WorldWideScience

Sample records for local parametric estimation

  1. 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)

  2. 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...

  3. 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...

  4. 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)

  5. 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...

  6. 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.

  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. 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...

  9. 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

  10. 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....

  11. 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...

  12. 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.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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)

  19. 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...

  20. 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...

  1. 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

  2. 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...

  3. 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 ...

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  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. 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...

  11. 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...

  12. 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...

  13. 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 ...

  14. 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.

  15. 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 (...

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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...

  3. 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)

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. 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

  10. 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

  11. 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.

  12. 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),

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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).

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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...

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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....

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. 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 ...

  2. 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.

  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. 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).

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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

  14. 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...

  15. 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.

  16. 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.

  17. 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....

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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…

  10. 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…

  11. 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

  12. 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.

  13. 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)

  14. 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)

  15. 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.

  16. 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)

  17. 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.

  18. 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...

  19. [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.

  20. An integrated approach to estimate storage reliability with initial failures based on E-Bayesian estimates

    International Nuclear Information System (INIS)

    Zhang, Yongjin; Zhao, Ming; Zhang, Shitao; Wang, Jiamei; Zhang, Yanjun

    2017-01-01

    Storage reliability that measures the ability of products in a dormant state to keep their required functions is studied in this paper. For certain types of products, Storage reliability may not always be 100% at the beginning of storage, unlike the operational reliability, which exist possible initial failures that are normally neglected in the models of storage reliability. In this paper, a new integrated technique, the non-parametric measure based on the E-Bayesian estimates of current failure probabilities is combined with the parametric measure based on the exponential reliability function, is proposed to estimate and predict the storage reliability of products with possible initial failures, where the non-parametric method is used to estimate the number of failed products and the reliability at each testing time, and the parameter method is used to estimate the initial reliability and the failure rate of storage product. The proposed method has taken into consideration that, the reliability test data of storage products containing the unexamined before and during the storage process, is available for providing more accurate estimates of both the initial failure probability and the storage failure probability. When storage reliability prediction that is the main concern in this field should be made, the non-parametric estimates of failure numbers can be used into the parametric models for the failure process in storage. In the case of exponential models, the assessment and prediction method for storage reliability is presented in this paper. Finally, a numerical example is given to illustrate the method. Furthermore, a detailed comparison between the proposed and traditional method, for examining the rationality of assessment and prediction on the storage reliability, is investigated. The results should be useful for planning a storage environment, decision-making concerning the maximum length of storage, and identifying the production quality. - Highlights:

  1. 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.

  2. 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

  3. 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.

  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

    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.

  5. 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...

  6. 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

  7. 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.

  8. 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

  9. 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...

  10. 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...

  11. 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.

  12. 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....

  13. 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...

  14. 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.)

  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. 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.

  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. 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. Identification of parametric models with a priori knowledge of process properties

    Directory of Open Access Journals (Sweden)

    Janiszowski Krzysztof B.

    2016-12-01

    Full Text Available An approach to estimation of a parametric discrete-time model of a process in the case of some a priori knowledge of the investigated process properties is presented. The knowledge of plant properties is introduced in the form of linear bounds, which can be determined for the coefficient vector of the parametric model studied. The approach yields special biased estimation of model coefficients that preserves demanded properties. A formula for estimation of the model coefficients is derived and combined with a recursive scheme determined for minimization of the sum of absolute model errors. The estimation problem of a model with known static gains of inputs is discussed and proper formulas are derived. This approach can overcome the non-identifiability problem which has been observed during estimation based on measurements recorded in industrial closed-loop control systems. The application of the proposed approach to estimation of a model for an industrial plant (a water injector into the steam flow in a power plant is presented and discussed.

  20. Robust-BD Estimation and Inference for General Partially Linear Models

    Directory of Open Access Journals (Sweden)

    Chunming Zhang

    2017-11-01

    Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.

  1. Non-parametric system identification from non-linear stochastic response

    DEFF Research Database (Denmark)

    Rüdinger, Finn; Krenk, Steen

    2001-01-01

    An estimation method is proposed for identification of non-linear stiffness and damping of single-degree-of-freedom systems under stationary white noise excitation. Non-parametric estimates of the stiffness and damping along with an estimate of the white noise intensity are obtained by suitable...... of the energy at mean-level crossings, which yields the damping relative to white noise intensity. Finally, an estimate of the noise intensity is extracted by estimating the absolute damping from the autocovariance functions of a set of modified phase plane variables at different energy levels. The method...

  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. 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....

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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....

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Radionuclide mass inventory, activity, decay heat, and dose rate parametric data for TRIGA spent nuclear fuels

    International Nuclear Information System (INIS)

    Sterbentz, J.W.

    1997-03-01

    Parametric burnup calculations are performed to estimate radionuclide isotopic mass and activity concentrations for four different Training, Research, and Isotope General Atomics (TRIGA) nuclear reactor fuel element types: (1) Aluminum-clad standard, (2) Stainless Steel-clad standard, (3) High-enrichment Fuel Life Improvement Program (FLIP), and (4) Low-enrichment Fuel Life Improvement Program (FLIP-LEU-1). Parametric activity data are tabulated for 145 important radionuclides that can be used to generate gamma-ray emission source terms or provide mass quantity estimates as a function of decay time. Fuel element decay heats and dose rates are also presented parametrically as a function of burnup and decay time. Dose rates are given at the fuel element midplane for contact, 3.0-feet, and 3.0-meter detector locations in air. The data herein are estimates based on specially derived Beginning-of-Life (BOL) neutron cross sections using geometrically-explicit TRIGA reactor core models. The calculated parametric data should represent good estimates relative to actual values, although no experimental data were available for direct comparison and validation. However, because the cross sections were not updated as a function of burnup, the actinide concentrations may deviate from the actual values at the higher burnups

  15. 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

  16. 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...

  17. 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

  18. 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.

  19. 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)

  20. Open and Closed Loop Parametric System Identification in Compact Disk Players

    DEFF Research Database (Denmark)

    Vidal, Enrique Sanchez; Stoustrup, Jakob; Andersen, Palle

    2001-01-01

    By measuring the current through the coil of the actuators in the optical pick-up in a compact disk player, open loop parametric system identification can be performed. The parameters are identified by minimizing the least-squares loss function of the ARX model. The only parameter which cannot be...... be identified in open loop is the optical gain. This is therefore estimated in closed loop. Practical results are analyzed and show very accurate estimates of the real parameters.......By measuring the current through the coil of the actuators in the optical pick-up in a compact disk player, open loop parametric system identification can be performed. The parameters are identified by minimizing the least-squares loss function of the ARX model. The only parameter which cannot...

  1. 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...

  2. 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.

  3. 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...

  4. 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)

  5. 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)

  6. Estimation of viscoelastic parameters in Prony series from shear wave propagation

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Jae-Wook; Hong, Jung-Wuk, E-mail: j.hong@kaist.ac.kr, E-mail: jwhong@alum.mit.edu [Department of Civil and Environmental Engineering, KAIST, 291 Deahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Lee, Hyoung-Ki; Choi, Kiwan [Health and Medical Equipment, Samsung Electronics, 1003 Daechi-dong, Gangnam-gu, Seoul 135-280 (Korea, Republic of)

    2016-06-21

    When acquiring accurate ultrasonic images, we must precisely estimate the mechanical properties of the soft tissue. This study investigates and estimates the viscoelastic properties of the tissue by analyzing shear waves generated through an acoustic radiation force. The shear waves are sourced from a localized pushing force acting for a certain duration, and the generated waves travel horizontally. The wave velocities depend on the mechanical properties of the tissue such as the shear modulus and viscoelastic properties; therefore, we can inversely calculate the properties of the tissue through parametric studies.

  7. 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

  8. Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs

    Directory of Open Access Journals (Sweden)

    Liang Kung-Yee

    2010-07-01

    Full Text Available Abstract Background Many dichotomous traits for complex diseases are often involved more than one locus and/or associated with quantitative biomarkers or environmental factors. Incorporating these quantitative variables into linkage analysis as well as localizing two linked disease loci simultaneously could therefore improve the efficiency in mapping genes. We extended the robust multipoint Identity-by-Descent (IBD approach with incorporation of covariates developed previously to simultaneously estimate two linked loci using different types of affected relative pairs (ARPs. Results We showed that the efficiency was enhanced by incorporating a quantitative covariate parametrically or non-parametrically while localizing two disease loci using ARPs. In addition to its help in identifying factors associated with the disease and in improving the efficiency in estimating disease loci, this extension also allows investigators to account for heterogeneity in risk-ratios for different ARPs. Data released from the collaborative study on the genetics of alcoholism (COGA for Genetic Analysis Workshop 14 (GAW 14 were used to illustrate the application of this extended method. Conclusions The simulation studies and example illustrated that the efficiency in estimating disease loci was demonstratively enhanced by incorporating a quantitative covariate and by using all relative pairs while mapping two linked loci simultaneously.

  9. A parametric level-set approach for topology optimization of flow domains

    DEFF Research Database (Denmark)

    Pingen, Georg; Waidmann, Matthias; Evgrafov, Anton

    2010-01-01

    of the design variables in the traditional approaches is seen as a possible cause for the slow convergence. Non-smooth material distributions are suspected to trigger premature onset of instationary flows which cannot be treated by steady-state flow models. In the present work, we study whether the convergence...... and the versatility of topology optimization methods for fluidic systems can be improved by employing a parametric level-set description. In general, level-set methods allow controlling the smoothness of boundaries, yield a non-local influence of design variables, and decouple the material description from the flow...... field discretization. The parametric level-set method used in this study utilizes a material distribution approach to represent flow boundaries, resulting in a non-trivial mapping between design variables and local material properties. Using a hydrodynamic lattice Boltzmann method, we study...

  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. 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)

  12. 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

  13. 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.

  14. 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

  15. Parametric trends analysis of the critical heat flux based on artificial neural networks

    International Nuclear Information System (INIS)

    Moon, S.K.; Baek, W.P.; Chang, S.H.

    1996-01-01

    Parametric trends of the critical heat flux (CHF) are analyzed by applying artificial neural networks (ANNs) to a CHF data base for upward flow of water in uniformly heated vertical round tubes. The analyses are performed from three viewpoints, i.e., for fixed inlet conditions, for fixed exit conditions, and based on local conditions hypothesis. Katto's and Groeneveld et al. dimensionless parameters are used to train the ANNs with the experimental CHF data. The trained ANNs predict the CHF better than any other conventional correlations, showing RMS errors of 8.9%, 13.1% and 19.3% for fixed inlet conditions, for fixed exit conditions, and for local conditions hypothesis, respectively. The parametric trends of the CHF obtained from those trained ANNs show a general agreement with previous understanding. In addition, this study provides more comprehensive information and indicates interesting points for the effects of the tube diameter, the heated length, and the mass flux. It is expected that better understanding of the parametric trends is feasible with an extended data base. (orig.)

  16. 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)

  17. 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.

  18. 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....

  19. 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) ...

  20. 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

  1. 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....

  2. 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

  3. 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.

  4. Application of semi parametric modelling to times series forecasting: case of the electricity consumption

    International Nuclear Information System (INIS)

    Lefieux, V.

    2007-10-01

    Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)

  5. Quantitative myocardial perfusion PET parametric imaging at the voxel-level

    International Nuclear Information System (INIS)

    Mohy-ud-Din, Hassan; Rahmim, Arman; Lodge, Martin A

    2015-01-01

    Quantitative myocardial perfusion (MP) PET has the potential to enhance detection of early stages of atherosclerosis or microvascular dysfunction, characterization of flow-limiting effects of coronary artery disease (CAD), and identification of balanced reduction of flow due to multivessel stenosis. We aim to enable quantitative MP-PET at the individual voxel level, which has the potential to allow enhanced visualization and quantification of myocardial blood flow (MBF) and flow reserve (MFR) as computed from uptake parametric images. This framework is especially challenging for the 82 Rb radiotracer. The short half-life enables fast serial imaging and high patient throughput; yet, the acquired dynamic PET images suffer from high noise-levels introducing large variability in uptake parametric images and, therefore, in the estimates of MBF and MFR. Robust estimation requires substantial post-smoothing of noisy data, degrading valuable functional information of physiological and pathological importance. We present a feasible and robust approach to generate parametric images at the voxel-level that substantially reduces noise without significant loss of spatial resolution. The proposed methodology, denoted physiological clustering, makes use of the functional similarity of voxels to penalize deviation of voxel kinetics from physiological partners. The results were validated using extensive simulations (with transmural and non-transmural perfusion defects) and clinical studies. Compared to post-smoothing, physiological clustering depicted enhanced quantitative noise versus bias performance as well as superior recovery of perfusion defects (as quantified by CNR) with minimal increase in bias. Overall, parametric images obtained from the proposed methodology were robust in the presence of high-noise levels as manifested in the voxel time-activity-curves. (paper)

  6. Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

    Science.gov (United States)

    Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

    2017-05-01

    Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

  7. Composite likelihood and two-stage estimation in family studies

    DEFF Research Database (Denmark)

    Andersen, Elisabeth Anne Wreford

    2004-01-01

    In this paper register based family studies provide the motivation for linking a two-stage estimation procedure in copula models for multivariate failure time data with a composite likelihood approach. The asymptotic properties of the estimators in both parametric and semi-parametric models are d...

  8. 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.

  9. 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...

  10. Non-asymptotic fractional order differentiators via an algebraic parametric method

    KAUST Repository

    Liu, Dayan; Gibaru, O.; Perruquetti, Wilfrid

    2012-01-01

    Recently, Mboup, Join and Fliess [27], [28] introduced non-asymptotic integer order differentiators by using an algebraic parametric estimation method [7], [8]. In this paper, in order to obtain non-asymptotic fractional order differentiators we apply this algebraic parametric method to truncated expansions of fractional Taylor series based on the Jumarie's modified Riemann-Liouville derivative [14]. Exact and simple formulae for these differentiators are given where a sliding integration window of a noisy signal involving Jacobi polynomials is used without complex mathematical deduction. The efficiency and the stability with respect to corrupting noises of the proposed fractional order differentiators are shown in numerical simulations. © 2012 IEEE.

  11. Non-asymptotic fractional order differentiators via an algebraic parametric method

    KAUST Repository

    Liu, Dayan

    2012-08-01

    Recently, Mboup, Join and Fliess [27], [28] introduced non-asymptotic integer order differentiators by using an algebraic parametric estimation method [7], [8]. In this paper, in order to obtain non-asymptotic fractional order differentiators we apply this algebraic parametric method to truncated expansions of fractional Taylor series based on the Jumarie\\'s modified Riemann-Liouville derivative [14]. Exact and simple formulae for these differentiators are given where a sliding integration window of a noisy signal involving Jacobi polynomials is used without complex mathematical deduction. The efficiency and the stability with respect to corrupting noises of the proposed fractional order differentiators are shown in numerical simulations. © 2012 IEEE.

  12. Performances of non-parametric statistics in sensitivity analysis and parameter ranking

    International Nuclear Information System (INIS)

    Saltelli, A.

    1987-01-01

    Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis

  13. Plug and Play Robust Distributed Control with Ellipsoidal Parametric Uncertainty System

    Directory of Open Access Journals (Sweden)

    Hong Wang-jian

    2016-01-01

    Full Text Available We consider a continuous linear time invariant system with ellipsoidal parametric uncertainty structured into subsystems. Since the design of a local controller uses only information on a subsystem and its neighbours, we combine the plug and play idea and robust distributed control to propose one distributed control strategy for linear system with ellipsoidal parametric uncertainty. Firstly for linear system with ellipsoidal parametric uncertainty, a necessary and sufficient condition for robust state feedback control is proposed by means of linear matrix inequality. If this necessary and sufficient condition is satisfied, this robust state feedback gain matrix can be easily derived to guarantee robust stability and prescribed closed loop performance. Secondly the plug and play idea is introduced in the design process. Finally by one example of aircraft flutter model parameter identification, the efficiency of the proposed control strategy can be easily realized.

  14. Density Fluctuations in the Solar Wind Driven by Alfvén Wave Parametric Decay

    Science.gov (United States)

    Bowen, Trevor A.; Badman, Samuel; Hellinger, Petr; Bale, Stuart D.

    2018-02-01

    Measurements and simulations of inertial compressive turbulence in the solar wind are characterized by anti-correlated magnetic fluctuations parallel to the mean field and density structures. This signature has been interpreted as observational evidence for non-propagating pressure balanced structures, kinetic ion-acoustic waves, as well as the MHD slow-mode. Given the high damping rates of parallel propagating compressive fluctuations, their ubiquity in satellite observations is surprising and suggestive of a local driving process. One possible candidate for the generation of compressive fluctuations in the solar wind is the Alfvén wave parametric instability. Here, we test the parametric decay process as a source of compressive waves in the solar wind by comparing the collisionless damping rates of compressive fluctuations with growth rates of the parametric decay instability daughter waves. Our results suggest that generation of compressive waves through parametric decay is overdamped at 1 au, but that the presence of slow-mode-like density fluctuations is correlated with the parametric decay of Alfvén waves.

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

    Science.gov (United States)

    Sumarjaya, I. W.

    2017-10-01

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

  16. Parametric imaging for characterizing focal liver lesions in contrast-enhanced ultrasound.

    Science.gov (United States)

    Rognin, Nicolas G; Arditi, Marcel; Mercier, Laurent; Frinking, Peter J A; Schneider, Michel; Perrenoud, Geneviève; Anaye, Anass; Meuwly, Jean-Yves; Tranquart, François

    2010-11-01

    The differentiation between benign and malignant focal liver lesions plays an important role in diagnosis of liver disease and therapeutic planning of local or general disease. This differentiation, based on characterization, relies on the observation of the dynamic vascular patterns (DVP) of lesions with respect to adjacent parenchyma, and may be assessed during contrast-enhanced ultrasound imaging after a bolus injection. For instance, hemangiomas (i.e., benign lesions) exhibit hyper-enhanced signatures over time, whereas metastases (i.e., malignant lesions) frequently present hyperenhanced foci during the arterial phase and always become hypo-enhanced afterwards. The objective of this work was to develop a new parametric imaging technique, aimed at mapping the DVP signatures into a single image called a DVP parametric image, conceived as a diagnostic aid tool for characterizing lesion types. The methodology consisted in processing a time sequence of images (DICOM video data) using four consecutive steps: (1) pre-processing combining image motion correction and linearization to derive an echo-power signal, in each pixel, proportional to local contrast agent concentration over time; (2) signal modeling, by means of a curve-fitting optimization, to compute a difference signal in each pixel, as the subtraction of adjacent parenchyma kinetic from the echopower signal; (3) classification of difference signals; and (4) parametric image rendering to represent classified pixels as a support for diagnosis. DVP parametric imaging was the object of a clinical assessment on a total of 146 lesions, imaged using different medical ultrasound systems. The resulting sensitivity and specificity were 97% and 91%, respectively, which compare favorably with scores of 81 to 95% and 80 to 95% reported in medical literature for sensitivity and specificity, respectively.

  17. 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....

  18. Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models

    NARCIS (Netherlands)

    J.V.K. Rombouts; M.J.C.M. Verbeek (Marno)

    2009-01-01

    textabstractIn this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes.

  19. 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

  20. 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.

  1. 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.

  2. Constrained Convolutional Sparse Coding for Parametric Based Reconstruction of Line Drawings

    KAUST Repository

    Shaheen, Sara

    2017-12-25

    Convolutional sparse coding (CSC) plays an essential role in many computer vision applications ranging from image compression to deep learning. In this work, we spot the light on a new application where CSC can effectively serve, namely line drawing analysis. The process of drawing a line drawing can be approximated as the sparse spatial localization of a number of typical basic strokes, which in turn can be cast as a non-standard CSC model that considers the line drawing formation process from parametric curves. These curves are learned to optimize the fit between the model and a specific set of line drawings. Parametric representation of sketches is vital in enabling automatic sketch analysis, synthesis and manipulation. A couple of sketch manipulation examples are demonstrated in this work. Consequently, our novel method is expected to provide a reliable and automatic method for parametric sketch description. Through experiments, we empirically validate the convergence of our method to a feasible solution.

  3. 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....

  4. 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

  5. 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)

  6. 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.

  7. Parametric model measurement: reframing traditional measurement ideas in neuropsychological practice and research.

    Science.gov (United States)

    Brown, Gregory G; Thomas, Michael L; Patt, Virginie

    Neuropsychology is an applied measurement field with its psychometric work primarily built upon classical test theory (CTT). We describe a series of psychometric models to supplement the use of CTT in neuropsychological research and test development. We introduce increasingly complex psychometric models as measurement algebras, which include model parameters that represent abilities and item properties. Within this framework of parametric model measurement (PMM), neuropsychological assessment involves the estimation of model parameters with ability parameter values assuming the role of test 'scores'. Moreover, the traditional notion of measurement error is replaced by the notion of parameter estimation error, and the definition of reliability becomes linked to notions of item and test information. The more complex PMM approaches incorporate into the assessment of neuropsychological performance formal parametric models of behavior validated in the experimental psychology literature, along with item parameters. These PMM approaches endorse the use of experimental manipulations of model parameters to assess a test's construct representation. Strengths and weaknesses of these models are evaluated by their implications for measurement error conditional upon ability level, sensitivity to sample characteristics, computational challenges to parameter estimation, and construct validity. A family of parametric psychometric models can be used to assess latent processes of interest to neuropsychologists. By modeling latent abilities at the item level, psychometric studies in neuropsychology can investigate construct validity and measurement precision within a single framework and contribute to a unification of statistical methods within the framework of generalized latent variable modeling.

  8. 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.

  9. 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.

  10. 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

  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. 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.

  13. 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.

  14. 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.

  15. Multi-parametric MR imaging for prostate carcinoma; Multiparametrische MR-Bildgebung beim Prostatakarzinom

    Energy Technology Data Exchange (ETDEWEB)

    Schlemmer, Heinz-Peter [Deutsches Krebsforschungszentrum, Heidelberg (Germany). Abt. Radiologie

    2017-03-15

    Multi-parametric NMR imaging in case of prostate carcinoma can improve diagnostics, allows reliable prognostic estimations and helps to find the optimum individual therapy. The contribution is focused to deliver the needed methodological tools and background knowledge for the daily routine.

  16. 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.

  17. 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...

  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 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.

  20. A semi-parametric within-subject mixture approach to the analyses of responses and response times.

    Science.gov (United States)

    Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

    2018-05-01

    In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

  1. 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.

  2. Super learning to hedge against incorrect inference from arbitrary parametric assumptions in marginal structural modeling.

    Science.gov (United States)

    Neugebauer, Romain; Fireman, Bruce; Roy, Jason A; Raebel, Marsha A; Nichols, Gregory A; O'Connor, Patrick J

    2013-08-01

    Clinical trials are unlikely to ever be launched for many comparative effectiveness research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data, but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called super learning (SL) to avoid reliance on arbitrary parametric assumptions in CER. Using the electronic health records data from adults with new-onset type 2 diabetes, we implemented MSM with inverse probability weighting (IPW) estimation to evaluate the effect of three oral antidiabetic therapies on the worsening of glomerular filtration rate. Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, that is, time-dependent measurements of hemoglobin A1c. SL was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Erroneous IPW inference about clinical effectiveness because of arbitrary and incorrect modeling decisions may be avoided with SL. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. 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.)

  4. 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.

  5. 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.

  6. A parametrization of σT(γ*p) above the resonance region for Q2 ≥ 0

    International Nuclear Information System (INIS)

    Abramowicz, H.; Maor, U.

    1991-06-01

    A smooth description of the total γ*p cross section from the deep inelastic scattering region to the real photoproduction limit is obtained with a parametrization based on a Regge type approach. The parametrization is obtained from a fit to the structure function data of BCDMS, SLAC and NA28 and the available total photoproduction cross section measurements above the resonance region, W>1.75 GeV. The fit give a reliable description of the data and provides a smooth transition from photoproduction to the deep inelastic region. Together with an earlier parametrization of the resonance region, it can be used to estimate radiative corrections over the full kinematical range. (orig.)

  7. 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....

  8. Temperature dependent power capability estimation of lithium-ion batteries for hybrid electric vehicles

    International Nuclear Information System (INIS)

    Zheng, Fangdan; Jiang, Jiuchun; Sun, Bingxiang; Zhang, Weige; Pecht, Michael

    2016-01-01

    The power capability of lithium-ion batteries affects the safety and reliability of hybrid electric vehicles and the estimate of power by battery management systems provides operating information for drivers. In this paper, lithium ion manganese oxide batteries are studied to illustrate the temperature dependency of power capability and an operating map of power capability is presented. Both parametric and non-parametric models are established in conditions of temperature, state of charge, and cell resistance to estimate the power capability. Six cells were tested and used for model development, training, and validation. Three samples underwent hybrid pulse power characterization tests at varied temperatures and were used for model parameter identification and model training. The other three were used for model validation. By comparison, the mean absolute error of the parametric model is about 29 W, and that of the non-parametric model is around 20 W. The mean relative errors of two models are 0.076 and 0.397, respectively. The parametric model has a higher accuracy in low temperature and state of charge conditions, while the non-parametric model has better estimation result in high temperature and state of charge conditions. Thus, two models can be utilized together to achieve a higher accuracy of power capability estimation. - Highlights: • The temperature dependency of power capability of lithium-ion battery is investigated. • The parametric and non-parametric power capability estimation models are proposed. • An exponential function is put forward to compensate the effects of temperature. • A comparative study on the accuracy of two models using statistical metrics is presented.

  9. 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...

  10. PET image reconstruction using multi-parametric anato-functional priors

    Science.gov (United States)

    Mehranian, Abolfazl; Belzunce, Martin A.; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J.

    2017-08-01

    In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [18F]florbetaben and [18F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical results

  11. Parametric Characterization of TES Detectors Under DC Bias

    Science.gov (United States)

    Chiao, Meng P.; Smith, Stephen James; Kilbourne, Caroline A.; Adams, Joseph S.; Bandler, Simon R.; Betancourt-Martinez, Gabriele L.; Chervenak, James A.; Datesman, Aaron M.; Eckart, Megan E.; Ewin, Audrey J.; hide

    2016-01-01

    The X-ray integrated field unit (X-IFU) in European Space Agency's (ESA's) Athena mission will be the first high-resolution X-ray spectrometer in space using a large-format transition-edge sensor microcalorimeter array. Motivated by optimization of detector performance for X-IFU, we have conducted an extensive campaign of parametric characterization on transition-edge sensor (TES) detectors with nominal geometries and physical properties in order to establish sensitivity trends relative to magnetic field, dc bias on detectors, operating temperature, and to improve our understanding of detector behavior relative to its fundamental properties such as thermal conductivity, heat capacity, and transition temperature. These results were used for validation of a simple linear detector model in which a small perturbation can be introduced to one or multiple parameters to estimate the error budget for X-IFU. We will show here results of our parametric characterization of TES detectors and briefly discuss the comparison with the TES model.

  12. 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

  13. 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....

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. On the parametrization of the planetary boundary layer of the atmosphere

    Energy Technology Data Exchange (ETDEWEB)

    Yordanov, D. [Bulgarian Academy of Sciences, Geophysical Inst., Sofia (Bulgaria); Syrakov, D.; Kolarova, M. [Bulgarian Academy of Sciences, National Inst. of Meteorology and Hydrology, Sofia (United Kingdom)

    1997-10-01

    The investigation of the dynamic processes in the planetary boundary layer presents a definite theoretical challenge and plays a growing role for the solution of a number of practical tasks. The improvement of large-scale atmospheric weather forecast depends, to a certain degree, on the proper inclusion of the planetary boundary layer dynamics in the numerical models. The modeling of the transport and the diffusion of air pollutants is connected with estimation of the different processes in the Planetary Boundary Layer (PBL) and needs also a proper PBL parametrization. For the solution of these practical tasks the following PBL models;(i) a baroclinic PBL model with its barotropic version, and (ii) a convective PBL model were developed. Both models are one dimensional and are based on the similarity theory and the resistance lows extended for the whole PBL. Two different PBL parametrizations under stable and under convective conditions are proposed, on the basis of which the turbulent surface heat and momentum fluxes are estimated using generalized similarity theory. By the proposed parametrizations the internal parameters are calculated from the synoptic scale parameters as geostrophyc wind, potential temperature and humidity given at two levels (ground level and at 850 hPa) and from them - the PBL profiles. The models consists of two layers: a surface layer (SL) with a variable height and a second (Ekman layer) over it with a constant with height turbulent exchange coefficient. (au) 14 refs.

  19. 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)

  20. 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

  1. 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....

  2. New Parametric Imaging Algorithm for Quantification of Binding Parameter in non-reversible compartment model: MLAIR

    International Nuclear Information System (INIS)

    Kim, Su Jin; Lee, Jae Sung; Kim, Yu Kyeong; Lee, Dong Soo

    2007-01-01

    Parametric imaging allows us analysis of the entire brain or body image. Graphical approaches are commonly employed to generate parametric imaging through linear or multilinear regression. However, this linear regression method has limited accuracy due to bias in high level of noise data. Several methods have been proposed to reduce bias for linear regression estimation especially in reversible model. In this study, we focus on generating a net accumulation rate (K i ), which is related to binding parameter in brain receptor study, parametric imaging in an irreversible compartment model using multiple linear analysis. The reliability of a newly developed multiple linear analysis method (MLAIR) was assessed through the Monte Carlo simulation, and we applied it to a [ 11 C]MeNTI PET for opioid receptor

  3. 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.

  4. Comparison of radiation parametrizations within the HARMONIE-AROME NWP model

    Science.gov (United States)

    Rontu, Laura; Lindfors, Anders V.

    2018-05-01

    Downwelling shortwave radiation at the surface (SWDS, global solar radiation flux), given by three different parametrization schemes, was compared to observations in the HARMONIE-AROME numerical weather prediction (NWP) model experiments over Finland in spring 2017. Simulated fluxes agreed well with each other and with the observations in the clear-sky cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS at the daily level, as compared to the measurements. Large local and temporal differences between the model results and observations were seen, related to the variations and uncertainty of the predicted cloud properties. The results suggest a possibility to benefit from the use of different radiative transfer parametrizations in a NWP model to obtain perturbations for the fine-resolution ensemble prediction systems. In addition, we recommend usage of the global radiation observations for the standard validation of the NWP models.

  5. 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

  6. A non-parametric Bayesian approach to decompounding from high frequency data

    NARCIS (Netherlands)

    Gugushvili, Shota; van der Meulen, F.H.; Spreij, Peter

    2016-01-01

    Given a sample from a discretely observed compound Poisson process, we consider non-parametric estimation of the density f0 of its jump sizes, as well as of its intensity λ0. We take a Bayesian approach to the problem and specify the prior on f0 as the Dirichlet location mixture of normal densities.

  7. A physiology-based parametric imaging method for FDG-PET data

    Science.gov (United States)

    Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

    2017-12-01

    Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

  8. 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....

  9. Modelling present-day basal melt rates for Antarctic ice shelves using a parametrization of buoyant meltwater plumes

    Science.gov (United States)

    Lazeroms, Werner M. J.; Jenkins, Adrian; Hilmar Gudmundsson, G.; van de Wal, Roderik S. W.

    2018-01-01

    Basal melting below ice shelves is a major factor in mass loss from the Antarctic Ice Sheet, which can contribute significantly to possible future sea-level rise. Therefore, it is important to have an adequate description of the basal melt rates for use in ice-dynamical models. Most current ice models use rather simple parametrizations based on the local balance of heat between ice and ocean. In this work, however, we use a recently derived parametrization of the melt rates based on a buoyant meltwater plume travelling upward beneath an ice shelf. This plume parametrization combines a non-linear ocean temperature sensitivity with an inherent geometry dependence, which is mainly described by the grounding-line depth and the local slope of the ice-shelf base. For the first time, this type of parametrization is evaluated on a two-dimensional grid covering the entire Antarctic continent. In order to apply the essentially one-dimensional parametrization to realistic ice-shelf geometries, we present an algorithm that determines effective values for the grounding-line depth and basal slope in any point beneath an ice shelf. Furthermore, since detailed knowledge of temperatures and circulation patterns in the ice-shelf cavities is sparse or absent, we construct an effective ocean temperature field from observational data with the purpose of matching (area-averaged) melt rates from the model with observed present-day melt rates. Our results qualitatively replicate large-scale observed features in basal melt rates around Antarctica, not only in terms of average values, but also in terms of the spatial pattern, with high melt rates typically occurring near the grounding line. The plume parametrization and the effective temperature field presented here are therefore promising tools for future simulations of the Antarctic Ice Sheet requiring a more realistic oceanic forcing.

  10. A comparison of dependence function estimators in multivariate extremes

    KAUST Repository

    Vettori, Sabrina; Huser, Raphaë l; Genton, Marc G.

    2017-01-01

    Various nonparametric and parametric estimators of extremal dependence have been proposed in the literature. Nonparametric methods commonly suffer from the curse of dimensionality and have been mostly implemented in extreme-value studies up to three dimensions, whereas parametric models can tackle higher-dimensional settings. In this paper, we assess, through a vast and systematic simulation study, the performance of classical and recently proposed estimators in multivariate settings. In particular, we first investigate the performance of nonparametric methods and then compare them with classical parametric approaches under symmetric and asymmetric dependence structures within the commonly used logistic family. We also explore two different ways to make nonparametric estimators satisfy the necessary dependence function shape constraints, finding a general improvement in estimator performance either (i) by substituting the estimator with its greatest convex minorant, developing a computational tool to implement this method for dimensions $$D\\ge 2$$D≥2 or (ii) by projecting the estimator onto a subspace of dependence functions satisfying such constraints and taking advantage of Bernstein–Bézier polynomials. Implementing the convex minorant method leads to better estimator performance as the dimensionality increases.

  11. A comparison of dependence function estimators in multivariate extremes

    KAUST Repository

    Vettori, Sabrina

    2017-05-11

    Various nonparametric and parametric estimators of extremal dependence have been proposed in the literature. Nonparametric methods commonly suffer from the curse of dimensionality and have been mostly implemented in extreme-value studies up to three dimensions, whereas parametric models can tackle higher-dimensional settings. In this paper, we assess, through a vast and systematic simulation study, the performance of classical and recently proposed estimators in multivariate settings. In particular, we first investigate the performance of nonparametric methods and then compare them with classical parametric approaches under symmetric and asymmetric dependence structures within the commonly used logistic family. We also explore two different ways to make nonparametric estimators satisfy the necessary dependence function shape constraints, finding a general improvement in estimator performance either (i) by substituting the estimator with its greatest convex minorant, developing a computational tool to implement this method for dimensions $$D\\\\ge 2$$D≥2 or (ii) by projecting the estimator onto a subspace of dependence functions satisfying such constraints and taking advantage of Bernstein–Bézier polynomials. Implementing the convex minorant method leads to better estimator performance as the dimensionality increases.

  12. 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...

  13. Hyperbolic and semi-parametric models in finance

    Science.gov (United States)

    Bingham, N. H.; Kiesel, Rüdiger

    2001-02-01

    The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.

  14. A nonparametric mixture model for cure rate estimation.

    Science.gov (United States)

    Peng, Y; Dear, K B

    2000-03-01

    Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

  15. SHAPE FROM TEXTURE USING LOCALLY SCALED POINT PROCESSES

    Directory of Open Access Journals (Sweden)

    Eva-Maria Didden

    2015-09-01

    Full Text Available Shape from texture refers to the extraction of 3D information from 2D images with irregular texture. This paper introduces a statistical framework to learn shape from texture where convex texture elements in a 2D image are represented through a point process. In a first step, the 2D image is preprocessed to generate a probability map corresponding to an estimate of the unnormalized intensity of the latent point process underlying the texture elements. The latent point process is subsequently inferred from the probability map in a non-parametric, model free manner. Finally, the 3D information is extracted from the point pattern by applying a locally scaled point process model where the local scaling function represents the deformation caused by the projection of a 3D surface onto a 2D image.

  16. Estimation and asymptotic theory for transition probabilities in Markov Renewal Multi–state models

    NARCIS (Netherlands)

    Spitoni, C.; Verduijn, M.; Putter, H.

    2012-01-01

    In this paper we discuss estimation of transition probabilities for semi–Markov multi–state models. Non–parametric and semi–parametric estimators of the transition probabilities for a large class of models (forward going models) are proposed. Large sample theory is derived using the functional

  17. Nonparametric estimation of location and scale parameters

    KAUST Repository

    Potgieter, C.J.

    2012-12-01

    Two random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations. © 2012 Elsevier B.V. All rights reserved.

  18. Sensitivity enhancement of remotely coupled NMR detectors using wirelessly powered parametric amplification.

    Science.gov (United States)

    Qian, Chunqi; Murphy-Boesch, Joseph; Dodd, Stephen; Koretsky, Alan

    2012-09-01

    A completely wireless detection coil with an integrated parametric amplifier has been constructed to provide local amplification and transmission of MR signals. The sample coil is one element of a parametric amplifier using a zero-bias diode that mixes the weak MR signal with a strong pump signal that is obtained from an inductively coupled external loop. The NMR sample coil develops current gain via reduction in the effective coil resistance. Higher gain can be obtained by adjusting the level of the pumping power closer to the oscillation threshold, but the gain is ultimately constrained by the bandwidth requirement of MRI experiments. A feasibility study here shows that on a NaCl/D(2) O phantom, (23) Na signals with 20 dB of gain can be readily obtained with a concomitant bandwidth of 144 kHz. This gain is high enough that the integrated coil with parametric amplifier, which is coupled inductively to external loops, can provide sensitivity approaching that of direct wire connection. Copyright © 2012 Wiley Periodicals, Inc.

  19. Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

    Science.gov (United States)

    Yang, Li; Wang, Guobao; Qi, Jinyi

    2016-04-01

    Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

  20. 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.

  1. Semiparametric estimation of covariance matrices for longitudinal data.

    Science.gov (United States)

    Fan, Jianqing; Wu, Yichao

    2008-12-01

    Estimation of longitudinal data covariance structure poses significant challenges because the data are usually collected at irregular time points. A viable semiparametric model for covariance matrices was proposed in Fan, Huang and Li (2007) that allows one to estimate the variance function nonparametrically and to estimate the correlation function parametrically via aggregating information from irregular and sparse data points within each subject. However, the asymptotic properties of their quasi-maximum likelihood estimator (QMLE) of parameters in the covariance model are largely unknown. In the current work, we address this problem in the context of more general models for the conditional mean function including parametric, nonparametric, or semi-parametric. We also consider the possibility of rough mean regression function and introduce the difference-based method to reduce biases in the context of varying-coefficient partially linear mean regression models. This provides a more robust estimator of the covariance function under a wider range of situations. Under some technical conditions, consistency and asymptotic normality are obtained for the QMLE of the parameters in the correlation function. Simulation studies and a real data example are used to illustrate the proposed approach.

  2. 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.

  3. Characterization and parametric dependencies of low wavenumber pedestal turbulence in the National Spherical Torus Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D. R.; Fonck, R. J.; McKee, G. R.; Thompson, D. S. [Department of Engineering Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Bell, R. E.; Diallo, A.; Guttenfelder, W.; Kaye, S. M.; LeBlanc, B. P.; Podesta, M. [Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States)

    2013-05-15

    The spherical torus edge region is among the most challenging regimes for plasma turbulence simulations. Here, we measure the spatial and temporal properties of ion-scale turbulence in the steep gradient region of H-mode pedestals during edge localized mode-free, MHD quiescent periods in the National Spherical Torus Experiment. Poloidal correlation lengths are about 10 ρ{sub i}, and decorrelation times are about 5 a/c{sub s}. Next, we introduce a model aggregation technique to identify parametric dependencies among turbulence quantities and transport-relevant plasma parameters. The parametric dependencies show the most agreement with transport driven by trapped-electron mode, kinetic ballooning mode, and microtearing mode turbulence, and the least agreement with ion temperature gradient turbulence. In addition, the parametric dependencies are consistent with turbulence regulation by flow shear and the empirical relationship between wider pedestals and larger turbulent structures.

  4. Unified triminimal parametrizations of quark and lepton mixing matrices

    International Nuclear Information System (INIS)

    He Xiaogang; Li Shiwen; Ma Boqiang

    2009-01-01

    We present a detailed study on triminimal parametrizations of quark and lepton mixing matrices with different basis matrices. We start with a general discussion on the triminimal expansion of the mixing matrix and on possible unified quark and lepton parametrization using quark-lepton complementarity. We then consider several interesting basis matrices and compare the triminimal parametrizations with the Wolfenstein-like parametrizations. The usual Wolfenstein parametrization for quark mixing is a triminimal expansion around the unit matrix as the basis. The corresponding quark-lepton complementarity lepton mixing matrix is a triminimal expansion around the bimaximal basis. Current neutrino oscillation data show that the lepton mixing matrix is very well represented by the tribimaximal mixing. It is natural to take it as an expanding basis. The corresponding zeroth order basis for quark mixing in this case makes the triminimal expansion converge much faster than the usual Wolfenstein parametrization. The triminimal expansion based on tribimaximal mixing can be converted to the Wolfenstein-like parametrizations discussed in the literature. We thus have a unified description between different kinds of parametrizations for quark and lepton sectors: the standard parametrizations, the Wolfenstein-like parametrizations, and the triminimal parametrizations.

  5. 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.

  6. 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.

  7. Parametric variation of radiated power in Aditya Tokamak

    International Nuclear Information System (INIS)

    Tahiliani, Kumudni; Chowdhuri, M.B.; Manchanda, R.

    2017-01-01

    We report the study of parametric variation of radiated power in Aditya Tokamak for ohmic discharges. The radiated power was measured using AXUV diodes that are responsive to radiation in the range 1 eV to 4 keV and are insensitive to the neutral particles (<0.5 keV). Hence only the radiation power loss is measured and charge exchange losses are excluded. The measured radiated power was also used for the estimation of the effective ion charge, Z eff based on the scaling obtained by the regression analysis of the data from multiple Tokamaks. The estimated values were compared with the experimental Z eff values obtained from the visible continuum measurement. We also tested the scaling for modelled radiation power loss. (author)

  8. Ultrasonic defect characterization using parametric-manifold mapping

    Science.gov (United States)

    Velichko, A.; Bai, L.; Drinkwater, B. W.

    2017-06-01

    The aim of ultrasonic non-destructive evaluation includes the detection and characterization of defects, and an understanding of the nature of defects is essential for the assessment of structural integrity in safety critical systems. In general, the defect characterization challenge involves an estimation of defect parameters from measured data. In this paper, we explore the extent to which defects can be characterized by their ultrasonic scattering behaviour. Given a number of ultrasonic measurements, we show that characterization information can be extracted by projecting the measurement onto a parametric manifold in principal component space. We show that this manifold represents the entirety of the characterization information available from far-field harmonic ultrasound. We seek to understand the nature of this information and hence provide definitive statements on the defect characterization performance that is, in principle, extractable from typical measurement scenarios. In experiments, the characterization problem of surface-breaking cracks and the more general problem of elliptical voids are studied, and a good agreement is achieved between the actual parameter values and the characterization results. The nature of the parametric manifold enables us to explain and quantify why some defects are relatively easy to characterize, whereas others are inherently challenging.

  9. Estimations of On-site Directional Wave Spectra from Measured Ship Responses

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2006-01-01

    include an quivalence of energy in the governing equations and, as regards the parametric concept, a frequency dependent spreading of the waves is introduced. The paper includes an extensive analysis of full-scale measurements for which the directional wave spectra are estimated by the two ship response......In general, two main concepts can be applied to estimate the on-site directional wave spectrum on the basis of ship response measurements: 1) a parametric method which assumes the wave spectrum to be composed by parameterised wave spectra, or 2) a non-parametric method where the directional wave...

  10. 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.

  11. A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

    Science.gov (United States)

    Pan, Yang; Archer, Cristina L.

    2018-04-01

    To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

  12. 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

  13. 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

  14. Parametric study of unconstrained high-pressure torsion- Finite element analysis

    International Nuclear Information System (INIS)

    Halloumi, A; Busquet, M; Descartes, S

    2014-01-01

    The high-pressure torsion (HPT) experiments have been investigated numerically. An axisymmetric model with twist was developed with commercial finite element software (Abaqus) to study locally the specificity of the stress and strain history within the transformed layers produced during HPT processing. The material local behaviour law in the plastic domain was modelled. A parametric study highlights the role of the imposed parameters (friction coefficient at the interfaces anvil surfaces/sample, imposed pressure) on the stress/strain distribution in the sample bulk for two materials: ultra-high purity iron and steel grade R260. The present modelling provides a tool to investigate and to analyse the effect of pressure and friction on the local stress and strain history during the HPT process and to couple with experimental results

  15. Composite Estimation for Single-Index Models with Responses Subject to Detection Limits

    KAUST Repository

    Tang, Yanlin; Wang, Huixia Judy; Liang, Hua

    2017-01-01

    We propose a semiparametric estimator for single-index models with censored responses due to detection limits. In the presence of left censoring, the mean function cannot be identified without any parametric distributional assumptions, but the quantile function is still identifiable at upper quantile levels. To avoid parametric distributional assumption, we propose to fit censored quantile regression and combine information across quantile levels to estimate the unknown smooth link function and the index parameter. Under some regularity conditions, we show that the estimated link function achieves the non-parametric optimal convergence rate, and the estimated index parameter is asymptotically normal. The simulation study shows that the proposed estimator is competitive with the omniscient least squares estimator based on the latent uncensored responses for data with normal errors but much more efficient for heavy-tailed data under light and moderate censoring. The practical value of the proposed method is demonstrated through the analysis of a human immunodeficiency virus antibody data set.

  16. Composite Estimation for Single-Index Models with Responses Subject to Detection Limits

    KAUST Repository

    Tang, Yanlin

    2017-11-03

    We propose a semiparametric estimator for single-index models with censored responses due to detection limits. In the presence of left censoring, the mean function cannot be identified without any parametric distributional assumptions, but the quantile function is still identifiable at upper quantile levels. To avoid parametric distributional assumption, we propose to fit censored quantile regression and combine information across quantile levels to estimate the unknown smooth link function and the index parameter. Under some regularity conditions, we show that the estimated link function achieves the non-parametric optimal convergence rate, and the estimated index parameter is asymptotically normal. The simulation study shows that the proposed estimator is competitive with the omniscient least squares estimator based on the latent uncensored responses for data with normal errors but much more efficient for heavy-tailed data under light and moderate censoring. The practical value of the proposed method is demonstrated through the analysis of a human immunodeficiency virus antibody data set.

  17. Parametric curve evaluation of a phototransistor used as detector in stereotactic radiosurgery X-ray beam

    International Nuclear Information System (INIS)

    Lima, Daniela Pontes A.; Santos, Luiz Antonio P.; Santos, Walter M.; Silva Junior, Eronides F. da

    2005-01-01

    Phototransistors have been widely used as detectors for low energy X-rays. However, when they are used in high energy X-rays fields like those generated from linear accelerators (linac), there is a certain loss of sensibility to the ionizing radiation. This damage is cumulative and irreversible. Thus, a correction factor must be applied to its response, which is proportional to the integrated dose. However, it is possible to estimate the correction factor by using the V x I parametric curve of the device. The aim of this work was to develop studies to evaluate and correlate the parametric response curve of a phototransistor with its loss of sensibility after irradiation. An Agilent 4155C semiconductor parameter analyzer was used to trace the parametric curve. X-rays were generated by a 14 MV Primus-Siemens linear accelerator. The results demonstrated that there is a correlation between the integrated dose applied to the phototransistor and the parametric response of the device. Studies are under way to determine how such behavior can provide information for the dosimetric planning in stereotactic radiosurgery. (author)

  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. Efficient estimation of an additive quantile regression model

    NARCIS (Netherlands)

    Cheng, Y.; de Gooijer, J.G.; Zerom, D.

    2011-01-01

    In this paper, two non-parametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a more viable alternative to existing kernel-based approaches. The second estimator

  20. 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

  1. Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

    KAUST Repository

    Kouramas, K.I.

    2011-08-01

    This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.

  2. Two-step estimation procedures for inhomogeneous shot-noise Cox processes

    DEFF Research Database (Denmark)

    Prokesová, Michaela; Dvorák, Jirí; Jensen, Eva B. Vedel

    In the present paper we develop several two-step estimation procedures for inhomogeneous shot-noise Cox processes. The intensity function is parametrized by the inhomogeneity parameters while the pair-correlation function is parametrized by the interaction parameters. The suggested procedures...

  3. 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).

  4. Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

    Science.gov (United States)

    Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

    2016-06-01

    Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

  5. 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

  6. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

    2017-05-01

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

  7. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong

    2017-01-01

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other

  8. 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.

  9. A local cubic smoothing in an adaptation mode

    International Nuclear Information System (INIS)

    Dikoussar, N.D.

    2001-01-01

    A new approach to a local curve approximation and the smoothing is proposed. The relation between curve points is defined using a special cross-ratio weight functions. The coordinates of three curve points are used as parameters for both the weight functions and the tree-point cubic model (TPS). A very simple in computing and stable to random errors cubic smoother in an adaptation mode (LOCUS) is constructed. The free parameter of TPS is estimated independently of the fixed parameters by recursion with the effective error suppression and can be controlled by the cross-ratio parameters. Efficiency and the noise stability of the algorithm are confirmed by examples and by comparison with other known non-parametric smoothers

  10. Prescription duration and treatment episodes in oral glucocorticoid users: application of the parametric waiting time distribution

    DEFF Research Database (Denmark)

    Laugesen, Kristina; Støvring, Henrik; Hallas, Jesper

    2017-01-01

    for oral glucocorticoids and to describe continuous treatment episodes using the parametric waiting time distribution. Methods: We used Danish nationwide registries to identify all prescriptions for oral glucocorticoids during 1996-2014. We applied the parametric waiting time distribution to estimate...... duration of individual prescriptions each year by estimating the 80th, 90th, 95th and 99th percentiles for the interarrival distribution. These corresponded to the time since last prescription during which 80%, 90%, 95% and 99% of users presented a new prescription for redemption. We used the Kaplan...... of the interarrival distribution to apply as prescription duration has an impact on the level of misclassification. Use of the 80th percentile provides a measure of drug exposure that is specific, while the 99th percentile provides a sensitive measure....

  11. 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

  12. 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.

  13. Toward an Empirically-based Parametric Explosion Spectral Model

    Science.gov (United States)

    Ford, S. R.; Walter, W. R.; Ruppert, S.; Matzel, E.; Hauk, T. F.; Gok, R.

    2010-12-01

    Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases (Pn, Pg, and Lg) 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. These parameters are then correlated with near-source geology and containment conditions. There is a correlation of high gas-porosity (low strength) with increased spectral slope. However, there are trade-offs between the slope and corner-frequency, which we try to independently constrain using Mueller-Murphy relations and coda-ratio techniques. The relationship between the parametric equation and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source, and aid in the prediction of observed local and regional distance seismic amplitudes for event identification and yield determination in regions with incomplete or no prior history of underground nuclear testing.

  14. The Knowledge Base Interface for Parametric Grid Information

    International Nuclear Information System (INIS)

    Hipp, James R.; Simons, Randall W.; Young, Chris J.

    1999-01-01

    The parametric grid capability of the Knowledge Base (KBase) provides an efficient robust way to store and access interpolatable information that is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use an approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation. The method involves three basic steps: data preparation, data storage, and data access. In past presentations we have discussed in detail the first step. In this paper we focus on the latter two, describing in detail the type of information which must be stored and the interface used to retrieve parametric grid data from the Knowledge Base. Once data have been properly prepared, the information (tessellation and associated value surfaces) needed to support the interface functionality, can be entered into the KBase. The primary types of parametric grid data that must be stored include (1) generic header information; (2) base model, station, and phase names and associated ID's used to construct surface identifiers; (3) surface accounting information; (4) tessellation accounting information; (5) mesh data for each tessellation; (6) correction data defined for each surface at each node of the surfaces owning tessellation (7) mesh refinement calculation set-up and flag information; and (8) kriging calculation set-up and flag information. The eight data components not only represent the results of the data preparation process but also include all required input information for several population tools that would enable the complete regeneration of the data results if that should be necessary

  15. Theoretical and algorithmic advances in multi-parametric programming and control

    KAUST Repository

    Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar

    2012-01-01

    This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

  16. Theoretical and algorithmic advances in multi-parametric programming and control

    KAUST Repository

    Pistikopoulos, Efstratios N.

    2012-04-21

    This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

  17. 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.

  18. Estimating the period of a cyclic non-homogeneous Poisson process

    NARCIS (Netherlands)

    Belitser, E.; Andrade Serra, De P.J.; Zanten, van J.H.

    2013-01-01

    Motivated by applications of Poisson processes for modelling periodic time-varying phenomena, we study a semi-parametric estimator of the period of cyclic intensity function of a non-homogeneous Poisson process. There are no parametric assumptions on the intensity function which is treated as an

  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. 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...

  1. 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.

  2. 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...

  3. 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...

  4. 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

  5. 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.

  6. Latest astronomical constraints on some non-linear parametric dark energy models

    Science.gov (United States)

    Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos

    2018-04-01

    We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.

  7. 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

  8. Modeling river discharge and sediment transport in the Wax Lake-Atchafalaya basin with remote sensing parametrization.

    Science.gov (United States)

    Simard, M.; Liu, K.; Denbina, M. W.; Jensen, D.; Rodriguez, E.; Liao, T. H.; Christensen, A.; Jones, C. E.; Twilley, R.; Lamb, M. P.; Thomas, N. A.

    2017-12-01

    Our goal is to estimate the fluxes of water and sediments throughout the Wax Lake-Atchafalaya basin. This was achieved by parametrization of a set of 1D (HEC-RAS) and 2D (DELFT3D) hydrology models with state of the art remote sensing measurements of water surface elevation, water surface slope and total suspended sediment (TSS) concentrations. The model implementations are spatially explicit, simulating river currents, lateral flows to distributaries and marshes, and spatial variations of sediment concentrations. Three remote sensing instruments were flown simultaneously to collect data over the Wax Lake-Atchafalaya basin, and along with in situ field data. A Riegl Lidar was used to measure water surface elevation and slope, while the UAVSAR L-band radar collected data in repeat-pass interferometric mode to measure water level change within adjacent marshes and islands. These data were collected several times as the tide rose and fell. AVRIS-NG instruments measured water surface reflectance spectra, used to estimate TSS. Bathymetry was obtained from sonar transects and water level changes were recorded by 19 water level pressure transducers. We used several Acoustic Doppler Current Profiler (ADCP) transects to estimate river discharge. The remotely sensed measurements of water surface slope were small ( 1cm/km) and varied slightly along the channel, especially at the confluence with bayous and the intra-coastal waterway. The slope also underwent significant changes during the tidal cycle. Lateral fluxes to island marshes were mainly observed by UAVSAR close to the distributaries. The extensive remote sensing measurements showed significant disparity with the hydrology model outputs. Observed variations in water surface slopes were unmatched by the model and tidal wave propagation was much faster than gauge measurements. The slope variations were compensated for in the models by tuning local lateral fluxes, bathymetry and riverbed friction. Overall, the simpler 1D

  9. Nonparametric autocovariance estimation from censored time series by Gaussian imputation.

    Science.gov (United States)

    Park, Jung Wook; Genton, Marc G; Ghosh, Sujit K

    2009-02-01

    One of the most frequently used methods to model the autocovariance function of a second-order stationary time series is to use the parametric framework of autoregressive and moving average models developed by Box and Jenkins. However, such parametric models, though very flexible, may not always be adequate to model autocovariance functions with sharp changes. Furthermore, if the data do not follow the parametric model and are censored at a certain value, the estimation results may not be reliable. We develop a Gaussian imputation method to estimate an autocovariance structure via nonparametric estimation of the autocovariance function in order to address both censoring and incorrect model specification. We demonstrate the effectiveness of the technique in terms of bias and efficiency with simulations under various rates of censoring and underlying models. We describe its application to a time series of silicon concentrations in the Arctic.

  10. 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.

  11. 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

  12. 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

  13. Nonscaling parametrization of hadronic spectra and dual parton model

    International Nuclear Information System (INIS)

    Gaponenko, O.N.

    2001-01-01

    Using the popular Wdowczyk-Wolfendale parametrization (WW-parametrization) as an example one studies restrictions imposed by a dual parton model for different nonscaling parametrizations of the pulsed hadron spectra in soft hadron-hadron and hadron-nuclear interactions. One derived a new parametrization free from basic drawback of the WW-formulae. In the central range the determined parametrization show agreement with the Wdowczyk-Wolfendale formula, but in contrast to the last-named one it does not result in contradiction with the experiment due to fast reduction of inelastic factor reduction with energy increase [ru

  14. 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...

  15. Functional brain mapping using H{sub 2}{sup 15}O positron emission tomography (I): statistical parametric mapping method

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Dong Soo; Lee, Jae Sung; Kim, Kyeong Min; Chung, June Key; Lee, Myung Chul [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of)

    1998-08-01

    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{sub 2}{sup 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.

  16. Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

    KAUST Repository

    Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

    2011-01-01

    This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

  17. 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

  18. 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...

  19. Comparative Study of Parametric and Non-parametric Approaches in Fault Detection and Isolation

    DEFF Research Database (Denmark)

    Katebi, S.D.; Blanke, M.; Katebi, M.R.

    This report describes a comparative study between two approaches to fault detection and isolation in dynamic systems. The first approach uses a parametric model of the system. The main components of such techniques are residual and signature generation for processing and analyzing. The second...... approach is non-parametric in the sense that the signature analysis is only dependent on the frequency or time domain information extracted directly from the input-output signals. Based on these approaches, two different fault monitoring schemes are developed where the feature extraction and fault decision...

  20. Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

    Science.gov (United States)

    Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

    2015-05-01

    Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Impulse response identification with deterministic inputs using non-parametric methods

    International Nuclear Information System (INIS)

    Bhargava, U.K.; Kashyap, R.L.; Goodman, D.M.

    1985-01-01

    This paper addresses the problem of impulse response identification using non-parametric methods. Although the techniques developed herein apply to the truncated, untruncated, and the circulant models, we focus on the truncated model which is useful in certain applications. Two methods of impulse response identification will be presented. The first is based on the minimization of the C/sub L/ Statistic, which is an estimate of the mean-square prediction error; the second is a Bayesian approach. For both of these methods, we consider the effects of using both the identity matrix and the Laplacian matrix as weights on the energy in the impulse response. In addition, we present a method for estimating the effective length of the impulse response. Estimating the length is particularly important in the truncated case. Finally, we develop a method for estimating the noise variance at the output. Often, prior information on the noise variance is not available, and a good estimate is crucial to the success of estimating the impulse response with a nonparametric technique

  2. Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

    Science.gov (United States)

    Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

    2017-07-01

    A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

  3. 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.

  4. 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.

  5. 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

  6. 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...

  7. 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

  8. 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

  9. 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...

  10. 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.

  11. 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

  12. Parametric manipulation of the conflict signal and control-state adaptation.

    Science.gov (United States)

    Forster, Sarah E; Carter, Cameron S; Cohen, Jonathan D; Cho, Raymond Y

    2011-04-01

    Mechanisms by which the brain monitors and modulates performance are an important focus of recent research. The conflict-monitoring hypothesis posits that the ACC detects conflict between competing response pathways which, in turn, signals for enhanced control. The N2, an ERP component that has been localized to ACC, has been observed after high conflict stimuli. As a candidate index of the conflict signal, the N2 would be expected to be sensitive to the degree of response conflict present, a factor that depends on both the features of external stimuli and the internal control state. In the present study, we sought to explore the relationship between N2 amplitude and these variables through use of a modified Eriksen flankers task in which target-distracter compatibility was parametrically varied. We hypothesized that greater target-distracter incompatibility would result in higher levels of response conflict, as indexed by both behavior and the N2 component. Consistent with this prediction, there were parametric degradations in behavioral performance and increases in N2 amplitudes with increasing incompatibility. Further, increasingly incompatible stimuli led to the predicted parametric increases in control on subsequent incompatible trials as evidenced by enhanced performance and reduced N2 amplitudes. These findings suggest that the N2 component and associated behavioral performance are finely sensitive to the degree of response conflict present and to the control adjustments that result from modulations in conflict.

  13. 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.

  14. Current-driven parametric resonance in magnetic multilayers

    International Nuclear Information System (INIS)

    Wang, C; Seinige, H; Tsoi, M

    2013-01-01

    Current-induced parametric excitations were observed in point-contact spin-valve nanodevices. Point contacts were used to inject high densities of direct and microwave currents into spin valves, thus producing oscillating spin-transfer and Oersted-field torques on magnetic moments. The resulting magnetodynamics were observed electrically by measuring rectified voltage signals across the contact. In addition to the spin-torque-driven ferromagnetic resonance we observe doubled-frequency signals which correspond to the parametric excitation of magnetic moments. Numerical simulations suggest that while both spin-transfer torque and ac Oersted field contribute to the parametrically excited dynamics, the ac spin torque dominates, and dc spin torque can switch it on and off. The dc bias dependence of the parametric resonance signal enabled the mapping of instability regions characterizing the nonlinearity of the oscillation. (paper)

  15. Autonomous Supervision and Control of Parametric Roll Resonance

    DEFF Research Database (Denmark)

    Galeazzi, Roberto

    therefore two objectives. The first is to develop methods for detection of the inception of parametric roll resonance. The second is to develop control strategies to stabilize the motion after parametric roll has started. Stabilisation of parametric roll resonance points to two possible courses of action...... strategies are then combined to stabilise parametric roll resonance within few roll cycles. Limitations on the maximum stabilisable roll angle are analysed and linked to the ii slew rate saturation and hydrodynamic stall characteristics of the fin stabilisers. The study on maximum stabilisable roll angle...... leads to the requirements for early detection. Two novel detectors are proposed, which work within a shorttime prediction horizon, and issue early warnings of parametric roll inception within few roll cycles from its onset. The main idea behind these detection schemes is that of exploiting the link...

  16. 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.

  17. 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

  18. A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

    Science.gov (United States)

    Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

    2017-11-01

    -enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset. © 2017 American Association of Physicists in Medicine.

  19. 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)

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. Parametric instabilities of parallel propagating incoherent Alfven waves in a finite ion beta plasma

    International Nuclear Information System (INIS)

    Nariyuki, Y.; Hada, T.; Tsubouchi, K.

    2007-01-01

    Large amplitude, low-frequency Alfven waves constitute one of the most essential elements of magnetohydrodynamic (MHD) turbulence in the fast solar wind. Due to small collisionless dissipation rates, the waves can propagate long distances and efficiently convey such macroscopic quantities as momentum, energy, and helicity. Since loading of such quantities is completed when the waves damp away, it is important to examine how the waves can dissipate in the solar wind. Among various possible dissipation processes of the Alfven waves, parametric instabilities have been believed to be important. In this paper, we numerically discuss the parametric instabilities of coherent/incoherent Alfven waves in a finite ion beta plasma using a one-dimensional hybrid (superparticle ions plus an electron massless fluid) simulation, in order to explain local production of sunward propagating Alfven waves, as suggested by Helios/Ulysses observation results. Parameter studies clarify the dependence of parametric instabilities of coherent/incoherent Alfven waves on the ion and electron beta ratio. Parametric instabilities of coherent Alfven waves in a finite ion beta plasma are vastly different from those in the cold ions (i.e., MHD and/or Hall-MHD systems), even if the collisionless damping of the Alfven waves are neglected. Further, ''nonlinearly driven'' modulational instability is important for the dissipation of incoherent Alfven waves in a finite ion beta plasma regardless of their polarization, since the ion kinetic effects let both the right-hand and left-hand polarized waves become unstable to the modulational instability. The present results suggest that, although the antisunward propagating dispersive Alfven waves are efficiently dissipated through the parametric instabilities in a finite ion beta plasma, these instabilities hardly produce the sunward propagating waves

  5. 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.

  6. Fault detection and isolation in systems with parametric faults

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1999-01-01

    The problem of fault detection and isolation of parametric faults is considered in this paper. A fault detection problem based on parametric faults are associated with internal parameter variations in the dynamical system. A fault detection and isolation method for parametric faults is formulated...

  7. 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

  8. Direction of arrival estimation based on information geometry

    NARCIS (Netherlands)

    Coutiño Minguez, M.A.; Pribic, R; Leus, G.J.T.; Dong, Min; Zheng, Thomas Fang

    2016-01-01

    In this paper, a new direction of arrival (DOA) estimation approach is devised using concepts from information geometry (IG). The proposed method uses geodesic distances in the statistical manifold of probability distributions parametrized by their covariance matrix to estimate the direction of

  9. 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.

  10. 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.

  11. 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)

  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. Pump to signal noise transfer in parametric fiber amplifiers

    DEFF Research Database (Denmark)

    Lund-Hansen, Toke; Rottwitt, Karsten; Peucheret, Christophe

    2010-01-01

    Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal.......Fiber optic parametric amplifiers have been suggested due to their potential low spontaneous emission. However, by nature the parametric amplifier only work in a forward pumped configuration, which result in transfer of relative intensity noise in the pump to the signal....

  14. The finite sample performance of estimators for mediation analysis under sequential conditional independence

    DEFF Research Database (Denmark)

    Huber, Martin; Lechner, Michael; Mellace, Giovanni

    Using a comprehensive simulation study based on empirical data, this paper investigates the finite sample properties of different classes of parametric and semi-parametric estimators of (natural) direct and indirect causal effects used in mediation analysis under sequential conditional independence...

  15. 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)

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Parametric Instability in Advanced Laser Interferometer Gravitational Wave Detectors

    International Nuclear Information System (INIS)

    Ju, L; Grass, S; Zhao, C; Degallaix, J; Blair, D G

    2006-01-01

    High frequency parametric instabilities in optical cavities are radiation pressure induced interactions between test mass mechanical modes and cavity optical modes. The parametric gain depends on the cavity power and the quality factor of the test mass internal modes (usually in ultrasonic frequency range), as well as the overlap integral for the mechanical and optical modes. In advanced laser interferometers which require high optical power and very low acoustic loss test masses, parametric instabilities could prevent interferometer operation if not suppressed. Here we review the problem of parametric instabilities in advanced detector configurations for different combinations of sapphire and fused silica test masses, and compare three methods for control or suppression of parametric instabilities-thermal tuning, surface damping and active feedback

  1. A new approach for product cost estimation using data envelopment analysis

    Directory of Open Access Journals (Sweden)

    Adil Salam

    2012-10-01

    Full Text Available Cost estimation of new products has always been difficult as only few design, manufacturing and operational features will be known. In these situations, parametric or non-parametric methods are commonly used to estimate the cost of a product given the corresponding cost drivers. The parametric models use priori determined cost function where the parameters of the function are evaluated from historical data. Non-parametric methods, on the other hand, attempt to fit curves to the historic data without predetermined function. In both methods, it is assumed that the historic data used in the analysis is a true representation of the relation between the cost drivers and the corresponding costs. However, because of efficiency variations of the manufacturers and suppliers, changes in supplier selections, market fluctuations, and several other reasons, certain costs in the historic data may be too high whereas other costs may represent better deals for their corresponding cost drivers. Thus, it may be important to rank the historic data and identify benchmarks and estimate the target costs of the product based on these benchmarks. In this paper, a novel adaptation of cost drivers and cost data is introduced in order to use data envelopment analysis for the purpose of ranking cost data and identify benchmarks, and then estimate the target costs of a new product based on these benchmarks. An illustrative case study has been presented for the cost estimation of landing gears of an aircraft manufactured by an aerospace company located in Montreal, CANADA.

  2. Semi-Parametric Maximum Likelihood Method for Interaction in Case-Mother Control-Mother Designs: Package SPmlficmcm

    Directory of Open Access Journals (Sweden)

    Moliere Nguile-Makao

    2015-12-01

    Full Text Available The analysis of interaction effects involving genetic variants and environmental exposures on the risk of adverse obstetric and early-life outcomes is generally performed using standard logistic regression in the case-mother and control-mother design. However such an analysis is inefficient because it does not take into account the natural family-based constraints present in the parent-child relationship. Recently, a new approach based on semi-parametric maximum likelihood estimation was proposed. The advantage of this approach is that it takes into account the parental relationship between the mother and her child in estimation. But a package implementing this method has not been widely available. In this paper, we present SPmlficmcm, an R package implementing this new method and we propose an extension of the method to handle missing offspring genotype data by maximum likelihood estimation. Our choice to treat missing data of the offspring genotype was motivated by the fact that in genetic association studies where the genetic data of mother and child are available, there are usually more missing data on the genotype of the offspring than that of the mother. The package builds a non-linear system from the data and solves and computes the estimates from the gradient and the Hessian matrix of the log profile semi-parametric likelihood function. Finally, we analyze a simulated dataset to show the usefulness of the package.

  3. Advectional enhancement of eddy diffusivity under parametric disorder

    International Nuclear Information System (INIS)

    Goldobin, Denis S

    2010-01-01

    Frozen parametric disorder can lead to the appearance of sets of localized convective currents in an otherwise stable (quiescent) fluid layer heated from below. These currents significantly influence the transport of an admixture (or any other passive scalar) along the layer. When the molecular diffusivity of the admixture is small in comparison to the thermal one, which is quite typical in nature, disorder can enhance the effective (eddy) diffusivity by several orders of magnitude in comparison to the molecular diffusivity. In this paper, we study the effect of an imposed longitudinal advection on the delocalization of convective currents, both numerically and analytically, and report a subsequent drastic boost of the effective diffusivity for weak advection.

  4. 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.

  5. 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 ...

  6. Rate-dependent extensions of the parametric magneto-dynamic model with magnetic hysteresis

    Directory of Open Access Journals (Sweden)

    S. Steentjes

    2017-05-01

    Full Text Available This paper extends the parametric magneto-dynamic model of soft magnetic steel sheets to account for the phase shift between local magnetic flux density and magnetic field strength. This phase shift originates from the damped motion of domain walls and is strongly dependent on the microstructure of the material. In this regard, two different approaches to include the rate-dependent effects are investigated: a purely phenomenological, mathematical approach and a physical-based one.

  7. 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...

  8. 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.

  9. A simple parametric model observer for quality assurance in computer tomography

    Science.gov (United States)

    Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.

    2018-04-01

    Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.

  10. 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.

  11. 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.

  12. 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.

  13. 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 ...

  14. 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

  15. X-1 to X-Wings: Developing a Parametric Cost Model

    Science.gov (United States)

    Sterk, Steve; McAtee, Aaron

    2015-01-01

    In todays cost-constrained environment, NASA needs an X-Plane database and parametric cost model that can quickly provide rough order of magnitude predictions of cost from initial concept to first fight of potential X-Plane aircraft. This paper takes a look at the steps taken in developing such a model and reports the results. The challenges encountered in the collection of historical data and recommendations for future database management are discussed. A step-by-step discussion of the development of Cost Estimating Relationships (CERs) is then covered.

  16. 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.

  17. 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.

  18. Set-membership estimations for the evolution of infectious diseases in heterogeneous populations.

    Science.gov (United States)

    Tsachev, Tsvetomir; Veliov, Vladimir M; Widder, Andreas

    2017-04-01

    The paper presents an approach for set-membership estimation of the state of a heterogeneous population in which an infectious disease is spreading. The population state may consist of susceptible, infected, recovered, etc. groups, where the individuals are heterogeneous with respect to traits, relevant to the particular disease. Set-membership estimations in this context are reasonable, since only vague information about the distribution of the population along the space of heterogeneity is available in practice. The presented approach comprises adapted versions of methods which are known in estimation and control theory, and involve solving parametrized families of optimization problems. Since the models of disease spreading in heterogeneous populations involve distributed systems (with non-local dynamics and endogenous boundary conditions), these problems are non-standard. The paper develops the needed theoretical instruments and a solution scheme. SI and SIR models of epidemic diseases are considered as case studies and the results reveal qualitative properties that may be of interest.

  19. A Strategy for a Parametric Flood Insurance Using Proxies

    Science.gov (United States)

    Haraguchi, M.; Lall, U.

    2017-12-01

    Traditionally, the design of flood control infrastructure and flood plain zoning require the estimation of return periods, which have been calculated by river hydraulic models with rainfall-runoff models. However, this multi-step modeling process leads to significant uncertainty to assess inundation. In addition, land use change and changing climate alter the potential losses, as well as make the modeling results obsolete. For these reasons, there is a strong need to create parametric indexes for the financial risk transfer for large flood events, to enable rapid response and recovery. Hence, this study examines the possibility of developing a parametric flood index at the national or regional level in Asia, which can be quickly mobilized after catastrophic floods. Specifically, we compare a single trigger based on rainfall index with multiple triggers using rainfall and streamflow indices by conducting case studies in Bangladesh and Thailand. The proposed methodology is 1) selecting suitable indices of rainfall and streamflow (if available), 2) identifying trigger levels for specified return periods for losses using stepwise and logistic regressions, 3) measuring the performance of indices, and 4) deriving return periods of selected windows and trigger levels. Based on the methodology, actual trigger levels were identified for Bangladesh and Thailand. Models based on multiple triggers reduced basis risks, an inherent problem in an index insurance. The proposed parametric flood index can be applied to countries with similar geographic and meteorological characteristics, and serve as a promising method for ex-ante risk financing for developing countries. This work is intended to be a preliminary work supporting future work on pricing risk transfer mechanisms in ex-ante risk finance.

  20. SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

    Science.gov (United States)

    Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

    2007-05-01

    (R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

  1. Fundamental Frequency Estimation of the Speech Signal Compressed by MP3 Algorithm Using PCC Interpolation

    Directory of Open Access Journals (Sweden)

    MILIVOJEVIC, Z. N.

    2010-02-01

    Full Text Available In this paper the fundamental frequency estimation results of the MP3 modeled speech signal are analyzed. The estimation of the fundamental frequency was performed by the Picking-Peaks algorithm with the implemented Parametric Cubic Convolution (PCC interpolation. The efficiency of PCC was tested for Catmull-Rom, Greville and Greville two-parametric kernel. Depending on MSE, a window that gives optimal results was chosen.

  2. Two-parametric model of electron beam in computational dosimetry for radiation processing

    International Nuclear Information System (INIS)

    Lazurik, V.M.; Lazurik, V.T.; Popov, G.; Zimek, Z.

    2016-01-01

    Computer simulation of irradiation process of various materials with electron beam (EB) can be applied to correct and control the performances of radiation processing installations. Electron beam energy measurements methods are described in the international standards. The obtained results of measurements can be extended by implementation computational dosimetry. Authors have developed the computational method for determination of EB energy on the base of two-parametric fitting of semi-empirical model for the depth dose distribution initiated by mono-energetic electron beam. The analysis of number experiments show that described method can effectively consider random displacements arising from the use of aluminum wedge with a continuous strip of dosimetric film and minimize the magnitude uncertainty value of the electron energy evaluation, calculated from the experimental data. Two-parametric fitting method is proposed for determination of the electron beam model parameters. These model parameters are as follow: E 0 – energy mono-energetic and mono-directional electron source, X 0 – the thickness of the aluminum layer, located in front of irradiated object. That allows obtain baseline data related to the characteristic of the electron beam, which can be later on applied for computer modeling of the irradiation process. Model parameters which are defined in the international standards (like E p – the most probably energy and R p – practical range) can be linked with characteristics of two-parametric model (E 0 , X 0 ), which allows to simulate the electron irradiation process. The obtained data from semi-empirical model were checked together with the set of experimental results. The proposed two-parametric model for electron beam energy evaluation and estimation of accuracy for computational dosimetry methods on the base of developed model are discussed. - Highlights: • Experimental and computational methods of electron energy evaluation. • Development

  3. Two-parametric PT-symmetric quartic family

    International Nuclear Information System (INIS)

    Eremenko, Alexandre; Gabrielov, Andrei

    2012-01-01

    We describe a parametrization of the real spectral locus of the two-parametric family of PT-symmetric quartic oscillators. For this family, we find a parameter region where all eigenvalues are real, extending the results of Dorey et al (2007 J. Phys. A: Math Theor. 40 R205–83) and Shin (2005 J. Phys. A: Math. Gen. 38 6147–66; 2002 Commun. Math. Phys. 229 543–64). (paper)

  4. Efficient, Differentially Private Point Estimators

    OpenAIRE

    Smith, Adam

    2008-01-01

    Differential privacy is a recent notion of privacy for statistical databases that provides rigorous, meaningful confidentiality guarantees, even in the presence of an attacker with access to arbitrary side information. We show that for a large class of parametric probability models, one can construct a differentially private estimator whose distribution converges to that of the maximum likelihood estimator. In particular, it is efficient and asymptotically unbiased. This result provides (furt...

  5. A nonparametric approach to calculate critical micelle concentrations: the local polynomial regression method

    Energy Technology Data Exchange (ETDEWEB)

    Lopez Fontan, J.L.; Costa, J.; Ruso, J.M.; Prieto, G. [Dept. of Applied Physics, Univ. of Santiago de Compostela, Santiago de Compostela (Spain); Sarmiento, F. [Dept. of Mathematics, Faculty of Informatics, Univ. of A Coruna, A Coruna (Spain)

    2004-02-01

    The application of a statistical method, the local polynomial regression method, (LPRM), based on a nonparametric estimation of the regression function to determine the critical micelle concentration (cmc) is presented. The method is extremely flexible because it does not impose any parametric model on the subjacent structure of the data but rather allows the data to speak for themselves. Good concordance of cmc values with those obtained by other methods was found for systems in which the variation of a measured physical property with concentration showed an abrupt change. When this variation was slow, discrepancies between the values obtained by LPRM and others methods were found. (orig.)

  6. Economic policy optimization based on both one stochastic model and the parametric control theory

    Science.gov (United States)

    Ashimov, Abdykappar; Borovskiy, Yuriy; Onalbekov, Mukhit

    2016-06-01

    A nonlinear dynamic stochastic general equilibrium model with financial frictions is developed to describe two interacting national economies in the environment of the rest of the world. Parameters of nonlinear model are estimated based on its log-linearization by the Bayesian approach. The nonlinear model is verified by retroprognosis, estimation of stability indicators of mappings specified by the model, and estimation the degree of coincidence for results of internal and external shocks' effects on macroeconomic indicators on the basis of the estimated nonlinear model and its log-linearization. On the base of the nonlinear model, the parametric control problems of economic growth and volatility of macroeconomic indicators of Kazakhstan are formulated and solved for two exchange rate regimes (free floating and managed floating exchange rates)

  7. Parametric methods of describing and extrapolating the characteristics of long-term strength of refractory materials

    International Nuclear Information System (INIS)

    Tsvilyuk, I.S.; Avramenko, D.S.

    1986-01-01

    This paper carries out the comparative analysis of the suitability of parametric methods for describing and extrapolating the results of longterm tests on refractory materials. Diagrams are presented of the longterm strength of niobium based alloys tested in a vacuum of 1.3 X 10 -3 Pa. The predicted values and variance of the estimate of endurance of refractory alloys are presented by parametric dependences. The longterm strength characteristics can be described most adequately by the Manson-Sakkop and Sherby-Dorn methods. Several methods must be used to ensure the reliable extrapolation of the longterm strength characteristics to the time period an order of magnitude longer than the experimental data. The most suitable method cannot always be selected on the basis of the correlation ratio

  8. 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.

  9. The parametrized simulation of electromagnetic showers

    International Nuclear Information System (INIS)

    Peters, S.

    1992-09-01

    The simulation of electromagnetic showers in calorimeters by detailed tracking of all secondary particles is extremely computer time consuming. Without loosing considerably in precision, the use of parametrizations for global shower properties may reduce the computing time by factors of 10 1 to 10 4 , depending on the energy, the degree of parametrization, and the complexity in the material description and the cut off energies in the detailed simulation. To arrive at a high degree of universality, parametrizations of individual electromagnetic showers in homogeneous media are developed, taking the dependence of the shower development on the material into account. In sampling calorimeters, the inhomogeneous material distribution leads to additional effects which can be taken into account by geometry dependent terms in the parametrization of the longitudinal and radial energy density distributions. Comparisons with detailed simulations of homogeneous and sampling calorimeters show very good agreement in the fluctuations, correlations, and signal averages of spatial energy distributions. Verifications of the algorithms for the simulation of the H1 detector are performed using calorimeter test data for different moduls of the H1 liquid argon calorimeter. Special attention has been paid to electron pion separation, which is of great importance for physics analysis. (orig.) [de

  10. Maximum a posteriori reconstruction of the Patlak parametric image from sinograms in dynamic PET

    International Nuclear Information System (INIS)

    Wang Guobao; Fu Lin; Qi Jinyi

    2008-01-01

    Parametric imaging using the Patlak graphical method has been widely used to analyze dynamic PET data. Conventionally a Patlak parametric image is generated by reconstructing a sequence of dynamic images first and then performing Patlak graphical analysis on the time-activity curves pixel-by-pixel. However, because it is rather difficult to model the noise distribution in reconstructed images, the spatially variant noise correlation is simply ignored in the Patlak analysis, which leads to sub-optimal results. In this paper we present a Bayesian method for reconstructing Patlak parametric images directly from raw sinogram data by incorporating the Patlak plot model into the image reconstruction procedure. A preconditioned conjugate gradient algorithm is used to find the maximum a posteriori solution. The proposed direct method is statistically more efficient than the conventional indirect approach because the Poisson noise distribution in PET data can be accurately modeled in the direct reconstruction. The computation cost of the direct method is similar to reconstruction time of two dynamic frames. Therefore, when more than two dynamic frames are used in the Patlak analysis, the direct method is faster than the conventional indirect approach. We conduct computer simulations to validate the proposed direct method. Comparisons with the conventional indirect approach show that the proposed method results in a more accurate estimate of the parametric image. The proposed method has been applied to dynamic fully 3D PET data from a microPET scanner

  11. 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

  12. 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.

  13. GHz-rate optical parametric amplifier in hydrogenated amorphous silicon

    International Nuclear Information System (INIS)

    Wang, Ke-Yao; Foster, Amy C

    2015-01-01

    We demonstrate optical parametric amplification operating at GHz-rates at telecommunications wavelengths using a hydrogenated amorphous silicon waveguide through the nonlinear optical process of four-wave mixing. We investigate how the parametric amplification scales with repetition rate. The ability to achieve amplification at GHz-repetition rates shows hydrogenated amorphous silicon’s potential for telecommunication applications and a GHz-rate optical parametric oscillator. (paper)

  14. 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...

  15. MTL-Model Checking of One-Clock Parametric Timed Automata is Undecidable

    Directory of Open Access Journals (Sweden)

    Karin Quaas

    2014-03-01

    Full Text Available Parametric timed automata extend timed automata (Alur and Dill, 1991 in that they allow the specification of parametric bounds on the clock values. Since their introduction in 1993 by Alur, Henzinger, and Vardi, it is known that the emptiness problem for parametric timed automata with one clock is decidable, whereas it is undecidable if the automaton uses three or more parametric clocks. The problem is open for parametric timed automata with two parametric clocks. Metric temporal logic, MTL for short, is a widely used specification language for real-time systems. MTL-model checking of timed automata is decidable, no matter how many clocks are used in the timed automaton. In this paper, we prove that MTL-model checking for parametric timed automata is undecidable, even if the automaton uses only one clock and one parameter and is deterministic.

  16. Performance of non-parametric algorithms for spatial mapping of tropical forest structure

    Directory of Open Access Journals (Sweden)

    Liang Xu

    2016-08-01

    Full Text Available Abstract Background Mapping tropical forest structure is a critical requirement for accurate estimation of emissions and removals from land use activities. With the availability of a wide range of remote sensing imagery of vegetation characteristics from space, development of finer resolution and more accurate maps has advanced in recent years. However, the mapping accuracy relies heavily on the quality of input layers, the algorithm chosen, and the size and quality of inventory samples for calibration and validation. Results By using airborne lidar data as the “truth” and focusing on the mean canopy height (MCH as a key structural parameter, we test two commonly-used non-parametric techniques of maximum entropy (ME and random forest (RF for developing maps over a study site in Central Gabon. Results of mapping show that both approaches have improved accuracy with more input layers in mapping canopy height at 100 m (1-ha pixels. The bias-corrected spatial models further improve estimates for small and large trees across the tails of height distributions with a trade-off in increasing overall mean squared error that can be readily compensated by increasing the sample size. Conclusions A significant improvement in tropical forest mapping can be achieved by weighting the number of inventory samples against the choice of image layers and the non-parametric algorithms. Without future satellite observations with better sensitivity to forest biomass, the maps based on existing data will remain slightly biased towards the mean of the distribution and under and over estimating the upper and lower tails of the distribution.

  17. Parametric Audio Based Decoder and Music Synthesizer for Mobile Applications

    NARCIS (Netherlands)

    Oomen, A.W.J.; Szczerba, M.Z.; Therssen, D.

    2011-01-01

    This paper reviews parametric audio coders and discusses novel technologies introduced in a low-complexity, low-power consumption audiodecoder and music synthesizer platform developed by the authors. Thedecoder uses parametric coding scheme based on the MPEG-4 Parametric Audio standard. In order to

  18. 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...

  19. 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

  20. Synchronization of chaos in non-identical parametrically excited systems

    International Nuclear Information System (INIS)

    Idowu, B.A.; Vincent, U.E.; Njah, A.N.

    2009-01-01

    In this paper, we investigate the synchronization of chaotic systems consisting of non-identical parametrically excited oscillators. The active control technique is employed to design control functions based on Lyapunov stability theory and Routh-Hurwitz criteria so as to achieve global chaos synchronization between a parametrically excited gyroscope and each of the parametrically excited pendulum and Duffing oscillator. Numerical simulations are implemented to verify the results.

  1. 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.

  2. 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.

  3. Study of parametric instabilities during the Alcator C lower hybrid wave heating experiments

    International Nuclear Information System (INIS)

    Takase, Y.

    1983-10-01

    Parametric excitation of ion-cyclotron quasi-modes (ω/sub R/ approx. = nω/sub ci/) and ion-sound quasi-modes (ω/sub R/ approx. = k/sub parallel to/v/sub ti/) during lower hybrid wave heating of tokamak plasmas have been studied in detail. Such instabilities may significantly modify the incident wavenumber spectrum near the plasma edge. Convective losses for these instabilities are high if well-defined resonance cones exist, but they are significantly reduced if the resonance cones spread and fill the plasma volume (or some region of it). These instabilities preferentially excite lower hybrid waves with larger values of n/sub parallel to/ than themselves possess, and the new waves tend to be absorbed near the outer layers of the plasma. Parametric instabilities during lower hybrid heating of Alcator C plasmas have been investigated using rf probes (to study tilde phi and tilde n/sub i/) and CO 2 scattering technique (to study tilde n/sub e/). At lower densities (anti n/sub e/ less than or equal to 0.5 x 10 14 cm -3 ) where waves observed in the plasma interior using CO 2 scattering appear to be localized, parametric decay is very weak. Both ion-sound and ion-cyclotron parametric decay processes have been observed at higher densities (anti n greater than or equal to 1.5 x 10 14 cm -3 ) where waves appear to be unlocalized. Finally, at still higher densities (anti n /sub e/ greater than or equal to 2 x 10 4 cm -3 ) pump depletion has been observed. Above these densities heating and current drive efficiencies are expected to degrade significantly

  4. Parametric roll resonance monitoring using signal-based detection

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Blanke, Mogens; Falkenberg, Thomas

    2015-01-01

    Extreme roll motion of ships can be caused by several phenomena, one of which is parametric roll resonance. Several incidents occurred unexpectedly around the millennium and caused vast fiscal losses on large container vessels. The phenomenon is now well understood and some consider parametric roll...... algorithms in real conditions, and to evaluate the frequency of parametric roll events on the selected vessels. Detection performance is scrutinised through the validation of the detected events using owners’ standard methods, and supported by available wave radar data. Further, a bivariate statistical...... analysis of the outcome of the signal-based detectors is performed to assess the real life false alarm probability. It is shown that detection robustness and very low false warning rates are obtained. The study concludes that small parametric roll events are occurring, and that the proposed signal...

  5. Parametric resonance and cooling on an atom chip

    International Nuclear Information System (INIS)

    Yan Bo; Li Xiaolin; Ke Min; Wang Yuzhu

    2008-01-01

    This paper observes the parametric excitation on atom chip by measuring the trap loss when applying a parametric modulation. By modulating the current in chip wires, it modulates not only the trap frequency but also the trap position. It shows that the strongest resonance occurs when the modulation frequency equals to the trap frequency. The resonance amplitude increases exponentially with modulation depth. Because the Z-trap is an anharmonic trap, there exists energy selective excitation which would cause parametric cooling. We confirm this effect by observing the temperature of atom cloud dropping

  6. Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites

    Energy Technology Data Exchange (ETDEWEB)

    Zianni, Xanthippi, E-mail: xzianni@teiste.gr, E-mail: xzianni@gmail.com [Department of Aircraft Technology, Technological Educational Institution of Sterea Ellada, 34400 Psachna (Greece); Department of Microelectronics, INN, NCSR “Demokritos,” 15310 Athens (Greece); Narducci, Dario [Department of Materials Science, University of Milano Bicocca, 20125 Milano (Italy)

    2015-01-21

    We present a parametric modeling of the thermoelectric transport coefficients based on a model previously used to interpret experimental measurements on the conductivity, σ, and Seebeck coefficient, S, in highly Boron-doped polycrystalline Si, where a very significant thermoelectric power factor (TPF) enhancement was observed. We have derived analytical formalism for the transport coefficients in the presence of an energy barrier assuming thermionic emission over the barrier for (i) non-degenerate and (ii) degenerate one-band semiconductor. Simple generic parametric equations are found that are in agreement with the exact Boltzmann transport formalism in a wide range of parameters. Moreover, we explore the effect of energy barriers in 1-d composite semiconductors in the presence of two phases: (a) the bulk-like phase and (b) the barrier phase. It is pointed out that significant TPF enhancement can be achieved in the composite structure of two phases with different thermal conductivities. The TPF enhancement is estimated as a function of temperature, the Fermi energy position, the type of scattering, and the barrier height. The derived modeling provides guidance for experiments and device design.

  7. 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.

  8. 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

  9. 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

  10. Robust estimation of seismic coda shape

    Science.gov (United States)

    Nikkilä, Mikko; Polishchuk, Valentin; Krasnoshchekov, Dmitry

    2014-04-01

    We present a new method for estimation of seismic coda shape. It falls into the same class of methods as non-parametric shape reconstruction with the use of neural network techniques where data are split into a training and validation data sets. We particularly pursue the well-known problem of image reconstruction formulated in this case as shape isolation in the presence of a broadly defined noise. This combined approach is enabled by the intrinsic feature of seismogram which can be divided objectively into a pre-signal seismic noise with lack of the target shape, and the remainder that contains scattered waveforms compounding the coda shape. In short, we separately apply shape restoration procedure to pre-signal seismic noise and the event record, which provides successful delineation of the coda shape in the form of a smooth almost non-oscillating function of time. The new algorithm uses a recently developed generalization of classical computational-geometry tool of α-shape. The generalization essentially yields robust shape estimation by ignoring locally a number of points treated as extreme values, noise or non-relevant data. Our algorithm is conceptually simple and enables the desired or pre-determined level of shape detail, constrainable by an arbitrary data fit criteria. The proposed tool for coda shape delineation provides an alternative to moving averaging and/or other smoothing techniques frequently used for this purpose. The new algorithm is illustrated with an application to the problem of estimating the coda duration after a local event. The obtained relation coefficient between coda duration and epicentral distance is consistent with the earlier findings in the region of interest.

  11. Parametric analysis of the statistical model of the stick-slip process

    Science.gov (United States)

    Lima, Roberta; Sampaio, Rubens

    2017-06-01

    In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.

  12. Markov models for digraph panel data : Monte Carlo-based derivative estimation

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A. B.

    2007-01-01

    A parametric, continuous-time Markov model for digraph panel data is considered. The parameter is estimated by the method of moments. A convenient method for estimating the variance-covariance matrix of the moment estimator relies on the delta method, requiring the Jacobian matrix-that is, the

  13. 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.

  14. 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.

  15. Post-Newtonian parameter γ in generalized non-local gravity

    Science.gov (United States)

    Zhang, Xue; Wu, YaBo; Yang, WeiQiang; Zhang, ChengYuan; Chen, BoHai; Zhang, Nan

    2017-10-01

    We investigate the post-Newtonian parameter γ and derive its formalism in generalized non-local (GNL) gravity, which is the modified theory of general relativity (GR) obtained by adding a term m 2 n-2 R☐-n R to the Einstein-Hilbert action. Concretely, based on parametrizing the generalized non-local action in which gravity is described by a series of dynamical scalar fields ϕ i in addition to the metric tensor g μν, the post-Newtonian limit is computed, and the effective gravitational constant as well as the post-Newtonian parameters are directly obtained from the generalized non-local gravity. Moreover, by discussing the values of the parametrized post-Newtonian parameters γ, we can compare our expressions and results with those in Hohmann and Järv et al. (2016), as well as current observational constraints on the values of γ in Will (2006). Hence, we draw restrictions on the nonminimal coupling terms F̅ around their background values.

  16. Design and development of a parametrically excited nonlinear energy harvester

    International Nuclear Information System (INIS)

    Yildirim, Tanju; Ghayesh, Mergen H.; Li, Weihua; Alici, Gursel

    2016-01-01

    Highlights: • A parametrically broadband energy harvester was fabricated. • Strong softening-type nonlinear behaviour was observed. • Experiments were conducted showing the large bandwidth of the device. - Abstract: An energy harvester has been designed, fabricated and tested based on the nonlinear dynamical response of a parametrically excited clamped-clamped beam with a central point-mass; magnets have been used as the central point-mass which pass through a coil when parametrically excited. Experiments have been conducted for the energy harvester when the system is excited (i) harmonically near the primary resonance; (ii) harmonically near the principal parametric resonance; (iii) by means of a non-smooth periodic excitation. An electrodynamic shaker was used to parametrically excite the system and the corresponding displacement of the magnet and output voltages of the coil were measured. It has been shown that the system displays linear behaviour at the primary resonance; however, at the principal parametric resonance, the motion characteristic of the magnet substantially changed displaying a strong softening-type nonlinearity. Theoretical simulations have also been conducted in order to verify the experimental results; the comparison between theory and experiment were within very good agreement of each other. The energy harvester developed in this paper is capable of harvesting energy close to the primary resonance as well as the principal parametric resonance; the frequency-band has been broadened significantly mainly due to the nonlinear effects as well as the parametric excitation.

  17. Nonparametric estimation of benchmark doses in environmental risk assessment

    Science.gov (United States)

    Piegorsch, Walter W.; Xiong, Hui; Bhattacharya, Rabi N.; Lin, Lizhen

    2013-01-01

    Summary An important statistical objective in environmental risk analysis is estimation of minimum exposure levels, called benchmark doses (BMDs), that induce a pre-specified benchmark response in a dose-response experiment. In such settings, representations of the risk are traditionally based on a parametric dose-response model. It is a well-known concern, however, that if the chosen parametric form is misspecified, inaccurate and possibly unsafe low-dose inferences can result. We apply a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007). We determine the large-sample properties of the estimator, develop bootstrap-based confidence limits on the BMDs, and explore the confidence limits’ small-sample properties via a short simulation study. An example from cancer risk assessment illustrates the calculations. PMID:23914133

  18. 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...

  19. Schwinger-type parametrization of open string worldsheets

    Directory of Open Access Journals (Sweden)

    Sam Playle

    2017-03-01

    Full Text Available A parametrization of (super moduli space near the corners corresponding to bosonic or Neveu–Schwarz open string degenerations is introduced for worldsheets of arbitrary topology. With this parametrization, Feynman graph polynomials arise as the α′→0 limit of objects on moduli space. Furthermore, the integration measures of string theory take on a very simple and elegant form.

  20. 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.

  1. OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE.

    Science.gov (United States)

    Xie, Xianchao; Kou, S C; Brown, Lawrence

    2016-03-01

    This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semi-parametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results.

  2. Estimation of Stochastic Volatility Models by Nonparametric Filtering

    DEFF Research Database (Denmark)

    Kanaya, Shin; Kristensen, Dennis

    2016-01-01

    /estimated volatility process replacing the latent process. Our estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps and market microstructure noise. The resulting estimators of the stochastic volatility model will carry additional biases...... and variances due to the first-step estimation, but under regularity conditions we show that these vanish asymptotically and our estimators inherit the asymptotic properties of the infeasible estimators based on observations of the volatility process. A simulation study examines the finite-sample properties...

  3. 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.

  4. 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)

  5. A general three-dimensional parametric geometry of the native aortic valve and root for biomechanical modeling.

    Science.gov (United States)

    Haj-Ali, Rami; Marom, Gil; Ben Zekry, Sagit; Rosenfeld, Moshe; Raanani, Ehud

    2012-09-21

    The complex three-dimensional (3D) geometry of the native tricuspid aortic valve (AV) is represented by select parametric curves allowing for a general construction and representation of the 3D-AV structure including the cusps, commissures and sinuses. The proposed general mathematical description is performed by using three independent parametric curves, two for the cusp and one for the sinuses. These curves are used to generate different surfaces that form the structure of the AV. Additional dependent curves are also generated and utilized in this process, such as the joint curve between the cusps and the sinuses. The model's feasibility to generate patient-specific parametric geometry is examined against 3D-transesophageal echocardiogram (3D-TEE) measurements from a non-pathological AV. Computational finite-element (FE) mesh can then be easily constructed from these surfaces. Examples are given for constructing several 3D-AV geometries by estimating the needed parameters from echocardiographic measurements. The average distance (error) between the calculated geometry and the 3D-TEE measurements was only 0.78±0.63mm. The proposed general 3D parametric method is very effective in quantitatively representing a wide range of native AV structures, with and without pathology. It can also facilitate a methodical quantitative investigation over the effect of pathology and mechanical loading on these major AV parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Phase coherence of parametric-decay modes during high-harmonic fast-wave heating in the National Spherical Torus Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Carlsson, J. A., E-mail: carlsson@pppl.gov [Crow Radio and Plasma Science, Princeton, New Jersey 08540 (United States); Wilson, J. R.; Hosea, J. C.; Greenough, N. L.; Perkins, R. J. [Princeton Plasma Physics Laboratory, P.O. Box 451, Princeton, New Jersey 08543-0451 (United States)

    2016-06-15

    Third-order spectral analysis, in particular, the auto bicoherence, was applied to probe signals from high-harmonic fast-wave heating experiments in the National Spherical Torus Experiment. Strong evidence was found for parametric decay of the 30 MHz radio-frequency (RF) pump wave, with a low-frequency daughter wave at 2.7 MHz, the local majority-ion cyclotron frequency. The primary decay modes have auto bicoherence values around 0.85, very close to the theoretical value of one, which corresponds to total phase coherence with the pump wave. The threshold RF pump power for onset of parametric decay was found to be between 200 kW and 400 kW.

  7. Observational Signatures of Parametric Instability at 1AU

    Science.gov (United States)

    Bowen, T. A.; Bale, S. D.; Badman, S.

    2017-12-01

    Observations and simulations of inertial compressive turbulence in the solar wind are characterized by density structures anti-correlated with magnetic fluctuations parallel to the mean field. This signature has been interpreted as observational evidence for non-propagating pressure balanced structures (PBS), kinetic ion acoustic waves, as well as the MHD slow mode. Recent work, specifically Verscharen et al. (2017), has highlighted the unexpected fluid like nature of the solar wind. Given the high damping rates of parallel propagating compressive fluctuations, their ubiquity in satellite observations is surprising and suggests the presence of a driving process. One possible candidate for the generation of compressive fluctuations in the solar wind is the parametric instability, in which large amplitude Alfvenic fluctuations decay into parallel propagating compressive waves. This work employs 10 years of WIND observations in order to test the parametric decay process as a source of compressive waves in the solar wind through comparing collisionless damping rates of compressive fluctuations with growth rates of the parametric instability. Preliminary results suggest that generation of compressive waves through parametric decay is overdamped at 1 AU. However, the higher parametric decay rates expected in the inner heliosphere likely allow for growth of the slow mode-the remnants of which could explain density fluctuations observed at 1AU.

  8. Magnetorheological fluid dampers: a review of parametric modelling

    International Nuclear Information System (INIS)

    Wang, D H; Liao, W H

    2011-01-01

    Due to the inherent nonlinear nature of magnetorheological (MR) dampers, one of the challenging aspects for developing and utilizing these devices to achieve high performance is the development of models that can accurately describe their unique characteristics. In this review, the characteristics of MR dampers are summarized according to the measured responses under different conditions. On these bases, the considerations and methods of the parametric dynamic modelling for MR dampers are given and the state-of-the-art parametric dynamic modelling, identification and validation techniques for MR dampers are reviewed. In the past two decades, the models for MR dampers have been focused on how to improve the modelling accuracy. Although the force–displacement behaviour is well represented by most of the proposed dynamic models for MR dampers, no simple parametric models with high accuracy for MR dampers can be found. In addition, the parametric dynamic models for MR dampers with on-line updating ability and the inverse parametric models for MR dampers are scarcely explored. Moreover, whether one dynamic model for MR dampers can portray the force–displacement and force–velocity behaviour is not only determined by the dynamic model itself but also determined by the identification method. (topical review)

  9. A capacitive ultrasonic transducer based on parametric resonance

    Science.gov (United States)

    Surappa, Sushruta; Satir, Sarp; Levent Degertekin, F.

    2017-07-01

    A capacitive ultrasonic transducer based on a parametric resonator structure is described and experimentally demonstrated. The transducer structure, which we call capacitive parametric ultrasonic transducer (CPUT), uses a parallel plate capacitor with a movable membrane as part of a degenerate parametric series RLC resonator circuit with a resonance frequency of fo. When the capacitor plate is driven with an incident harmonic ultrasonic wave at the pump frequency of 2fo with sufficient amplitude, the RLC circuit becomes unstable and ultrasonic energy can be efficiently converted to an electrical signal at fo frequency in the RLC circuit. An important characteristic of the CPUT is that unlike other electrostatic transducers, it does not require DC bias or permanent charging to be used as a receiver. We describe the operation of the CPUT using an analytical model and numerical simulations, which shows drive amplitude dependent operation regimes including parametric resonance when a certain threshold is exceeded. We verify these predictions by experiments with a micromachined membrane based capacitor structure in immersion where ultrasonic waves incident at 4.28 MHz parametrically drive a signal with significant amplitude in the 2.14 MHz RLC circuit. With its unique features, the CPUT can be particularly advantageous for applications such as wireless power transfer for biomedical implants and acoustic sensing.

  10. Multi-level approach for parametric roll analysis

    Science.gov (United States)

    Kim, Taeyoung; Kim, Yonghwan

    2011-03-01

    The present study considers multi-level approach for the analysis of parametric roll phenomena. Three kinds of computation method, GM variation, impulse response function (IRF), and Rankine panel method, are applied for the multi-level approach. IRF and Rankine panel method are based on the weakly nonlinear formulation which includes nonlinear Froude- Krylov and restoring forces. In the computation result of parametric roll occurrence test in regular waves, IRF and Rankine panel method show similar tendency. Although the GM variation approach predicts the occurrence of parametric roll at twice roll natural frequency, its frequency criteria shows a little difference. Nonlinear roll motion in bichromatic wave is also considered in this study. To prove the unstable roll motion in bichromatic waves, theoretical and numerical approaches are applied. The occurrence of parametric roll is theoretically examined by introducing the quasi-periodic Mathieu equation. Instability criteria are well predicted from stability analysis in theoretical approach. From the Fourier analysis, it has been verified that difference-frequency effects create the unstable roll motion. The occurrence of unstable roll motion in bichromatic wave is also observed in the experiment.

  11. Consistent Estimation of Pricing Kernels from Noisy Price Data

    OpenAIRE

    Vladislav Kargin

    2003-01-01

    If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

  12. 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.

  13. Estimating extreme losses for the Florida Public Hurricane Model—part II

    Science.gov (United States)

    Gulati, Sneh; George, Florence; Hamid, Shahid

    2018-02-01

    Rising global temperatures are leading to an increase in the number of extreme events and losses (http://www.epa.gov/climatechange/science/indicators/). Accurate estimation of these extreme losses with the intention of protecting themselves against them is critical to insurance companies. In a previous paper, Gulati et al. (2014) discussed probable maximum loss (PML) estimation for the Florida Public Hurricane Loss Model (FPHLM) using parametric and nonparametric methods. In this paper, we investigate the use of semi-parametric methods to do the same. Detailed analysis of the data shows that the annual losses from FPHLM do not tend to be very heavy tailed, and therefore, neither the popular Hill's method nor the moment's estimator work well. However, Pickand's estimator with threshold around the 84th percentile provides a good fit for the extreme quantiles for the losses.

  14. Interplay between parametric instabilities in fusion - relevant laser plasmas

    International Nuclear Information System (INIS)

    Huller, St.

    2003-01-01

    The control of parametric instabilities plays an important role in laser fusion. They are driven by the incident laser beams in the underdense plasma surrounding a fusion capsule and hinder the absorption process of incident laser light which is necessary to heat the fusion target. Due to its high intensity and power, the laser light modifies the plasma density dynamically, such that two or more parametric instabilities compete, in particular stimulated Brillouin scattering and the filamentation instability. The complicated interplay between these parametric instabilities is studied in detail by developing an adequate model accompanied by numerical simulations with multidimensional codes. The model is applied to generic and to smoothed laser beams, which are necessary to limit parametric instabilities, with parameters close to experimental conditions. (author)

  15. A locally adaptive normal distribution

    DEFF Research Database (Denmark)

    Arvanitidis, Georgios; Hansen, Lars Kai; Hauberg, Søren

    2016-01-01

    entropy distribution under the given metric. The underlying metric is, however, non-parametric. We develop a maximum likelihood algorithm to infer the distribution parameters that relies on a combination of gradient descent and Monte Carlo integration. We further extend the LAND to mixture models......The multivariate normal density is a monotonic function of the distance to the mean, and its ellipsoidal shape is due to the underlying Euclidean metric. We suggest to replace this metric with a locally adaptive, smoothly changing (Riemannian) metric that favors regions of high local density...

  16. Performance Analysis Of Single-Pumped And Dual-Pumped Parametric Optical Amplifier

    Directory of Open Access Journals (Sweden)

    Sandar Myint

    2015-06-01

    Full Text Available Abstract In this study we present a performance analysis of single-pumped and dual- pumped parametric optical amplifier and present the analysis of gain flatness in dual- pumped Fiber Optical Parametric Amplifier FOPA based on four-wave mixing FWM. Result shows that changing the signal power and pump power give the various gains in FOPA. It is also found out that the parametric gain increase with increase in pump power and decrease in signal power. .Moreover in this paper the phase matching condition in FWM plays a vital role in predicting the gain profile of the FOPAbecause the parametric gain is maximum when the total phase mismatch is zero.In this paper single-pumped parametric amplification over a 50nm gain bandwidth is demonstrated using 500 nm highly nonlinear fiber HNLF and signal achieves about 31dB gain. For dual-pumped parametric amplification signal achieves 26.5dB gains over a 50nm gain bandwidth. Therefore dual-pumped parametric amplifier can provide relatively flat gain over a much wider bandwidth than the single-pumped FOPA.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. Response-based estimation of sea state parameters - Influence of filtering

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam

    2007-01-01

    Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling...

  2. Multi-copy entanglement purification with practical spontaneous parametric down conversion sources

    International Nuclear Information System (INIS)

    Zhang Shuai-Shuai; Shu Qi; Sheng Yu-Bo; Zhou Lan

    2017-01-01

    Entanglement purification is to distill the high quality entanglement from the low quality entanglement with local operations and classical communications. It is one of the key technologies in long-distance quantum communication. We discuss an entanglement purification protocol (EPP) with spontaneous parametric down conversion (SPDC) sources, in contrast to previous EPP with multi-copy mixed states, which requires ideal entanglement sources. We show that the SPDC source is not an obstacle for purification, but can benefit the fidelity of the purified mixed state. This EPP works for linear optics and is feasible in current experiment technology. (paper)

  3. 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

  4. 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

  5. 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

  6. Physiological responses at short distances from a parametric speaker

    Directory of Open Access Journals (Sweden)

    Lee Soomin

    2012-06-01

    Full Text Available Abstract In recent years, parametric speakers have been used in various circumstances. In our previous studies, we verified that the physiological burden of the sound of parametric speaker set at 2.6 m from the subjects was lower than that of the general speaker. However, nothing has yet been demonstrated about the effects of the sound of a parametric speaker at the shorter distance between parametric speakers the human body. Therefore, we studied this effect on physiological functions and task performance. Nine male subjects participated in this study. They completed three consecutive sessions: a 20-minute quiet period as a baseline, a 30-minute mental task period with general speakers or parametric speakers, and a 20-minute recovery period. We measured electrocardiogram (ECG photoplethysmogram (PTG, electroencephalogram (EEG, systolic and diastolic blood pressure. Four experiments, one with a speaker condition (general speaker and parametric speaker, the other with a distance condition (0.3 m and 1.0 m, were conducted respectively at the same time of day on separate days. To examine the effects of the speaker and distance, three-way repeated measures ANOVA (speaker factor x distance factor x time factor were conducted. In conclusion, we found that the physiological responses were not significantly different between the speaker condition and the distance condition. Meanwhile, it was shown that the physiological burdens increased with progress in time independently of speaker condition and distance condition. In summary, the effects of the parametric speaker at the 2.6 m distance were not obtained at the distance of 1 m or less.

  7. Adaptive Variance Scaling in Continuous Multi-Objective Estimation-of-Distribution Algorithms

    NARCIS (Netherlands)

    P.A.N. Bosman (Peter); D. Thierens (Dirk); D. Thierens (Dirk)

    2007-01-01

    htmlabstractRecent research into single-objective continuous Estimation-of-Distribution Algorithms (EDAs) has shown that when maximum-likelihood estimations are used for parametric distributions such as the normal distribution, the EDA can easily suffer from premature convergence. In this paper we

  8. [Technical background of data collection for parametric observation of total mesorectal excision (TME) in rectal cancer].

    Science.gov (United States)

    Bláha, M; Hoch, J; Ferko, A; Ryška, A; Hovorková, E

    Improvement in any human activity is preconditioned by inspection of results and providing feedback used for modification of the processes applied. Comparison of experts experience in the given field is another indispensable part leading to optimisation and improvement of processes, and optimally to implementation of standards. For the purpose of objective comparison and assessment of the processes, it is always necessary to describe the processes in a parametric way, to obtain representative data, to assess the achieved results, and to provide unquestionable and data-driven feedback based on such analysis. This may lead to a consensus on the definition of standards in the given area of health care. Total mesorectal excision (TME) is a standard procedure of rectal cancer (C20) surgical treatment. However, the quality of performed procedures varies in different health care facilities, which is given, among others, by internal processes and surgeons experience. Assessment of surgical treatment results is therefore of key importance. A pathologist who assesses the resected tissue can provide valuable feedback in this respect. An information system for the parametric assessment of TME performance is described in our article, including technical background in the form of a multicentre clinical registry and the structure of observed parameters. We consider the proposed system of TME parametric assessment as significant for improvement of TME performance, aimed at reducing local recurrences and at improving the overall prognosis of patients. rectal cancer total mesorectal excision parametric data clinical registries TME registry.

  9. 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.

  10. Field calibration and modification of scs design equation for predicting length of border under local conditions

    International Nuclear Information System (INIS)

    Choudhary, M.R.; Mustafa, U.S.

    2009-01-01

    Field tests were conducted to calibrate the existing SCS design equation in determining field border length using field data of different field lengths during 2nd and 3rd irrigations under local conditions. A single ring infiltrometer was used to estimate the water movement into and through the irrigated soil profile and in estimating the coefficients of Kostiakov infiltration function. Measurements of the unit discharge and time of advance were carried out during different irrigations on wheat irrigated fields having clay loam soil. The collected field data were used to calibrate the existing SCS design equation developed by USDA for testing its validity under local field conditions. SCS equation was modified further to improve its applicability. Results from the study revealed that the Kostiakov model over predicted the coefficients, which in turn overestimated the water advance length for boarder in the selected field using existing SCS design equation. However, the calibrated SCS design equation after parametric modification produced more satisfactory results encouraging the scientists to make its use at larger scale. (author)

  11. Rayleigh-type parametric chemical oscillation

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Shyamolina; Ray, Deb Shankar, E-mail: pcdsr@iacs.res.in [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032 (India)

    2015-09-28

    We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.

  12. Rayleigh-type parametric chemical oscillation.

    Science.gov (United States)

    Ghosh, Shyamolina; Ray, Deb Shankar

    2015-09-28

    We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.

  13. On the unlimited gain of a nonlinear parametric amplifier

    DEFF Research Database (Denmark)

    Sorokin, Vladislav

    2014-01-01

    The present paper is concerned with analysis of the response of a nonlinear parametric amplifier in abroad range of system parameters, particularly beyond resonance. Such analysis is of particular interestfor micro- and nanosystems, since many small-scale parametric amplifiers exhibit a distinctly...... nonlinearbehavior when amplitude of their response is sufficiently large. The modified method of direct separa-tion of motions is employed to study the considered system. As the result it is obtained that steady-stateamplitude of the nonlinear parametric amplifier response can reach large values in the case...... of arbitrarilysmall amplitude of external excitation, so that the amplifier gain tends to infinity. Very large amplifiergain can be achieved in a broad range of system parameters, in particular when the amplitude of para-metric excitation is comparatively small. The obtained results clearly demonstrate that very...

  14. Comparing parametric and nonparametric regression methods for panel data

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

  15. 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).

  16. Parametric instabilities in magnetized bi-ion and dusty plasmas

    Indian Academy of Sciences (India)

    -ion or dusty plasma with parametric pumping of the magnetic field is analysed. The equation of motion governing the perturbed plasma is derived and parametrically excited transverse modes propagating along the magnetic field are found.

  17. 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.

  18. The finite sample performance of estimators for mediation analysis under sequential conditional independence

    DEFF Research Database (Denmark)

    Huber, Martin; Lechner, Michael; Mellace, Giovanni

    2016-01-01

    Using a comprehensive simulation study based on empirical data, this paper investigates the finite sample properties of different classes of parametric and semi-parametric estimators of (natural) direct and indirect causal effects used in mediation analysis under sequential conditional independen...... of the methods often (but not always) varies with the features of the data generating process....

  19. A capacitive ultrasonic transducer based on parametric resonance.

    Science.gov (United States)

    Surappa, Sushruta; Satir, Sarp; Levent Degertekin, F

    2017-07-24

    A capacitive ultrasonic transducer based on a parametric resonator structure is described and experimentally demonstrated. The transducer structure, which we call capacitive parametric ultrasonic transducer (CPUT), uses a parallel plate capacitor with a movable membrane as part of a degenerate parametric series RLC resonator circuit with a resonance frequency of f o . When the capacitor plate is driven with an incident harmonic ultrasonic wave at the pump frequency of 2f o with sufficient amplitude, the RLC circuit becomes unstable and ultrasonic energy can be efficiently converted to an electrical signal at f o frequency in the RLC circuit. An important characteristic of the CPUT is that unlike other electrostatic transducers, it does not require DC bias or permanent charging to be used as a receiver. We describe the operation of the CPUT using an analytical model and numerical simulations, which shows drive amplitude dependent operation regimes including parametric resonance when a certain threshold is exceeded. We verify these predictions by experiments with a micromachined membrane based capacitor structure in immersion where ultrasonic waves incident at 4.28 MHz parametrically drive a signal with significant amplitude in the 2.14 MHz RLC circuit. With its unique features, the CPUT can be particularly advantageous for applications such as wireless power transfer for biomedical implants and acoustic sensing.

  20. 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...

  1. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.

    2015-01-01

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  2. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaël

    2015-11-17

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  3. Parametric imaging of collagen structural changes in human osteoarthritic cartilage using optical polarization tractography

    Science.gov (United States)

    Ravanfar, Mohammadreza; Pfeiffer, Ferris M.; Bozynski, Chantelle C.; Wang, Yuanbo; Yao, Gang

    2017-12-01

    Collagen degeneration is an important pathological feature of osteoarthritis. The purpose of this study is to investigate whether the polarization-sensitive optical coherence tomography (PSOCT)-based optical polarization tractography (OPT) can be useful in imaging collagen structural changes in human osteoarthritic cartilage samples. OPT eliminated the banding artifacts in conventional PSOCT by calculating the depth-resolved local birefringence and fiber orientation. A close comparison between OPT and PSOCT showed that OPT provided improved visualization and characterization of the zonal structure in human cartilage. Experimental results obtained in this study also underlined the importance of knowing the collagen fiber orientation in conventional polarized light microscopy assessment. In addition, parametric OPT imaging was achieved by quantifying the surface roughness, birefringence, and fiber dispersion in the superficial zone of the cartilage. These quantitative parametric images provided complementary information on the structural changes in cartilage, which can be useful for a comprehensive evaluation of collagen damage in osteoarthritic cartilage.

  4. Estimating the potential gains from mergers

    DEFF Research Database (Denmark)

    Bogetoft, Peter; Wang, Dexiang

    2005-01-01

    We introduce simple production economic models to estimate the potential gains from mergers. We decompose the gains into technical ef¿ciency, size (scale) and harmony (mix) gains, and we discuss alternative ways to capture these gains. We propose to approximate the production processes using...... the non-parametric. Data Envelopment Analysis (DEA) approach, and we use the resulting operational approach to estimate the potential gains from merging agricultural extension of¿ces in Denmark....

  5. A multitemporal and non-parametric approach for assessing the impacts of drought on vegetation greenness

    DEFF Research Database (Denmark)

    Carrao, Hugo; Sepulcre, Guadalupe; Horion, Stéphanie Marie Anne F

    2013-01-01

    This study evaluates the relationship between the frequency and duration of meteorological droughts and the subsequent temporal changes on the quantity of actively photosynthesizing biomass (greenness) estimated from satellite imagery on rainfed croplands in Latin America. An innovative non-parametric...... and non-supervised approach, based on the Fisher-Jenks optimal classification algorithm, is used to identify multi-scale meteorological droughts on the basis of empirical cumulative distributions of 1, 3, 6, and 12-monthly precipitation totals. As input data for the classifier, we use the gridded GPCC...... for the period between 1998 and 2010. The time-series analysis of vegetation greenness is performed during the growing season with a non-parametric method, namely the seasonal Relative Greenness (RG) of spatially accumulated fAPAR. The Global Land Cover map of 2000 and the GlobCover maps of 2005/2006 and 2009...

  6. On the Feasibility of Stabilizing Parametric Roll with Active Bifurcation Control

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Blanke, Mogens

    2007-01-01

    When parametric resonance occurs on a ship, large roll motion develops rapidly and severe damage on cargo is likely. Some vessels have even capsized in moderate seas for reasons believed to be parametric resonance. This paper revisits the analysis of parametric resonance and assess the possibility...

  7. Validation of Simplified Urban-Canopy Aerodynamic Parametrizations Using a Numerical Simulation of an Actual Downtown Area

    Science.gov (United States)

    Ramirez, N.; Afshari, Afshin; Norford, L.

    2018-02-01

    A steady-state Reynolds-averaged Navier-Stoke computational fluid dynamics (CFD) investigation of boundary-layer flow over a major portion of downtown Abu Dhabi is conducted. The results are used to derive the shear stress and characterize the logarithmic region for eight sub-domains, where the sub-domains overlap and are overlaid in the streamwise direction. They are characterized by a high frontal area index initially, which decreases significantly beyond the fifth sub-domain. The plan area index is relatively stable throughout the domain. For each sub-domain, the estimated local roughness length and displacement height derived from CFD results are compared to prevalent empirical formulations. We further validate and tune a mixing-length model proposed by Coceal and Belcher (Q J R Meteorol Soc 130:1349-1372, 2004). Finally, the in-canopy wind-speed attenuation is analysed as a function of fetch. It is shown that, while there is some room for improvement in Macdonald's empirical formulations (Boundary-Layer Meteorol 97:25-45, 2000), Coceal and Belcher's mixing model in combination with the resolution method of Di Sabatino et al. (Boundary-Layer Meteorol 127:131-151, 2008) can provide a robust estimation of the average wind speed in the logarithmic region. Within the roughness sublayer, a properly parametrized Cionco exponential model is shown to be quite accurate.

  8. 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

  9. PISC II: Parametric studies. Monitoring of PISC-II parametric studies in ultrasonic NDT for PWR

    International Nuclear Information System (INIS)

    Toft, M.W.

    1989-09-01

    The CEGB NDT Applications Centre is partipating in the EEC-funded international Programme for the Inspection of Steel Components (PISC) on account of its relevance to the inspection of Sizewell B and future PWRs. This report describes an inspection monitoring exercise undertaken by NDTAC under partial funding from JRC Ispra, at the initiation of the PISC-III Ultrasonic Modelling Group. Experimental studies have been carried out under PISC-II to investigate ultrasonic defect response as a function of various parameters which characterise the inspection situation. Some of these parametric studies are potentially useful for the validation of theoretical models of ultrasonic inspection and are consequently relevant to the work of the PISC-III Modelling Group. The aim of the present exercise was to ensure that data obtained by the various contract organizations participating in the PISC-II Parametric Studies was of high quality, was a complete record of the inspection and would yield valid comparisons with the predictions of theoretical models. The exercise entailed visits by a nominated CEGB observer to 4 European NDT Laboratories at which the parametric studies were in progress; CISE (Milan); UKAEA (Harwell); UKAEA (Risley) and Vincotte (Brussels). This report presents the findings of those visits

  10. Machine learning-based dual-energy CT parametric mapping.

    Science.gov (United States)

    Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Al Helo, Rose; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C; Rassouli, Negin; Gilkeson, Robert C; Traughber, Bryan J; Cheng, Chee-Wai; Muzic, Raymond F

    2018-05-22

    The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Zeff), relative electron density (ρe), mean excitation energy (Ix), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 seconds. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency. . © 2018 Institute of Physics and Engineering in

  11. Parametric Portfolio Selection: Evaluating and Comparing to Markowitz Portfolios

    Directory of Open Access Journals (Sweden)

    Marcelo C. Medeiros

    2014-10-01

    Full Text Available In this paper we exploit the parametric portfolio optimization in the Brazilian market. Our data consists of monthly returns of 306 Brazilian stocks in the period between 2001 and 2013. We tested the model both in and out of sample and compared the results with the value and equal weighted portfolios and with a Markowitz based portfolio. We performed statistical inference in the parametric optimization using bootstrap techniques in order to build the parameters empirical distributions. Our results showed that the parametric optimization is a very efficient technique out of sample. It consistently showed superior results when compared with the VW, EW and Markowitz portfolios even when transaction costs were included. Finally, we consider the parametric approach to be very flexible to the inclusion of constraints in weights, transaction costs and listing and delisting of stocks.

  12. Incorporating Oxygen-Enhanced MRI into Multi-Parametric Assessment of Human Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Heling Zhou

    2017-08-01

    Full Text Available Hypoxia is associated with prostate tumor aggressiveness, local recurrence, and biochemical failure. Magnetic resonance imaging (MRI offers insight into tumor pathophysiology and recent reports have related transverse relaxation rate (R2* and longitudinal relaxation rate (R1 measurements to tumor hypoxia. We have investigated the inclusion of oxygen-enhanced MRI for multi-parametric evaluation of tumor malignancy. Multi-parametric MRI sequences at 3 Tesla were evaluated in 10 patients to investigate hypoxia in prostate cancer prior to radical prostatectomy. Blood oxygen level dependent (BOLD, tissue oxygen level dependent (TOLD, dynamic contrast enhanced (DCE, and diffusion weighted imaging MRI were intercorrelated and compared with the Gleason score. The apparent diffusion coefficient (ADC was significantly lower in tumor than normal prostate. Baseline R2* (BOLD-contrast was significantly higher in tumor than normal prostate. Upon the oxygen breathing challenge, R2* decreased significantly in the tumor tissue, suggesting improved vascular oxygenation, however changes in R1 were minimal. R2* of contralateral normal prostate decreased in most cases upon oxygen challenge, although the differences were not significant. Moderate correlation was found between ADC and Gleason score. ADC and R2* were correlated and trends were found between Gleason score and R2*, as well as maximum-intensity-projection and area-under-the-curve calculated from DCE. Tumor ADC and R2* have been associated with tumor hypoxia, and thus the correlations are of particular interest. A multi-parametric approach including oxygen-enhanced MRI is feasible and promises further insights into the pathophysiological information of tumor microenvironment.

  13. Implementing quantum optics with parametrically driven superconducting circuits

    Science.gov (United States)

    Aumentado, Jose

    Parametric coupling has received much attention, in part because it forms the core of many low-noise amplifiers in superconducting quantum information experiments. However, parametric coupling in superconducting circuits is, as a general rule, simple to generate and forms the basis of a methodology for interacting microwave fields at different frequencies. In the quantum regime, this has important consequences, allowing relative novices to do experiments in superconducting circuits today that were previously heroic efforts in quantum optics and cavity-QED. In this talk, I'll give an overview of some of our work demonstrating parametric coupling within the context of circuit-QED as well as some of the possibilities this concept creates in our field.

  14. 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.

  15. 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.

  16. Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

    Science.gov (United States)

    Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges

    2013-10-01

    Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.

  17. Parametric feedback cooling of a single atom inside on optical cavity

    International Nuclear Information System (INIS)

    Tatjana Wilk

    2014-01-01

    An optical cavity can be used as a kind of intensifier to study radiation features of an atom, which are hard to detect in free space, like squeezing. Such experiments make use of strong coupling between atom and cavity mode, which experimentally requires the atom to be well localized in the cavity mode. This can be achieved using feedback on the atomic motion: from intensity variations of a probe beam transmitted through the cavity information about the atomic motion is gained, which is used to synchronously modulate the trapping potential holding the atom, leading to cooling and better localization. Here, we report on efficient parametric feedback cooling of a single atom held in an intra-cavity standing wave dipole trap. In contrast to previous feedback strategies, this scheme cools the fast axial oscillation of the atom as well as the slower radial motion. (author)

  18. Personalized precision radiotherapy by integration of multi-parametric functional and biological imaging in prostate cancer. A feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Thorwarth, Daniela [Tuebingen Univ. (Germany). Section for Biomedical Physics; Notohamiprodjo, Mike [Tuebingen Univ. (Germany). Dept. of Diagnostic and Interventional Radiology; Zips, Daniel; Mueller, Arndt-Christan [Tuebingen Univ. (Germany). Dept. of Radiation Oncology

    2017-05-01

    To increase tumour control probability (TCP) in prostate cancer a method was developed integrating multi-parametric functional and biological information into a dose painting treatment plan aiming focal dose-escalation to tumour sub-volumes. A dose-escalation map was derived considering individual, multi-parametric estimated tumour aggressiveness. Multi-parametric functional imaging (MRI, Choline-/PSMA-/FMISO-PET/CT) was acquired for a high risk prostate cancer patient with a high level of tumour load (cT3b cN0 cM0) indicated by subtotal involvement of prostate including the right seminal vesicle and by PSA-level >100. Probability of tumour presence was determined by a combination of multi-parametric functional image information resulting in a voxel-based map of tumour aggressiveness. This probability map was directly integrated into dose optimization in order to plan for inhomogeneous, biological imaging based dose painting. Histograms of the multi-parametric prescription function were generated in addition to a differential histogram of the planned inhomogeneous doses. Comparison of prescribed doses with planned doses on a voxel level was realized using an effective DVH, containing the ratio of prescribed vs. planned dose for each tumour voxel. Multi-parametric imaging data of PSMA, Choline and FMISO PET/CT as well as ADC maps derived from diffusion weighted MRI were combined to an individual probability map of tumour presence. Voxel-based prescription doses ranged from 75.3 Gy up to 93.4 Gy (median: 79.6 Gy), whereas the planned dose painting doses varied only between 72.5 and 80.0 Gy with a median dose of 75.7 Gy. However, inhomogeneous voxel-based dose prescriptions can only be implemented into a treatment plan until a certain level. Multi-parametric probability based dose painting in prostate cancer is technically and clinically feasible. However, detailed calibration functions to define the necessary probability functions need to be assessed in future

  19. Rapid computation of single PET scan rest-stress myocardial blood flow parametric images by table look up.

    Science.gov (United States)

    Guehl, Nicolas J; Normandin, Marc D; Wooten, Dustin W; Rozen, Guy; Ruskin, Jeremy N; Shoup, Timothy M; Woo, Jonghye; Ptaszek, Leon M; Fakhri, Georges El; Alpert, Nathaniel M

    2017-09-01

    We have recently reported a method for measuring rest-stress myocardial blood flow (MBF) using a single, relatively short, PET scan session. The method requires two IV tracer injections, one to initiate rest imaging and one at peak stress. We previously validated absolute flow quantitation in ml/min/cc for standard bull's eye, segmental analysis. In this work, we extend the method for fast computation of rest-stress MBF parametric images. We provide an analytic solution to the single-scan rest-stress flow model which is then solved using a two-dimensional table lookup method (LM). Simulations were performed to compare the accuracy and precision of the lookup method with the original nonlinear method (NLM). Then the method was applied to 16 single scan rest/stress measurements made in 12 pigs: seven studied after infarction of the left anterior descending artery (LAD) territory, and nine imaged in the native state. Parametric maps of rest and stress MBF as well as maps of left (f LV ) and right (f RV ) ventricular spill-over fractions were generated. Regions of interest (ROIs) for 17 myocardial segments were defined in bull's eye fashion on the parametric maps. The mean of each ROI was then compared to the rest (K 1r ) and stress (K 1s ) MBF estimates obtained from fitting the 17 regional TACs with the NLM. In simulation, the LM performed as well as the NLM in terms of precision and accuracy. The simulation did not show that bias was introduced by the use of a predefined two-dimensional lookup table. In experimental data, parametric maps demonstrated good statistical quality and the LM was computationally much more efficient than the original NLM. Very good agreement was obtained between the mean MBF calculated on the parametric maps for each of the 17 ROIs and the regional MBF values estimated by the NLM (K 1map LM  = 1.019 × K 1 ROI NLM  + 0.019, R 2  = 0.986; mean difference = 0.034 ± 0.036 mL/min/cc). We developed a table lookup method for fast

  20. Parametric instabilities of rotor-support systems with application to industrial ventilators

    Science.gov (United States)

    Parszewski, Z.; Krodkiemski, T.; Marynowski, K.

    1980-01-01

    Rotor support systems interaction with parametric excitation is considered for both unequal principal shaft stiffness (generators) and offset disc rotors (ventilators). Instability regions and types of instability are computed in the first case, and parametric resonances in the second case. Computed and experimental results are compared for laboratory machine models. A field case study of parametric vibrations in industrial ventilators is reported. Computed parametric resonances are confirmed in field measurements, and some industrial failures are explained. Also the dynamic influence and gyroscopic effect of supporting structures are shown and computed.

  1. MEASURING DARK MATTER PROFILES NON-PARAMETRICALLY IN DWARF SPHEROIDALS: AN APPLICATION TO DRACO

    International Nuclear Information System (INIS)

    Jardel, John R.; Gebhardt, Karl; Fabricius, Maximilian H.; Williams, Michael J.; Drory, Niv

    2013-01-01

    We introduce a novel implementation of orbit-based (or Schwarzschild) modeling that allows dark matter density profiles to be calculated non-parametrically in nearby galaxies. Our models require no assumptions to be made about velocity anisotropy or the dark matter profile. The technique can be applied to any dispersion-supported stellar system, and we demonstrate its use by studying the Local Group dwarf spheroidal galaxy (dSph) Draco. We use existing kinematic data at larger radii and also present 12 new radial velocities within the central 13 pc obtained with the VIRUS-W integral field spectrograph on the 2.7 m telescope at McDonald Observatory. Our non-parametric Schwarzschild models find strong evidence that the dark matter profile in Draco is cuspy for 20 ≤ r ≤ 700 pc. The profile for r ≥ 20 pc is well fit by a power law with slope α = –1.0 ± 0.2, consistent with predictions from cold dark matter simulations. Our models confirm that, despite its low baryon content relative to other dSphs, Draco lives in a massive halo.

  2. Noise-enhanced Parametric Resonance in Perturbed Galaxies

    Science.gov (United States)

    Sideris, Ioannis V.; Kandrup, Henry E.

    2004-02-01

    This paper describes how parametric resonances associated with a galactic potential subjected to relatively low-amplitude, strictly periodic time-dependent perturbations can be impacted by pseudo-random variations in the pulsation frequency, modeled as colored noise. One aim thereby is to allow for the effects of a changing oscillation frequency as the density distribution associated with a galaxy evolves during violent relaxation. Another is to mimic the possible effects of internal substructures, satellite galaxies, and/or a high-density environment. The principal conclusions are that allowing for a variable frequency does not vitiate the effects of parametric resonance, and that, in at least some cases, such variations can increase the overall importance of parametric resonance associated with systematic pulsations. In memory of Professor H. E. Kandrup, a brilliant scientist, excellent teacher, and good friend. His genius and sense of humor will be greatly missed.

  3. International comparisons of the technical efficiency of the hospital sector: panel data analysis of OECD countries using parametric and non-parametric approaches.

    Science.gov (United States)

    Varabyova, Yauheniya; Schreyögg, Jonas

    2013-09-01

    There is a growing interest in the cross-country comparisons of the performance of national health care systems. The present work provides a comparison of the technical efficiency of the hospital sector using unbalanced panel data from OECD countries over the period 2000-2009. The estimation of the technical efficiency of the hospital sector is performed using nonparametric data envelopment analysis (DEA) and parametric stochastic frontier analysis (SFA). Internal and external validity of findings is assessed by estimating the Spearman rank correlations between the results obtained in different model specifications. The panel-data analyses using two-step DEA and one-stage SFA show that countries, which have higher health care expenditure per capita, tend to have a more technically efficient hospital sector. Whether the expenditure is financed through private or public sources is not related to the technical efficiency of the hospital sector. On the other hand, the hospital sector in countries with higher income inequality and longer average hospital length of stay is less technically efficient. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  4. Interference of two photons in parametric down conversion

    International Nuclear Information System (INIS)

    Ghosh, R.; Hong, C.K.; Ou, Z.Y.; Mandel, L.

    1986-01-01

    A theoretical treatment is given of the process in which the two photons produced simultaneously in the parametric frequency splitting of light are allowed to interfere. It is shown that, while there is no interference in the usual sense involving quantities that are of the second order in the field, fourth-order interference effects are present. These may be revealed by measuring the joint probability of detecting two photons at two points x,x' in the interference plane with photoelectric detectors as a function of the separation x-x'. The probability exhibits a cosine modulation with x-x', with visibility that can approach 100%, even though the integration time in the experiment may greatly exceed the reciprocal bandwidth of the photons. The interference effect has a nonclassical origin and implies a violation of local realism in the highly correlated two-photon state

  5. A New and General Formulation of the Parametric HFGMC Micromechanical Method for Three-Dimensional Multi-Phase Composites

    Science.gov (United States)

    Haj-Ali, Rami; Aboudi, Jacob

    2012-01-01

    The recent two-dimensional (2-D) parametric formulation of the high fidelity generalized method of cells (HFGMC) reported by the authors is generalized for the micromechanical analysis of three-dimensional (3-D) multiphase composites with periodic microstructure. Arbitrary hexahedral subcell geometry is developed to discretize a triply periodic repeating unit-cell (RUC). Linear parametric-geometric mapping is employed to transform the arbitrary hexahedral subcell shapes from the physical space to an auxiliary orthogonal shape, where a complete quadratic displacement expansion is performed. Previously in the 2-D case, additional three equations are needed in the form of average moments of equilibrium as a result of the inclusion of the bilinear terms. However, the present 3-D parametric HFGMC formulation eliminates the need for such additional equations. This is achieved by expressing the coefficients of the full quadratic polynomial expansion of the subcell in terms of the side or face average-displacement vectors. The 2-D parametric and orthogonal HFGMC are special cases of the present 3-D formulation. The continuity of displacements and tractions, as well as the equilibrium equations, are imposed in the average (integral) sense as in the original HFGMC formulation. Each of the six sides (faces) of a subcell has an independent average displacement micro-variable vector which forms an energy-conjugate pair with the transformed average-traction vector. This allows generating symmetric stiffness matrices along with internal resisting vectors for the subcells which enhances the computational efficiency. The established new parametric 3-D HFGMC equations are formulated and solution implementations are addressed. Several applications for triply periodic 3-D composites are presented to demonstrate the general capability and varsity of the present parametric HFGMC method for refined micromechanical analysis by generating the spatial distributions of local stress fields

  6. Analytical work on local faults in LMFBR subassembly

    International Nuclear Information System (INIS)

    Yoshikawa, H.; Miyaguchi, K.; Hirata, N.; Kasahara, F.

    1979-01-01

    Analytical codes have been developed for evaluating various severe but highly unlikely events of local faults in the LMFBR subassembly (S/A). These include: (1) local flow blockage, (2) two-phase thermohydraulics under fission gas release, and (3) inter-S/A failure propagation. A simple inter-S/A thermal failure propagation analysis code, FUMES, is described that allows an easy parametric study of propagation potential of fuel fog in a S/A. 7 refs

  7. Parametric oesophageal multiple swallow scintigraphy for validation of dysphageal symptoms during external beam irradiation of mediastinal tumours

    Energy Technology Data Exchange (ETDEWEB)

    Brandt-Mainz, K.; Eising, E.G.; Bockisch, A. [Essen Univ. (Gesamthochschule) (Germany). Klinik und Poliklinik fuer Nuklearmedizin; Mallek, D. von; Poettgen, C.; Stuschke, M.; Sack, H. [Klinik und Poliklinik fuer Strahlentherapie, Universitaetsklinikum Essen (Germany)

    2001-03-01

    The aim of the study was to evaluate dysphageal symptoms and to measure the effect of local analgesic treatment using parametric oesophageal multiple swallow scintigraphy (PES) during external beam irradiation of the mediastinal region. Fifteen patients (most with lung cancer) with dysphagia grade II underwent PES during external beam radiotherapy of the mediastinum before and after application of local analgesics. Dynamic parametric condensed images were recorded. The intensity of clinical symptoms was correlated with the emptying rate at 10 s (ER-10 s) and the mean transit time (MTT). Visual analysis of the images was performed and the results were correlated with the fields of irradiation portals. Of the 15 patients, 12 showed a correlation between irradiation portals and the region of oesophageal motility disorder. Concordant results of clinical symptoms and PES data were found. In nine patients with a decrease in dysphagia following local analgesia, an increase in mean ER-10 s and a decrease in MTT were observed. In three patients with deterioration in clinical symptoms after analgesic treatment, a similar decrease in mean ER-10 s was found, though MTT remained constant. In three patients with normal values, motility disorders were detected in the dynamic study. In conclusion, PES was found to be a sensitive tool for the validation of dysphageal symptoms in patients during external beam irradiation of mediastinal tumours and for the evaluation and quantification of the efficacy of local analgesic treatment. Additional visual analysis of the dynamic study is helpful in diagnosing minimal disorders. (orig.)

  8. Parametric oesophageal multiple swallow scintigraphy for validation of dysphageal symptoms during external beam irradiation of mediastinal tumours

    International Nuclear Information System (INIS)

    Brandt-Mainz, K.; Eising, E.G.; Bockisch, A.

    2001-01-01

    The aim of the study was to evaluate dysphageal symptoms and to measure the effect of local analgesic treatment using parametric oesophageal multiple swallow scintigraphy (PES) during external beam irradiation of the mediastinal region. Fifteen patients (most with lung cancer) with dysphagia grade II underwent PES during external beam radiotherapy of the mediastinum before and after application of local analgesics. Dynamic parametric condensed images were recorded. The intensity of clinical symptoms was correlated with the emptying rate at 10 s (ER-10 s) and the mean transit time (MTT). Visual analysis of the images was performed and the results were correlated with the fields of irradiation portals. Of the 15 patients, 12 showed a correlation between irradiation portals and the region of oesophageal motility disorder. Concordant results of clinical symptoms and PES data were found. In nine patients with a decrease in dysphagia following local analgesia, an increase in mean ER-10 s and a decrease in MTT were observed. In three patients with deterioration in clinical symptoms after analgesic treatment, a similar decrease in mean ER-10 s was found, though MTT remained constant. In three patients with normal values, motility disorders were detected in the dynamic study. In conclusion, PES was found to be a sensitive tool for the validation of dysphageal symptoms in patients during external beam irradiation of mediastinal tumours and for the evaluation and quantification of the efficacy of local analgesic treatment. Additional visual analysis of the dynamic study is helpful in diagnosing minimal disorders. (orig.)

  9. 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.

  10. A predictor-corrector algorithm to estimate the fractional flow in oil-water models

    International Nuclear Information System (INIS)

    Savioli, Gabriela B; Berdaguer, Elena M Fernandez

    2008-01-01

    We introduce a predictor-corrector algorithm to estimate parameters in a nonlinear hyperbolic problem. It can be used to estimate the oil-fractional flow function from the Buckley-Leverett equation. The forward model is non-linear: the sought- for parameter is a function of the solution of the equation. Traditionally, the estimation of functions requires the selection of a fitting parametric model. The algorithm that we develop does not require a predetermined parameter model. Therefore, the estimation problem is carried out over a set of parameters which are functions. The algorithm is based on the linearization of the parameter-to-output mapping. This technique is new in the field of nonlinear estimation. It has the advantage of laying aside parametric models. The algorithm is iterative and is of predictor-corrector type. We present theoretical results on the inverse problem. We use synthetic data to test the new algorithm.

  11. 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

  12. Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data

    International Nuclear Information System (INIS)

    Jun, Sung C; Plis, Sergey M; Ranken, Doug M; Schmidt, David M

    2006-01-01

    The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We

  13. Path integral quantization of parametrized field theory

    International Nuclear Information System (INIS)

    Varadarajan, Madhavan

    2004-01-01

    Free scalar field theory on a flat spacetime can be cast into a generally covariant form known as parametrized field theory in which the action is a functional of the scalar field as well as the embedding variables which describe arbitrary, in general curved, foliations of the flat spacetime. We construct the path integral quantization of parametrized field theory in order to analyze issues at the interface of quantum field theory and general covariance in a path integral context. We show that the measure in the Lorentzian path integral is nontrivial and is the analog of the Fradkin-Vilkovisky measure for quantum gravity. We construct Euclidean functional integrals in the generally covariant setting of parametrized field theory using key ideas of Schleich and show that our constructions imply the existence of nonstandard 'Wick rotations' of the standard free scalar field two-point function. We develop a framework to study the problem of time through computations of scalar field two-point functions. We illustrate our ideas through explicit computation for a time independent (1+1)-dimensional foliation. Although the problem of time seems to be absent in this simple example, the general case is still open. We discuss our results in the contexts of the path integral formulation of quantum gravity and the canonical quantization of parametrized field theory

  14. Rank-shaping regularization of exponential spectral analysis for application to functional parametric mapping

    International Nuclear Information System (INIS)

    Turkheimer, Federico E; Hinz, Rainer; Gunn, Roger N; Aston, John A D; Gunn, Steve R; Cunningham, Vincent J

    2003-01-01

    Compartmental models are widely used for the mathematical modelling of dynamic studies acquired with positron emission tomography (PET). The numerical problem involves the estimation of a sum of decaying real exponentials convolved with an input function. In exponential spectral analysis (SA), the nonlinear estimation of the exponential functions is replaced by the linear estimation of the coefficients of a predefined set of exponential basis functions. This set-up guarantees fast estimation and attainment of the global optimum. SA, however, is hampered by high sensitivity to noise and, because of the positivity constraints implemented in the algorithm, cannot be extended to reference region modelling. In this paper, SA limitations are addressed by a new rank-shaping (RS) estimator that defines an appropriate regularization over an unconstrained least-squares solution obtained through singular value decomposition of the exponential base. Shrinkage parameters are conditioned on the expected signal-to-noise ratio. Through application to simulated and real datasets, it is shown that RS ameliorates and extends SA properties in the case of the production of functional parametric maps from PET studies

  15. Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

    Science.gov (United States)

    Bereau, Tristan; DiStasio, Robert A.; Tkatchenko, Alexandre; von Lilienfeld, O. Anatole

    2018-06-01

    Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.

  16. A case study to estimate costs using Neural Networks and regression based models

    Directory of Open Access Journals (Sweden)

    Nadia Bhuiyan

    2012-07-01

    Full Text Available Bombardier Aerospace’s high performance aircrafts and services set the utmost standard for the Aerospace industry. A case study in collaboration with Bombardier Aerospace is conducted in order to estimate the target cost of a landing gear. More precisely, the study uses both parametric model and neural network models to estimate the cost of main landing gears, a major aircraft commodity. A comparative analysis between the parametric based model and those upon neural networks model will be considered in order to determine the most accurate method to predict the cost of a main landing gear. Several trials are presented for the design and use of the neural network model. The analysis for the case under study shows the flexibility in the design of the neural network model. Furthermore, the performance of the neural network model is deemed superior to the parametric models for this case study.

  17. An interactive local flattening operator to support digital investigations on artwork surfaces.

    Science.gov (United States)

    Pietroni, Nico; Massimiliano, Corsini; Cignoni, Paolo; Scopigno, Roberto

    2011-12-01

    Analyzing either high-frequency shape detail or any other 2D fields (scalar or vector) embedded over a 3D geometry is a complex task, since detaching the detail from the overall shape can be tricky. An alternative approach is to move to the 2D space, resolving shape reasoning to easier image processing techniques. In this paper we propose a novel framework for the analysis of 2D information distributed over 3D geometry, based on a locally smooth parametrization technique that allows us to treat local 3D data in terms of image content. The proposed approach has been implemented as a sketch-based system that allows to design with a few gestures a set of (possibly overlapping) parameterizations of rectangular portions of the surface. We demonstrate that, due to the locality of the parametrization, the distortion is under an acceptable threshold, while discontinuities can be avoided since the parametrized geometry is always homeomorphic to a disk. We show the effectiveness of the proposed technique to solve specific Cultural Heritage (CH) tasks: the analysis of chisel marks over the surface of a unfinished sculpture and the local comparison of multiple photographs mapped over the surface of an artwork. For this very difficult task, we believe that our framework and the corresponding tool are the first steps toward a computer-based shape reasoning system, able to support CH scholars with a medium they are more used to. © 2011 IEEE

  18. Parametric adaptive filtering and data validation in the bar GW detector AURIGA

    CERN Document Server

    Ortolan, A; Cerdonio, M; Prodi, G A; Vedovato, G; Vitale, S

    2002-01-01

    We report on our experience gained in the signal processing of the resonant GW detector AURIGA. Signal amplitude and arrival time are estimated by means of a matched-adaptive Wiener filter. The detector noise, entering in the filter set-up, is modelled as a parametric ARMA process; to account for slow non-stationarity of the noise, the ARMA parameters are estimated on an hourly basis. A requirement of the set-up of an unbiased Wiener filter is the separation of time spans with 'almost Gaussian' noise from non-Gaussian and/or strongly non-stationary time spans. The separation algorithm consists basically of a variance estimate with the Chauvenet convergence method and a threshold on the Curtosis index. The subsequent validation of data is strictly connected with the separation procedure: in fact, by injecting a large number of artificial GW signals into the 'almost Gaussian' part of the AURIGA data stream, we have demonstrated that the effective probability distributions of the signal-to-noise ratio chi sup 2 ...

  19. 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

  20. Study on Semi-Parametric Statistical Model of Safety Monitoring of Cracks in Concrete Dams

    Directory of Open Access Journals (Sweden)

    Chongshi Gu

    2013-01-01

    Full Text Available Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.