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
Precomputing Process Noise Covariance for Onboard Sequential Filters
Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell
2017-01-01
Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
Spatio-Temporal Audio Enhancement Based on IAA Noise Covariance Matrix Estimates
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
A method for estimating the noise covariance matrix in a mul- tichannel setup is proposed. The method is based on the iter- ative adaptive approach (IAA), which only needs short seg- ments of data to estimate the covariance matrix. Therefore, the method can be used for fast varying signals....... The method is based on an assumption of the desired signal being harmonic, which is used for estimating the noise covariance matrix from the covariance matrix of the observed signal. The noise co- variance estimate is used in the linearly constrained minimum variance (LCMV) filter and compared...
Integrated covariance estimation using high-frequency data in the presence of noise
DEFF Research Database (Denmark)
Voev, Valeri; Lunde, Asger
2007-01-01
We analyze the effects of nonsynchronicity and market microstructure noise on realized covariance type estimators. Hayashi and Yoshida (2005) propose a simple estimator that resolves the problem of nonsynchronicity and is unbiased and consistent for the integrated covariance in the absence of noise...
Smooth individual level covariates adjustment in disease mapping.
Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise
2018-05-01
Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Covariance measurement in the presence of non-synchronous trading and market microstructure noise
Griffin, J.E.; Oomen, R.C.A.
2011-01-01
This paper studies the problem of covariance estimation when prices are observed non-synchronously and contaminated by i.i.d. microstructure noise. We derive closed form expressions for the bias and variance of three popular covariance estimators, namely realised covariance, realised covariance plus
Two-antenna GNSS Aided-INS Alignment Using Adaptive Control of Filter Noise Covariance
Directory of Open Access Journals (Sweden)
HAO Yushi
2018-04-01
Full Text Available This paper developed a theory of INS fine alignment in order to restrain the divergence of yaw angle,two antennas GNSS aided-INS integrated alignment algorithm was utilized.An attitude error measurement equation was conducted based on the relationship between baseline vectors calculated by two sensors and attitude error.The algorithm was executed by EKF using adaptive control of filter noise covariance.The experimental results showed that stability of the integrated system was improved under the system noise covariance adaptive control mechanism;The measurement noise covariance adaptive control mechanism can reduce the influence of measurement noise and improve the alignment absolute accuracy;Further improvement was achieved under the condition of minim bias of baseline length.The accuracy of roll and pitch was 0.02°,the accuracy of yaw was 0.04°.
Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J
2011-10-07
Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
The dependence of signal-to-noise ratio on number of scans in covariance spectroscopy.
Qian, Yi; Shen, Ming; Amoureux, Jean-Paul; Noda, Isao; Hu, Bingwen
2014-01-01
The dependence of signal-to-noise ratio on the number of scans in covariance spectroscopy has been systematically analyzed for the first time with the intriguing relationship of SNRcov∝n/2, which is different from that in FT2D spectrum with SNRFT∝n. This relationship guarantees the signal-to-noise ratio when increasing the number of scans. Copyright © 2014 Elsevier Inc. All rights reserved.
Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan
2017-09-05
The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.
Directory of Open Access Journals (Sweden)
R. Caballero-Águila
2014-01-01
Full Text Available The optimal least-squares linear estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems subject to randomly delayed measurements with different delay rates. For each sensor, a different binary sequence is used to model the delay process. The measured outputs are perturbed by both random parameter matrices and one-step autocorrelated and cross correlated noises. Using an innovation approach, computationally simple recursive algorithms are obtained for the prediction, filtering, and smoothing problems, without requiring full knowledge of the state-space model generating the signal process, but only the information provided by the delay probabilities and the mean and covariance functions of the processes (signal, random parameter matrices, and noises involved in the observation model. The accuracy of the estimators is measured by their error covariance matrices, which allow us to analyze the estimator performance in a numerical simulation example that illustrates the feasibility of the proposed algorithms.
Lorentz Covariance of Langevin Equation
International Nuclear Information System (INIS)
Koide, T.; Denicol, G.S.; Kodama, T.
2008-01-01
Relativistic covariance of a Langevin type equation is discussed. The requirement of Lorentz invariance generates an entanglement between the force and noise terms so that the noise itself should not be a covariant quantity. (author)
Klees, R.; Slobbe, D. C.; Farahani, H. H.
2018-03-01
The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.
Earth Observing System Covariance Realism
Zaidi, Waqar H.; Hejduk, Matthew D.
2016-01-01
The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Generalized Linear Covariance Analysis
Carpenter, James R.; Markley, F. Landis
2014-01-01
This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Covariation of Color and Luminance Facilitate Object Individuation in Infancy
Woods, Rebecca J.; Wilcox, Teresa
2010-01-01
The ability to individuate objects is one of our most fundamental cognitive capacities. Recent research has revealed that when objects vary in color or luminance alone, infants fail to individuate those objects until 11.5 months. However, color and luminance frequently covary in the natural environment, thus providing a more salient and reliable…
A Generalized Autocovariance Least-Squares Method for Covariance Estimation
DEFF Research Database (Denmark)
Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad
2007-01-01
A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....
Analysis of Individual Preferences for Tuning Noise-Reduction Algorithms
Houben, Rolph; Dijkstra, Tjeerd M. H.; Dreschler, Wouter A.
2012-01-01
There is little research on user preference for different settings of noise reduction, especially for individual users. We therefore measured individual preferences for pairs of audio streams differing in the trade-off between noise reduction and speech distortion. A logistic probability model was
Effects of road traffic background noise on judgments of individual airplane noises. Ph.D. Thesis
Powell, C. A.
1979-01-01
Two laboratory experiments were conducted to investigate the effects of road-traffic background noise on judgments of individual airplane flyover noises. In the first experiment, 27 subjects judged a set of 16 airplane flyover noises in the presence of traffic-noise sessions of 30-min duration consisting of the combinations of 3 traffic-noise types and 3 noise levels. In the second experiment, 24 subjects judged the same airplane flyover noises in the presence of traffic-noise sessions of 10-min duration consisting of the combinations of 2 traffic-noise types and 4 noise levels. In both experiments the airplane noises were judged less annoying in the presence of high traffic-noise levels than in the presence of low traffic-noise levels.
A special covariance structure for random coefficient models with both between and within covariates
International Nuclear Information System (INIS)
Riedel, K.S.
1990-07-01
We review random coefficient (RC) models in linear regression and propose a bias correction to the maximum likelihood (ML) estimator. Asymmptotic expansion of the ML equations are given when the between individual variance is much larger or smaller than the variance from within individual fluctuations. The standard model assumes all but one covariate varies within each individual, (we denote the within covariates by vector χ 1 ). We consider random coefficient models where some of the covariates do not vary in any single individual (we denote the between covariates by vector χ 0 ). The regression coefficients, vector β k , can only be estimated in the subspace X k of X. Thus the number of individuals necessary to estimate vector β and the covariance matrix Δ of vector β increases significantly in the presence of more than one between covariate. When the number of individuals is sufficient to estimate vector β but not the entire matrix Δ , additional assumptions must be imposed on the structure of Δ. A simple reduced model is that the between component of vector β is fixed and only the within component varies randomly. This model fails because it is not invariant under linear coordinate transformations and it can significantly overestimate the variance of new observations. We propose a covariance structure for Δ without these difficulties by first projecting the within covariates onto the space perpendicular to be between covariates. (orig.)
Disturbance of sleep by noise: Individual differences
Wilkinson, R. T.
1984-07-01
The literature on the effects of noise on sleep is searched for evidence on individual differences along the dimensions of age, sex, occupation, personality, neuroticism, and mental health. With the exception of age, little firm evidence is found. Thus there remains a need to establish at better than the anecdotal level whether or not real individual differences exist.
Prewhitening for Rank-Deficient Noise in Subspace Methods for Noise Reduction
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Søren Holdt
2005-01-01
A fundamental issue in connection with subspace methods for noise reduction is that the covariance matrix for the noise is required to have full rank, in order for the prewhitening step to be defined. However, there are important cases where this requirement is not fulfilled, e.g., when the noise...... has narrow-band characteristics, or in the case of tonal noise. We extend the concept of prewhitening to include the case when the noise covariance matrix is rank deficient, using a weighted pseudoinverse and the quotient SVD, and we show how to formulate a general rank-reduction algorithm that works...... also for rank deficient noise. We also demonstrate how to formulate this algorithm by means of a quotient ULV decomposition, which allows for faster computation and updating. Finally we apply our algorithm to a problem involving a speech signal contaminated by narrow-band noise....
Shepherd, Daniel; Dirks, Kim; Welch, David; McBride, David; Landon, Jason
2016-08-06
Air pollution originating from road traffic is a known risk factor of respiratory and cardiovascular disease (both in terms of chronic and acute effects). While adverse effects on cardiovascular health have also been linked with noise (after controlling for air pollution), noise exposure has been commonly linked to sleep impairment and negative emotional reactions. Health is multi-faceted, both conceptually and operationally; Health-Related Quality of Life (HRQOL) is one of many measures capable of probing health. In this study, we examine pre-collected data from postal surveys probing HRQOL obtained from a variety of urban, suburban, and rural contexts across the North Island of New Zealand. Analyses focus on the covariance between air pollution annoyance and noise annoyances, and their independent and combined effects on HRQOL. Results indicate that the highest ratings of air pollution annoyance and noise annoyances were for residents living close to the motorway, while the lowest were for rural residents. Most of the city samples indicated no significant difference between air pollution- and noise-annoyance ratings, and of all of the correlations between air pollution- and noise-annoyance, the highest were found in the city samples. These findings suggest that annoyance is driven by exposure to environmental factors and not personality characteristics. Analysis of HRQOL indicated that air pollution annoyance predicts greater variability in the physical HRQOL domain while noise annoyance predicts greater variability in the psychological, social and environmental domains. The lack of an interaction effect between air pollution annoyance and noise annoyance suggests that air pollution and noise impact on health independently. These results echo those obtained from objective measures of health and suggest that mitigation of traffic effects should address both air and noise pollution.
Shepherd, Daniel; Dirks, Kim; Welch, David; McBride, David; Landon, Jason
2016-01-01
Air pollution originating from road traffic is a known risk factor of respiratory and cardiovascular disease (both in terms of chronic and acute effects). While adverse effects on cardiovascular health have also been linked with noise (after controlling for air pollution), noise exposure has been commonly linked to sleep impairment and negative emotional reactions. Health is multi-faceted, both conceptually and operationally; Health-Related Quality of Life (HRQOL) is one of many measures capable of probing health. In this study, we examine pre-collected data from postal surveys probing HRQOL obtained from a variety of urban, suburban, and rural contexts across the North Island of New Zealand. Analyses focus on the covariance between air pollution annoyance and noise annoyances, and their independent and combined effects on HRQOL. Results indicate that the highest ratings of air pollution annoyance and noise annoyances were for residents living close to the motorway, while the lowest were for rural residents. Most of the city samples indicated no significant difference between air pollution- and noise-annoyance ratings, and of all of the correlations between air pollution- and noise-annoyance, the highest were found in the city samples. These findings suggest that annoyance is driven by exposure to environmental factors and not personality characteristics. Analysis of HRQOL indicated that air pollution annoyance predicts greater variability in the physical HRQOL domain while noise annoyance predicts greater variability in the psychological, social and environmental domains. The lack of an interaction effect between air pollution annoyance and noise annoyance suggests that air pollution and noise impact on health independently. These results echo those obtained from objective measures of health and suggest that mitigation of traffic effects should address both air and noise pollution. PMID:27509512
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
2017-01-01
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many...
Cressler, Clayton E; Bengtson, Stefan; Nelson, William A
2017-07-01
Individual differences in genetics, age, or environment can cause tremendous differences in individual life-history traits. This individual heterogeneity generates demographic heterogeneity at the population level, which is predicted to have a strong impact on both ecological and evolutionary dynamics. However, we know surprisingly little about the sources of individual heterogeneity for particular taxa or how different sources scale up to impact ecological and evolutionary dynamics. Here we experimentally study the individual heterogeneity that emerges from both genetic and nongenetic sources in a species of freshwater zooplankton across a large gradient of food quality. Despite the tight control of environment, we still find that the variation from nongenetic sources is greater than that from genetic sources over a wide range of food quality and that this variation has strong positive covariance between growth and reproduction. We evaluate the general consequences of genetic and nongenetic covariance for ecological and evolutionary dynamics theoretically and find that increasing nongenetic variation slows evolution independent of the correlation in heritable life-history traits but that the impact on ecological dynamics depends on both nongenetic and genetic covariance. Our results demonstrate that variation in the relative magnitude of nongenetic versus genetic sources of variation impacts the predicted ecological and evolutionary dynamics.
A three domain covariance framework for EEG/MEG data.
Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C
2015-10-01
In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.
Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation
Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.
2018-01-01
Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.
Galaxy-galaxy lensing estimators and their covariance properties
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose
2017-11-01
We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Galaxy–galaxy lensing estimators and their covariance properties
International Nuclear Information System (INIS)
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; Slosar, Anze; Gonzalez, Jose Vazquez
2017-01-01
Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Noise removal in multichannel image data by a parametric maximum noise fraction estimator
DEFF Research Database (Denmark)
Conradsen, Knut; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg
1991-01-01
Some approaches to noise removal in multispectral imagery are presented. The primary contribution of the present work is the establishment of several ways of estimating the noise covariance matrix from image data and a comparison of the noise separation performances. A case study with Landsat MSS...
Aquatic noise pollution: implications for individuals, populations, and ecosystems.
Kunc, Hansjoerg P; McLaughlin, Kirsty Elizabeth; Schmidt, Rouven
2016-08-17
Anthropogenically driven environmental changes affect our planet at an unprecedented scale and are considered to be a key threat to biodiversity. According to the World Health Organization, anthropogenic noise is one of the most hazardous forms of anthropogenically driven environmental change and is recognized as a major global pollutant. However, crucial advances in the rapidly emerging research on noise pollution focus exclusively on single aspects of noise pollution, e.g. on behaviour, physiology, terrestrial ecosystems, or on certain taxa. Given that more than two-thirds of our planet is covered with water, there is a pressing need to get a holistic understanding of the effects of anthropogenic noise in aquatic ecosystems. We found experimental evidence for negative effects of anthropogenic noise on an individual's development, physiology, and/or behaviour in both invertebrates and vertebrates. We also found that species differ in their response to noise, and highlight the potential underlying mechanisms for these differences. Finally, we point out challenges in the study of aquatic noise pollution and provide directions for future research, which will enhance our understanding of this globally present pollutant. © 2016 The Author(s).
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continuous-time system excited by Gaussian white noise. This result is generalize...
Noisy covariance matrices and portfolio optimization II
Pafka, Szilárd; Kondor, Imre
2003-03-01
Recent studies inspired by results from random matrix theory (Galluccio et al.: Physica A 259 (1998) 449; Laloux et al.: Phys. Rev. Lett. 83 (1999) 1467; Risk 12 (3) (1999) 69; Plerou et al.: Phys. Rev. Lett. 83 (1999) 1471) found that covariance matrices determined from empirical financial time series appear to contain such a high amount of noise that their structure can essentially be regarded as random. This seems, however, to be in contradiction with the fundamental role played by covariance matrices in finance, which constitute the pillars of modern investment theory and have also gained industry-wide applications in risk management. Our paper is an attempt to resolve this embarrassing paradox. The key observation is that the effect of noise strongly depends on the ratio r= n/ T, where n is the size of the portfolio and T the length of the available time series. On the basis of numerical experiments and analytic results for some toy portfolio models we show that for relatively large values of r (e.g. 0.6) noise does, indeed, have the pronounced effect suggested by Galluccio et al. (1998), Laloux et al. (1999) and Plerou et al. (1999) and illustrated later by Laloux et al. (Int. J. Theor. Appl. Finance 3 (2000) 391), Plerou et al. (Phys. Rev. E, e-print cond-mat/0108023) and Rosenow et al. (Europhys. Lett., e-print cond-mat/0111537) in a portfolio optimization context, while for smaller r (around 0.2 or below), the error due to noise drops to acceptable levels. Since the length of available time series is for obvious reasons limited in any practical application, any bound imposed on the noise-induced error translates into a bound on the size of the portfolio. In a related set of experiments we find that the effect of noise depends also on whether the problem arises in asset allocation or in a risk measurement context: if covariance matrices are used simply for measuring the risk of portfolios with a fixed composition rather than as inputs to optimization, the
Audiologic and otoacoustic emission evaluation in individuals exposed to noise and plaguecides
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Morini, Renata Graziele
2009-09-01
Full Text Available Introduction: The noise induced hearing loss (NIHL has been studied for many years and today the specialized literature also studies the synergic action of chemicals. Objective: To research the audiologic findings and DPOAE in workers exposed to occupational noise and plaguecides and to compare them with data obtained in individuals without exposure to these harmful elements. Method: 51 individuals were evaluated (102 ears, divided into three groups. Group I was composed by 17 workers with exposure to noise and plaguecides, all with neurosensorial auditory loss; group II was composed by 17 workers with exposure to noise and plaguecides with audiometric thresholds within normality standards (up to 25 dBNA and group III by 17 healthy individuals without auditory alterations and without exposure to noise and plaguecides, control group. Results: In the audiologic anamnesis, as for groups I and II, we observed that the main auditory complaints presented by the workers were those of recruitment (29.5%, tinnitus (26.5%, allergy (23.5% and arterial hypertension (12%. The findings of the audiometry appointed that the research's individuals did not present with auditory losses in the frequencies of 500 Hz, 1 and 2 kHz, the losses occurred in the frequencies of 3 and 8 kHz. As for the distortion-product otoacoustic emissions (DPOAEs, we observed that the individuals in group III had a major incidence of responses when compared to those of groups I and II. Conclusion: The results analysis allowed us to conclude that the DPOAE test represents an important tool for follow up and prevention of NIHL.
Beamforming using subspace estimation from a diagonally averaged sample covariance.
Quijano, Jorge E; Zurk, Lisa M
2017-08-01
The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.
Age-related hearing decline in individuals with and without occupational noise exposure
Directory of Open Access Journals (Sweden)
Christina Hederstierna
2016-01-01
Full Text Available This study was conducted to compare the pattern of age-related hearing decline in individuals with and without self-reported previous occupational noise exposure. This was a prospective, population-based, longitudinal study of individuals aged 70-75 years, from an epidemiological investigation, comprising three age cohorts. In total there were 1013 subjects (432 men and 581 women. Participants were tested with pure tone audiometry, and they answered a questionnaire to provide information regarding number of years of occupational noise exposure. There were no significant differences in hearing decline, at any frequency, for those aged 70-75 years between the noise-exposed (N= 62 men, 22 women and the nonexposed groups (N = 96 men, 158 women. This study supports the additive model of noise-induced hearing loss (NIHL and age-related hearing loss (ARHL. The concept of different patterns of hearing decline between persons exposed and not exposed to noise could not be verified.
Image covariance and lesion detectability in direct fan-beam x-ray computed tomography.
Wunderlich, Adam; Noo, Frédéric
2008-05-21
We consider noise in computed tomography images that are reconstructed using the classical direct fan-beam filtered backprojection algorithm, from both full- and short-scan data. A new, accurate method for computing image covariance is presented. The utility of the new covariance method is demonstrated by its application to the implementation of a channelized Hotelling observer for a lesion detection task. Results from the new covariance method and its application to the channelized Hotelling observer are compared with results from Monte Carlo simulations. In addition, the impact of a bowtie filter and x-ray tube current modulation on reconstruction noise and lesion detectability are explored for full-scan reconstruction.
Image covariance and lesion detectability in direct fan-beam x-ray computed tomography
International Nuclear Information System (INIS)
Wunderlich, Adam; Noo, Frederic
2008-01-01
We consider noise in computed tomography images that are reconstructed using the classical direct fan-beam filtered backprojection algorithm, from both full- and short-scan data. A new, accurate method for computing image covariance is presented. The utility of the new covariance method is demonstrated by its application to the implementation of a channelized Hotelling observer for a lesion detection task. Results from the new covariance method and its application to the channelized Hotelling observer are compared with results from Monte Carlo simulations. In addition, the impact of a bowtie filter and x-ray tube current modulation on reconstruction noise and lesion detectability are explored for full-scan reconstruction
Directory of Open Access Journals (Sweden)
Friederike Hammersen
2016-09-01
Full Text Available The health implications of environmental noise, especially cardiovascular effects, have been studied intensively. Research on associations between noise and mental health, however, has shown contradictory results. The present study examined associations between individual levels of noise annoyance due to noise from various sources in the living environment and mental health of adults in Germany. It evaluated whether these associations persisted after adjusting for potential covariates. Data were obtained from the cross-sectional “German Health Update” study 2012 (GEDA 2012, a national health interview survey among adults in Germany conducted by the Robert Koch Institute (n = 19,294. Noise annoyance questions referred to overall noise and that from road traffic, neighbours, and air traffic. Mental health was measured with the five-item Mental Health Inventory. Bivariate analysis showed associations between high levels of noise annoyance and impaired mental health for all noise sources except air traffic. After adjusting for covariates (sociodemographic factors, chronic disease, and social support, both men and women who reported high overall noise annoyance showed more than doubled odds of impaired mental health compared to those who were not annoyed. The odds of impaired mental health in the highest noise annoyance category from road traffic and neighbours were also significantly increased. These findings indicate that high noise annoyance is associated with impaired mental health and that this association can vary with the source of environmental noise. Further research on covariates of this association is necessary. Particularly, longitudinal data are required to establish the direction of associations and to address questions of causality.
Agnostic Estimation of Mean and Covariance
Lai, Kevin A.; Rao, Anup B.; Vempala, Santosh
2016-01-01
We consider the problem of estimating the mean and covariance of a distribution from iid samples in $\\mathbb{R}^n$, in the presence of an $\\eta$ fraction of malicious noise; this is in contrast to much recent work where the noise itself is assumed to be from a distribution of known type. The agnostic problem includes many interesting special cases, e.g., learning the parameters of a single Gaussian (or finding the best-fit Gaussian) when $\\eta$ fraction of data is adversarially corrupted, agn...
Kim, Hee-Jong; Shin, Jeong-Hyeon; Han, Cheol E; Kim, Hee Jin; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung
2016-01-01
Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC
Temporal and speech processing skills in normal hearing individuals exposed to occupational noise.
Kumar, U Ajith; Ameenudin, Syed; Sangamanatha, A V
2012-01-01
Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13), 41 50 ( = 13), 41-50 (n = 9), and 51-60 (n = 6) years and their non-noise-exposed counterparts (n = 30 in each age group). Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.
Temporal and speech processing skills in normal hearing individuals exposed to occupational noise
Directory of Open Access Journals (Sweden)
U Ajith Kumar
2012-01-01
Full Text Available Prolonged exposure to high levels of occupational noise can cause damage to hair cells in the cochlea and result in permanent noise-induced cochlear hearing loss. Consequences of cochlear hearing loss on speech perception and psychophysical abilities have been well documented. Primary goal of this research was to explore temporal processing and speech perception Skills in individuals who are exposed to occupational noise of more than 80 dBA and not yet incurred clinically significant threshold shifts. Contribution of temporal processing skills to speech perception in adverse listening situation was also evaluated. A total of 118 participants took part in this research. Participants comprised three groups of train drivers in the age range of 30-40 (n= 13, 41 50 ( = 13, 41-50 (n = 9, and 51-60 (n = 6 years and their non-noise-exposed counterparts (n = 30 in each age group. Participants of all the groups including the train drivers had hearing sensitivity within 25 dB HL in the octave frequencies between 250 and 8 kHz. Temporal processing was evaluated using gap detection, modulation detection, and duration pattern tests. Speech recognition was tested in presence multi-talker babble at -5dB SNR. Differences between experimental and control groups were analyzed using ANOVA and independent sample t-tests. Results showed a trend of reduced temporal processing skills in individuals with noise exposure. These deficits were observed despite normal peripheral hearing sensitivity. Speech recognition scores in the presence of noise were also significantly poor in noise-exposed group. Furthermore, poor temporal processing skills partially accounted for the speech recognition difficulties exhibited by the noise-exposed individuals. These results suggest that noise can cause significant distortions in the processing of suprathreshold temporal cues which may add to difficulties in hearing in adverse listening conditions.
Converse, Sarah J.; Royle, J. Andrew; Urbanek, Richard P.
2012-01-01
Inbreeding depression is frequently a concern of managers interested in restoring endangered species. Decisions to reduce the potential for inbreeding depression by balancing genotypic contributions to reintroduced populations may exact a cost on long-term demographic performance of the population if those decisions result in reduced numbers of animals released and/or restriction of particularly successful genotypes (i.e., heritable traits of particular family lines). As part of an effort to restore a migratory flock of Whooping Cranes (Grus americana) to eastern North America using the offspring of captive breeders, we obtained a unique dataset which includes post-release mark-recapture data, as well as the pedigree of each released individual. We developed a Bayesian formulation of a multi-state model to analyze radio-telemetry, band-resight, and dead recovery data on reintroduced individuals, in order to track survival and breeding state transitions. We used studbook-based individual covariates to examine the comparative evidence for and degree of effects of inbreeding, genotype, and genotype quality on post-release survival of reintroduced individuals. We demonstrate implementation of the Bayesian multi-state model, which allows for the integration of imperfect detection, multiple data types, random effects, and individual- and time-dependent covariates. Our results provide only weak evidence for an effect of the quality of an individual's genotype in captivity on post-release survival as well as for an effect of inbreeding on post-release survival. We plan to integrate our results into a decision-analytic modeling framework that can explicitly examine tradeoffs between the effects of inbreeding and the effects of genotype and demographic stochasticity on population establishment.
Directory of Open Access Journals (Sweden)
Ekaterina Vinnik
2011-02-01
Full Text Available Important sounds can be easily missed or misidentified in the presence of extraneous noise. We describe an auditory illusion in which a continuous ongoing tone becomes inaudible during a brief, non-masking noise burst more than one octave away, which is unexpected given the frequency resolution of human hearing. Participants strongly susceptible to this illusory discontinuity did not perceive illusory auditory continuity (in which a sound subjectively continues during a burst of masking noise when the noises were short, yet did so at longer noise durations. Participants who were not prone to illusory discontinuity showed robust early electroencephalographic responses at 40-66 ms after noise burst onset, whereas those prone to the illusion lacked these early responses. These data suggest that short-latency neural responses to auditory scene components reflect subsequent individual differences in the parsing of auditory scenes.
Mikosch, Jochen; Patchkovskii, Serguei
2013-10-01
We use an analytical theory of noisy Poisson processes, developed in the preceding companion publication, to compare coincidence and covariance measurement approaches in photoelectron and -ion spectroscopy. For non-unit detection efficiencies, coincidence data acquisition (DAQ) suffers from false coincidences. The rate of false coincidences grows quadratically with the rate of elementary ionization events. To minimize false coincidences for rare event outcomes, very low event rates may hence be required. Coincidence measurements exhibit high tolerance to noise introduced by unstable experimental conditions. Covariance DAQ on the other hand is free of systematic errors as long as stable experimental conditions are maintained. In the presence of noise, all channels in a covariance measurement become correlated. Under favourable conditions, covariance DAQ may allow orders of magnitude reduction in measurement times. Finally, we use experimental data for strong-field ionization of 1,3-butadiene to illustrate how fluctuations in experimental conditions can contaminate a covariance measurement, and how such contamination can be detected.
Power Adaptive Feedback Communication over an Additive Individual Noise Sequence Channel
Lomnitz, Yuval; Feder, Meir
2009-01-01
We consider a real-valued additive channel with an individual unknown noise sequence. We present a simple sequential communication scheme based on the celebrated Schalkwijk-Kailath scheme, which varies the transmit power according to the power of the sequence, so that asymptotically the relation between the SNR and the rate matches the Gaussian channel capacity 1/2 log(1+SNR)for almost every noise sequence.
Chen, Fei; Loizou, Philipos C
2010-12-01
The normalized covariance measure (NCM) has been shown previously to predict reliably the intelligibility of noise-suppressed speech containing non-linear distortions. This study analyzes a simplified NCM measure that requires only a small number of bands (not necessarily contiguous) and uses simple binary (1 or 0) weighting functions. The rationale behind the use of a small number of bands is to account for the fact that the spectral information contained in contiguous or nearby bands is correlated and redundant. The modified NCM measure was evaluated with speech intelligibility scores obtained by normal-hearing listeners in 72 noisy conditions involving noise-suppressed speech corrupted by four different types of maskers (car, babble, train, and street interferences). High correlation (r = 0.8) was obtained with the modified NCM measure even when only one band was used. Further analysis revealed a masker-specific pattern of correlations when only one band was used, and bands with low correlation signified the corresponding envelopes that have been severely distorted by the noise-suppression algorithm and/or the masker. Correlation improved to r = 0.84 when only two disjoint bands (centered at 325 and 1874 Hz) were used. Even further improvements in correlation (r = 0.85) were obtained when three or four lower-frequency (<700 Hz) bands were selected.
Pitch and Loudness from Tinnitus in Individuals with Noise-induced Hearing Loss
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Flores, Leticia Sousa
2015-08-01
Full Text Available Introduction Tinnitus is one of the symptoms that affects individuals suffering from noise induced hearing loss. This condition can be disabling, leading the affected individual to turn away from work. Objective This literature review aims to analyze the possible association between gender and tinnitus pitch and loudness, the degree of hearing loss and the frequencies affected in subjects with noise-induced hearing loss. Methods This contemporary cohort study was conducted through a cross-sectional analysis. The study sample consisted of adults with unilateral or bilateral tinnitus, who had been diagnosed with noise-induced hearing loss. The patients under analysis underwent an otorhinolaryngological evaluation, pure tone audiometry, and acuphenometry. Results The study included 33 subjects with noise-induced hearing loss diagnoses, of which 22 (66.7% were men. Authors observed no statistical difference between gender and loudness/pitch tinnitus and loudness/pitch in subjects with bilateral tinnitus. Authors found an inverse relation between tinnitus loudness with intensity greater hearing threshold and the average of the thresholds and the grade of hearing loss. The tinnitus pitch showed no association with higher frequency of hearing threshold. Conclusion Data analysis shows that, among the individuals evaluated, the greater the hearing loss, the lower the loudness of tinnitus. We did not observe an association between hearing loss and tinnitus pitch.
Linear Covariance Analysis and Epoch State Estimators
Markley, F. Landis; Carpenter, J. Russell
2014-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many...
MIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levels
Ahmed, Sajid
2012-12-29
MIMO-radar has better parametric identifiability but compared to phased-array radar it shows loss in signal-to-noise ratio due to non-coherent processing. To exploit the benefits of both MIMO-radar and phased-array two transmit covariance matrices are found. Both of the covariance matrices yield gain in signal-to-interference-plus-noise ratio (SINR) compared to MIMO-radar and have lower side-lobe levels (SLL)\\'s compared to phased-array and MIMO-radar. Moreover, in contrast to recently introduced phased-MIMO scheme, where each antenna transmit different power, our proposed schemes allows same power transmission from each antenna. The SLL\\'s of the proposed first covariance matrix are higher than the phased-MIMO scheme while the SLL\\'s of the second proposed covariance matrix are lower than the phased-MIMO scheme. The first covariance matrix is generated using an auto-regressive process, which allow us to change the SINR and side lobe levels by changing the auto-regressive parameter, while to generate the second covariance matrix the values of sine function between 0 and $\\\\pi$ with the step size of $\\\\pi/n_T$ are used to form a positive-semidefinite Toeplitiz matrix, where $n_T$ is the number of transmit antennas. Simulation results validate our analytical results.
Anomaly detection in OECD Benchmark data using co-variance methods
International Nuclear Information System (INIS)
Srinivasan, G.S.; Krinizs, K.; Por, G.
1993-02-01
OECD Benchmark data distributed for the SMORN VI Specialists Meeting in Reactor Noise were investigated for anomaly detection in artificially generated reactor noise benchmark analysis. It was observed that statistical features extracted from covariance matrix of frequency components are very sensitive in terms of the anomaly detection level. It is possible to create well defined alarm levels. (R.P.) 5 refs.; 23 figs.; 1 tab
Does occupational noise cause asymmetric hearing loss?
Dobie, Robert A
2014-01-01
Determine whether occupational noise exposure increases audiometric asymmetry. Audiograms were performed on 2044 men from the Occupational Noise and Hearing Survey, representing four groups based on preliminary screening (for previous noise exposure, otologic history, and otoscopy) and current occupational noise exposure. The effects of current noise exposure on audiometric asymmetry were tested using ANCOVA, with binaural average thresholds as covariates. There were no significant differences in asymmetry attributable to current occupational noise exposure. Occupational noise exposure does not usually cause or exacerbate audiometric asymmetry.
[Occupational noise exposure and work accidents].
Dias, Adriano; Cordeiro, Ricardo; Gonçalves, Cláudia Giglio de Oliveira
2006-10-01
The purpose of this study was to verify whether occupational noise exposure is a significant risk factor for work accidents in the city of Piracicaba, São Paulo State, Brazil. This hospital-based case-control study included 600 workers aged 15-60 who suffered typical occupational accidents between May and October 2004 and were seen at the Piracicaba Orthopedics and Trauma Center. The control group comprised 822 workers, aged 15-60, who were also seen at the Center, and either had a non-occupational accident or were accompanying someone who had suffered an accident. A multiple logistic regression model was adjusted with work accident as an independent variable, controlled by covariables of interest such as noise exposure. The risk of having a work accident was about twice as high among workers exposed to noise, after controlling for several covariables. Occupational noise exposure not only affected auditory health status but was also a risk factor for work accidents.
Single-Channel Noise Reduction using Unified Joint Diagonalization and Optimal Filtering
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Benesty, Jacob; Jensen, Jesper Rindom
2014-01-01
consider two cases, where, respectively, no distortion and distortion are incurred on the desired signal. The former can be achieved when the covariance matrix of the desired signal is rank deficient, which is the case, for example, for voiced speech. In the latter case, the covariance matrix......In this paper, the important problem of single-channel noise reduction is treated from a new perspective. The problem is posed as a filtering problem based on joint diagonalization of the covariance matrices of the desired and noise signals. More specifically, the eigenvectors from the joint...
Institute of Scientific and Technical Information of China (English)
QI Wen-Juan; ZHANG Peng; DENG Zi-Li
2014-01-01
This paper deals with the problem of designing robust sequential covariance intersection (SCI) fusion Kalman filter for the clustering multi-agent sensor network system with measurement delays and uncertain noise variances. The sensor network is partitioned into clusters by the nearest neighbor rule. Using the minimax robust estimation principle, based on the worst-case conservative sensor network system with conservative upper bounds of noise variances, and applying the unbiased linear minimum variance (ULMV) optimal estimation rule, we present the two-layer SCI fusion robust steady-state Kalman filter which can reduce communication and computation burdens and save energy sources, and guarantee that the actual filtering error variances have a less-conservative upper-bound. A Lyapunov equation method for robustness analysis is proposed, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented and the robust accuracy relations of the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the global SCI fuser is higher than those of the local SCI fusers and the robust accuracies of all SCI fusers are higher than that of each local robust Kalman filter. A simulation example for a tracking system verifies the robustness and robust accuracy relations.
Covariance Evaluation Methodology for Neutron Cross Sections
Energy Technology Data Exchange (ETDEWEB)
Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.
2008-09-01
We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
Ziyatdinov, Andrey; Vázquez-Santiago, Miquel; Brunel, Helena; Martinez-Perez, Angel; Aschard, Hugues; Soria, Jose Manuel
2018-02-27
Quantitative trait locus (QTL) mapping in genetic data often involves analysis of correlated observations, which need to be accounted for to avoid false association signals. This is commonly performed by modeling such correlations as random effects in linear mixed models (LMMs). The R package lme4 is a well-established tool that implements major LMM features using sparse matrix methods; however, it is not fully adapted for QTL mapping association and linkage studies. In particular, two LMM features are lacking in the base version of lme4: the definition of random effects by custom covariance matrices; and parameter constraints, which are essential in advanced QTL models. Apart from applications in linkage studies of related individuals, such functionalities are of high interest for association studies in situations where multiple covariance matrices need to be modeled, a scenario not covered by many genome-wide association study (GWAS) software. To address the aforementioned limitations, we developed a new R package lme4qtl as an extension of lme4. First, lme4qtl contributes new models for genetic studies within a single tool integrated with lme4 and its companion packages. Second, lme4qtl offers a flexible framework for scenarios with multiple levels of relatedness and becomes efficient when covariance matrices are sparse. We showed the value of our package using real family-based data in the Genetic Analysis of Idiopathic Thrombophilia 2 (GAIT2) project. Our software lme4qtl enables QTL mapping models with a versatile structure of random effects and efficient computation for sparse covariances. lme4qtl is available at https://github.com/variani/lme4qtl .
Noise estimation for remote sensing image data analysis
Du, Qian
2004-01-01
Noise estimation does not receive much attention in remote sensing society. It may be because normally noise is not large enough to impair image analysis result. Noise estimation is also very challenging due to the randomness nature of the noise (for random noise) and the difficulty of separating the noise component from the signal in each specific location. We review and propose seven different types of methods to estimate noise variance and noise covariance matrix in a remotely sensed image. In the experiment, it is demonstrated that a good noise estimate can improve the performance of an algorithm via noise whitening if this algorithm assumes white noise.
Autism-specific covariation in perceptual performances: "g" or "p" factor?
Meilleur, Andrée-Anne S; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent
2014-01-01
Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor). Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor), which may drive perceptual abilities differently in autistic and
Autism-specific covariation in perceptual performances: "g" or "p" factor?
Directory of Open Access Journals (Sweden)
Andrée-Anne S Meilleur
Full Text Available Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination and mid-level (e.g., pattern matching tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals.We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ and Raven Progressive Matrices (RPM. We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence.In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism.Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor. Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor, which may drive perceptual abilities differently in
Higher songs of city birds may not be an individual response to noise.
Zollinger, Sue Anne; Slater, Peter J B; Nemeth, Erwin; Brumm, Henrik
2017-08-16
It has been observed in many songbird species that populations in noisy urban areas sing with a higher minimum frequency than do matched populations in quieter, less developed areas. However, why and how this divergence occurs is not yet understood. We experimentally tested whether chronic noise exposure during vocal learning results in songs with higher minimum frequencies in great tits ( Parus major ), the first species for which a correlation between anthropogenic noise and song frequency was observed. We also tested vocal plasticity of adult great tits in response to changing background noise levels by measuring song frequency and amplitude as we changed noise conditions. We show that noise exposure during ontogeny did not result in songs with higher minimum frequencies. In addition, we found that adult birds did not make any frequency or song usage adjustments when their background noise conditions were changed after song crystallization. These results challenge the common view of vocal adjustments by city birds, as they suggest that either noise itself is not the causal force driving the divergence of song frequency between urban and forest populations, or that noise induces population-wide changes over a time scale of several generations rather than causing changes in individual behaviour. © 2017 The Author(s).
Individual differences in language and working memory affect children's speech recognition in noise.
McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc
2017-05-01
We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.
Development of a perceptually calibrated objective metric of noise
Keelan, Brian W.; Jin, Elaine W.; Prokushkin, Sergey
2011-01-01
A system simulation model was used to create scene-dependent noise masks that reflect current performance of mobile phone cameras. Stimuli with different overall magnitudes of noise and with varying mixtures of red, green, blue, and luminance noises were included in the study. Eleven treatments in each of ten pictorial scenes were evaluated by twenty observers using the softcopy ruler method. In addition to determining the quality loss function in just noticeable differences (JNDs) for the average observer and scene, transformations for different combinations of observer sensitivity and scene susceptibility were derived. The psychophysical results were used to optimize an objective metric of isotropic noise based on system noise power spectra (NPS), which were integrated over a visual frequency weighting function to yield perceptually relevant variances and covariances in CIE L*a*b* space. Because the frequency weighting function is expressed in terms of cycles per degree at the retina, it accounts for display pixel size and viewing distance effects, so application-specific predictions can be made. Excellent results were obtained using only L* and a* variances and L*a* covariance, with relative weights of 100, 5, and 12, respectively. The positive a* weight suggests that the luminance (photopic) weighting is slightly narrow on the long wavelength side for predicting perceived noisiness. The L*a* covariance term, which is normally negative, reflects masking between L* and a* noise, as confirmed in informal evaluations. Test targets in linear sRGB and rendered L*a*b* spaces for each treatment are available at http://www.aptina.com/ImArch/ to enable other researchers to test metrics of their own design and calibrate them to JNDs of quality loss without performing additional observer experiments. Such JND-calibrated noise metrics are particularly valuable for comparing the impact of noise and other attributes, and for computing overall image quality.
New perspective in covariance evaluation for nuclear data
International Nuclear Information System (INIS)
Kanda, Y.
1992-01-01
Methods of nuclear data evaluation have been highly developed during the past decade, especially after introducing the concept of covariance. This makes it utmost important how to evaluate covariance matrices for nuclear data. It can be said that covariance evaluation is just the nuclear data evaluation, because the covariance matrix has quantitatively decisive function in current evaluation methods. The covariance primarily represents experimental uncertainties. However, correlation of individual uncertainties between different data must be taken into account and it can not be conducted without detailed physical considerations on experimental conditions. This procedure depends on the evaluator and the estimated covariance does also. The mathematical properties of the covariance have been intensively discussed. Their physical properties should be studied to apply it to the nuclear data evaluation, and then, in this report, are reviewed to give the base for further development of the covariance application. (orig.)
Antonioli, Cleonice Aparecida Silva; Momensohn-Santos, Teresa Maria; Benaglia, Tatiana Aparecida Silva
2016-07-01
The literature reports on high-frequency audiometry as one of the exams used on hearing monitoring of individuals exposed to high sound pressure in their work environment, due to the method́s greater sensitivity in early identification of hearing loss caused by noise. The frequencies that compose the exam are generally between 9 KHz and 20KHz, depending on the equipment. This study aims to perform a retrospective and secondary systematic revision of publications on high-frequency audiometry on hearing monitoring of individuals exposed to occupational noise. This systematic revision followed the methodology proposed in the Cochrane Handbook, focusing on the question: "Is High-frequency Audiometry more sensitive than Conventional Audiometry in the screening of early hearing loss individuals exposed to occupational noise?" The search was based on PubMed data, Base, Web of Science (Capes), Biblioteca Virtual em Saúde (BVS), and in the references cited in identified and selected articles. The search resulted in 6059 articles in total. Of these, only six studies were compatible with the criteria proposed in this study. The performed meta-analysis does not definitively answer the study's proposed question. It indicates that the 16 KHz high frequency audiometry (HFA) frequency is sensitive in early identification of hearing loss in the control group (medium difference (MD = 8.33)), as well as the 4 KHz frequency (CA), this one being a little less expressive (MD = 5.72). Thus, others studies are necessary to confirm the HFA importance for the early screening of hearing loss on individuals exposed to noise at the workplace.
Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise
International Nuclear Information System (INIS)
Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym
2008-01-01
This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method
A Noise Robust Statistical Texture Model
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus
2002-01-01
Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise......This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...
Directory of Open Access Journals (Sweden)
Jianxin Feng
2014-01-01
Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.
Comparative Analyses of Phenotypic Trait Covariation within and among Populations.
Peiman, Kathryn S; Robinson, Beren W
2017-10-01
Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.
DEFF Research Database (Denmark)
Kinnebrock, Silja; Podolskij, Mark
This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....
Autism-Specific Covariation in Perceptual Performances: “g” or “p” Factor?
Meilleur, Andrée-Anne S.; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent
2014-01-01
Background Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. Methods We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. Results In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Conclusions Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or “g” factor). Instead, this residual covariation is accounted for by a common perceptual process (or “p” factor), which may drive
Directory of Open Access Journals (Sweden)
Antonioli, Cleonice Aparecida Silva
2015-12-01
Full Text Available Introduction The literature reports on high-frequency audiometry as one of the exams used on hearing monitoring of individuals exposed to high sound pressure in their work environment, due to the method́s greater sensitivity in early identification of hearing loss caused by noise. The frequencies that compose the exam are generally between 9 KHz and 20KHz, depending on the equipment. Objective This study aims to perform a retrospective and secondary systematic revision of publications on high-frequency audiometry on hearing monitoring of individuals exposed to occupational noise. Data Synthesis This systematic revision followed the methodology proposed in the Cochrane Handbook, focusing on the question: “Is High-frequency Audiometry more sensitive than Conventional Audiometry in the screening of early hearing loss individuals exposed to occupational noise?” The search was based on PubMed data, Base, Web of Science (Capes, Biblioteca Virtual em Saúde (BVS, and in the references cited in identified and selected articles. The search resulted in 6059 articles in total. Of these, only six studies were compatible with the criteria proposed in this study. Conclusion The performed meta-analysis does not definitively answer the study's proposed question. It indicates that the 16 KHz high frequency audiometry (HFA frequency is sensitive in early identification of hearing loss in the control group (medium difference (MD = 8.33, as well as the 4 KHz frequency (CA, this one being a little less expressive (MD = 5.72. Thus, others studies are necessary to confirm the HFA importance for the early screening of hearing loss on individuals exposed to noise at the workplace.
Individual differences in language and working memory affect children’s speech recognition in noise
McCreery, Ryan W.; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc
2017-01-01
Objective We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. Design As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Study sample Ninety-six children with normal hearing, who were between 5 and 12 years of age. Results Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Conclusions Working memory and language both influence children’s speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child’s auditory skills, consistent with the Ease of Language Understanding model. PMID:27981855
Delphi, Maryam; Lotfi, M-Yones; Moossavi, Abdollah; Bakhshi, Enayatollah; Banimostafa, Maryam
2017-09-01
Previous studies have shown that interaural-time-difference (ITD) training can improve localization ability. Surprisingly little is, however, known about localization training vis-à-vis speech perception in noise based on interaural time difference in the envelope (ITD ENV). We sought to investigate the reliability of an ITD ENV-based training program in speech-in-noise perception among elderly individuals with normal hearing and speech-in-noise disorder. The present interventional study was performed during 2016. Sixteen elderly men between 55 and 65 years of age with the clinical diagnosis of normal hearing up to 2000 Hz and speech-in-noise perception disorder participated in this study. The training localization program was based on changes in ITD ENV. In order to evaluate the reliability of the training program, we performed speech-in-noise tests before the training program, immediately afterward, and then at 2 months' follow-up. The reliability of the training program was analyzed using the Friedman test and the SPSS software. Significant statistical differences were shown in the mean scores of speech-in-noise perception between the 3 time points (P=0.001). The results also indicated no difference in the mean scores of speech-in-noise perception between the 2 time points of immediately after the training program and 2 months' follow-up (P=0.212). The present study showed the reliability of an ITD ENV-based localization training in elderly individuals with speech-in-noise perception disorder.
Hua, Hairui; Burke, Danielle L; Crowther, Michael J; Ensor, Joie; Tudur Smith, Catrin; Riley, Richard D
2017-02-28
Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd
MIMO-radar Waveform Covariance Matrices for High SINR and Low Side-lobe Levels
Ahmed, Sajid; Alouini, Mohamed-Slim
2012-01-01
MIMO-radar has better parametric identifiability but compared to phased-array radar it shows loss in signal-to-noise ratio due to non-coherent processing. To exploit the benefits of both MIMO-radar and phased-array two transmit covariance matrices
Chen, Yue; McBain, Ryan; Norton, Daniel
2015-02-28
Face perception plays a foundational role in the social world. This perceptual ability is deficient in schizophrenia. A noise-filtering mechanism is essential for perceptual processing. It remains unclear as to whether a specific noise-filtering mechanism is implicated in the face perception problem or a general noise-filtering mechanism is involved which also mediates non-face visual perception problems associated with this psychiatric disorder. This study examined and compared the effects of external noise on the performance of face discrimination and car discrimination in schizophrenia patients (n=25) and healthy controls (n=27). Superimposing the external visual noise on face or car stimuli elevated perceptual thresholds (i.e. degraded performance levels) for both face and car discrimination. However, the effect of noise was significantly larger on face than on car discrimination, both in patients and controls. This pattern of results suggests specific vulnerability of face processing to noise in healthy individuals and those with schizophrenia. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Maryam Delphi
2017-09-01
Full Text Available Background: Previous studies have shown that interaural-time-difference (ITD training can improve localization ability. Surprisingly little is, however, known about localization training vis-à-vis speech perception in noise based on interaural time difference in the envelope (ITD ENV. We sought to investigate the reliability of an ITD ENV-based training program in speech-in-noise perception among elderly individuals with normal hearing and speech-in-noise disorder. Methods: The present interventional study was performed during 2016. Sixteen elderly men between 55 and 65 years of age with the clinical diagnosis of normal hearing up to 2000 Hz and speech-in-noise perception disorder participated in this study. The training localization program was based on changes in ITD ENV. In order to evaluate the reliability of the training program, we performed speech-in-noise tests before the training program, immediately afterward, and then at 2 months’ follow-up. The reliability of the training program was analyzed using the Friedman test and the SPSS software. Results: Significant statistical differences were shown in the mean scores of speech-in-noise perception between the 3 time points (P=0.001. The results also indicated no difference in the mean scores of speech-in-noise perception between the 2 time points of immediately after the training program and 2 months’ follow-up (P=0.212. Conclusion: The present study showed the reliability of an ITD ENV-based localization training in elderly individuals with speech-in-noise perception disorder.
Photonic quantum simulator for unbiased phase covariant cloning
Knoll, Laura T.; López Grande, Ignacio H.; Larotonda, Miguel A.
2018-01-01
We present the results of a linear optics photonic implementation of a quantum circuit that simulates a phase covariant cloner, using two different degrees of freedom of a single photon. We experimentally simulate the action of two mirrored 1→ 2 cloners, each of them biasing the cloned states into opposite regions of the Bloch sphere. We show that by applying a random sequence of these two cloners, an eavesdropper can mitigate the amount of noise added to the original input state and therefore, prepare clones with no bias, but with the same individual fidelity, masking its presence in a quantum key distribution protocol. Input polarization qubit states are cloned into path qubit states of the same photon, which is identified as a potential eavesdropper in a quantum key distribution protocol. The device has the flexibility to produce mirrored versions that optimally clone states on either the northern or southern hemispheres of the Bloch sphere, as well as to simulate optimal and non-optimal cloning machines by tuning the asymmetry on each of the cloning machines.
Globally covering a-priori regional gravity covariance models
Directory of Open Access Journals (Sweden)
D. Arabelos
2003-01-01
Full Text Available Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation, the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-22. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`
Covariate-adjusted measures of discrimination for survival data
DEFF Research Database (Denmark)
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...
Multi-compartment linear noise approximation
International Nuclear Information System (INIS)
Challenger, Joseph D; McKane, Alan J; Pahle, Jürgen
2012-01-01
The ability to quantify the stochastic fluctuations present in biochemical and other systems is becoming increasing important. Analytical descriptions of these fluctuations are attractive, as stochastic simulations are computationally expensive. Building on previous work, a linear noise approximation is developed for biochemical models with many compartments, for example cells. The procedure is then implemented in the software package COPASI. This technique is illustrated with two simple examples and is then applied to a more realistic biochemical model. Expressions for the noise, given in the form of covariance matrices, are presented. (paper)
Gene regulation and noise reduction by coupling of stochastic processes
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Gene regulation and noise reduction by coupling of stochastic processes.
Ramos, Alexandre F; Hornos, José Eduardo M; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Colom, Roberto; Quiroga, Ma Angeles
2009-08-01
Some studies show positive correlations between intraindividual variability in elementary speed measures (reflecting processing efficiency) and individual differences in neuroticism (reflecting instability in behaviour). The so-called neural noise hypothesis assumes that higher levels of noise are related both to smaller indices of processing efficiency and greater levels of neuroticism. Here, we test this hypothesis measuring mental speed by means of three elementary cognitive tasks tapping similar basic processes but varying systematically their content (verbal, numerical, and spatial). Neuroticism and intelligence are also measured. The sample comprised 196 undergraduate psychology students. The results show that (1) processing efficiency is generally unrelated to individual differences in neuroticism, (2) processing speed and efficiency correlate with intelligence, and (3) only the efficiency index is genuinely related to intelligence when the colinearity between speed and efficiency is controlled.
Selection of noise parameters for Kalman filter
Institute of Scientific and Technical Information of China (English)
Ka-Veng Yuen; Ka-In Hoi; Kai-Meng Mok
2007-01-01
The Bayesian probabilistic approach is proposed to estimate the process noise and measurement noise parameters for a Kalman filter. With state vectors and covariance matrices estimated by the Kalman filter, the likehood of the measurements can be constructed as a function of the process noise and measurement noise parameters. By maximizing the likklihood function with respect to these noise parameters, the optimal values can be obtained. Furthermore, the Bayesian probabilistic approach allows the associated uncertainty to be quantified. Examples using a single-degree-of-freedom system and a ten-story building illustrate the proposed method. The effect on the performance of the Kalman filter due to the selection of the process noise and measurement noise parameters was demonstrated. The optimal values of the noise parameters were found to be close to the actual values in the sense that the actual parameters were in the region with significant probability density. Through these examples, the Bayesian approach was shown to have the capability to provide accurate estimates of the noise parameters of the Kalman filter, and hence for state estimation.
Naguib, M.; Van Oers, K.; Braakhuis, A.; Griffioen, M.; De Goede, P.; Waas, J.R.
2013-01-01
Anthropogenic noise can have serious implications for animals, especially when they communicate acoustically. Yet, the impacts of noise may depend not only on noise characteristics but also on an individual's coping style or personality. We tested whether noise is more disturbing if it masks
Weak lensing of the cosmic microwave background: Power spectrum covariance
International Nuclear Information System (INIS)
Cooray, Asantha
2002-01-01
We discuss the non-Gaussian contribution to the power spectrum covariance of cosmic microwave background (CMB) anisotropies resulting through weak gravitational lensing angular deflections and the correlation of deflections with secondary sources of temperature fluctuations generated by the large scale structure, such as the integrated Sachs-Wolfe effect and the Sunyaev-Zel'dovich effect. This additional contribution to the covariance of binned angular power spectrum, beyond the well known cosmic variance and any associated instrumental noise, results from a trispectrum, or a four point correlation function, in temperature anisotropy data. With substantially wide bins in multipole space, the resulting non-Gaussian contribution from lensing to the binned power spectrum variance is insignificant out to multipoles of a few thousand and is not likely to affect the cosmological parameter estimation with acoustic peaks and the damping tail. The non-Gaussian contribution to covariance, however, should be considered when interpreting binned CMB power spectrum measurements at multipoles of a few thousand corresponding to angular scales of few arcminutes and less
Lee, Paul H
2016-08-01
This study aims to show that under several assumptions, in randomized controlled trials (RCTs), unadjusted, crude analysis will underestimate the Cohen's d effect size of the treatment, and an unbiased estimate of effect size can be obtained only by adjusting for all predictors of the outcome. Four simulations were performed to examine the effects of adjustment on the estimated effect size of the treatment and power of the analysis. In addition, we analyzed data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (older adults aged 65-94), an RCT with three treatment arms and one control arm. We showed that (1) the number of unadjusted covariates was associated with the effect size of the treatment; (2) the biasedness of effect size estimation was minimized if all covariates were adjusted for; (3) the power of the statistical analysis slightly decreased with the number of adjusted noise variables; and (4) exhaustively searching the covariates and noise variables adjusted for can lead to exaggeration of the true effect size. Analysis of the ACTIVE study data showed that the effect sizes adjusting for covariates of all three treatments were 7.39-24.70% larger than their unadjusted counterparts, whereas the effect size would be elevated by at most 57.92% by exhaustively searching the variables adjusted for. All covariates of the outcome in RCTs should be adjusted for, and if the effect of a particular variable on the outcome is unknown, adjustment will do more good than harm. Copyright © 2016 Elsevier Inc. All rights reserved.
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
International Nuclear Information System (INIS)
Oblozinsky, P.; Oblozinsky, P.; Mattoon, C.M.; Herman, M.; Mughabghab, S.F.; Pigni, M.T.; Talou, P.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Young, P.G
2009-01-01
Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10 -5 eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: 23 Na and 55 Mn where more detailed evaluation was done; improvements in major structural materials 52 Cr, 56 Fe and 58 Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for 23 Na and 56 Fe. LANL contributed improved covariance data for 235 U and 239 Pu including prompt neutron fission spectra and completely new evaluation for 240 Pu. New R-matrix evaluation for 16 O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.
2015-05-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.; Kleiber, William
2015-01-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Directory of Open Access Journals (Sweden)
Changgan SHU
2014-09-01
Full Text Available In the standard root multiple signal classification algorithm, the performance of direction of arrival estimation will reduce and even lose effect in circumstances that a low signal noise ratio and a small signals interval. By reconstructing and weighting the covariance matrix of received signal, the modified algorithm can provide more accurate estimation results. The computer simulation and performance analysis are given next, which show that under the condition of lower signal noise ratio and stronger correlation between signals, the proposed modified algorithm could provide preferable azimuth estimating performance than the standard method.
Neher, Tobias; Wagener, Kirsten C; Fischer, Rosa-Linde
2016-09-01
A better understanding of individual differences in hearing aid (HA) outcome is a prerequisite for more personalized HA fittings. Currently, knowledge of how different user factors relate to response to directional processing (DIR) and noise reduction (NR) is sparse. To extend a recent study linking preference for DIR and NR to pure-tone average hearing thresholds (PTA) and cognitive factors by investigating if (1) equivalent links exist for different types of DIR and NR, (2) self-reported noise sensitivity and personality can account for additional variability in preferred DIR and NR settings, and (3) spatial target speech configuration interacts with individual DIR preference. Using a correlational study design, overall preference for different combinations of DIR and NR programmed into a commercial HA was assessed in a complex speech-in-noise situation and related to PTA, cognitive function, and different personality traits. Sixty experienced HA users aged 60-82 yr with controlled variation in PTA and working memory capacity took part in this study. All of them had participated in the earlier study, as part of which they were tested on a measure of "executive control" tapping into cognitive functions such as working memory, mental flexibility, and selective attention. Six HA settings based on unilateral (within-device) or bilateral (across-device) DIR combined with inactive, moderate, or strong single-microphone NR were programmed into a pair of behind-the-ear HAs together with individually prescribed amplification. Overall preference was assessed using a free-field simulation of a busy cafeteria situation with either a single frontal talker or two talkers at ±30° azimuth as the target speech. In addition, two questionnaires targeting noise sensitivity and the "Big Five" personality traits were administered. Data were analyzed using multiple regression analyses and repeated-measures analyses of variance with a focus on potential interactions between the HA
Effects of background noise on total noise annoyance
Willshire, K. F.
1987-01-01
Two experiments were conducted to assess the effects of combined community noise sources on annoyance. The first experiment baseline relationships between annoyance and noise level for three community noise sources (jet aircraft flyovers, traffic and air conditioners) presented individually. Forty eight subjects evaluated the annoyance of each noise source presented at four different noise levels. Results indicated the slope of the linear relationship between annoyance and noise level for the traffic noise was significantly different from that of aircraft and of air conditioner noise, which had equal slopes. The second experiment investigated annoyance response to combined noise sources, with aircraft noise defined as the major noise source and traffic and air conditioner noise as background noise sources. Effects on annoyance of noise level differences between aircraft and background noise for three total noise levels and for both background noise sources were determined. A total of 216 subjects were required to make either total or source specific annoyance judgements, or a combination of the two, for a wide range of combined noise conditions.
Universal correlations and power-law tails in financial covariance matrices
Akemann, G.; Fischmann, J.; Vivo, P.
2010-07-01
We investigate whether quantities such as the global spectral density or individual eigenvalues of financial covariance matrices can be best modelled by standard random matrix theory or rather by its generalisations displaying power-law tails. In order to generate individual eigenvalue distributions a chopping procedure is devised, which produces a statistical ensemble of asset-price covariances from a single instance of financial data sets. Local results for the smallest eigenvalue and individual spacings are very stable upon reshuffling the time windows and assets. They are in good agreement with the universal Tracy-Widom distribution and Wigner surmise, respectively. This suggests a strong degree of robustness especially in the low-lying sector of the spectra, most relevant for portfolio selections. Conversely, the global spectral density of a single covariance matrix as well as the average over all unfolded nearest-neighbour spacing distributions deviate from standard Gaussian random matrix predictions. The data are in fair agreement with a recently introduced generalised random matrix model, with correlations showing a power-law decay.
Park, Woon Ju; Schauder, Kimberly B; Zhang, Ruyuan; Bennetto, Loisa; Tadin, Duje
2017-12-14
An emerging hypothesis postulates that internal noise is a key factor influencing perceptual abilities in autism spectrum disorder (ASD). Given fundamental and inescapable effects of noise on nearly all aspects of neural processing, this could be a critical abnormality with broad implications for perception, behavior, and cognition. However, this proposal has been challenged by both theoretical and empirical studies. A crucial question is whether and how internal noise limits perception in ASD, independently from other sources of perceptual inefficiency, such as the ability to filter out external noise. Here, we separately estimated internal noise and external noise filtering in ASD. In children and adolescents with and without ASD, we computationally modeled individuals' visual orientation discrimination in the presence of varying levels of external noise. The results revealed increased internal noise and worse external noise filtering in individuals with ASD. For both factors, we also observed high inter-individual variability in ASD, with only the internal noise estimates significantly correlating with severity of ASD symptoms. We provide evidence for reduced perceptual efficiency in ASD that is due to both increased internal noise and worse external noise filtering, while highlighting internal noise as a possible contributing factor to variability in ASD symptoms.
Contributions to Large Covariance and Inverse Covariance Matrices Estimation
Kang, Xiaoning
2016-01-01
Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimat...
Kisil, Vladimir V.
2010-01-01
The paper develops theory of covariant transform, which is inspired by the wavelet construction. It was observed that many interesting types of wavelets (or coherent states) arise from group representations which are not square integrable or vacuum vectors which are not admissible. Covariant transform extends an applicability of the popular wavelets construction to classic examples like the Hardy space H_2, Banach spaces, covariant functional calculus and many others. Keywords: Wavelets, cohe...
An alternative covariance estimator to investigate genetic heterogeneity in populations.
Heslot, Nicolas; Jannink, Jean-Luc
2015-11-26
For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative
Directory of Open Access Journals (Sweden)
Pablo Gregori
2014-03-01
Full Text Available This paper represents a survey of recent advances in modeling of space or space-time Gaussian Random Fields (GRF, tools of Geostatistics at hand for the understanding of special cases of noise in image analysis. They can be used when stationarity or isotropy are unrealistic assumptions, or even when negative covariance between some couples of locations are evident. We show some strategies in order to escape from these restrictions, on the basis of rich classes of well known stationary or isotropic non negative covariance models, and through suitable operations, like linear combinations, generalized means, or with particular Fourier transforms.
Time-Distance Helioseismology: Noise Estimation
Gizon, L.; Birch, A. C.
2004-10-01
As in global helioseismology, the dominant source of noise in time-distance helioseismology measurements is realization noise due to the stochastic nature of the excitation mechanism of solar oscillations. Characterizing noise is important for the interpretation and inversion of time-distance measurements. In this paper we introduce a robust definition of travel time that can be applied to very noisy data. We then derive a simple model for the full covariance matrix of the travel-time measurements. This model depends only on the expectation value of the filtered power spectrum and assumes that solar oscillations are stationary and homogeneous on the solar surface. The validity of the model is confirmed through comparison with SOHO MDI measurements in a quiet-Sun region. We show that the correlation length of the noise in the travel times is about half the dominant wavelength of the filtered power spectrum. We also show that the signal-to-noise ratio in quiet-Sun travel-time maps increases roughly as the square root of the observation time and is at maximum for a distance near half the length scale of supergranulation.
Solid-state NMR covariance of homonuclear correlation spectra.
Hu, Bingwen; Amoureux, Jean-Paul; Trebosc, Julien; Deschamps, Michael; Tricot, Gregory
2008-04-07
Direct covariance NMR spectroscopy, which does not involve a Fourier transformation along the indirect dimension, is demonstrated to obtain homonuclear correlation two-dimensional (2D) spectra in the solid state. In contrast to the usual 2D Fourier transform (2D-FT) NMR, in a 2D covariance (2D-Cov) spectrum the spectral resolution in the indirect dimension is determined by the resolution along the detection dimension, thereby largely reducing the time-consuming indirect sampling requirement. The covariance method does not need any separate phase correction or apodization along the indirect dimension because it uses those applied in the detection dimension. We compare in detail the specifications obtained with 2D-FT and 2D-Cov, for narrow and broad resonances. The efficiency of the covariance data treatment is demonstrated in organic and inorganic samples that are both well crystallized and amorphous, for spin -1/2 nuclei with 13C, 29Si, and 31P through-space or through-bond homonuclear 2D correlation spectra. In all cases, the experimental time has been reduced by at least a factor of 10, without any loss of resolution and signal to noise ratio, with respect to what is necessary with the 2D-FT NMR. According to this method, we have been able to study the silicate network of glasses by 2D NMR within reasonable experimental time despite the very long relaxation time of the 29Si nucleus. The main limitation of the 2D-Cov data treatment is related to the introduction of autocorrelated peaks onto the diagonal, which does not represent any actual connectivity.
Are your covariates under control? How normalization can re-introduce covariate effects.
Pain, Oliver; Dudbridge, Frank; Ronald, Angelica
2018-04-30
Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.
Directory of Open Access Journals (Sweden)
Stephanie Rosemann
2017-06-01
Full Text Available Noise-vocoded speech is commonly used to simulate the sensation after cochlear implantation as it consists of spectrally degraded speech. High individual variability exists in learning to understand both noise-vocoded speech and speech perceived through a cochlear implant (CI. This variability is partly ascribed to differing cognitive abilities like working memory, verbal skills or attention. Although clinically highly relevant, up to now, no consensus has been achieved about which cognitive factors exactly predict the intelligibility of speech in noise-vocoded situations in healthy subjects or in patients after cochlear implantation. We aimed to establish a test battery that can be used to predict speech understanding in patients prior to receiving a CI. Young and old healthy listeners completed a noise-vocoded speech test in addition to cognitive tests tapping on verbal memory, working memory, lexicon and retrieval skills as well as cognitive flexibility and attention. Partial-least-squares analysis revealed that six variables were important to significantly predict vocoded-speech performance. These were the ability to perceive visually degraded speech tested by the Text Reception Threshold, vocabulary size assessed with the Multiple Choice Word Test, working memory gauged with the Operation Span Test, verbal learning and recall of the Verbal Learning and Retention Test and task switching abilities tested by the Comprehensive Trail-Making Test. Thus, these cognitive abilities explain individual differences in noise-vocoded speech understanding and should be considered when aiming to predict hearing-aid outcome.
Portfolio management using realized covariances: Evidence from Brazil
Directory of Open Access Journals (Sweden)
João F. Caldeira
2017-09-01
Full Text Available It is often argued that intraday returns can be used to construct covariance estimates that are more accurate than those based on daily returns. However, it is still unclear whether high frequency data provide more precise covariance estimates in markets more contaminated from microstructure noise such as higher bid-ask spreads and lower liquidity. We address this question by investigating the benefits of using high frequency data in the Brazilian equities market to construct optimal minimum variance portfolios. We implement alternative realized covariance estimators based on intraday returns sampled at alternative frequencies and obtain their dynamic versions using a multivariate GARCH framework. Our evidence based on a high-dimensional data set suggests that realized covariance estimators performed significantly better from an economic point of view in comparison to standard estimators based on low-frequency (close-to-close data as they delivered less risky portfolios. Resumo: Argumenta-se frequentemente que retornos intradiários podem ser usados para construir estimativas de covariâncias mais precisas em relação àquelas obtidas com retornos diários. No entanto, ainda não está claro se os dados de alta freqüência fornecem estimativas de covariância mais precisas em mercados mais contaminados pelo ruído da microestrutura, como maiores spreads entre ofertas de compra e venda e baixa liquidez. Abordamos essa questão investigando os benefícios do uso de dados de alta freqüência no mercado de ações brasileiro através da construção de portfólios ótimos de variância mínima. Implementamos diversos estimadores de covariâncias realizadas com base em retornos intradiários amostrados em diferentes frequências e obtemos suas versões dinâmicas usando uma estrutura GARCH multivariada. Nossa evidência baseada em um conjunto de dados de alta dimensão sugere que os estimadores de covariâncias realizadas obtiveram um desempenho
International Nuclear Information System (INIS)
Kawano, Toshihiko; Shibata, Keiichi.
1997-09-01
A covariance evaluation system for the evaluated nuclear data library was established. The parameter estimation method and the least squares method with a spline function are used to generate the covariance data. Uncertainties of nuclear reaction model parameters are estimated from experimental data uncertainties, then the covariance of the evaluated cross sections is calculated by means of error propagation. Computer programs ELIESE-3, EGNASH4, ECIS, and CASTHY are used. Covariances of 238 U reaction cross sections were calculated with this system. (author)
Asymptotic theory for the sample covariance matrix of a heavy-tailed multivariate time series
DEFF Research Database (Denmark)
Davis, Richard A.; Mikosch, Thomas Valentin; Pfaffel, Olivier
2016-01-01
In this paper we give an asymptotic theory for the eigenvalues of the sample covariance matrix of a multivariate time series. The time series constitutes a linear process across time and between components. The input noise of the linear process has regularly varying tails with index α∈(0,4) in...... particular, the time series has infinite fourth moment. We derive the limiting behavior for the largest eigenvalues of the sample covariance matrix and show point process convergence of the normalized eigenvalues. The limiting process has an explicit form involving points of a Poisson process and eigenvalues...... of a non-negative definite matrix. Based on this convergence we derive limit theory for a host of other continuous functionals of the eigenvalues, including the joint convergence of the largest eigenvalues, the joint convergence of the largest eigenvalue and the trace of the sample covariance matrix...
Zhong, Tao; Chung, Pak-Kwong; Liu, Jing Dong
2018-02-01
Independent from noise exposure, noise sensitivity plays a pivotal role in people's noise annoyance perception and concomitant health deteriorations. The present study empirically investigated the psychometric properties of the Chinese version of the Weinstein Noise Sensitivity Scale-Short Form (CNSS-SF), the widely used inventory measuring individual differences in noise perception. In total, 373 Chinese participants (age = 21.41 ± 3.36) completed the online, anonymous questionnaire package. Examination of the CNSS-SF's reliability (internal consistency), factorial validity through validation and cross-validation, nomological validity and measurement invariance across gender groups were undertaken. The Cronbach alpha coefficients and composite reliabilities indicated sufficient reliability of the CNSS-SF. Two confirmatory factor analyses (CFA), in two randomly partitioned groups of participants, substantiated the factorial validity of the scale. The nomological validity of the scale was also corroborated by the significant positive association of its score with the trait anxiety score. Measurement invariance of the CNSS-SF was also found across genders via multi-group CFA. Though not without limitations, findings from the present research provide promising evidence for the utility of the scale in measuring noise sensitivity among the Chinese population. The availability of the CNSS-SF can promote research related to environmental noise and health in China, as well as facilitate cross-cultural comparisons. Copyright © 2018 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.
Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C
2017-08-01
One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
On the algebraic structure of covariant anomalies and covariant Schwinger terms
International Nuclear Information System (INIS)
Kelnhofer, G.
1992-01-01
A cohomological characterization of covariant anomalies and covariant Schwinger terms in an anomalous Yang-Mills theory is formulated and w ill be geometrically interpreted. The BRS and anti-BRS transformations are defined as purely differential geometric objects. Finally the covariant descent equations are formulated within this context. (author)
Preconditioner-free Wiener filtering with a dense noise matrix
Huffenberger, Kevin M.
2018-05-01
This work extends the Elsner & Wandelt (2013) iterative method for efficient, preconditioner-free Wiener filtering to cases in which the noise covariance matrix is dense, but can be decomposed into a sum whose parts are sparse in convenient bases. The new method, which uses multiple messenger fields, reproduces Wiener-filter solutions for test problems, and we apply it to a case beyond the reach of the Elsner & Wandelt (2013) method. We compute the Wiener-filter solution for a simulated Cosmic Microwave Background (CMB) map that contains spatially varying, uncorrelated noise, isotropic 1/f noise, and large-scale horizontal stripes (like those caused by atmospheric noise). We discuss simple extensions that can filter contaminated modes or inverse-noise-filter the data. These techniques help to address complications in the noise properties of maps from current and future generations of ground-based Microwave Background experiments, like Advanced ACTPol, Simons Observatory, and CMB-S4.
A class of covariate-dependent spatiotemporal covariance functions
Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.
2014-01-01
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
ENDF-6 File 30: Data covariances obtained from parameter covariances and sensitivities
International Nuclear Information System (INIS)
Muir, D.W.
1989-01-01
File 30 is provided as a means of describing the covariances of tabulated cross sections, multiplicities, and energy-angle distributions that result from propagating the covariances of a set of underlying parameters (for example, the input parameters of a nuclear-model code), using an evaluator-supplied set of parameter covariances and sensitivities. Whenever nuclear data are evaluated primarily through the application of nuclear models, the covariances of the resulting data can be described very adequately, and compactly, by specifying the covariance matrix for the underlying nuclear parameters, along with a set of sensitivity coefficients giving the rate of change of each nuclear datum of interest with respect to each of the model parameters. Although motivated primarily by these applications of nuclear theory, use of File 30 is not restricted to any one particular evaluation methodology. It can be used to describe data covariances of any origin, so long as they can be formally separated into a set of parameters with specified covariances and a set of data sensitivities
Energy Technology Data Exchange (ETDEWEB)
Greco, Johnny P. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ (United States); Brandt, Timothy D. [Institute for Advanced Study, Princeton, NJ (United States)
2016-12-20
The recovery of an exoplanet’s atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from the Gemini Planet Imager (GPI) early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the χ {sup 2} per degree of freedom to unity; the input parameters then fall outside the 95% confidence regions in as many as ∼80% of noise realizations. The biases we observe can approach the typical levels of precision achieved in high-contrast spectroscopy. Accounting for realistic priors in fully Bayesian retrievals can also have a significant impact on the inferred parameters. Plausible priors on effective temperature and surface gravity can vary by an order of magnitude across the confidence regions appropriate for objects with weak age constraints; priors for objects with good age constraints are dominated by modeling uncertainties. Our methods are directly applicable to existing high-contrast IFSs including GPI and SPHERE, as well as upcoming instruments like CHARIS and, ultimately, WFIRST-AFTA.
Summary of the benchmark test on artificial noise data
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J.E.; Ciftcioglu, O.; Dam, H. van
1988-01-01
A survey is given of the SMORN-V artificial noise benchmark test for checking autoregressive modelling of noise and testing anomaly detection methods. A detailed description of the system used to generate the signals is given. Contributions from 7 participants have been received. Not all participants executed both the tests on the stationary data and the anomaly data. Comparison of plots of transfer functions, noise contribution ratios and the spectrum of a noise source obtained from AR-analysis partly shows satisfactory agreement (except for normalization), partly distinct disagreement. This was also the case for the several parameters to be determined numerically. The covariance matrices of the intrinsic noise sources showed considerable differences. Participants dealing with the anomaly data used very different methods for anomaly detection. Two of them detected both anomalies present in the signals. One participant the first anomaly and the other participant the second anomaly only.
Summary of the benchmark test on artificial noise data
International Nuclear Information System (INIS)
Hoogenboom, J.E.; Ciftcioglu, O.; Dam, H. van
1988-01-01
A survey is given of the SMORN-V artificial noise benchmark test for checking autoregressive modelling of noise and testing anomaly detection methods. A detailed description of the system used to generate the signals is given. Contributions from 7 participants have been received. Not all participants executed both the tests on the stationary data and the anomaly data. Comparison of plots of transfer functions, noise contribution ratios and the spectrum of a noise source obtained from AR-analysis partly shows satisfactory agreement (except for normalization), partly distinct disagreement. This was also the case for the several parameters to be determined numerically. The covariance matrices of the intrinsic noise sources showed considerable differences. Participants dealing with the anomaly data used very different methods for anomaly detection. Two of them detected both anomalies present in the signals. One participant the first anomaly and the other participant the second anomaly only. (author)
Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game
Zai, Dawei; Li, Jonathan; Guo, Yulan; Cheng, Ming; Huang, Pengdi; Cao, Xiaofei; Wang, Cheng
2017-12-01
It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework.
Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z
2015-11-01
Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Székely, Gábor J.; Rizzo, Maria L.
2010-01-01
Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...
Irgens-Hansen, Kaja; Gundersen, Hilde; Sunde, Erlend; Baste, Valborg; Harris, Anette; Bråtveit, Magne; Moen, Bente E
2015-01-01
Prior research shows that work on board vessels of the Royal Norwegian Navy (RNoN) is associated with noise exposure levels above recommended standards. Further, noise exposure has been found to impair cognitive performance in environmental, occupational, and experimental settings, although prior research in naval and maritime settings is sparse. The aim of this study was to evaluate cognitive performance after exposure to noise among personnel working on board vessels in the RNoN. Altogether 87 Navy personnel (80 men, 7 women; 31 ± 9 years) from 24 RNoN vessels were included. Noise exposure was recorded by personal noise dosimeters at a minimum of 4 h prior to testing, and categorized into 4 groups for the analysis: 85.2 dB(A). The participants performed a visual attention test based on the Posner cue-target paradigm. Multivariable general linear model (GLM) analyses were performed to analyze whether noise exposure was associated with response time (RT) when adjusting for the covariates age, alertness, workload, noise exposure in test location, sleep the night before testing, use of hearing protection device (HPD), and percentage of errors. When adjusting for covariates, RT was significantly increased among personnel exposed to >85.2 dB(A) and 77.1-85.2 dB(A) compared to personnel exposed to <72.6 dB(A).
Noise exposure and cognitive performance: A study on personnel on board Royal Norwegian Navy vessels
Directory of Open Access Journals (Sweden)
Kaja Irgens-Hansen
2015-01-01
Full Text Available Prior research shows that work on board vessels of the Royal Norwegian Navy (RNoN is associated with noise exposure levels above recommended standards. Further, noise exposure has been found to impair cognitive performance in environmental, occupational, and experimental settings, although prior research in naval and maritime settings is sparse. The aim of this study was to evaluate cognitive performance after exposure to noise among personnel working on board vessels in the RNoN. Altogether 87 Navy personnel (80 men, 7 women; 31 ± 9 years from 24 RNoN vessels were included. Noise exposure was recorded by personal noise dosimeters at a minimum of 4 h prior to testing, and categorized into 4 groups for the analysis: 85.2 dB(A. The participants performed a visual attention test based on the Posner cue-target paradigm. Multivariable general linear model (GLM analyses were performed to analyze whether noise exposure was associated with response time (RT when adjusting for the covariates age, alertness, workload, noise exposure in test location, sleep the night before testing, use of hearing protection device (HPD, and percentage of errors. When adjusting for covariates, RT was significantly increased among personnel exposed to >85.2 dB(A and 77.1-85.2 dB(A compared to personnel exposed to <72.6 dB(A.
Cross-covariance based global dynamic sensitivity analysis
Shi, Yan; Lu, Zhenzhou; Li, Zhao; Wu, Mengmeng
2018-02-01
For identifying the cross-covariance source of dynamic output at each time instant for structural system involving both input random variables and stochastic processes, a global dynamic sensitivity (GDS) technique is proposed. The GDS considers the effect of time history inputs on the dynamic output. In the GDS, the cross-covariance decomposition is firstly developed to measure the contribution of the inputs to the output at different time instant, and an integration of the cross-covariance change over the specific time interval is employed to measure the whole contribution of the input to the cross-covariance of output. Then, the GDS main effect indices and the GDS total effect indices can be easily defined after the integration, and they are effective in identifying the important inputs and the non-influential inputs on the cross-covariance of output at each time instant, respectively. The established GDS analysis model has the same form with the classical ANOVA when it degenerates to the static case. After degeneration, the first order partial effect can reflect the individual effects of inputs to the output variance, and the second order partial effect can reflect the interaction effects to the output variance, which illustrates the consistency of the proposed GDS indices and the classical variance-based sensitivity indices. The MCS procedure and the Kriging surrogate method are developed to solve the proposed GDS indices. Several examples are introduced to illustrate the significance of the proposed GDS analysis technique and the effectiveness of the proposed solution.
Covariant representations of nuclear *-algebras
International Nuclear Information System (INIS)
Moore, S.M.
1978-01-01
Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations
Small, Robert J.; Brost, Brian M.; Hooten, Mevin B.; Castellote, Manuel; Mondragon, Jeffrey
2017-01-01
The population of beluga whales in Cook Inlet, Alaska, USA, declined by nearly half in the mid-1990s, primarily from an unsustainable harvest, and was listed as endangered in 2008. In 2014, abundance was ~340 whales, and the population trend during 1999-2014 was -1.3% yr-1. Cook Inlet beluga whales are particularly vulnerable to anthropogenic impacts, and noise that has the potential to reduce communication and echolocation range considerably has been documented in critical habitat; thus, noise was ranked as a high potential threat in the Cook Inlet beluga Recovery Plan. The current recovery strategy includes research on effects of threats potentially limiting recovery, and thus we examined the potential impact of anthropogenic noise in critical habitat, specifically, spatial displacement. Using a subset of data on anthropogenic noise and beluga detections from a 5 yr acoustic study, we evaluated the influence of noise events on beluga occupancy probability. We used occupancy models, which account for factors that affect detection probability when estimating occupancy, the first application of these models to examine the potential impacts of anthropogenic noise on marine mammal behavior. Results were inconclusive, primarily because beluga detections were relatively infrequent. Even though noise metrics (sound pressure level and noise duration) appeared in high-ranking models as covariates for occupancy probability, the data were insufficient to indicate better predictive ability beyond those models that only included environmental covariates. Future studies that implement protocols designed specifically for beluga occupancy will be most effective for accurately estimating the effect of noise on beluga displacement.
Wang, Jun-Sheng; Yang, Guang-Hong
2017-07-25
This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.
Directory of Open Access Journals (Sweden)
Shlomit Farkash-Amar
2014-03-01
Full Text Available To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.
On the regularity of the covariance matrix of a discretized scalar field on the sphere
Energy Technology Data Exchange (ETDEWEB)
Bilbao-Ahedo, J.D. [Departamento de Física Moderna, Universidad de Cantabria, Av. los Castros s/n, 39005 Santander (Spain); Barreiro, R.B.; Herranz, D.; Vielva, P.; Martínez-González, E., E-mail: bilbao@ifca.unican.es, E-mail: barreiro@ifca.unican.es, E-mail: herranz@ifca.unican.es, E-mail: vielva@ifca.unican.es, E-mail: martinez@ifca.unican.es [Instituto de Física de Cantabria (CSIC-UC), Av. los Castros s/n, 39005 Santander (Spain)
2017-02-01
We present a comprehensive study of the regularity of the covariance matrix of a discretized field on the sphere. In a particular situation, the rank of the matrix depends on the number of pixels, the number of spherical harmonics, the symmetries of the pixelization scheme and the presence of a mask. Taking into account the above mentioned components, we provide analytical expressions that constrain the rank of the matrix. They are obtained by expanding the determinant of the covariance matrix as a sum of determinants of matrices made up of spherical harmonics. We investigate these constraints for five different pixelizations that have been used in the context of Cosmic Microwave Background (CMB) data analysis: Cube, Icosahedron, Igloo, GLESP and HEALPix, finding that, at least in the considered cases, the HEALPix pixelization tends to provide a covariance matrix with a rank closer to the maximum expected theoretical value than the other pixelizations. The effect of the propagation of numerical errors in the regularity of the covariance matrix is also studied for different computational precisions, as well as the effect of adding a certain level of noise in order to regularize the matrix. In addition, we investigate the application of the previous results to a particular example that requires the inversion of the covariance matrix: the estimation of the CMB temperature power spectrum through the Quadratic Maximum Likelihood algorithm. Finally, some general considerations in order to achieve a regular covariance matrix are also presented.
A simple procedure to estimate reactivity with good noise filtering characteristics
International Nuclear Information System (INIS)
Shimazu, Yoichiro
2014-01-01
Highlights: • A new and simple on-line reactivity estimation method is proposed. • The estimator has robust noise filtering characteristics. • The noise filtering is equivalent to those of conventional reactivity meters. • The new estimator eliminates the burden of selecting optimum filter constants. • The new estimation performance is assessed without and with measurement noise. - Abstract: A new and simple on-line reactivity estimation method is proposed. The estimator has robust noise filtering characteristics without the use of complex filters. The noise filtering capability is equivalent to or better than that of a conventional estimator based on Inverse Point Kinetics (IPK). The new estimator can also eliminate the burden of selecting optimum filter time constants, such as would be required for the IPK-based estimator, or noise covariance matrices, which are needed if the extended Kalman filter (EKF) technique is used. In this paper, the new estimation method is introduced and its performance assessed without and with measurement noise
Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang
2018-05-08
When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.
Small fluctuations in epitaxial growth via conservative noise
International Nuclear Information System (INIS)
Patrone, Paul N; Wang Rongrong; Margetis, Dionisios
2011-01-01
We study the combined effect of growth (material deposition from above) and nearest-neighbor entropic and force-dipole interactions in a stochastically perturbed system of N line defects (steps) on a vicinal crystal surface in 1+1 dimensions. First, we formulate a general model of conservative white noise and derive simplified formulas for the terrace width distribution and terrace width correlations in the limit N → ∞ for small step fluctuations. Our general result expresses terrace width correlations as an interplay of noise covariance and step interaction strength. Second, we apply our formalism to two specific noise models which stem, respectively, from (i) the fluctuation-dissipation theorem for diffusion of adsorbed atoms; and (ii) the phenomenological consideration of deposition-flux-induced asymmetric attachment and detachment of atoms at step edges. In both cases of noise, we find that terrace width correlations decay exponentially with the step number difference; this behavior leads to vanishing correlations in the macroscopic limit. Our analysis may be used to (i) determine the noise in quasi-one-dimensional surfaces and (ii) assess the validity of previous mean field approximations.
Using machine learning to assess covariate balance in matching studies.
Linden, Ariel; Yarnold, Paul R
2016-12-01
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.
Yoneoka, Daisuke; Henmi, Masayuki
2017-06-01
Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Knospe, Steffen H G
2010-04-01
We study anisotropic spatial autocorrelation in differential synthetic aperture radar interferometric (dInSAR) measurements and its impact on geophysical parameter estimations. The dInSAR phase acquired by the satellite sensor is a superposition of different contributions, and when studying geophysical processes, we are usually only interested in the surface deformation part of the signal. Therefore, to obtain high-quality results, we would like to characterize and/or remove other phase components. A stochastic model has been found to be appropriate to describe atmospheric phase delay in dInSAR images. However, these phase delays are usually modeled as being isotropic, which is a simplification, because InSAR images often show directional atmospheric anomalies. Here, we analyze anisotropic structures and show validation results using both real and simulated data. We calculate experimental semivariograms of the dInSAR phase in several European Remote Sensing satellite-1/2 tandem interferograms. Based on the theory of random functions (RFs), we then fit anisotropic variogram models in the spatial domain, employing Matérn-and Bessel-family correlation functions in nested models to represent complex dInSAR covariance structures. The presented covariance function types, in the statistical framework of stationary RFs, are consistent with tropospheric delay models. We find that by using anisotropic data covariance information to weight dInSAR measurements, we can significantly improve both the precision and accuracy of geophysical parameter estimations. Furthermore, the improvement is dependent on how similar the deformation pattern is to the dominant structure of the anisotropic atmospheric signals. © 2009 IEEE.
Covariant field equations in supergravity
Energy Technology Data Exchange (ETDEWEB)
Vanhecke, Bram [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium); Ghent University, Faculty of Physics, Gent (Belgium); Proeyen, Antoine van [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium)
2017-12-15
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Covariant field equations in supergravity
International Nuclear Information System (INIS)
Vanhecke, Bram; Proeyen, Antoine van
2017-01-01
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Noise mapping inside a car cabin
DEFF Research Database (Denmark)
Knudsen, Kim; Sjøj, Sidsel Marie Nørholm; Jacobsen, Finn
The mapping of noise is of considerable interest in the car industry where a good noise mapping can make it much easier to identify the sources that generate the noise and eventually reduce the individual contributions to the noise. The methods used for this purpose include delay-and-sum beamform......The mapping of noise is of considerable interest in the car industry where a good noise mapping can make it much easier to identify the sources that generate the noise and eventually reduce the individual contributions to the noise. The methods used for this purpose include delay......-and-sum beamforming and spherical harmonics beamforming. These methods have a poor spatial esolution at low frequencies, and since much noise generated in cars is dominated by low frequencies the methods are not optimal. In the present paper the mapping is done by solving an inverse problem with a transfer matrix...
Exploiting Data Sparsity In Covariance Matrix Computations on Heterogeneous Systems
Charara, Ali M.
2018-05-24
Covariance matrices are ubiquitous in computational sciences, typically describing the correlation of elements of large multivariate spatial data sets. For example, covari- ance matrices are employed in climate/weather modeling for the maximum likelihood estimation to improve prediction, as well as in computational ground-based astronomy to enhance the observed image quality by filtering out noise produced by the adap- tive optics instruments and atmospheric turbulence. The structure of these covariance matrices is dense, symmetric, positive-definite, and often data-sparse, therefore, hier- archically of low-rank. This thesis investigates the performance limit of dense matrix computations (e.g., Cholesky factorization) on covariance matrix problems as the number of unknowns grows, and in the context of the aforementioned applications. We employ recursive formulations of some of the basic linear algebra subroutines (BLAS) to accelerate the covariance matrix computation further, while reducing data traffic across the memory subsystems layers. However, dealing with large data sets (i.e., covariance matrices of billions in size) can rapidly become prohibitive in memory footprint and algorithmic complexity. Most importantly, this thesis investigates the tile low-rank data format (TLR), a new compressed data structure and layout, which is valuable in exploiting data sparsity by approximating the operator. The TLR com- pressed data structure allows approximating the original problem up to user-defined numerical accuracy. This comes at the expense of dealing with tasks with much lower arithmetic intensities than traditional dense computations. In fact, this thesis con- solidates the two trends of dense and data-sparse linear algebra for HPC. Not only does the thesis leverage recursive formulations for dense Cholesky-based matrix al- gorithms, but it also implements a novel TLR-Cholesky factorization using batched linear algebra operations to increase hardware occupancy and
Variance and covariance components for liability of piglet survival during different periods
DEFF Research Database (Denmark)
Su, G; Sorensen, D; Lund, M S
2008-01-01
Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individu...
Analysis of fMRI data using noise-diffusion network models: a new covariance-coding perspective.
Gilson, Matthieu
2018-04-01
Since the middle of the 1990s, studies of resting-state fMRI/BOLD data have explored the correlation patterns of activity across the whole brain, which is referred to as functional connectivity (FC). Among the many methods that have been developed to interpret FC, a recently proposed model-based approach describes the propagation of fluctuating BOLD activity within the recurrently connected brain network by inferring the effective connectivity (EC). In this model, EC quantifies the strengths of directional interactions between brain regions, viewed from the proxy of BOLD activity. In addition, the tuning procedure for the model provides estimates for the local variability (input variances) to explain how the observed FC is generated. Generalizing, the network dynamics can be studied in the context of an input-output mapping-determined by EC-for the second-order statistics of fluctuating nodal activities. The present paper focuses on the following detection paradigm: observing output covariances, how discriminative is the (estimated) network model with respect to various input covariance patterns? An application with the model fitted to experimental fMRI data-movie viewing versus resting state-illustrates that changes in local variability and changes in brain coordination go hand in hand.
Automatic physiological waveform processing for FMRI noise correction and analysis.
Directory of Open Access Journals (Sweden)
Daniel J Kelley
2008-03-01
Full Text Available Functional MRI resting state and connectivity studies of brain focus on neural fluctuations at low frequencies which share power with physiological fluctuations originating from lung and heart. Due to the lack of automated software to process physiological signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise, in the python language. We tested its automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistently identifies physiological fluctuations for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity.
The effects of railway noise on sleep medication intake: Results from the ALPNAP-study
Directory of Open Access Journals (Sweden)
P Lercher
2010-01-01
Full Text Available In the 1980s/90s, a number of socio-acoustic surveys and laboratory studies on railway noise effects have observed less reported disturbance/interference with sleep at the same exposure level compared with other modes of transportation. This lower grade of disturbance has received the label "railway bonus", was implemented in noise legislation in a number of European countries and was applied in planning and environmental impact assessments. However, majority of the studies investigating physiological outcomes did not find the bespoke difference. In a telephone survey (N=1643 we investigated the relationship between railway noise and sleep medication intake and the impact of railway noise events on motility parameters during night was assessed with contact-free high resolution actimetry devices. Multiple logistic regression analysis with cubic splines was applied to assess the probability of sleep medication use based on railway sound level and nine covariates. The non-linear exposure-response curve showed a statistically significant leveling off around 60 dB (A, Lden. Age, health status and trauma history were the most important covariates. The results were supported also by a similar analysis based on the indicator "night time noise annoyance". No railway bonus could be observed above 55 dB(A, Lden. In the actimetry study, the slope of rise of train noise events proved to be almost as important a predictor for motility reactions as was the maximum sound pressure level - an observation which confirms similar findings from laboratory experiments and field studies on aircraft noise and sleep disturbance. Legislation using a railway bonus will underestimate the noise impact by about 10 dB (A, Lden under the conditions comparable with those in the survey study. The choice of the noise calculation method may influence the threshold for guideline setting.
The effects of railway noise on sleep medication intake: results from the ALPNAP-study.
Lercher, P; Brink, M; Rudisser, J; Van Renterghem, T; Botteldooren, D; Baulac, M; Defrance, J
2010-01-01
In the 1980s/90s, a number of socio-acoustic surveys and laboratory studies on railway noise effects have observed less reported disturbance/interference with sleep at the same exposure level compared with other modes of transportation. This lower grade of disturbance has received the label "railway bonus", was implemented in noise legislation in a number of European countries and was applied in planning and environmental impact assessments. However, majority of the studies investigating physiological outcomes did not find the bespoke difference. In a telephone survey (N=1643) we investigated the relationship between railway noise and sleep medication intake and the impact of railway noise events on motility parameters during night was assessed with contact-free high resolution actimetry devices. Multiple logistic regression analysis with cubic splines was applied to assess the probability of sleep medication use based on railway sound level and nine covariates. The non-linear exposure-response curve showed a statistically significant leveling off around 60 dB (A), Lden. Age, health status and trauma history were the most important covariates. The results were supported also by a similar analysis based on the indicator "night time noise annoyance". No railway bonus could be observed above 55 dB(A), Lden. In the actimetry study, the slope of rise of train noise events proved to be almost as important a predictor for motility reactions as was the maximum sound pressure level - an observation which confirms similar findings from laboratory experiments and field studies on aircraft noise and sleep disturbance. Legislation using a railway bonus will underestimate the noise impact by about 10 dB (A), Lden under the conditions comparable with those in the survey study. The choice of the noise calculation method may influence the threshold for guideline setting.
DEFF Research Database (Denmark)
He, Peng; Eriksson, Frank; Scheike, Thomas H.
2016-01-01
function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight......With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution...... and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight...
Bergshoeff, E.; Pope, C.N.; Stelle, K.S.
1990-01-01
We discuss the notion of higher-spin covariance in w∞ gravity. We show how a recently proposed covariant w∞ gravity action can be obtained from non-chiral w∞ gravity by making field redefinitions that introduce new gauge-field components with corresponding new gauge transformations.
DEFF Research Database (Denmark)
Olsen, Steen Østergaard; Nielsen, Lars Holme; Lantz, Johannes
2012-01-01
The acceptable noise level (ANL) is used to quantify the amount of background noise that subjects can accept while listening to speech, and is suggested for prediction of individual hearing-aid use. The aim of this study was to assess the repeatability of the ANL measured in normal-hearing subjects...... using running Danish and non-semantic speech materials as stimuli and modulated speech-spectrum and multi-talker babble noises as competing stimuli....
DEFF Research Database (Denmark)
Olsen, Steen Østergaard; Nielsen, Lars Holme; Lantz, Johannes
2012-01-01
The acceptable noise level (ANL) is used to quantify the amount of background noise that subjects can accept while listening to speech, and is suggested for prediction of individual hearing-aid use. The aim of this study was to assess the repeatability of the ANL measured in normal-hearing subjec...... using running Danish and non-semantic speech materials as stimuli and modulated speech-spectrum and multi-talker babble noises as competing stimuli....
Directory of Open Access Journals (Sweden)
Helena Jahncke
2012-01-01
Full Text Available Hearing impaired and normal hearing individuals were compared in two within-participant office noise conditions (high noise: 60 L Aeq and low noise: 30 L Aeq . Performance, subjective fatigue, and physiological stress were tested during working on a simulated open-plan office. We also tested two between-participants restoration conditions following the work period with high noise (nature movie or continued office noise. Participants with a hearing impairment (N = 20 were matched with normal hearing participants (N = 18 and undertook one practice session and two counterbalanced experimental sessions. In each experimental session they worked for two hours with basic memory and attention tasks. We also measured physiological stress indicators (cortisol and catecholamines and self-reports of mood and fatigue. The hearing impaired participants were more affected by high noise than the normal hearing participants, as shown by impaired performance for tasks that involve recall of semantic information. The hearing impaired participants were also more fatigued by high noise exposure than participants with normal hearing, and they tended to have higher stress hormone levels during the high noise compared to the low noise condition. Restoration with a movie increased performance and motivation for the normal hearing participants, while rest with continued noise did not. For the hearing impaired participants, continued noise during rest increased motivation and performance, while the movie did not. In summary, the impact of noise and restorative conditions varied with the hearing characteristics of the participants. The small sample size does however encourage caution when interpreting the results.
International Nuclear Information System (INIS)
Andersen, B.; Jakobsen, J.
1992-11-01
Based on a previous project concerning the calculation of the amount of noise emanating from wind turbine arrays, this one examines the subject further by investigating whether there could be significant differences in the amount of noise made by individual wind turbines in an array, and whether the noise is transmitted in varying directions - so that when it is carried in the same direction as the wind blows it would appear to be louder. The aim was also to determine whether the previously used method of calculation lacked precision. It was found that differences in noise niveaux related to individual wind turbines were insignificant and that noise was not so loud when it was not borne in the direction of the wind. It was necessary to change the method of calculation as reckoning should include the influence of the terrain, wind velocity and distance. The measuring and calculation methods are exemplified and the resulting measurements are presented in detail. (AB)
Analysis and Extension of the PCA Method, Estimating a Noise Curve from a Single Image
Directory of Open Access Journals (Sweden)
Miguel Colom
2016-12-01
Full Text Available In the article 'Image Noise Level Estimation by Principal Component Analysis', S. Pyatykh, J. Hesser, and L. Zheng propose a new method to estimate the variance of the noise in an image from the eigenvalues of the covariance matrix of the overlapping blocks of the noisy image. Instead of using all the patches of the noisy image, the authors propose an iterative strategy to adaptively choose the optimal set containing the patches with lowest variance. Although the method measures uniform Gaussian noise, it can be easily adapted to deal with signal-dependent noise, which is realistic with the Poisson noise model obtained by a CMOS or CCD device in a digital camera.
Sensitivity of PPI analysis to differences in noise reduction strategies.
Barton, M; Marecek, R; Rektor, I; Filip, P; Janousova, E; Mikl, M
2015-09-30
In some fields of fMRI data analysis, using correct methods for dealing with noise is crucial for achieving meaningful results. This paper provides a quantitative assessment of the effects of different preprocessing and noise filtering strategies on psychophysiological interactions (PPI) methods for analyzing fMRI data where noise management has not yet been established. Both real and simulated fMRI data were used to assess these effects. Four regions of interest (ROIs) were chosen for the PPI analysis on the basis of their engagement during two tasks. PPI analysis was performed for 32 different preprocessing and analysis settings, which included data filtering with RETROICOR or no such filtering; different filtering of the ROI "seed" signal with a nuisance data-driven time series; and the involvement of these data-driven time series in the subsequent PPI GLM analysis. The extent of the statistically significant results was quantified at the group level using simple descriptive statistics. Simulated data were generated to assess statistical improvement of different filtering strategies. We observed that different approaches for dealing with noise in PPI analysis yield differing results in real data. In simulated data, we found RETROICOR, seed signal filtering and the addition of data-driven covariates to the PPI design matrix significantly improves results. We recommend the use of RETROICOR, and data-driven filtering of the whole data, or alternatively, seed signal filtering with data-driven signals and the addition of data-driven covariates to the PPI design matrix. Copyright © 2015 Elsevier B.V. All rights reserved.
Long-term exposure to wind turbine noise at night and risk for diabetes: A nationwide cohort study
DEFF Research Database (Denmark)
Poulsen, Aslak Harbo; Raaschou-Nielsen, Ole; Pena Diaz, Alfredo
2018-01-01
Focus on renewable energy sources and reduced unit costs has led to increased number of wind turbines (WTs). WT noise (WTN) is reported to be highly annoying at levels from 30 to 35 dB and up, whereas for traffic noise people report to be highly annoyed from 40 to 45 dB and up. This has raised...... from a WT. Using detailed data on WT type and hourly wind data at each WT position and height, we estimated hourly outdoor and low frequency indoor WTN for all dwellings, aggregated as nighttime 1- and 5-year running means. Using nationwide registries, we identified a study population of 614......,731 persons living in these dwellings in the period from 1996 to 2012, of whom 25,148 developed diabetes. Data were analysed using Poisson regression with adjustment for individual and area-levels covariates. We found no associations between long-term exposure to WTN during night and diabetes risk...
Impact of noise and air pollution on pregnancy outcomes.
Gehring, Ulrike; Tamburic, Lillian; Sbihi, Hind; Davies, Hugh W; Brauer, Michael
2014-05-01
Motorized traffic is an important source of both air pollution and community noise. While there is growing evidence for an adverse effect of ambient air pollution on reproductive health, little is known about the association between traffic noise and pregnancy outcomes. We evaluated the impact of residential noise exposure on small size for gestational age, preterm birth, term birth weight, and low birth weight at term in a population-based cohort study, for which we previously reported associations between air pollution and pregnancy outcomes. We also evaluated potential confounding of air pollution effects by noise and vice versa. Linked administrative health data sets were used to identify 68,238 singleton births (1999-2002) in Vancouver, British Columbia, Canada, with complete covariate data (sex, ethnicity, parity, birth month and year, income, and education) and maternal residential history. We estimated exposure to noise with a deterministic model (CadnaA) and exposure to air pollution using temporally adjusted land-use regression models and inverse distance weighting of stationary monitors for the entire pregnancy. Noise exposure was negatively associated with term birth weight (mean difference = -19 [95% confidence interval = -23 to -15] g per 6 dB(A)). In joint air pollution-noise models, associations between noise and term birth weight remained largely unchanged, whereas associations decreased for all air pollutants. Traffic may affect birth weight through exposure to both air pollution and noise.
Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.
Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W
2017-06-01
Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.
Evaluation and processing of covariance data
International Nuclear Information System (INIS)
Wagner, M.
1993-01-01
These proceedings of a specialists'meeting on evaluation and processing of covariance data is divided into 4 parts bearing on: part 1- Needs for evaluated covariance data (2 Papers), part 2- generation of covariance data (15 Papers), part 3- Processing of covariance files (2 Papers), part 4-Experience in the use of evaluated covariance data (2 Papers)
Covariance data processing code. ERRORJ
International Nuclear Information System (INIS)
Kosako, Kazuaki
2001-01-01
The covariance data processing code, ERRORJ, was developed to process the covariance data of JENDL-3.2. ERRORJ has the processing functions of covariance data for cross sections including resonance parameters, angular distribution and energy distribution. (author)
Directory of Open Access Journals (Sweden)
Jangho Park
2017-04-01
Full Text Available Abstract Background Excessive noise affects human health and interferes with daily activities. Although environmental noise may not directly cause mental illness, it may accelerate and intensify the development of latent mental disorders. Noise sensitivity (NS is considered a moderator of non-auditory noise effects. In the present study, we aimed to assess whether NS is associated with non-auditory effects. Methods We recruited a community sample of 1836 residents residing in Ulsan and Seoul, South Korea. From July to November 2015, participants were interviewed regarding their demographic characteristics, socioeconomic status, medical history, and NS. The non-auditory effects of noise were assessed using the Center of Epidemiologic Studies Depression, Insomnia Severity index, State Trait Anxiety Inventory state subscale, and Stress Response Inventory-Modified Form. Individual noise levels were recorded from noise maps. A three-model multivariate logistic regression analysis was performed to identify factors that might affect psychiatric illnesses. Results Participants ranged in age from 19 to 91 years (mean: 47.0 ± 16.1 years, and 37.9% (n = 696 were male. Participants with high NS were more likely to have been diagnosed with diabetes and hyperlipidemia and to use psychiatric medication. The multivariable analysis indicated that even after adjusting for noise-related variables, sociodemographic factors, medical illness, and duration of residence, subjects in the high NS group were more than 2 times more likely to experience depression and insomnia and 1.9 times more likely to have anxiety, compared with those in the low NS group. Noise exposure level was not identified as an explanatory value. Conclusions NS increases the susceptibility and hence moderates there actions of individuals to noise. NS, rather than noise itself, is associated with an elevated susceptibility to non-auditory effects.
Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems
Directory of Open Access Journals (Sweden)
Min Chul Kim
2011-10-01
Full Text Available Recently, the range of available Radio Frequency Identification (RFID tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.
Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.
Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon
2011-01-01
Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.
Kumasaka, Henry A.; Martinez, Michael M.; Weir, Donald S.
1996-01-01
This report describes the methodology for assessing the impact of component noise reduction on total airplane system noise. The methodology is intended to be applied to the results of individual study elements of the NASA-Advanced Subsonic Technology (AST) Noise Reduction Program, which will address the development of noise reduction concepts for specific components. Program progress will be assessed in terms of noise reduction achieved, relative to baseline levels representative of 1992 technology airplane/engine design and performance. In this report, the 1992 technology reference levels are defined for assessment models based on four airplane sizes - an average business jet and three commercial transports: a small twin, a medium sized twin, and a large quad. Study results indicate that component changes defined as program final goals for nacelle treatment and engine/airframe source noise reduction would achieve from 6-7 EPNdB reduction of total airplane noise at FAR 36 Stage 3 noise certification conditions for all of the airplane noise assessment models.
Moerbeek, Mirjam; van Schie, Sander
2016-07-11
The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.
Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling
2018-01-01
We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.
Pozsgay, Victor; Hirsch, Flavien; Branciard, Cyril; Brunner, Nicolas
2017-12-01
We introduce Bell inequalities based on covariance, one of the most common measures of correlation. Explicit examples are discussed, and violations in quantum theory are demonstrated. A crucial feature of these covariance Bell inequalities is their nonlinearity; this has nontrivial consequences for the derivation of their local bound, which is not reached by deterministic local correlations. For our simplest inequality, we derive analytically tight bounds for both local and quantum correlations. An interesting application of covariance Bell inequalities is that they can act as "shared randomness witnesses": specifically, the value of the Bell expression gives device-independent lower bounds on both the dimension and the entropy of the shared random variable in a local model.
Distance covariance for stochastic processes
DEFF Research Database (Denmark)
Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady
2017-01-01
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
Covariance Manipulation for Conjunction Assessment
Hejduk, M. D.
2016-01-01
The manipulation of space object covariances to try to provide additional or improved information to conjunction risk assessment is not an uncommon practice. Types of manipulation include fabricating a covariance when it is missing or unreliable to force the probability of collision (Pc) to a maximum value ('PcMax'), scaling a covariance to try to improve its realism or see the effect of covariance volatility on the calculated Pc, and constructing the equivalent of an epoch covariance at a convenient future point in the event ('covariance forecasting'). In bringing these methods to bear for Conjunction Assessment (CA) operations, however, some do not remain fully consistent with best practices for conducting risk management, some seem to be of relatively low utility, and some require additional information before they can contribute fully to risk analysis. This study describes some basic principles of modern risk management (following the Kaplan construct) and then examines the PcMax and covariance forecasting paradigms for alignment with these principles; it then further examines the expected utility of these methods in the modern CA framework. Both paradigms are found to be not without utility, but only in situations that are somewhat carefully circumscribed.
INFLUENCE OF STOCHASTIC NOISE STATISTICS ON KALMAN FILTER PERFORMANCE BASED ON VIDEO TARGET TRACKING
Institute of Scientific and Technical Information of China (English)
Chen Ken; Napolitano; Zhang Yun; Li Dong
2010-01-01
The system stochastic noises involved in Kalman filtering are preconditioned on being ideally white and Gaussian distributed. In this research,efforts are exerted on exploring the influence of the noise statistics on Kalman filtering from the perspective of video target tracking quality. The correlation of tracking precision to both the process and measurement noise covariance is investigated; the signal-to-noise power density ratio is defined; the contribution of predicted states and measured outputs to Kalman filter behavior is discussed; the tracking precision relative sensitivity is derived and applied in this study case. The findings are expected to pave the way for future study on how the actual noise statistics deviating from the assumed ones impacts on the Kalman filter optimality and degradation in the application of video tracking.
Structural covariance networks across the life span, from 6 to 94 years of age.
DuPre, Elizabeth; Spreng, R Nathan
2017-10-01
Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete life span perspective-bridging childhood with early, middle, and late adulthood-on the development of structural covariance networks. Here, we investigate the life span trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open-access data sources, we examine the structural covariance trajectories of these networks from 6 to 94 years of age in a sample of 1,580 participants. Using partial least squares, we show that structural covariance patterns across the life span exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the life span. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the life span and reveal both shared and network-specific trajectories.
Novel Diagonal Reloading Based Direction of Arrival Estimation in Unknown Non-Uniform Noise
Directory of Open Access Journals (Sweden)
Hao Zhou
2018-01-01
Full Text Available Nested array can expand the degrees of freedom (DOF from difference coarray perspective, but suffering from the performance degradation of direction of arrival (DOA estimation in unknown non-uniform noise. In this paper, a novel diagonal reloading (DR based DOA estimation algorithm is proposed using a recently developed nested MIMO array. The elements in the main diagonal of the sample covariance matrix are eliminated; next the smallest MN-K eigenvalues of the revised matrix are obtained and averaged to estimate the sum value of the signal power. Further the estimated sum value is filled into the main diagonal of the revised matrix for estimating the signal covariance matrix. In this case, the negative effect of noise is eliminated without losing the useful information of the signal matrix. Besides, the degrees of freedom are expanded obviously, resulting in the performance improvement. Several simulations are conducted to demonstrate the effectiveness of the proposed algorithm.
Study on individual stochastic model of GNSS observations for precise kinematic applications
Próchniewicz, Dominik; Szpunar, Ryszard
2015-04-01
The proper definition of mathematical positioning model, which is defined by functional and stochastic models, is a prerequisite to obtain the optimal estimation of unknown parameters. Especially important in this definition is realistic modelling of stochastic properties of observations, which are more receiver-dependent and time-varying than deterministic relationships. This is particularly true with respect to precise kinematic applications which are characterized by weakening model strength. In this case, incorrect or simplified definition of stochastic model causes that the performance of ambiguity resolution and accuracy of position estimation can be limited. In this study we investigate the methods of describing the measurement noise of GNSS observations and its impact to derive precise kinematic positioning model. In particular stochastic modelling of individual components of the variance-covariance matrix of observation noise performed using observations from a very short baseline and laboratory GNSS signal generator, is analyzed. Experimental test results indicate that the utilizing the individual stochastic model of observations including elevation dependency and cross-correlation instead of assumption that raw measurements are independent with the same variance improves the performance of ambiguity resolution as well as rover positioning accuracy. This shows that the proposed stochastic assessment method could be a important part in complex calibration procedure of GNSS equipment.
Risk factor noise - otological aspects
Energy Technology Data Exchange (ETDEWEB)
Haas, E
1984-06-11
After a short review of the anatomy and physiology of the inner ear the pathogenesis of chronic noise-induced hearing loss is discussed. The exposure to noise results first in a temporary but reversible threshold shift. But if the exposure to noise was exceedingly high or if the rest period would have required further noise reduction, a state of so-called auditory fatigue develops, finally leading to noise-induced hearing loss, a state which is considered irreversible. The noise-perception varies greatly among individuals and thus it is impossible to determine a certain noise intensity above which noise leasions will to be expected. It is generally accepted, that longterm exposure to noise above 85 dB (A) may lead to hearing loss in a portion of the exposed persons.
International Nuclear Information System (INIS)
Takada, Masahiro; Bridle, Sarah
2007-01-01
Several dark energy experiments are available from a single large-area imaging survey and may be combined to improve cosmological parameter constraints and/or test inherent systematics. Two promising experiments are cosmic shear power spectra and counts of galaxy clusters. However, the two experiments probe the same cosmic mass density field in large-scale structure, therefore the combination may be less powerful than first thought. We investigate the cross-covariance between the cosmic shear power spectra and the cluster counts based on the halo model approach, where the cross-covariance arises from the three-point correlations of the underlying mass density field. Fully taking into account the cross-covariance, as well as non-Gaussian errors on the lensing power spectrum covariance, we find a significant cross-correlation between the lensing power spectrum signals at multipoles l∼10 3 and the cluster counts containing halos with masses M∼>10 14 M o-dot . Including the cross-covariance for the combined measurement degrades and in some cases improves the total signal-to-noise (S/N) ratios up to ∼±20% relative to when the two are independent. For cosmological parameter determination, the cross-covariance has a smaller effect as a result of working in a multi-dimensional parameter space, implying that the two observables can be considered independent to a good approximation. We also discuss the fact that cluster count experiments using lensing-selected mass peaks could be more complementary to cosmic shear tomography than mass-selected cluster counts of the corresponding mass threshold. Using lensing selected clusters with a realistic usable detection threshold ((S/N) cluster ∼6 for a ground-based survey), the uncertainty on each dark energy parameter may be roughly halved by the combined experiments, relative to using the power spectra alone
Poincare covariance and κ-Minkowski spacetime
International Nuclear Information System (INIS)
Dabrowski, Ludwik; Piacitelli, Gherardo
2011-01-01
A fully Poincare covariant model is constructed as an extension of the κ-Minkowski spacetime. Covariance is implemented by a unitary representation of the Poincare group, and thus complies with the original Wigner approach to quantum symmetries. This provides yet another example (besides the DFR model), where Poincare covariance is realised a la Wigner in the presence of two characteristic dimensionful parameters: the light speed and the Planck length. In other words, a Doubly Special Relativity (DSR) framework may well be realised without deforming the meaning of 'Poincare covariance'. -- Highlights: → We construct a 4d model of noncommuting coordinates (quantum spacetime). → The coordinates are fully covariant under the undeformed Poincare group. → Covariance a la Wigner holds in presence of two dimensionful parameters. → Hence we are not forced to deform covariance (e.g. as quantum groups). → The underlying κ-Minkowski model is unphysical; covariantisation does not cure this.
DEFF Research Database (Denmark)
Hounyo, Ulrich
to a gneral class of estimators of integrated covolatility. We then show the first-order asymptotic validity of this method in the multivariate context with a potential presence of jumps, dependent microsturcture noise, irregularly spaced and non-synchronous data. Due to our focus on non...... covariance estimator. As an application of our results, we also consider the bootstrap for regression coefficients. We show that the wild blocks of bootstrap, appropriately centered, is able to mimic both the dependence and heterogeneity of the scores, thus justifying the construction of bootstrap percentile...... intervals as well as variance estimates in this context. This contrasts with the traditional pairs bootstrap which is not able to mimic the score heterogeneity even in the simple case where no microsturcture noise is present. Our Monte Carlo simulations show that the wild blocks of blocks bootstrap improves...
Physiologic correlates to background noise acceptance
Tampas, Joanna; Harkrider, Ashley; Nabelek, Anna
2004-05-01
Acceptance of background noise can be evaluated by having listeners indicate the highest background noise level (BNL) they are willing to accept while following the words of a story presented at their most comfortable listening level (MCL). The difference between the selected MCL and BNL is termed the acceptable noise level (ANL). One of the consistent findings in previous studies of ANL is large intersubject variability in acceptance of background noise. This variability is not related to age, gender, hearing sensitivity, personality, type of background noise, or speech perception in noise performance. The purpose of the current experiment was to determine if individual differences in physiological activity measured from the peripheral and central auditory systems of young female adults with normal hearing can account for the variability observed in ANL. Correlations between ANL and various physiological responses, including spontaneous, click-evoked, and distortion-product otoacoustic emissions, auditory brainstem and middle latency evoked potentials, and electroencephalography will be presented. Results may increase understanding of the regions of the auditory system that contribute to individual noise acceptance.
Lonsdorf, Tina B; Merz, Christian J
2017-09-01
Why do only some individuals develop pathological anxiety following adverse events? Fear acquisition, extinction and return of fear paradigms serve as experimental learning models for the development, treatment and relapse of anxiety. Individual differences in experimental performance were however mostly regarded as 'noise' by researchers interested in basic associative learning principles. Our work for the first time presents a comprehensive literature overview and methodological discussion on inter-individual differences in fear acquisition, extinction and return of fear. We tell a story from noise that steadily develops into a meaningful tune and converges to a model of mechanisms contributing to individual risk/resilience with respect to fear and anxiety-related behavior. Furthermore, in light of the present 'replicability crisis' we identify methodological pitfalls and provide suggestions for study design and analyses tailored to individual difference research in fear conditioning. Ultimately, synergistic transdisciplinary and collaborative efforts hold promise to not only improve our mechanistic understanding but can also be expected to contribute to the development of specifically tailored ('individualized') intervention and targeted prevention programs in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.
Language Ability Predicts Cortical Structure and Covariance in Boys with Autism Spectrum Disorder.
Sharda, Megha; Foster, Nicholas E V; Tryfon, Ana; Doyle-Thomas, Krissy A R; Ouimet, Tia; Anagnostou, Evdokia; Evans, Alan C; Zwaigenbaum, Lonnie; Lerch, Jason P; Lewis, John D; Hyde, Krista L
2017-03-01
There is significant clinical heterogeneity in language and communication abilities of individuals with Autism Spectrum Disorders (ASD). However, no consistent pathology regarding the relationship of these abilities to brain structure has emerged. Recent developments in anatomical correlation-based approaches to map structural covariance networks (SCNs), combined with detailed behavioral characterization, offer an alternative for studying these relationships. In this study, such an approach was used to study the integrity of SCNs of cortical thickness and surface area associated with language and communication, in 46 high-functioning, school-age children with ASD compared with 50 matched, typically developing controls (all males) with IQ > 75. Findings showed that there was alteration of cortical structure and disruption of fronto-temporal cortical covariance in ASD compared with controls. Furthermore, in an analysis of a subset of ASD participants, alterations in both cortical structure and covariance were modulated by structural language ability of the participants, but not communicative function. These findings indicate that structural language abilities are related to altered fronto-temporal cortical covariance in ASD, much more than symptom severity or cognitive ability. They also support the importance of better characterizing ASD samples while studying brain structure and for better understanding individual differences in language and communication abilities in ASD. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Peng Fangfang
2014-01-01
Full Text Available This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.
Modeling Covariance Breakdowns in Multivariate GARCH
Jin, Xin; Maheu, John M
2014-01-01
This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Ole E. Barndorff-Nielsen; Neil Shephard
2002-01-01
This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...
Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun
2014-01-01
We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.
Community reaction to noise from power stations
International Nuclear Information System (INIS)
Job, R.F.S.; Hede, A.J.
1989-01-01
Community reaction is a major consideration in noise control. The relationship between noise exposure and community reaction has received considerable attention in relation to railway, traffic, aircraft and impulsive noise. The results have shown a number of features in common, including: similarly shaped noise/reaction functions; similar results across different measurement techniques and cultures, noise/reaction correlations based on individual respondent data are low (mean r = 0.42 ± 0.12: Job, 1988), although correlations of .58 and above have been reported correlations based on data grouped by noise exposure are generally high and relatively unaffected by the type of noise studied whereas correlations based on individual data tend to be lower for impulsive noise than for transportation noise attitude to the noise source and sensitivity to noise shows strong correlations with reaction. This paper reports that the present study was undertaken in order toe establish over a wider range of noise exposure whether community reaction to power station noise is similar to reaction to other types of non-impulsive noise. It is possible that reaction is different given important differences in the source of the noise which may affect attitude. Attitudes towards power stations may be more positive than attitudes to aircraft or rail noise for example, because almost all respondents use electricity regularly every day. Further, the power stations in the present study provided employment for the relatively small surrounding communities
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
Energy Technology Data Exchange (ETDEWEB)
Mattoon, C.M.; Oblozinsky,P.
2010-04-30
We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
Variational Bayesian labeled multi-Bernoulli filter with unknown sensor noise statistics
Directory of Open Access Journals (Sweden)
Qiu Hao
2016-10-01
Full Text Available It is difficult to build accurate model for measurement noise covariance in complex backgrounds. For the scenarios of unknown sensor noise variances, an adaptive multi-target tracking algorithm based on labeled random finite set and variational Bayesian (VB approximation is proposed. The variational approximation technique is introduced to the labeled multi-Bernoulli (LMB filter to jointly estimate the states of targets and sensor noise variances. Simulation results show that the proposed method can give unbiased estimation of cardinality and has better performance than the VB probability hypothesis density (VB-PHD filter and the VB cardinality balanced multi-target multi-Bernoulli (VB-CBMeMBer filter in harsh situations. The simulations also confirm the robustness of the proposed method against the time-varying noise variances. The computational complexity of proposed method is higher than the VB-PHD and VB-CBMeMBer in extreme cases, while the mean execution times of the three methods are close when targets are well separated.
Large-region acoustic source mapping using a movable array and sparse covariance fitting.
Zhao, Shengkui; Tuna, Cagdas; Nguyen, Thi Ngoc Tho; Jones, Douglas L
2017-01-01
Large-region acoustic source mapping is important for city-scale noise monitoring. Approaches using a single-position measurement scheme to scan large regions using small arrays cannot provide clean acoustic source maps, while deploying large arrays spanning the entire region of interest is prohibitively expensive. A multiple-position measurement scheme is applied to scan large regions at multiple spatial positions using a movable array of small size. Based on the multiple-position measurement scheme, a sparse-constrained multiple-position vectorized covariance matrix fitting approach is presented. In the proposed approach, the overall sample covariance matrix of the incoherent virtual array is first estimated using the multiple-position array data and then vectorized using the Khatri-Rao (KR) product. A linear model is then constructed for fitting the vectorized covariance matrix and a sparse-constrained reconstruction algorithm is proposed for recovering source powers from the model. The user parameter settings are discussed. The proposed approach is tested on a 30 m × 40 m region and a 60 m × 40 m region using simulated and measured data. Much cleaner acoustic source maps and lower sound pressure level errors are obtained compared to the beamforming approaches and the previous sparse approach [Zhao, Tuna, Nguyen, and Jones, Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2016)].
Gaskins, J T; Daniels, M J
2016-01-02
The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)
2017-05-30
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2017-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Robust adaptive multichannel SAR processing based on covariance matrix reconstruction
Tan, Zhen-ya; He, Feng
2018-04-01
With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.
Fast Computing for Distance Covariance
Huo, Xiaoming; Szekely, Gabor J.
2014-01-01
Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O($n^2$) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be...
On estimating cosmology-dependent covariance matrices
International Nuclear Information System (INIS)
Morrison, Christopher B.; Schneider, Michael D.
2013-01-01
We describe a statistical model to estimate the covariance matrix of matter tracer two-point correlation functions with cosmological simulations. Assuming a fixed number of cosmological simulation runs, we describe how to build a 'statistical emulator' of the two-point function covariance over a specified range of input cosmological parameters. Because the simulation runs with different cosmological models help to constrain the form of the covariance, we predict that the cosmology-dependent covariance may be estimated with a comparable number of simulations as would be needed to estimate the covariance for fixed cosmology. Our framework is a necessary first step in planning a simulations campaign for analyzing the next generation of cosmological surveys
ERRORJ. Covariance processing code. Version 2.2
International Nuclear Information System (INIS)
Chiba, Go
2004-07-01
ERRORJ is the covariance processing code that can produce covariance data of multi-group cross sections, which are essential for uncertainty analyses of nuclear parameters, such as neutron multiplication factor. The ERRORJ code can process the covariance data of cross sections including resonance parameters, angular and energy distributions of secondary neutrons. Those covariance data cannot be processed by the other covariance processing codes. ERRORJ has been modified and the version 2.2 has been developed. This document describes the modifications and how to use. The main topics of the modifications are as follows. Non-diagonal elements of covariance matrices are calculated in the resonance energy region. Option for high-speed calculation is implemented. Perturbation amount is optimized in a sensitivity calculation. Effect of the resonance self-shielding on covariance of multi-group cross section can be considered. It is possible to read a compact covariance format proposed by N.M. Larson. (author)
Directory of Open Access Journals (Sweden)
Ali R Khoshdel
2016-01-01
Full Text Available Background: Chronic exposure to noise is known to cause a wide range of health problems including extracellular matrix (ECM proliferation and involvement of cardiovascular system. There are a few studies to investigate noise-induced vascular changes using noninvasive methods. In this study we used carotid artery intima-media thickness (CIMT and aortic augmentation as indices of arterial properties and cystatin C as a serum biomarker relating to ECM metabolism. Materials and Methods: Ninety-three male participants were included in this study from aeronautic technicians: 39 with and 54 without a history of wide band noise (WBN exposure. For better discrimination, the participants were divided into the two age groups: 40 years old. Adjusted aortic augmentation index (AI for a heart rate equal to 75 beats per minute (AIx@HR75 were calculated using pulse wave analysis (PWA. CIMT was measured in 54 participants who accepted to undergo Doppler ultrasonography. Serum cystatin C was also measured. Results: Among younger individuals the mean CIMT was 0.85 ± 0.09 mm and 0.75 ± 0.22 mm in the in the exposed and the control groups respectively. Among older individuals CIMT had a mean of 1.04 ± 0.22 mm vs. 1.00 ± 0.25 mm for the exposed vs. the control group. However, in both age groups the difference was not significant at the 0.05 level. A comparison of AIx@HR75 between exposure group and control group both in younger age group (5.46 ± 11.22 vs. 8.56 ± 8.66 and older age group (17.55 ± 10.07 vs. 16.61 ± 5.77 revealed no significant difference. We did not find any significant correlation between CIMT and AIx@HR75 in exposed group (r = 0.314, P value = 0.145 but the correlation was significant in control group (r = 0.455, P value = 0.019. Serum cystatin C level was significantly lower in individuals with WBN exposure compared to controls (441.10 ± 104.70 ng/L vs. 616.89 ± 136.14, P
Signs of noise-induced neural degeneration in humans
DEFF Research Database (Denmark)
Holtegaard, Pernille; Olsen, Steen Østergaard
2015-01-01
of background noise, while leaving the processing of low-level stimuli unaffected. The purpose of this study was to investigate if signs of such primary neural damage from noise-exposure could also be found in noiseexposed human individuals. It was investigated: (1) if noise-exposed listeners with hearing......Animal studies demonstrated that noise exposure causes a primary and selective loss of auditory-nerve fibres with low spontaneous firing rate. This neuronal impairment, if also present in humans, can be assumed to affect the processing of supra-threshold stimuli, especially in the presence...... thresholds within the “normal” range perform poorer, in terms of their speech recognition threshold in noise (SRTN), and (2) if auditory brainstem responses (ABR) reveal lower amplitude of wave I in the noise-exposed listeners. A test group of noise/music-exposed individuals and a control group were...
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families
Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert
2016-01-01
In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363
Covariance matrix estimation for stationary time series
Xiao, Han; Wu, Wei Biao
2011-01-01
We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or Fourier transforms...
General Galilei Covariant Gaussian Maps
Gasbarri, Giulio; Toroš, Marko; Bassi, Angelo
2017-09-01
We characterize general non-Markovian Gaussian maps which are covariant under Galilean transformations. In particular, we consider translational and Galilean covariant maps and show that they reduce to the known Holevo result in the Markovian limit. We apply the results to discuss measures of macroscopicity based on classicalization maps, specifically addressing dissipation, Galilean covariance and non-Markovianity. We further suggest a possible generalization of the macroscopicity measure defined by Nimmrichter and Hornberger [Phys. Rev. Lett. 110, 16 (2013)].
Traffic noise in Hyderabad city, part-II. vehicular contribution to road traffic noise
International Nuclear Information System (INIS)
Sheikh, G.H.
2001-01-01
The results of a road traffic noise survey carried out in Hyderabad city showed that the levels of traffic noise in the City are alarmingly high and much beyond the comfortable limits. There, in order to investigate the level of the noise emitted by different types of vehicles plying on the city roads and to assess their individual contribution to high level traffic noise, studies have been carried out on the measurement of noise emitted by motorcycles, buses, auto-rickshaws, and motor vehicle horns as they normally move on the city roads. The data collected has been analyzed for L/sub v99/, L/sub v90/, L/sub v50/, L/sub v10/ and L/sub v1/ and results are discussed with reference to the existing motor vehicle rules in Pakistan and motor vehicle noise emission limits set by the EEC and other developed countries. Some suggestion have also been made to limit high level traffic noise. (author)
Competing risks and time-dependent covariates
DEFF Research Database (Denmark)
Cortese, Giuliana; Andersen, Per K
2010-01-01
Time-dependent covariates are frequently encountered in regression analysis for event history data and competing risks. They are often essential predictors, which cannot be substituted by time-fixed covariates. This study briefly recalls the different types of time-dependent covariates......, as classified by Kalbfleisch and Prentice [The Statistical Analysis of Failure Time Data, Wiley, New York, 2002] with the intent of clarifying their role and emphasizing the limitations in standard survival models and in the competing risks setting. If random (internal) time-dependent covariates...
Activities of covariance utilization working group
International Nuclear Information System (INIS)
Tsujimoto, Kazufumi
2013-01-01
During the past decade, there has been a interest in the calculational uncertainties induced by nuclear data uncertainties in the neutronics design of advanced nuclear system. The covariance nuclear data is absolutely essential for the uncertainty analysis. In the latest version of JENDL, JENDL-4.0, the covariance data for many nuclides, especially actinide nuclides, was substantialy enhanced. The growing interest in the uncertainty analysis and the covariance data has led to the organisation of the working group for covariance utilization under the JENDL committee. (author)
Kim, Jihyun; Lee, Wanhyung; Won, Jong-Uk; Yoon, Jin-Ha; Seok, Hongdeok; Kim, Yeong-Kwang; Lee, Seunghyun; Roh, Jaehoon
2017-01-01
The individual and combined effect of occupational noise and vibration exposures, on workers' health has not been thoroughly investigated. In order to find better ways to prevent and manage workers' headache, this study aimed to investigate the effects of occupational noise and vibration exposure on headache/eyestrain. We used data from the fourth Korean Working Condition Survey (2014). After applying inclusion and exclusion criteria, 25,751 workers were included. Occupational noise and vibration exposure and the prevalence of headache/eyestrain were investigated by self-reported survey. Chi-square tests were used to compare differences in baseline characteristics between the group with headache/eyestrain and the group without. Odds ratios and 95% confidence intervals were estimated using a logistic regression model adjusted for several covariates. Area under the receiver operating characteristics curve (AUROC) analysis was used to evaluate the effect of occupational noise and/or vibration exposure. Among the 25,751 study subjects, 4,903 had experienced headache/eyestrain in the preceding year. There were significant differences in age, education level, household income, occupational classification, shift work, occupational vibration exposure, and occupational noise exposure between the two groups (all pheadache/eyestrain increased proportionally with the level of exposure, increasing from 1.08 to 1.26 with increasing vibration exposure, and from 1.25 to 1.41 with increasing noise exposure. According to the AUROC analysis, the predictive power of each exposure was significant, and increased when the two exposures were considered in combination. The findings of this study show that both occupational noise and vibration exposures are associated with headache/eyestrain; noise exposure more strongly so. However, when the two exposures are considered in combination, the explanatory power for headache/eyestrain is increased. Therefore, efforts aimed at reducing and
Clark, Charlotte; Paunovic, Katarina
2018-02-07
This systematic review assesses the quality of the evidence across individual studies on the effect of environmental noise (road traffic, aircraft, and train and railway noise) on cognition. Quantitative non-experimental studies of the association between environmental noise exposure on child and adult cognitive performance published up to June 2015 were reviewed: no limit was placed on the start date for the search. A total of 34 papers were identified, all of which were of child populations. 82% of the papers were of cross-sectional design, with fewer studies of longitudinal or intervention design. A range of cognitive outcomes were examined. The quality of the evidence across the studies for each individual noise source and cognitive outcome was assessed using an adaptation of GRADE methodology. This review found, given the predominance of cross-sectional studies, that the quality of the evidence across studies ranged from being of moderate quality for an effect for some outcomes, e.g., aircraft noise effects on reading comprehension and on long-term memory, to no effect for other outcomes such as attention and executive function and for some noise sources such as road traffic noise and railway noise. The GRADE evaluation of low quality evidence across studies for some cognitive domains and for some noise sources does not necessarily mean that there are no effects: rather, that more robust and a greater number of studies are required.
Compressor noise control begins with design--Part 2
International Nuclear Information System (INIS)
Frank, L.
1993-01-01
Reduction of noise pollution at gas compressor stations associated with natural gas pipelines and distribution systems, has long been a complex problem. Specified noise levels of individual components tell nothing of the overall system when it is installed and placed in a site-specific setting. Further, testing for compliance performance guarantees is virtually impossible to conduct at a distant location because one cannot distinguish among various contributing noise sources. This paper develops a plan for calculating an estimate of sound generation from a compressor station and the methods for controlling and measuring sounds of individual components. It also classifies the types of noise and gives various methods of dealing with each noise type
Directory of Open Access Journals (Sweden)
Jorswieck E. A.
2004-01-01
Full Text Available The capacity of a cellular multiuser MIMO system depends on various parameters, for example, the system structure, the transmit and receive strategies, the channel state information at the transmitter and the receiver, and the channel properties. Recently, the main focus of research was on single-user MIMO systems, their channel capacity, and their error performance with space-time coding. In general, the capacity of a cellular multiuser MIMO system is limited by additive white Gaussian noise, intracell interference from other users within the cell, and intercell interference from users outside the considered cell. We study one point-to-point link, on which interference acts. The interference models the different system scenarios and various parameters. Therefore, we consider three scenarios in which the noise is subject to different constraints. A general trace constraint is used in the first scenario. The noise covariance matrix eigenvalues are kept fixed in the second scenario, and in the third scenario the entries on the diagonal of the noise covariance matrix are kept fixed. We assume that the receiver as well as the transmitter have perfect channel state information. We solve the corresponding minimax programming problems and characterize the worst-case noise and the optimal transmit strategy. In all scenarios, the achievable capacity of the MIMO system with worst-case noise is equal to the capacity of some MIMO system in which either the channels are orthogonal or the transmit antennas are not allowed to cooperate or in which no channel state information is available at the transmitter. Furthermore, the minimax expressions fulfill a saddle point property. All theoretical results are illustrated by examples and numerical simulations.
Quality Quantification of Evaluated Cross Section Covariances
International Nuclear Information System (INIS)
Varet, S.; Dossantos-Uzarralde, P.; Vayatis, N.
2015-01-01
Presently, several methods are used to estimate the covariance matrix of evaluated nuclear cross sections. Because the resulting covariance matrices can be different according to the method used and according to the assumptions of the method, we propose a general and objective approach to quantify the quality of the covariance estimation for evaluated cross sections. The first step consists in defining an objective criterion. The second step is computation of the criterion. In this paper the Kullback-Leibler distance is proposed for the quality quantification of a covariance matrix estimation and its inverse. It is based on the distance to the true covariance matrix. A method based on the bootstrap is presented for the estimation of this criterion, which can be applied with most methods for covariance matrix estimation and without the knowledge of the true covariance matrix. The full approach is illustrated on the 85 Rb nucleus evaluations and the results are then used for a discussion on scoring and Monte Carlo approaches for covariance matrix estimation of the cross section evaluations
Improvement of covariance data for fast reactors
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
2000-02-01
We estimated covariances of the JENDL-3.2 data on the nuclides and reactions needed to analyze fast-reactor cores for the past three years, and produced covariance files. The present work was undertaken to re-examine the covariance files and to make some improvements. The covariances improved are the ones for the inelastic scattering cross section of 16 O, the total cross section of 23 Na, the fission cross section of 235 U, the capture cross section of 238 U, and the resolved resonance parameters for 238 U. Moreover, the covariances of 233 U data were newly estimated by the present work. The covariances obtained were compiled in the ENDF-6 format. (author)
Structural covariance networks across the life span, from 6 to 94 years of age
Directory of Open Access Journals (Sweden)
Elizabeth DuPre
2017-10-01
Full Text Available Structural covariance examines covariation of gray matter morphology between brain regions and across individuals. Despite significant interest in the influence of age on structural covariance patterns, no study to date has provided a complete life span perspective—bridging childhood with early, middle, and late adulthood—on the development of structural covariance networks. Here, we investigate the life span trajectories of structural covariance in six canonical neurocognitive networks: default, dorsal attention, frontoparietal control, somatomotor, ventral attention, and visual. By combining data from five open-access data sources, we examine the structural covariance trajectories of these networks from 6 to 94 years of age in a sample of 1,580 participants. Using partial least squares, we show that structural covariance patterns across the life span exhibit two significant, age-dependent trends. The first trend is a stable pattern whose integrity declines over the life span. The second trend is an inverted-U that differentiates young adulthood from other age groups. Hub regions, including posterior cingulate cortex and anterior insula, appear particularly influential in the expression of this second age-dependent trend. Overall, our results suggest that structural covariance provides a reliable definition of neurocognitive networks across the life span and reveal both shared and network-specific trajectories. The importance of life span perspectives is increasingly apparent in understanding normative interactions of large-scale neurocognitive networks. Although recent work has made significant strides in understanding the functional and structural connectivity of these networks, there has been comparatively little attention to life span trajectories of structural covariance networks. In this study we examine patterns of structural covariance across the life span for six neurocognitive networks. Our results suggest that networks exhibit
Noise properties of Hilbert transform evaluation
International Nuclear Information System (INIS)
Pavliček, Pavel; Svak, Vojtěch
2015-01-01
The Hilbert transform is a standard method for the calculation of the envelope and phase of a modulated signal in optical measurement methods. Usually, the intensity of light is converted into an electric signal at a detector. Therefore the actual spatially or temporally sampled signal is always affected by noise. Because the noise values of individual samples are independent, the noise can be considered as white. If the envelope and phase are calculated from the noised signal, they will also be affected by the noise. We calculate the variance and spectral density of both the envelope noise and the phase noise. We determine which parameters influence the variance and spectral density of both the envelope noise and the phase noise. Finally, we determine the influence of the noise on the measurement uncertainty in white-light interferometry and fringe-pattern analysis. (paper)
Hierarchical multivariate covariance analysis of metabolic connectivity.
Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J
2014-12-01
Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).
Harvey, Nate
2016-08-01
Extending results from previous work by Bandikova et al. (2012) and Inacio et al. (2015), this paper analyzes Gravity Recovery and Climate Experiment (GRACE) star camera attitude measurement noise by processing inter-camera quaternions from 2003 to 2015. We describe a correction to star camera data, which will eliminate a several-arcsec twice-per-rev error with daily modulation, currently visible in the auto-covariance function of the inter-camera quaternion, from future GRACE Level-1B product releases. We also present evidence supporting the argument that thermal conditions/settings affect long-term inter-camera attitude biases by at least tens-of-arcsecs, and that several-to-tens-of-arcsecs per-rev star camera errors depend largely on field-of-view.
Communication system with adaptive noise suppression
Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)
2007-01-01
A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.
Yoneoka, Daisuke; Henmi, Masayuki
2017-11-30
Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.
Note on guilt appeals in advertising: covariate effects of self-esteem and locus of control.
Pinto, M B; Worobetz, N D
1992-02-01
A 1991 study by Pinto and Priest demonstrated the effectiveness of advertisements employing moderate levels of guilt in inducing guilt responses in subjects. Because individuals' responses to guilt are often influenced by their specific personality characteristics, researchers have pointed to the potential moderating effects of individual difference variables such as level of self-esteem and locus of control on individuals' susceptibility to guilt appeals. A study was conducted to evaluate the possibility that self-esteem and locus of control can act as covariates across three treatment levels of guilt advertising. From a sample of 57 working mothers, advertisements stimulating medium and high levels of guilt elicited significantly greater feelings of guilt in subjects than the control advertisement stimulating low guilt. However, the relationship between susceptibility to guilt appeals and self-esteem and locus of control was not observed to covary.
Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.
Wei, Luqing; Chen, Hong; Wu, Guo-Rong
2018-01-01
The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.
Covariance descriptor fusion for target detection
Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih
2016-05-01
Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2004-01-01
This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Covariant canonical quantization of fields and Bohmian mechanics
International Nuclear Information System (INIS)
Nikolic, H.
2005-01-01
We propose a manifestly covariant canonical method of field quantization based on the classical De Donder-Weyl covariant canonical formulation of field theory. Owing to covariance, the space and time arguments of fields are treated on an equal footing. To achieve both covariance and consistency with standard non-covariant canonical quantization of fields in Minkowski spacetime, it is necessary to adopt a covariant Bohmian formulation of quantum field theory. A preferred foliation of spacetime emerges dynamically owing to a purely quantum effect. The application to a simple time-reparametrization invariant system and quantum gravity is discussed and compared with the conventional non-covariant Wheeler-DeWitt approach. (orig.)
Proofs of Contracted Length Non-covariance
International Nuclear Information System (INIS)
Strel'tsov, V.N.
1994-01-01
Different proofs of contracted length non covariance are discussed. The way based on the establishment of interval inconstancy (dependence on velocity) seems to be the most convincing one. It is stressed that the known non covariance of the electromagnetic field energy and momentum of a moving charge ('the problem 4/3') is a direct consequence of contracted length non covariance. 8 refs
Auditory sensitivity in opiate addicts with and without a history of noise exposure
Directory of Open Access Journals (Sweden)
Vishakha Rawool
2011-01-01
Full Text Available Several case reports suggest that some individuals are susceptible to hearing loss from opioids. A combination of noise and opium exposure is possible in either occupational setting such as military service or recreational settings. According to the Drug Enforcement Agency of the U.S. Department of Justice, prescriptions for opiate-based drugs have skyrocketed in the past decade. Since both opium and noise independently can cause hearing loss, it is important to know the prevalence of hearing loss among individuals who are exposed to opium or both opium and noise. The purpose of this research was to evaluate auditory sensitivity in individuals with a history of opium abuse and/or occupational or nonoccupational noise exposure. Twenty-three men who reported opiate abuse served as participants in the study. Four of the individuals reported no history of noise exposure, 12 reported hobby-related noise exposure, 7 reported occupational noise exposure including 2 who also reported hobby-related noise exposure. Fifty percent (2/4 of the individuals without any noise exposure had a hearing loss confirming previous reports that some of the population is vulnerable to the ototoxic effects of opioids. The percentage of population with hearing loss increased with hobby-related (58% and occupational noise exposure (100%. Mixed MANOVA revealed a significant ear, frequency, and noise exposure interaction. Health professionals need to be aware of the possible ototoxic effects of opioids, since early detection of hearing loss from opium abuse may lead to cessation of abuse and further progression of hearing loss. The possibility that opium abuse may interact with noise exposure in determining auditory thresholds needs to be considered in noise exposed individuals who are addicted to opiates. Possible mechanisms of cochlear damage from opium abuse, possible reasons for individual susceptibility, and recommendations for future studies are presented in the article.
Realistic Noise Assessment and Strain Analysis of Iranian Permanent GPS Stations
Razeghi, S. M.; Amiri Simkooei, A. A.; Sharifi, M. A.
2012-04-01
To assess noise characteristics of Iranian Permanent GPS Stations (IPGS), northwestern part of this network namely Azerbaijan Continuous GPS Station (ACGS), was selected. For a realistic noise assessment it is required to model all deterministic signals of the GPS time series by means of least squares harmonic estimation (LS-HE) and derive all periodic behavior of the series. After taking all deterministic signals into account, the least squares variance component estimation (LS-VCE) is used to obtain a realistic noise model (white noise plus flicker noise) of the ACGS. For this purpose, one needs simultaneous GPS time series for which a multivariate noise assessment is applied. Having determined realistic noise model, a realistic strain analysis of the network is obtained for which one relies on the finite element methods. Finite element is now considered to be a new functional model and the new stochastic model is given based on the multivariate noise assessment using LS-VCE. The deformation rates of the components along with their full covariance matries are input to the strain analysis. Further, the results are also provided using a pure white noise model. The normalized strains for these two models show that the strain parameters derived from a realistic noise model are less significant than those derived from the white model. This could be either due to the short time span of the time series used or due to the intrinsic behavior of the strain parameters in the ACGS. Longer time series are required to further elaborate this issue.
Covariate analysis of bivariate survival data
Energy Technology Data Exchange (ETDEWEB)
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2016-10-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2016-10-15
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariance and sensitivity data generation at ORNL
International Nuclear Information System (INIS)
Leal, L. C.; Derrien, H.; Larson, N. M.; Alpan, A.
2005-01-01
Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the 'retroactive' resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes. (authors)
International Nuclear Information System (INIS)
Collins, Philip G.; Fuhrer, M. S.; Zettl, A.
2000-01-01
The electrical noise characteristics of single-walled carbon nanotubes have been investigated. For all three cases of individual isolated nanotubes, thin films of interconnected nanotubes, and bulk nanotube mats, anomalously large bias-dependent 1/f noise is found. The noise magnitude greatly exceeds that commonly observed in metal films, carbon resistors, or even carbon fibers with comparable resistances. A single empirical expression describes the noise for all nanotube samples, suggesting a common noise-generating mechanism proportional only to the number of nanotubes in the conductor. We consider likely sources of the fluctuations, and consequences for electronic applications of nanotubes if the excessive noise cannot be suppressed. (c) 2000 American Institute of Physics
Genotype-covariate interaction effects and the heritability of adult body mass index
Robinson, Matthew R.; English, Geoffrey; Moser, Gerhard; Lloyd-Jones, Luke R; Triplett, Marcus A; Zhu, Zhihong; Nolte, Ilja M; van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Esko, Tonu; Milani, Lili; Mägi, Reedik; Metspalu, Andres; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Ingelsson, Erik; Johannesson, Magnus; Yang, Jian; Cesarini, David; Visscher, Peter M.
Obesity is a worldwide epidemic, with major health and economic costs. Here we estimate heritability for body mass index (BMI) in 172,000 sibling pairs and 150,832 unrelated individuals and explore the contribution of genotype-covariate interaction effects at common SNP loci. We find evidence for
Directory of Open Access Journals (Sweden)
Stefano Livi
2018-05-01
Full Text Available Several studies have underlined how chronic exposure to environmental noise may have negative effects on performance, wellbeing, and social relations. The present study (N = 90 employees of a motor factory who are chronically exposed to environmental noise investigated whether the negative effects of chronic exposure of noise-sensitive individuals to noise in the workplace may be moderated by the need for cognitive closure (i.e., an epistemic tendency to reduce uncertainty; NFCC, Kruglanski, 2004. As NFCC has been shown to enhance protection of the focal goal by reducing interference (Kossowska, 2007; Pica et al., 2013, we hypothesized that people with high NFCC should be able to manage the interference coming from environmental noise and concentrate on their tasks more than their low-NFCC counterparts. The results confirm that the negative effects of noise sensitivity on job satisfaction, state anxiety, and turnover intent were higher among low (vs. high-NFCC individuals.
Covariance matrices of experimental data
International Nuclear Information System (INIS)
Perey, F.G.
1978-01-01
A complete statement of the uncertainties in data is given by its covariance matrix. It is shown how the covariance matrix of data can be generated using the information available to obtain their standard deviations. Determination of resonance energies by the time-of-flight method is used as an example. The procedure for combining data when the covariance matrix is non-diagonal is given. The method is illustrated by means of examples taken from the recent literature to obtain an estimate of the energy of the first resonance in carbon and for five resonances of 238 U
Covariant perturbations of Schwarzschild black holes
International Nuclear Information System (INIS)
Clarkson, Chris A; Barrett, Richard K
2003-01-01
We present a new covariant and gauge-invariant perturbation formalism for dealing with spacetimes having spherical symmetry (or some preferred spatial direction) in the background, and apply it to the case of gravitational wave propagation in a Schwarzschild black-hole spacetime. The 1 + 3 covariant approach is extended to a '1 + 1 + 2 covariant sheet' formalism by introducing a radial unit vector in addition to the timelike congruence, and decomposing all covariant quantities with respect to this. The background Schwarzschild solution is discussed and a covariant characterization is given. We give the full first-order system of linearized 1 + 1 + 2 covariant equations, and we show how, by introducing (time and spherical) harmonic functions, these may be reduced to a system of first-order ordinary differential equations and algebraic constraints for the 1 + 1 + 2 variables which may be solved straightforwardly. We show how both odd- and even-parity perturbations may be unified by the discovery of a covariant, frame- and gauge-invariant, transverse-traceless tensor describing gravitational waves, which satisfies a covariant wave equation equivalent to the Regge-Wheeler equation for both even- and odd-parity perturbations. We show how the Zerilli equation may be derived from this tensor, and derive a similar transverse-traceless tensor equation equivalent to this equation. The so-called special quasinormal modes with purely imaginary frequency emerge naturally. The significance of the degrees of freedom in the choice of the two frame vectors is discussed, and we demonstrate that, for a certain frame choice, the underlying dynamics is governed purely by the Regge-Wheeler tensor. The two transverse-traceless Weyl tensors which carry the curvature of gravitational waves are discussed, and we give the closed system of four first-order ordinary differential equations describing their propagation. Finally, we consider the extension of this work to the study of
Thompson, Elaine C.; Carr, Kali Woodruff; White-Schwoch, Travis; Otto-Meyer, Sebastian; Kraus, Nina
2016-01-01
From bustling classrooms to unruly lunchrooms, school settings are noisy. To learn effectively in the unwelcome company of numerous distractions, children must clearly perceive speech in noise. In older children and adults, speech-in-noise perception is supported by sensory and cognitive processes, but the correlates underlying this critical listening skill in young children (3–5 year olds) remain undetermined. Employing a longitudinal design (two evaluations separated by ~12 months), we followed a cohort of 59 preschoolers, ages 3.0–4.9, assessing word-in-noise perception, cognitive abilities (intelligence, short-term memory, attention), and neural responses to speech. Results reveal changes in word-in-noise perception parallel changes in processing of the fundamental frequency (F0), an acoustic cue known for playing a role central to speaker identification and auditory scene analysis. Four unique developmental trajectories (speech-in-noise perception groups) confirm this relationship, in that improvements and declines in word-in-noise perception couple with enhancements and diminishments of F0 encoding, respectively. Improvements in word-in-noise perception also pair with gains in attention. Word-in-noise perception does not relate to strength of neural harmonic representation or short-term memory. These findings reinforce previously-reported roles of F0 and attention in hearing speech in noise in older children and adults, and extend this relationship to preschool children. PMID:27864051
Scott, M
2012-08-01
The time-covariance function captures the dynamics of biochemical fluctuations and contains important information about the underlying kinetic rate parameters. Intrinsic fluctuations in biochemical reaction networks are typically modelled using a master equation formalism. In general, the equation cannot be solved exactly and approximation methods are required. For small fluctuations close to equilibrium, a linearisation of the dynamics provides a very good description of the relaxation of the time-covariance function. As the number of molecules in the system decrease, deviations from the linear theory appear. Carrying out a systematic perturbation expansion of the master equation to capture these effects results in formidable algebra; however, symbolic mathematics packages considerably expedite the computation. The authors demonstrate that non-linear effects can reveal features of the underlying dynamics, such as reaction stoichiometry, not available in linearised theory. Furthermore, in models that exhibit noise-induced oscillations, non-linear corrections result in a shift in the base frequency along with the appearance of a secondary harmonic.
Aircraft and background noise annoyance effects
Willshire, K. F.
1984-01-01
To investigate annoyance of multiple noise sources, two experiments were conducted. The first experiment, which used 48 subjects, was designed to establish annoyance-noise level functions for three community noise sources presented individually: jet aircraft flyovers, air conditioner, and traffic. The second experiment, which used 216 subjects, investigated the effects of background noise on aircraft annoyance as a function of noise level and spectrum shape; and the differences between overall, aircraft, and background noise annoyance. In both experiments, rated annoyance was the dependent measure. Results indicate that the slope of the linear relationship between annoyance and noise level for traffic is significantly different from that of flyover and air conditioner noise and that further research was justified to determine the influence of the two background noises on overall, aircraft, and background noise annoyance (e.g., experiment two). In experiment two, total noise exposure, signal-to-noise ratio, and background source type were found to have effects on all three types of annoyance. Thus, both signal-to-noise ratio, and the background source must be considered when trying to determine community response to combined noise sources.
Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
Directory of Open Access Journals (Sweden)
Dirk Schreckenberg
2010-01-01
Full Text Available One hundred and ninety residents around Frankfurt Airport (46% female; 17-80 years were interviewed concerning noise annoyance due to transportation noise (aircraft, road traffic, perceived mental and physical health, perceived environmental quality, and noise sensitivity. The aim of the analyses was to test whether noise sensitivity reflects partly general environmental sensitivity and is associated with an elevated susceptibility for the perception of mental and physical health. In this study, the reported physical and mental health variables were not associated with noise exposure but with noise annoyance, and were interpreted to reflect nonspecific codeterminants of annoyance rather than noise effects. Noise sensitivity was found to influence total noise annoyance and aircraft noise annoyance but to a lesser degree annoyance due to road traffic noise. Noise sensitivity was associated with reported physical health, but not with reported mental health. Noise-sensitive persons reported poorer environmental quality in their residential area than less sensitive persons in particular with regard to air traffic (including the facets noise, pollution, and contaminations and quietness. Other aspects of the perceived quality of the environment were scarcely associated with noise sensitivity. This indicates that noise sensitivity is more specific and a reliable predictor of responses to noise from the dominant source (in this case air traffic rather than a predictor of the individual perception of the environmental quality in general.
Model of aircraft noise adaptation
Dempsey, T. K.; Coates, G. D.; Cawthorn, J. M.
1977-01-01
Development of an aircraft noise adaptation model, which would account for much of the variability in the responses of subjects participating in human response to noise experiments, was studied. A description of the model development is presented. The principal concept of the model, was the determination of an aircraft adaptation level which represents an annoyance calibration for each individual. Results showed a direct correlation between noise level of the stimuli and annoyance reactions. Attitude-personality variables were found to account for varying annoyance judgements.
Directory of Open Access Journals (Sweden)
Nerrière Eléna
2009-09-01
Full Text Available Abstract Background Limited information on the covariates of burnout syndrome in French teachers is available. The aim of this study was to evaluate the relative contributions of individual and contextual factors on the three burnout dimensions: emotional exhaustion, depersonalization, and reduced personal accomplishment. Methods The source data come from an epidemiological postal survey on physical and mental health conducted in 2005 among 20,099 education workers (in activity or retired selected at random from the health plan records of the national education system. The response rate was 52.4%. Teachers in activity currently giving classes to students who participated in the survey (n = 3,940 were invited to complete a self-administered questionnaire including the Maslach Burnout Inventory. 2,558 teachers provided complete data (64.9%. Variables associated with high emotional exhaustion (highest quartile of score, high depersonalization (highest quartile, and reduced personal accomplishment (lowest quartile were evaluated using multivariate logistic regression. Studied variables referred to demographic characteristics, socio-professional environment, job dissatisfaction, experienced difficulties at work, and teaching motivations. Results Different variables were associated with each burnout dimension. Female teachers were more susceptible to high emotional exhaustion and reduced personal accomplishment, whereas male teachers were more susceptible to high depersonalization. Elementary school teachers were more susceptible to high emotional exhaustion, but less susceptible to high depersonalization and reduced personal accomplishment than their higher school level counterparts. Experienced difficulties with pupils were associated with all three dimensions. A socio-economically underprivileged school neighbourhood was also related to high emotional exhaustion and high depersonalization. Conclusion Programs to enhance teaching environment might
TH-A-18C-07: Noise Suppression in Material Decomposition for Dual-Energy CT
International Nuclear Information System (INIS)
Dong, X; Petrongolo, M; Wang, T; Zhu, L
2014-01-01
Purpose: A general problem of dual-energy CT (DECT) is that the decomposition is sensitive to noise in the two sets of dual-energy projection data, resulting in severely degraded qualities of decomposed images. We have previously proposed an iterative denoising method for DECT. Using a linear decomposition function, the method does not gain the full benefits of DECT on beam-hardening correction. In this work, we expand the framework of our iterative method to include non-linear decomposition models for noise suppression in DECT. Methods: We first obtain decomposed projections, which are free of beam-hardening artifacts, using a lookup table pre-measured on a calibration phantom. First-pass material images with high noise are reconstructed from the decomposed projections using standard filter-backprojection reconstruction. Noise on the decomposed images is then suppressed by an iterative method, which is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, we include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Analytical formulae are derived to compute the variance-covariance matrix from the measured decomposition lookup table. Results: We have evaluated the proposed method via phantom studies. Using non-linear decomposition, our method effectively suppresses the streaking artifacts of beam-hardening and obtains more uniform images than our previous approach based on a linear model. The proposed method reduces the average noise standard deviation of two basis materials by one order of magnitude without sacrificing the spatial resolution. Conclusion: We propose a general framework of iterative denoising for material decomposition of DECT. Preliminary phantom studies have shown the proposed method improves the image uniformity and reduces noise level without resolution loss. In the future
Structural Analysis of Covariance and Correlation Matrices.
Joreskog, Karl G.
1978-01-01
A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Sang, Huiyan
2011-12-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.
Hidden symmetries and equilibrium properties of multiplicative white-noise stochastic processes
International Nuclear Information System (INIS)
Arenas, Zochil González; Barci, Daniel G
2012-01-01
Multiplicative white-noise stochastic processes continue to attract attention in a wide area of scientific research. The variety of prescriptions available for defining them makes the development of general tools for their characterization difficult. In this work, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for such processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. Representing the stochastic process in a functional Grassmann formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of the equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicative Markovian white-noise process and study some of the constraints that it imposes on correlation functions using Ward–Takahashi identities. (paper)
Hidden symmetries and equilibrium properties of multiplicative white-noise stochastic processes
González Arenas, Zochil; Barci, Daniel G.
2012-12-01
Multiplicative white-noise stochastic processes continue to attract attention in a wide area of scientific research. The variety of prescriptions available for defining them makes the development of general tools for their characterization difficult. In this work, we study equilibrium properties of Markovian multiplicative white-noise processes. For this, we define the time reversal transformation for such processes, taking into account that the asymptotic stationary probability distribution depends on the prescription. Representing the stochastic process in a functional Grassmann formalism, we avoid the necessity of fixing a particular prescription. In this framework, we analyze equilibrium properties and study hidden symmetries of the process. We show that, using a careful definition of the equilibrium distribution and taking into account the appropriate time reversal transformation, usual equilibrium properties are satisfied for any prescription. Finally, we present a detailed deduction of a covariant supersymmetric formulation of a multiplicative Markovian white-noise process and study some of the constraints that it imposes on correlation functions using Ward-Takahashi identities.
Modifications of Sp(2) covariant superfield quantization
Energy Technology Data Exchange (ETDEWEB)
Gitman, D.M.; Moshin, P.Yu
2003-12-04
We propose a modification of the Sp(2) covariant superfield quantization to realize a superalgebra of generating operators isomorphic to the massless limit of the corresponding superalgebra of the osp(1,2) covariant formalism. The modified scheme ensures the compatibility of the superalgebra of generating operators with extended BRST symmetry without imposing restrictions eliminating superfield components from the quantum action. The formalism coincides with the Sp(2) covariant superfield scheme and with the massless limit of the osp(1,2) covariant quantization in particular cases of gauge-fixing and solutions of the quantum master equations.
Energy Technology Data Exchange (ETDEWEB)
Meyer-Paron, M.
2000-07-01
Does a person's strategy of coping with traffic noise influence the extent to which he or she feels stressed by it? Ever sSince the seventies, noise research has been attempting to identify factors apart from the noise level that contribute to extraaural noise effects. This investigation discusses new results in the light of transactional stress theory and also investigates the influence of individual coping. Studies on 116 persons showed that it is not the concrete attempt to cope which is the decisive factor but a person's assumptions about his or her potential influence on the experienced noise and its effects, i.e. control. The degree of control experienced was found to be an intermediate step in the development of stress effects. [German] Hat die Art, wie Personen mit taeglich erlebtem Verkehrslaerm umgehen, Einfluss darauf, wie stark sie sich beeintraechtigt fuehlen? Seit den 70er Jahren bemueht sich die Laermforschung, Faktoren zu benennen, die neben dem Schallpegel an der Entstehung (extraauraler) Laermwirkungen beteiligt sind. Die vorliegenden Erkenntnisse erhalten hier durch ihre Einordnung in den Rahmen der transaktionalen Stresstheorien eine theoretische Fundierung. Gleichzeitig wird die Frage aufgeworfen, ob auch das Theorieelement Coping (individuelle Bewaeltigungsversuche) als Einflussfaktor fuer die Staerke von Laermwirkungen zu betrachten ist. Empirisch wurde geprueft, ob sich Gestoertheitsurteile und Schlafqualitaetsindikatoren bei schienenverkehrslaermbelasteten Personen in Abhaengigkeit vom individuellen Coping unterscheiden. Die Untersuchung an 116 Personen zeigte, dass nicht konkrete Bewaeltigungsversuche die Groesse von Laermwirkungen mitbestimmen, sondern die Einschaetzung, Einfluss auf den Laerm oder seine Wirkungen nehmen zu koennen (Kontrolle). Belegt wurde, dass die wahrgenommene Kontrolle einen Zwischenschritt bei der Entstehung von Gestoertheitsurteilen darstellt. (orig.)
Covariant quantizations in plane and curved spaces
International Nuclear Information System (INIS)
Assirati, J.L.M.; Gitman, D.M.
2017-01-01
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Covariant quantizations in plane and curved spaces
Energy Technology Data Exchange (ETDEWEB)
Assirati, J.L.M. [University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil); Gitman, D.M. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); P.N. Lebedev Physical Institute, Moscow (Russian Federation); University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil)
2017-07-15
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Construction of covariance matrix for experimental data
International Nuclear Information System (INIS)
Liu Tingjin; Zhang Jianhua
1992-01-01
For evaluators and experimenters, the information is complete only in the case when the covariance matrix is given. The covariance matrix of the indirectly measured data has been constructed and discussed. As an example, the covariance matrix of 23 Na(n, 2n) cross section is constructed. A reasonable result is obtained
Development of covariance date for fast reactor cores. 3
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
1999-03-01
Covariances have been estimated for nuclear data contained in JENDL-3.2. As for Cr and Ni, the physical quantities for which covariances are deduced are cross sections and the first order Legendre-polynomial coefficient for the angular distribution of elastically scattered neutrons. The covariances were estimated by using the same methodology that had been used in the JENDL-3.2 evaluation in order to keep a consistency between mean values and their covariances. In a case where evaluated data were based on experimental data, the covariances were estimated from the same experimental data. For cross section that had been evaluated by nuclear model calculations, the same model was applied to generate the covariances. The covariances obtained were compiled into ENDF-6 format files. The covariances, which had been prepared by the previous fiscal year, were re-examined, and some improvements were performed. Parts of Fe and 235 U covariances were updated. Covariances of nu-p and nu-d for 241 Pu and of fission neutron spectra for 233,235,238 U and 239,240 Pu were newly added to data files. (author)
Theory and Measurement of Signal-to-Noise Ratio in Continuous-Wave Noise Radar.
Stec, Bronisław; Susek, Waldemar
2018-05-06
Determination of the signal power-to-noise power ratio on the input and output of reception systems is essential to the estimation of their quality and signal reception capability. This issue is especially important in the case when both signal and noise have the same characteristic as Gaussian white noise. This article considers the problem of how a signal-to-noise ratio is changed as a result of signal processing in the correlation receiver of a noise radar in order to determine the ability to detect weak features in the presence of strong clutter-type interference. These studies concern both theoretical analysis and practical measurements of a noise radar with a digital correlation receiver for 9.2 GHz bandwidth. Firstly, signals participating individually in the correlation process are defined and the terms signal and interference are ascribed to them. Further studies show that it is possible to distinguish a signal and a noise on the input and output of a correlation receiver, respectively, when all the considered noises are in the form of white noise. Considering the above, a measurement system is designed in which it is possible to represent the actual conditions of noise radar operation and power measurement of a useful noise signal and interference noise signals—in particular the power of an internal leakage signal between a transmitter and a receiver of the noise radar. The proposed measurement stands and the obtained results show that it is possible to optimize with the use of the equipment and not with the complex processing of a noise signal. The radar parameters depend on its prospective application, such as short- and medium-range radar, ground-penetrating radar, and through-the-wall detection radar.
Spreadsheet tool for estimating noise reduction costs
International Nuclear Information System (INIS)
Frank, L.; Senden, V.; Leszczynski, Y.
2009-01-01
The Northeast Capital Industrial Association (NCIA) represents industry in Alberta's industrial heartland. The organization is in the process of developing a regional noise management plan (RNMP) for their member companies. The RNMP includes the development of a noise reduction cost spreadsheet tool to conduct reviews of practical noise control treatments available for individual plant equipment, inclusive of ranges of noise attenuation achievable, which produces a budgetary prediction of the installed cost of practical noise control treatments. This paper discussed the noise reduction cost spreadsheet tool, with particular reference to noise control best practices approaches and spreadsheet tool development such as prerequisite, assembling data required, approach, and unit pricing database. Use and optimization of the noise reduction cost spreadsheet tool was also discussed. It was concluded that the noise reduction cost spreadsheet tool is an easy interactive tool to estimate implementation costs related to different strategies and options of noise control mitigating measures and was very helpful in gaining insight for noise control planning purposes. 2 tabs.
Jennings, J Richard; Sheu, Lei K; Kuan, Dora C-H; Manuck, Stephen B; Gianaros, Peter J
2016-04-01
Resting high-frequency heart rate variability (HF-HRV) relates to cardiac vagal control and predicts individual differences in health and longevity, but its functional neural correlates are not well defined. The medial prefrontal cortex (mPFC) encompasses visceral control regions that are components of intrinsic networks of the brain, particularly the default mode network (DMN) and the salience network (SN). Might individual differences in resting HF-HRV covary with resting state neural activity in the DMN and SN, particularly within the mPFC? This question was addressed using fMRI data from an eyes-open, 5-min rest period during which echoplanar brain imaging yielded BOLD time series. Independent component analysis yielded functional connectivity estimates defining the DMN and SN. HF-HRV was measured in a rest period outside of the scanner. Midlife (52% female) adults were assessed in two studies (Study 1, N = 107; Study 2, N = 112). Neither overall DMN nor SN connectivity strength was related to HF-HRV. However, HF-HRV related to connectivity of one region within mPFC shared by the DMN and SN, namely, the perigenual anterior cingulate cortex, an area with connectivity to other regions involved in autonomic control. In sum, HF-HRV does not seem directly related to global resting state activity of intrinsic brain networks, but rather to more localized connectivity. A mPFC region was of particular interest as connectivity related to HF-HRV was shared by the DMN and SN. These findings may indicate a functional basis for the coordination of autonomic cardiac control with engagement and disengagement from the environment. © 2015 Society for Psychophysiological Research.
Directory of Open Access Journals (Sweden)
Jihyun Kim
Full Text Available The individual and combined effect of occupational noise and vibration exposures, on workers' health has not been thoroughly investigated. In order to find better ways to prevent and manage workers' headache, this study aimed to investigate the effects of occupational noise and vibration exposure on headache/eyestrain.We used data from the fourth Korean Working Condition Survey (2014. After applying inclusion and exclusion criteria, 25,751 workers were included. Occupational noise and vibration exposure and the prevalence of headache/eyestrain were investigated by self-reported survey. Chi-square tests were used to compare differences in baseline characteristics between the group with headache/eyestrain and the group without. Odds ratios and 95% confidence intervals were estimated using a logistic regression model adjusted for several covariates. Area under the receiver operating characteristics curve (AUROC analysis was used to evaluate the effect of occupational noise and/or vibration exposure.Among the 25,751 study subjects, 4,903 had experienced headache/eyestrain in the preceding year. There were significant differences in age, education level, household income, occupational classification, shift work, occupational vibration exposure, and occupational noise exposure between the two groups (all p<0.05. The odds ratios between each exposure and headache/eyestrain increased proportionally with the level of exposure, increasing from 1.08 to 1.26 with increasing vibration exposure, and from 1.25 to 1.41 with increasing noise exposure. According to the AUROC analysis, the predictive power of each exposure was significant, and increased when the two exposures were considered in combination.The findings of this study show that both occupational noise and vibration exposures are associated with headache/eyestrain; noise exposure more strongly so. However, when the two exposures are considered in combination, the explanatory power for headache
Energy Technology Data Exchange (ETDEWEB)
Bourget, Antoine; Troost, Jan [Laboratoire de Physique Théorique, École Normale Supérieure, 24 rue Lhomond, 75005 Paris (France)
2016-03-23
We construct a covariant generating function for the spectrum of chiral primaries of symmetric orbifold conformal field theories with N=(4,4) supersymmetry in two dimensions. For seed target spaces K3 and T{sup 4}, the generating functions capture the SO(21) and SO(5) representation theoretic content of the chiral ring respectively. Via string dualities, we relate the transformation properties of the chiral ring under these isometries of the moduli space to the Lorentz covariance of perturbative string partition functions in flat space.
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1992-01-01
GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations are considered. It is that, up to some innessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. 25 refs
An automated procedure for covariation-based detection of RNA structure
International Nuclear Information System (INIS)
Winker, S.; Overbeek, R.; Woese, C.R.; Olsen, G.J.; Pfluger, N.
1989-12-01
This paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential bondings of secondary and tertiary structure, but also provides the covariation evidence that supports the proposed bondings, and any counter-evidence that can be detected in the known sequences. A small number of previously unknown bondings have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. Currently, we are systematically studying mitochondrial rRNA. Our goal is to detect tertiary structure within 16S rRNA and quaternary structure between 16S and 23S rRNA. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosome structure. Our colleagues in biology have begun experiments to test certain hypotheses suggested by an examination of our program's output. These experiments involve sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. The hope is that the 23S ribosomal RNA of these species will exhibit corresponding complementary variation or generalized covariation. 24 refs
An automated procedure for covariation-based detection of RNA structure
Energy Technology Data Exchange (ETDEWEB)
Winker, S.; Overbeek, R.; Woese, C.R.; Olsen, G.J.; Pfluger, N.
1989-12-01
This paper summarizes our investigations into the computational detection of secondary and tertiary structure of ribosomal RNA. We have developed a new automated procedure that not only identifies potential bondings of secondary and tertiary structure, but also provides the covariation evidence that supports the proposed bondings, and any counter-evidence that can be detected in the known sequences. A small number of previously unknown bondings have been detected in individual RNA molecules (16S rRNA and 7S RNA) through the use of our automated procedure. Currently, we are systematically studying mitochondrial rRNA. Our goal is to detect tertiary structure within 16S rRNA and quaternary structure between 16S and 23S rRNA. Our ultimate hope is that automated covariation analysis will contribute significantly to a refined picture of ribosome structure. Our colleagues in biology have begun experiments to test certain hypotheses suggested by an examination of our program's output. These experiments involve sequencing key portions of the 23S ribosomal RNA for species in which the known 16S ribosomal RNA exhibits variation (from the dominant pattern) at the site of a proposed bonding. The hope is that the 23S ribosomal RNA of these species will exhibit corresponding complementary variation or generalized covariation. 24 refs.
Introduction to covariant formulation of superstring (field) theory
International Nuclear Information System (INIS)
Anon.
1987-01-01
The author discusses covariant formulation of superstring theories based on BRS invariance. New formulation of superstring was constructed by Green and Schwarz in the light-cone gauge first and then a covariant action was discovered. The covariant action has some interesting geometrical interpretation, however, covariant quantizations are difficult to perform because of existence of local supersymmetries. Introducing extra variables into the action, a modified action has been proposed. However, it would be difficult to prescribe constraints to define a physical subspace, or to reproduce the correct physical spectrum. Hence the old formulation, i.e., the Neveu-Schwarz-Ramond (NSR) model for covariant quantization is used. The author begins by quantizing the NSR model in a covariant way using BRS charges. Then the author discusses the field theory of (free) superstring
Graphical representation of covariant-contravariant modal formulae
Directory of Open Access Journals (Sweden)
Miguel Palomino
2011-08-01
Full Text Available Covariant-contravariant simulation is a combination of standard (covariant simulation, its contravariant counterpart and bisimulation. We have previously studied its logical characterization by means of the covariant-contravariant modal logic. Moreover, we have investigated the relationships between this model and that of modal transition systems, where two kinds of transitions (the so-called may and must transitions were combined in order to obtain a simple framework to express a notion of refinement over state-transition models. In a classic paper, Boudol and Larsen established a precise connection between the graphical approach, by means of modal transition systems, and the logical approach, based on Hennessy-Milner logic without negation, to system specification. They obtained a (graphical representation theorem proving that a formula can be represented by a term if, and only if, it is consistent and prime. We show in this paper that the formulae from the covariant-contravariant modal logic that admit a "graphical" representation by means of processes, modulo the covariant-contravariant simulation preorder, are also the consistent and prime ones. In order to obtain the desired graphical representation result, we first restrict ourselves to the case of covariant-contravariant systems without bivariant actions. Bivariant actions can be incorporated later by means of an encoding that splits each bivariant action into its covariant and its contravariant parts.
Bayesian Noise Estimation for Non-ideal Cosmic Microwave Background Experiments
Wehus, I. K.; Næss, S. K.; Eriksen, H. K.
2012-03-01
We describe a Bayesian framework for estimating the time-domain noise covariance of cosmic microwave background (CMB) observations, typically parameterized in terms of a 1/f frequency profile. This framework is based on the Gibbs sampling algorithm, which allows for exact marginalization over nuisance parameters through conditional probability distributions. In this paper, we implement support for gaps in the data streams and marginalization over fixed time-domain templates, and also outline how to marginalize over confusion from CMB fluctuations, which may be important for high signal-to-noise experiments. As a by-product of the method, we obtain proper constrained realizations, which themselves can be useful for map making. To validate the algorithm, we demonstrate that the reconstructed noise parameters and corresponding uncertainties are unbiased using simulated data. The CPU time required to process a single data stream of 100,000 samples with 1000 samples removed by gaps is 3 s if only the maximum posterior parameters are required, and 21 s if one also wants to obtain the corresponding uncertainties by Gibbs sampling.
BAYESIAN NOISE ESTIMATION FOR NON-IDEAL COSMIC MICROWAVE BACKGROUND EXPERIMENTS
International Nuclear Information System (INIS)
Wehus, I. K.; Næss, S. K.; Eriksen, H. K.
2012-01-01
We describe a Bayesian framework for estimating the time-domain noise covariance of cosmic microwave background (CMB) observations, typically parameterized in terms of a 1/f frequency profile. This framework is based on the Gibbs sampling algorithm, which allows for exact marginalization over nuisance parameters through conditional probability distributions. In this paper, we implement support for gaps in the data streams and marginalization over fixed time-domain templates, and also outline how to marginalize over confusion from CMB fluctuations, which may be important for high signal-to-noise experiments. As a by-product of the method, we obtain proper constrained realizations, which themselves can be useful for map making. To validate the algorithm, we demonstrate that the reconstructed noise parameters and corresponding uncertainties are unbiased using simulated data. The CPU time required to process a single data stream of 100,000 samples with 1000 samples removed by gaps is 3 s if only the maximum posterior parameters are required, and 21 s if one also wants to obtain the corresponding uncertainties by Gibbs sampling.
BAYESIAN NOISE ESTIMATION FOR NON-IDEAL COSMIC MICROWAVE BACKGROUND EXPERIMENTS
Energy Technology Data Exchange (ETDEWEB)
Wehus, I. K. [Theoretical Physics, Imperial College London, London SW7 2AZ (United Kingdom); Naess, S. K.; Eriksen, H. K., E-mail: i.k.wehus@fys.uio.no, E-mail: sigurdkn@astro.uio.no, E-mail: h.k.k.eriksen@astro.uio.no [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029, Blindern, N-0315 Oslo (Norway)
2012-03-01
We describe a Bayesian framework for estimating the time-domain noise covariance of cosmic microwave background (CMB) observations, typically parameterized in terms of a 1/f frequency profile. This framework is based on the Gibbs sampling algorithm, which allows for exact marginalization over nuisance parameters through conditional probability distributions. In this paper, we implement support for gaps in the data streams and marginalization over fixed time-domain templates, and also outline how to marginalize over confusion from CMB fluctuations, which may be important for high signal-to-noise experiments. As a by-product of the method, we obtain proper constrained realizations, which themselves can be useful for map making. To validate the algorithm, we demonstrate that the reconstructed noise parameters and corresponding uncertainties are unbiased using simulated data. The CPU time required to process a single data stream of 100,000 samples with 1000 samples removed by gaps is 3 s if only the maximum posterior parameters are required, and 21 s if one also wants to obtain the corresponding uncertainties by Gibbs sampling.
Trajectories of Brownian particles with space-correlated noise
Indian Academy of Sciences (India)
EDOARDO MILOTTI
walks with spatially correlated white noise: the time- dependence of the distance of pairs of random walkers. ... Dedicated to the memory of the late Professor Charusita Chakravarty. also quite well-known that the two-sided noise .... due to the individual noise components, we find that in the present context the value of ξ2 is.
Blind Identification of FIR Channels in the Presence of Unknown Noise
Directory of Open Access Journals (Sweden)
Kon Max Wong
2007-01-01
Full Text Available Blind channel identification techniques based on second-order statistics (SOS of the received data have been a topic of active research in recent years. Among the most popular is the subspace method (SS proposed by Moulines et al. (1995. It has good performance when the channel output is corrupted by white noise. However, when the channel noise is correlated and unknown as is often encountered in practice, the performance of the SS method degrades severely. In this paper, we address the problem of estimating FIR channels in the presence of arbitrarily correlated noise whose covariance matrix is unknown. We propose several algorithms according to the different available system resources: (1 when only one receiving antenna is available, by upsampling the output, we develop the maximum a posteriori (MAP algorithm for which a simple criterion is obtained and an efficient implementation algorithm is developed; (2 when two receiving antennae are available, by upsampling both the outputs and utilizing canonical correlation decomposition (CCD to obtain the subspaces, we present two algorithms (CCD-SS and CCD-ML to blindly estimate the channels. Our algorithms perform well in unknown noise environment and outperform existing methods proposed for similar scenarios.
Multivariate covariance generalized linear models
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...
Noise-induced hearing loss: an occupational medicine perspective.
Stucken, Emily Z; Hong, Robert S
2014-10-01
Up to 30 million workers in the United States are exposed to potentially detrimental levels of noise. Although reliable medications for minimizing or reversing noise-induced hearing loss (NIHL) are not currently available, NIHL is entirely preventable. The purpose of this article is to review the epidemiology and pathophysiology of occupational NIHL. We will focus on at-risk populations and discuss prevention programs. Current prevention programs focus on reducing inner ear damage by minimizing environmental noise production and through the use of personal hearing protective devices. NIHL is the result of a complex interaction between environmental factors and patient factors, both genetic and acquired. The effects of noise exposure are specific to an individual. Trials are currently underway evaluating the role of antioxidants in protection from, and even reversal of, NIHL. Occupational NIHL is the most prevalent occupational disease in the United States. Occupational noise exposures may contribute to temporary or permanent threshold shifts, although even temporary threshold shifts may predispose an individual to eventual permanent hearing loss. Noise prevention programs are paramount in reducing hearing loss as a result of occupational exposures.
The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination
Directory of Open Access Journals (Sweden)
Liangping Wu
2014-08-01
Full Text Available Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.
Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise.
Vuković, Najdan; Miljković, Zoran
2015-03-01
Feedforward neural networks (FFNN) are among the most used neural networks for modeling of various nonlinear problems in engineering. In sequential and especially real time processing all neural networks models fail when faced with outliers. Outliers are found across a wide range of engineering problems. Recent research results in the field have shown that to avoid overfitting or divergence of the model, new approach is needed especially if FFNN is to run sequentially or in real time. To accommodate limitations of FFNN when training data contains a certain number of outliers, this paper presents new learning algorithm based on improvement of conventional extended Kalman filter (EKF). Extended Kalman filter robust to outliers (EKF-OR) is probabilistic generative model in which measurement noise covariance is not constant; the sequence of noise measurement covariance is modeled as stochastic process over the set of symmetric positive-definite matrices in which prior is modeled as inverse Wishart distribution. In each iteration EKF-OR simultaneously estimates noise estimates and current best estimate of FFNN parameters. Bayesian framework enables one to mathematically derive expressions, while analytical intractability of the Bayes' update step is solved by using structured variational approximation. All mathematical expressions in the paper are derived using the first principles. Extensive experimental study shows that FFNN trained with developed learning algorithm, achieves low prediction error and good generalization quality regardless of outliers' presence in training data. Copyright © 2014 Elsevier Ltd. All rights reserved.
Covariant single-hole optical potential
International Nuclear Information System (INIS)
Kam, J. de
1982-01-01
In this investigation a covariant optical potential model is constructed for scattering processes of mesons from nuclei in which the meson interacts repeatedly with one of the target nucleons. The nuclear binding interactions in the intermediate scattering state are consistently taken into account. In particular for pions and K - projectiles this is important in view of the strong energy dependence of the elementary projectile-nucleon amplitude. Furthermore, this optical potential satisfies unitarity and relativistic covariance. The starting point in our discussion is the three-body model for the optical potential. To obtain a practical covariant theory I formulate the three-body model as a relativistic quasi two-body problem. Expressions for the transition interactions and propagators in the quasi two-body equations are found by imposing the correct s-channel unitarity relations and by using dispersion integrals. This is done in such a way that the correct non-relativistic limit is obtained, avoiding clustering problems. Corrections to the quasi two-body treatment from the Pauli principle and the required ground-state exclusion are taken into account. The covariant equations that we arrive at are amenable to practical calculations. (orig.)
Nuclear data covariances in the Indian context
International Nuclear Information System (INIS)
Ganesan, S.
2014-01-01
The topic of covariances is recognized as an important part of several ongoing nuclear data science activities, since 2007, in the Nuclear Data Physics Centre of India (NDPCI). A Phase-1 project in collaboration with the Statistics department in Manipal University, Karnataka (Prof. K.M. Prasad and Prof. S. Nair) on nuclear data covariances was executed successfully during 2007-2011 period. In Phase-I, the NDPCI has conducted three national Theme meetings sponsored by the DAE-BRNS in 2008, 2010 and 2013 on nuclear data covariances. In Phase-1, the emphasis was on a thorough basic understanding of the concept of covariances including assigning uncertainties to experimental data in terms of partial errors and micro correlations, through a study and a detailed discussion of open literature. Towards the end of Phase-1, measurements and a first time covariance analysis of cross-sections for 58 Ni (n, p) 58 Co reaction measured in Mumbai Pelletron accelerator using 7 Li (p,n) reactions as neutron source in the MeV energy region were performed under a PhD programme on nuclear data covariances in which enrolled are two students, Shri B.S. Shivashankar and Ms. Shanti Sheela. India is also successfully evolving a team of young researchers to code nuclear data of uncertainties, with the perspectives on covariances, in the IAEA-EXFOR format. A Phase-II DAE-BRNS-NDPCI proposal of project at Manipal has been submitted and the proposal is undergoing a peer-review at this time. In Phase-2, modern nuclear data evaluation techniques that including covariances will be further studied as a research and development effort, as a first time effort. These efforts include the use of techniques such as that of the Kalman filter. Presently, a 48 hours lecture series on treatment of errors and their propagation is being formulated under auspices of the Homi Bhabha National Institute. The talk describes the progress achieved thus far in the learning curve of the above-mentioned and exciting
AFCI-2.0 Neutron Cross Section Covariance Library
Energy Technology Data Exchange (ETDEWEB)
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
AFCI-2.0 Neutron Cross Section Covariance Library
International Nuclear Information System (INIS)
Herman, M.; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-01-01
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R and D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78
Metagenomic covariation along densely sampled environmental gradients in the Red Sea
Thompson, Luke R
2016-07-15
Oceanic microbial diversity covaries with physicochemical parameters. Temperature, for example, explains approximately half of global variation in surface taxonomic abundance. It is unknown, however, whether covariation patterns hold over narrower parameter gradients and spatial scales, and extending to mesopelagic depths. We collected and sequenced 45 epipelagic and mesopelagic microbial metagenomes on a meridional transect through the eastern Red Sea. We asked which environmental parameters explain the most variation in relative abundances of taxonomic groups, gene ortholog groups, and pathways—at a spatial scale of <2000 km, along narrow but well-defined latitudinal and depth-dependent gradients. We also asked how microbes are adapted to gradients and extremes in irradiance, temperature, salinity, and nutrients, examining the responses of individual gene ortholog groups to these parameters. Functional and taxonomic metrics were equally well explained (75–79%) by environmental parameters. However, only functional and not taxonomic covariation patterns were conserved when comparing with an intruding water mass with different physicochemical properties. Temperature explained the most variation in each metric, followed by nitrate, chlorophyll, phosphate, and salinity. That nitrate explained more variation than phosphate suggested nitrogen limitation, consistent with low surface N:P ratios. Covariation of gene ortholog groups with environmental parameters revealed patterns of functional adaptation to the challenging Red Sea environment: high irradiance, temperature, salinity, and low nutrients. Nutrient-acquisition gene ortholog groups were anti-correlated with concentrations of their respective nutrient species, recapturing trends previously observed across much larger distances and environmental gradients. This dataset of metagenomic covariation along densely sampled environmental gradients includes online data exploration supplements, serving as a community
Orga, Ferran; Alías, Francesc; Alsina-Pagès, Rosa Ma
2017-12-23
Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.
Spatial noise in staring IR focal plane arrays
International Nuclear Information System (INIS)
Scribner, D.A.; Kruer, M.R.; Sarkady, K.; Gridley, J.C.
1988-01-01
Problems with nonuniformity correction algorithms due to nonlinear pixel response and 1/f noise have been shown previously to cause spatial noise which can be significantly greater than temporal noise. The residual spatial noise after correction cannot be reduced with time averaging. Because of spatial noise the sensitivity of staring FPA sensors is often less than predicted on the basis of the temporal noise of the individual elements. A review is given of methods for measuring and analyzing spatial noise (after nonuniformity correction) in staring infrared focal plane arrays. Automated measurement techniques are described briefly, including necessary equipment and data reduction procedures. An example of spatial noise measurements is given using a staring InSb Charge Injection Device (CID) array
Dias, Adriano; Cordeiro, Ricardo
2007-07-01
Noise is the most frequent type of occupational exposure and can lead to both auditory and extra-auditory dysfunction as well as increasing the risk of work accidents. The purpose of this study was to estimate the attributable fraction of work accidents related to occupational noise exposure in a medium-sized city in Southeast Brazil. In this hospital-based case-control study, including 600 cases and 822 controls, the odds ratio of work accidents (controlled for several covariables) was obtained classifying occupational noise exposure into four levels and determining the prevalence at each level. Based on these data, the calculated attributable fraction was 0.3041 (95%CI: 0.2341-0.3676), i.e., 30% of work accidents in the study area were statistically associated with occupational noise exposure. The authors discuss the causes of this association and the implications for the prevention of work accidents.
Speech perception in noise in unilateral hearing loss
Mondelli, Maria Fernanda Capoani Garcia; dos Santos, Marina de Marchi; José, Maria Renata
2016-01-01
ABSTRACT INTRODUCTION: Unilateral hearing loss is characterized by a decrease of hearing in one ear only. In the presence of ambient noise, individuals with unilateral hearing loss are faced with greater difficulties understanding speech than normal listeners. OBJECTIVE: To evaluate the speech perception of individuals with unilateral hearing loss in speech perception with and without competitive noise, before and after the hearing aid fitting process. METHODS: The study included 30 adu...
Central subspace dimensionality reduction using covariance operators.
Kim, Minyoung; Pavlovic, Vladimir
2011-04-01
We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.
International Nuclear Information System (INIS)
Fu, C.Y.; Hetrick, D.M.
1982-01-01
Recent ratio data, with carefully evaluated covariances, were combined with eleven of the ENDF/B-V dosimetry cross sections using the generalized least-squares method. The purpose was to improve these evaluated cross sections and covariances, as well as to generate values for the cross-reaction covariances. The results represent improved cross sections as well as realistic and usable covariances. The latter are necessary for meaningful intergral-differential comparisons and for spectrum unfolding
High-dimensional covariance estimation with high-dimensional data
Pourahmadi, Mohsen
2013-01-01
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Covariance problem in two-dimensional quantum chromodynamics
International Nuclear Information System (INIS)
Hagen, C.R.
1979-01-01
The problem of covariance in the field theory of a two-dimensional non-Abelian gauge field is considered. Since earlier work has shown that covariance fails (in charged sectors) for the Schwinger model, particular attention is given to an evaluation of the role played by the non-Abelian nature of the fields. In contrast to all earlier attempts at this problem, it is found that the potential covariance-breaking terms are identical to those found in the Abelian theory provided that one expresses them in terms of the total (i.e., conserved) current operator. The question of covariance is thus seen to reduce in all cases to a determination as to whether there exists a conserved global charge in the theory. Since the charge operator in the Schwinger model is conserved only in neutral sectors, one is thereby led to infer a probable failure of covariance in the non-Abelian theory, but one which is identical to that found for the U(1) case
Schroedinger covariance states in anisotropic waveguides
International Nuclear Information System (INIS)
Angelow, A.; Trifonov, D.
1995-03-01
In this paper Squeezed and Covariance States based on Schroedinger inequality and their connection with other nonclassical states are considered for particular case of anisotropic waveguide in LiNiO 3 . Here, the problem of photon creation and generation of squeezed and Schroedinger covariance states in optical waveguides is solved in two steps: 1. Quantization of electromagnetic field is provided in the presence of dielectric waveguide using normal-mode expansion. The photon creation and annihilation operators are introduced, expanding the solution A-vector(r-vector,t) in a series in terms of the Sturm - Liouville mode-functions. 2. In terms of these operators the Hamiltonian of the field in a nonlinear waveguide is derived. For such Hamiltonian we construct the covariance states as stable (with nonzero covariance), which minimize the Schroedinger uncertainty relation. The evolutions of the three second momenta of q-circumflex j and p-circumflex j are calculated. For this Hamiltonian all three momenta are expressed in terms of one real parameters s only. It is found out how covariance, via this parameter s, depends on the waveguide profile n(x,y), on the mode-distributions u-vector j (x,y), and on the waveguide phase mismatching Δβ. (author). 37 refs
Form of the manifestly covariant Lagrangian
Johns, Oliver Davis
1985-10-01
The preferred form for the manifestly covariant Lagrangian function of a single, charged particle in a given electromagnetic field is the subject of some disagreement in the textbooks. Some authors use a ``homogeneous'' Lagrangian and others use a ``modified'' form in which the covariant Hamiltonian function is made to be nonzero. We argue in favor of the ``homogeneous'' form. We show that the covariant Lagrangian theories can be understood only if one is careful to distinguish quantities evaluated on the varied (in the sense of the calculus of variations) world lines from quantities evaluated on the unvaried world lines. By making this distinction, we are able to derive the Hamilton-Jacobi and Klein-Gordon equations from the ``homogeneous'' Lagrangian, even though the covariant Hamiltonian function is identically zero on all world lines. The derivation of the Klein-Gordon equation in particular gives Lagrangian theoretical support to the derivations found in standard quantum texts, and is also shown to be consistent with the Feynman path-integral method. We conclude that the ``homogeneous'' Lagrangian is a completely adequate basis for covariant Lagrangian theory both in classical and quantum mechanics. The article also explores the analogy with the Fermat theorem of optics, and illustrates a simple invariant notation for the Lagrangian and other four-vector equations.
Convex Banding of the Covariance Matrix.
Bien, Jacob; Bunea, Florentina; Xiao, Luo
2016-01-01
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.
Annoyance rating of wind turbine noise
International Nuclear Information System (INIS)
Iredale, R.
1993-01-01
Annoyance rating is important, but more important still is agreement on techniques for formulating minimal complaint criteria for design and specification purposes thus integrating noise control into the plant at the outset. A minimal complaint design criteria is suggested that finds its origin in the logic and techniques used successfully over many years for a wide range of power plant and other installations. The criterion is based on the masking of the wind turbine noise by the wind generated background noise. Satisfactory use of the criterion depends on the specification of inaudibility for the tones generated by the mechanical plant. Wind turbines generate more drive train noise than is realized and this contains many tones which tend to characterize the noise. Reduction of drive train noise would not only reduce the overall noise level but also give it a more acceptable character providing a margin against complaint in unusual circumstances of propagation. This requires very careful design of noise and vibration control in individual components. Vibration isolation between the support structures and the nacelle also requires careful attention. (UK)
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the covariant commutator anomalies are calculated for the two- and four dimensional case. (orig.)
Cross-population myelination covariance of human cerebral cortex.
Ma, Zhiwei; Zhang, Nanyin
2017-09-01
Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Covariant extensions and the nonsymmetric unified field
International Nuclear Information System (INIS)
Borchsenius, K.
1976-01-01
The problem of generally covariant extension of Lorentz invariant field equations, by means of covariant derivatives extracted from the nonsymmetric unified field, is considered. It is shown that the contracted curvature tensor can be expressed in terms of a covariant gauge derivative which contains the gauge derivative corresponding to minimal coupling, if the universal constant p, characterizing the nonsymmetric theory, is fixed in terms of Planck's constant and the elementary quantum of charge. By this choice the spinor representation of the linear connection becomes closely related to the spinor affinity used by Infeld and Van Der Waerden (Sitzungsber. Preuss. Akad. Wiss. Phys. Math. Kl.; 9:380 (1933)) in their generally covariant formulation of Dirac's equation. (author)
Computing more proper covariances of energy dependent nuclear data
International Nuclear Information System (INIS)
Vanhanen, R.
2016-01-01
Highlights: • We present conditions for covariances of energy dependent nuclear data to be proper. • We provide methods to detect non-positive and inconsistent covariances in ENDF-6 format. • We propose methods to find nearby more proper covariances. • The methods can be used as a part of a quality assurance program. - Abstract: We present conditions for covariances of energy dependent nuclear data to be proper in the sense that the covariances are positive, i.e., its eigenvalues are non-negative, and consistent with respect to the sum rules of nuclear data. For the ENDF-6 format covariances we present methods to detect non-positive and inconsistent covariances. These methods would be useful as a part of a quality assurance program. We also propose methods that can be used to find nearby more proper energy dependent covariances. These methods can be used to remove unphysical components, while preserving most of the physical components. We consider several different senses in which the nearness can be measured. These methods could be useful if a re-evaluation of improper covariances is not feasible. Two practical examples are processed and analyzed. These demonstrate some of the properties of the methods. We also demonstrate that the ENDF-6 format covariances of linearly dependent nuclear data should usually be encoded with the derivation rules.
Covariance Spectroscopy for Fissile Material Detection
International Nuclear Information System (INIS)
Trainham, Rusty; Tinsley, Jim; Hurley, Paul; Keegan, Ray
2009-01-01
Nuclear fission produces multiple prompt neutrons and gammas at each fission event. The resulting daughter nuclei continue to emit delayed radiation as neutrons boil off, beta decay occurs, etc. All of the radiations are causally connected, and therefore correlated. The correlations are generally positive, but when different decay channels compete, so that some radiations tend to exclude others, negative correlations could also be observed. A similar problem of reduced complexity is that of cascades radiation, whereby a simple radioactive decay produces two or more correlated gamma rays at each decay. Covariance is the usual means for measuring correlation, and techniques of covariance mapping may be useful to produce distinct signatures of special nuclear materials (SNM). A covariance measurement can also be used to filter data streams because uncorrelated signals are largely rejected. The technique is generally more effective than a coincidence measurement. In this poster, we concentrate on cascades and the covariance filtering problem
Optimal covariate designs theory and applications
Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar
2015-01-01
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Aircraft noise, health, and residential sorting: evidence from two quasi-experiments.
Boes, Stefan; Nüesch, Stephan; Stillman, Steven
2013-09-01
We explore two unexpected changes in flight regulations to estimate the causal effect of aircraft noise on health. Detailed measures of noise are linked with longitudinal data on individual health outcomes based on the exact address information. Controlling for individual heterogeneity and spatial sorting into different neighborhoods, we find that aircraft noise significantly increases sleeping problems and headaches. Models that do not control for such heterogeneity and sorting substantially underestimate the negative health effects, which suggests that individuals self-select into residence based on their unobserved sensitivity to noise. Our study demonstrates that the combination of quasi-experimental variation and panel data is very powerful for identifying causal effects in epidemiological field studies. Copyright © 2013 John Wiley & Sons, Ltd.
Covariate Imbalance and Precision in Measuring Treatment Effects
Liu, Xiaofeng Steven
2011-01-01
Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…
Covariant description of Hamiltonian form for field dynamics
International Nuclear Information System (INIS)
Ozaki, Hiroshi
2005-01-01
Hamiltonian form of field dynamics is developed on a space-like hypersurface in space-time. A covariant Poisson bracket on the space-like hypersurface is defined and it plays a key role to describe every algebraic relation into a covariant form. It is shown that the Poisson bracket has the same symplectic structure that was brought in the covariant symplectic approach. An identity invariant under the canonical transformations is obtained. The identity follows a canonical equation in which the interaction Hamiltonian density generates a deformation of the space-like hypersurface. The equation just corresponds to the Yang-Feldman equation in the Heisenberg pictures in quantum field theory. By converting the covariant Poisson bracket on the space-like hypersurface to four-dimensional commutator, we can pass over to quantum field theory in the Heisenberg picture without spoiling the explicit relativistic covariance. As an example the canonical QCD is displayed in a covariant way on a space-like hypersurface
Dimension from covariance matrices.
Carroll, T L; Byers, J M
2017-02-01
We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.
ANL Critical Assembly Covariance Matrix Generation - Addendum
Energy Technology Data Exchange (ETDEWEB)
McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)
2014-01-13
In March 2012, a report was issued on covariance matrices for Argonne National Laboratory (ANL) critical experiments. That report detailed the theory behind the calculation of covariance matrices and the methodology used to determine the matrices for a set of 33 ANL experimental set-ups. Since that time, three new experiments have been evaluated and approved. This report essentially updates the previous report by adding in these new experiments to the preceding covariance matrix structure.
Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.
2011-01-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models
Condition Number Regularized Covariance Estimation.
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2013-06-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Analysis of broadband aerodynamic noise from VS45
Energy Technology Data Exchange (ETDEWEB)
Dundabin, P. [Renewable Energy Systems Ltd., Glasgow, Scotland (United Kingdom)
1997-12-31
This paper describes the analysis of acoustic data taken from the VS45 at Kaiser-Wilhelm-Koog. The aim was to investigate the dependence of aerodynamic noise on tip speed and angle of attack. In particular, the dependence of noise in individual third octave bands on these variable is examined. The analysis is divided into 3 sections: data selection, data checks and analysis of broadband nacelle noise; analysis of broadband aerodynamic noise and its sensitivity to tip speed and angle of attack. (LN)
Parametric Covariance Model for Horizon-Based Optical Navigation
Hikes, Jacob; Liounis, Andrew J.; Christian, John A.
2016-01-01
This Note presents an entirely parametric version of the covariance for horizon-based optical navigation measurements. The covariance can be written as a function of only the spacecraft position, two sensor design parameters, the illumination direction, the size of the observed planet, the size of the lit arc to be used, and the total number of observed horizon points. As a result, one may now more clearly understand the sensitivity of horizon-based optical navigation performance as a function of these key design parameters, which is insight that was obscured in previous (and nonparametric) versions of the covariance. Finally, the new parametric covariance is shown to agree with both the nonparametric analytic covariance and results from a Monte Carlo analysis.
Directory of Open Access Journals (Sweden)
Farinoosh Fakharnia
2010-06-01
Full Text Available Background and Aim: Balance disturbance is one of the non-auditory effects of noisy industrial environments that is usually neglected. The aim of the current study was to investigate the effect of occupational noise on vestibular system among workers with noise-induced hearing loss (NIHL, based on both vestibular evoked myogenic potentials (VEMP and caloric tests.Methods: Thirty male workers with noise-induced hearing loss and thirty male matched controls were examined by VEMP and caloric tests. Study parameters included unilateral weakness, p13 and n23 latencies, and p13-n23 amplitude. Caloric test was performed only for 20 patients.Results: No significant difference was observed in unilateral weakness between the two groups. On the other hand, the difference in mean latencies of p13 in the right ear (p=0.003 and left ear (p=0.01 was significant between the two groups. However, the difference in n23 latency was significant only in the right ear (p=0.03. There was no significant difference between groups in p13-n23 amplitude.Conclusion: It seems that pars inferior of vestibule is the susceptible part in individuals with NIHL. In general, abnormal findings in both VEMP and caloric tests were more common compared to functional symptoms such as vertigo, which may be due to central compensation and the symmetry of the disorder.
Activities on covariance estimation in Japanese Nuclear Data Committee
Energy Technology Data Exchange (ETDEWEB)
Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1997-03-01
Described are activities on covariance estimation in the Japanese Nuclear Data Committee. Covariances are obtained from measurements by using the least-squares methods. A simultaneous evaluation was performed to deduce covariances of fission cross sections of U and Pu isotopes. A code system, KALMAN, is used to estimate covariances of nuclear model calculations from uncertainties in model parameters. (author)
Neutron spectrum adjustment. The role of covariances
International Nuclear Information System (INIS)
Remec, I.
1992-01-01
Neutron spectrum adjustment method is shortly reviewed. Practical example dealing with power reactor pressure vessel exposure rates determination is analysed. Adjusted exposure rates are found only slightly affected by the covariances of measured reaction rates and activation cross sections, while the multigroup spectra covariances were found important. Approximate spectra covariance matrices, as suggested in Astm E944-89, were found useful but care is advised if they are applied in adjustments of spectra at locations without dosimetry. (author) [sl
The method of covariant symbols in curved space-time
International Nuclear Information System (INIS)
Salcedo, L.L.
2007-01-01
Diagonal matrix elements of pseudodifferential operators are needed in order to compute effective Lagrangians and currents. For this purpose the method of symbols is often used, which however lacks manifest covariance. In this work the method of covariant symbols, introduced by Pletnev and Banin, is extended to curved space-time with arbitrary gauge and coordinate connections. For the Riemannian connection we compute the covariant symbols corresponding to external fields, the covariant derivative and the Laplacian, to fourth order in a covariant derivative expansion. This allows one to obtain the covariant symbol of general operators to the same order. The procedure is illustrated by computing the diagonal matrix element of a nontrivial operator to second order. Applications of the method are discussed. (orig.)
Healy, Eric W; Yoho, Sarah E
2016-08-01
A primary complaint of hearing-impaired individuals involves poor speech understanding when background noise is present. Hearing aids and cochlear implants often allow good speech understanding in quiet backgrounds. But hearing-impaired individuals are highly noise intolerant, and existing devices are not very effective at combating background noise. As a result, speech understanding in noise is often quite poor. In accord with the significance of the problem, considerable effort has been expended toward understanding and remedying this issue. Fortunately, our understanding of the underlying issues is reasonably good. In sharp contrast, effective solutions have remained elusive. One solution that seems promising involves a single-microphone machine-learning algorithm to extract speech from background noise. Data from our group indicate that the algorithm is capable of producing vast increases in speech understanding by hearing-impaired individuals. This paper will first provide an overview of the speech-in-noise problem and outline why hearing-impaired individuals are so noise intolerant. An overview of our approach to solving this problem will follow.
Conformally covariant massless spin-two field equations
International Nuclear Information System (INIS)
Drew, M.S.; Gegenberg, J.D.
1980-01-01
An explicit proof is constructed to show that the field equations for a symmetric tensor field hsub(ab) describing massless spin-2 particles in Minkowski space-time are not covariant under the 15-parameter group SOsub(4,2); this group is usually associated with conformal transformations on flat space, and here it will be considered as a global gauge group which acts upon matter fields defined on space-time. Notwithstanding the above noncovariance, the equations governing the rank-4 tensor Ssub(abcd) constructed from hsub(ab) are shown to be covariant provided the contraction Ssub(ab) vanishes. Conformal covariance is proved by demonstrating the covariance of the equations for the equivalent 5-component complex field; in fact, covariance is proved for a general field equation applicable to massless particles of any spin >0. It is shown that the noncovariance of the hsub(ab) equations may be ascribed to the fact that the transformation behaviour of hsub(ab) is not the same as that of a field consisting of a gauge only. Since this is in contradistinction to the situation for the electromagnetic-field equations, the vector form of the electromagnetic equations is cast into a form which can be duplicated for the hsub(ab)-field. This procedure results in an alternative, covariant, field equation for hsub(ab). (author)
Directory of Open Access Journals (Sweden)
Mariola Sliwinska-Kowalska
2012-01-01
Full Text Available Noise-induced hearing loss (NIHL still remains a problem in developed countries, despite reduced occupational noise exposure, strict standards for hearing protection and extensive public health awareness campaigns. Therefore NIHL continues to be the focus of noise research activities. This paper summarizes progress achieved recently in our knowledge of NIHL. It includes papers published between the years 2008-2011 (in English, which were identified by a literature search of accessible medical and other relevant databases. A substantial part of this research has been concerned with the risk of NIHL in the entertainment sector, particularly in professional, orchestral musicians. There are also constant concerns regarding noise exposure and hearing risk in "hard to control" occupations, such as farming and construction work. Although occupational noise has decreased since the early 1980s, the number of young people subject to social noise exposure has tripled. If the exposure limits from the Noise at Work Regulations are applied, discotheque music, rock concerts, as well as music from personal music players are associated with the risk of hearing loss in teenagers and young adults. Several recent research studies have increased the understanding of the pathomechanisms of acoustic trauma, the genetics of NIHL, as well as possible dietary and pharmacologic otoprotection in acoustic trauma. The results of these studies are very promising and offer grounds to expect that targeted therapies might help prevent the loss of sensory hair cells and protect the hearing of noise-exposed individuals. These studies emphasize the need to launch an improved noise exposure policy for hearing protection along with developing more efficient norms of NIHL risk assessment.
Do executive functions explain the covariance between internalizing and externalizing behaviors?
Hatoum, Alexander S; Rhee, Soo Hyun; Corley, Robin P; Hewitt, John K; Friedman, Naomi P
2017-11-16
This study examined whether executive functions (EFs) might be common features of internalizing and externalizing behavior problems across development. We examined relations between three EF latent variables (a common EF factor and factors specific to updating working memory and shifting sets), constructed from nine laboratory tasks administered at age 17, to latent growth intercept (capturing stability) and slope (capturing change) factors of teacher- and parent-reported internalizing and externalizing behaviors in 885 individual twins aged 7 to 16 years. We then estimated the proportion of intercept-intercept and slope-slope correlations predicted by EF as well as the association between EFs and a common psychopathology factor (P factor) estimated from all 9 years of internalizing and externalizing measures. Common EF was negatively associated with the intercepts of teacher-rated internalizing and externalizing behavior in males, and explained 32% of their covariance; in the P factor model, common EF was associated with the P factor in males. Shifting-specific was positively associated with the externalizing slope across sex. EFs did not explain covariation between parent-rated behaviors. These results suggest that EFs are associated with stable problem behavior variation, explain small proportions of covariance, and are a risk factor that that may depend on gender.
Noise-driven manifestation of learning in mature neural networks
International Nuclear Information System (INIS)
Monterola, Christopher; Saloma, Caesar
2002-01-01
We show that the generalization capability of a mature thresholding neural network to process above-threshold disturbances in a noise-free environment is extended to subthreshold disturbances by ambient noise without retraining. The ability to benefit from noise is intrinsic and does not have to be learned separately. Nonlinear dependence of sensitivity with noise strength is significantly narrower than in individual threshold systems. Noise has a minimal effect on network performance for above-threshold signals. We resolve two seemingly contradictory responses of trained networks to noise--their ability to benefit from its presence and their robustness against noisy strong disturbances
Evaluation of covariance for 238U cross sections
International Nuclear Information System (INIS)
Kawano, Toshihiko; Nakamura, Masahiro; Matsuda, Nobuyuki; Kanda, Yukinori
1995-01-01
Covariances of 238 U are generated using analytic functions for representation of the cross sections. The covariances of the (n,2n) and (n,3n) reactions are derived with a spline function, while the covariances of the total and the inelastic scattering cross section are estimated with a linearized nuclear model calculation. (author)
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1993-01-01
We consider GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations. We show that, up to some inessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. The connection with the bicovariant differential calculus on the linear quantum groups is discussed. (orig.)
Asset allocation with different covariance/correlation estimators
Μανταφούνη, Σοφία
2007-01-01
The subject of the study is to test whether the use of different covariance – correlation estimators than the historical covariance matrix that is widely used, would help in portfolio optimization through the mean-variance analysis. In other words, if an investor would like to use the mean-variance analysis in order to invest in assets like stocks or indices, would it be of some help to use more sophisticated estimators for the covariance matrix of the returns of his portfolio? The procedure ...
Co-variation of fatigue and psychobiological stress in couples' everyday life.
Doerr, Johanna M; Nater, Urs M; Ehlert, Ulrike; Ditzen, Beate
2018-06-01
There is limited knowledge about how fatigue develops and worsens and what influences fluctuations in daily fatigue. Stress was found to influence fatigue, and being in a relationship seems to either increase or decrease stress depending on the couple interaction. In this study, co-variation of fatigue, self-reported stress, and biological stress markers in couples' everyday lives was investigated. Specifically, we examined a) whether momentary couple interactions moderated dyadic outcomes and b) whether and how stress and relationship measures influenced individual momentary fatigue. Forty heterosexual couples (age: 28 ± 5 years) reported subjective fatigue and stress levels 4 times a day for 5 consecutive days (1600 measures). Furthermore, participants reported whether they had interacted with their partner since the last data entry and, if so, they rated the valence of this interaction. Salivary cortisol (a measure of HPA axis activity) and alpha amylase (a measure of ANS activity) were analyzed as biological stress markers from saliva samples obtained at the same time points. Moment-to-moment data were analyzed using dyadic multilevel models to account for the nested design. Stress (women and men: p ≤ 0.001) and fatigue (women: p = .003, men: p = .020) showed patterns of co-variation within couples, especially if partners had interacted with each other since the previous data entry. Cortisol was also found to co-vary between partners (women: unstandardized coefficient (UC) = 0.12, p ≤ .001, men: UC = 0.18, p ≤ .001), whereas the regulation of alpha-amylase levels depending on the partner's levels was only present in women (UC = 0.11, p = .002). Valence of couple interaction was negatively associated with fatigue (women: UC = -0.13, p ≤ .001, men: UC = -0.06, p = .011). There was no momentary association of fatigue with an individual's own or the partner's subjective or biological stress markers
Paquola, Casey; Bennett, Maxwell; Lagopoulos, Jim
2018-05-15
Structural covariance networks (SCNs) may offer unique insights into the developmental impact of childhood maltreatment because they are thought to reflect coordinated maturation of distinct grey matter regions. T1-weighted magnetic resonance images were acquired from 121 young people with emerging mental illness. Diffusion weighted and resting state functional imaging was also acquired from a random subset of the participants (n=62). Ten study-specific SCNs were identified using a whole brain grey matter independent component analysis. The effects of childhood maltreatment and age on average grey matter density and the expression of each SCN were calculated. Childhood maltreatment was linked to age-related decreases in grey matter density across a SCN that overlapped with the default mode and fronto-parietal networks. Resting state functional connectivity and structural connectivity were calculated in the study-specific SCN and across the whole brain. Grey matter covariance was significantly correlated with rsFC across the SCN, and rsFC fully mediated the relationship between grey matter covariance and structural connectivity in the non-maltreated group. A unique association of grey matter covariance with structural connectivity was detected amongst individuals with a history of childhood maltreatment. Perturbation of grey matter development across the default mode and fronto-parietal networks following childhood maltreatment may have significant implications for mental well-being, given the networks' roles in self-referential activity. Cross-modal comparisons suggest reduced grey matter following childhood maltreatment could arise from deficient functional activity earlier in life.
40 CFR 1065.305 - Verifications for accuracy, repeatability, and noise.
2010-07-01
..., repeatability, and noise. 1065.305 Section 1065.305 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Verifications for accuracy, repeatability, and noise. (a) This section describes how to determine the accuracy, repeatability, and noise of an instrument. Table 1 of § 1065.205 specifies recommended values for individual...
Socio-Cognitive Phenotypes Differentially Modulate Large-Scale Structural Covariance Networks.
Valk, Sofie L; Bernhardt, Boris C; Böckler, Anne; Trautwein, Fynn-Mathis; Kanske, Philipp; Singer, Tania
2017-02-01
Functional neuroimaging studies have suggested the existence of 2 largely distinct social cognition networks, one for theory of mind (taking others' cognitive perspective) and another for empathy (sharing others' affective states). To address whether these networks can also be dissociated at the level of brain structure, we combined behavioral phenotyping across multiple socio-cognitive tasks with 3-Tesla MRI cortical thickness and structural covariance analysis in 270 healthy adults, recruited across 2 sites. Regional thickness mapping only provided partial support for divergent substrates, highlighting that individual differences in empathy relate to left insular-opercular thickness while no correlation between thickness and mentalizing scores was found. Conversely, structural covariance analysis showed clearly divergent network modulations by socio-cognitive and -affective phenotypes. Specifically, individual differences in theory of mind related to structural integration between temporo-parietal and dorsomedial prefrontal regions while empathy modulated the strength of dorsal anterior insula networks. Findings were robust across both recruitment sites, suggesting generalizability. At the level of structural network embedding, our study provides a double dissociation between empathy and mentalizing. Moreover, our findings suggest that structural substrates of higher-order social cognition are reflected rather in interregional networks than in the the local anatomical markup of specific regions per se. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Students’ Covariational Reasoning in Solving Integrals’ Problems
Harini, N. V.; Fuad, Y.; Ekawati, R.
2018-01-01
Covariational reasoning plays an important role to indicate quantities vary in learning calculus. This study investigates students’ covariational reasoning during their studies concerning two covarying quantities in integral problem. Six undergraduate students were chosen to solve problems that involved interpreting and representing how quantities change in tandem. Interviews were conducted to reveal the students’ reasoning while solving covariational problems. The result emphasizes that undergraduate students were able to construct the relation of dependent variables that changes in tandem with the independent variable. However, students faced difficulty in forming images of continuously changing rates and could not accurately apply the concept of integrals. These findings suggest that learning calculus should be increased emphasis on coordinating images of two quantities changing in tandem about instantaneously rate of change and to promote conceptual knowledge in integral techniques.
Forecasting Covariance Matrices: A Mixed Frequency Approach
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...
Covariance upperbound controllers for networked control systems
International Nuclear Information System (INIS)
Ko, Sang Ho
2012-01-01
This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers
ERRORJ. Covariance processing code system for JENDL. Version 2
International Nuclear Information System (INIS)
Chiba, Gou
2003-09-01
ERRORJ is the covariance processing code system for Japanese Evaluated Nuclear Data Library (JENDL) that can produce group-averaged covariance data to apply it to the uncertainty analysis of nuclear characteristics. ERRORJ can treat the covariance data for cross sections including resonance parameters as well as angular distributions and energy distributions of secondary neutrons which could not be dealt with by former covariance processing codes. In addition, ERRORJ can treat various forms of multi-group cross section and produce multi-group covariance file with various formats. This document describes an outline of ERRORJ and how to use it. (author)
ACORNS, Covariance and Correlation Matrix Diagonalization
International Nuclear Information System (INIS)
Szondi, E.J.
1990-01-01
1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT
The association of noise sensitivity with music listening, training, and aptitude.
Kliuchko, Marina; Heinonen-Guzejev, Marja; Monacis, Lucia; Gold, Benjamin P; Heikkilä, Kauko V; Spinosa, Vittoria; Tervaniemi, Mari; Brattico, Elvira
2015-01-01
After intensive, long-term musical training, the auditory system of a musician is specifically tuned to perceive musical sounds. We wished to find out whether a musician's auditory system also develops increased sensitivity to any sound of everyday life, experiencing them as noise. For this purpose, an online survey, including questionnaires on noise sensitivity, musical background, and listening tests for assessing musical aptitude, was administered to 197 participants in Finland and Italy. Subjective noise sensitivity (assessed with the Weinstein's Noise Sensitivity Scale) was analyzed for associations with musicianship, musical aptitude, weekly time spent listening to music, and the importance of music in each person's life (or music importance). Subjects were divided into three groups according to their musical expertise: Nonmusicians (N = 103), amateur musicians (N = 44), and professional musicians (N = 50). The results showed that noise sensitivity did not depend on musical expertise or performance on musicality tests or the amount of active (attentive) listening to music. In contrast, it was associated with daily passive listening to music, so that individuals with higher noise sensitivity spent less time in passive (background) listening to music than those with lower sensitivity to noise. Furthermore, noise-sensitive respondents rated music as less important in their life than did individuals with lower sensitivity to noise. The results demonstrate that the special sensitivity of the auditory system derived from musical training does not lead to increased irritability from unwanted sounds. However, the disposition to tolerate contingent musical backgrounds in everyday life depends on the individual's noise sensitivity.
Condition Number Regularized Covariance Estimation*
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2012-01-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Larranaga, Nicolas; Baguette, Michel; Calvez, Olivier; Trochet, Audrey; Ducatez, Simon; Legrand, Delphine
2013-08-15
Flight direction is a major component of an animal's migratory success. However, few studies have focused on variation in flight direction both between and within individuals, which is likely to be correlated with other traits implied in migration processes. We report patterns of intra- and inter-individual variation in flight direction in the large white butterfly Pieris brassicae. The presence of inter-individual variation in flight direction for individuals tested in the same conditions suggests that this trait is inherited in P. brassicae and we propose that a rapid loss of migratory skills may exist in the absence of selection for migration. The magnitude of intra-individual variation was negatively correlated to two surrogates of the potential for migration: mobility and wing length. Highly mobile and longed-winged individuals within the same family were found to fly in similar directions, whereas less mobile and short-winged individuals displayed divergent flight direction compared with the average direction of their kin. There was also a negative correlation between the variance to the mean flight direction of a family and its average mobility, but no correlation with wing length. We discuss these issues in terms of the evolution of traits potentially implied in both migration and dispersal in P. brassicae.
Heteroscedasticity resistant robust covariance matrix estimator
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2010-01-01
Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf
How much do genetic covariances alter the rate of adaptation?
Agrawal, Aneil F; Stinchcombe, John R
2009-03-22
Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.
Directory of Open Access Journals (Sweden)
Vincent Raquin
2017-12-01
Full Text Available Dengue virus (DENV causes more human infections than any other mosquito-borne virus. The current lack of antiviral strategies has prompted genome-wide screens for host genes that are required for DENV infectivity. Earlier transcriptomic studies that identified DENV host factors in the primary vector Aedes aegypti used inbred laboratory colonies and/or pools of mosquitoes that erase individual variation. Here, we performed transcriptome sequencing on individual midguts in a field-derived Ae. aegypti population to identify new candidate host factors modulating DENV replication. We analyzed the transcriptomic data using an approach that accounts for individual co-variation between viral RNA load and gene expression. This approach generates a prediction about the agonist or antagonist effect of candidate genes on DENV replication based on the sign of the correlation between gene expression and viral RNA load. Using this method, we identified 39 candidate genes that went undetected by conventional pairwise comparison of gene expression levels between DENV-infected midguts and uninfected controls. Only four candidate genes were detected by both methods, emphasizing their complementarity. We demonstrated the value of our approach by functional validation of a candidate agonist gene encoding a sterol regulatory element-binding protein (SREBP, which was identified by correlation analysis but not by pairwise comparison. We confirmed that SREBP promotes DENV infection in the midgut by RNAi-mediated gene knockdown in vivo. We suggest that our approach for transcriptomic analysis can empower genome-wide screens for potential agonist or antagonist factors by leveraging inter-individual variation in gene expression. More generally, this method is applicable to a wide range of phenotypic traits displaying inter-individual variation.
Squares of White Noise, SL(2,C) and Kubo - Martin -Schwinger States
Prokhorenko, D. V.
2007-01-01
We investigate the structure of Kubo - Martin - Schwinger (KMS) states on some extension of the universal enveloping algebra of SL(2,C}. We find that there exists a one-to-one correspondence between the set of all covariant KMS states on this algebra and the set of all probability measures d\\mu on the real half-line, which decrease faster than any inverse polynomial. This problem is connected to the problem of KMS states on square of white noise algebra.
Long-term exposure to noise impairs cortical sound processing and attention control.
Kujala, Teija; Shtyrov, Yury; Winkler, Istvan; Saher, Marieke; Tervaniemi, Mari; Sallinen, Mikael; Teder-Sälejärvi, Wolfgang; Alho, Kimmo; Reinikainen, Kalevi; Näätänen, Risto
2004-11-01
Long-term exposure to noise impairs human health, causing pathological changes in the inner ear as well as other anatomical and physiological deficits. Numerous individuals are daily exposed to excessive noise. However, there is a lack of systematic research on the effects of noise on cortical function. Here we report data showing that long-term exposure to noise has a persistent effect on central auditory processing and leads to concurrent behavioral deficits. We found that speech-sound discrimination was impaired in noise-exposed individuals, as indicated by behavioral responses and the mismatch negativity brain response. Furthermore, irrelevant sounds increased the distractibility of the noise-exposed subjects, which was shown by increased interference in task performance and aberrant brain responses. These results demonstrate that long-term exposure to noise has long-lasting detrimental effects on central auditory processing and attention control.
Noise in the Sea and Its Impacts on Marine Organisms
Peng, Chao; Zhao, Xinguo; Liu, Guangxu
2015-01-01
With the growing utilization and exploration of the ocean, anthropogenic noise increases significantly and gives rise to a new kind of pollution: noise pollution. In this review, the source and the characteristics of noise in the sea, the significance of sound to marine organisms, and the impacts of noise on marine organisms are summarized. In general, the studies about the impact of noise on marine organisms are mainly on adult fish and mammals, which account for more than 50% and 20% of all the cases reported. Studies showed that anthropogenic noise can cause auditory masking, leading to cochlear damage, changes in individual and social behavior, altered metabolisms, hampered population recruitment, and can subsequently affect the health and service functions of marine ecosystems. However, since different sampling methodologies and unstandarized measurements were used and the effects of noise on marine organisms are dependent on the characteristics of the species and noise investigated, it is difficult to compare the reported results. Moreover, the scarcity of studies carried out with other species and with larval or juvenile individuals severely constrains the present understanding of noise pollution. In addition, further studies are needed to reveal in detail the causes for the detected impacts. PMID:26437424
Earth Observation System Flight Dynamics System Covariance Realism
Zaidi, Waqar H.; Tracewell, David
2016-01-01
This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Directory of Open Access Journals (Sweden)
Rachel N. Zakpala
2014-01-01
Full Text Available Although accumulating evidence over the past thirty years indicates that noise is an environmental stressor in residential settings, much of the data emanated from studies in high-intensity, noise impact zones around airports or major roads. Little is known about religious noise, especially at night, which is increasingly a growing concern for both the general public and policy-makers in sub-Saharan Africa. Using geographical information systems (GIS, this study measured and mapped exposure to religious noise in a rapidly urbanising municipality in Ghana. Quantitative noise risk assessment was used to evaluate the risk of religious noise-induced hearing loss to residents in the exposed neighbourhoods. The results show that all neighbourhoods where churches were situated had at least one location with significant risk of noise-induced hearing loss. However, there was no statistically significant relationship between neighbourhoods where religious noise exposure was the highest and where noise annoyance was the highest. The magnitude of the noise values for night-time exposure is remarkable particularly given that excessive night-time noise exposure has the greatest detrimental effect on public health. There is the need to focus on vulnerable groups, sensitive hours of the night, and possible confounding with air pollution in order to wholly address this potential hazard.
Aasvang, Gunn Marit; Moum, Torbjorn; Engdahl, Bo
2008-07-01
The objective of the present survey was to study self-reported sleep disturbances due to railway noise with respect to nighttime equivalent noise level (L(p,A,eq,night)) and maximum noise level (L(p,A,max)). A sample of 1349 people in and around Oslo in Norway exposed to railway noise was studied in a cross-sectional survey to obtain data on sleep disturbances, sleep problems due to noise, and personal characteristics including noise sensitivity. Individual noise exposure levels were determined outside of the bedroom facade, the most-exposed facade, and inside the respondents' bedrooms. The exposure-response relationships were analyzed by using logistic regression models, controlling for possible modifying factors including the number of noise events (train pass-by frequency). L(p,A,eq,night) and L(p,A,max) were significantly correlated, and the proportion of reported noise-induced sleep problems increased as both L(p,A,eq,night) and L(p,A,max) increased. Noise sensitivity, type of bedroom window, and pass-by frequency were significant factors affecting noise-induced sleep disturbances, in addition to the noise exposure level. Because about half of the study population did not use a bedroom at the most-exposed side of the house, the exposure-response curve obtained by using noise levels for the most-exposed facade underestimated noise-induced sleep disturbance for those who actually have their bedroom at the most-exposed facade.
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the commutator anomalies are calculated for the two- and four dimensional case. (Author) 13 refs
Coherent states and covariant semi-spectral measures
International Nuclear Information System (INIS)
Scutaru, H.
1976-01-01
The close connection between Mackey's theory of imprimitivity systems and the so called generalized coherent states introduced by Perelomov is established. Coherent states give a covariant description of the ''localization'' of a quantum system in the phase space in a similar way as the imprimitivity systems give a covariant description of the localization of a quantum system in the configuration space. The observation that for any system of coherent states one can define a covariant semi-spectral measure made possible a rigurous formulation of this idea. A generalization of the notion of coherent states is given. Covariant semi-spectral measures associated with systems of coherent states are defined and characterized. Necessary and sufficient conditions for a unitary representation of a Lie group to be i) a subrepresentation of an induced one and ii) a representation with coherent states are given (author)
Covariance NMR Processing and Analysis for Protein Assignment.
Harden, Bradley J; Frueh, Dominique P
2018-01-01
During NMR resonance assignment it is often necessary to relate nuclei to one another indirectly, through their common correlations to other nuclei. Covariance NMR has emerged as a powerful technique to correlate such nuclei without relying on error-prone peak peaking. However, false-positive artifacts in covariance spectra have impeded a general application to proteins. We recently introduced pre- and postprocessing steps to reduce the prevalence of artifacts in covariance spectra, allowing for the calculation of a variety of 4D covariance maps obtained from diverse combinations of pairs of 3D spectra, and we have employed them to assign backbone and sidechain resonances in two large and challenging proteins. In this chapter, we present a detailed protocol describing how to (1) properly prepare existing 3D spectra for covariance, (2) understand and apply our processing script, and (3) navigate and interpret the resulting 4D spectra. We also provide solutions to a number of errors that may occur when using our script, and we offer practical advice when assigning difficult signals. We believe such 4D spectra, and covariance NMR in general, can play an integral role in the assignment of NMR signals.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2013-09-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Dias, Adriano; Cordeiro, Ricardo
2008-01-01
Noise is the most common agent of occupational exposure. It may induce both auditory and extraauditory dysfunction and increase the risk of work accidents. The purpose of this study was to estimate the fraction of accidents attributable to noise occupational exposure in a mid-size city located in southeastern Brazil. In this population case-control study, which included 108 cases and 324 controls, the incidence rate ratio of work accidents controlled for several covariables was obtained by classifying occupational noise exposure into three levels, as well as determining the prevalence in each level. Based on these data, the attributable fraction was estimated as 0.6391 (95% CI = 0.2341-0.3676), i.e., 63% of the work accidents that took place in the study site were statistically associated with occupational noise exposure. The causes of this association as well as its implications in the prevention of work accidents are discussed.
Some remarks on general covariance of quantum theory
International Nuclear Information System (INIS)
Schmutzer, E.
1977-01-01
If one accepts Einstein's general principle of relativity (covariance principle) also for the sphere of microphysics (quantum, mechanics, quantum field theory, theory of elemtary particles), one has to ask how far the fundamental laws of traditional quantum physics fulfil this principle. Attention is here drawn to a series of papers that have appeared during the last years, in which the author criticized the usual scheme of quantum theory (Heisenberg picture, Schroedinger picture etc.) and presented a new foundation of the basic laws of quantum physics, obeying the 'principle of fundamental covariance' (Einstein's covariance principle in space-time and covariance principle in Hilbert space of quantum operators and states). (author)
Vilar, J. M. G. (José M. G.), 1972-; Rubí Capaceti, José Miguel
2001-01-01
We have analyzed the interplay between an externally added noise and the intrinsic noise of systems that relax fast towards a stationary state, and found that increasing the intensity of the external noise can reduce the total noise of the system. We have established a general criterion for the appearance of this phenomenon and discussed two examples in detail.
Noise, impulse noise, and other physical factors: combined effects on hearing.
Pekkarinen, J
1995-01-01
In most of the epidemiologic studies conducted during the last 20 years, impulse noise caused increased risk of hearing loss in comparison to continuous noise with the same acoustical energy. The interaction between noise exposure (broadband at 100 dB(A)) and hand-arm vibration (125 Hz at 2 ms-2 acceleration level) has been proven for people having vibration-induced white finger symptoms. This interaction is evidenced as a permanent hearing loss. However, why the interaction is seen only in people with VWF is not known. The mechanisms may be related to individual susceptibility, and hypotheses are given on the role of the autonomous nervous system regulating the peripheral vascular reaction. Whole-body vibration (2-10 Hz, at 10 ms-2 level) seems to increase the TTS when noise (broadband at 90 dB(A)) is present. This effect is more pronounced at higher temperatures. The hypothermia protects hearing against the effects of noise in animal studies. The interaction between noise and temperature decrease seems obvious in animal studies. Exercise has both increased and decreased the TTS during noise exposure. The effects have been successfully explained as the depression of the stapedius reflex. Thus, less protection against noise is provided for the inner ear in exercise conditions. The increase of the blood temperature also has been suggested to increase noise-induced TTS during exercise. Electromagnetic fields have been found to cause acoustical interactions in the inner ear. Animal studies and human studies have given contradictory results on the effects of magnetic coil devices on hearing. The MR imaging devices produce noise levels of 82-93 dB, which is not sufficient to produce the risk of permanent hearing loss when short exposure durations are taken into consideration. More systematic research is needed with accurately defined electromagnetic characteristics to reveal the potential interactions. The interactions seem to exist, but relatively high levels and
Piervirgili, G; Petracca, F; Merletti, R
2014-10-01
A model-based new procedure for measuring the single electrode-gel-skin impedance (ZEGS) is presented. The method is suitable for monitoring the contact impedance of the electrodes of a large array with limited modifications of the hardware and without removing or disconnecting the array from the amplifier. The procedure is based on multiple measurements between electrode pairs and is particularly suitable for electrode arrays. It has been applied to study the effectiveness of three skin treatments, with respect to no treatment, for reducing the electrode-gel-skin impedance (ZEGS) and noise: (i) rubbing with alcohol; (ii) rubbing with abrasive conductive paste; (iii) stripping with adhesive tape. The complex impedances ZEGS of the individual electrodes were measured by applying this procedure to disposable commercial Ag-AgCl gelled electrode arrays (4 × 1) with a 5 mm(2) contact area. The impedance unbalance ΔZ = ZEGS1 - ZEGS2 and the RMS noise (VRMS) were measured between pairs of electrodes. The tissue impedance ZT was also obtained, as a collateral result. Measurements were repeated at t0 = 0 min and at t30 = 30 min from the electrode application. Mixed linear models and linear regression analysis applied to ZEGS, ΔZ and noise VRMS for the skin treatment factor demonstrated (a) that skin rubbing with abrasive conductive paste is more effective in lowering ZEGS, ΔZ and VRMS (p decrement (p < 0.01), between t0 and t30, of magnitude and phase of ZEGS.Rubbing with abrasive conductive paste significantly decreased the noise VRMS with respect to other treatments or no treatment.
Noise pollution from wind turbine gears loudness of structural noise sources related to gears
International Nuclear Information System (INIS)
Crone, A.
1995-04-01
The purpose of the project has been to develop a method for determination of the structure-borne noise source strength of the gearbox in a typical modern Danish wind turbine construction, with special reference to the tonal noise emission form the turbines. Through study and evaluation of eight potential methods, a simple method has ben formulated. The method is based on measurements of the free vibration velocity level on the gearbox in a load test bed. The relation between this source strength measure and the gearbox related noise from wind turbines has been documented by measurements made during the project together with earlier measurements. The method is intended as a tool for the wind turbine manufacturer, for control of the gearbox related noise from the wind turbines, due to structure-borne noise from the gearbox. It may be used for preparation of specifications to the gearbox manufacturer on test procedure and acceptable source strength levels. Also, it may be used for evaluation of the transmission and radiation of gearbox related noise, for example in order to uncover weaknesses in a prototype turbine. Suggestions for adaptation and evolution of the method has been given, thereby improving the strength of the method for the individual wind turbine manufacturer. (au) 19 refs
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C
2014-07-01
Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions. CPs are thought to be determined by both selective decoding of neural activity and by the structure of correlated noise among neurons, but the respective roles of these factors in creating CPs have been controversial. We used biologically-constrained simulations to explore this issue, taking advantage of a peculiar pattern of CPs exhibited by multisensory neurons in area MSTd that represent self-motion. Although models that relied on correlated noise or selective decoding could both account for the peculiar pattern of CPs, predictions of the selective decoding model were substantially more consistent with various features of the neural and behavioral data. While correlated noise is essential to observe CPs, our findings suggest that selective decoding of neuronal signals also plays important roles.
Noise sensitivity of portfolio selection in constant conditional correlation GARCH models
Varga-Haszonits, I.; Kondor, I.
2007-11-01
This paper investigates the efficiency of minimum variance portfolio optimization for stock price movements following the Constant Conditional Correlation GARCH process proposed by Bollerslev. Simulations show that the quality of portfolio selection can be improved substantially by computing optimal portfolio weights from conditional covariances instead of unconditional ones. Measurement noise can be further reduced by applying some filtering method on the conditional correlation matrix (such as Random Matrix Theory based filtering). As an empirical support for the simulation results, the analysis is also carried out for a time series of S&P500 stock prices.
Could driving safety be compromised by noise exposure at work and noise-induced hearing loss?
Picard, Michel; Girard, Serge André; Courteau, Marilène; Leroux, Tony; Larocque, Richard; Turcotte, Fernand; Lavoie, Michel; Simard, Marc
2008-10-01
A study was conducted to verify if there is an association between occupational noise exposure, noise-induced hearing loss and driving safety expanding on previous findings by Picard, et al. (2008) that the two factors did increase accident risk in the workplace. This study was made possible when driving records of all Quebec drivers were made available by the Societe de l'assurance automobile du Quebec (SAAQ is the state monopoly responsible for the provision of motor vehicle insurance and the compensation of victims of traffic accidents). These records were linked with personal records maintained by the Quebec National Institute of Public Health as part of its mission to prevent noise induced hearing loss in the workplace. Individualized information on occupational noise exposure and hearing sensitivity was available for 46,030 male workers employed in noisy industries who also held a valid driver's permit. The observation period is of five years duration, starting with the most recent audiometric examination. The associations between occupational noise exposure levels, hearing status, and personal driving record were examined by log-binomial regression on data adjusted for age and duration of exposure. Daily noise exposures and bilateral average hearing threshold levels at 3, 4, and 6 kHz were used as independent variables while the dependent variables were 1) the number of motor vehicle accidents experienced by participants during the study period and 2) participants' records of registered traffic violations of the highway safety code. The findings are reported as prevalence ratios (PRs) with their 95% confidence intervals (CIs). Attributable numbers of events were computed with the relevant PRs, lesser-noise, exposed workers and those with normal hearing levels making the group of reference. Adjusting for age confirmed that experienced workers had fewer traffic accidents. The data show that occupational noise exposure and hearing loss have the same effect on
Early risk factors for alcohol use across high school and its covariation with deviant friends.
Armstrong, Jeffrey M; Ruttle, Paula L; Burk, Linnea R; Costanzo, Philip R; Strauman, Timothy J; Essex, Marilyn J
2013-09-01
Past research has associated childhood characteristics and experiences with alcohol use at single time points in adolescence. Other work has focused on drinking trajectories across adolescence but with risk factors typically no earlier than middle or high school. Similarly, although the connection between underage drinking and affiliation with deviant friends is well established, early risk factors for their covariation across adolescence are uncertain. The present study examines the influence of early individual and contextual factors on (a) trajectories across high school of per-occasion alcohol use and (b) the covariation of alcohol use and deviant friends over time. In a longitudinal community sample (n = 374; 51% female), temperamental disinhibition, authoritarian and authoritative parenting, and parental alcohol use were assessed during childhood, and adolescents reported on alcohol use and affiliation with deviant friends in the spring of Grades 9, 10, 11, and 12. Early parental alcohol use predicted the intercept of adolescent drinking. Subsequent patterns of adolescent alcohol use were predicted by sex and interactions of sex and childhood disinhibition with early authoritarian parenting. Additionally, childhood disinhibition interacted with parental alcohol use to moderate the covariation of drinking and deviant friends. These findings highlight early individual and contextual risk factors for alcohol use across high school, extending previous work and underscoring the importance of developmental approaches and longitudinal techniques for understanding patterns of growth in underage drinking.
Treatment Effects with Many Covariates and Heteroskedasticity
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.
The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...
Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.
Xie, Yanmei; Zhang, Biao
2017-04-20
Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and
Cosmic censorship conjecture revisited: covariantly
International Nuclear Information System (INIS)
Hamid, Aymen I M; Goswami, Rituparno; Maharaj, Sunil D
2014-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general locally rotationally symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible. (paper)
Compressor noise control begins with design--Part 1
International Nuclear Information System (INIS)
Frank, L.
1993-01-01
This paper describes the typical methods used by oil and gas pipeline companies to reduce the noise level associated with their pump and compressor stations. The common method is for the design engineer to specify an acceptable noise level at a specified distance. Unfortunately, the results by this method are rarely acceptable because vendors have not considered the effects of sound propagation outside the station, the owners have not considered the cumulative effect of various machinery, and there is little methodology available to distinguish the individual components which might be contributing the acoustically unacceptable noise levels in a multi-component system. This article stresses balanced noise control designs using noise control engineering
Evaluation of covariance in theoretical calculation of nuclear data
International Nuclear Information System (INIS)
Kikuchi, Yasuyuki
1981-01-01
Covariances of the cross sections are discussed on the statistical model calculations. Two categories of covariance are discussed: One is caused by the model approximation and the other by the errors in the model parameters. As an example, the covariances are calculated for 100 Ru. (author)
Dzhambov, Angel M; Dimitrova, Donka D
2016-01-01
Type 2 diabetes mellitus (T2DM) is a growing public health problem in Bulgaria. While individual and lifestyle determinants have been researched; till date there has been no study on environmental risks such as road traffic, noise, and air pollution. As a first step toward designing a large-scale population-based survey, we aimed at exploring the overall associations of prevalent T2DM with exposures to road traffic, noise, and air pollution. A total of 513 residents of Plovdiv city, Bulgaria were recruited. Individual data on self-reported doctor-diagnosed T2DM and confounding factors were linked to objective and self-rated exposure indicators. Logistic and log-link Poisson regressions were conducted. In the fully adjusted logistic models, T2DM was positively associated with exposures to Lden 71-80 dB (odds ratio (OR) = 4.49, 95% confidence interval (CI): 1.38, 14.68), fine particulate matter (PM)2.5 25.0-66.8 μg/m3 (OR = 1.32, 95% CI: 0.28, 6.24), benzo alpha pyrene 6.0-14.02 ng/m3 (OR = 1.76, 95% CI: 0.52, 5.98) and high road traffic (OR = 1.40, 95% CI: 0.48, 4.07). Lden remained a significant risk factor in the: Poisson regression model. Other covariates with consistently high multivariate effects were age, gender, body mass index, family history of T2DM, subjective sleep disturbance, and especially bedroom location. We concluded that residential noise exposure might be associated with elevated risk of prevalent T2DM. The inferences made by this research and the lessons learned from its limitations could guide the designing of a longitudinal epidemiological survey in Bulgaria. PMID:27157686
Updated Covariance Processing Capabilities in the AMPX Code System
International Nuclear Information System (INIS)
Wiarda, Dorothea; Dunn, Michael E.
2007-01-01
A concerted effort is in progress within the nuclear data community to provide new cross-section covariance data evaluations to support sensitivity/uncertainty analyses of fissionable systems. The objective of this work is to update processing capabilities of the AMPX library to process the latest Evaluated Nuclear Data File (ENDF)/B formats to generate covariance data libraries for radiation transport software such as SCALE. The module PUFF-IV was updated to allow processing of new ENDF covariance formats in the resolved resonance region. In the resolved resonance region, covariance matrices are given in terms of resonance parameters, which need to be processed into covariance matrices with respect to the group-averaged cross-section data. The parameter covariance matrix can be quite large if the evaluation has many resonances. The PUFF-IV code has recently been used to process an evaluation of 235U, which was prepared in collaboration between Oak Ridge National Laboratory and Los Alamos National Laboratory.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Impact of the 235U Covariance Data in Benchmark Calculations
International Nuclear Information System (INIS)
Leal, Luiz C.; Mueller, D.; Arbanas, G.; Wiarda, D.; Derrien, H.
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235U. The resulting 235U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235U covariance data in calculations of critical benchmark systems
Impact of the 235U covariance data in benchmark calculations
International Nuclear Information System (INIS)
Leal, Luiz; Mueller, Don; Arbanas, Goran; Wiarda, Dorothea; Derrien, Herve
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes' method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235 U. The resulting 235 U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235 U covariance data in calculations of critical benchmark systems. (authors)
Parameters of the covariance function of galaxies
International Nuclear Information System (INIS)
Fesenko, B.I.; Onuchina, E.V.
1988-01-01
The two-point angular covariance functions for two samples of galaxies are considered using quick methods of analysis. It is concluded that in the previous investigations the amplitude of the covariance function in the Lick counts was overestimated and the rate of decrease of the function underestimated
Generally covariant gauge theories
International Nuclear Information System (INIS)
Capovilla, R.
1992-01-01
A new class of generally covariant gauge theories in four space-time dimensions is investigated. The field variables are taken to be a Lie algebra valued connection 1-form and a scalar density. Modulo an important degeneracy, complex [euclidean] vacuum general relativity corresponds to a special case in this class. A canonical analysis of the generally covariant gauge theories with the same gauge group as general relativity shows that they describe two degrees of freedom per space point, qualifying therefore as a new set of neighbors of general relativity. The modification of the algebra of the constraints with respect to the general relativity case is computed; this is used in addressing the question of how general relativity stands out from its neighbors. (orig.)
Noise-induced enhancement of network reciprocity in social dilemmas
International Nuclear Information System (INIS)
Zhang, Gui-Qing; Sun, Qi-Bo; Wang, Lin
2013-01-01
Highlights: • We introduce the noise-induced mechanism into the prisoner’s dilemma game. • Cooperation will be largely enhanced by introducing the noise into the calculation of fitness. • Despite the defectors prevail initially, the stressed factor still promotes the cooperation. • The mechanism studied here is helpful on different kinds of interaction networks. -- Abstract: The network reciprocity is an important dynamic rule fostering the emergence of cooperation among selfish individuals. This was reported firstly in the seminal work of Nowak and May, where individuals were arranged on the regular lattice network, and played the prisoner’s dilemma game (PDG). In the standard PDG, one often assumes that the players have perfect rationality. However, in reality, we human are far from rational agents, as we often make mistakes, and behave irrationally. Accordingly, in this work, we introduce the element of noise into the measurement of fitness, which is determined by the parameter α controlling the degree of noise. The considered noise-induced mechanism remarkably promotes the behavior of cooperation, which may be conducive to interpret the emergence of cooperation within the population
Objective measures of listening effort: effects of background noise and noise reduction.
Sarampalis, Anastasios; Kalluri, Sridhar; Edwards, Brent; Hafter, Ervin
2009-10-01
This work is aimed at addressing a seeming contradiction related to the use of noise-reduction (NR) algorithms in hearing aids. The problem is that although some listeners claim a subjective improvement from NR, it has not been shown to improve speech intelligibility, often even making it worse. To address this, the hypothesis tested here is that the positive effects of NR might be to reduce cognitive effort directed toward speech reception, making it available for other tasks. Normal-hearing individuals participated in 2 dual-task experiments, in which 1 task was to report sentences or words in noise set to various signal-to-noise ratios. Secondary tasks involved either holding words in short-term memory or responding in a complex visual reaction-time task. At low values of signal-to-noise ratio, although NR had no positive effect on speech reception thresholds, it led to better performance on the word-memory task and quicker responses in visual reaction times. Results from both dual tasks support the hypothesis that NR reduces listening effort and frees up cognitive resources for other tasks. Future hearing aid research should incorporate objective measurements of cognitive benefits.
Páez, David James; Bernatchez, Louis; Dodson, Julian J
2011-07-22
Alternative reproductive tactics are ubiquitous in many species. Tactic expression often depends on whether an individual's condition surpasses thresholds that are responsible for activating particular developmental pathways. Two central goals in understanding the evolution of reproductive tactics are quantifying the extent to which thresholds are explained by additive genetic effects, and describing their covariation with condition-related traits. We monitored the development of early sexual maturation that leads to the sneaker reproductive tactic in Atlantic salmon (Salmo salar L.). We found evidence for additive genetic variance in the timing of sexual maturity (which is a measure of the surpassing of threshold values) and body-size traits. This suggests that selection can affect the patterns of sexual development by changing the timing of this event and/or body size. Significant levels of covariation between these traits also occurred, implying a potential for correlated responses to selection. Closer examination of genetic covariances suggests that the detected genetic variation is distributed along at least five directions of phenotypic variation. Our results show that the potential for evolution of the life-history traits constituting this reproductive phenotype is greatly influenced by their patterns of genetic covariance.
Directory of Open Access Journals (Sweden)
Rainer Guski
2017-12-01
Full Text Available Background: This paper describes a systematic review and meta-analyses on effects of environmental noise on annoyance. The noise sources include aircraft, road, and rail transportation noise as well as wind turbines and noise source combinations. Objectives: Update knowledge about effects of environmental noise on people living in the vicinity of noise sources. Methods: Eligible were published studies (2000–2014 providing comparable acoustical and social survey data including exposure-response functions between standard indicators of noise exposure and standard annoyance responses. The systematic literature search in 20 data bases resulted in 62 studies, of which 57 were used for quantitative meta-analyses. By means of questionnaires sent to the study authors, additional study data were obtained. Risk of bias was assessed by means of study characteristics for individual studies and by funnel plots to assess the risk of publication bias. Main Results: Tentative exposure-response relations for percent highly annoyed residents (%HA in relation to noise levels for aircraft, road, rail, wind turbine and noise source combinations are presented as well as meta-analyses of correlations between noise levels and annoyance raw scores, and the OR for increase of %HA with increasing noise levels. Quality of evidence was assessed using the GRADE terminology. The evidence of exposure-response relations between noise levels and %HA is moderate (aircraft and railway or low (road traffic and wind turbines. The evidence of correlations between noise levels and annoyance raw scores is high (aircraft and railway or moderate (road traffic and wind turbines. The evidence of ORs representing the %HA increase by a certain noise level increase is moderate (aircraft noise, moderate/high (road and railway traffic, and low (wind turbines. Strengths and Limitations: The strength of the evidence is seen in the large total sample size encompassing the included studies (e
Thresholding of auditory cortical representation by background noise
Liang, Feixue; Bai, Lin; Tao, Huizhong W.; Zhang, Li I.; Xiao, Zhongju
2014-01-01
It is generally thought that background noise can mask auditory information. However, how the noise specifically transforms neuronal auditory processing in a level-dependent manner remains to be carefully determined. Here, with in vivo loose-patch cell-attached recordings in layer 4 of the rat primary auditory cortex (A1), we systematically examined how continuous wideband noise of different levels affected receptive field properties of individual neurons. We found that the background noise, when above a certain critical/effective level, resulted in an elevation of intensity threshold for tone-evoked responses. This increase of threshold was linearly dependent on the noise intensity above the critical level. As such, the tonal receptive field (TRF) of individual neurons was translated upward as an entirety toward high intensities along the intensity domain. This resulted in preserved preferred characteristic frequency (CF) and the overall shape of TRF, but reduced frequency responding range and an enhanced frequency selectivity for the same stimulus intensity. Such translational effects on intensity threshold were observed in both excitatory and fast-spiking inhibitory neurons, as well as in both monotonic and nonmonotonic (intensity-tuned) A1 neurons. Our results suggest that in a noise background, fundamental auditory representations are modulated through a background level-dependent linear shifting along intensity domain, which is equivalent to reducing stimulus intensity. PMID:25426029
Thresholding of auditory cortical representation by background noise.
Liang, Feixue; Bai, Lin; Tao, Huizhong W; Zhang, Li I; Xiao, Zhongju
2014-01-01
It is generally thought that background noise can mask auditory information. However, how the noise specifically transforms neuronal auditory processing in a level-dependent manner remains to be carefully determined. Here, with in vivo loose-patch cell-attached recordings in layer 4 of the rat primary auditory cortex (A1), we systematically examined how continuous wideband noise of different levels affected receptive field properties of individual neurons. We found that the background noise, when above a certain critical/effective level, resulted in an elevation of intensity threshold for tone-evoked responses. This increase of threshold was linearly dependent on the noise intensity above the critical level. As such, the tonal receptive field (TRF) of individual neurons was translated upward as an entirety toward high intensities along the intensity domain. This resulted in preserved preferred characteristic frequency (CF) and the overall shape of TRF, but reduced frequency responding range and an enhanced frequency selectivity for the same stimulus intensity. Such translational effects on intensity threshold were observed in both excitatory and fast-spiking inhibitory neurons, as well as in both monotonic and nonmonotonic (intensity-tuned) A1 neurons. Our results suggest that in a noise background, fundamental auditory representations are modulated through a background level-dependent linear shifting along intensity domain, which is equivalent to reducing stimulus intensity.
Nonrelativistic fluids on scale covariant Newton-Cartan backgrounds
Mitra, Arpita
2017-12-01
The nonrelativistic covariant framework for fields is extended to investigate fields and fluids on scale covariant curved backgrounds. The scale covariant Newton-Cartan background is constructed using the localization of space-time symmetries of nonrelativistic fields in flat space. Following this, we provide a Weyl covariant formalism which can be used to study scale invariant fluids. By considering ideal fluids as an example, we describe its thermodynamic and hydrodynamic properties and explicitly demonstrate that it satisfies the local second law of thermodynamics. As a further application, we consider the low energy description of Hall fluids. Specifically, we find that the gauge fields for scale transformations lead to corrections of the Wen-Zee and Berry phase terms contained in the effective action.
Noise Annoyance in Urban Children: A Cross-Sectional Population-Based Study
Grelat, Natacha; Houot, Hélène; Pujol, Sophie; Levain, Jean-Pierre; Defrance, Jérôme; Mariet, Anne-Sophie; Mauny, Frédéric
2016-01-01
Acoustical and non-acoustical factors influencing noise annoyance in adults have been well-documented in recent years; however, similar knowledge is lacking in children. The aim of this study was to quantify the annoyance caused by chronic ambient noise at home in children and to assess the relationship between these children′s noise annoyance level and individual and contextual factors in the surrounding urban area. A cross sectional population-based study was conducted including 517 children attending primary school in a European city. Noise annoyance was measured using a self-report questionnaire adapted for children. Six noise exposure level indicators were built at different locations at increasing distances from the child′s bedroom window using a validated strategic noise map. Multilevel logistic models were constructed to investigate factors associated with noise annoyance in children. Noise indicators in front of the child′s bedroom (p ≤ 0.01), family residential satisfaction (p ≤ 0.03) and socioeconomic characteristics of the individuals and their neighbourhood (p ≤ 0.05) remained associated with child annoyance. These findings illustrate the complex relationships between our environment, how we may perceive it, social factors and health. Better understanding of these relationships will undoubtedly allow us to more effectively quantify the actual effect of noise on human health. PMID:27801858
International Nuclear Information System (INIS)
Piervirgili, G; Petracca, F; Merletti, R
2014-01-01
A model-based new procedure for measuring the single electrode–gel–skin impedance (Z EGS ) is presented. The method is suitable for monitoring the contact impedance of the electrodes of a large array with limited modifications of the hardware and without removing or disconnecting the array from the amplifier. The procedure is based on multiple measurements between electrode pairs and is particularly suitable for electrode arrays. It has been applied to study the effectiveness of three skin treatments, with respect to no treatment, for reducing the electrode–gel–skin impedance (Z EGS ) and noise: (i) rubbing with alcohol; (ii) rubbing with abrasive conductive paste; (iii) stripping with adhesive tape. The complex impedances Z EGS of the individual electrodes were measured by applying this procedure to disposable commercial Ag–AgCl gelled electrode arrays (4 × 1) with a 5 mm 2 contact area. The impedance unbalance ΔZ = Z EGS1 − Z EGS2 and the RMS noise (V RMS ) were measured between pairs of electrodes. The tissue impedance Z T was also obtained, as a collateral result. Measurements were repeated at t 0 = 0 min and at t 30 = 30 min from the electrode application. Mixed linear models and linear regression analysis applied to Z EGS , ΔZ and noise V RMS for the skin treatment factor demonstrated (a) that skin rubbing with abrasive conductive paste is more effective in lowering Z EGS , ΔZ and V RMS (p < 0.01) than the other treatments or no treatment, and (b) a statistically significant decrement (p < 0.01), between t 0 and t 30 , of magnitude and phase of Z EGS . Rubbing with abrasive conductive paste significantly decreased the noise V RMS with respect to other treatments or no treatment. (paper)
Bayes Factor Covariance Testing in Item Response Models.
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-12-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.
A model for measurement of noise in CCD digital-video cameras
International Nuclear Information System (INIS)
Irie, K; Woodhead, I M; McKinnon, A E; Unsworth, K
2008-01-01
This study presents a comprehensive measurement of CCD digital-video camera noise. Knowledge of noise detail within images or video streams allows for the development of more sophisticated algorithms for separating true image content from the noise generated in an image sensor. The robustness and performance of an image-processing algorithm is fundamentally limited by sensor noise. The individual noise sources present in CCD sensors are well understood, but there has been little literature on the development of a complete noise model for CCD digital-video cameras, incorporating the effects of quantization and demosaicing
The K-Step Spatial Sign Covariance Matrix
Croux, C.; Dehon, C.; Yadine, A.
2010-01-01
The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its e±ciency while keeping the maximal breakdown
On the covariance matrices in the evaluated nuclear data
International Nuclear Information System (INIS)
Corcuera, R.P.
1983-05-01
The implications of the uncertainties of nuclear data on reactor calculations are shown. The concept of variance, covariance and correlation are expressed first by intuitive definitions and then through statistical theory. The format of the covariance data for ENDF/B is explained and the formulas to obtain the multigroup covariances are given. (Author) [pt
Massive data compression for parameter-dependent covariance matrices
Heavens, Alan F.; Sellentin, Elena; de Mijolla, Damien; Vianello, Alvise
2017-12-01
We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated data sets which are required to estimate the covariance matrix required for the analysis of Gaussian-distributed data. This is relevant when the covariance matrix cannot be calculated directly. The compression is especially valuable when the covariance matrix varies with the model parameters. In this case, it may be prohibitively expensive to run enough simulations to estimate the full covariance matrix throughout the parameter space. This compression may be particularly valuable for the next generation of weak lensing surveys, such as proposed for Euclid and Large Synoptic Survey Telescope, for which the number of summary data (such as band power or shear correlation estimates) is very large, ∼104, due to the large number of tomographic redshift bins which the data will be divided into. In the pessimistic case where the covariance matrix is estimated separately for all points in an Monte Carlo Markov Chain analysis, this may require an unfeasible 109 simulations. We show here that MOPED can reduce this number by a factor of 1000, or a factor of ∼106 if some regularity in the covariance matrix is assumed, reducing the number of simulations required to a manageable 103, making an otherwise intractable analysis feasible.
Alterations in Anatomical Covariance in the Prematurely Born.
Scheinost, Dustin; Kwon, Soo Hyun; Lacadie, Cheryl; Vohr, Betty R; Schneider, Karen C; Papademetris, Xenophon; Constable, R Todd; Ment, Laura R
2017-01-01
Preterm (PT) birth results in long-term alterations in functional and structural connectivity, but the related changes in anatomical covariance are just beginning to be explored. To test the hypothesis that PT birth alters patterns of anatomical covariance, we investigated brain volumes of 25 PTs and 22 terms at young adulthood using magnetic resonance imaging. Using regional volumetrics, seed-based analyses, and whole brain graphs, we show that PT birth is associated with reduced volume in bilateral temporal and inferior frontal lobes, left caudate, left fusiform, and posterior cingulate for prematurely born subjects at young adulthood. Seed-based analyses demonstrate altered patterns of anatomical covariance for PTs compared with terms. PTs exhibit reduced covariance with R Brodmann area (BA) 47, Broca's area, and L BA 21, Wernicke's area, and white matter volume in the left prefrontal lobe, but increased covariance with R BA 47 and left cerebellum. Graph theory analyses demonstrate that measures of network complexity are significantly less robust in PTs compared with term controls. Volumes in regions showing group differences are significantly correlated with phonological awareness, the fundamental basis for reading acquisition, for the PTs. These data suggest both long-lasting and clinically significant alterations in the covariance in the PTs at young adulthood. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Phase-covariant quantum cloning of qudits
International Nuclear Information System (INIS)
Fan Heng; Imai, Hiroshi; Matsumoto, Keiji; Wang, Xiang-Bin
2003-01-01
We study the phase-covariant quantum cloning machine for qudits, i.e., the input states in a d-level quantum system have complex coefficients with arbitrary phase but constant module. A cloning unitary transformation is proposed. After optimizing the fidelity between input state and single qudit reduced density operator of output state, we obtain the optimal fidelity for 1 to 2 phase-covariant quantum cloning of qudits and the corresponding cloning transformation
Covariant differential calculus on quantum spheres of odd dimension
International Nuclear Information System (INIS)
Welk, M.
1998-01-01
Covariant differential calculus on the quantum spheres S q 2N-1 is studied. Two classification results for covariant first order differential calculi are proved. As an important step towards a description of the noncommutative geometry of the quantum spheres, a framework of covariant differential calculus is established, including first and higher order calculi and a symmetry concept. (author)
Study of neutron noise from reflected, metal assemblies with criticality safety applications in mind
International Nuclear Information System (INIS)
Barnett, C.S.
1985-01-01
The author studied the statistics of detected neutrons that leaked from four subcritical reflected, enriched-uranium assemblies, to explore the feasibility of developing a criticality warning system based on neutron noise analysis. The calculated multiplication factors of the assemblies are 0.59, 0.74, 0.82, and 0.92. The author studied three possible discriminators, i.e., three signatures that might be used to discriminate among assemblies of various multiplications. They are (1) variance-to-mean ratio of the counts in a time bin (V/M), (2) covariance-to-mean ratio of the counts in a common time bin from two different detectors (C/M), (3) covariance-to-mean ratio of the counts from a single detector in two adjacent time bins of equal length, which the author calls the serial-covariance-to-mean ratio (SC/M). The performances of the three discriminators were not greatly different, but a hierarchy did emerge: SC/M greater than or equal to V/M greater than or equal to C/M. An example of some results: in the neighborhood of k = 0.6 the Δk required for satisfactory discrimination varies from about 3% to 7% as detector solid angle varies from 19% to 5%. In the neighborhood of k = 0.8 the corresponding Δks are 1% and 2%. The noise analysis techniques studied performed well enough in deeply subcritical situations to deserve testing in an applications environment. They have a good chance of detecting changes in reactivity that are potentially dangerous. One can expect sharpest results when doing comparison, i.e., when comparing two records, one taken in the past under circumstances known to be normal and one taken now to search for change
Study of neutron noise from reflected, metal assemblies with criticality safety applications in mind
International Nuclear Information System (INIS)
Barnett, C.S.
1985-01-01
The author studied the statistics of detected neutrons that leaked from four subcritical reflected, enriched-uranium assemblies, to explore the feasibility of developing a criticality warning system based on neutron noise analysis. The calculated multiplication factors of the assemblies are 0.59, 0.74, 0.82, and 0.92. The author studied three possible discriminators, i.e., three signatures that might be used to discriminate among assemblies of various multiplications. They are: (1) variance-to-mean ratio of the counts in a time bin (V/M); (2) covariance-to-mean ratio of the counts in a common time bin from two different detectors (C/M); and (3) covariance-to-mean ratio of the counts from a single detector in two adjacent time bins of equal length, which the author calls the serial-covariance-to-mean ratio (SC/M). The performances of the three discriminators were not greatly different, but a hierarchy did emerge: SC/M greater than or equal to V/M greater than or equal to C/M. An example of some results: in the neighborhood of k = 0.6 the Δk required for satisfactory discrimination varies from about 3% to 7% as detector solid angle varies from 19% to 5%. In the neighborhood of k = 0.8 the corresponding Δks are 1% and 2%. The noise analysis techniques studied performed well enough in deeply subcritical situations to deserve testing in an applications environment. They have a good chance of detecting changes in reactivity that are potentially dangerous. One can expect sharpest results when doing comparisons, i.e., when comparing two records, one taken in the past under circumstances known to be normal and one taken now to search for change
Energy Technology Data Exchange (ETDEWEB)
Leitão, Sofia, E-mail: sofia.leitao@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Stadler, Alfred, E-mail: stadler@uevora.pt [Departamento de Física, Universidade de Évora, 7000-671 Évora (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Peña, M.T., E-mail: teresa.pena@tecnico.ulisboa.pt [Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Biernat, Elmar P., E-mail: elmar.biernat@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)
2017-01-10
The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy–light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin–orbit and tensor forces and do not allow to separate the spin–spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark–antiquark interactions.
Elucidating the relationship between noise sensitivity and personality
Directory of Open Access Journals (Sweden)
Daniel Shepherd
2015-01-01
Full Text Available Sensitivity to unwanted sounds is common in general and clinical populations. Noise sensitivity refers to physiological and psychological internal states of an individual that increase the degree of reactivity to noise in general. The current study investigated the relationship between the Big Five personality dimensions and noise sensitivity using the 240-item NEO Personality Inventory (NEO-PI and 35-item The Noise-Sensitivity-Questionnaire (NoiSeQ scales, respectively. Overall, the Big Five accounted for 33% of the variance in noise sensitivity, with the Introversion-Extroversion dimension explaining the most variability. Furthermore, the Big Five personality dimensions (neuroticism, extroversion, openness, agreeableness, and conscientiousness had an independent effect on noise sensitivity, which were linear. However, additional analyses indicated that the influence of gender and age must be considered when examining the relationship between personality and noise sensitivity. The findings caution against pooling data across genders, not controlling for age, and using personality dimensions in isolation.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
A New Approach for Nuclear Data Covariance and Sensitivity Generation
International Nuclear Information System (INIS)
Leal, L.C.; Larson, N.M.; Derrien, H.; Kawano, T.; Chadwick, M.B.
2005-01-01
Covariance data are required to correctly assess uncertainties in design parameters in nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the U.S. Evaluated Nuclear Data File, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance-parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. The parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes
Hearing loss and perceptions of noise in the workplace among rural Australians.
Williams, Warwick; Purdy, Suzanne; Murray, Narelle; LePage, Eric; Challinor, Kathy
2004-06-01
To compare measured hearing levels of individuals regularly exposed to noise in their workplace to self-reported and family-reported hearing loss. To compare the attitudes and preventative actions adopted by individuals who are more aware of the potential for hearing loss to less aware individuals. The project examined the perceptions of rural workers concerning noise, noise exposure and hearing. The subjects completed a 'Noise at Work' questionnaire and some demographic data at the time of audiometric testing. The subjects were recruited when attending their rural health clinic for audiometric testing. Participants comprised 113 men and 23 women (20-65 years, mean = 39.6, SD = 11.4) working across a range of activities at different levels in their workplaces. The range in current employment was from 0.5 to 45 years (mean = 13.8, SD = 10.7). Hearing tests were compared with perceptions of noise annoyance, hearing damage risk and preventative action. Self- and family-reported hearing loss and conversational difficulties in noise correlated well with measured audiograms. Perceptions of workplace noise tended to be more positive if people felt they had hearing problems. There was no difference in preventative action between those who did and did not feel they had hearing problems. Both groups rated barriers to action and lack of self-efficacy in a similar negative way. There is a need for specific training to ensure that rural workers have skills to take more positive action in reducing noise exposure at work.
Early Risk Factors for Alcohol Use Across High School and Its Covariation With Deviant Friends
Armstrong, Jeffrey M.; Ruttle, Paula L.; Burk, Linnea R.; Costanzo, Philip R.; Strauman, Timothy J.; Essex, Marilyn J.
2013-01-01
Objective: Past research has associated childhood characteristics and experiences with alcohol use at single time points in adolescence. Other work has focused on drinking trajectories across adolescence but with risk factors typically no earlier than middle or high school. Similarly, although the connection between underage drinking and affiliation with deviant friends is well established, early risk factors for their covariation across adolescence are uncertain. The present study examines the influence of early individual and contextual factors on (a) trajectories across high school of per-occasion alcohol use and (b) the covariation of alcohol use and deviant friends over time. Method: In a longitudinal community sample (n = 374; 51% female), temperamental disinhibition, authoritarian and authoritative parenting, and parental alcohol use were assessed during childhood, and adolescents reported on alcohol use and affiliation with deviant friends in the spring of Grades 9, 10, 11, and 12. Results: Early parental alcohol use predicted the intercept of adolescent drinking. Subsequent patterns of adolescent alcohol use were predicted by sex and interactions of sex and childhood disinhibition with early authoritarian parenting. Additionally, childhood disinhibition interacted with parental alcohol use to moderate the covariation of drinking and deviant friends. Conclusions: These findings highlight early individual and contextual risk factors for alcohol use across high school, extending previous work and underscoring the importance of developmental approaches and longitudinal techniques for understanding patterns of growth in underage drinking. PMID:23948534
Ohlenforst, Barbara; Souza, Pamela E; MacDonald, Ewen N
2016-01-01
Previous work has shown that individuals with lower working memory demonstrate reduced intelligibility for speech processed with fast-acting compression amplification. This relationship has been noted in fluctuating noise, but the extent of noise modulation that must be present to elicit such an effect is unknown. This study expanded on previous study by exploring the effect of background noise modulations in relation to compression speed and working memory ability, using a range of signal to noise ratios. Twenty-six older participants between ages 61 and 90 years were grouped by high or low working memory according to their performance on a reading span test. Speech intelligibility was measured for low-context sentences presented in background noise, where the noise varied in the extent of amplitude modulation. Simulated fast- or slow-acting compression amplification combined with individual frequency-gain shaping was applied to compensate for the individual's hearing loss. Better speech intelligibility scores were observed for participants with high working memory when fast compression was applied than when slow compression was applied. The low working memory group behaved in the opposite way and performed better under slow compression compared with fast compression. There was also a significant effect of the extent of amplitude modulation in the background noise, such that the magnitude of the score difference (fast versus slow compression) depended on the number of talkers in the background noise. The presented signal to noise ratios were not a significant factor on the measured intelligibility performance. In agreement with earlier research, high working memory allowed better speech intelligibility when fast compression was applied in modulated background noise. In the present experiment, that effect was present regardless of the extent of background noise modulation.
Effects of noise in excitable systems
International Nuclear Information System (INIS)
Lindner, B.; Garcia-Ojalvo, J.; Neiman, A.; Schimansky-Geier, L.
2004-01-01
We review the behavior of theoretical models of excitable systems driven by Gaussian white noise. We focus mainly on those general properties of such systems that are due to noise, and present several applications of our findings in biophysics and lasers. As prototypes of excitable stochastic dynamics we consider the FitzHugh-Nagumo and the leaky integrate-and-fire model, as well as cellular automata and phase models. In these systems, taken as individual units or as networks of globally or locally coupled elements, we study various phenomena due to noise, such as noise-induced oscillations, stochastic resonance, stochastic synchronization, noise-induced phase transitions and noise-induced pulse and spiral dynamics. Our approach is based on stochastic differential equations and their corresponding Fokker-Planck equations, treated by both analytical calculations and/or numerical simulations. We calculate and/or measure the rate and diffusion coefficient of the excitation process, as well as spectral quantities like power spectra and degree of coherence. Combined with a multiparametric bifurcation analysis of the corresponding cumulant equations, these approaches provide a comprehensive picture of the multifaceted dynamical behaviour of noisy excitable systems
Schiefer, Jonathan; Niederbühl, Alexander; Pernice, Volker; Lennartz, Carolin; Hennig, Jürgen; LeVan, Pierre; Rotter, Stefan
2018-03-01
Knowing brain connectivity is of great importance both in basic research and for clinical applications. We are proposing a method to infer directed connectivity from zero-lag covariances of neuronal activity recorded at multiple sites. This allows us to identify causal relations that are reflected in neuronal population activity. To derive our strategy, we assume a generic linear model of interacting continuous variables, the components of which represent the activity of local neuronal populations. The suggested method for inferring connectivity from recorded signals exploits the fact that the covariance matrix derived from the observed activity contains information about the existence, the direction and the sign of connections. Assuming a sparsely coupled network, we disambiguate the underlying causal structure via L1-minimization, which is known to prefer sparse solutions. In general, this method is suited to infer effective connectivity from resting state data of various types. We show that our method is applicable over a broad range of structural parameters regarding network size and connection probability of the network. We also explored parameters affecting its activity dynamics, like the eigenvalue spectrum. Also, based on the simulation of suitable Ornstein-Uhlenbeck processes to model BOLD dynamics, we show that with our method it is possible to estimate directed connectivity from zero-lag covariances derived from such signals. In this study, we consider measurement noise and unobserved nodes as additional confounding factors. Furthermore, we investigate the amount of data required for a reliable estimate. Additionally, we apply the proposed method on full-brain resting-state fast fMRI datasets. The resulting network exhibits a tendency for close-by areas being connected as well as inter-hemispheric connections between corresponding areas. In addition, we found that a surprisingly large fraction of more than one third of all identified connections were of
Continuous Covariate Imbalance and Conditional Power for Clinical Trial Interim Analyses
Ciolino, Jody D.; Martin, Renee' H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.
2014-01-01
Oftentimes valid statistical analyses for clinical trials involve adjustment for known influential covariates, regardless of imbalance observed in these covariates at baseline across treatment groups. Thus, it must be the case that valid interim analyses also properly adjust for these covariates. There are situations, however, in which covariate adjustment is not possible, not planned, or simply carries less merit as it makes inferences less generalizable and less intuitive. In this case, covariate imbalance between treatment groups can have a substantial effect on both interim and final primary outcome analyses. This paper illustrates the effect of influential continuous baseline covariate imbalance on unadjusted conditional power (CP), and thus, on trial decisions based on futility stopping bounds. The robustness of the relationship is illustrated for normal, skewed, and bimodal continuous baseline covariates that are related to a normally distributed primary outcome. Results suggest that unadjusted CP calculations in the presence of influential covariate imbalance require careful interpretation and evaluation. PMID:24607294
Thomas, R. E.; Schindfessel, L.; McLelland, S. J.; Creëlle, S.; De Mulder, T.
2017-07-01
This paper compiles the technical characteristics and operating principles of the Nortek Vectrino Profiler and reviews previously reported user experiences. A series of experiments are then presented that investigate instrument behaviour and performance, with a particular focus on variations within the profile. First, controlled tests investigate the sensitivity of acoustic amplitude (and Signal-to-Noise Ratio, SNR) and pulse-to-pulse correlation coefficient, R 2, to seeding concentration and cell geometry. Second, a novel methodology that systematically shifts profiling cells through a single absolute vertical position investigates the sensitivity of mean velocities, SNR and noise to: (a) emitted sound intensity and the presence (or absence) of acoustic seeding; and (b) varying flow rates under ideal acoustic seeding conditions. A new solution is derived to quantify the noise affecting the two perpendicular tristatic systems of the Vectrino Profiler and its contribution to components of the Reynolds stress tensor. Results suggest that for the Vectrino Profiler: 1. optimum acoustic seeding concentrations are ~3000 to 6000 mg L-1 2. mean velocity magnitudes are biased by variable amounts in proximal cells but are consistently underestimated in distal cells; 3. noise varies parabolically with a minimum around the ‘sweet spot’, 50 mm below the transceiver; 4. the receiver beams only intersect at the sweet spot and diverge nearer to and further from the transceiver. This divergence significantly reduces the size of the sampled area away from the sweet spot, reducing data quality; 5. the most reliable velocity data will normally be collected in the region between approximately 43 and 61 mm below the transceiver.
International Nuclear Information System (INIS)
Thomas, R E; Schindfessel, L; Creëlle, S; De Mulder, T; McLelland, S J
2017-01-01
This paper compiles the technical characteristics and operating principles of the Nortek Vectrino Profiler and reviews previously reported user experiences. A series of experiments are then presented that investigate instrument behaviour and performance, with a particular focus on variations within the profile. First, controlled tests investigate the sensitivity of acoustic amplitude (and Signal-to-Noise Ratio, SNR) and pulse-to-pulse correlation coefficient, R 2 , to seeding concentration and cell geometry. Second, a novel methodology that systematically shifts profiling cells through a single absolute vertical position investigates the sensitivity of mean velocities, SNR and noise to: (a) emitted sound intensity and the presence (or absence) of acoustic seeding; and (b) varying flow rates under ideal acoustic seeding conditions. A new solution is derived to quantify the noise affecting the two perpendicular tristatic systems of the Vectrino Profiler and its contribution to components of the Reynolds stress tensor. Results suggest that for the Vectrino Profiler: 1. optimum acoustic seeding concentrations are ∼3000 to 6000 mg L −1 ; 2. mean velocity magnitudes are biased by variable amounts in proximal cells but are consistently underestimated in distal cells; 3. noise varies parabolically with a minimum around the ‘sweet spot’, 50 mm below the transceiver; 4. the receiver beams only intersect at the sweet spot and diverge nearer to and further from the transceiver. This divergence significantly reduces the size of the sampled area away from the sweet spot, reducing data quality; 5. the most reliable velocity data will normally be collected in the region between approximately 43 and 61 mm below the transceiver. (paper)
Noise affects resource assessment in an invertebrate.
Walsh, Erin P; Arnott, Gareth; Kunc, Hansjoerg P
2017-04-01
Anthropogenic noise is a global pollutant, affecting animals across taxa. However, how noise pollution affects resource acquisition is unknown. Hermit crabs ( Pagurus bernhardus ) engage in detailed assessment and decision-making when selecting a critical resource, their shell; this is crucial as individuals in poor shells suffer lower reproductive success and higher mortality. We experimentally exposed hermit crabs to anthropogenic noise during shell selection. When exposed to noise, crabs approached the shell faster, spent less time investigating it, and entered it faster. Our results demonstrate that changes in the acoustic environment affect the behaviour of hermit crabs by modifying the selection process of a vital resource. This is all the more remarkable given that the known cues used in shell selection involve chemical, visual and tactile sensory channels. Thus, our study provides rare evidence for a cross-modal impact of noise pollution. © 2017 The Author(s).
Covariance Function for Nearshore Wave Assimilation Systems
2018-01-30
which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE
Maximizing noise energy for noise-masking studies.
Jules Étienne, Cédric; Arleo, Angelo; Allard, Rémy
2017-08-01
Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100 %. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.
Visualization and assessment of spatio-temporal covariance properties
Huang, Huang
2017-11-23
Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.
Summary of the Workshop on Neutron Cross Section Covariances
International Nuclear Information System (INIS)
Smith, Donald L.
2008-01-01
A Workshop on Neutron Cross Section Covariances was held from June 24-27, 2008, in Port Jefferson, New York. This Workshop was organized by the National Nuclear Data Center, Brookhaven National Laboratory, to provide a forum for reporting on the status of the growing field of neutron cross section covariances for applications and for discussing future directions of the work in this field. The Workshop focused on the following four major topical areas: covariance methodology, recent covariance evaluations, covariance applications, and user perspectives. Attention was given to the entire spectrum of neutron cross section covariance concerns ranging from light nuclei to the actinides, and from the thermal energy region to 20 MeV. The papers presented at this conference explored topics ranging from fundamental nuclear physics concerns to very specific applications in advanced reactor design and nuclear criticality safety. This paper provides a summary of this workshop. Brief comments on the highlights of each Workshop contribution are provided. In addition, a perspective on the achievements and shortcomings of the Workshop as well as on the future direction of research in this field is offered
Real-time probabilistic covariance tracking with efficient model update.
Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li
2012-05-01
The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.
Random noise suppression of seismic data using non-local Bayes algorithm
Chang, De-Kuan; Yang, Wu-Yang; Wang, Yi-Hui; Yang, Qing; Wei, Xin-Jian; Feng, Xiao-Ying
2018-02-01
For random noise suppression of seismic data, we present a non-local Bayes (NL-Bayes) filtering algorithm. The NL-Bayes algorithm uses the Gaussian model instead of the weighted average of all similar patches in the NL-means algorithm to reduce the fuzzy of structural details, thereby improving the denoising performance. In the denoising process of seismic data, the size and the number of patches in the Gaussian model are adaptively calculated according to the standard deviation of noise. The NL-Bayes algorithm requires two iterations to complete seismic data denoising, but the second iteration makes use of denoised seismic data from the first iteration to calculate the better mean and covariance of the patch Gaussian model for improving the similarity of patches and achieving the purpose of denoising. Tests with synthetic and real data sets demonstrate that the NL-Bayes algorithm can effectively improve the SNR and preserve the fidelity of seismic data.
Multiple feature fusion via covariance matrix for visual tracking
Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui
2018-04-01
Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.
Active Noise Control for Dishwasher noise
Lee, Nokhaeng; Park, Youngjin
2016-09-01
The dishwasher is a useful home appliance and continually used for automatically washing dishes. It's commonly placed in the kitchen with built-in style for practicality and better use of space. In this environment, people are easily exposed to dishwasher noise, so it is an important issue for the consumers, especially for the people living in open and narrow space. Recently, the sound power levels of the noise are about 40 - 50 dBA. It could be achieved by removal of noise sources and passive means of insulating acoustical path. For more reduction, such a quiet mode with the lower speed of cycle has been introduced, but this deteriorates the washing capacity. Under this background, we propose active noise control for dishwasher noise. It is observed that the noise is propagating mainly from the lower part of the front side. Control speakers are placed in the part for the collocation. Observation part of estimating sound field distribution and control part of generating the anti-noise are designed for active noise control. Simulation result shows proposed active noise control scheme could have a potential application for dishwasher noise reduction.
Bayesian hierarchical model for large-scale covariance matrix estimation.
Zhu, Dongxiao; Hero, Alfred O
2007-12-01
Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
von Cramon-Taubadel, Noreen; Schroeder, Lauren
2016-10-01
Estimation of the variance-covariance (V/CV) structure of fragmentary bioarchaeological populations requires the use of proxy extant V/CV parameters. However, it is currently unclear whether extant human populations exhibit equivalent V/CV structures. Random skewers (RS) and hierarchical analyses of common principal components (CPC) were applied to a modern human cranial dataset. Cranial V/CV similarity was assessed globally for samples of individual populations (jackknifed method) and for pairwise population sample contrasts. The results were examined in light of potential explanatory factors for covariance difference, such as geographic region, among-group distance, and sample size. RS analyses showed that population samples exhibited highly correlated multivariate responses to selection, and that differences in RS results were primarily a consequence of differences in sample size. The CPC method yielded mixed results, depending upon the statistical criterion used to evaluate the hierarchy. The hypothesis-testing (step-up) approach was deemed problematic due to sensitivity to low statistical power and elevated Type I errors. In contrast, the model-fitting (lowest AIC) approach suggested that V/CV matrices were proportional and/or shared a large number of CPCs. Pairwise population sample CPC results were correlated with cranial distance, suggesting that population history explains some of the variability in V/CV structure among groups. The results indicate that patterns of covariance in human craniometric samples are broadly similar but not identical. These findings have important implications for choosing extant covariance matrices to use as proxy V/CV parameters in evolutionary analyses of past populations. © 2016 Wiley Periodicals, Inc.
Xu, Xu Steven; Yuan, Min; Yang, Haitao; Feng, Yan; Xu, Jinfeng; Pinheiro, Jose
2017-01-01
Covariate analysis based on population pharmacokinetics (PPK) is used to identify clinically relevant factors. The likelihood ratio test (LRT) based on nonlinear mixed effect model fits is currently recommended for covariate identification, whereas individual empirical Bayesian estimates (EBEs) are considered unreliable due to the presence of shrinkage. The objectives of this research were to investigate the type I error for LRT and EBE approaches, to confirm the similarity of power between the LRT and EBE approaches from a previous report and to explore the influence of shrinkage on LRT and EBE inferences. Using an oral one-compartment PK model with a single covariate impacting on clearance, we conducted a wide range of simulations according to a two-way factorial design. The results revealed that the EBE-based regression not only provided almost identical power for detecting a covariate effect, but also controlled the false positive rate better than the LRT approach. Shrinkage of EBEs is likely not the root cause for decrease in power or inflated false positive rate although the size of the covariate effect tends to be underestimated at high shrinkage. In summary, contrary to the current recommendations, EBEs may be a better choice for statistical tests in PPK covariate analysis compared to LRT. We proposed a three-step covariate modeling approach for population PK analysis to utilize the advantages of EBEs while overcoming their shortcomings, which allows not only markedly reducing the run time for population PK analysis, but also providing more accurate covariate tests.
A trade-off analysis design tool. Aircraft interior noise-motion/passenger satisfaction model
Jacobson, I. D.
1977-01-01
A design tool was developed to enhance aircraft passenger satisfaction. The effect of aircraft interior motion and noise on passenger comfort and satisfaction was modelled. Effects of individual aircraft noise sources were accounted for, and the impact of noise on passenger activities and noise levels to safeguard passenger hearing were investigated. The motion noise effect models provide a means for tradeoff analyses between noise and motion variables, and also provide a framework for optimizing noise reduction among noise sources. Data for the models were collected onboard commercial aircraft flights and specially scheduled tests.
Noise properties of the EM algorithm. Pt. 1
International Nuclear Information System (INIS)
Barrett, H.H.; Wilson, D.W.; Tsui, B.M.W.
1994-01-01
The expectation-maximisation (EM) algorithm is an important tool for maximum-likelihood (ML) estimation and image reconstruction, especially in medical imaging. It is a non-linear iterative algorithm that attempts to find the ML estimate of the object that produced a data set. The convergence of the algorithm and other deterministic properties are well established, but relatively little is known about how noise in the data influences noise in the final reconstructed image. In this paper we present a detailed treatment of these statistical properties. The specific application we have in mind is image reconstruction in emission tomography, but the results are valid for any application of the EM algorithm in which the data set can be described by Poisson statistics. We show that the probability density function for the grey level at a pixel in the image is well approximated by a log-normal law. An expression is derived for the variance of the grey level and for pixel-to-pixel covariance. The variance increases rapidly with iteration number at first, but eventually saturates as the ML estimate is approached. Moreover, the variance at any iteration number has a factor proportional to the square of the mean image (though other factors may also depend on the mean image), so a map of the standard deviation resembles the object itself. Thus low-intensity regions of the image tend to have low noise. (author)
Identifying and characterizing systematic temporally-lagged BOLD artifacts.
Byrge, Lisa; Kennedy, Daniel P
2018-05-01
Residual noise in the BOLD signal remains problematic for fMRI - particularly for techniques such as functional connectivity, where findings can be spuriously influenced by noise sources that can covary with individual differences. Many such potential noise sources - for instance, motion and respiration - can have a temporally lagged effect on the BOLD signal. Thus, here we present a tool for assessing residual lagged structure in the BOLD signal that is associated with nuisance signals, using a construction similar to a peri-event time histogram. Using this method, we find that framewise displacements - both large and very small - were followed by structured, prolonged, and global changes in the BOLD signal that depend on the magnitude of the preceding displacement and extend for tens of seconds. This residual lagged BOLD structure was consistent across datasets, and independently predicted considerable variance in the global cortical signal (as much as 30-40% in some subjects). Mean functional connectivity estimates varied similarly as a function of displacements occurring many seconds in the past, even after strict censoring. Similar patterns of residual lagged BOLD structure were apparent following respiratory fluctuations (which covaried with framewise displacements), implicating respiration as one likely mechanism underlying the displacement-linked structure observed. Global signal regression largely attenuates this artifactual structure. These findings suggest the need for caution in interpreting results of individual difference studies where noise sources might covary with the individual differences of interest, and highlight the need for further development of preprocessing techniques for mitigating such structure in a more nuanced and targeted manner. Copyright © 2018 Elsevier Inc. All rights reserved.
Cross-covariance functions for multivariate random fields based on latent dimensions
Apanasovich, T. V.
2010-02-16
The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable and computationally feasible classes of cross-covariance functions in closed form. We focus on spatio-temporal cross-covariance functions that can be nonseparable, asymmetric and can have different covariance structures, for instance different smoothness parameters, in each component. We discuss estimation of these models and perform a small simulation study to demonstrate our approach. We illustrate our methodology on a trivariate spatio-temporal pollution dataset from California and demonstrate that our cross-covariance performs better than other competing models. © 2010 Biometrika Trust.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Position Error Covariance Matrix Validation and Correction
Frisbee, Joe, Jr.
2016-01-01
In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.
Noise and neurotoxic chemical exposure relationship to workplace traumatic injuries: A review.
Estill, Cheryl Fairfield; Rice, Carol H; Morata, Thais; Bhattacharya, Amit
2017-02-01
More than 5,000 fatalities and eight million injuries occurred in the workplace in 2007 at a cost of $6 billion and $186 billion, respectively. Neurotoxic chemicals are known to affect central nervous system functions among workers, which include balance and hearing disorders. However, it is not known if there is an association between exposure to noise and solvents and acute injuries. A thorough review was conducted of the literature on the relationship between noise or solvent exposures and hearing loss with various health outcomes. The search resulted in 41 studies. Health outcomes included: hearing loss, workplace injuries, absence from work due to sickness, fatalities, hospital admissions due to workplace accidents, traffic accidents, hypertension, balance, slip, trips, or falls, cognitive measures, or disability retirement. Important covariates in these studies were age of employee, type of industry or occupation, or length of employment. Most authors that evaluated noise exposure concluded that higher exposure to noise resulted in more of the chosen health effect but the relationship is not well understood. Studies that evaluated hearing loss found that hearing loss was related to occupational injury, disability retirement, or traffic accidents. Studies that assessed both noise exposure and hearing loss as risk factors for occupational injuries reported that hearing loss was related to occupational injuries as much or more than noise exposure. Evidence suggests that solvent exposure is likely to be related to accidents or other health consequences such balance disorders. Many authors reported that noise exposures and hearing loss, respectively, are likely to be related to occupational accidents. Practical applications: The potential significance of the study is that findings could be used by managers to reduce injuries and the costs associated with those injures. Published by Elsevier Ltd.
Covariant fields on anti-de Sitter spacetimes
Cotăescu, Ion I.
2018-02-01
The covariant free fields of any spin on anti-de Sitter (AdS) spacetimes are studied, pointing out that these transform under isometries according to covariant representations (CRs) of the AdS isometry group, induced by those of the Lorentz group. Applying the method of ladder operators, it is shown that the CRs with unique spin are equivalent with discrete unitary irreducible representations (UIRs) of positive energy of the universal covering group of the isometry one. The action of the Casimir operators is studied finding how the weights of these representations (reps.) may depend on the mass and spin of the covariant field. The conclusion is that on AdS spacetime, one cannot formulate a universal mass condition as in special relativity.
Covariant Noncommutative Field Theory
Energy Technology Data Exchange (ETDEWEB)
Estrada-Jimenez, S [Licenciaturas en Fisica y en Matematicas, Facultad de Ingenieria, Universidad Autonoma de Chiapas Calle 4a Ote. Nte. 1428, Tuxtla Gutierrez, Chiapas (Mexico); Garcia-Compean, H [Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN P.O. Box 14-740, 07000 Mexico D.F., Mexico and Centro de Investigacion y de Estudios Avanzados del IPN, Unidad Monterrey Via del Conocimiento 201, Parque de Investigacion e Innovacion Tecnologica (PIIT) Autopista nueva al Aeropuerto km 9.5, Lote 1, Manzana 29, cp. 66600 Apodaca Nuevo Leon (Mexico); Obregon, O [Instituto de Fisica de la Universidad de Guanajuato P.O. Box E-143, 37150 Leon Gto. (Mexico); Ramirez, C [Facultad de Ciencias Fisico Matematicas, Universidad Autonoma de Puebla, P.O. Box 1364, 72000 Puebla (Mexico)
2008-07-02
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced.
Covariant Noncommutative Field Theory
International Nuclear Information System (INIS)
Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.
2008-01-01
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced
Physical properties of the Schur complement of local covariance matrices
International Nuclear Information System (INIS)
Haruna, L F; Oliveira, M C de
2007-01-01
General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state ρ 12 described by a 4 x 4 covariance matrix V, the Schur complement of a local covariance submatrix V 1 of it can be interpreted as a new covariance matrix representing a Gaussian operator of party 1 conditioned to local parity measurements on party 2. The connection with a partial parity measurement over a bipartite quantum state and the determination of the reduced Wigner function is given and an operational process of parity measurement is developed. Generalization of this procedure to an n-partite Gaussian state is given, and it is demonstrated that the n - 1 system state conditioned to a partial parity projection is given by a covariance matrix such that its 2 x 2 block elements are Schur complements of special local matrices
Anthropogenic noise pollution from pile-driving disrupts the structure and dynamics of fish shoals.
Herbert-Read, James E; Kremer, Louise; Bruintjes, Rick; Radford, Andrew N; Ioannou, Christos C
2017-09-27
Noise produced from a variety of human activities can affect the physiology and behaviour of individual animals, but whether noise disrupts the social behaviour of animals is largely unknown. Animal groups such as flocks of birds or shoals of fish use simple interaction rules to coordinate their movements with near neighbours. In turn, this coordination allows individuals to gain the benefits of group living such as reduced predation risk and social information exchange. Noise could change how individuals interact in groups if noise is perceived as a threat, or if it masked, distracted or stressed individuals, and this could have impacts on the benefits of grouping. Here, we recorded trajectories of individual juvenile seabass ( Dicentrarchus labrax ) in groups under controlled laboratory conditions. Groups were exposed to playbacks of either ambient background sound recorded in their natural habitat, or playbacks of pile-driving, commonly used in marine construction. The pile-driving playback affected the structure and dynamics of the fish shoals significantly more than the ambient-sound playback. Compared to the ambient-sound playback, groups experiencing the pile-driving playback became less cohesive, less directionally ordered, and were less correlated in speed and directional changes. In effect, the additional-noise treatment disrupted the abilities of individuals to coordinate their movements with one another. Our work highlights the potential for noise pollution from pile-driving to disrupt the collective dynamics of fish shoals, which could have implications for the functional benefits of a group's collective behaviour. © 2017 The Authors.
Covariant n2-plet mass formulas
International Nuclear Information System (INIS)
Davidson, A.
1979-01-01
Using a generalized internal symmetry group analogous to the Lorentz group, we have constructed a covariant n 2 -plet mass operator. This operator is built as a scalar matrix in the (n;n*) representation, and its SU(n) breaking parameters are identified as intrinsic boost ones. Its basic properties are: covariance, Hermiticity, positivity, charge conjugation, quark contents, and a self-consistent n 2 -1, 1 mixing. The GMO and the Okubo formulas are obtained by considering two different limits of the same generalized mass formula
Summary report of technical meeting on neutron cross section covariances
International Nuclear Information System (INIS)
Trkov, A.; Smith, D.L.; Capote Noy, R.
2011-01-01
A summary is given of the Technical Meeting on Neutron Cross Section Covariances. The meeting goal was to assess covariance data needs and recommend appropriate methodologies to address those needs. Discussions on covariance data focused on three general topics: 1) Resonance and unresolved resonance regions; 2) Fast neutron region; and 3) Users' perspective: benchmarks' uncertainty and reactor dosimetry. A number of recommendations for further work were generated and the important work that remains to be done in the field of covariances was identified. (author)
Ichino, Shinya; Mawaki, Takezo; Teramoto, Akinobu; Kuroda, Rihito; Park, Hyeonwoo; Wakashima, Shunichi; Goto, Tetsuya; Suwa, Tomoyuki; Sugawa, Shigetoshi
2018-04-01
Random telegraph noise (RTN), which occurs in in-pixel source follower (SF) transistors, has become one of the most critical problems in high-sensitivity CMOS image sensors (CIS) because it is a limiting factor of dark random noise. In this paper, the behaviors of RTN toward changes in SF drain current conditions were analyzed using a low-noise array test circuit measurement system with a floor noise of 35 µV rms. In addition to statistical analysis by measuring a large number of transistors (18048 transistors), we also analyzed the behaviors of RTN parameters such as amplitude and time constants in the individual transistors. It is demonstrated that the appearance probability of RTN becomes small under a small drain current condition, although large-amplitude RTN tends to appear in a very small number of cells.
Assessing Instructional Modalities: Individualized Treatment Effects for Personalized Learning
Beemer, Joshua; Spoon, Kelly; Fan, Juanjuan; Stronach, Jeanne; Frazee, James P.; Bohonak, Andrew J.; Levine, Richard A.
2018-01-01
Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…
Comparison of noise impact indicators, calculated on the basis of noise maps of DENL
Borst, H.C.; Miedema, H.M.E.
2005-01-01
In this paper, the following four indicators describing noise annoyance in a community are considered: the percentage of people being highly annoyed (pHA), annoyed (pA), (at least) little annoyed (p LA), and the mean of the expected individual annoyance scores (m EA) in the population concerned.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Pu239 Cross-Section Variations Based on Experimental Uncertainties and Covariances
Energy Technology Data Exchange (ETDEWEB)
Sigeti, David Edward [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Brian J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parsons, D. Kent [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-10-18
Algorithms and software have been developed for producing variations in plutonium-239 neutron cross sections based on experimental uncertainties and covariances. The varied cross-section sets may be produced as random samples from the multi-variate normal distribution defined by an experimental mean vector and covariance matrix, or they may be produced as Latin-Hypercube/Orthogonal-Array samples (based on the same means and covariances) for use in parametrized studies. The variations obey two classes of constraints that are obligatory for cross-section sets and which put related constraints on the mean vector and covariance matrix that detemine the sampling. Because the experimental means and covariances do not obey some of these constraints to sufficient precision, imposing the constraints requires modifying the experimental mean vector and covariance matrix. Modification is done with an algorithm based on linear algebra that minimizes changes to the means and covariances while insuring that the operations that impose the different constraints do not conflict with each other.
Greenwood, Eric, II; Schmitz, Fredric H.
2010-01-01
A new physics-based parameter identification method for rotor harmonic noise sources is developed using an acoustic inverse simulation technique. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. This new method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor Blade-Vortex Interaction (BVI) noise, allowing accurate estimates of BVI noise to be made for operating conditions based on a small number of measurements taken at different operating conditions.
A scale invariant covariance structure on jet space
DEFF Research Database (Denmark)
Pedersen, Kim Steenstrup; Loog, Marco; Markussen, Bo
2005-01-01
This paper considers scale invariance of statistical image models. We study statistical scale invariance of the covariance structure of jet space under scale space blurring and derive the necessary structure and conditions of the jet covariance matrix in order for it to be scale invariant. As par...
Covarient quantization of heterotic strings in supersymmetric chiral boson formulation
International Nuclear Information System (INIS)
Yu, F.
1992-01-01
This dissertation presents the covariant supersymmetric chiral boson formulation of the heterotic strings. The main feature of this formulation is the covariant quantization of the so-called leftons and rightons -- the (1,0) supersymmetric generalizations of the world-sheet chiral bosons -- that constitute basic building blocks of general heterotic-type string models. Although the (Neveu-Schwarz-Ramond or Green-Schwarz) heterotic strings provide the most realistic string models, their covariant quantization, with the widely-used Siegel formalism, has never been rigorously carried out. It is clarified in this dissertation that the covariant Siegel formalism is pathological upon quantization. As a test, a general classical covariant (NSR) heterotic string action that has the Siegel symmetry is constructed in arbitrary curved space-time coupled to (1,0) world-sheet super-gravity. In the light-cone gauge quantization, the critical dimensions are derived for such an action with leftons and rightons compactified on group manifolds G L x G R . The covariant quantization of this action does not agree with the physical results in the light-cone gauge quantization. This dissertation establishes a new formalism for the covariant quantization of heterotic strings. The desired consistent covariant path integral quantization of supersymmetric chiral bosons, and thus the general (NSR) heterotic-type strings with leftons and rightons compactified on torus circle-times d L S 1 x circle-times d R S 1 are carried out. An infinite set of auxiliary (1,0) scalar superfields is introduced to convert the second-class chiral constraint into first-class ones. The covariant gauge-fixed action has an extended BRST symmetry described by the graded algebra GL(1/1). A regularization respecting this symmetry is proposed to deal with the contributions of the infinite towers of auxiliary fields and associated ghosts
Covariance of time-ordered products implies local commutativity of fields
International Nuclear Information System (INIS)
Greenberg, O.W.
2006-01-01
We formulate Lorentz covariance of a quantum field theory in terms of covariance of time-ordered products (or other Green's functions). This formulation of Lorentz covariance implies spacelike local commutativity or anticommutativity of fields, sometimes called microscopic causality or microcausality. With this formulation microcausality does not have to be taken as a separate assumption
The impact of auditory white noise on semantic priming.
Angwin, Anthony J; Wilson, Wayne J; Copland, David A; Barry, Robert J; Myatt, Grace; Arnott, Wendy L
2018-04-10
It has been proposed that white noise can improve cognitive performance for some individuals, particularly those with lower attention, and that this effect may be mediated by dopaminergic circuitry. Given existing evidence that semantic priming is modulated by dopamine, this study investigated whether white noise can facilitate semantic priming. Seventy-eight adults completed an auditory semantic priming task with and without white noise, at either a short or long inter-stimulus interval (ISI). Measures of both direct and indirect semantic priming were examined. Analysis of the results revealed significant direct and indirect priming effects at each ISI in noise and silence, however noise significantly reduced the magnitude of indirect priming. Analyses of subgroups with higher versus lower attention revealed a reduction to indirect priming in noise relative to silence for participants with lower executive and orienting attention. These findings suggest that white noise focuses automatic spreading activation, which may be driven by modulation of dopaminergic circuitry. Copyright © 2018 Elsevier Inc. All rights reserved.
The association of noise sensitivity with music listening, training, and aptitude
Directory of Open Access Journals (Sweden)
Marina Kliuchko
2015-01-01
Full Text Available After intensive, long-term musical training, the auditory system of a musician is specifically tuned to perceive musical sounds. We wished to find out whether a musician′s auditory system also develops increased sensitivity to any sound of everyday life, experiencing them as noise. For this purpose, an online survey, including questionnaires on noise sensitivity, musical background, and listening tests for assessing musical aptitude, was administered to 197 participants in Finland and Italy. Subjective noise sensitivity (assessed with the Weinstein′s Noise Sensitivity Scale was analyzed for associations with musicianship, musical aptitude, weekly time spent listening to music, and the importance of music in each person′s life (or music importance. Subjects were divided into three groups according to their musical expertise: Nonmusicians (N = 103, amateur musicians (N = 44, and professional musicians (N = 50. The results showed that noise sensitivity did not depend on musical expertise or performance on musicality tests or the amount of active (attentive listening to music. In contrast, it was associated with daily passive listening to music, so that individuals with higher noise sensitivity spent less time in passive (background listening to music than those with lower sensitivity to noise. Furthermore, noise-sensitive respondents rated music as less important in their life than did individuals with lower sensitivity to noise. The results demonstrate that the special sensitivity of the auditory system derived from musical training does not lead to increased irritability from unwanted sounds. However, the disposition to tolerate contingent musical backgrounds in everyday life depends on the individual′s noise sensitivity.
Kalantary, Saba; Dehghani, Ali; Yekaninejad, Mir Saeed; Omidi, Leila; Rahimzadeh, Mitra
2015-07-01
One of the most important impacts of industrial noise is physiological and psychological effects. The increases in workers' blood pressure and heart rate were detected during and after exposure to high levels of noise. The objectives of this research were to determine whether the noise exposures have any effects on blood pressure and heart rate of workers in the automotive parts industry. This case study was done in 2011 at different units of an automotive parts manufacturing in Tehran. Sound pressure level was measured at different units of the factory with a calibrated instrument. Demographic features of workers were gathered with an appropriate questionnaire. Heart rate and blood pressure were measured twice in a day in the start time of work day (before exposure to noise) and middle shift hours (during exposure to noise) in the occupational physician office. For analyzing data, chi-square, independent sample t-test, paired t-test, and analysis of covariance (ANCOVA) were used. P industrial noise may increase the heart rate of workers. Although rises in heart rate, systolic, and diastolic blood pressure of workers in the case group were observed after exposure to noise, the values of heart rate, systolic, and diastolic blood pressure were in the normal range. Further experimental investigations are needed to determine the relationships between these variables.
DEFF Research Database (Denmark)
Møller, Jesper; Diaz-Avalos, Carlos
Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... dataset consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....
DEFF Research Database (Denmark)
Møller, Jesper; Diaz-Avalos, Carlos
2010-01-01
Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable fo...... data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent....
Noncommutative Gauge Theory with Covariant Star Product
International Nuclear Information System (INIS)
Zet, G.
2010-01-01
We present a noncommutative gauge theory with covariant star product on a space-time with torsion. In order to obtain the covariant star product one imposes some restrictions on the connection of the space-time. Then, a noncommutative gauge theory is developed applying this product to the case of differential forms. Some comments on the advantages of using a space-time with torsion to describe the gravitational field are also given.
Hearing aid noise suppression and working memory function
DEFF Research Database (Denmark)
Neher, Tobias; Wagener, Kirsten C.; Fischer, Rosa-Linde
2018-01-01
OBJECTIVE: Research findings concerning the relation between benefit from hearing aid (HA) noise suppression and working memory function are inconsistent. The current study thus investigated the effects of three noise suppression algorithms on auditory working memory and the relation with reading......-to-noise ratio (SNR) improvement. Auditory working memory was assessed at +6 dB SNR using listening span and N-back paradigms. STUDY SAMPLE: Twenty experienced HA users ages 55-80 with large differences in reading span. RESULTS: For the listening span measurements, there was an influence of HA setting....... CONCLUSIONS: HA noise suppression may affect the recognition and recall of speech at positive SNRs, irrespective of individual reading span. Future work should improve the reliability of the auditory working memory measurements....
Signs of depth-luminance covariance in 3-D cluttered scenes.
Scaccia, Milena; Langer, Michael S
2018-03-01
In three-dimensional (3-D) cluttered scenes such as foliage, deeper surfaces often are more shadowed and hence darker, and so depth and luminance often have negative covariance. We examined whether the sign of depth-luminance covariance plays a role in depth perception in 3-D clutter. We compared scenes rendered with negative and positive depth-luminance covariance where positive covariance means that deeper surfaces are brighter and negative covariance means deeper surfaces are darker. For each scene, the sign of the depth-luminance covariance was given by occlusion cues. We tested whether subjects could use this sign information to judge the depth order of two target surfaces embedded in 3-D clutter. The clutter consisted of distractor surfaces that were randomly distributed in a 3-D volume. We tested three independent variables: the sign of the depth-luminance covariance, the colors of the targets and distractors, and the background luminance. An analysis of variance showed two main effects: Subjects performed better when the deeper surfaces were darker and when the color of the target surfaces was the same as the color of the distractors. There was also a strong interaction: Subjects performed better under a negative depth-luminance covariance condition when targets and distractors had different colors than when they had the same color. Our results are consistent with a "dark means deep" rule, but the use of this rule depends on the similarity between the color of the targets and color of the 3-D clutter.
Covariance fitting of highly-correlated data in lattice QCD
Yoon, Boram; Jang, Yong-Chull; Jung, Chulwoo; Lee, Weonjong
2013-07-01
We address a frequently-asked question on the covariance fitting of highly-correlated data such as our B K data based on the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have a fitting function accurate enough to fit extremely precise data. When eigenvalues of the covariance matrix are small, even a tiny error in the fitting function yields a large chi-square value and spoils the fitting procedure. We have applied a number of prescriptions available in the market, such as the cut-off method, modified covariance matrix method, and Bayesian method. We also propose a brand new method, the eigenmode shift (ES) method, which allows a full covariance fitting without modifying the covariance matrix at all. We provide a pedagogical example of data analysis in which the cut-off method manifestly fails in fitting, but the rest work well. In our case of the B K fitting, the diagonal approximation, the cut-off method, the ES method, and the Bayesian method work reasonably well in an engineering sense. However, interpreting the meaning of χ 2 is easier in the case of the ES method and the Bayesian method in a theoretical sense aesthetically. Hence, the ES method can be a useful alternative optional tool to check the systematic error caused by the covariance fitting procedure.
Directory of Open Access Journals (Sweden)
Sabine A. Janssen
2011-05-01
Full Text Available In environmental noise control one commonly employs the A-weighted sound level as an approximate measure of the effect of noise on people. A measure that is more closely related to direct human perception of noise is the loudness level. At constant A-weighted sound level, the loudness level of a noise signal varies considerably with the shape of the frequency spectrum of the noise signal. In particular the bandwidth of the spectrum has a large effect on the loudness level, due to the effect of critical bands in the human hearing system. The low-frequency content of the spectrum also has an effect on the loudness level. In this note the relation between loudness level and A-weighted sound level is analyzed for various environmental noise spectra, including spectra of traffic noise, aircraft noise, and industrial noise. From loudness levels calculated for these environmental noise spectra, diagrams are constructed that show the relation between loudness level, A‑weighted sound level, and shape of the spectrum. The diagrams show that the upper limits of the loudness level for broadband environmental noise spectra are about 20 to 40 phon higher than the lower limits for narrowband spectra, which correspond to the loudness levels of pure tones. The diagrams are useful for assessing limitations and potential improvements of environmental noise control methods and policy based on A-weighted sound levels.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei; Holbrook, Andrew; Fortin, Norbert J.; Ombao, Hernando; Shahbaba, Babak
2017-01-01
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix
Evaluation of noise levels in manufacturing sectors in Thika district ...
African Journals Online (AJOL)
Noise is considered as any unwanted sound that may adversely affect the health and wellbeing of individuals or populations exposed. This study assessed the magnitude of occupational noise exposures to workers in different manufacturing sectors in Thika District‐Kenya. Systematic random sampling was used to select 8 ...
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-01-01
-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters
Fermionic covariant prolongation structure theory for supernonlinear evolution equation
International Nuclear Information System (INIS)
Cheng Jipeng; Wang Shikun; Wu Ke; Zhao Weizhong
2010-01-01
We investigate the superprincipal bundle and its associated superbundle. The super(nonlinear)connection on the superfiber bundle is constructed. Then by means of the connection theory, we establish the fermionic covariant prolongation structure theory of the supernonlinear evolution equation. In this geometry theory, the fermionic covariant fundamental equations determining the prolongation structure are presented. As an example, the supernonlinear Schroedinger equation is analyzed in the framework of this fermionic covariant prolongation structure theory. We obtain its Lax pairs and Baecklund transformation.
On Galilean covariant quantum mechanics
International Nuclear Information System (INIS)
Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna
1991-08-01
Formalism exhibiting the Galilean covariance of wave mechanics is proposed. A new notion of quantum mechanical forces is introduced. The formalism is illustrated on the example of the harmonic oscillator. (author)
Advantages of binaural amplification to acceptable noise level of directional hearing aid users.
Kim, Ja-Hee; Lee, Jae Hee; Lee, Ho-Ki
2014-06-01
The goal of the present study was to examine whether Acceptable Noise Levels (ANLs) would be lower (greater acceptance of noise) in binaural listening than in monaural listening condition and also whether meaningfulness of background speech noise would affect ANLs for directional microphone hearing aid users. In addition, any relationships between the individual binaural benefits on ANLs and the individuals' demographic information were investigated. Fourteen hearing aid users (mean age, 64 years) participated for experimental testing. For the ANL calculation, listeners' most comfortable listening levels and background noise level were measured. Using Korean ANL material, ANLs of all participants were evaluated under monaural and binaural amplification with a counterbalanced order. The ANLs were also compared across five types of competing speech noises, consisting of 1- through 8-talker background speech maskers. Seven young normal-hearing listeners (mean age, 27 years) participated for the same measurements as a pilot testing. The results demonstrated that directional hearing aid users accepted more noise (lower ANLs) with binaural amplification than with monaural amplification, regardless of the type of competing speech. When the background speech noise became more meaningful, hearing-impaired listeners accepted less amount of noise (higher ANLs), revealing that ANL is dependent on the intelligibility of the competing speech. The individuals' binaural advantages in ANLs were significantly greater for the listeners with longer experience of hearing aids, yet not related to their age or hearing thresholds. Binaural directional microphone processing allowed hearing aid users to accept a greater amount of background noise, which may in turn improve listeners' hearing aid success. Informational masking substantially influenced background noise acceptance. Given a significant association between ANLs and duration of hearing aid usage, ANL measurement can be useful for
Astrophysical tests of scale-covariant gravity theories
International Nuclear Information System (INIS)
Mansfield, V.N.; Malin, S.
1980-01-01
Starting from the most general form of the conservation laws in scale-covariant gravitation theory, a conservation of energy equation appropriate for stars is derived. Applications to white dwarfs and neutron stars reveal serious difficulties for some choices of gauge that have been frequently employed in the literature on scale-covariant gravity. We also show how to restrict some of the possible gauges that result from theories which are independent of the Large Numbers Hypothesis
Covariant phase difference observables in quantum mechanics
International Nuclear Information System (INIS)
Heinonen, Teiko; Lahti, Pekka; Pellonpaeae, Juha-Pekka
2003-01-01
Covariant phase difference observables are determined in two different ways, by a direct computation and by a group theoretical method. A characterization of phase difference observables which can be expressed as the difference of two phase observables is given. The classical limits of such phase difference observables are determined and the Pegg-Barnett phase difference distribution is obtained from the phase difference representation. The relation of Ban's theory to the covariant phase theories is exhibited
White noise enhances new-word learning in healthy adults.
Angwin, Anthony J; Wilson, Wayne J; Arnott, Wendy L; Signorini, Annabelle; Barry, Robert J; Copland, David A
2017-10-12
Research suggests that listening to white noise may improve some aspects of cognitive performance in individuals with lower attention. This study investigated the impact of white noise on new word learning in healthy young adults, and whether this effect was mediated by executive attention skills. Eighty participants completed a single training session to learn the names of twenty novel objects. The session comprised 5 learning phases, each followed by a recall test. A final recognition test was also administered. Half the participants listened to white noise during the learning phases, and half completed the learning in silence. The noise group demonstrated superior recall accuracy over time, which was not impacted by participant attentional capacity. Recognition accuracy was near ceiling for both groups. These findings suggest that white noise has the capacity to enhance lexical acquisition.
"Ladder" structure in tonal noise generated by laminar flow around an airfoil.
Chong, Tze Pei; Joseph, Phillip
2012-06-01
The presence of a "ladder" structure in the airfoil tonal noise was discovered in the 1970s, but its mechanism hitherto remains a subject of continual investigation in the research community. Based on the measured noise results and some numerical analysis presented in this letter, the variations of four types of airfoil tonal noise frequencies with the flow velocity were analyzed individually. The ladder structure is proposed to be caused by the acoustic/hydrodynamic frequency lag between the scattering of the boundary layer instability noise and the discrete noise produced by an aeroacoustic feedback loop.
A Tool for Kalman Filter Tuning
DEFF Research Database (Denmark)
Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad
2007-01-01
The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. A method for estimating noise covariances from process data has been investigated. The method gives a least-squares estimate of the noise covariances......, which can be used to compute the Kalman filter gain....
Measurement of Acceptable Noise Level with Background Music.
Ahn, Hyun-Jung; Bahng, Junghwa; Lee, Jae Hee
2015-09-01
Acceptable noise level (ANL) is a measure of the maximum background noise level (BNL) that a person is willing to tolerate while following a target story. Although researchers have used various sources of target sound in ANL measures, a limited type of background noise has been used. Extending the previous study of Gordon-Hickey & Moore (2007), the current study determined the effect of music genre and tempo on ANLs as possible factors affecting ANLs. We also investigated the relationships between individual ANLs and the familiarity of music samples and between music ANLs and subjective preference. Forty-one participants were seperated into two groups according to their ANLs, 29 low-ANL listeners and 12 high-ANL listeners. Using Korean ANL material, the individual ANLs were measured based on the listeners' most comfortable listening level and BNL. The ANLs were measured in six conditions, with different music tempo (fast, slow) and genre (K-pop, pop, classical) in a counterbalanced order. Overall, ANLs did not differ by the tempo of background music, but music genre significantly affected individual ANLs. We observed relatively higher ANLs with K-pop music and relatively lower ANLs with classical music. This tendency was similar in both low-ANL and high-ANL groups. However, the subjective ratings of music familiarity and preference affected ANLs differently for low-ANL and high-ANL groups. In contrast to the low-ANL listeners, the ANLs of the high-ANL listeners were significantly affected by music familiarity and preference. The genre of background music affected ANLs obtained using background music. The degree of music familiarity and preference appears to be associated with individual susceptibility to background music only for listeners who are greatly annoyed by background noise (high-ANL listeners).
Directory of Open Access Journals (Sweden)
Edward Pace
Full Text Available Tinnitus has a complex etiology that involves auditory and non-auditory factors and may be accompanied by hyperacusis, anxiety and cognitive changes. Thus far, investigations of the interrelationship between tinnitus and auditory and non-auditory impairment have yielded conflicting results. To further address this issue, we noise exposed rats and assessed them for tinnitus using a gap detection behavioral paradigm combined with statistically-driven analysis to diagnose tinnitus in individual rats. We also tested rats for hearing detection, responsivity, and loss using prepulse inhibition and auditory brainstem response, and for spatial cognition and anxiety using Morris water maze and elevated plus maze. We found that our tinnitus diagnosis method reliably separated noise-exposed rats into tinnitus((+ and tinnitus((- groups and detected no evidence of tinnitus in tinnitus((- and control rats. In addition, the tinnitus((+ group demonstrated enhanced startle amplitude, indicating hyperacusis-like behavior. Despite these results, neither tinnitus, hyperacusis nor hearing loss yielded any significant effects on spatial learning and memory or anxiety, though a majority of rats with the highest anxiety levels had tinnitus. These findings showed that we were able to develop a clinically relevant tinnitus((+ group and that our diagnosis method is sound. At the same time, like clinical studies, we found that tinnitus does not always result in cognitive-emotional dysfunction, although tinnitus may predispose subjects to certain impairment like anxiety. Other behavioral assessments may be needed to further define the relationship between tinnitus and anxiety, cognitive deficits, and other impairments.
Pace, Edward; Zhang, Jinsheng
2013-01-01
Tinnitus has a complex etiology that involves auditory and non-auditory factors and may be accompanied by hyperacusis, anxiety and cognitive changes. Thus far, investigations of the interrelationship between tinnitus and auditory and non-auditory impairment have yielded conflicting results. To further address this issue, we noise exposed rats and assessed them for tinnitus using a gap detection behavioral paradigm combined with statistically-driven analysis to diagnose tinnitus in individual rats. We also tested rats for hearing detection, responsivity, and loss using prepulse inhibition and auditory brainstem response, and for spatial cognition and anxiety using Morris water maze and elevated plus maze. We found that our tinnitus diagnosis method reliably separated noise-exposed rats into tinnitus(+) and tinnitus(−) groups and detected no evidence of tinnitus in tinnitus(−) and control rats. In addition, the tinnitus(+) group demonstrated enhanced startle amplitude, indicating hyperacusis-like behavior. Despite these results, neither tinnitus, hyperacusis nor hearing loss yielded any significant effects on spatial learning and memory or anxiety, though a majority of rats with the highest anxiety levels had tinnitus. These findings showed that we were able to develop a clinically relevant tinnitus(+) group and that our diagnosis method is sound. At the same time, like clinical studies, we found that tinnitus does not always result in cognitive-emotional dysfunction, although tinnitus may predispose subjects to certain impairment like anxiety. Other behavioral assessments may be needed to further define the relationship between tinnitus and anxiety, cognitive deficits, and other impairments. PMID:24069375
Phenotypic covariance at species' borders.
Caley, M Julian; Cripps, Edward; Game, Edward T
2013-05-28
Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.
Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure.
Birk, Matthias; Ivina, Olga; von Klot, Stephanie; Babisch, Wolfgang; Heinrich, Joachim
2011-11-01
self-reported road traffic noise annoyance is commonly used in epidemiological studies for assessment of potential health effects. Alternatively, some studies have used geographic information system (GIS) modelled exposure to road traffic noise as an objective parameter. The aim of this study was to analyse the association between noise exposure due to neighbouring road traffic and the noise annoyance of adults, taking other determinants into consideration. parents of 951 Munich children from the two German birth cohorts GINIplus and LISAplus reported their annoyance due to road traffic noise at home. GIS modelled road traffic noise exposure (L(den), maximum within a 50 m buffer) from the noise map of the city of Munich was available for all families. GIS-based calculated distance to the closest major road (≥10,000 vehicles per day) and questionnaire based-information about family income, parental education and the type of the street of residence were explored for their potential influence. An ordered logit regression model was applied. The noise levels (L(den)) and the reported noise annoyance were compared with an established exposure-response function. the correlation between noise annoyance and noise exposure (L(den)) was fair (Spearman correlation r(s) = 0.37). The distance to a major road and the type of street were strong predictors for the noise annoyance. The annoyance modelled by the established exposure-response function and that estimated by the ordered logit model were moderately associated (Pearson's correlation r(p) = 0.50). road traffic noise annoyance was associated with GIS modelled neighbouring road traffic noise exposure (L(den)). The distance to a major road and the type of street were additional explanatory factors of the noise annoyance appraisal.
Patterns of physiological and affective responses to vehicle pass-by noises
Directory of Open Access Journals (Sweden)
Gert Notbohm
2013-01-01
Full Text Available Traffic noise is considered causing annoyance and severe health effects like cardiovascular disease (CVD. The present laboratory study examines the importance of individual factors, namely age, gender and personality traits on short term physiological and affective response to vehicle pass-by noises. Four groups of subjects (20-30 vs. 40-55 year-old male or female, n = 66 in total were exposed to a series of vehicle pass-by noises. Physiological responses (finger-pulse amplitude [FPA], skin conductance level [SCL] were registered during the exposure; affective responses and judgements regarding the sounds were assessed by questionnaires. Noise sensitivity and sensation seeking were measured by validated questionnaires. The results show different patterns of response depending on age, gender and personality. The strongest sympathetic stress reaction as measured by SCL was found for the older female group. In regression analysis, the SCL response was predicted by the female gender and low score of sensation seeking only (adjusted R2 = 0.139. The FPA response was strongest among the young men and age was the only significant predictor. For affective responses of pleasantness and activation, regression analysis proved noise sensitivity and sensation seeking to be significant predictors (adjusted R2 = 0.187 respectively 0.154. Age, gender and personality influence physiological and affective reactions to traffic noise, which might affect health conditions. Especially, a potential risk of older women for CVD owing to noise should be investigated further. Individual sensitiveness in terms of noise sensitivity or sensation seeking proves to be important for explaining differences in response to noise.
Quasi-local mass in the covariant Newtonian spacetime
International Nuclear Information System (INIS)
Wu, Y-H; Wang, C-H
2008-01-01
In general relativity, quasi-local energy-momentum expressions have been constructed from various formulae. However, the Newtonian theory of gravity gives a well-known and a unique quasi-local mass expression (surface integration). Since geometrical formulation of Newtonian gravity has been established in the covariant Newtonian spacetime, it provides a covariant approximation from relativistic to Newtonian theories. By using this approximation, we calculate the Komar integral, the Brown-York quasi-local energy and the Dougan-Mason quasi-local mass in the covariant Newtonian spacetime. It turns out that the Komar integral naturally gives the Newtonian quasi-local mass expression; however, further conditions (spherical symmetry) need to be made for Brown-York and Dougan-Mason expressions
Judgments of aircraft noise in a traffic noise background
Powell, C. A.; Rice, C. G.
1975-01-01
An investigation was conducted to determine subjective response to aircraft noise in different road traffic backgrounds. In addition, two laboratory techniques for presenting the aircraft noise with the background noise were evaluated. For one technique, the background noise was continuous over an entire test session; for the other, the background noise level was changed with each aircraft noise during a session. Subjective response to aircraft noise was found to decrease with increasing background noise level, for a range of typical indoor noise levels. Subjective response was found to be highly correlated with the Noise Pollution Level (NPL) measurement scale.
The Performance Analysis Based on SAR Sample Covariance Matrix
Directory of Open Access Journals (Sweden)
Esra Erten
2012-03-01
Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
Babisch, Wolfgang; Wolf, Kathrin; Petz, Markus; Heinrich, Joachim; Cyrys, Josef; Peters, Annette
2014-05-01
Studies on the association between traffic noise and cardiovascular diseases have rarely considered air pollution as a covariate in the analyses. Isolated systolic hypertension has not yet been in the focus of epidemiological noise research. The association between traffic noise (road and rail) and the prevalence of hypertension was assessed in two study populations with a total of 4,166 participants 25-74 years of age. Traffic noise (weighted day-night average noise level; LDN) at the facade of the dwellings was derived from noise maps. Annual average PM2.5 mass concentrations at residential addresses were estimated by land-use regression. Hypertension was assessed by blood pressure readings, self-reported doctor-diagnosed hypertension, and antihypertensive drug intake. In the Greater Augsburg, Germany, study population, traffic noise and air pollution were not associated with hypertension. In the City of Augsburg population (n = 1,893), where the exposure assessment was more detailed, the adjusted odds ratio (OR) for a 10-dB(A) increase in noise was 1.16 (95% CI: 1.00, 1.35), and 1.11 (95% CI: 0.94, 1.30) after additional adjustment for PM2.5. The adjusted OR for a 1-μg/m3 increase in PM2.5 was 1.15 (95% CI: 1.02, 1.30), and 1.11 (95% CI: 0.98, 1.27) after additional adjustment for noise. For isolated systolic hypertension, the fully adjusted OR for noise was 1.43 (95% CI: 1.10, 1.86) and for PM2.5 was 1.08 (95% CI: 0.87, 1.34). Traffic noise and PM2.5 were both associated with a higher prevalence of hypertension. Mutually adjusted associations with hypertension were positive but no longer statistically significant.
Papale, Dario; Fratini, Gerardo
2013-04-01
implementation in eddy-covariance processing software and will be readily applicable by individual investigators as well as by centralized processing facilities of long-term research infrastructures. This new understandings suggest that a reanalysis of eddy-covariance data collected in the last 20 years may be appropriate in order to obtain more accurate and consistent flux time series. The availability of dedicated powerful computing facilities at the research infrastructures today makes this goal achievable at an affordable cost.
ANGELO-LAMBDA, Covariance matrix interpolation and mathematical verification
International Nuclear Information System (INIS)
Kodeli, Ivo
2007-01-01
1 - Description of program or function: The codes ANGELO-2.3 and LAMBDA-2.3 are used for the interpolation of the cross section covariance data from the original to a user defined energy group structure, and for the mathematical tests of the matrices, respectively. The LAMBDA-2.3 code calculates the eigenvalues of the matrices (both for the original or the converted) and lists them accordingly into positive and negative matrices. This verification is strongly recommended before using any covariance matrices. These versions of the two codes are the extended versions of the previous codes available in the Packages NEA-1264 - ZZ-VITAMIN-J/COVA. They were specifically developed for the purposes of the OECD LWR UAM benchmark, in particular for the processing of the ZZ-SCALE5.1/COVA-44G cross section covariance matrix library retrieved from the SCALE-5.1 package. Either the original SCALE-5.1 libraries or the libraries separated into several files by Nuclides can be (in principle) processed by ANGELO/LAMBDA codes, but the use of the one-nuclide data is strongly recommended. Due to large deviations of the correlation matrix terms from unity observed in some SCALE5.1 covariance matrices, the previous more severe acceptance condition in the ANGELO2.3 code was released. In case the correlation coefficients exceed 1.0, only a warning message is issued, and coefficients are replaced by 1.0. 2 - Methods: ANGELO-2.3 interpolates the covariance matrices to a union grid using flat weighting. LAMBDA-2.3 code includes the mathematical routines to calculate the eigenvalues of the covariance matrices. 3 - Restrictions on the complexity of the problem: The algorithm used in ANGELO is relatively simple, therefore the interpolations involving energy group structure which are very different from the original (e.g. large difference in the number of energy groups) may not be accurate. In particular in the case of the MT=1018 data (fission spectra covariances) the algorithm may not be
Listening to white noise counteracts visual and haptic pseudoneglect.
Cattaneo, Zaira; Lega, Carlotta; Vecchi, Tomaso; Vallar, Giuseppe
2012-01-01
Neurologically intact individuals usually show a leftward bias in line bisection, a tendency known as "pseudoneglect", likely reflecting a right-hemisphere dominance in controlling the allocation of spatial attention. Studies in brain-damaged patients with left visuospatial neglect have reported that auditory stimulation may reduce the deficit, both in a spatially dependent and in a spatially independent way. Here we show for the first time that the concurrent binaural presentation of auditory white noise affects healthy individuals' performance in both visual and haptic bisection, reducing their leftward error. We suggest that this effect depends on the noise boosting alertness and restoring the hemispheric activation balance. Our data clearly show that task-irrelevant auditory noise crossmodally affects the allocation of spatial resources in both the haptic and the visual space; future research may clarify whether these effects are specific for the type of auditory stimulation.
Individual differneces in degraded speech perception
Carbonell, Kathy M.
One of the lasting concerns in audiology is the unexplained individual differences in speech perception performance even for individuals with similar audiograms. One proposal is that there are cognitive/perceptual individual differences underlying this vulnerability and that these differences are present in normal hearing (NH) individuals but do not reveal themselves in studies that use clear speech produced in quiet (because of a ceiling effect). However, previous studies have failed to uncover cognitive/perceptual variables that explain much of the variance in NH performance on more challenging degraded speech tasks. This lack of strong correlations may be due to either examining the wrong measures (e.g., working memory capacity) or to there being no reliable differences in degraded speech performance in NH listeners (i.e., variability in performance is due to measurement noise). The proposed project has 3 aims; the first, is to establish whether there are reliable individual differences in degraded speech performance for NH listeners that are sustained both across degradation types (speech in noise, compressed speech, noise-vocoded speech) and across multiple testing sessions. The second aim is to establish whether there are reliable differences in NH listeners' ability to adapt their phonetic categories based on short-term statistics both across tasks and across sessions; and finally, to determine whether performance on degraded speech perception tasks are correlated with performance on phonetic adaptability tasks, thus establishing a possible explanatory variable for individual differences in speech perception for NH and hearing impaired listeners.
The effects of background white noise on memory performance in inattentive school children
S?derlund, G?ran BW; Sikstr?m, Sverker; Loftesnes, Jan M; Sonuga-Barke, Edmund J
2010-01-01
Abstract Background Noise is typically conceived of as being detrimental for cognitive performance; however, a recent computational model based on the concepts of stochastic resonance and dopamine related internal noise postulates that a moderate amount of auditive noise benefit individuals in hypodopaminergic states. On the basis of this model we predicted that inattentive children would be enhanced by adding background white noise while attentive children's performance would deteriorate. Me...
Covariance and correlation estimation in electron-density maps.
Altomare, Angela; Cuocci, Corrado; Giacovazzo, Carmelo; Moliterni, Anna; Rizzi, Rosanna
2012-03-01
Quite recently two papers have been published [Giacovazzo & Mazzone (2011). Acta Cryst. A67, 210-218; Giacovazzo et al. (2011). Acta Cryst. A67, 368-382] which calculate the variance in any point of an electron-density map at any stage of the phasing process. The main aim of the papers was to associate a standard deviation to each pixel of the map, in order to obtain a better estimate of the map reliability. This paper deals with the covariance estimate between points of an electron-density map in any space group, centrosymmetric or non-centrosymmetric, no matter the correlation between the model and target structures. The aim is as follows: to verify if the electron density in one point of the map is amplified or depressed as an effect of the electron density in one or more other points of the map. High values of the covariances are usually connected with undesired features of the map. The phases are the primitive random variables of our probabilistic model; the covariance changes with the quality of the model and therefore with the quality of the phases. The conclusive formulas show that the covariance is also influenced by the Patterson map. Uncertainty on measurements may influence the covariance, particularly in the final stages of the structure refinement; a general formula is obtained taking into account both phase and measurement uncertainty, valid at any stage of the crystal structure solution.
Erickson, Jonathan C; Putney, Joy; Hilbert, Douglas; Paskaranandavadivel, Niranchan; Cheng, Leo K; O'Grady, Greg; Angeli, Timothy R
2016-11-01
The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation. A novel iterative Covariance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance. Application of COBRA substantially increased the signal-to-artifact ratio (12.8 ± 2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average ( -11.1 ± 3.9 dB). COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90 ± 0.04; positive-predictive value = 0.74 ± 0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms. Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains.
Moderating the Covariance Between Family Member’s Substance Use Behavior
Eaves, Lindon J.; Neale, Michael C.
2014-01-01
Twin and family studies implicitly assume that the covariation between family members remains constant across differences in age between the members of the family. However, age-specificity in gene expression for shared environmental factors could generate higher correlations between family members who are more similar in age. Cohort effects (cohort × genotype or cohort × common environment) could have the same effects, and both potentially reduce effect sizes estimated in genome-wide association studies where the subjects are heterogeneous in age. In this paper we describe a model in which the covariance between twins and non-twin siblings is moderated as a function of age difference. We describe the details of the model and simulate data using a variety of different parameter values to demonstrate that model fitting returns unbiased parameter estimates. Power analyses are then conducted to estimate the sample sizes required to detect the effects of moderation in a design of twins and siblings. Finally, the model is applied to data on cigarette smoking. We find that (1) the model effectively recovers the simulated parameters, (2) the power is relatively low and therefore requires large sample sizes before small to moderate effect sizes can be found reliably, and (3) the genetic covariance between siblings for smoking behavior decays very rapidly. Result 3 implies that, e.g., genome-wide studies of smoking behavior that use individuals assessed at different ages, or belonging to different birth-year cohorts may have had substantially reduced power to detect effects of genotype on cigarette use. It also implies that significant special twin environmental effects can be explained by age-moderation in some cases. This effect likely contributes to the missing heritability paradox. PMID:24647834
Effect of correlation on covariate selection in linear and nonlinear mixed effect models.
Bonate, Peter L
2017-01-01
The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Superlinearly scalable noise robustness of redundant coupled dynamical systems.
Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L
2016-03-01
We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.
Extended covariance data formats for the ENDF/B-VI differential data evaluation
International Nuclear Information System (INIS)
Peelle, R.W.; Muir, D.W.
1988-01-01
The ENDF/B-V included cross section covariance data, but covariances could not be encoded for all the important data types. New ENDF-6 covariance formats are outlined including those for cross-file (MF) covariances, resonance parameters over the whole range, and secondary energy and angle distributions. One ''late entry'' format encodes covariance data for cross sections that are output from model or fitting codes in terms of the model parameter covariance matrix and the tabulated derivatives of cross sections with respect to the model parameters. Another new format yields multigroup cross section variances that increase as the group width decreases. When evaluators use the new formats, the files can be processed and used for improved uncertainty propagation and data combination. 22 refs
Di, Xin; Gohel, Suril; Thielcke, Andre; Wehrl, Hans F; Biswal, Bharat B
2017-11-01
Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.
The dose-response relationship between in-ear occupational noise exposure and hearing loss.
Rabinowitz, Peter M; Galusha, Deron; Dixon-Ernst, Christine; Clougherty, Jane E; Neitzel, Richard L
2013-10-01
Current understanding of the dose-response relationship between occupational noise and hearing loss is based on cross-sectional studies prior to the widespread use of hearing protection, and with limited data regarding noise exposures below 85 dBA. We report on the hearing loss experience of a unique cohort of industrial workers, with daily monitoring of noise inside of hearing protection devices. At an industrial facility, workers exhibiting accelerated hearing loss were enrolled in a mandatory programme to monitor daily noise exposures inside of hearing protection. We compared these noise measurements (as time-weighted LAVG) to interval rates of high-frequency hearing loss over a 6-year period using a mixed-effects model, adjusting for potential confounders. Workers' high-frequency hearing levels at study inception averaged more than 40 dB Hearing threshold level (HTL). Most noise exposures were less than 85 dBA (mean LAVG 76 dBA, IQR 74-80 dBA). We found no statistical relationship between LAvg and high-frequency hearing loss (p=0.53). Using a metric for monthly maximum noise exposure did not improve model fit. At-ear noise exposures below 85 dBA did not show an association with risk of high-frequency hearing loss among workers with substantial past noise exposure and hearing loss at baseline. Therefore, effective noise control to below 85 dBA may lead to significant reduction in occupational hearing loss risk in such individuals. Further research is needed on the dose-response relationship of noise and hearing loss in individuals with normal hearing and little prior noise exposure.
Cai, Yutong; Hodgson, Susan; Blangiardo, Marta; Gulliver, John; Morley, David; Fecht, Daniela; Vienneau, Danielle; de Hoogh, Kees; Key, Tim; Hveem, Kristian; Elliott, Paul; Hansell, Anna L
2018-05-01
This study aimed to investigate the effects of long-term exposure to road traffic noise and air pollution on incident cardiovascular disease (CVD) in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. In pooled complete-case sample of the three cohorts from Norway and the United Kingdom (N = 355,732), 21,081 incident all CVD cases including 5259 ischemic heart disease (IHD) and 2871 cerebrovascular cases were ascertained between baseline (1993-2010) and end of follow-up (2008-2013) through medical record linkage. Annual mean 24-hour weighted road traffic noise (Lden) and air pollution (particulate matter with aerodynamic diameter ≤ 10 μm [PM10], ≤2.5 μm [PM2.5] and nitrogen dioxide [NO2]) exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU) and European-wide Land Use Regression models. Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustments for both noise and air pollution and potential confounders. No significant associations were found between annual mean Lden and incident CVD, IHD or cerebrovascular disease in the overall population except that the association with incident IHD was significant among current-smokers. In the fully adjusted models including adjustment for Lden, an interquartile range (IQR) higher PM10 (4.1 μg/m3) or PM2.5 (1.4 μg/m3) was associated with a 5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higher risk for all incident CVD respectively. No significant associations were found between NO2 and any of the CVD outcomes. We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, was significantly associated with incident CVD. Copyright
Covariance specification and estimation to improve top-down Green House Gas emission estimates
Ghosh, S.; Lopez-Coto, I.; Prasad, K.; Whetstone, J. R.
2015-12-01
The National Institute of Standards and Technology (NIST) operates the North-East Corridor (NEC) project and the Indianapolis Flux Experiment (INFLUX) in order to develop measurement methods to quantify sources of Greenhouse Gas (GHG) emissions as well as their uncertainties in urban domains using a top down inversion method. Top down inversion updates prior knowledge using observations in a Bayesian way. One primary consideration in a Bayesian inversion framework is the covariance structure of (1) the emission prior residuals and (2) the observation residuals (i.e. the difference between observations and model predicted observations). These covariance matrices are respectively referred to as the prior covariance matrix and the model-data mismatch covariance matrix. It is known that the choice of these covariances can have large effect on estimates. The main objective of this work is to determine the impact of different covariance models on inversion estimates and their associated uncertainties in urban domains. We use a pseudo-data Bayesian inversion framework using footprints (i.e. sensitivities of tower measurements of GHGs to surface emissions) and emission priors (based on Hestia project to quantify fossil-fuel emissions) to estimate posterior emissions using different covariance schemes. The posterior emission estimates and uncertainties are compared to the hypothetical truth. We find that, if we correctly specify spatial variability and spatio-temporal variability in prior and model-data mismatch covariances respectively, then we can compute more accurate posterior estimates. We discuss few covariance models to introduce space-time interacting mismatches along with estimation of the involved parameters. We then compare several candidate prior spatial covariance models from the Matern covariance class and estimate their parameters with specified mismatches. We find that best-fitted prior covariances are not always best in recovering the truth. To achieve
Parametric number covariance in quantum chaotic spectra.
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.
Minimum Energy Decentralized Estimation in a Wireless Sensor Network with Correlated Sensor Noises
Directory of Open Access Journals (Sweden)
Krasnopeev Alexey
2005-01-01
Full Text Available Consider the problem of estimating an unknown parameter by a sensor network with a fusion center (FC. Sensor observations are corrupted by additive noises with an arbitrary spatial correlation. Due to bandwidth and energy limitation, each sensor is only able to transmit a finite number of bits to the FC, while the latter must combine the received bits to estimate the unknown parameter. We require the decentralized estimator to have a mean-squared error ( that is within a constant factor to that of the best linear unbiased estimator (BLUE. We minimize the total sensor transmitted energy by selecting sensor quantization levels using the knowledge of noise covariance matrix while meeting the target requirement. Computer simulations show that our designs can achieve energy savings up to when compared to the uniform quantization strategy whereby each sensor generates the same number of bits, irrespective of the quality of its observation and the condition of its channel to the FC.
Minimum Energy Decentralized Estimation in a Wireless Sensor Network with Correlated Sensor Noises
Directory of Open Access Journals (Sweden)
Krasnopeev Alexey
2005-01-01
Full Text Available Consider the problem of estimating an unknown parameter by a sensor network with a fusion center (FC. Sensor observations are corrupted by additive noises with an arbitrary spatial correlation. Due to bandwidth and energy limitation, each sensor is only able to transmit a finite number of bits to the FC, while the latter must combine the received bits to estimate the unknown parameter. We require the decentralized estimator to have a mean-squared error (MSE that is within a constant factor to that of the best linear unbiased estimator (BLUE. We minimize the total sensor transmitted energy by selecting sensor quantization levels using the knowledge of noise covariance matrix while meeting the target MSE requirement. Computer simulations show that our designs can achieve energy savings up to 70 % when compared to the uniform quantization strategy whereby each sensor generates the same number of bits, irrespective of the quality of its observation and the condition of its channel to the FC.
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides an efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit two- and three-loop results derived using analytic geometry (one loop is known to be okay). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various nontrivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides and efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit 2- and 3- loop results derived using analytic geometry (1 loop is known to be ok). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various non-trivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
A covariant canonical description of Liouville field theory
International Nuclear Information System (INIS)
Papadopoulos, G.; Spence, B.
1993-03-01
This paper presents a new parametrisation of the space of solutions of Liouville field theory on a cylinder. In this parametrisation, the solutions are well-defined and manifestly real functions over all space-time and all of parameter space. It is shown that the resulting covariant phase space of the Liouville theory is diffeomorphic to the Hamiltonian one, and to the space of initial data of the theory. The Poisson brackets are derived and shown to be those of the co-tangent bundle of the loop group of the real line. Using Hamiltonian reduction, it is shown that this covariant phase space formulation of Liouville theory may also be obtained from the covariant phase space formulation of the Wess-Zumino-Witten model. 19 refs
Begault, Durand R.
2018-01-01
This document reviews non-auditory effects of noise relevant to habitable volume requirements in cislunar space. The non-auditory effects of noise in future long-term space habitats are likely to be impactful on team and individual performance, sleep, and cognitive well-being. This report has provided several recommendations for future standards and procedures for long-term space flight habitats, along with recommendations for NASA's Human Research Program in support of DST mission success.
Individual-based versus aggregate meta-analysis in multi-database studies of pregnancy outcomes
DEFF Research Database (Denmark)
Selmer, Randi; Haglund, Bengt; Furu, Kari
2016-01-01
Purpose: Compare analyses of a pooled data set on the individual level with aggregate meta-analysis in a multi-database study. Methods: We reanalysed data on 2.3 million births in a Nordic register based cohort study. We compared estimated odds ratios (OR) for the effect of selective serotonin...... covariates in the pooled data set, and 1.53 (1.19–1.96) after country-optimized adjustment. Country-specific adjusted analyses at the substance level were not possible for RVOTO. Conclusion: Results of fixed effects meta-analysis and individual-based analyses of a pooled dataset were similar in this study...... reuptake inhibitors (SSRI) and venlafaxine use in pregnancy on any cardiovascular birth defect and the rare outcome right ventricular outflow tract obstructions (RVOTO). Common covariates included maternal age, calendar year, birth order, maternal diabetes, and co-medication. Additional covariates were...
Abnormalities in structural covariance of cortical gyrification in schizophrenia.
Palaniyappan, Lena; Park, Bert; Balain, Vijender; Dangi, Raj; Liddle, Peter
2015-07-01
The highly convoluted shape of the adult human brain results from several well-coordinated maturational events that start from embryonic development and extend through the adult life span. Disturbances in these maturational events can result in various neurological and psychiatric disorders, resulting in abnormal patterns of morphological relationship among cortical structures (structural covariance). Structural covariance can be studied using graph theory-based approaches that evaluate topological properties of brain networks. Covariance-based graph metrics allow cross-sectional study of coordinated maturational relationship among brain regions. Disrupted gyrification of focal brain regions is a consistent feature of schizophrenia. However, it is unclear if these localized disturbances result from a failure of coordinated development of brain regions in schizophrenia. We studied the structural covariance of gyrification in a sample of 41 patients with schizophrenia and 40 healthy controls by constructing gyrification-based networks using a 3-dimensional index. We found that several key regions including anterior insula and dorsolateral prefrontal cortex show increased segregation in schizophrenia, alongside reduced segregation in somato-sensory and occipital regions. Patients also showed a lack of prominence of the distributed covariance (hubness) of cingulate cortex. The abnormal segregated folding pattern in the right peri-sylvian regions (insula and fronto-temporal cortex) was associated with greater severity of illness. The study of structural covariance in cortical folding supports the presence of subtle deviation in the coordinated development of cortical convolutions in schizophrenia. The heterogeneity in the severity of schizophrenia could be explained in part by aberrant trajectories of neurodevelopment.
An Empirical State Error Covariance Matrix Orbit Determination Example
Frisbee, Joseph H., Jr.
2015-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Effects of noise and audiovisual cues on speech processing in adults with and without ADHD.
Michalek, Anne M P; Watson, Silvana M; Ash, Ivan; Ringleb, Stacie; Raymer, Anastasia
2014-03-01
This study examined the interplay among internal (e.g. attention, working memory abilities) and external (e.g. background noise, visual information) factors in individuals with and without ADHD. A 2 × 2 × 6 mixed design with correlational analyses was used to compare participant results on a standardized listening in noise sentence repetition task (QuickSin; Killion et al, 2004 ), presented in an auditory and an audiovisual condition as signal-to-noise ratio (SNR) varied from 25-0 dB and to determine individual differences in working memory capacity and short-term recall. Thirty-eight young adults without ADHD and twenty-five young adults with ADHD. Diagnosis, modality, and signal-to-noise ratio all affected the ability to process speech in noise. The interaction between the diagnosis of ADHD, the presence of visual cues, and the level of noise had an effect on a person's ability to process speech in noise. conclusion: Young adults with ADHD benefited less from visual information during noise than young adults without ADHD, an effect influenced by working memory abilities.
Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Liang, Yuli
2015-01-01
This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data....
Sparse reduced-rank regression with covariance estimation
Chen, Lisha
2014-12-08
Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
The covariant formulation of f ( T ) gravity
International Nuclear Information System (INIS)
Krššák, Martin; Saridakis, Emmanuel N
2016-01-01
We show that the well-known problem of frame dependence and violation of local Lorentz invariance in the usual formulation of f ( T ) gravity is a consequence of neglecting the role of spin connection. We re-formulate f ( T ) gravity starting from, instead of the ‘pure tetrad’ teleparallel gravity, the covariant teleparallel gravity, using both the tetrad and the spin connection as dynamical variables, resulting in a fully covariant, consistent, and frame-independent version of f ( T ) gravity, which does not suffer from the notorious problems of the usual, pure tetrad, f ( T ) theory. We present the method to extract solutions for the most physically important cases, such as the Minkowski, the Friedmann–Robertson–Walker (FRW) and the spherically symmetric ones. We show that in covariant f ( T ) gravity we are allowed to use an arbitrary tetrad in an arbitrary coordinate system along with the corresponding spin connection, resulting always in the same physically relevant field equations. (paper)
Sparse reduced-rank regression with covariance estimation
Chen, Lisha; Huang, Jianhua Z.
2014-01-01
Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
Directory of Open Access Journals (Sweden)
Qiang Luo
2013-10-01
Full Text Available We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention.
Recent Advances with the AMPX Covariance Processing Capabilities in PUFF-IV
International Nuclear Information System (INIS)
Wiarda, Dorothea; Arbanas, Goran; Leal, Luiz C.; Dunn, Michael E.
2008-01-01
The program PUFF-IV is used to process resonance parameter covariance information given in ENDF/B File 32 and point-wise covariance matrices given in ENDF/B File 33 into group-averaged covariances matrices on a user-supplied group structure. For large resonance covariance matrices, found for example in 235U, the execution time of PUFF-IV can be quite long. Recently the code was modified to take advandage of Basic Linear Algebra Subprograms (BLAS) routines for the most time-consuming matrix multiplications. This led to a substantial decrease in execution time. This faster processing capability allowed us to investigate the conversion of File 32 data into File 33 data using a larger number of user-defined groups. While conversion substantially reduces the ENDF/B file size requirements for evaluations with a large number of resonances, a trade-off is made between the number of groups used to represent the resonance parameter covariance as a point-wise covariance matrix and the file size. We are also investigating a hybrid version of the conversion, in which the low-energy part of the File 32 resonance parameter covariances matrix is retained and the correlations with higher energies as well as the high energy part are given in File 33.
Eddy covariance methane measurements at a Ponderosa pine plantation in California
Directory of Open Access Journals (Sweden)
T. Röckmann
2009-11-01
Full Text Available Long term methane flux measurements have been mostly performed with plant or soil enclosure techniques on specific components of an ecosystem. New fast response methane analyzers make it possible to use the eddy covariance (EC technique instead. The EC technique is advantageous because it allows continuous flux measurements integrating over a larger and more representative area including the complete ecosystem, and allows fluxes to be observed as environmental conditions change naturally without disturbance. We deployed the closed-path Fast Methane analyzer (FMA from Los Gatos Research Ltd and demonstrate its performance for EC measurements at a Ponderosa pine plantation at the Blodgett Forest site in central California. The fluctuations of the CH_{4} concentration measured at 10 Hz appear to be small and their standard deviation is comparable to the magnitude of the signal noise (±5 ppbv. Consequently, the power spectra typically have a white noise signature at the high frequency end (a slope of +1. Nevertheless, in the frequency range important for turbulent exchange, the cospectra of CH_{4} compare very well with all other scalar cospectra confirming the quality of the FMA measurements are good for the EC technique. We furthermore evaluate the complications of combined open and closed-path measurements when applying the Webb-Pearman-Leuning (WPL corrections (Webb et al., 1980 and the consequences of a phase lag between the water vapor and methane signal inside the closed path system. The results of diurnal variations of CH_{4} concentrations and fluxes are summarized and compared to the monthly results of process-based model calculations.
Van der Gugten, J; Slangen, J L; de Boer, S.F.
1989-01-01
Plasma noradrenaline (NA), adrenaline (A) and corticosterone (CS) increases were determined in individual rats subjected to either 20 regularly or irregularly scheduled white-noise stimulations (4 min, 100 dBA). Blood was frequently sampled during the first and twentieth noise exposure, and during a reexposure after 24 hr. During the sampling periods, behavioral activities of the rats were recorded. The initial noise-induced CS release was partially reduced following the regular noise present...
Conversed, gauge-covariant colour charge in Su(n)QCD
International Nuclear Information System (INIS)
Selikhov, A.V.
1988-01-01
The definition of the integral of the group tensor and the gauge-covariant differential with respect to a distant point are given in the work. A conserved covariant charge dependence on family of paths has been contracted with the help of these notions. It has been shown that the same family of paths fixes a gauge in which the covariant and noncovariant conserved currents coicide. The gauge is characterized by representation of the vector potential via field strength tensor. The possibility of connecting the choice of the family of paths with the measurement procedure is discussed. 13 refs.; 2 figs
Semiparametric estimation of covariance matrices for longitudinal data.
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.
Altered Cerebral Blood Flow Covariance Network in Schizophrenia.
Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui
2016-01-01
Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia.
Covariant Gauss law commutator anomaly
International Nuclear Information System (INIS)
Dunne, G.V.; Trugenberger, C.A.; Massachusetts Inst. of Tech., Cambridge
1990-01-01
Using a (fixed-time) hamiltonian formalism we derive a covariant form for the anomaly in the commutator algebra of Gauss law generators for chiral fermions interacting with a dynamical non-abelian gauge field in 3+1 dimensions. (orig.)
Directory of Open Access Journals (Sweden)
Mohsin Ahmed Shaikh
2017-02-01
Full Text Available This study aimed to investigate differences between ears in performance on a monaural word recognition in noise test among individuals across a broad range of ages assessed for (CAPD. Word recognition scores in quiet and in speech noise were collected retrospectively from the medical files of 107 individuals between the ages of 7 and 30 years who were diagnosed with (CAPD. No ear advantage was found on the word recognition in noise task in groups less than ten years. Performance in both ears was equally poor. Right ear performance improved across age groups, with scores of individuals above age 10 years falling within the normal range. In contrast, left ear performance remained essentially stable and in the impaired range across all age groups. Findings indicate poor left hemispheric dominance for speech perception in noise in children below the age of 10 years with (CAPD. However, a right ear advantage on this monaural speech in noise task was observed for individuals 10 years and older.