix, one of which is an important anatomical landmark on the ectocervix - the transformation zone (TZ). In this paper we proposed a new method for estimation of the local spectrum features of cervical cancer in vivo. We used a 2D method to estimate the energy of the local frequency bands, using a geometric restriction (GR). In the current work we reported up to 12 dB difference between the local power spectral density content of the region of interest (ROI) and (ROI) C for the mid-frequency band. We devised a method to present pseudo-color visual maps of the cervical images, useful for CAD and successful ROI segmentation. (author)

  10. Calibração regional e local da equação de Hargreaves para estimativa da evapotranspiração de referência Regional and local calibration of Hargreaves equation for estimating reference evapotranspiration

    Directory of Open Access Journals (Sweden)

    Diego Simões Fernandes

    2012-06-01

    Full Text Available A equação de Penman-Monteith FAO-56 (EToPM tem sido recomendada pela FAO, Organização para a Alimentação e Agricultura das Nações Unidas (ONU, como padrão para estimar a evapotranspiração de referência (ETo. Essa equação requer muitas variáveis que não estão disponíveis na maioria das estações meteorológicas no Brasil central. Por outro lado, a equação de Hargreaves é considerada simples e demanda somente dados de temperatura máxima e mínima para estimar a ETo. Entretanto, essa equação requer um ajuste local. Esse estudo analisa a possibilidade de utilizar a equação de Hargreaves ajustada para estimar a ETo no estado de Goiás. Para isso, os parâmetros empíricos, HC (coeficiente empírico de Hargreaves e HE (expoente empírico de Hargreaves, da equação de Hargreaves foram ajustados considerando dois processos, ajuste local (HGR - Hargreaves ajuste local e ajuste regional (HGL - Hargreaves ajuste regional. Para o HGL, os parâmetros empíricos foram ajustados para cada estação meteorológica. Já, para o HGR, os parâmetros empíricos foram ajustados considerando conjuntamente os dados de todas as estações meteorológicas. A equação de Hargreaves ajustada para ambos os processos, local e regional, apresentou valores de ERQM de 17,95 e 21,93%, respectivamente, considerando o conjunto total de dados climáticos. A equação de Hargreaves ajustada localmente ou regionalmente é uma opção para estimar os valores diários de ETo no Estado de Goiás em locais em que a disponibilidade de dados climáticos é limitada.The FAO-56 Penman-Monteith equation (EToPM has been recommended by the Food and Agriculture Organization (FAO of the United Nations as the standard equation for estimating reference evapotranspiration (ETo. The FAO-56 PM equation requires numerous weather data that are not available in most of the stations of Brazil central. On the other hand, the Hargreaves equation is a more simple equation for

  11. Fast and Statistically Efficient Fundamental Frequency Estimation

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm; Jensen, Jesper Rindom

    2016-01-01

    Fundamental frequency estimation is a very important task in many applications involving periodic signals. For computational reasons, fast autocorrelation-based estimation methods are often used despite parametric estimation methods having superior estimation accuracy. However, these parametric...... a recursive solver. Via benchmarks, we demonstrate that the computation time is reduced by approximately two orders of magnitude. The proposed fast algorithm is available for download online....

  12. Neuro-fuzzy computing for vibration-based damage localization and severity estimation in an experimental wind turbine blade with superimposed operational effects

    Science.gov (United States)

    Hoell, Simon; Omenzetter, Piotr

    2016-04-01

    Fueled by increasing demand for carbon neutral energy, erections of ever larger wind turbines (WTs), with WT blades (WTBs) with higher flexibilities and lower buckling capacities lead to increasing operation and maintenance costs. This can be counteracted with efficient structural health monitoring (SHM), which allows scheduling maintenance actions according to the structural state and preventing dramatic failures. The present study proposes a novel multi-step approach for vibration-based structural damage localization and severity estimation for application in operating WTs. First, partial autocorrelation coefficients (PACCs) are estimated from vibrational responses. Second, principal component analysis is applied to PACCs from the healthy structure in order to calculate scores. Then, the scores are ranked with respect to their ability to differentiate different damage scenarios. This ranking information is used for constructing hierarchical adaptive neuro-fuzzy inference systems (HANFISs), where cross-validation is used to identify optimal numbers of hierarchy levels. Different HANFISs are created for the purposes of structural damage localization and severity estimation. For demonstrating the applicability of the approach, experimental data are superimposed with signals from numerical simulations to account for characteristics of operational noise. For the physical experiments, a small scale WTB is excited with a domestic fan and damage scenarios are introduced non-destructively by attaching small masses. Numerical simulations are also performed for a representative fully functional small WT operating in turbulent wind. The obtained results are promising for future applications of vibration-based SHM to facilitate improved safety and reliability of WTs at lower costs.

  13. Improved estimation of the noncentrality parameter distribution from a large number of t-statistics, with applications to false discovery rate estimation in microarray data analysis.

    Science.gov (United States)

    Qu, Long; Nettleton, Dan; Dekkers, Jack C M

    2012-12-01

    Given a large number of t-statistics, we consider the problem of approximating the distribution of noncentrality parameters (NCPs) by a continuous density. This problem is closely related to the control of false discovery rates (FDR) in massive hypothesis testing applications, e.g., microarray gene expression analysis. Our methodology is similar to, but improves upon, the existing approach by Ruppert, Nettleton, and Hwang (2007, Biometrics, 63, 483-495). We provide parametric, nonparametric, and semiparametric estimators for the distribution of NCPs, as well as estimates of the FDR and local FDR. In the parametric situation, we assume that the NCPs follow a distribution that leads to an analytically available marginal distribution for the test statistics. In the nonparametric situation, we use convex combinations of basis density functions to estimate the density of the NCPs. A sequential quadratic programming procedure is developed to maximize the penalized likelihood. The smoothing parameter is selected with the approximate network information criterion. A semiparametric estimator is also developed to combine both parametric and nonparametric fits. Simulations show that, under a variety of situations, our density estimates are closer to the underlying truth and our FDR estimates are improved compared with alternative methods. Data-based simulations and the analyses of two microarray datasets are used to evaluate the performance in realistic situations. © 2012, The International Biometric Society.

  14. Parametric Estimation by Generalized Moment Methods for Extremes

    Czech Academy of Sciences Publication Activity Database

    Fabián, Zdeněk

    2008-01-01

    Roč. 11, č. 4 (2008), s. 26-35 ISSN 1450-7196 R&D Projects: GA MŠk ME 949 Institutional research plan: CEZ:AV0Z10300504 Keywords : heavy tails * transformation-based score Subject RIV: BB - Applied Statistics, Operational Research

  15. Parametric Estimation of Load for Air Force Data Centers

    Science.gov (United States)

    2015-03-27

    inferential statistics . The purpose of descriptive statistics is to describe and summarize the characteristics of a sample. To accomplish that...28 Descriptive Statistical Analysis... Inferential Statistical Analysis ....................................................................................33 Contrasting with Sixty Percent

  16. Linear minimax estimation for random vectors with parametric uncertainty

    KAUST Repository

    Bitar, E; Baeyens, E; Packard, A; Poolla, K

    2010-01-01

    consider two uncertainty models, PA and PB. Model PA represents X and Y as jointly Gaussian whose covariance matrix Λ belongs to the convex hull of a set of m known covariance matrices. Model PB characterizes X and Y as jointly distributed according to a

  17. Estimation of Parametric Roll in a Stochastic Seaway

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Pedersen, Preben Terndrup; Vidic-Perunovic, Jelena

    2008-01-01

    -degree of freedom (roll and heave) time domain model [10]. In the present paper the effect of the increased added resistance when the bow heaves and pitches down in a wave crest is introduced. Due to the resulting forward speed variation the roll resonance condition will be changed. The influence of ship speed...

  18. Robust Parametric Fault Estimation in a Hopper System

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal

    2012-01-01

    The ability of diagnosis of the possible faults is a necessity for satellite launch vehicles during their mission. In this paper, a structural analysis method is employed to divide the complex propulsion system into simpler subsystems for fault diagnosis filter design. A robust fault diagnosis me...

  19. Impacts of Advanced Manufacturing Technology on Parametric Estimating

    Science.gov (United States)

    1989-12-01

    been build ( Blois , p. 65). As firms move up the levels of automation, there is a large capital investment to acquire robots, computer numerically...Affordable Acquisition Approach Study, Executive Summary, Air Force Systems Command, Andrews AFB, Maryland, February 9, 1983. Blois , K.J., "Manufacturing

  20. Modeling MEA with the CPA equation of state: A parameter estimation study adding local search to PSO algorithm

    DEFF Research Database (Denmark)

    Santos, Letícia Cotia dos; Tavares, Frederico Wanderley; Ahón, Victor Rolando Ruiz

    2015-01-01

    parameters for MEA. This work proposes adding LLE information systematically in the CPA parameter estimation procedure. At first, the parameter search space is defined by the results from the PSO sensitivity analysis for VLE considering the experimental error for vapor pressures and liquid densities...... (objective function cut off). Then, two possible methodologies are discussed: the first one uses all the possible parameter sets and check them against the LLE and VLE experimental data. The second method explicitly incorporates LLE information into the objective function and uses both PSO and PSO...

  1. Parametric optimization of inverse trapezoid oleophobic surfaces

    DEFF Research Database (Denmark)

    Cavalli, Andrea; Bøggild, Peter; Okkels, Fridolin

    2012-01-01

    In this paper, we introduce a comprehensive and versatile approach to the parametric shape optimization of oleophobic surfaces. We evaluate the performance of inverse trapezoid microstructures in terms of three objective parameters: apparent contact angle, maximum sustainable hydrostatic pressure...

  2. Parametric decay below the upper hybrid frequency

    Energy Technology Data Exchange (ETDEWEB)

    Albers, E; Krause, K; Schlueter, H [Bochum Univ. (Germany, F.R.). Inst. fuer Experimentalphysik 2

    1977-03-21

    Parametric decay of the upper hybrid mode is observed between the electron cyclotron frequency and its first two harmonics. The decay products are identified as electron Bernstein and ion acoustic mode. The diagnostic results confirm the relevant dispersion relations.

  3. Robust and Efficient Parametric Face Alignment

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Zafeiriou, Stefanos; Pantic, Maja

    2011-01-01

    We propose a correlation-based approach to parametric object alignment particularly suitable for face analysis applications which require efficiency and robustness against occlusions and illumination changes. Our algorithm registers two images by iteratively maximizing their correlation coefficient

  4. Ranking Forestry Investments With Parametric Linear Programming

    Science.gov (United States)

    Paul A. Murphy

    1976-01-01

    Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

  5. Parametric resonance in neutrino oscillations in matter

    Indian Academy of Sciences (India)

    specific phase relationships has an interesting property that it can accumulate if the matter .... In Д 3 we discuss the physical interpretation of the parametric reso- nance in neutrino ..... long-baseline accelerator and reactor experiments [12,29].

  6. Applying coda envelope measurements to local and regional waveforms for stable estimates of magnitude, source spectra and energy

    International Nuclear Information System (INIS)

    Hofstetter, R.; Mayeda, K.; Rodgers, A.; Walter, W.

    1999-01-01

    Magnitude estimation forms an integral part in any seismic monitoring endeavor. For monitoring compliance of the Comprehensive Nuclear-Test-Ban Treaty, regional seismic discriminants are often functions of magnitude such as m(sub b):M(sub 0) high-to-low spectral ratios, and nuclear yield estimation. For small-to-moderate magnitude events that cannot be studied by a large regional or global network of stations, there is a need for stable magnitudes that can be obtained from as few as one station. To date, magnitudes based on coda envelopes are by far the most stable because of the coda's averaging properties. Unlike conventional magnitudes which utilize the direct phases such as P (P(sub n), P(sub g)) or S (S(sub n), L(sub g)), or M(sub g), a coda envelope magnitude is not as sensitive to the undesirable effects of source radiation pattern, 3-D path heterogeneity, and constructive/destructive interference near the recording site. The stability of the coda comes from a time-domain measurement made over a large portion of the seismogram thereby averaging over the scattered wavefield. This approach has been applied to earthquakes in the western United States where it was found that a single-station coda magnitude was approximately equivalent to an average over a 64 station network which used only the direct waves such as L(sub g) (Mayeda and Walter, JGR, 1996). In this paper we describe in detail our calibration procedure starting with a broadband recording, correlation with independent moment estimates, formation of narrowband envelopes, coda envelope fitting with synthetics, and finally the resultant moment-rate spectra. Our procedure accounts for all propagation, site, and S-to-coda transfer function effects. The resultant coda-derived moment-rate spectra are then used to estimate seismic moment (M(sub o)), narrowband magnitudes such as m(sub b) or M(sub L), and total seismic energy. For the eastern Mediterranean region a preliminary study was completed for

  7. Efficiency Analysis of German Electricity Distribution Utilities : Non-Parametric and Parametric Tests

    OpenAIRE

    von Hirschhausen, Christian R.; Cullmann, Astrid

    2005-01-01

    Abstract This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. We use labour, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) ...

  8. The torus parametrization of quasiperiodic LI-classes

    CERN Document Server

    Baake, M; Pleasants, P A B

    2002-01-01

    The torus parametrization of quasiperiodic local isomorphism classes is introduced and used to determine the number of elements in such a class with special symmetries or inflation properties. The method is explained in an illustrative fashion for some widely used tiling classes with golden mean rescaling, namely for the Fibonacci chain (1D), the triangle and Penrose patterns (2D) and for Kramer's and Danzer's icosahedral tilings (3D). We obtain a rather complete picture of the orbit structure within these classes, but discuss also various general results.

  9. How Much Do We Spend? Creating Historical Estimates of Public Health Expenditures in the United States at the Federal, State, and Local Levels.

    Science.gov (United States)

    Leider, Jonathon P; Resnick, Beth; Bishai, David; Scutchfield, F Douglas

    2018-04-01

    The United States has a complex governmental public health system. Agencies at the federal, state, and local levels all contribute to the protection and promotion of the population's health. Whether the modern public health system is well situated to deliver essential public health services, however, is an open question. In some part, its readiness relates to how agencies are funded and to what ends. A mix of Federalism, home rule, and happenstance has contributed to a siloed funding system in the United States, whereby health agencies are given particular dollars for particular tasks. Little discretionary funding remains. Furthermore, tracking how much is spent, by whom, and on what is notoriously challenging. This review both outlines the challenges associated with estimating public health spending and explains the known sources of funding that are used to estimate and demonstrate the value of public health spending.

  10. Model to estimate the local radiation doses to man from the atmospheric release of radionuclides (LWBR development program)

    International Nuclear Information System (INIS)

    Rider, J.L.; Beal, S.K.

    1977-04-01

    A model was developed to estimate the radiation dose commitments received by people in the vicinity of a facility that releases radionuclides into the atmosphere. This model considers dose commitments resulting from immersion in the plume, ingestion of contaminated food, inhalation of gaseous and suspended radioactivity, and exposure to ground deposits. The dose commitments from each of these pathways is explicitly considered for each radionuclide released into the atmosphere and for each daughter of each released nuclide. Using the release rate of only the parent radionuclide, the air and ground concentrations of each daughter are calculated for each position of interest. This is considered to be a significant improvement over other models in which the concentrations of daughter radionuclides must be approximated by separate releases

  11. Measuring economy-wide energy efficiency performance: A parametric frontier approach

    International Nuclear Information System (INIS)

    Zhou, P.; Ang, B.W.; Zhou, D.Q.

    2012-01-01

    This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts.

  12. [Detection of quadratic phase coupling between EEG signal components by nonparamatric and parametric methods of bispectral analysis].

    Science.gov (United States)

    Schmidt, K; Witte, H

    1999-11-01

    Recently the assumption of the independence of individual frequency components in a signal has been rejected, for example, for the EEG during defined physiological states such as sleep or sedation [9, 10]. Thus, the use of higher-order spectral analysis capable of detecting interrelations between individual signal components has proved useful. The aim of the present study was to investigate the quality of various non-parametric and parametric estimation algorithms using simulated as well as true physiological data. We employed standard algorithms available for the MATLAB. The results clearly show that parametric bispectral estimation is superior to non-parametric estimation in terms of the quality of peak localisation and the discrimination from other peaks.

  13. Estimating live fuel status by drought indices: an approach for assessing local impact of climate change on fire danger

    Science.gov (United States)

    Pellizzaro, Grazia; Dubrovsky, Martin; Bortolu, Sara; Ventura, Andrea; Arca, Bachisio; Masia, Pierpaolo; Duce, Pierpaolo

    2014-05-01

    Mediterranean shrubs are an important component of both Mediterranean vegetation communities and understorey vegetation. They also constitute the surface fuels primarily responsible for the ignition and the spread of wildland fires in Mediterranean forests. Although fire spread and behaviour are dependent on several factors, the water content of live fuel plays an important role in determining fire occurrence and spread, especially in the Mediterranean shrubland, where live fuel is often the main component of the available fuel which catches fire. According to projections on future climate, an increase in risk of summer droughts is likely to take place in Southern Europe. More prolonged drought seasons induced by climatic changes are likely to influence general flammability characteristics of fuel, affecting load distribution in vegetation strata, floristic composition, and live and dead fuel ratio. In addition, variations in precipitation and mean temperature could directly affect fuel water status, and consequently flammability, and length of critical periods of high ignition danger for Mediterranean ecosystems. The main aim of this work was to propose a methodology for evaluating possible impacts of future climate change on moisture dynamic and length of fire danger period at local scale. Specific objectives were: i) evaluating performances of meteorological drought indices in describing seasonal pattern of live fuel moisture content (LFMC), and ii) simulating the potential impacts of future climate changes on the duration of fire danger period. Measurements of LFMC seasonal pattern of three Mediterranean shrub species were performed in North Western Sardinia (Italy) for 8 years. Seasonal patterns of LFMC were compared with the Drought Code of the Canadian Forest Fire Weather Index and the Keetch-Byram Drought Index. Analysis of frequency distribution and cumulative distribution curves were carried out in order to evaluate performance of codes and to identify

  14. Parametric design study of tandem mirror fusion reactors

    International Nuclear Information System (INIS)

    Carlson, G.A.

    1977-01-01

    The parametric design study of the tandem mirror reactor (TMR) is described. The results of this study illustrate the variation of reactor characteristics with changes in the independent design parameters, reveal the set of design parameters which minimizes the cost of the reactor, and show the sensitivity of the optimized design to physics and technological uncertainties. The total direct capital cost of an optimized 1000 MWe TMR is estimated to be $1300/kWe. The direct capital cost of a 2000 MWe plant is less than $1000/kWe

  15. Tokamak transmutation of (nuclear) waste (TTW): Parametric studies

    International Nuclear Information System (INIS)

    Cheng, E.T.; Krakowski, R.A.; Peng, Y.K.M.

    1994-01-01

    Radioactive waste generated as part of the commercial-power and defense nuclear programs can be either stored or transmuted. The latter treatment requires a capital-intensive neutron source and is reserved for particularly hazardous and long-lived actinide and fission-product waste. A comparative description of fusion-based transmutation is made on the basis of rudimentary estimates of ergonic performance and transmutation capacities versus inventories for both ultra-low-aspect-ratio (spherical torus, ST) and conversional (aspect-ratio) tokamak fusion-power-core drivers. The parametric systems studies reported herein provides a preamble to more-detailed, cost-based systems analyses

  16. Process simulation and parametric modeling for strategic project management

    CERN Document Server

    Morales, Peter J

    2013-01-01

    Process Simulation and Parametric Modeling for Strategic Project Management will offer CIOs, CTOs and Software Development Managers, IT Graduate Students an introduction to a set of technologies that will help them understand how to better plan software development projects, manage risk and have better insight into the complexities of the software development process.A novel methodology will be introduced that allows a software development manager to better plan and access risks in the early planning of a project.  By providing a better model for early software development estimation and softw

  17. Parametric decay instabilities in ECR heated plasmas

    International Nuclear Information System (INIS)

    Porkolab, M.

    1982-01-01

    The possibility of parametric excitation of electron Bernstein waves and low frequency ion oscillations during ECR heating at omega/sub o/ approx. = l omega/sub ce/, l = 1,2 is examined. In particular, the thresholds for such instabilities are calculated. It is found that Bernstein waves and lower hybrid quasi-modes have relatively low homogeneous where T/sub e/ approx. = T/sub i/. Thus, these processes may lead to nonlinear absorption and/or scattering of the incident pump wave. The resulting Bernstein waves may lead to either more effective heating (especially during the start-up phase) or to loss of microwave energy if the decay waves propagate out of the system before their energy is absorbed by particles. While at omega/sub o/ = omega/sub UH/ the threshold is reduced due to the WKB enhancement of the pump wave, (and this instability may be important in tokamaks) in EBT's and tandem mirrors the instability at omega /sub o/ greater than or equal to 2 omega/sub ce/ may be important. The instability may persist even if omega > 2 omega/sub ce/ and this may be the case during finite beta depression of the magnetic field in which case the decay waves may be trapped in the local magnetic well so that convective losses are minimized. The excited fluctuations may lead to additional scattering of the ring electrons and the incident microwave fields. Application of these calculations to ECR heating of tokamaks, tandem mirrors, and EBT's will be examined

  18. Uncertainty importance analysis using parametric moment ratio functions.

    Science.gov (United States)

    Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

    2014-02-01

    This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

  19. Parametric packet-based audiovisual quality model for IPTV services

    CERN Document Server

    Garcia, Marie-Neige

    2014-01-01

    This volume presents a parametric packet-based audiovisual quality model for Internet Protocol TeleVision (IPTV) services. The model is composed of three quality modules for the respective audio, video and audiovisual components. The audio and video quality modules take as input a parametric description of the audiovisual processing path, and deliver an estimate of the audio and video quality. These outputs are sent to the audiovisual quality module which provides an estimate of the audiovisual quality. Estimates of perceived quality are typically used both in the network planning phase and as part of the quality monitoring. The same audio quality model is used for both these phases, while two variants of the video quality model have been developed for addressing the two application scenarios. The addressed packetization scheme is MPEG2 Transport Stream over Real-time Transport Protocol over Internet Protocol. In the case of quality monitoring, that is the case for which the network is already set-up, the aud...

  20. Localization-Free Detection of Replica Node Attacks in Wireless Sensor Networks Using Similarity Estimation with Group Deployment Knowledge

    Directory of Open Access Journals (Sweden)

    Chao Ding

    2017-01-01

    Full Text Available Due to the unattended nature and poor security guarantee of the wireless sensor networks (WSNs, adversaries can easily make replicas of compromised nodes, and place them throughout the network to launch various types of attacks. Such an attack is dangerous because it enables the adversaries to control large numbers of nodes and extend the damage of attacks to most of the network with quite limited cost. To stop the node replica attack, we propose a location similarity-based detection scheme using deployment knowledge. Compared with prior solutions, our scheme provides extra functionalities that prevent replicas from generating false location claims without deploying resource-consuming localization techniques on the resource-constraint sensor nodes. We evaluate the security performance of our proposal under different attack strategies through heuristic analysis, and show that our scheme achieves secure and robust replica detection by increasing the cost of node replication. Additionally, we evaluate the impact of network environment on the proposed scheme through theoretic analysis and simulation experiments, and indicate that our scheme achieves effectiveness and efficiency with substantially lower communication, computational, and storage overhead than prior works under different situations and attack strategies.

  1. Local and regional estimation of floods in the Timis and Bega hydrographic basins: application of converging QDF model concept

    International Nuclear Information System (INIS)

    Mic, Rodica; Gaida, Gilles

    2004-01-01

    A flow-duration-frequency regionalisation is carried out on the Timis and Bega rivers sub-catchments in the west of Romania. This regionalisation concerns 28 sub-catchments having about thirty years of stream flow measurements (daily flow, instantaneous flood peaks and hydrographs). This work about the floods regionalisation is realized in the framework of the European project Riverlife. The regional model will allow defining the hydrographs of project necessary for the hydraulic modelling. This hydraulic project is necessary in order to protect Timisoara - city against the floods. The method uses the hypotheses of the converging QdF model and adapts the index flood method for obtaining a regional dimensionless distribution. For long return periods, this approach uses the GRADEX method, which extrapolates discharge distributions according to the rainfall distributions. The dimensionless regional QdF model needs two local descriptors of target site to be denormed: QIXA10 and Δ: the annual maximum instantaneous flow with a 10% probability to be exceeded (the 10-year peak flood) and a characteristic duration, respectively. For these both variables, the relations obtained by regression are presented, involving morphologic and climatic basin characteristics.(Author)

  2. Parametric system identification of catamaran for improving controller design

    Science.gov (United States)

    Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

    2018-01-01

    This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

  3. Regional and parametric sensitivity analysis of Sobol' indices

    International Nuclear Information System (INIS)

    Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

    2015-01-01

    Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields. These estimators are usually based on n+2 sample matrices well designed for computing both the main and total effect indices, where n is the input dimension. The aim of this paper is to use such n+2 sample matrices to investigate how the main and total effect indices change when the uncertainty of the model inputs are reduced. For this purpose, the regional main and total effect functions are defined for measuring the changes on the main and total effect indices when the distribution range of one input is reduced, and the parametric main and total effect functions are introduced to quantify the residual main and total effect indices due to the reduced variance of one input. Monte Carlo estimators are derived for all the developed sensitivity concepts based on the n+2 samples matrices originally used for computing the main and total effect indices, thus no extra computational cost is introduced. The Ishigami function, a nonlinear model and a planar ten-bar structure are utilized for illustrating the developed sensitivity concepts, and for demonstrating the efficiency and accuracy of the derived Monte Carlo estimators. - Highlights: • The regional main and total effect functions are developed. • The parametric main and total effect functions are introduced. • The proposed sensitivity functions are all generalizations of Sobol' indices. • The Monte Carlo estimators are derived for the four sensitivity functions. • The computational cost of the estimators is the same as that of Sobol' indices

  4. Parametric models to relate spike train and LFP dynamics with neural information processing.

    Science.gov (United States)

    Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

    2012-01-01

    Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

  5. Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

    Science.gov (United States)

    Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

    2017-12-01

    Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability

  6. Refined estimates of local recurrence risks by DCIS score adjusting for clinicopathological features: a combined analysis of ECOG-ACRIN E5194 and Ontario DCIS cohort studies.

    Science.gov (United States)

    Rakovitch, E; Gray, R; Baehner, F L; Sutradhar, R; Crager, M; Gu, S; Nofech-Mozes, S; Badve, S S; Hanna, W; Hughes, L L; Wood, W C; Davidson, N E; Paszat, L; Shak, S; Sparano, J A; Solin, L J

    2018-06-01

    Better tools are needed to estimate local recurrence (LR) risk after breast-conserving surgery (BCS) for DCIS. The DCIS score (DS) was validated as a predictor of LR in E5194 and Ontario DCIS cohort (ODC) after BCS. We combined data from E5194 and ODC adjusting for clinicopathological factors to provide refined estimates of the 10-year risk of LR after treatment by BCS alone. Data from E5194 and ODC were combined. Patients with positive margins or multifocality were excluded. Identical Cox regression models were fit for each study. Patient-specific meta-analysis was used to calculate precision-weighted estimates of 10-year LR risk by DS, age, tumor size and year of diagnosis. The combined cohort includes 773 patients. The DS and age at diagnosis, tumor size and year of diagnosis provided independent prognostic information on the 10-year LR risk (p ≤ 0.009). Hazard ratios from E5194 and ODC cohorts were similar for the DS (2.48, 1.95 per 50 units), tumor size ≤ 1 versus  > 1-2.5 cm (1.45, 1.47), age ≥ 50 versus  15%) 10-year LR risk after BCS alone compared to utilization of DS alone or clinicopathological factors alone. The combined analysis provides refined estimates of 10-year LR risk after BCS for DCIS. Adding information on tumor size and age at diagnosis to the DS adjusting for year of diagnosis provides improved LR risk estimates to guide treatment decision making.

  7. Parametric Studies of Square Solar Sails Using Finite Element Analysis

    Science.gov (United States)

    Sleight, David W.; Muheim, Danniella M.

    2004-01-01

    Parametric studies are performed on two generic square solar sail designs to identify parameters of interest. The studies are performed on systems-level models of full-scale solar sails, and include geometric nonlinearity and inertia relief, and use a Newton-Raphson scheme to apply sail pre-tensioning and solar pressure. Computational strategies and difficulties encountered during the analyses are also addressed. The purpose of this paper is not to compare the benefits of one sail design over the other. Instead, the results of the parametric studies may be used to identify general response trends, and areas of potential nonlinear structural interactions for future studies. The effects of sail size, sail membrane pre-stress, sail membrane thickness, and boom stiffness on the sail membrane and boom deformations, boom loads, and vibration frequencies are studied. Over the range of parameters studied, the maximum sail deflection and boom deformations are a nonlinear function of the sail properties. In general, the vibration frequencies and modes are closely spaced. For some vibration mode shapes, local deformation patterns that dominate the response are identified. These localized patterns are attributed to the presence of negative stresses in the sail membrane that are artifacts of the assumption of ignoring the effects of wrinkling in the modeling process, and are not believed to be physically meaningful. Over the range of parameters studied, several regions of potential nonlinear modal interaction are identified.

  8. Organizational flexibility estimation

    OpenAIRE

    Komarynets, Sofia

    2013-01-01

    By the help of parametric estimation the evaluation scale of organizational flexibility and its parameters was formed. Definite degrees of organizational flexibility and its parameters for the Lviv region enterprises were determined. Grouping of the enterprises under the existing scale was carried out. Special recommendations to correct the enterprises behaviour were given.

  9. Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Peng, E-mail: peng@ices.utexas.edu [The Institute for Computational Engineering and Sciences, The University of Texas at Austin, 201 East 24th Street, Stop C0200, Austin, TX 78712-1229 (United States); Schwab, Christoph, E-mail: christoph.schwab@sam.math.ethz.ch [Seminar für Angewandte Mathematik, Eidgenössische Technische Hochschule, Römistrasse 101, CH-8092 Zürich (Switzerland)

    2016-07-01

    We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by the so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online data

  10. Parametric pendulum based wave energy converter

    Science.gov (United States)

    Yurchenko, Daniil; Alevras, Panagiotis

    2018-01-01

    The paper investigates the dynamics of a novel wave energy converter based on the parametrically excited pendulum. The herein developed concept of the parametric pendulum allows reducing the influence of the gravity force thereby significantly improving the device performance at a regular sea state, which could not be achieved in the earlier proposed original point-absorber design. The suggested design of a wave energy converter achieves a dominant rotational motion without any additional mechanisms, like a gearbox, or any active control involvement. Presented numerical results of deterministic and stochastic modeling clearly reflect the advantage of the proposed design. A set of experimental results confirms the numerical findings and validates the new design of a parametric pendulum based wave energy converter. Power harvesting potential of the novel device is also presented.

  11. Parametric methods for spatial point processes

    DEFF Research Database (Denmark)

    Møller, Jesper

    is studied in Section 4, and Bayesian inference in Section 5. On one hand, as the development in computer technology and computational statistics continues,computationally-intensive simulation-based methods for likelihood inference probably will play a increasing role for statistical analysis of spatial...... inference procedures for parametric spatial point process models. The widespread use of sensible but ad hoc methods based on summary statistics of the kind studied in Chapter 4.3 have through the last two decades been supplied by likelihood based methods for parametric spatial point process models......(This text is submitted for the volume ‘A Handbook of Spatial Statistics' edited by A.E. Gelfand, P. Diggle, M. Fuentes, and P. Guttorp, to be published by Chapmand and Hall/CRC Press, and planned to appear as Chapter 4.4 with the title ‘Parametric methods'.) 1 Introduction This chapter considers...

  12. Parametric Conversion Using Custom MOS Varactors

    Directory of Open Access Journals (Sweden)

    Iniewski Krzysztof (Kris

    2006-01-01

    Full Text Available The possible role of customized MOS varactors in amplification, mixing, and frequency control of future millimeter wave CMOS RFICs is outlined. First, the parametric conversion concept is revisited and discussed in terms of modern RF communications systems. Second, the modeling, design, and optimization of MOS varactors are reconsidered in the context of their central role in parametric circuits. Third, a balanced varactor structure is proposed for robust oscillator frequency control in the presence of large extrinsic noise expected in tightly integrated wireless communicators. Main points include the proposal of a subharmonic pumping scheme based on the MOS varactor, a nonequilibrium elastance-voltage model, optimal varactor layout suggestions, custom m-CMOS varactor design and measurement, device-level balanced varactor simulations, and parametric circuit evaluation based on measured device characteristics.

  13. Piezoelectric energy harvesting with parametric uncertainty

    International Nuclear Information System (INIS)

    Ali, S F; Friswell, M I; Adhikari, S

    2010-01-01

    The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty

  14. Parametric analysis of ATM solar array.

    Science.gov (United States)

    Singh, B. K.; Adkisson, W. B.

    1973-01-01

    The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

  15. Nonparametric predictive inference for combining diagnostic tests with parametric copula

    Science.gov (United States)

    Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

    2017-09-01

    Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

  16. Wind effect in turbulence parametrization

    Science.gov (United States)

    Colombini, M.; Stocchino, A.

    2005-09-01

    The action of wind blowing over a closed basin ultimately results in a steady shear-induced circulation pattern and in a leeward rising of the free surface—and a corresponding windward lowering—known as wind set-up. If the horizontal dimensions of the basin are large with respect to the average flow depth, the occurrence of local quasi-equilibrium conditions can be expected, i.e. the flow can be assumed to be locally driven only by the wind stress and by the opposing free surface gradient due to set-up. This wind-induced flow configuration shows a strong similarity with turbulent Couette-Poiseuille flow, the one dimensional flow between parallel plates generated by the simultaneous action of a constant pressure gradient and of the shear induced by the relative motion of the plates. A two-equation turbulence closure is then employed to perform a numerical study of turbulent Couette-Poiseuille flows for different values of the ratio of the shear stresses at the two walls. The resulting eddy viscosity vertical distributions are analyzed in order to devise analytical profiles of eddy viscosity that account for the effect of wind. The results of this study, beside allowing for a physical insight on the turbulence process of this class of flows, will allow for a more accurate description of the wind effect to be included in the formulation of quasi-3D and 3D models of lagoon hydrodynamics.

  17. Local and omnibus goodness-of-fit tests in classical measurement error models

    KAUST Repository

    Ma, Yanyuan

    2010-09-14

    We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

  18. Parametric Landau damping of space charge modes

    Energy Technology Data Exchange (ETDEWEB)

    Macridin, Alexandru [Fermilab; Burov, Alexey [Fermilab; Stern, Eric [Fermilab; Amundson, James [Fermilab; Spentzouris, Panagiotis [Fermilab

    2016-09-23

    Landau damping is the mechanism of plasma and beam stabilization; it arises through energy transfer from collective modes to the incoherent motion of resonant particles. Normally this resonance requires the resonant particle's frequency to match the collective mode frequency. We have identified an important new damping mechanism, parametric Landau damping, which is driven by the modulation of the mode-particle interaction. This opens new possibilities for stability control through manipulation of both particle and mode-particle coupling spectra. We demonstrate the existence of parametric Landau damping in a simulation of transverse coherent modes of bunched accelerator beams with space charge.

  19. Parametric frequency conversion in long Josephson junctions

    International Nuclear Information System (INIS)

    Irie, F.; Ashihara, S.; Yoshida, K.

    1976-01-01

    Current steps at voltages corresponding to the parametric coupling between an applied r.f. field and junction resonant modes have been observed in long Josephson tunnel junctions in the flux-flow state. The observed periodic variations of the step height due to the applied magnetic field are explained quantitatively by a perturbational analysis using Josephson phase equations. The present study demonstrates that the moving vortex array can serve as a coherent pump wave for signal waves propagating in the barrier region, which indicates, as a result, the possibility of traveling-wave parametric devices with long Josephson tunnel junctions. (author)

  20. Semi-parametric modelling of investments in heating installations: The case of the Dutch glasshouse industry

    NARCIS (Netherlands)

    Oude Lansink, A.G.J.M.; Pietola, K.

    2005-01-01

    This paper applies a semi-parametric approach to estimating a generalised model of investments in heating installations. The results suggest that marginal costs of investments in heating installations increase quickly at small investment levels, whereas the increase slows down at higher investment